High-density Genotyping Arrays Research Articles

Abstract 3430: Mosaic loss of the Y chromosome is associated with prostate cancer risk

Abstract Mosaic loss of the Y chromosome (mLOY), a type of clonal hematopoiesis, is the most frequent chromosomal alteration observed in leukocytes of aging men. mLOY is a putative biomarker of genomic instability with evidence of associations with risk of some solid tumors, but more studies are needed to refine associations and identify potential mechanisms for cancer risk. Prostate cancer (PCa), the most common non-cutaneous cancer in males, is also associated with aging. To further investigate potential relationships between mLOY and PCa, we examined DNA derived from leukocytes of male participants in two large biobanks: the UK Biobank (UKBB; N = 210,103) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, N = 26,795). Of the 236,898 male participants without previous cancer diagnosis, 14,253 (6.0%) were diagnosed with incident PCa after DNA collection. High-density genotyping array data collected during the studies were used to create virtual karyotypes for detecting mLOY in whole blood samples utilizing a phase-based detection method in MoChA software. Analyses were restricted to men without cancer at genotyping and multivariable regression models were adjusted for age, smoking status, and genetic similarity. Men with detectable mLOY were older (mean = 62 vs 56 years) and more likely to be smokers (14.8% vs 9.7%) than men without mLOY. A total of 3,848 (27.0%) men with PCa and 42,835 (19.2%) men free of PCa had detectable mLOY. mLOY clonal fraction ranged from 0.01% to 72.1% of total leukocytes. 18.7% of PCa cases and 13.6% of men free of PCa had high clonal fraction mLOY, defined as greater than 10% of leukocytes with mLOY. Fixed effect meta-analysis of multivariable models from UKBB and PLCO produced evidence for a positive association between mLOY in leukocytes and incident PCa; (Odds Ratio (OR) = 1.062, 95% Confidence Interval (CI) [1.020, 1.107], P-Value (p) = 0.004). The effect estimate was the same in men with low clonal fraction of mLOY (OR = 1.062, 95% CI [1.012, 1.113], p = 0.014) and men with high clonal fraction of mLOY (OR = 1.065, 95% CI [0.998, 1.137], p = 0.057). Age at PCa diagnosis was not associated with mLOY or the clonal fraction of mLOY. A sub-analysis of separate participants from PLCO with mLOY detected in buccal cells (n = 18,011) also showed a small positive effect between mLOY and PCa risk, but the relationship did not reach statistical significance (OR = 1.036, 95% CI [0.877, 1.224], p = 0.673)). Our investigation of the relationship between mLOY and PCa in two large prospective studies provides additional evidence for an association between mLOY detected in the blood and increased PCa risk, meriting additional studies of potential biologic mechanisms underlying the relationship. Citation Format: Rebecca L. Kelly, Weiyin Zhou, Kara M. Barnao, Corey D. Young, Aubrey K. Hubbard, Sairah M. Khan, Wen-Yi Huang, Stephen J. Chanock, Mitchell J. Machiela. Mosaic loss of the Y chromosome is associated with prostate cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3430.

