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Dwinell, M. R., E. A. Worthey, M. Shimoyama, B. Bakir-Gungor, J. DePons, S. Laulederkind, T. Lowry, et al. "The Rat Genome Database 2009: variation, ontologies and pathways." Nucleic Acids Research 37, Database (January 1, 2009): D744—D749. http://dx.doi.org/10.1093/nar/gkn842.
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Legaz-García, María del Carmen, José Antonio Miñarro-Giménez, Marisa Madrid, Marcos Menárguez-Tortosa, Santiago Torres Martínez, and Jesualdo Tomás Fernández-Breis. "Linking Genome Annotation Projects with Genetic Disorders using Ontologies." Journal of Medical Systems 36, S1 (November 2012): 11–23. http://dx.doi.org/10.1007/s10916-012-9890-7.
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Ringwald, Martin, Joel E. Richardson, Richard M. Baldarelli, Judith A. Blake, James A. Kadin, Cynthia Smith, and Carol J. Bult. "Mouse Genome Informatics (MGI): latest news from MGD and GXD." Mammalian Genome 33, no. 1 (October 26, 2021): 4–18. http://dx.doi.org/10.1007/s00335-021-09921-0.
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AbstractThe Mouse Genome Informatics (MGI) database system combines multiple expertly curated community data resources into a shared knowledge management ecosystem united by common metadata annotation standards. MGI’s mission is to facilitate the use of the mouse as an experimental model for understanding the genetic and genomic basis of human health and disease. MGI is the authoritative source for mouse gene, allele, and strain nomenclature and is the primary source of mouse phenotype annotations, functional annotations, developmental gene expression information, and annotations of mouse models with human diseases. MGI maintains mouse anatomy and phenotype ontologies and contributes to the development of the Gene Ontology and Disease Ontology and uses these ontologies as standard terminologies for annotation. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are MGI’s two major knowledgebases. Here, we highlight some of the recent changes and enhancements to MGD and GXD that have been implemented in response to changing needs of the biomedical research community and to improve the efficiency of expert curation. MGI can be accessed freely at http://www.informatics.jax.org.
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Wong, Hector R., Thomas P. Shanley, Bhuvaneswari Sakthivel, Natalie Cvijanovich, Richard Lin, Geoffrey L. Allen, Neal J. Thomas, et al. "Genome-level expression profiles in pediatric septic shock indicate a role for altered zinc homeostasis in poor outcome." Physiological Genomics 30, no. 2 (July 2007): 146–55. http://dx.doi.org/10.1152/physiolgenomics.00024.2007.
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Human septic shock involves multiple genome-level perturbations. We have conducted microarray analyses in children with septic shock within 24 h of intensive care unit admission, using whole blood-derived RNA. Based on sequential statistical and expression filters, there were 2,482 differentially regulated gene probes (1,081 upregulated and 1,401 downregulated) between patients with septic shock ( n = 42) and controls ( n = 15). Both gene lists encompassed several biologically relevant gene ontologies and canonical pathways. Notably, many of the genes downregulated in the patients with septic shock, relative to the controls, participate in gene ontologies related to metal or zinc homeostasis. Comparison of septic shock survivors ( n = 33) and nonsurvivors ( n = 9) demonstrated differential regulation of 63 gene probes. Among the 63 gene probes differentially regulated between septic shock survivors and nonsurvivors, two isoforms of metallothionein (MT) demonstrated increased expression in the nonsurvivors. Consistent with the ability of MT to sequester zinc in the intracellular compartment, nonsurvivors had lower serum zinc levels compared with survivors. In a corroborating study of murine sepsis, MT-null mice demonstrated a survival advantage compared with wild-type mice. These data represent the largest reported cohort of pediatric patients with septic shock that has undergone genome-level expression profiling based on microarray. The data are biologically plausible and demonstrate that genome-level alterations of zinc homeostasis may be prevalent in clinical pediatric septic shock.
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Shimoyama, Mary, Victoria Petri, Dean Pasko, Susan Bromberg, Wenhua Wu, Jiali Chen, Nataliya Nenasheva, Anne Kwitek, Simon Twigger, and Howard Jacob. "Using Multiple Ontologies to Integrate Complex Biological Data." Comparative and Functional Genomics 6, no. 7-8 (2005): 373–78. http://dx.doi.org/10.1002/cfg.498.
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The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has developed a comprehensive ontology-based data structure and annotation system to integrate physiological data along with environmental and experimental factors, as well as genetic and genomic information. RGD uses multiple ontologies to integrate complex biological information from the molecular level to the whole organism, and to develop data mining and presentation tools. This approach allows RGD to indicate not only the phenotypes seen in a strain but also the specific values under each diet and atmospheric condition, as well as gender differences. Harnessing the power of ontologies in this way allows the user to gather and filter data in a customized fashion, so that a researcher can retrieve all phenotype readings for which a high hypoxia is a factor. Utilizing the same data structure for expression data, pathways and biological processes, RGD will provide a comprehensive research platform which allows users to investigate the conditions under which biological processes are altered and to elucidate the mechanisms of disease.
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Jaiswal, Pankaj, Doreen Ware, Junjian Ni, Kuan Chang, Wei Zhao, Steven Schmidt, Xiaokang Pan, et al. "Gramene: Development and Integration of Trait and Gene Ontologies for Rice." Comparative and Functional Genomics 3, no. 2 (2002): 132–36. http://dx.doi.org/10.1002/cfg.156.
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Gramene (http://www.gramene.org/) is a comparative genome database for cereal crops and a community resource for rice. We are populating and curating Gramene with annotated rice (Oryza sativa) genomic sequence data and associated biological information including molecular markers, mutants, phenotypes, polymorphisms and Quantitative Trait Loci (QTL). In order to support queries across various data sets as well as across external databases, Gramene will employ three related controlled vocabularies. The specific goal of Gramene is, first to provide a Trait Ontology (TO) that can be used across the cereal crops to facilitate phenotypic comparisons both within and between the genera. Second, a vocabulary for plant anatomy terms, the Plant Ontology (PO) will facilitate the curation of morphological and anatomical feature information with respect to expression, localization of genes and gene products and the affected plant parts in a phenotype. The TO and PO are both in the early stages of development in collaboration with the International Rice Research Institute, TAIR and MaizeDB as part of the Plant Ontology Consortium. Finally, as part of another consortium comprising macromolecular databases from other model organisms, the Gene Ontology Consortium, we are annotating the confirmed and predicted protein entries from rice using both electronic and manual curation.
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Lan, Ning, Gaetano T. Montelione, and Mark Gerstein. "Ontologies for proteomics: towards a systematic definition of structure and function that scales to the genome level." Current Opinion in Chemical Biology 7, no. 1 (February 2003): 44–54. http://dx.doi.org/10.1016/s1367-5931(02)00020-0.
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Tian, Dongmei, Pei Wang, Bixia Tang, Xufei Teng, Cuiping Li, Xiaonan Liu, Dong Zou, Shuhui Song, and Zhang Zhang. "GWAS Atlas: a curated resource of genome-wide variant-trait associations in plants and animals." Nucleic Acids Research 48, no. D1 (September 30, 2019): D927—D932. http://dx.doi.org/10.1093/nar/gkz828.
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Abstract GWAS Atlas (https://bigd.big.ac.cn/gwas/) is a manually curated resource of genome-wide variant-trait associations for a wide range of species. Unlike existing related resources, it features comprehensive integration of a high-quality collection of 75 467 variant-trait associations for 614 traits across 7 cultivated plants (cotton, Japanese apricot, maize, rapeseed, rice, sorghum and soybean) and two domesticated animals (goat and pig), which were manually curated from 254 publications. We integrated these associations into GWAS Atlas and presented them in terms of variants, genes, traits, studies and publications. More importantly, all associations and traits were annotated and organized based on a suite of ontologies (Plant Trait Ontology, Animal Trait Ontology for Livestock, etc.). Taken together, GWAS Atlas integrates high-quality curated GWAS associations for animals and plants and provides user-friendly web interfaces for data browsing and downloading, accordingly serving as a valuable resource for genetic research of important traits and breeding application.
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Schoof, Heiko. "Towards Interoperability in Genome Databases: The MAtDB (MIPSArabidopsis thalianaDatabase) Experience." Comparative and Functional Genomics 4, no. 2 (2003): 255–58. http://dx.doi.org/10.1002/cfg.278.
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Increasing numbers of whole-genome sequences are available, but to interpret them fully requires more than listing all genes. Genome databases are faced with the challenges of integrating heterogenous data and enabling data mining. In comparison to a data warehousing approach, where integration is achieved through replication of all relevant data in a unified schema, distributed approaches provide greater flexibility and maintainability. These are important in a field where new data is generated rapidly and our understanding of the data changes. Interoperability between distributed data sources allows data maintenance to be separated from integration and analysis. Simple ways to access the data can facilitate the development of new data mining tools and the transition from model genome analysis to comparative genomics. With the MIPSArabidopsis thalianagenome database (MAtDB, http://mips.gsf.de/proj/thal/db) our aim is to go beyond a data repository towards creating an integrated knowledge resource. To this end, theArabidopsisgenome has been a backbone against which to structure and integrate heterogenous data. The challenges to be met are continuous updating of data, the design of flexible data models that can evolve with new data, the integration of heterogenous data, e.g. through the use of ontologies, comprehensive views and visualization of complex information, simple interfaces for application access locally or via the Internet, and knowledge transfer across species.
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Wang, Shur-Jen, Stanley J. F. Laulederkind, G. Thomas Hayman, Victoria Petri, Jennifer R. Smith, Marek Tutaj, Rajni Nigam, Melinda R. Dwinell, and Mary Shimoyama. "Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database." Physiological Genomics 48, no. 8 (August 1, 2016): 589–600. http://dx.doi.org/10.1152/physiolgenomics.00046.2016.
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Cardiovascular diseases are complex diseases caused by a combination of genetic and environmental factors. To facilitate progress in complex disease research, the Rat Genome Database (RGD) provides the community with a disease portal where genome objects and biological data related to cardiovascular diseases are systematically organized. The purpose of this study is to present biocuration at RGD, including disease, genetic, and pathway data. The RGD curation team uses controlled vocabularies/ontologies to organize data curated from the published literature or imported from disease and pathway databases. These organized annotations are associated with genes, strains, and quantitative trait loci (QTLs), thus linking functional annotations to genome objects. Screen shots from the web pages are used to demonstrate the organization of annotations at RGD. The human cardiovascular disease genes identified by annotations were grouped according to data sources and their annotation profiles were compared by in-house tools and other enrichment tools available to the public. The analysis results show that the imported cardiovascular disease genes from ClinVar and OMIM are functionally different from the RGD manually curated genes in terms of pathway and Gene Ontology annotations. The inclusion of disease genes from other databases enriches the collection of disease genes not only in quantity but also in quality.
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Iqbal, Muhammad Asad, Mingyang Li, Jiang Lin, Guoliang Zhang, Miao Chen, Nida Fatima Moazzam, and Wei Qian. "Preliminary Study on the Sequencing of Whole Genomic Methylation and Transcriptome-Related Genes in Thyroid Carcinoma." Cancers 14, no. 5 (February 24, 2022): 1163. http://dx.doi.org/10.3390/cancers14051163.
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Thyroid carcinoma is the most prevalent endocrine cancer globally and the primary cause of cancer-related mortality. Epigenetic modifications are progressively being linked to metastasis. This study aimed to examine whole-genome DNA methylation patterns and the gene expression profiles in thyroid cancer tissue samples using a MethylationEPIC BeadChip (850K), RNA sequencing, and a targeted bisulfite sequencing assay. The results of the Illumina Infinium human methylation kit (850K) analyses identified differentially methylated CpG locations (DMPs) and differentially methylated CpG regions (DMRs) encompassing nearly the entire genome with high resolution and depth. Gene ontology and KEGG pathway analyses revealed that the genes associated with DMRs belonged to various domain-specific ontologies, including cell adhesion, molecule binding, and proliferation. The RNA-Seq study found 1627 differentially expressed genes, 1174 of which that were up-regulated and 453 of which that were down-regulated. The targeted bisulfite sequencing assay revealed that CHST2, DPP4, DUSP6, ITGA2, SLC1A5, TIAM1, TNIK, and ABTB2 methylation levels were dramatically lowered in thyroid cancer patients when compared to the controls, but GALNTL6, HTR7, SPOCD1, and GRM5 methylation levels were significantly raised. Our study revealed that the whole-genome DNA methylation patterns and gene expression profiles in thyroid cancer shed new light on the tumorigenesis of thyroid cancer.
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De Toma, Ilario, Cesar Sierra, and Mara Dierssen. "Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome." PLOS Computational Biology 17, no. 9 (September 27, 2021): e1009317. http://dx.doi.org/10.1371/journal.pcbi.1009317.
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Trisomy of human chromosome 21 (HSA21) causes Down syndrome (DS). The trisomy does not simply result in the upregulation of HSA21--encoded genes but also leads to a genome-wide transcriptomic deregulation, which may differently affect each tissue and cell type as results of epigenetic mechanisms and protein-protein interactions. We performed a meta-analysis integrating the differential expression (DE) analyses of all publicly available transcriptomic datasets, both in human and mouse, comparing trisomic and euploid transcriptomes from different sources. We integrated all these data in a “DS network”. We found that genome wide deregulation as a consequence of trisomy 21 is not arbitrary, but involves deregulation of specific molecular cascades in which both HSA21 genes and HSA21 interactors are more consistently deregulated compared to other genes. In fact, gene deregulation happens in “clusters”, so that groups from 2 to 13 genes are found consistently deregulated. Most of these events of “co-deregulation” involve genes belonging to the same GO category, and genes associated with the same disease class. The most consistent changes are enriched in interferon related categories and neutrophil activation, reinforcing the concept that DS is an inflammatory disease. Our results also suggest that the impact of the trisomy might diverge in each tissue due to the different gene set deregulation, even though the triplicated genes are the same. Our original method to integrate transcriptomic data confirmed not only the importance of known genes, such as SOD1, but also detected new ones that could be extremely useful for generating or confirming hypotheses and supporting new putative therapeutic candidates. We created “metaDEA” an R package that uses our method to integrate every kind of transcriptomic data and therefore could be used with other complex disorders, such as cancer. We also created a user-friendly web application to query Ensembl gene IDs and retrieve all the information of their differential expression across the datasets.
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Kolmykov, Semyon, Ivan Yevshin, Mikhail Kulyashov, Ruslan Sharipov, Yury Kondrakhin, Vsevolod J. Makeev, Ivan V. Kulakovskiy, Alexander Kel, and Fedor Kolpakov. "GTRD: an integrated view of transcription regulation." Nucleic Acids Research 49, no. D1 (November 24, 2020): D104—D111. http://dx.doi.org/10.1093/nar/gkaa1057.
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Abstract The Gene Transcription Regulation Database (GTRD; http://gtrd.biouml.org/) contains uniformly annotated and processed NGS data related to gene transcription regulation: ChIP-seq, ChIP-exo, DNase-seq, MNase-seq, ATAC-seq and RNA-seq. With the latest release, the database has reached a new level of data integration. All cell types (cell lines and tissues) presented in the GTRD were arranged into a dictionary and linked with different ontologies (BRENDA, Cell Ontology, Uberon, Cellosaurus and Experimental Factor Ontology) and with related experiments in specialized databases on transcription regulation (FANTOM5, ENCODE and GTEx). The updated version of the GTRD provides an integrated view of transcription regulation through a dedicated web interface with advanced browsing and search capabilities, an integrated genome browser, and table reports by cell types, transcription factors, and genes of interest.
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Williams, Lesedi M., Zhihua Qi, Ken Batai, Stanley Hooker, Nancy J. Hall, Roberto F. Machado, Alice Chen, et al. "A locus on chromosome 5 shows African ancestry–limited association with alloimmunization in sickle cell disease." Blood Advances 2, no. 24 (December 21, 2018): 3637–47. http://dx.doi.org/10.1182/bloodadvances.2018020594.
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Abstract Red blood cell (RBC) transfusion remains a critical therapeutic intervention in sickle cell disease (SCD); however, the apparent propensity of some patients to regularly develop RBC alloantibodies after transfusion presents a significant challenge to finding compatible blood for so-called alloimmunization responders. Predisposing genetic loci have long been thought to contribute to the responder phenomenon, but to date, no definitive loci have been identified. We undertook a genome-wide association study of alloimmunization responder status in 267 SCD multiple transfusion recipients, using genetic estimates of ancestral admixture to bolster our findings. Analyses revealed single nucleotide polymorphisms (SNPs) on chromosomes 2 and 5 approaching genome-wide significance (minimum P = 2.0 × 10−8 and 8.4 × 10−8, respectively), with local ancestry analysis demonstrating similar levels of admixture in responders and nonresponders at implicated loci. Association at chromosome 5 was nominally replicated in an independent cohort of 130 SCD transfusion recipients, with meta-analysis surpassing genome-wide significance (rs75853687, Pmeta = 6.6 × 10−9), and this extended to individuals forming multiple (>3) alloantibodies (Pmeta = 9.4 × 10−5). The associated variant is rare outside of African populations, and orthogonal genome-wide haplotype analyses, contingent on local ancestry, revealed genome-wide significant sharing of a ∼60-kb haplotype of African ancestry at the chromosome 5 locus (Bayes Factor = 4.95). This locus overlaps a putative cis-acting enhancer predicted to regulate transcription of ADRA1B and the lncRNA LINC01847, both members of larger ontologies associated with immune regulation. Our findings provide potential insights to the pathophysiology underlying the development of alloantibodies and implicate non-RBC ancestry-limited loci in the susceptibility to alloimmunization.
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Go, Alwyn, Doaa Alhazmi, and Alberto Civetta. "Altered expression of cell adhesion genes and hybrid male sterility between subspecies ofDrosophila pseudoobscura." Genome 62, no. 10 (October 2019): 657–63. http://dx.doi.org/10.1139/gen-2019-0066.
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Drosophila pseudoobscura pseudoobscura and Drosophila pseudoobscura bogotana are two closely related subspecies with incomplete reproductive isolation. A genome-wide comparison of expression in hybrids relative to parental subspecies has been previously used to identify genes with significant changes in expression uniquely associated with the sterile condition. The misexpression (i.e., gene expression beyond levels found in parentals) of such genes could be directly linked to the onset of sterility or could alternatively be caused by incompatibilities in a hybrid genome without a direct link to sterility. Cell adhesion was previously found to be one of the largest gene ontologies with changes in expression linked to sterility. Here we used gene expression assays in fertile backcross male progeny, along with introgression progeny in which we swap a major hybrid male sterility (HMS) allele, to generate fertile and sterile males genotypically similar to F1sterile hybrids. We identify a cell adhesion gene (GA10921) whose change in expression is directly linked to sterility and modulated by a previously characterized HMS protein. GA10921 adds to our rather limited knowledge of changes in gene expression associated with HMS, and to the identification of gene interacting partners linked to HMS.
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G, Kopke, Anklam K, Kulow M, Baker L, Swalve HH, Lopes FB, Rosa GJM, and Dopfer D. "The identification of gene ontologies and candidate genes for digital dermatitis in beef cattle from a genome-wide association study." International Journal of Veterinary Science and Research 6, no. 1 (May 13, 2020): 027–37. http://dx.doi.org/10.17352/ijvsr.000050.
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Dehghannasiri, Roozbeh, Linda Szabo, and Julia Salzman. "Ambiguous splice sites distinguish circRNA and linear splicing in the human genome." Bioinformatics 35, no. 8 (September 5, 2018): 1263–68. http://dx.doi.org/10.1093/bioinformatics/bty785.
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Abstract Motivation Identification of splice sites is critical to gene annotation and to determine which sequences control circRNA biogenesis. Full-length RNA transcripts could in principle complete annotations of introns and exons in genomes without external ontologies, i.e., ab initio. However, whether it is possible to reconstruct genomic positions where splicing occurs from full-length transcripts, even if sampled in the absence of noise, depends on the genome sequence composition. If it is not, there exist provable limits on the use of RNA-Seq to define splice locations (linear or circular) in the genome. Results We provide a formal definition of splice site ambiguity due to the genomic sequence by introducing equivalent junction, which is the set of local genomic positions resulting in the same RNA sequence when joined through RNA splicing. We show that equivalent junctions are prevalent in diverse eukaryotic genomes and occur in 88.64% and 78.64% of annotated human splice sites in linear and circRNA junctions, respectively. The observed fractions of equivalent junctions and the frequency of many individual motifs are statistically significant when compared against the null distribution computed via simulation or closed-form. The frequency of equivalent junctions establishes a fundamental limit on the possibility of ab initio reconstruction of RNA transcripts without appealing to the ontology of “GT-AG” boundaries defining introns. Said differently, completely ab initio is impossible in the vast majority of splice sites in annotated circRNAs and linear transcripts. Availability and implementation Two python scripts generating an equivalent junction sequence per junction are available at: https://github.com/salzmanlab/Equivalent-Junctions. Supplementary information Supplementary data are available at Bioinformatics online.
