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Journal articles on the topic 'Genetic variation'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 July 2025

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1

Ansari, K. I., N. Palacios, C. Araya, T. Langin, D. Egan, and F. M. Doohan. "Genetic variation between Colletotrichum lindemuthianum isolates." Plant Protection Science 38, SI 2 - 6th Conf EFPP 2002 (December 31, 2017): 378–80. http://dx.doi.org/10.17221/10496-pps.

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We characterized the genetic diversity of seventy-three C. lindemuthianum isolates collected from 10 different countries by Amplified Fragment Length Polymorphism (AFLP) analysis. The results of this research highlighted the fact that there is huge variation in the genetic diversity between isolates from different countries. The molecular profile of the isolates showed correlation with geographic origin of the isolates.

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2

Alex O. Sierra-Rosales, Katya I. Rosales-Rosales, Jesús F. Salas-Montes, Oziel A. Vidales-Simental, and Brissia Lazalde. "Genetic variants and influence in cognitive diseases." GSC Advanced Research and Reviews 21, no. 3 (December 30, 2024): 062–68. https://doi.org/10.30574/gscarr.2024.21.3.0456.

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The relationship between genetic variation and cognitive ability has become a central focus in modern genetics and neuroscience. Cognitive functions are complex traits influenced by both genetic and environmental factors. Over the past decades, advances in genomic technologies, such as genome-wide association studies (GWAS), have revealed a multitude of genetic variants associated with cognitive performance. One of the most studied types of genetic variation are single nucleotide polymorphisms (SNPs), which represent the most common form of variation in the human genome. Evidence indicates that copy number variations (CNVs) play an important role along with the SNPs.

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3

Bedge, Kiran, and Pratima Salunkhe. "Population Genetics : A Review." International Journal of Scientific Research in Science and Technology 11, no. 2 (April 20, 2024): 746–48. http://dx.doi.org/10.32628/ijsrst24112109.

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Genetics is the study of genes and genetic variations alongwith the hereditary characteristics of an organism. Genetics is a central pillar of biology. It overlaps with other areas, such as: Agriculture, Medicine, Biotechnology. Genetics involves studying: Gene structure and function Gene variation and changes How genes affect health, appearance, and personality. Population genetics studies genetic variation within and among populations, based on the Hardy-Weinberg law, which remains constant in large populations with random mating and minimal mutation, selection, and migration.

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4

Paaby, Annalise, and Greg Gibson. "Cryptic Genetic Variation in Evolutionary Developmental Genetics." Biology 5, no. 2 (June 13, 2016): 28. http://dx.doi.org/10.3390/biology5020028.

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5

Ellsworth, Katarzyna A., Irene Moon, Bruce W. Eckloff, Brooke L. Fridley, Gregory D. Jenkins, Anthony Batzler, Joanna M. Biernacka, et al. "FKBP5 genetic variation." Pharmacogenetics and Genomics 23, no. 3 (March 2013): 156–66. http://dx.doi.org/10.1097/fpc.0b013e32835dc133.

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6

Ryan, Stephen G. "Human Genetic Variation." Pharmacogenomics 3, no. 1 (January 2002): 9–11. http://dx.doi.org/10.1517/14622416.3.1.9.

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7

Gibson, Greg, and Laura K. Reed. "Cryptic genetic variation." Current Biology 18, no. 21 (November 2008): R989—R990. http://dx.doi.org/10.1016/j.cub.2008.08.011.

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8

Vihinen, Mauno. "Individual Genetic Heterogeneity." Genes 13, no. 9 (September 10, 2022): 1626. http://dx.doi.org/10.3390/genes13091626.

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Genetic variation has been widely covered in literature, however, not from the perspective of an individual in any species. Here, a synthesis of genetic concepts and variations relevant for individual genetic constitution is provided. All the different levels of genetic information and variation are covered, ranging from whether an organism is unmixed or hybrid, has variations in genome, chromosomes, and more locally in DNA regions, to epigenetic variants or alterations in selfish genetic elements. Genetic constitution and heterogeneity of microbiota are highly relevant for health and wellbeing of an individual. Mutation rates vary widely for variation types, e.g., due to the sequence context. Genetic information guides numerous aspects in organisms. Types of inheritance, whether Mendelian or non-Mendelian, zygosity, sexual reproduction, and sex determination are covered. Functions of DNA and functional effects of variations are introduced, along with mechanism that reduce and modulate functional effects, including TARAR countermeasures and intraindividual genetic conflict. TARAR countermeasures for tolerance, avoidance, repair, attenuation, and resistance are essential for life, integrity of genetic information, and gene expression. The genetic composition, effects of variations, and their expression are considered also in diseases and personalized medicine. The text synthesizes knowledge and insight on individual genetic heterogeneity and organizes and systematizes the central concepts.

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9

Varvio, Sirkka-Liisa, Ranajit Chakraborty, and Masatoshi Nei. "Genetic variation in subdivided populations and conservation genetics." Heredity 57, no. 2 (October 1986): 189–98. http://dx.doi.org/10.1038/hdy.1986.109.

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10

Korpelainen, Helena, and Noris Salazar Allen. "Genetic variation in three species of epiphytic Octoblepharum (Leucobryaceae)." Nova Hedwigia 68, no. 3-4 (June 2, 1999): 281–90. http://dx.doi.org/10.1127/nova.hedwigia/68/1999/281.

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11

Gooding, R. H. "Genetic variation in arthropod vectors of disease-causing organisms: obstacles and opportunities." Clinical Microbiology Reviews 9, no. 3 (July 1996): 301–20. http://dx.doi.org/10.1128/cmr.9.3.301.

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An overview of the genetic variation in arthropods that transmit pathogens to vertebrates is presented, emphasizing the genetics of vector-pathogen relationships and the biochemical genetics of vectors. Vector-pathogen interactions are reviewed briefly as a prelude to a discussion of the genetics of susceptibility and refractoriness in vectors. Susceptibility to pathogens is controlled by maternally inherited factors, sex-linked dominant alleles, and dominant and recessive autosomal genes. There is widespread interpopulation (including intercolony) and temporal variation in susceptibility to pathogens. The amount of biochemical genetic variation in vectors is similar to that found in other invertebrates. However, the amount varies widely among species, among populations within species, and temporally within populations. Biochemical genetic studies show that there is considerable genetic structuring of many vectors at the local, regional, and global levels. It is argued that genetic variation in vectors is critical in understanding vector-pathogen interactions and that genetic variation in vectors creates both obstacles to and opportunities for application of genetic techniques to the control of vectors.

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12

Biros, Erik, Mirko Karan, and Jonathan Golledge. "Genetic Variation and Atherosclerosis." Current Genomics 9, no. 1 (March 1, 2008): 29–42. http://dx.doi.org/10.2174/138920208783884856.

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13

Phuong Nhung, Vu, Nguyen Dang Ton, Nong Van Hai, and Nguyen Hai Ha. "Genetic variation of pharmacogenes." Vietnam Journal of Biotechnology 18, no. 3 (September 30, 2020): 393–416. http://dx.doi.org/10.15625/1811-4989/18/3/14972.

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Patient specific response against a particular drug could be affected by various factors, in which genetic factors are the most crucial contributor. The genetic variability in pharmacogenes might result in variable drug response of individuals, which in turn can lead to unexpected treatment outcomes or even adverse drug reactions. The pharmacogenes include of genes that encode for several proteins which divided into 3 main functional categories: drug metabolizing enzymes, drug transporters and receptor-drug targets. Genetic variants of genes coding for drug metabolizing enzymes phase I (CYP450), phase II (GSTs, UGT, TPMT) as well as drug transporters (ABC, SLCO) of numerous populations in global have been extensively studied. Among these, SNPs are the major contributor behind variants of pharmacogenes along with copy number variants. Furthermore, the clinical impact on drug response of common variants belonging to several important pharmacogenes has been well understood. On the other hand, information on the variant spectrum of genes encoding for receptor-drug targets as well as their physiological effects have remained limited. In recent years, along with computational methods, next generation sequencing technologies had been developed tremendously. These high throughput methods had greatly promoted the field of pharmacogenetic research through providing ability to detect novel and rare genetic variants. The data on genetic variants of pharmacogenes would be valuable for determining the responder and non-responder to medication during treatment. These are also significant basis which play a vital role in development of the field of optimizing drug dose for individuals and personalized medicine in the future.

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14

Childs, B. "Genetic variation and nutrition." American Journal of Clinical Nutrition 48, no. 6 (December 1, 1988): 1500–1504. http://dx.doi.org/10.1093/ajcn/48.6.1500.

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15

Vohl, Marie-Claude, Mostafa Badr, and Stefan Wieczorek. "Genetic Variation of PPARs." PPAR Research 2009 (2009): 1. http://dx.doi.org/10.1155/2009/189091.

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16

Zahn, Laura M. "Genetic background affects variation." Science 366, no. 6464 (October 24, 2019): 440.15–442. http://dx.doi.org/10.1126/science.366.6464.440-o.

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17

Simopoulos, Artemis P. "Genetic variation and nutrition." Food Reviews International 12, no. 2 (May 1996): 273–77. http://dx.doi.org/10.1080/87559129609541078.

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18

Simopoulos, Artemis P. "Genetic Variation and Nutrition." Nutrition Reviews 57, no. 5 (April 27, 2009): 10–19. http://dx.doi.org/10.1111/j.1753-4887.1999.tb01783.x.

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19

Chen, J. "Genetic Variation AmongXylella fastidiosaStrains." Phytopathology 82, no. 9 (1992): 973. http://dx.doi.org/10.1094/phyto-82-973.

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20

Lee, Gilho. "Genetic Variation inMycoplasma genitalium." Urogenital Tract Infection 12, no. 2 (2017): 65. http://dx.doi.org/10.14777/uti.2017.12.2.65.

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21

SIMOPOULOS, ARTEMIS P. "Genetic Variation and Nutrition." Nutrition Today 30, no. 4 (July 1995): 157–67. http://dx.doi.org/10.1097/00017285-199507000-00005.

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22

SIMOPOULOS, ARTEMIS P. "Genetic Variation and Nutrition." Nutrition Today 30, no. 5 (September 1995): 194–206. http://dx.doi.org/10.1097/00017285-199509000-00004.

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23

Gibson, Greg, and Ian Dworkin. "Uncovering cryptic genetic variation." Nature Reviews Genetics 5, no. 9 (September 2004): 681–90. http://dx.doi.org/10.1038/nrg1426.

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24

ARNAUD, CELIA. "PROBING HUMAN GENETIC VARIATION." Chemical & Engineering News 88, no. 44 (November 2010): 8. http://dx.doi.org/10.1021/cen-v088n044.p008a.

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25

Thorne, A., M. Wolpoff, and R. Eckhardt. "Genetic variation in Africa." Science 261, no. 5128 (September 17, 1993): 1507–8. http://dx.doi.org/10.1126/science.8372344.

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26

Runyan, T. J. "Genetic Variation and Nutrition." Journal of the American College of Nutrition 11, no. 1 (February 1992): 102–3. http://dx.doi.org/10.1080/07315724.1992.10738191.

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27

Larkin, Marilynn. "Genetic variation creatively celebrated." Lancet 358, no. 9278 (July 2001): 341. http://dx.doi.org/10.1016/s0140-6736(01)05475-7.

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28

BORMAN, STU. "MAPPING HUMAN GENETIC VARIATION." Chemical & Engineering News 83, no. 8 (February 21, 2005): 13. http://dx.doi.org/10.1021/cen-v083n008.p013.

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29

Austin, R. B. "Genetic variation in photosynthesis." Journal of Agricultural Science 112, no. 3 (June 1989): 287–94. http://dx.doi.org/10.1017/s0021859600085737.

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30

Owen, J. B. "Genetic variation and nutrition." Clinical Nutrition 10, no. 1 (February 1991): 61–62. http://dx.doi.org/10.1016/0261-5614(91)90086-r.

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31

Doi, Kazuyuki, Hideshi Yasui, and Atsushi Yoshimura. "Genetic variation in rice." Current Opinion in Plant Biology 11, no. 2 (April 2008): 144–48. http://dx.doi.org/10.1016/j.pbi.2008.01.008.

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32

Curtsinger, James W., Hidenori H. Fukui, Aziz A. Khazaeli, Andrew Kirscher, Scott D. Pletcher, Daniel E. L. Promislow, and Marc Tatar. "Genetic Variation and Aging." Annual Review of Genetics 29, no. 1 (December 1995): 553–75. http://dx.doi.org/10.1146/annurev.ge.29.120195.003005.

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33

Stower, Hannah. "Explosive human genetic variation." Nature Reviews Genetics 14, no. 1 (December 18, 2012): 5. http://dx.doi.org/10.1038/nrg3390.

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34

Barton, Nicholas H., and Peter D. Keightley. "Understanding quantitative genetic variation." Nature Reviews Genetics 3, no. 1 (January 2002): 11–21. http://dx.doi.org/10.1038/nrg700.

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35

Nevo, Eviatar, and Avigdor Beiles. "Genetic variation in nature." Scholarpedia 6, no. 7 (2011): 8821. http://dx.doi.org/10.4249/scholarpedia.8821.

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36

Stewart, Jill Campbell, and Steven C. Cramer. "Genetic Variation and Neuroplasticity." Journal of Neurologic Physical Therapy 41 (July 2017): S17—S23. http://dx.doi.org/10.1097/npt.0000000000000180.

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37

Son, Joonmo, and John Wilson. "Genetic Variation in Volunteerism." Sociological Quarterly 51, no. 1 (February 1, 2010): 46–64. http://dx.doi.org/10.1111/j.1533-8525.2009.01167.x.

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38

Vijg, Jan. "Detecting Individual Genetic Variation." Nature Biotechnology 13, no. 2 (February 1995): 137–39. http://dx.doi.org/10.1038/nbt0295-137.

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39

Vigilant, Linda, and Brenda J. Bradley. "Genetic variation in gorillas." American Journal of Primatology 64, no. 2 (2004): 161–72. http://dx.doi.org/10.1002/ajp.20070.

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40

Amini, Dara Suci, and Afifatul Achyar. "Analysis of Genetic Variation of MatK Gene Sequences in Ammothamnus lehmannii NCBI Popset 2440747918 Using In Silico RFLP." Tropical Genetics 3, no. 2 (November 29, 2023): 53–59. http://dx.doi.org/10.24036/tg.v3i2.49.

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Genetic diversity or genetic variation is variation that occurs in an organism due to differences in the sequence of nucleotide bases (adenine, thymine, guanine and cytosine) that form DNA in cells. Variation genetics can be studied in silico using available gene sequences in the NCBI genbank database. This study used the MatK (Maturase-K) gene sequence with the identity number Popset 2440747918 which was downloaded in fasta format from NCBI . Then screening of restriction enzyme candidates was carried out to determine the restriction enzymes prior to in silico RFLP. The restriction enzyme selected from the screening was the restriction enzyme HindIII which has the recognition site A'AGC_T. The results obtained from 79 samples of DNA sequences, 76 samples were cut and 3 samples were not. And found three allele variations with the percentage of the presence of fragments A1 (86.07%), A2 (10.12%) and A3 (3.79%). The percentage values and frequencies of these A1, A2 and A3 alleles indicate a low level of genetic variation.

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41

Hill, William G. "Understanding and using quantitative genetic variation." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1537 (January 12, 2010): 73–85. http://dx.doi.org/10.1098/rstb.2009.0203.

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Quantitative genetics, or the genetics of complex traits, is the study of those characters which are not affected by the action of just a few major genes. Its basis is in statistical models and methodology, albeit based on many strong assumptions. While these are formally unrealistic, methods work. Analyses using dense molecular markers are greatly increasing information about the architecture of these traits, but while some genes of large effect are found, even many dozens of genes do not explain all the variation. Hence, new methods of prediction of merit in breeding programmes are again based on essentially numerical methods, but incorporating genomic information. Long-term selection responses are revealed in laboratory selection experiments, and prospects for continued genetic improvement are high. There is extensive genetic variation in natural populations, but better estimates of covariances among multiple traits and their relation to fitness are needed. Methods based on summary statistics and predictions rather than at the individual gene level seem likely to prevail for some time yet.

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42

Vyhnánek, T., J. Bednář, S. Helánová, L. Nedomová, and J. Milotová. "Use of Prolamin Polymorphism to Describe Genetic Variation in a Collection of Barley Genetic Resources." Czech Journal of Genetics and Plant Breeding 39, No. 2 (November 23, 2011): 45–50. http://dx.doi.org/10.17221/3720-cjgpb.

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&nbsp;The polymorphism of prolamin storage proteins was studied in seed samples of 20 historical cultivars of&nbsp; &nbsp;spring barley (Hordeum vulgare L.) of Czech and Slovak origin, using polyacrylamide gel electrophoresis (PAGE). Only two samples were uniform. Most heterogeneity of prolamin patterns was observed in the oldest accessions. By means of a prolamin identity index it was possible to distinguish sister lines from admixtures within the seed samples. The obtained spectra will be used as additional descriptors for the spring barley core collection of the Collection of Genetic Resources of the Agricultural Research Institute Kroměř&iacute;ž, Ltd. &nbsp;

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43

Mulyasari, Mulyasari, Dinar Tri Soelistyowati, Anang Hari Kristanto, and Irin Iriana Kusmini. "KARAKTERISTIK GENETIK ENAM POPULASI IKAN NILEM (Osteochilus hasselti) DI JAWA BARAT." Jurnal Riset Akuakultur 5, no. 2 (November 25, 2016): 175. http://dx.doi.org/10.15578/jra.5.2.2010.175-182.

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Penelitian karakteristik genetik populasi ikan nilem, Osteochilus hasselti di Jawa Barat dilakukan untuk mendapatkan data base sebagai langkah awal dalam melaksanakan program pemuliaan guna mempertahankan dan meningkatkan produksi dari ikan nilem di Jawa Barat. Tujuan penelitian ini adalah melakukan identifikasi genetik ikan nilem menggunakan metode RAPD dan menelusuri keragaman intra dan inter-populasi ikan nilem, Osteochilus hasselti di sentra budidaya yang terdapat di daerah Jawa Barat. Berdasarkan hasil penelitian, populasi Sumedang secara genetis memiliki keragaman paling tinggi dibandingkan dengan populasi lainnya serta alel spesifik yang tidak ditemukan pada populasi lain (1.100 bp). Sedangkan Sukabumi memiliki keragaman genetik dan jumlah alel yang paling rendah. Hubungan inter-populasi ikan nilem hijau di Jawa Barat tidak berbeda nyata di mana jarak genetik enam populasi ikan nilem tersebut berkisar antara 0,0153-0,1392.Research on genetic variation was done to conduct breeding program as the effort to maintain and increase the production of nilem carp fish at West Java. The aim of this study was to identify nilem carp genetically and to estimate the variation of the intra and inter population of nilem carp fish from West Java using RAPD methods. The result showed that Sumedang population had the highest genetic variation and had specific allele that cannot be found at other population (1,100 bp). But in contrast Sukabumi population had the lowest genetic variation and allele number. The inter- population relationship among fish from West Java were not significantly different. Genetic distance among population were between 0.0153-0.1392.

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44

Ghai, Roma, Ashu Mittal, Deepali Pandey, Md Shamshir Alam, Shikha Kaushik, Pasha Ishtiyaq, Yogita Kaushik, and Shardendu Kumar Mishra. "Role of Personalized Medicine in Clinical Practice: An Overview of Current and Future Perspectives." Biomedical and Pharmacology Journal 17, no. 4 (December 30, 2024): 2111–33. https://doi.org/10.13005/bpj/3011.

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Drug administration at similar doses in patients can often lead to various clinical responses. It has been hypothesized that genetics primarily accounts for variation in drug efficacy and toxicity in individuals. Personalized medicine has been a breakthrough achieved by the Human Genome Project which contributes to enhancing quality-based patient care. It deals with the customization of medication considering the distinct genetic and proteomic data that underpins the originality of every patient and every instance of therapeutic intervention. Many cases have shown that inter-individual differences related to drug response can be traced to genetic polymorphism in the gene alleles that codes for metabolizing enzymes, drug transporters, and genetic variations in a person’s Major Histocompatibility Complex (MHC). So, the paper throws an insight into epidemiological variations due to genetics, variations in response based on metabolic parameters, and transporters. It also covers genetic variation related to immune-related drug toxicities. Pharmacogenetic testing plays an important role in achieving more precise personalized therapeutics for better public health. The paper discusses various tests for human leukocyte antigen variants and metabolic variants. Every technology inclusion comes with advantages and limitations so personalized medicine also faces certain challenges which are discussed in the paper. Once personalized medicine is used in clinical settings, patients will be able to receive the best medications for them based on their unique genetic and protein profiles.

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45

Hutami, Sri, Ika Mariska, and Yati Supriati. "Peningkatan Keragaman Genetik Tanaman melalui Keragaman Somaklonal." Jurnal AgroBiogen 2, no. 2 (August 5, 2016): 81. http://dx.doi.org/10.21082/jbio.v2n2.2006.p81-88.

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<p class="p1">High genetic variability’s are important factors in the development of new crop varieties. <em>In vitro </em>techniques are applicable for development of crop variability that is not found in the gene pool. One of the <em>in vitro </em>techniques that can be used for this purpose is the somaclonal variation technique. Somaclonal variation may be derived from genetic variations in explants and genetic variations in tissue cultures. Variations in the explant may be obtained from cell mutations or polysomic mutations of a certain tissue. Genetic variations in tissue culture may be caused by ploidy of chromosomes (endomitosis fusion), changes of chromosom structures (crossings), as well as changes of genes and cytoplasms. Changes of genetic characters may be improved if anorganic compound was added into the medium. To improve the plant tolerances to biotic or abiotic factors, selection components may also be added to the medium. Research results showed that somaclonal variation in tissue culture can improve genetic variations in plants. The variation produced in tissue culture provide chances to develop new plant genotipes. Many selection components, such as Gamma-ray irradiation, Al contents and low pH, pure toxin or filtrate, polyethylene glycol (PEG), and plant growth regulators can be used to improve somaclonal variations in many plants to produce new genotipes.</p>

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46

Wagner, Günter P. "Evolutionary Genetics: The Nature of Hidden Genetic Variation Unveiled." Current Biology 13, no. 24 (December 2003): R958—R960. http://dx.doi.org/10.1016/j.cub.2003.11.042.

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47

Wagner, G.-P. "Evolutionary Genetics: The Nature of Hidden Genetic Variation Unveiled." Current Biology 13 (June 5, 2003): R958—R960. https://doi.org/10.1016/j.cub.2003.11.042.

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48

Sanders, Ian R. "Intraspecific genetic variation in arbuscular mycorrhizal fungi and its consequences for molecular biology, ecology, and development of inoculum." Canadian Journal of Botany 82, no. 8 (August 1, 2004): 1057–62. http://dx.doi.org/10.1139/b04-094.

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It has been known for some time that different arbuscular mycorrhizal fungal (AMF) taxa confer differences in plant growth. Although genetic variation within AMF species has been given less attention, it could potentially be an ecologically important source of variation. Ongoing studies on variability in AMF genes within Glomus intraradices indicate that at least for some genes, such as the BiP gene, sequence variability can be high, even in coding regions. This suggests that genetic variation within an AMF may not be selectively neutral. This clearly needs to be investigated in more detail for other coding regions of AMF genomes. Similarly, studies on AMF population genetics indicate high genetic variation in AMF populations, and a considerable amount of variation seen in phenotypes in the population can be attributed to genetic differences among the fungi. The existence of high within-species genetic variation could have important consequences for how investigations on AMF gene expression and function are conducted. Furthermore, studies of within-species genetic variability and how it affects variation in plant growth will help to identify at what level of precision ecological studies should be conducted to identify AMF in plant roots in the field. A population genetic approach to studying AMF genetic variability can also be useful for inoculum development. By knowing the amount of genetic variability in an AMF population, the maximum and minimum numbers of spores that will contain a given amount of genetic diversity can be estimated. This could be particularly useful for developing inoculum with high adaptability to different environments.Key words: arbuscular mycorrhizas, symbiosis, genomics, genetic diversity, population genetics, evolutionary ecology.

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49

Malau, Sabam, and And Samse Pandiangan. "Morphological Variation in Arabica Coffee (Coffea arabica L.) Growing in North Sumatra Indonesia." Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy) 46, no. 3 (December 31, 2018): 314–21. http://dx.doi.org/10.24831/jai.v46i3.19342.

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Genetic variation is important in plant breeding. However, information on the genetic variability of Arabica coffee especially in coffee field of North Sumatra was not yet available. Magnitude of morphological variation, genotypic variation, phenotypic variation, heritability, genetic advance, genetic correlation, and phenotypic correlation of plant vigors and yield components of 28 genotypes were evaluated using nested design. This research showed morphological and genetic variations of the genotypes in the field. Based on the research locations as operational taxonomic unit, the genotypes were separated into three clusters. Most of the parameters had low to moderate genotypic variation, while phenotypic variation was moderate to high. Heritability and genetic advance were low, moderate, and high. Several plant vigors and yield components had a positive significant genetic and phenotypic correlation one another, and several had negative ones. Coffee berry borer infestation (CBBI) had a highly significant negative genetic correlation with leaf width (rG = -0.309**), leaf weight (rG = -0.671**), fruit diameter (rG = -0.320**), and bean length (rG = -0.175**). CBBI showed a significant positive genetic correlation with mesocarp pH (rG = 0.134*). To reduce CBBI, selection for higher leaf weight is better. Selection on lower pH of mesocarp could be considered to decrease CBBI.Keywords: cluster analysis, genetic correlation, genetic heritability, variability

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Higasa, Koichiro, Noriko Miyake, Jun Yoshimura, Kohji Okamura, Tetsuya Niihori, Hirotomo Saitsu, Koichiro Doi, et al. "Human genetic variation database, a reference database of genetic variations in the Japanese population." Journal of Human Genetics 61, no. 6 (February 25, 2016): 547–53. http://dx.doi.org/10.1038/jhg.2016.12.

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