Abstract 921: The value of cancer genomic data sharing

Abstract Our understanding of and ability to combat cancer relies on the generation, analysis, and sharing of data. The Epidemiology and Genomics Research Program in the National Cancer Institute’s Division of Cancer Control and Population Sciences (DCCPS) has supported generation of large genomic data sets and advocated for and/or required broad sharing of this data. One of DCCPS’s scientific priorities is focused on data strategies namely, “the use, enhancement, expansion, and accessibility of new and existing DCCPS-supported data resources to accelerate cancer control research” (https://cancercontrol.cancer.gov/overview-highlights/2022/future_directions.html).EGRP funded the Genetic Associations and Mechanisms in Oncology (GAME-ON) Initiative, a multidisciplinary collaboration of researchers focused on understanding the genetic architecture, biology, and clinical and epidemiologic utility of common cancer risk variants. This program focused on 5 common cancer types - breast, colorectal, lung, ovarian, and prostate - and required research that incorporated multiple research domains and sharing of any data generated. A major accomplishment of this program was development of the OncoArray genotyping chip, which used information from genetic epidemiology studies, biological/functional analyses, and clinical and epidemiologic insights to create a comprehensive, high-density genotyping array for pan-cancer studies that has led to the discovery of hundreds of new cancer predisposition variants. This chip was used in a massive, coordinated genotyping effort that culminated in the generation of 7 datasets comprising genotyping data for nearly 500,000 individuals. All the data were deposited in dbGaP between 2014 and 2021 and are available (via controlled access) to any investigators. To understand the secondary use of these data, we determined the number of times the data had been downloaded, who downloaded the data, and types of research for which it was used. We also identified publications using OncoArray data and characterized the publications by research type, cancer type, and other details. Through this analysis, we explore how well the GAME-ON initiative and the OncoArray projects promote the DCCPS scientific priority of optimizing secondary research by making the data findable, accessible, interoperable, and reusable (FAIR). Citation Format: Stefanie Nelson, Charlisse Caga Anan, Elizabeth Gillanders. The value of cancer genomic data sharing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 921.

Genetic sex validation for sample tracking in next-generation sequencing clinical testing

ObjectiveData from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.ResultsPrecise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

Genomic inbreeding measures applied to a population of mice divergently selected for birth weight environmental variance.

This study aimed to compare different inbreeding measures estimated from pedigree and molecular data from two divergent mouse lines selected for environmental birth weight during 26 generations. Furthermore, the performance of different approaches and both molecular and pedigree data sources for estimating Ne were tested in this population. A total of 1,699 individuals were genotyped using a high-density genotyping array. Genomic relationship matrices were used to calculate molecular inbreeding: Nejati-Javaremi (F NEJ), Li and Horvitz (F L&H), Van Raden method 1 (F VR1) and method 2 (F VR2), and Yang (F YAN). Inbreeding based on runs of homozygosity (F ROH) and pedigree inbreeding (F PED) were also computed. F ROH, F NEJ, and F L&H were also adjusted for their average values in the first generation of selection and named F ROH0, F NEJ0, and F L&H0. ∆F was calculated from pedigrees as the individual inbreeding rate between the individual and his parents (∆F PEDt) and individual increases in inbreeding (∆F PEDi). Moreover, individual ∆F was calculated from the different molecular inbreeding coefficients (∆F NEJ0, ∆F L&H, ∆F L&H0, ∆F VR1, ∆F VR2, ∆F YAN, and ∆F ROH0). The Ne was obtained from different ∆F, such as Ne PEDt, Ne PEDi, Ne NEJ0, Ne L&H, Ne L&H0, Ne VR1, Ne VR2, Ne YAN, and Ne ROH0. Comparing with F PED , F ROH , F NEJ and F VR2 overestimated inbreeding while F NEJ0 , F L&H , F L&H0 , F VR1 and F YAN underestimated inbreeding. Correlations between inbreeding coefficients and ∆F were calculated. F ROH had the highest correlation with F PED (0.89); F YAN had correlations >0.95 with all the other molecular inbreeding coefficients. Ne PEDi was more reliable than Ne PEDt and presented similar behaviour to Ne L&H0 and Ne NEJ0. Stable trends in Ne were not observed until the 10th generation. In the 10th generation Ne PEDi was 42.20, Ne L&H0 was 45.04 and Ne NEJ0 was 45.05 and in the last generation these Ne were 35.65, 35.94 and 35.93, respectively F ROH presented the highest correlation with F PED, which addresses the identity by descent probability (IBD). The evolution of Ne L&H0 and Ne NEJ0 was the most similar to that of Ne PEDi. Data from several generations was necessary to reach a stable trend for Ne, both with pedigree and molecular data. This population was useful to test different approaches to computing inbreeding coefficients and Ne using molecular and pedigree data.

Genome-wide association analysis for drought tolerance and associated traits in faba bean (Vicia faba L.).

Faba bean (Vicia faba L.) is an important high protein legume adapted to diverse climatic conditions with multiple benefits for the overall sustainability of the cropping systems. Plant-based protein demand is being expanded and faba bean is a good candidate to cover this need. However, the crop is very sensitive to abiotic stresses, especially drought, which severely affects faba bean yield and development worldwide. Therefore, identifying genes associated with drought stress tolerance is a major challenge in faba bean breeding. Although the faba bean response to drought stress has been widely studied, the molecular approaches to improve drought tolerance in this crop are still limited. Here we built on recent genomic advances such as the development of the first high-density SNP genotyping array, to conduct a genome-wide association study (GWAS) using thousands of genetic polymorphisms throughout the entire faba bean genome. A worldwide collection of 100 faba bean accessions was grown under control and drought conditions and 10 morphological, phenological and physiological traits were evaluated to identify single nucleotide polymorphism (SNP) markers associated with drought tolerance. We identified 29 SNP markers significantly correlated with these traits under drought stress conditions. The flanking sequences were blasted to the Medicago truncatula reference genomes in order to annotate potential candidate genes underlying the causal variants. Three of the SNPs for chlorophyll content after the stress, correspond to uncharacterized proteins indicating the presence of novel genes associated with drought tolerance in faba bean. The significance of stress-inducible signal transducers provides valuable information on the possible mechanisms underlying the faba bean response to drought stress, thus providing a foundation for future marker-assisted breeding in the crop.

A wheat chromosome segment substitution line series supports characterization and use of progenitor genetic variation.

Genome-wide introgression and substitution lines have been developed in many plant species, enhancing mapping precision, gene discovery, and the identification and exploitation of variation from wild relatives. Created over multiple generations of crossing and/or backcrossing accompanied by marker-assisted selection, the resulting introgression lines are a fixed genetic resource. In this study we report the development of spring wheat (Triticum aestivum L.) chromosome segment substitution lines (CSSLs) generated to systematically capture genetic variation from tetraploid (T. turgidum ssp. dicoccoides) and diploid (Aegilops tauschii) progenitor species. Generated in a common genetic background over four generations of backcrossing, this is a base resource for the mapping and characterization of wheat progenitor variation. To facilitate further exploitation the final population was genetically characterized using a high-density genotyping array and a range of agronomic and grain traits assessed to demonstrate the potential use of the populations for trait localization inwheat.

Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit.

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.

Patagonian sheepdog: Genomic analyses trace the footprints of extinct UK herding dogs to South America.

Most modern dog breeds were developed within the last two hundred years, following strong and recent human selection based predominantly on aesthetics, with few modern breeds constructed solely to maximize their work potential. In many cases, these working breeds represent the last remnants of now lost populations. The Patagonian sheepdog (PGOD), a rare herding breed, is a remarkable example of such a population. Maintained as an isolated population for over 130 years, the PGOD offers a unique opportunity to understand the genetic relationship amongst modern herding breeds, determine key genomic structure of the founder PGOD populations, and investigate how canine genomic data can mirror human migration patterns. We thus analyzed the population structure of 159 PGOD, comparing them with 1514 dogs representing 175 established breeds. Using 150,069 SNPs from a high-density SNP genotyping array, we establish the genomic composition, ancestry, and genetic diversity of the population, complementing genomic data with the PGOD’s migratory history to South America. Our phylogenetic analysis reveals that PGODs are most closely related to modern herding breeds hailing from the United Kingdom. Admixture models illustrate a greater degree of diversity and genetic heterogeneity within the very small PGOD population than in Western European herding breeds, suggesting the PGOD predates the 200-year-old construction of most pure breeds known today. We thus propose that PGODs originated from the foundational herding dogs of the UK, prior to the Victorian explosion of breeds, and that they are the closest link to a now-extinct population of herding dogs from which modern herding breeds descended.

New Genes and Emerging Mechanisms of Type 1 Diabetes

Type 1 Diabetes susceptibility depends upon the complex interaction between numerous genetic as well as environmental factors. 50% of the familial clustering of T1D is explained by HLA locus alleles. Other multiple loci contribute the rest of the susceptibility, in which very little were known since last few years. Four novel loci were found from the results of stage-I, genome wide association (GWA) studies which were carried out with high-density genotyping arrays. As the stage-II of the Genome Wide Association studies completed, hopefully, most of the genetic reasons of Type 1 Diabetes will be identified.

Whole genome analysis reveals aneuploidies in early pregnancy loss in the horse

The first 8 weeks of pregnancy is a critical time, with the majority of pregnancy losses occurring during this period. Abnormal chromosome number (aneuploidy) is a common finding in human miscarriage, yet is rarely reported in domestic animals. Equine early pregnancy loss (EPL) has no diagnosis in over 80% of cases. The aim of this study was to characterise aneuploidies associated with equine EPL. Genomic DNA from clinical cases of spontaneous miscarriage (EPLs; 14–65 days of gestation) and healthy control placentae (various gestational ages) were assessed using a high density genotyping array. Aneuploidy was detected in 12/55 EPLs (21.8%), and 0/15 healthy control placentae. Whole genome sequencing (30X) and digital droplet PCR (ddPCR) validated results. The majority of these aneuploidies have never been reported in live born equines, supporting their embryonic/fetal lethality. Aneuploidies were detected in both placental and fetal compartments. Rodents are currently used to study how maternal ageing impacts aneuploidy risk, however the differences in reproductive biology is a limitation of this model. We present the first evidence of aneuploidy in naturally occurring equine EPLs at a similar rate to human miscarriage. We therefore suggest the horse as an alternative to rodent models to study mechanisms resulting in aneuploid pregnancies.

Genomic measures of inbreeding in the Norwegian\u2013Swedish Coldblooded Trotter and their associations with known QTL for reproduction and health traits

BackgroundSince the 1950s, the Norwegian–Swedish Coldblooded trotter (NSCT) has been intensively selected for harness racing performance. As a result, the racing performance of the NSCT has improved remarkably; however, this improved racing performance has also been accompanied by a gradual increase in inbreeding level. Inbreeding in NSCT has historically been monitored by using traditional methods that are based on pedigree analysis, but with recent advancements in genomics, the NSCT industry has shown interest in adopting molecular approaches for the selection and maintenance of this breed. Consequently, the aims of the current study were to estimate genomic-based inbreeding coefficients, i.e. the proportion of runs of homozygosity (ROH), for a sample of NSCT individuals using high-density genotyping array data, and subsequently to compare the resulting rate of genomic-based F (FROH) to that of pedigree-based F (FPED) coefficients within the breed.ResultsA total of 566 raced NSCT were available for analyses. Average FROH ranged from 1.78 to 13.95%. Correlations between FROH and FPED were significant (P < 0.001) and ranged from 0.27 to 0.56, with FPED and FROH from 2000 to 2009 increasing by 1.48 and 3.15%, respectively. Comparisons of ROH between individuals yielded 1403 regions that were present in at least 95% of the sampled horses. The average percentage of a single chromosome covered in ROH ranged from 9.84 to 18.82% with chromosome 31 and 18 showing, respectively, the largest and smallest amount of homozygosity.ConclusionsGenomic inbreeding coefficients were higher than pedigree inbreeding coefficients with both methods showing a gradual increase in inbreeding level in the NSCT breed between 2000 and 2009. Opportunities exist for the NSCT industry to develop programs that provide breeders with easily interpretable feedback on regions of the genome that are suboptimal from the perspective of genetic merit or that are sensitive to inbreeding within the population. The use of molecular data to identify genomic regions that may contribute to inbreeding depression in the NSCT will likely prove to be a valuable tool for the preservation of its genetic diversity in the long term.

The contribution of myostatin (MSTN) and additional modifying genetic loci to race distance aptitude in Thoroughbred horses racing in different geographic regions.

Race distance aptitude in Thoroughbred horses is highly heritable and is influenced largely by variation at the myostatin gene (MSTN). In addition to MSTN, we hypothesised that other modifying loci contribute to best race distance. Using 3006 Thoroughbreds, including 835 'elite' horses, which were >3years old, had race records and were sampled from Europe/Middle-East, Australia/New Zealand, North America and South Africa, we performed genome-wide association (GWA) tests and separately developed a genomic prediction algorithm to comprehensively catalogue additive genetic variation contributing to best race distance. 48,896 single-nucleotide polymorphism (SNP) genotypes were generated from high-density SNP genotyping arrays. Heritability estimates, tests of GWA and genomic prediction models were derived for the phenotypes: average race distance, best race distance for elite, nonelite and all winning horses. Heritability estimates were high ( =0.51, best race distance - elite; =0.42, best race distance - nonelite; =0.40, best race distance - all) and most of the variation was attributed to the MSTN gene. MSTN locus SNPs were the most strongly associated with the trait and included BIEC2-438999 (ECA18:66913090; P=4.51×10-110 , average race distance; P=2.33×10-42 , best race distance - elite). The genomic prediction algorithm enabled the inclusion of variation from all SNPs in a model that partitioned horses into short and long cohorts following assignment of MSTN genotype. Additional genes with minor contributions to best race distance were identified. The nongenetic influence of owner/trainer decisions on placement of horses in suitable races could not be controlled. MSTN is the single most important genetic contributor to best race distance in the Thoroughbred. Employment of genetic prediction models will lead to more accurate placing of horses in races that are best suited to their inherited genetic potential for distance aptitude.

A Meta-Analysis of α-Synuclein Multiplication in Familial Parkinsonism.

Chronic alpha-synuclein (SNCA) overexpression is a relatively homogenous and well-defined cause of parkinsonism and dementia. Parkinson's disease (PD), PD with dementia, dementia with Lewy bodies and multiple system atrophy all manifest in SNCA multiplication families. Herein we summarize genealogic, clinical and genetic data from 59 families (25 not previously published) with parkinsonism caused by SNCA multiplications. Longitudinal clinical assessments and genealogic relationships were documented for all family members. All probands were genotyped with an Illumina MEGA high-density genotyping array to identify copy number variants (CNV) and enable SNCA multiplication breakpoints to be defined. Three SNCA short tandem repeat (STR) markers were genotyped in all available samples to validate genomic dosage and inheritance. A web-application was built as a forum for future data sharing. CNV analysis identified 49 subjects with heterozygous SNCA duplication (CNV3), 2 with homozygous duplication (CNV4) and 7 with a triplication mutation (CNV4). Clinical presentations varied greatly throughout the cohort. SNCA dosage correlates with disease onset (mean age of onset CNV3: 46.9 ± 10.5 years vs. 34.5 ± 7.4 CNV4, p = 0.003). Atypical or more severe clinical courses were described in several patients and dementia was noted in 50.9% of the probands. Neither the multiplication size (average 2.05 ± 2.45 Mb) nor the number of genes included (range 1–50) was associated with motor symptom onset or dementia. Families with SNCA multiplication are rare and globally-distributed. Nevertheless, they may both inform and benefit from the development of SNCA targeted therapeutic strategies relevant to the treatment of all alpha-synucleinopathies.

Genome-Wide Association Mapping of Host-Plant Resistance to Soybean Aphid.

Soybean aphid [ Matsumura (Hemiptera: Aphididae)] is the most damaging insect pest of soybean [ (L.) Merr.] in the Upper Midwest of the United States and is primarily controlled by insecticides. Soybean aphid resistance (i.e., genes) has been documented in some soybean accessions but more sources of resistance are needed. Incorporation of the resistance into marketed varieties has also been slow. Genome-wide association mapping can aid in identifying resistant accessions by correlating phenotypic data with single nucleotide polymorphisms (SNPs) across a genome. Aphid population measures from 2366 soybean accessions were collected from published studies screening cultivated soybean () and wild soybean ( Siebold & Zucc.) with aphids exhibiting Biotype 1, 2, or 3 characteristics. Genotypic data were obtained from the SoySNP50K high-density genotyping array previously used to genotype the USDA Soybean Germplasm Collection. Significant associations between SNPs and soybean aphid counts were found on 18 of the 20 soybean chromosomes. Significant SNPs were found on chromosomes 7, 8, 13, and 16 with known genes. SNPs were also significant on chromosomes 1, 2, 4 to 6, 9 to 12, 14, and 17 to 20 where genes have not yet been mapped, suggesting that many genes remain to be discovered. These SNPs can be used to determine accessions that are likely to have novel aphid resistance traits of value for breeding programs.

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Relationship of runs of homozygosity with adaptive and production traits in a paternal broiler line

Genomic regions under high selective pressure present specific runs of homozygosity (ROH), which provide valuable information on the genetic mechanisms underlying the adaptation to environment imposed challenges. In broiler chickens, the adaptation to conventional production systems in tropical environments lead the animals with favorable genotypes to be naturally selected, increasing the frequency of these alleles in the next generations. In this study, ~1400 chickens from a paternal broiler line were genotyped with the 600 K Affymetrix® Axiom® high-density (HD) genotyping array for estimation of linkage disequilibrium (LD), effective population size (Ne), inbreeding and ROH. The average LD between adjacent single nucleotide polymorphisms (SNPs) in all autosomes was 0.37, and the LD decay was higher in microchromosomes followed by intermediate and macrochromosomes. The Ne of the ancestral population was high and declined over time maintaining a sufficient number of animals to keep the inbreeding coefficient of this population at low levels. The ROH analysis revealed genomic regions that harbor genes associated with homeostasis maintenance and immune system mechanisms, which may have been selected in response to heat stress. Our results give a comprehensive insight into the relationship between shared ROH regions and putative regions related to survival and production traits in a paternal broiler line selected for over 20 years. These findings contribute to the understanding of the effects of environmental and artificial selection in shaping the distribution of functional variants in the chicken genome.

Abstract 1296: Bayesian fine-mapping using summary data of 145,000 subjects refines common risk associations, discovers secondary signals and novel candidate genes for prostate cancer

Abstract Genome-wide association studies (GWAS) have identified more than 160 prostate cancer (PrCa) genetic risk loci, however these variants rarely point directly to the true underlying functional variant driving the association. In this fine-mapping study to narrow the credible causal variant set for 80 PrCa regions representing 89 original independent GWAS signals, we performed Bayesian variable selection in combination with functional annotation and quantile regression. We used imputed data for 83,511 PrCa cases and 62,283 controls investigated with high-density genotyping arrays from the OncoArray, iCOGS and 5 previous GWAS studies from the PRACTICAL/ELLIPSE consortia. To facilitate fine-mapping from one-at-a-time SNP associations meta-analyzed over the consortia we first applied JAM, a novel Bayesian algorithm which searches multi-SNP models in summary data by imputing the correlation structure according to a reference panel. JAM provides inference on the number of independent signals, as well as the set of potential SNPs driving those signals. We utilized functional annotation and eQTL analysis (TCGA prostate tumor data) in combination with quantile regression to further prioritize the most likely causal variants within the credible set of SNPs and identify potential candidate genes and functional mechanisms. The median credible set size from JAM was 17 SNPs per region, shrinking the post-QC input set of variants by about 98%. In 13 regions evidence was found for multiple independent signals, up to a maximum of 5 SNPs. Within the single hit regions, almost half had less than 10 variants selected. In 34 regions the credible set included at least one SNP that was co-localized with a significant eQTL. Quantile regression highlighted enrichment for variants in promoters, DNase hypersensitivity site and eQTLs - representing candidate biological mechanisms underpinning disease development. This study has substantially reduced and prioritized the candidate causal PrCa risk variants within previously known GWAS regions, identifying a small subset of variants for further functional investigation and novel candidate genes at a number of loci. Citation Format: Zsofia Kote-Jarai, Tokhir Dadaev, Ed Saunders, