Academic literature on the topic 'KASP markers'

This investigation covers genetics of rust resistance in common wheat and durum wheat. Stripe rust resistance in AUS26615 was conferred by three QTL and these were temporarily named; QYr.sun-1B, QYr.sun-3D and QYr.sun-6B. QYr.sun-1B represented the previously named APR gene Yr29. The other two QTL appear to be new. The detection of QYr.sun-3D in late sown experiment points to its better expression at relatively higher temperature regimes. The all stage resistance gene, YrAW12, carried by AUS26674, was shown to be Yr34 based on its co-segregation with Yr34-linked marker sunKASP_112 and similar seedling expression. AUS26674/Avocet S RIL population was genotyped with Yr18 and Yr29 linked markers, and responses of RILs carrying different combination of these loci were compared. The RILs carrying combination of YrAW12, Yr18 and Yr29 produced adult plant responses equal to the parent AUS266674. Among the two gene combinations, YrAW12 and Yr18 combination, produced adult plant stripe rust score 3, lower than the score 4 exhibited by other two dual combinations). Four RILs that lacked YrAW12, Yr18 and Yr29 displayed stripe rust response scores 5 to 7 indicating the presence of an additional APR locus in AUS266674. Eight leaf rust genes (Lr1, Lr13, Lr16, Lr24, Lr26, Lr27+Lr31, Lr37 and Lr73) and 11 stem rust resistance genes (Sr2, Sr8a, Sr8b, Sr9b, Sr9g, Sr17, Sr23, Sr24, Sr30, Sr31 and Sr38) were postulated singly or in different combinations among a set 85 genotypes. Nine and five lines, respectively, appear to carry uncharacterised leaf rust and stem rust resistance. Adult plant leaf rust responses ranged from 2 to 6, while stem rust scores varied from 2 to 8. Genetic analysis of stem rust resistance in a durum landrace AUS26677 indicated involvement of a single resistance gene, temporarily named SrAW4. SrAW4 was located on chromosome 4B.

This investigation covered characterization of genetically diverse sources of resistance, identification of molecular markers linked with rust resistance genes and their validation across diverse backgrounds. Genetic analysis of leaf rust resistance using durum-specific pathotypes of the leaf rust pathogen revealed the presence of a single gene in Aus26579 and Aus26582. The resistance gene was mapped on chromosome 6BS. Markers sunKASP_60 and sun684 showed close associations with LrAW2. Lr61 was also mapped on chromosome 6BS and haplotype analysis using linked markers suggested that LrAW2 is likely to be Lr61. Aus26582 carried an additional leaf rust resistance gene that was effective against six Australian Pt pathotypes and was mapped on chromosome 3BL and the underlying locus was temporarily named LrAW3. Marker sun786 mapped 1.8 cM distal to LrAW3. As no other seedling leaf rust resistance gene was previously mapped on chromosome 3BL, LrAW3 was formally named Lr79. Markers sun711, sun712, sun725, sunKASP_109 and sun KASP_112 from chromosome 5AL co-segregated with Yr34. Yr48, also located on chromosome 5AL, was proved to be identical to Yr34 on the basis of allelism test, sequence information and haplotype analysis. Various genomic resources were utilized to identify a close genetic association between the marker sun180 and linked rust resistance genes Yr47 and Lr52 in a fine mapping study. The loci order of sun180-0.4 cM-Lr52-0.2 cM-Yr47 was deduced. Markers linked with LrAW2/Lr61 (sunKASP_60), Lr79 (sun786), Yr34/Yr48 (sun712) and linked resistance genes Yr47 and Lr52 (sun180) did not amplify resistance-linked alleles in any of the cultivars lacking these genes and thus demonstrated their robustness in marker-assisted pyramiding with other marker-tagged rust resistance genes to produce triple rust resistant cultivars.

Breeding for rust resistance in wheat relies on detailed understanding and availability of existing genetic diversity for rust resistance among global germplasm and knowledge of pathotypic variation among rust pathogens. This study involved assessment of genetic diversity for stem rust resistance in an international wheat nursery ZWB14, inheritance of stripe rust resistance in a common wheat landrace Aus27881 and molecular mapping of stripe rust resistance in genotype ZIZ13:69 imported from International Centre for Agricultural Research in the Dry Areas (ICARDA). All stage resistance (ASR) genes Sr8a, Sr17, Sr24, Sr30, Sr31 and Sr38 and adult plant resistance (APR) genes Sr2, Sr57 and Sr58 were present either singly or in different combinations in entries of ZWB14. Some entries were observed to carry additional uncharacterised resistance. Tri-genic inheritance of stripe rust resistance in Aus27881 was observed. Genotyping with Yr34 and Yr29 linked markers demonstrated the presence of these genes in Aus27881. Third locus that conditioned APR in Aus27881 appears to be new and needs further characterisation. Genotype ZIZ13:69 was demonstrated to carry ASR gene Yr1 and APR gene Yr29 based on greenhouse tests and marker genotyping, respectively. The targeted genotyping by sequencing (tGBS) assay of a set of RILs lacking Yr29 detected a new quantitative trait locus (QTL) on the long arm of chromosome 7D.

Master of Science<br>Department of Plant Pathology<br>John P. Fellers<br>Allan K. Fritz<br>Leaf rust is caused by Puccinia triticina and is one of the most widespread diseases of wheat worldwide. Breeding for resistance is one of the most effective methods of control. Lr16 is a leaf rust resistance gene that provides partial resistance at the seedling stage. One objective of this study was to use RNA-seq and in silico subtraction to develop new resistance gene analog (RGA) markers linked to Lr16. RNA was isolated from the susceptible wheat cultivar Thatcher (Tc) and the resistant Thatcher isolines TcLr10, TcLr16, and TcLr21. Using in silico subtraction, Tc isoline ESTs that did not align to the Tc reference were assembled into contigs and analyzed using BLAST. Primers were designed from 137 resistance gene analog sequences not found in Tc. A population of 260 F[subscript]2 lines derived from a cross between the rust-susceptible cultivar Chinese Spring (CS) and a Thatcher isoline containing Lr16 (TcLr16) was developed for mapping these markers. Two RGA markers XRGA266585 and XRGA22128 were identified that mapped 1.1 cM and 23.8 cM from Lr16, respectively. Three SSR markers Xwmc764, Xwmc661, and Xbarc35 mapped between these two RGA markers at distances of 4.1 cM, 10.7 cM, and 16.1 cM from Lr16, respectively. Another objective of this study was to use genotyping-by-sequencing (GBS) to develop single nucleotide polymorphism (SNP) markers closely linked to Lr16. DNA from 22 resistant and 22 susceptible F[subscript]2 plants from a cross between CS and TcLr16 was used for GBS analysis. A total of 39 Kompetitive Allele Specific PCR (KASP) markers were designed from SNPs identified using the UNEAK and Tassel pipelines. The KASP marker XSNP16_TP1456 mapped 0.7 cM proximal to Lr16 in a TcxTcLr16 population consisting of 129 F[subscript]2 plants. These results indicate that both techniques are viable methods to develop new molecular markers. RNA-seq and in silico subtraction were successfully used to develop two new RGA markers linked to Lr16, one of which was more closely linked than known SSR markers. GBS was also successfully used on an F[subscript]2 population to develop a KASP marker that is the most closely linked marker to Lr16 to date.

This investigation covered characterisation of various faba bean rust isolates by identifying a differential set in the host; identification of molecular markers linked with rust resistance genes Uvf-2 in Doza#12034 and Uvf-3 in Ac1655 and their validation across diverse backgrounds; and elucidation of the host-pathogen interactions of Uromyces viciae-fabae with faba bean, field pea (Pisum sativum), lentil (Lens culinaris), chickpea (Cicer arietinum), lupin (Lupinus albus and Lupinus angustifolius) and mungbean (Vigna radiata). The differential pathogenicity in the interaction of Vicia faba × Uromyces viciae-fabae led to the identification of nine faba bean rust pathotypes, characterised by the set of twelve genotypes (regarded as differential), and named 0-10, 0-46, 40-31, 40-55, 24-40, 63-53, 63-49, 55-63 and 63-63. This information will help faba bean breeders to carefully deploy rust resistance gene(s) which can effectively insight resistance against pathotypes of targeted environment. Genetic analysis, using pathotype 24-40, revealed monogenic inheritance of rust resistance in faba bean genotypes Doza#12034 and Ac1655, respectively. After genotyping Fiord/Doza#12034 and Fiord/Ac1655 RILs, two closely linked KASP markers KASP_Vf_0703 and KASP_Ac×F165 were mapped on chromosome III and V with Uvf-2 and Uvf-3, respectively and validated successfully in a set of local/exotic faba bean genotypes. These closely linked markers will allow breeders to implement markers assisted selection for both resistance genes. The histopathology of Australian U. viciae-fabae revealed a host range: both faba bean and field pea were competent hosts showing varietal differences to pathogen responses, with differential expression in resistance; lentil showed complete hypersensitive resistance by expressing cell death; and chickpea, lupin and mungbean appeared as non-hosts.

Migracijos reiškinys yra analizuojamas jau seniai. Iki Lietuvos narystės ES (ir po Lietuvos įstojimo į ES) paskelbta daug darbų migracijos tema. Ypač skaudi valstybei bei aktuali yra aukštąjį išsilavinimą turinčių žmonių emigracija, nes tokiu būdu yra ne tik prarandamos lėšos įdėtos į kvalifikuotos darbo jėgos paruošimą, bet ir prastėja valstybės teikiamų paslaugų kokybė, smunka vidutinis šalies kvalifikacijos lygis, o kartu ir šalies konkurencingumas tarptautinėje rinkoje. Darbo objektas – darbo rinkos politikos įtaka aukštos kvalifikacijos specialistų emigracijai. Pagrindiniai uždaviniai - išryškinti emigracijos esmę bei pasekmes; išskirti teorinius aukštos kvalifikacijos specialistams pritaikytus bei su darbo rinka susijusius emigracijos veiksnius; atskleisti Lietuvoje taikomą migracijos politiką; įvertinti aukštos kvalifikacijos specialistų emigracijos veiksnius Lietuvoje, didelį dėmesį skiriant darbo rinkos politikai; atlikti ketinimų emigruoti dėl darbo rinkos situacijos kiekybinį tyrimą bei sukurti jo rezultatus apibendrinantį modelį. Darbas susideda iš trijų pagrindinių dalių. Pirmojoje darbo dalyje išryškinama teoriniai aukštos kvalifikacijos specialistų migracijos aspektai, antrojoje darbo dalyje nagrinėjama statistiniai su emigracija susiję Lietuvos ir emigracijos tikslo šalių duomenys, trečiojoje darbo dalyje atliekamas empirinis tyrimas, siekiant įvertinti ketinimų emigruoti sąryšį su darbo rinkos situaciją. Pagal tyrimų rezultatus, pateikiamos išvados bei... [toliau žr. visą tekstą]<br>The subject of the Master work is emigration of highly qualified specialists. Emigration of highly qualified specialists is known for a long period of time, just now the scales of emigration is higher than ever. Economic recession is playing a big part in this, as all the countries are affected by recession at the different level. Due to migration of highly qualified specialists government looses money, which was spend in gaining the qualification, as well country looses tax payers and overall country looses competitiveness in international arena. The object of the study is the influence of labor market policy to the emigration of highly qualified specialists. The main tasks are to highlight the nature and consequences of emigration; to reveal theoretical immigration–related factors; to evaluate Lithuania’s migration policy; focusing on labor market policy to distinguish to high–qualified specialists orientated emigration factors; to perform a quantitative survey and create a model summarizing the results. Work structure: work consists of three main parts: in the first part is made an analysis of theoretical high qualified specialists emigration aspects, in the second part is made a statistical analysis of Lithuania’s and other countries migration related data and in third – an empirical research made to evaluate the influence of labor market factors to the emigration decision. Working volume: 73 pages, 23 tables, 26 figures and 83 references used: 55 Lithuanian and 28... [to full text]

A candidate gene approach was used to identify potential genetic markers associated with wool quality traits including mean fibre diameter (MFD), fibre diameter standard deviation (FDSD), coefficient of variation of fibre diameter (CVD), prickle factor, curvature, yellowness, brightness, staple strength, staple length, yield, greasy fleece weight (GFW) and clean fleece weight (CFW). Inheritance of potential genetic markers was studied in two half-sib Merino families and assessed for association with the wool quality traits. The sire for one of the half-sib families is referred to as MV144-58-00, and wool measurements from its progeny were taken at 12 (n = 131), 24 (n =128) and 36 (n = 37) months of age. The sire for the second half-sib family is referred to as Stoneyhurst, and wool measurements from its progeny (n = 35) were taken at 12 months of age. Genes that code for the keratin intermediate-filament proteins (KRTs) (KRT1.2, KRT2.10) and the keratin intermediate-filament-associated proteins (KAPs) (KAPl.1, KAPl.3, KAP3.2, KAP6.1, KAP 7, KAP8) were targeted for this investigation, along with the beta 3-adrenergic receptor (ADRB3) gene and microsatellites BfMS and OarFCB193. Polymerase chain reaction (PCR) was used to amplify specific DNA fragments from each locus and PCR- single strand conformational polymorphism (PCR-SSCP) analysis was used to detect polymorphism within the half-sib families for all the loci, except for the KAP1.1 gene, where length polymorphism was detected using agarose gel electrophoresis. Only the loci that were heterozygous for the sire (KAP1.1, KAP1.3, KRT1.2, ADRB3, KAP8) and hence were informative, were genotyped in the progeny. The total number of alleles observed at the KAP1.1, KAP1.3, KRT1.2, KAP8 and the ADRB3 loci were four, ten, six, five and six, respectively. Analysis of each of the informative loci revealed allelic associations with various wool traits. In the MV144-58-00 (genotypes KAP1.1 AB; KAP1.3 BD; KRT1.2 AB; ADRB3 CE) half-sib, inheritance of the KAP1.1 A allele was associated with a higher yield at 24 months of age (P = 0.037). This trend also observed at 36 months of age (P = 0.078). At 12 months of age, the KAP1.1 A allele tended to be associated with increased staple length (P = 0.08). At 36 months of age, the inheritance of the KAP1.1 B allele tended towards being associated with whiter wool (P = 0.080). The MV144-58-00 KAP1.3 D allele tended to be associated with increased yield at 24 and 36 months of age (P = 0.091 and 0.059, respectively), and with lower FDSD at 12 months of age (P = 0.055). The sire KAP1.3 B allele was associated with whiter wool colour at 36 months of age (P = 0.045). The inheritance of the MV144-58-00 KR T1.2 B allele was associated with or tended to be associated with a smaller FDSD (P = 0.040), an increase in staple strength (P = 0.025) and an increase in GFW (P = 0.069) at 12 months of age. At 24 months of age, the KR T1.2 B allele tended to be associated with increased yield (P = 0.057). At 36 months of age, the KRTl.2 A allele was associated with whiter wool (P = 0.019) and tended to be associated with increased crimp within the wool fibre (P = 0.089). In the Stoneyhurst (genotypes KAP1.1 BC; KAP1.3 CJ; KRT1.2 DE; ADRB3 CE) half-sib, inheritance of the KAP1.1 B allele was associated with longer staple length (P = 0.018) and a decrease in wool brightness (P = 0.039). In contrast, KAP1.1 C allele was associated with lowest staple length (P = 0.018) and brighter wool colour (P = 0.039). Associations observed with the inheritance of Stoneyhurst KAP 1.1 alleles were similar to the inheritance ofKAPl.3 alleles. Stoneyhurst KAP1.3 J allele was associated with longer staple length (P = 0.017) and a decrease in wool brightness (P = 0.010). In contrast, KAP1.3 C allele was associated with lowest staple length (P = 0.017) and brighter wool colour (P = 0.010). The Stoneyhurst KRT12 D allele was associated with longer staple length and a decrease in wool brightness (P = 0.033). In contrast, KRT1.2 E allele was associated with lowest staple length (P = 0.033) and brighter wool colour (P = 0.022). Sire alleles at the ADRB3 gene locus were associated with variation in staple strength (P = 0.025) for MV144-58-00's progeny, and with variation in yield (P = 0.023) for Stoneyhurst's progeny. The results obtained in this thesis are consistent with KAP1.1, KAP1.3 and KRT1.2 being clustered on one chromosome because both sires in this study passed on two major KAP1.1-KAP1.3-KRT1.2 haplotypes to their progeny, and the associations with wool traits were very similar for all the three loci. The major sire derived KAP1.1 – KAP1.3 - KRT1.2 haplotypes observed within the MV144-58-00 half-sib were: BBA (frequency of 43.4%; n = 43) and ADB (frequency of 44.4%; n = 44). Other minor haplotypes observed were: ADA (frequency of 4.0%; n = 4); BDA (frequency of 2.0%; n = 2); BBB (frequency of 3.0%; n = 3) and BDB (frequency of 3.0%; n = 3). In the Stoneyhurst half-sib, major sire-derived KAP 1.1 - KAP 1.3 - KR Tl.2 haplotypes observed were CCE (frequency of 53.1 %; n = 17) and BJD (frequency of 40.6%; n = 13). The minor haplotype BJE (frequency of 6.3%; n = 2) was also observed. Statistical analyses within the MVI44-58-00 half-sib showed that KAP1.1 AKAP1.3 D - KRT1.2 B haplotype was associated with increased yield (P = 0.023) and tended towards whiter wool colour (P = 0.059), smaller FDSD (P = 0.081) and stronger staple strength (P = 0.092). In the Stoneyhurst half-sib, the KAP1.1 B - KAP1.3 J - KRT1.2 D haplotype was associated with longer staple length (P = 0.010), while the KAP1.1 C - KAP1.3 C - KRT1.2 E haplotype showed a strong trend with increased wool brightness (P = 0.096). Result from this study indicated that the keratin genes on chromosome 11 are recombining relatively frequently at recombination "hotspots". A high rate of recombination among loci that impact on wool traits would make breeding for consistent wool quality very difficult. The results presented in this thesis suggest that genes coding for the KRTs and KAPs have the potential to impact on wool quality. KAP1.1, KAP1.3 and KRT1.2 could potentially be exploited in gene marker-assisted selection programmes within the wool industry to select for animals with increased staple length, 'increased staple strength, higher yield and brighter wool. This study was however limited to two half-sib families, and further investigation is required.

The ability to identify germplasm and select traits accurately is fundamental to successful plant breeding. Pedigrees and molecular markers facilitate these processes; however misleading experimental results can occur when incorrect relationships and/or cultivar names are recorded. Molecular markers can identify these inconsistencies, and with advances in genotyping technology these diagnostics can be done faster and more objectively. This study aimed to develop molecular marker assays and graphical genotyping methodologies for cultivar identification, seed purity assessment and trait selection in oat (Avena sativa L.). KBioscience’s Allele-Specific PCR (KASP™) and genotyping-by-sequencing (GBS) technologies were applied to a set of current Canadian oat cultivars to evaluate their utility for identifying cultivars and detecting intra-cultivar variation. Both KASP™ and GBS detected different extents of heterogeneity among a set of 160 seeds that originated from four seed sources of four cultivars. In both cases, the detected variation did not appear to be limited to a specific cultivar or seed source, reinforcing that all cultivars are heterogeneous. Graphical genotyping localized heterogeneity to specific chromosome regions, thereby distinguishing physical contamination from true genetic heterogeneity and heterozygosity. Pre-existing genotype data for 700 oat cultivars and breeding lines were also used to construct graphical genotypes for pedigree validation and discovery of potential sources for favourable quantitative trait loci (QTL) alleles. This methodology used historical QTLs and anchoring markers to identify 25 putative “high oil” allele carriers. The results from this study will provide diagnostic tools for cultivar identification and pedigree validation, in addition to meaningful information about existing heterogeneity and possible QTL locations in current cultivars.