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Dhombres, Ferdinand, and Jean Charlet. "Formal Medical Knowledge Representation Supports Deep Learning Algorithms, Bioinformatics Pipelines, Genomics Data Analysis, and Big Data Processes." Yearbook of Medical Informatics 28, no. 01 (August 2019): 152–55. http://dx.doi.org/10.1055/s-0039-1677933.
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Objective: To select, present, and summarize the best papers published in 2018 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers published in 2018 in KRM, based on PubMed and ISI Web Of Knowledge queries. Results: Four best papers were selected among the 962 publications retrieved following the Yearbook review process. The research areas in 2018 were mainly related to the ontology-based data integration for phenotype-genotype association mining, the design of ontologies and their application, and the semantic annotation of clinical texts. Conclusion: In the KRM selection for 2018, research on semantic representations demonstrated their added value for enhanced deep learning approaches in text mining and for designing novel bioinformatics pipelines based on graph databases. In addition, the ontology structure can enrich the analyses of whole genome expression data. Finally, semantic representations demonstrated promising results to process phenotypic big data.
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Lee, Young-Sup, Donghyun Shin, Kyeong-Hye Won, Dae Cheol Kim, Sang Chul Lee, and Ki-Duk Song. "Genome-wide scans for detecting the selection signature of the Jeju-island native pig in Korea." Asian-Australasian Journal of Animal Sciences 33, no. 4 (April 1, 2020): 539–46. http://dx.doi.org/10.5713/ajas.19.0026.
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Objective: The Jeju native pig (JNP) found on the Jeju Island of Korea is a unique black pig known for high-quality meat. To investigate the genetic uniqueness of JNP, we analyzed the selection signature of the JNP in comparison to commercial pigs such as Berkshire and Yorkshire pigs.Methods: We surveyed the genetic diversity to identify the genetic stability of the JNP, using the linkage disequilibrium method. A selective sweep of the JNP was performed to identify the selection signatures. To do so, the population differentiation measure, Weir-Cockerham’s F<sub>st</sub> was utilized. This statistic directly measures the population differentiation at the variant level. Additionally, we investigated the gene ontologies (GOs) and genetic features.Results: Compared to the Berkshire and Yorkshire pigs, the JNP had lower genetic diversity in terms of linkage disequilibrium decays. We summarized the selection signatures of the JNP as GO. In the JNP and Berkshire pigs, the most enriched GO terms were epithelium development and neuron-related. Considering the JNP and Yorkshire pigs, cellular response to oxygen-containing compound and generation of neurons were the most enriched GO.Conclusion: The selection signatures of the JNP were identified through the population differentiation statistic. The genes with possible selection signatures are expected to play a role in JNP’s unique pork quality.
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Nigam, Rajni, Stanley J. F. Laulederkind, G. Thomas Hayman, Jennifer R. Smith, Shur-Jen Wang, Timothy F. Lowry, Victoria Petri, et al. "Rat Genome Database: a unique resource for rat, human, and mouse quantitative trait locus data." Physiological Genomics 45, no. 18 (September 15, 2013): 809–16. http://dx.doi.org/10.1152/physiolgenomics.00065.2013.
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The rat has been widely used as a disease model in a laboratory setting, resulting in an abundance of genetic and phenotype data from a wide variety of studies. These data can be found at the Rat Genome Database (RGD, http://rgd.mcw.edu/ ), which provides a platform for researchers interested in linking genomic variations to phenotypes. Quantitative trait loci (QTLs) form one of the earliest and core datasets, allowing researchers to identify loci harboring genes associated with disease. These QTLs are not only important for those using the rat to identify genes and regions associated with disease, but also for cross-organism analyses of syntenic regions on the mouse and the human genomes to identify potential regions for study in these organisms. Currently, RGD has data on >1,900 rat QTLs that include details about the methods and animals used to determine the respective QTL along with the genomic positions and markers that define the region. RGD also curates human QTLs (>1,900) and houses >4,000 mouse QTLs (imported from Mouse Genome Informatics). Multiple ontologies are used to standardize traits, phenotypes, diseases, and experimental methods to facilitate queries, analyses, and cross-organism comparisons. QTLs are visualized in tools such as GBrowse and GViewer, with additional tools for analysis of gene sets within QTL regions. The QTL data at RGD provide valuable information for the study of mapped phenotypes and identification of candidate genes for disease associations.
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Leone, Michele, Eugenia Galeota, Marco Masseroli, and Mattia Pelizzola. "Identification, semantic annotation and comparison of combinations of functional elements in multiple biological conditions." Bioinformatics 38, no. 5 (December 2, 2021): 1183–90. http://dx.doi.org/10.1093/bioinformatics/btab815.
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Abstract Motivation Approaches such as chromatin immunoprecipitation followed by sequencing (ChIP-seq) represent the standard for the identification of binding sites of DNA-associated proteins, including transcription factors and histone marks. Public repositories of omics data contain a huge number of experimental ChIP-seq data, but their reuse and integrative analysis across multiple conditions remain a daunting task. Results We present the Combinatorial and Semantic Analysis of Functional Elements (CombSAFE), an efficient computational method able to integrate and take advantage of the valuable and numerous, but heterogeneous, ChIP-seq data publicly available in big data repositories. Leveraging natural language processing techniques, it integrates omics data samples with semantic annotations from selected biomedical ontologies; then, using hidden Markov models, it identifies combinations of static and dynamic functional elements throughout the genome for the corresponding samples. CombSAFE allows analyzing the whole genome, by clustering patterns of regions with similar functional elements and through enrichment analyses to discover ontological terms significantly associated with them. Moreover, it allows comparing functional states of a specific genomic region to analyze their different behavior throughout the various semantic annotations. Such findings can provide novel insights by identifying unexpected combinations of functional elements in different biological conditions. Availability and implementation The Python implementation of the CombSAFE pipeline is freely available for non-commercial use at: https://github.com/DEIB-GECO/CombSAFE. Supplementary information Supplementary data are available at Bioinformatics online.
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Kaldunski, M. L., J. R. Smith, G. T. Hayman, K. Brodie, J. L. De Pons, W. M. Demos, A. C. Gibson, et al. "The Rat Genome Database (RGD) facilitates genomic and phenotypic data integration across multiple species for biomedical research." Mammalian Genome 33, no. 1 (November 5, 2021): 66–80. http://dx.doi.org/10.1007/s00335-021-09932-x.
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AbstractModel organism research is essential for discovering the mechanisms of human diseases by defining biologically meaningful gene to disease relationships. The Rat Genome Database (RGD, (https://rgd.mcw.edu)) is a cross-species knowledgebase and the premier online resource for rat genetic and physiologic data. This rich resource is enhanced by the inclusion and integration of comparative data for human and mouse, as well as other human disease models including chinchilla, dog, bonobo, pig, 13-lined ground squirrel, green monkey, and naked mole-rat. Functional information has been added to records via the assignment of annotations based on sequence similarity to human, rat, and mouse genes. RGD has also imported well-supported cross-species data from external resources. To enable use of these data, RGD has developed a robust infrastructure of standardized ontologies, data formats, and disease- and species-centric portals, complemented with a suite of innovative tools for discovery and analysis. Using examples of single-gene and polygenic human diseases, we illustrate how data from multiple species can help to identify or confirm a gene as involved in a disease and to identify model organisms that can be studied to understand the pathophysiology of a gene or pathway. The ultimate aim of this report is to demonstrate the utility of RGD not only as the core resource for the rat research community but also as a source of bioinformatic tools to support a wider audience, empowering the search for appropriate models for human afflictions.
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Purwoko, Devit, Imam Civi Cartealy, Teuku Tajuddin, Diny Dinarti, and Sudarsono Sudarsono. "ANALISIS BIOINFORMATIKA BERBASIS WEB PADA SEKUEN GENOM PARSIAL SAGU (Metroxylon sagu Rottb.)." Jurnal Bioteknologi & Biosains Indonesia (JBBI) 5, no. 1 (June 29, 2018): 98. http://dx.doi.org/10.29122/jbbi.v5i1.2878.
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WEB-based bioinformatic analysis on partial genome sequence of Sago (Metroxylon sagu Rottb.)ABSTRACTSago genome sequencing analysis is still very limited. This study is a preliminary study of sago sequence analysis obtained from NGS technology to understand and identify new genetic sequences that have homology to genes in the NCBI database. Sequences were analyzed using Blast2Go to determine the genetic function annotation, putative gene identification was performed on the Arabidopsis database using the BLASTx program with a 10-3 e-value limit on The Arabidopsis Information Resource (TAIR) (http://www.arabidopsis.org/index.jsp). Gene interactions were analyzed using DAVID and GeneMania programs. Based on sequence analysis with Blast2Go, 33 sequences with Blastx hit consisting of: 29 sequences had a high homology. The sago sequences with a similarity of ≥ 90% are glutamate decarboxylase and HT1-like serine threonine kinase with hit number 10. The distribution of interactions between genes from GeneMania analysis is known to be mostly interconnected in the 65.13% protein domain, predicted 19.83%, genes with 14.47% shared expression and the remaining 0.57% had localization together.Keywords: bioinformatics, gene annotation, gene ontology, genome sequence, Metroxylon sagu ABSTRAKKajian analisis sekuen genom sagu hingga saat ini masih amat terbatas. Penelitian ini merupakan riset pendahuluan analisis sekuen sagu yang diperoleh dari teknologi NGS untuk mengetahui dan mengidentifikasi sekuen gen baru yang memiliki homologi dengan gen pada database NCBI. Sekuen dianalisis menggunakan perangkat Blast2Go untuk mengetahui anotasi fungsional gen, identifikasi gen putatif dilakukan terhadap database Arabidopsis menggunakan program BLASTx dengan batas e-value 10-3 pada The Arabidopsis Information Resource (TAIR). Interaksi gen dianalisis menggunakan program DAVID dan GeneMania. Berdasarkan analisis sekuen dengan Blast2Go, diperoleh 33 sekuen dengan Blastx hit yang terdiri atas: 29 sekuen memiliki homologi yang tinggi. Gen dengan rataan kemiripan ≥ 90% adalah glutamate decarboxylase dan serine threonine-kinase HT1-like dengan jumlah hit 10. Persebaran interaksi antar gen hasil analisis GeneMania diketahui sebagian besar saling terkait pada domain protein 65,13%, koneksi yang berhasil diprediksi 19,83%, gen dengan ekspresi bersama 14,47% dan sisanya 0,57% memiliki peranan bersama. Kata Kunci: anotasi gen, bioinformatika, Metroxylon sagu, ontologi gen, sekuen genome
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Chi, Xu, Maureen A. Sartor, Sanghoon Lee, Meenakshi Anurag, Snehal Patil, Pelle Hall, Matthew Wexler, and Xiao-Song Wang. "Universal concept signature analysis: genome-wide quantification of new biological and pathological functions of genes and pathways." Briefings in Bioinformatics 21, no. 5 (October 18, 2019): 1717–32. http://dx.doi.org/10.1093/bib/bbz093.
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Abstract Identifying new gene functions and pathways underlying diseases and biological processes are major challenges in genomics research. Particularly, most methods for interpreting the pathways characteristic of an experimental gene list defined by genomic data are limited by their dependence on assessing the overlapping genes or their interactome topology, which cannot account for the variety of functional relations. This is particularly problematic for pathway discovery from single-cell genomics with low gene coverage or interpreting complex pathway changes such as during change of cell states. Here, we exploited the comprehensive sets of molecular concepts that combine ontologies, pathways, interactions and domains to help inform the functional relations. We first developed a universal concept signature (uniConSig) analysis for genome-wide quantification of new gene functions underlying biological or pathological processes based on the signature molecular concepts computed from known functional gene lists. We then further developed a novel concept signature enrichment analysis (CSEA) for deep functional assessment of the pathways enriched in an experimental gene list. This method is grounded on the framework of shared concept signatures between gene sets at multiple functional levels, thus overcoming the limitations of the current methods. Through meta-analysis of transcriptomic data sets of cancer cell line models and single hematopoietic stem cells, we demonstrate the broad applications of CSEA on pathway discovery from gene expression and single-cell transcriptomic data sets for genetic perturbations and change of cell states, which complements the current modalities. The R modules for uniConSig analysis and CSEA are available through https://github.com/wangxlab/uniConSig.
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Vogel Ciernia, A., B. I. Laufer, H. Hwang, K. W. Dunaway, C. E. Mordaunt, R. L. Coulson, D. H. Yasui, and J. M. LaSalle. "Epigenomic Convergence of Neural-Immune Risk Factors in Neurodevelopmental Disorder Cortex." Cerebral Cortex 30, no. 2 (June 26, 2019): 640–55. http://dx.doi.org/10.1093/cercor/bhz115.
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Abstract Neurodevelopmental disorders (NDDs) affect 7–14% of all children in developed countries and are one of the leading causes of lifelong disability. Epigenetic modifications are poised at the interface between genes and environment and are predicted to reveal insight into NDD etiology. Whole-genome bisulfite sequencing was used to examine DNA cytosine methylation in 49 human cortex samples from 3 different NDDs (autism spectrum disorder, Rett syndrome, and Dup15q syndrome) and matched controls. Integration of methylation changes across NDDs with relevant genomic and genetic datasets revealed differentially methylated regions (DMRs) unique to each type of NDD but with shared regulatory functions in neurons and microglia. NDD DMRs were enriched within promoter regions and for transcription factor binding sites with identified methylation sensitivity. DMRs from all 3 disorders were enriched for ontologies related to nervous system development and genes with disrupted expression in brain from neurodevelopmental or neuropsychiatric disorders. Genes associated with NDD DMRs showed expression patterns indicating an important role for altered microglial function during brain development. These findings demonstrate an NDD epigenomic signature in human cortex that will aid in defining therapeutic targets and early biomarkers at the interface of genetic and environmental NDD risk factors.
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Seaver, Samuel M. D., Filipe Liu, Qizhi Zhang, James Jeffryes, José P. Faria, Janaka N. Edirisinghe, Michael Mundy, et al. "The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes." Nucleic Acids Research 49, no. D1 (September 28, 2020): D575—D588. http://dx.doi.org/10.1093/nar/gkaa746.
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Abstract For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.
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Schoof, H., R. Ernst, and K. F. X. Mayer. "The PlaNet Consortium: A Network of European Plant Databases Connecting Plant Genome Data in an Integrated Biological Knowledge Resource." Comparative and Functional Genomics 5, no. 2 (2004): 184–89. http://dx.doi.org/10.1002/cfg.374.
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The completion of theArabidopsisgenome and the large collections of other plant sequences generated in recent years have sparked extensive functional genomics efforts. However, the utilization of this data is inefficient, as data sources are distributed and heterogeneous and efforts at data integration are lagging behind. PlaNet aims to overcome the limitations of individual efforts as well as the limitations of heterogeneous, independent data collections. PlaNet is a distributed effort among European bioinformatics groups and plant molecular biologists to establish a comprehensive integrated database in a collaborative network. Objectives are the implementation of infrastructure and data sources to capture plant genomic information into a comprehensive, integrated platform. This will facilitate the systematic exploration ofArabidopsisand other plants. New methods for data exchange, database integration and access are being developed to create a highly integrated, federated data resource for research. The connection between the individual resources is realized with BioMOBY. BioMOBY provides an architecture for the discovery and distribution of biological data through web services. While knowledge is centralized, data is maintained at its primary source without a need for warehousing. To standardize nomenclature and data representation, ontologies and generic data models are defined in interaction with the relevant communities.Minimal data models should make it simple to allow broad integration, while inheritance allows detail and depth to be added to more complex data objects without losing integration. To allow expert annotation and keep databases curated, local and remote annotation interfaces are provided. Easy and direct access to all data is key to the project.
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Spin, Joshua M., Mark Hsu, Junya Azuma, Maureen M. Tedesco, Alicia Deng, Justin S. Dyer, Lars Maegdefessel, Ronald L. Dalman, and Philip S. Tsao. "Transcriptional profiling and network analysis of the murine angiotensin II-induced abdominal aortic aneurysm." Physiological Genomics 43, no. 17 (September 2011): 993–1003. http://dx.doi.org/10.1152/physiolgenomics.00044.2011.
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We sought to characterize temporal gene expression changes in the murine angiotensin II (ANG II)-ApoE−/− model of abdominal aortic aneurysm (AAA). Aortic ultrasound measurements were obtained over the 28-day time-course. Harvested suprarenal aortic segments were evaluated with whole genome expression profiling at 7, 14, and 28 days using the Agilent Whole Mouse Genome microarray platform and Statistical Analysis of Microarrays at a false discovery rate of <1%. A group of angiotensin-treated mice experienced contained rupture (CR) within 7 days and were analyzed separately. Progressive aortic dilatation occurred throughout the treatment period. However, the numerous early expression differences between ANG II-treated and control were not sustained over time. Ontologic analysis revealed widespread upregulation of inflammatory, immune, and matrix remodeling genes with ANG II treatment, among other pathways such as apoptosis, cell cycling, angiogenesis, and p53 signaling. CR aneurysms displayed significant decreases in TGF-β/BMP-pathway signaling, MAPK signaling, and ErbB signaling genes vs. non-CR/ANG II-treated samples. We also performed literature-based network analysis, extracting numerous highly interconnected genes associated with aneurysm development such as Spp1, Myd88, Adam17 and Lox. 1) ANG II treatment induces extensive early differential expression changes involving abundant signaling pathways in the suprarenal abdominal aorta, particularly wide-ranging increases in inflammatory genes with aneurysm development. 2) These gene expression changes appear to dissipate with time despite continued growth, suggesting that early changes in gene expression influence disease progression in this AAA model, and that the aortic tissue adapts to prolonged ANG II infusion. 3) Network analysis identified nexus genes that may constitute aneurysm biomarkers or therapeutic targets.
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Chetta, Massimiliano, Lorena Di Pietro, Nenad Bukvic, and Wanda Lattanzi. "Rising Roles of Small Noncoding RNAs in Cotranscriptional Regulation: In Silico Study of miRNA and piRNA Regulatory Network in Humans." Genes 11, no. 5 (April 29, 2020): 482. http://dx.doi.org/10.3390/genes11050482.
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Gene expression regulation is achieved through an intricate network of molecular interactions, in which trans-acting transcription factors (TFs) and small noncoding RNAs (sncRNAs), including microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs), play a key role. Recent observations allowed postulating an interplay between TFs and sncRNAs, in that they may possibly share DNA-binding sites. The aim of this study was to analyze the complete subset of miRNA and piRNA sequences stored in the main databases in order to identify the occurrence of conserved motifs and subsequently predict a possible innovative interplay with TFs at a transcriptional level. To this aim, we adopted an original in silico workflow to search motifs and predict interactions within genome-scale regulatory networks. Our results allowed categorizing miRNA and piRNA motifs, with corresponding TFs sharing complementary DNA-binding motifs. The biological interpretation of the gene ontologies of the TFs permitted observing a selective enrichment in developmental pathways, allowing the distribution of miRNA motifs along a topological and chronological frame. In addition, piRNA motifs were categorized for the first time and revealed specific functional implications in somatic tissues. These data might pose experimental hypotheses to be tested in biological models, towards clarifying novel in gene regulatory routes.
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Vempati, Uma D., Caty Chung, Chris Mader, Amar Koleti, Nakul Datar, Dušica Vidović, David Wrobel, et al. "Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS)." Journal of Biomolecular Screening 19, no. 5 (February 11, 2014): 803–16. http://dx.doi.org/10.1177/1087057114522514.
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The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.
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Goldman, Jonathan. "Éditorial." Circuit 17, no. 1 (December 7, 2007): 5–10. http://dx.doi.org/10.7202/016770ar.
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Le Human Genome Project (hgp) a été initié par le Département états-unien de l’énergie et des instituts nationaux de la santé, et avait pour but de découvrir les 20 000 à 25 000 gènes humains, afin de les rendre accessibles à l’étude biologique. Par analogie, l’auteur présente le numéro comme un parcours dans les « gènes » de l’oeuvre musicale contemporaine qui interroge ce qui se trouve à l’origine de l’oeuvre et qu’on désigne habituellement par « l’idée musicale ». Soulignant la provenance de ce terme chez Arnold Schoenberg, qui a fait un effort délibéré pour ressusciter le concept de « musikalische Gedanke » dans le discours sur la musique moderne, l’auteur avance que le caractère équivoque de ce concept — qui désigne à la fois une entité se situant avant et dans l’oeuvre — le rend pratique en tant qu’outil heuristique malléable et informe dont se sert le compositeur pour désigner un objet qui n’a pas encore de fonction, c’est-à-dire, dont il ignore encore le statut ontologique aux stades initiaux de son cheminement.
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Fang, Hai, and Julian C. Knight. "Priority index: database of genetic targets in immune-mediated disease." Nucleic Acids Research 50, no. D1 (November 9, 2021): D1358—D1367. http://dx.doi.org/10.1093/nar/gkab994.
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Abstract We describe a comprehensive and unique database ‘Priority index’ (Pi; http://pi.well.ox.ac.uk) of prioritized genes encoding potential therapeutic targets that encompasses all major immune-mediated diseases. We provide targets at the gene level, each receiving a 5-star rating supported by: genomic evidence arising from disease genome-wide associations and functional immunogenomics, annotation evidence using ontologies restricted to genes with genomic evidence, and network evidence from protein interactions. Target genes often act together in related molecular pathways. The underlying Pi approach is unique in identifying a network of highly rated genes that mediate pathway crosstalk. In the Pi website, disease-centric pages are specially designed to enable the users to browse a complete list of prioritized genes and also a manageable list of nodal genes at the pathway crosstalk level; both switchable by clicks. Moreover, target genes are cross-referenced and supported using additional information, particularly regarding tractability, including druggable pockets viewed in 3D within protein structures. Target genes highly rated across diseases suggest drug repurposing opportunity, while genes in a particular disease reveal disease-specific targeting potential. To facilitate the ease of such utility, cross-disease comparisons involving multiple diseases are also supported. This facility, together with the faceted search, enhances integrative mining of the Pi resource to accelerate early-stage therapeutic target identification and validation leveraging human genetics.
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Parker, Ceth W., Marcus de Melo Teixeira, Nitin K. Singh, Huzefa A. Raja, Kristof B. Cank, Giada Spigolon, Nicholas H. Oberlies, et al. "Genomic Characterization of Parengyodontium torokii sp. nov., a Biofilm-Forming Fungus Isolated from Mars 2020 Assembly Facility." Journal of Fungi 8, no. 1 (January 9, 2022): 66. http://dx.doi.org/10.3390/jof8010066.
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A fungal strain (FJII-L10-SW-P1) was isolated from the Mars 2020 spacecraft assembly facility and exhibited biofilm formation on spacecraft-qualified Teflon surfaces. The reconstruction of a six-loci gene tree (ITS, LSU, SSU, RPB1 and RPB2, and TEF1) using multi-locus sequence typing (MLST) analyses of the strain FJII-L10-SW-P1 supported a close relationship to other known Parengyodontium album subclade 3 isolates while being phylogenetically distinct from subclade 1 strains. The zig-zag rachides morphology of the conidiogenous cells and spindle-shaped conidia were the distinct morphological characteristics of the P. album subclade 3 strains. The MLST data and morphological analysis supported the conclusion that the P. album subclade 3 strains could be classified as a new species of the genus Parengyodontium and placed in the family Cordycipitaceae. The name Parengyodontium torokii sp. nov. is proposed to accommodate the strain, with FJII-L10-SW-P1 as the holotype. The genome of the FJII-L10-SW-P1 strain was sequenced, annotated, and the secondary metabolite clusters were identified. Genes predicted to be responsible for biofilm formation and adhesion to surfaces were identified. Homology-based assignment of gene ontologies to the predicted proteome of P. torokii revealed the presence of gene clusters responsible for synthesizing several metabolic compounds, including a cytochalasin that was also verified using traditional metabolomic analysis.
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Mastriani, Emilio, Alexey V. Rakov, and Shu-Lin Liu. "Isolating SARS-CoV-2 Strains From Countries in the Same Meridian: Genome Evolutionary Analysis." JMIR Bioinformatics and Biotechnology 2, no. 1 (January 22, 2021): e25995. http://dx.doi.org/10.2196/25995.
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Background COVID-19, caused by the novel SARS-CoV-2, is considered the most threatening respiratory infection in the world, with over 40 million people infected and over 0.934 million related deaths reported worldwide. It is speculated that epidemiological and clinical features of COVID-19 may differ across countries or continents. Genomic comparison of 48,635 SARS-CoV-2 genomes has shown that the average number of mutations per sample was 7.23, and most SARS-CoV-2 strains belong to one of 3 clades characterized by geographic and genomic specificity: Europe, Asia, and North America. Objective The aim of this study was to compare the genomes of SARS-CoV-2 strains isolated from Italy, Sweden, and Congo, that is, 3 different countries in the same meridian (longitude) but with different climate conditions, and from Brazil (as an outgroup country), to analyze similarities or differences in patterns of possible evolutionary pressure signatures in their genomes. Methods We obtained data from the Global Initiative on Sharing All Influenza Data repository by sampling all genomes available on that date. Using HyPhy, we achieved the recombination analysis by genetic algorithm recombination detection method, trimming, removal of the stop codons, and phylogenetic tree and mixed effects model of evolution analyses. We also performed secondary structure prediction analysis for both sequences (mutated and wild-type) and “disorder” and “transmembrane” analyses of the protein. We analyzed both protein structures with an ab initio approach to predict their ontologies and 3D structures. Results Evolutionary analysis revealed that codon 9628 is under episodic selective pressure for all SARS-CoV-2 strains isolated from the 4 countries, suggesting it is a key site for virus evolution. Codon 9628 encodes the P0DTD3 (Y14_SARS2) uncharacterized protein 14. Further investigation showed that the codon mutation was responsible for helical modification in the secondary structure. The codon was positioned in the more ordered region of the gene (41-59) and near to the area acting as the transmembrane (54-67), suggesting its involvement in the attachment phase of the virus. The predicted protein structures of both wild-type and mutated P0DTD3 confirmed the importance of the codon to define the protein structure. Moreover, ontological analysis of the protein emphasized that the mutation enhances the binding probability. Conclusions Our results suggest that RNA secondary structure may be affected and, consequently, the protein product changes T (threonine) to G (glycine) in position 50 of the protein. This position is located close to the predicted transmembrane region. Mutation analysis revealed that the change from G (glycine) to D (aspartic acid) may confer a new function to the protein—binding activity, which in turn may be responsible for attaching the virus to human eukaryotic cells. These findings can help design in vitro experiments and possibly facilitate a vaccine design and successful antiviral strategies.
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Dhaygude, Kishor, Kalevi Trontti, Jenni Paviala, Claire Morandin, Christopher Wheat, Liselotte Sundström, and Heikki Helanterä. "Transcriptome sequencing reveals high isoform diversity in the ant Formica exsecta." PeerJ 5 (November 21, 2017): e3998. http://dx.doi.org/10.7717/peerj.3998.
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Transcriptome resources for social insects have the potential to provide new insight into polyphenism, i.e., how divergent phenotypes arise from the same genome. Here we present a transcriptome based on paired-end RNA sequencing data for the ant Formica exsecta (Formicidae, Hymenoptera). The RNA sequencing libraries were constructed from samples of several life stages of both sexes and female castes of queens and workers, in order to maximize representation of expressed genes. We first compare the performance of common assembly and scaffolding software (Trinity, Velvet-Oases, and SOAPdenovo-trans), in producing de novo assemblies. Second, we annotate the resulting expressed contigs to the currently published genomes of ants, and other insects, including the honeybee, to filter genes that have annotation evidence of being true genes. Our pipeline resulted in a final assembly of altogether 39,262 mRNA transcripts, with an average coverage of >300X, belonging to 17,496 unique genes with annotation in the related ant species. From these genes, 536 genes were unique to one caste or sex only, highlighting the importance of comprehensive sampling. Our final assembly also showed expression of several splice variants in 6,975 genes, and we show that accounting for splice variants affects the outcome of downstream analyses such as gene ontologies. Our transcriptome provides an outstanding resource for future genetic studies on F. exsecta and other ant species, and the presented transcriptome assembly can be adapted to any non-model species that has genomic resources available from a related taxon.
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Magouliotis, Dimitrios E., Vasiliki S. Tasiopoulou, Ioannis Baloyiannis, Ioannis Mamaloudis, and George Tzovaras. "Transcriptomic Analysis of the Aquaporin Gene Family and Associated Interactors in Rectal Cancer." MicroRNA 9, no. 2 (March 4, 2020): 153–66. http://dx.doi.org/10.2174/2211536608666190917153332.
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Background: Rectal Cancer (RC) is a common type of cancer with poor prognosis. The identification of biomarkers regarding RC diagnosis, monitoring, and prognosis is crucial. Objectives: The purpose of the present study was to evaluate the differential expression of the Aquaporin (AQP) gene family network in RC, and the effect of Radiotherapy (RT) on their expression profile, to indicate novel biomarkers and prognostic factors. Methods: We used data mining techniques to construct the network of the AQP-associated genes to determine the Differentially Expressed Genes (DEGs) in RC and in irradiated as compared to nonirradiated RC patients. Furthermore, survival data of The Cancer Genome Atlas (TCGA) were analysed to assess the prognostic role of the DEGs, along with the functional enrichment of gene ontologies and miRNAs related to the DEGs in RC. Results: Microarray data of one PubMed GEO dataset was extracted, incorporating 22 RC and 20 normal rectal tissue samples. Eight DEGs were reported. Four DEGs were up-regulated and four downregulated in RC. Correlations were identified among the DEGs. Deming regression analysis was performed in order to demonstrate the equations describing these correlations. One gene (Aquaporin 3) was downregulated in irradiated RC samples compared with non-irradiated samples. The most significantly affected biological pathways and miRNAs were identified by functional enrichment analysis. Conclusion: The present study demonstrates an eight-gene molecular panel that could facilitate as biomarkers regarding RC patients, which are potential targets of five miRNA families. Finally, our results highlight the effect of radiotherapy on AQPs and the associated pathways in RC.
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Isom, S. Clay, John R. Stevens, Rongfeng Li, William G. Spollen, Lindsay Cox, Lee D. Spate, Clifton N. Murphy, and Randall S. Prather. "Transcriptional profiling by RNA-Seq of peri-attachment porcine embryos generated by a variety of assisted reproductive technologies." Physiological Genomics 45, no. 14 (July 15, 2013): 577–89. http://dx.doi.org/10.1152/physiolgenomics.00094.2012.
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Substantial mortality of in vitro manipulated porcine embryos is observed during peri-attachment development. Herein we describe our efforts to characterize the transcriptomes of embryonic disc (ED) and trophectoderm (TE) cells from porcine embryos derived from in vivo fertilization, in vitro fertilization (IVF), parthenogenetic oocyte activation (PA), and somatic cell nuclear transfer (SCNT) on days 10, 12, and 14 of gestation. The IVF, PA, and SCNT embryos were generated with in vitro matured oocytes and were cultured overnight in vitro before being transferred to recipient females. Sequencing of cDNA from the resulting embryonic samples was accomplished with the Genome Analyzer IIx platform from Illumina. Reads were aligned to a custom-built swine transcriptome. A generalized linear model was fit for ED and TE samples separately, accounting for embryo type, gestation day, and their interaction. Those genes with significant differences between embryo types were characterized in terms of gene ontologies and KEGG pathways. Transforming growth factor-β signaling was downregulated in the EDs of IVF embryos. In TE cells from IVF embryos, ubiquitin-mediated proteolysis and ErbB signaling were aberrantly regulated. Expression of genes involved in chromatin modification, gene silencing by RNA, and apoptosis was significantly disrupted in ED cells from SCNT embryos. In summary, we have used high-throughput sequencing technologies to compare gene expression profiles of various embryo types during peri-attachment development. We expect that these data will provide important insight into the root causes of (and possible opportunities for mitigation of) suboptimal development of embryos derived from assisted reproductive technologies.
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Dhombres, F., and J. Charlet. "Knowledge Representation and Management, It’s Time to Integrate!" Yearbook of Medical Informatics 26, no. 01 (2017): 148–51. http://dx.doi.org/10.15265/iy-2017-030.
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Summary Objectives: To select, present, and summarize the best papers published in 2016 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed based on a PubMed query. Results: Among the 1,421 retrieved papers, the review process resulted in the selection of four best papers focused on the integration of heterogeneous data via the development and the alignment of terminological resources. In the first article, the authors provide a curated and standardized version of the publicly available US FDA Adverse Event Reporting System. Such a resource will improve the quality of the underlying data, and enable standardized analyses using common vocabularies. The second article describes a project developed in order to facilitate heterogeneous data integration in the i2b2 framework. The originality is to allow users integrate the data described in different terminologies and to build a new repository, with a unique model able to support the representation of the various data. The third paper is dedicated to model the association between multiple phenotypic traits described within the Human Phenotype Ontology (HPO) and the corresponding genotype in the specific context of rare diseases (rare variants). Finally, the fourth paper presents solutions to annotation-ontology mapping in genome-scale data. Of particular interest in this work is the Experimental Factor Ontology (EFO) and its generic association model, the Ontology of Biomedical AssociatioN (OBAN). Conclusion: Ontologies have started to show their efficiency to integrate medical data for various tasks in medical informatics: electronic health records data management, clinical research, and knowledge-based systems development.
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Dhombres, F., and J. Charlet. "Knowledge Representation and Management, It’s Time to Integrate!" Yearbook of Medical Informatics 26, no. 01 (August 2017): 148–51. http://dx.doi.org/10.1055/s-0037-1606496.
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Summary Objectives: To select, present, and summarize the best papers published in 2016 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed based on a PubMed query. Results: Among the 1,421 retrieved papers, the review process resulted in the selection of four best papers focused on the integration of heterogeneous data via the development and the alignment of terminological resources. In the first article, the authors provide a curated and standardized version of the publicly available US FDA Adverse Event Reporting System. Such a resource will improve the quality of the underlying data, and enable standardized analyses using common vocabularies. The second article describes a project developed in order to facilitate heterogeneous data integration in the i2b2 framework. The originality is to allow users integrate the data described in different terminologies and to build a new repository, with a unique model able to support the representation of the various data. The third paper is dedicated to model the association between multiple phenotypic traits described within the Human Phenotype Ontology (HPO) and the corresponding genotype in the specific context of rare diseases (rare variants). Finally, the fourth paper presents solutions to annotation-ontology mapping in genome-scale data. Of particular interest in this work is the Experimental Factor Ontology (EFO) and its generic association model, the Ontology of Biomedical AssociatioN (OBAN). Conclusion: Ontologies have started to show their efficiency to integrate medical data for various tasks in medical informatics: electronic health records data management, clinical research, and knowledge-based systems development.
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Coulson, Garry B., Aleksandra A. Miranda-CasoLuengo, Raúl Miranda-CasoLuengo, Xiaoguang Wang, Jenna Oliver, Jennifer M. Willingham-Lane, Wim G. Meijer, and Mary K. Hondalus. "Transcriptome Reprogramming by Plasmid-Encoded Transcriptional Regulators Is Required for Host Niche Adaption of a Macrophage Pathogen." Infection and Immunity 83, no. 8 (May 26, 2015): 3137–45. http://dx.doi.org/10.1128/iai.00230-15.
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Rhodococcus equiis a facultative intracellular pathogen of macrophages, relying on the presence of a conjugative virulence plasmid harboring a 21-kb pathogenicity island (PAI) for growth in host macrophages. The PAI encodes a family of 6 virulence-associated proteins (Vaps) in addition to 20 other proteins. The contribution of these to virulence has remained unclear. We show that the presence of only 3 virulence plasmid genes (of 73 in total) is required and sufficient for intracellular growth. These include a singlevapfamily member,vapA, and two PAI-located transcriptional regulators,virRandvirS. Both transcriptional regulators are essential for wild-type-level expression ofvapA, yetvapAexpression alone is not sufficient to allow intracellular growth. A whole-genome microarray analysis revealed that VirR and VirS substantially integrate themselves into the chromosomal regulatory network, significantly altering the transcription of 18% of all chromosomal genes. This pathoadaptation involved significant enrichment of select gene ontologies, in particular, enrichment of genes involved in transport processes, energy production, and cellular metabolism, suggesting a major change in cell physiology allowing the bacterium to grow in the hostile environment of the host cell. The results suggest that following the acquisition of the virulence plasmid by an avirulent ancestor ofR. equi, coevolution between the plasmid and the chromosome took place, allowing VirR and VirS to regulate the transcription of chromosomal genes in a process that ultimately promoted intracellular growth. Our findings suggest a mechanism for cooption of existing chromosomal traits during the evolution of a pathogenic bacterium from an avirulent saprophyte.
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Dzale Yeumo, Esther, Michael Alaux, Elizabeth Arnaud, Sophie Aubin, Ute Baumann, Patrice Buche, Laurel Cooper, et al. "Developing data interoperability using standards: A wheat community use case." F1000Research 6 (October 16, 2017): 1843. http://dx.doi.org/10.12688/f1000research.12234.1.
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In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach’s potential to be generalizable to other (agricultural) domains.
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Dzale Yeumo, Esther, Michael Alaux, Elizabeth Arnaud, Sophie Aubin, Ute Baumann, Patrice Buche, Laurel Cooper, et al. "Developing data interoperability using standards: A wheat community use case." F1000Research 6 (December 6, 2017): 1843. http://dx.doi.org/10.12688/f1000research.12234.2.
Full textAbstract:
In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach’s potential to be generalizable to other (agricultural) domains.
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Ko, Haesu, Won-Il Kim, Han-Hwa Chae, Won-Chul Park, Jong-Eun Park, Jihye Cha, Mi-Rim Park, Yeong-jo Im, and Bong-Hwan Choi. "PSVI-36 Transcriptome analysis of porcine tonsils following PRRS virus infection." Journal of Animal Science 97, Supplement_3 (December 2019): 202–3. http://dx.doi.org/10.1093/jas/skz258.417.
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Abstract The major concern for the pig industry is disease control and prevention, and porcine reproductive and respiratory syndrome (PRRS) is one of the main threats to it. Tonsil is a part of the immune system and its role is to recognize and reject foreign antigens to prevent them from invading the lungs. Interestingly, porcine tonsil can harbor PRRS viruses over 150 days post infection (dpi) with no clinical signs, causing PRRS re-break. This study was conducted to find out variation in levels of gene expression in tonsils and investigate functional roles of differentially expressed genes in tonsils depending on days post infection. We used porcine tonsils from weaned pigs following experimental infection with PRRSV-2 (JA142 strain) at 3, 10, 21, 28, 35 dpi. Based on RNA-seq analysis pipeline, differentially expressed genes (DEGs) were considered significant at False Discovery Rate (FDR) ≤ 0.05 level and above the two-fold change. Comparative analyses of 3 dpi vs. 10 dpi, 3 dpi vs. 21 dpi, 3 dpi vs. 28 dpi, and 3 dpi vs. 35 dpi produced 368, 315, 754, and 336 DEGs, respectively. Then we annotated the functions of each DEG set using DAVID tool. Significant GO terms of the MF, BP, and CC ontologies and KEGG pathways were selected within the limit of FDR < 0.05. Common overrepresented GO terms of all DEG sets were mainly negative regulation of viral genome replication, defense response to virus, negative regulation of type Ⅰ interferon production, and type Ⅰ interferon signaling pathway. Specific GO terms were found such as cellular response to interleukin-1, interferon-gamma-mediated signaling pathway, growth factor activity, and acute-phase response from each DEG set, respectively. It suggested tonsil responded to protect itself from PRRSV infection but further study is required to understand PRRSV persistence in tonsils.
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Giannini, H. M., C. V. Cosgriff, X. M. Lu, J. R. Reilly, B. J. Anderson, T. K. Jones, C. A. G. Ittner, et al. "38081 A Whole Blood Signature of Neutrophil Expression and Adaptive Immune Downregulation Characterizes Sepsis Mortality." Journal of Clinical and Translational Science 5, s1 (March 2021): 102. http://dx.doi.org/10.1017/cts.2021.662.
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ABSTRACT IMPACT: This work identifies host immune perturbations in sepsis mortality that suggests targets for a precision medicine paradigm in the host response to infection. OBJECTIVES/GOALS: To compare the early whole blood transcriptome during sepsis between 30-day survivors and non-survivors in the Intensive Care Unit (ICU), and to evaluate for pathway enrichment that might explain sepsis lethality. METHODS/STUDY POPULATION: We enrolled 162 sepsis patients in the first 24 hours of ICU admission, particularly targeting individuals requiring vasopressors. Peripheral whole blood was collected in PAXgene vacutainers. Isolated RNA was analyzed with Affymetrix Human Genome ST 2.0 microarray. Differential gene expression was performed with Bioconductor/R/limma using log2 fold-change +/-0.6 as a threshold for differential expression, and a Benjamini-Hochberg adjusted p-value <0.05 to declare significance. Functional gene enrichment was performed using the Gene Ontology (GO) database with PANTHER overrepresentation test (Fisher’s Exact) on all transcripts with adjusted p-value <0.05. Pathways analysis was performed with the Reactome Project using the raw fold change and significance data to identify dysregulated pathways. RESULTS/ANTICIPATED RESULTS: There were 58 non-survivors (36% mortality). We identified 39 genes as differentially expressed between sepsis non-survivors and survivors; 31 were upregulated in non-survivors and 8 had reduced expression. Several of the most overexpressed transcripts are neutrophil-specific, including LCN, MPO, OLF4M4, DEFA3, and DEFA4. A functional gene overrepresentation test further supports this finding, as the most enriched gene ontologies were neutrophil-mediated killing, neutrophil cytotoxicity, neutrophil extravasation, and respiratory burst, all demonstrating higher than 10-fold enrichment and FDR < 0.02. Pathway analysis of the peripheral blood transcriptome was notable for immune response derangement, specifically downregulation of both innate and adaptive immune pathways (FDR < 0.00001). DISCUSSION/SIGNIFICANCE OF FINDINGS: We identified increased expression of neutrophil-related genes in sepsis non-survivors, replicating candidates previously identified in pediatric sepsis mortality and ARDS. These immune perturbations in sepsis mortality may represent key targets for eventually employing precision medicine strategies in sepsis.
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Maillo, V., P. O'Gaora, J. P. Mehta, C. De Frutos, N. Forde, T. E. Spencer, P. Lonergan, and D. Rizos. "77 OVIDUCT - EMBRYO INTERACTIONS: TWO-WAY TRAFFIC OR A ONE-WAY STREET? TRANSCRIPTOMIC RESPONSE OF THE BOVINE OVIDUCT TO THE PRESENCE OF AN EMBRYO." Reproduction, Fertility and Development 26, no. 1 (2014): 152. http://dx.doi.org/10.1071/rdv26n1ab77.
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Despite clear evidence of a two-way interaction between the developing conceptus and the uterine endometrium in early pregnancy, the evidence for reciprocal cross-talk during the transit of the embryo through the oviduct is less clear. The aims were (1) to characterise the transcriptome of the bovine oviduct at the initiation of embryonic genome activation (EGA), (2) to examine the effect, if any, of the presence of an embryo on the oviduct transcriptome, and (3) to compare gene expression in the ampulla and isthmus of the oviduct ipsilateral to the corpus luteum. The oestrous cycles of cross-bred beef heifers were synchronized and those recorded in standing oestrus were randomly allocated to control group, nonbred (n = 7), or AI group (n = 11). All heifers were slaughtered on Day 3 after oestrus. The oviducts from each animal were isolated, straightened, and cut in half (ampulla and isthmus). Each portion was flushed with 500 μL of PBS to confirm the presence of an oocyte/embryo and was then opened and scraped longitudinally to obtain epithelial cells. Cells were snap-frozen in liquid nitrogen for microarray analysis. All recovered oocytes and embryos were located in the isthmus of the oviduct ipsilateral to the corpus luteum. The recovery rate was 72.7% (8/11) and 83.3% (5/6) for pregnant and cyclic animals, respectively. The stage of the recovered embryos was as follows: 4-cell stage (n = 1), 8-cell stage (n = 5), and 8–16 cell stage (n = 2), whereas in the cyclic group all recovered structures were unfertilized oocytes. The cells of the isthmus from ipsilateral and contralateral oviducts from 5 cyclic and 5 pregnant animals (8-cell embryos) and the ipsilateral ampulla cells from the pregnant animals were used for microarray analysis (Affymetrix Bovine ST array, Affymetrix, Santa Clara, CA, USA). Array data were analysed using BioConductor packages in R and custom CDF files downloaded from MBNI. Preprocessing of raw data was performed with RMA, and differential expression was assessed by linear modelling implemented in the limma package. Genes displaying P < 0.05 after adjustment for multiple testing were considered differentially expressed. A total of 18 809 probe sets were assessed for differential expression. Comparison of pregnant and cyclic oviduct epithelium revealed no significantly altered genes. However, comparison of the isthmus and ampulla of the ipsilateral oviduct in pregnant animals revealed 4011 (P < 0.05) and 2327 (P < 0.01) differentially expressed genes. Some of the gene ontologies involved in biological processes included fatty acid metabolism, cell adhesion, cell morphogenesis, cellular developmental process, and reproduction. In conclusion, we have characterised the transcriptome of the bovine oviduct epithelium at the initiation of embryonic genome activation on Day 3 post-oestrus in pregnant and cyclic heifers. Although large differences in gene expression were observed between the isthmus and ampulla, data suggest that the presence of an 8-cell embryo had no effect on the transcriptome of the cells of the isthmus, although a local effect at the precise position of the embryo cannot be ruled out.
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Ciccone, Samantha, Anna Pulliam, Xiaohong Li, Yue Si, Attilio Orazi, Grover C. Bagby, and D. Wade Clapp. "A Model of Clonal Evolution and Myelodysplasia (MDS) on Mice with Genetic Disruption of Both Fancc and Fancg." Blood 108, no. 11 (November 16, 2006): 2627. http://dx.doi.org/10.1182/blood.v108.11.2627.2627.
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Abstract Fanconi anemia (FA) is a rare inherited chromosomal instability syndrome characterized by bone marrow failure and a high relative risk of MDS. Eight FA proteins associate in a core nuclear complex and function at least in part to catalyze the monoubiquitination of the downstream target protein, FANCD2 in response to DNA damage. In this nuclear pathway the FA proteins are epistatic in the activation of FANCD2 since inactivation of any one of the eight FA proteins results in failure of FANCD2 monoubiquitination and hypersensitivity to cross-linking agents. Although biochemical studies have attributed additional survival signaling functions to the FA proteins, these functions have not been evaluated using a genetic model. Murine models of FA have been established using homologous recombination for gene disruption. Although all strains of knockout mice are hypersensitive to mitomycin c, none of the single gene knockout mice display bone marrow failure, MDS, or myeloid leukemia. Seeking to develop such a model, we utilized a genetic intercross to generate mice that harbor disruptions in both Fancc and Fancg. Genetic disruption of both Fancc and Fancg predispose Fancc−/−;Fancg −/− mice or recipients adoptively transferred with Fancc −/−; Fancg −/− hematopoietic stem cells to MDS analogous to the disease phenotype in FA patients as defined histologically and by cytogenetic analysis. Genome wide transcriptomal analysis and hierarchical clustering by genotypic group of bone marrow cells from wild type, single knockout, and double knockout mice (n=3 each) confirmed substantial differences between hematopoietic cells of Fancc, Fancg and double knockout (DKO) mice. Serial pairwise analysis and gene pattern analyses (GeneSifter) showed that of the 1190 genes expressed differentially (by a factor of >1.5, FDR adjusted p<0.05) in Fancc−/− marrow cells only 134 were differentially expressed in Fancg−/− cells. Of the 524 genes expressed differentially in Fancg−/− marrow compared to WT, 277 were not expressed differentially in Fancc−/− marrow compared to WT. In pairwise analysis of Fancc−/− vs. Fancg−/− gene expression, ontologies of those genes more highly expressed in Fancc −/− cells included responses to biotic stress, defense and immune response. The most over-represented ontological category of those genes more highly expressed in Fancg−/− cells was response to oxidative stress. Since these genes are not epistatic in regards to the hematopoietic phenotype, and the transcriptomal consequences of their loss-of-function in marrow cells are significantly different, this genetic model confirms that the Fancc and Fancg proteins are multi-functional. Transcriptosomal analyses were conducted on DKO mice that contained MDS and DKO mice with no overt disease. The transcriptome of DKO marrow cells was unique in that 152 suppressed and 687 activated gene products relative to WT samples were not found in either Fancc−/− or Fancg−/− samples. Furthermore, there are distinct transcriptomal differences between the DKO mice with MDS and those that do not have MDS. These data suggest that some of these changes may be adaptive and involved in the molecular pathogenesis of MDS. The DKO model provides the first preclinical platform to systematically evaluate the molecular pathogenesis of bone marrow failure and myelodysplasia in the setting of Fanconi anemia.
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Douglas, Suvi, Atte Lahtinen, Jessica Koski, Lilli Leimi, Mikko A. Keränen, Kimmo Porkka, Caroline A. Heckman, Kirsi Jahnukainen, Outi Kilpivaara, and Ulla Wartiovaara-Kautto. "Germline Gene Aberrations Are Common in High-Risk Adult and Pediatric Acute Lymphoblastic Leukemia Patients." Blood 134, Supplement_1 (November 13, 2019): 1472. http://dx.doi.org/10.1182/blood-2019-126657.
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Personalized medicine involves a comprehensive analysis of factors affecting a disease. Family history is an important but not a definitive indicator of inherited predisposition to malignancy and thus studying the germline gene aberrations alongside somatic variants is warranted. The significance of germline predisposition has been increasingly recognized in acute myeloid leukemia and is noted in the latest WHO classification.1,2,3Despite the recent progress in acute lymphoblastic leukemia (ALL) therapies, many adult patients with ALL still do poorly and there is a need for new biomarkers and therapy targets. The aim of our study was to identify and determine the frequency of germline mutations in known ALL genes, to discover new genes associated with ALL predisposition, and to compare the germline genetic background and respective consequences of pediatric and adult high-risk ALL. We examined exome sequencing data from biobanked samples of adult (50) and pediatric (68) patients with high-risk ALL (Finnish Hematological Registry and Biobank - FHRB, and clinical repositories). First, a candidate-gene analysis consisted of 92 genes previously associated with germline predisposition to ALL or syndromes predisposing to ALL. Variants with minor allele frequency of <0.01 in the Genome Aggregation Database were considered. Missense variants were considered significant if ≥2/3 algorithms (CADD, DANN, Revel) classified it as pathogenic. We also reviewed literature, public databases and the American College of Medical Genetics classification (ACMG) in filtering the variants. Clinical characteristics of the patients were retrieved from hospital records and the Finnish Hematological Registry. Second, an unbiased approach was applied to find novel genes predisposing to ALL by checking pathogenic variants in the same gene in at least two (adult/pediatric) patients and filtering by gene ontologies DNA repair, cell cycle, and lymphocyte differentiation; and by COSMIC cancer census genes. In both analyses, only statistically significantly more common variants in our series compared to normal population were included. We also conducted a mutational signature analysis on the samples. Our analysis (Table 1) demonstrates that 8% of adult and 10% pediatric study patients carried a pathogenic or likely pathogenic mutation in their germline in known ALL predisposing genes. All these mutations were at least 30-fold more frequent in our study series compared with allele frequencies in the normal population (p<0.05). Four pediatric patients were identified to suffer from undiagnosed syndromes, which predispose to ALL (Li-Fraumeni and Noonan syndromes). We also found recurring aberrations in new genes with biological relevance to ALL, such as MUTYH and IL21R, potentially associating with ALL predisposition. Final results of the mutational signature analyses are pending. In conclusion, our results emphasize that germline predisposition is not rare among high-risk ALL patients. In addition to pediatric ALL patients, we show contributing germline variants also in adult patients. At least 20% of the adult ALL patients are transplanted and a potential germline basis of the disease should be considered when choosing the donor. Our analysis also reveals new information on the biology of high-risk ALL and may contribute to the future studies seeking for therapy options in this challenging patient category. Despite the anxiety that acknowledging inheritable factors may cause in patients, families, and caretakers, we encourage clinicians to integrate carefully interpreted germline data into patient care. References 1. Wartiovaara-Kautto U et al. Germline alterations in a consecutive series of acute myeloid leukemia. Leukemia. 2018. 2. Arber DA et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016. 3. Tawana K et al. Universal genetic testing for inherited susceptibility in children and adults with myelodysplastic syndrome and acute myeloid leukemia : are we there yet? Leukemia. 2018. Disclosures Porkka: Daiichi Sankyo: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy, Research Funding. Heckman:Celgene: Research Funding; Novartis: Research Funding; Oncopeptides: Research Funding; Orion Pharma: Research Funding.
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Bal, Susan, Saulius K. Girnius, Daniel T. Starczynowski, Heather J. Landau, and Kwangmin Choi. "Genomic Landscape of Multiple Myeloma with Elevated Lactate Dehydrogenase." Blood 132, Supplement 1 (November 29, 2018): 470. http://dx.doi.org/10.1182/blood-2018-99-115523.
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Abstract Background Multiple Myeloma (MM) is a heterogeneous disorder of clonal plasma cells. Genetic aberrations are important in heterogeneity and have prognostic and perhaps therapeutic implications. Elevated Lactate Dehydrogenase (LDH) has been associated with drug resistance and short survival. The biologic basis of this observation is uncertain. In this study, we sought to define the genomic landscape of MM patients with high LDH to understand pathophysiology and identify therapeutic targets. Methods Utilizing data from the Multiple Myeloma Research Foundation (MMRF) CoMMpass database (IA12), which includes over 1000 newly-diagnosed MM patients with enriched tumor and matched constitutional samples analyzed using whole genome/exome and RNA sequencing (RNA-seq), we identified a cohort of patients with baseline LDH values and RNA-seq data available for inclusion. High LDH was defined as LDH greater than upper limit of normal (>4.68 microkatals/L). The RNA-seq data was analyzed to predict differentially expressed genes, then gene set enrichment analyses using GSEA and ClueGO were performed to assess for highly enriched pathways and gene ontologies (GO). Thereafter we analyzed to see if there was an enrichment of high risk cytogenetic changes within the high LDH group. Overall survival (OS) was estimated by Kaplan Meier method and a log-rank test. Results We identified 871 patients who met inclusion criteria (High LDH N=143; Normal LDH N=728). LDH continued to remain a poor prognostic factor consistent with prior literature, with median survival 660 days vs 795 days (p=0.02852). Among the patients who underwent autologous transplant (N=385), LDH continued to be associated with poor prognosis with median overall survival (800.5 vs 878.8 days, p=0.01933). Patient characteristics and other clinical variables are submitted separately (Bal et al. ASH 2018). There was no difference in the non-synchronous mutations between the two groups when stratified by baseline LDH levels. To assess for enrichment of the known cytogenetic changes, we performed the hypergeometric test on the samples with both baseline LDH and cytogenetic information. Del(17p13) was significantly enriched (p=0.011) in the high LDH subset compared to normal LDH. (18.48% vs 10.36%) while there was no statistically significant difference in the presence of t(4;14) (p=0.16, 15.65% vs 11.8%) and t(14;16) (p=0.21, 6% vs 4%). GSEA detected 572 gene sets significantly up-regulated in the high LDH group (FDR q < 25%) compared to those with normal LDH including genes involved in the processing of capped intron containing pre-mRNA, recruitment of mitotic centrosome proteins and complexes, mRNA splicing and the proliferation signal in solid tumors leading to metastatic potential. No significantly down-regulated gene set was detected at same significance level. The ClueGO analysis using two separate sets of up-regulated DEGs (fold > 1.5x or fold > 2x, FDR < 0.05 for both) revealed upregulated molecular signatures in similar functional categories as the GSEA in patients with high LDH. The first gene set (fold > 1.5x) showed significant enrichments (p < 0.005) in cell cycle-related pathways, including microtubule cytoskeleton organization, polo-like kinase mediated events, regulation of cell cycle phase transition, regulation of nuclear division and kinesins which provide the myeloma cells with a proliferative advantage. The second gene set (fold > 2x) was strongly associated (p < 0.005) with sympathetic nervous system development (NELL2, NTRK1, and SOX11), collagen biosynthesis (ADAMTS family) and O-linked glycosylation (COL11A family). These genes play a role in lymphocyte differentiation, anti-apoptosis, local invasion, and metastasis. Conclusion Elevated LDH was confirmed as a poor prognostic factor in the MMRF CoMMpass cohort. Overrepresentation of Del17p in this population likely contributes to poor prognosis. In MM, the bone marrow microenvironment is crucial in the differentiation, migration, proliferation and survival. Overexpression of proteolytic and cell adhesion signatures, evasion/suppression of host immune system along with hyper-proliferative signatures via cell division and RTK pathways in MM patients with high LDH offers insight into the aggressive disease in these patients. Targeting tumor microenvironment and RTK pathways may provide novel therapeutic strategies in this subtype of MM Figure. Figure. Disclosures No relevant conflicts of interest to declare.
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Woolthuis, Carolien M., Hendrik JM de Jonge, Annet Z. Vos, Andre B. Mulder, Eva van den Berg, P. M. Kluin, Karen van der Weide, et al. "Gene Expression Profiling In Leukemic Stem Cell-Enriched AML CD34+ Cell Fraction Identifies Target Genes That Predict Prognosis In Normal Karyotype AML." Blood 116, no. 21 (November 19, 2010): 952. http://dx.doi.org/10.1182/blood.v116.21.952.952.
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Abstract Abstract 952 Acute myeloid leukemia (AML) is clinically, cytogenetically and molecularly a heterogeneous disease which makes it challenging to classify it properly. In recent years major advances have been achieved in predicting outcome. However, there is still need for more powerful and independent prognostic factors that can guide treatment decisions, especially for the large subgroup of patients presenting with normal karyotype AML. In order to improve the identification of prognostic markers, gene expression studies have been performed. However, most of these studies have analyzed the mononuclear cell fraction. So, very little has been revealed about gene expression programs that drive leukemic transformation in the small population of leukemic stem cells (LSCs). Although considerable heterogeneity appears to exist in the phenotype of LSCs, CD34 is uniformly expressed and LSCs have been found to reside in the CD34+ compartment in the vast majority of leukemias. In the present study AML CD34+-specific gene expression profiles were indentified and used to distinguish prognostically relevant target genes in normal karyotype AML. AML mononuclear cells (n=46) were sorted in CD34+ and CD34- subfractions and genome-wide expression analysis was performed using Illumina BeadChip Arrays. AML CD34+ and CD34- gene expression was compared to a large group of normal CD34+ bone marrow cells (n=31). Unsupervised hierarchical clustering analysis showed that CD34+ AML samples belonged to a distinct cluster compared to normal bone marrow and that in 61% of the cases the AML CD34+ transcriptome did not cluster together with the paired CD34- transcriptome. These data indicate that in the majority of AML cases the leukemic stem cell-enriched CD34+ gene expression profile is quite distinct from the leukemic CD34- compartment. GO analysis revealed that common differences in gene expression between CD34+ and CD34- groups were particularly enriched for genes that were associated with T-cells and erythropoiesis. This association with a more committed phenotype was found in all AML samples and not just in those samples where CD34+ and CD34- transcriptomes did not cluster together. Among the GO-ontologies representing the differentially expressed genes between CD34+ AML versus CD34+ normal bone marrow cells were gene sets related to DNA damage and a number of mitotic and metabolic processes. A top 50 of AML CD34+-specific genes was selected by comparing the AML CD34+ transcriptome with the AML CD34- and CD34+ normal bone marrow transcriptomes. The prognostic relevance of these 50 genes was assessed using univariate cox regression analyses between the continuous transcript levels of these 50 genes and overall survival (OS) in a large series of normal karyotype AML (n=163) (Metzeler et al. Blood 2008). The findings were validated in another independent cohort of 218 normal karyotype AML patients (Valk et al. NEJM 2004). Interestingly, higher transcript levels of three CD34+ AML specific genes, i.e. ankyrin repeat domain 28 (ANKRD28), guanine nucleotide binding protein, alpha 15 (GNA15) and UDP-glucose pyrophosphorylase 2 (UGP2) were associated with a significant poorer OS in both cohorts (p<0.01). For the cohort of 218 normal karyotype AML patients also event free survival (EFS) data were available for further analyses. A significant association between the continuous transcript levels of ANKRD28, GNA15 and UGP2 with poor EFS was evident. Also for the sum of expression of ANKRD28, GNA15 and UGP2 higher transcript levels were strongly associated with poorer OS (p=0.007) and EFS (p=0.006) in the cohort of 218 normal karyotype AML. Similar results were obtained in the cohort of 163 normal karyotype AML patients for OS (p<0.001). Importantly, the prognostic value of the continuous transcript levels of these three genes was independent from the well known risk factors FLT3-ITD, NPM1c+ and CEBPA mutation status as determined by a multivariate analysis in the cohort of 218 normal karyotype AML patients. In conclusion, by microarray analysis of the leukemic stem cell-enriched AML CD34+ cell fraction novel insight was obtained in gene expression programs that are potentially associated with leukemic stem cell self-renewal and transformation. Moreover, the identified new gene expression profiles were shown to have prognostic relevance in normal karyotype AML independent of well known risk factors. Disclosures: No relevant conflicts of interest to declare.
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Petegrosso, Raphael, Sunho Park, Tae Hyun Hwang, and Rui Kuang. "Transfer learning across ontologies for phenome–genome association prediction." Bioinformatics, October 22, 2016, btw649. http://dx.doi.org/10.1093/bioinformatics/btw649.
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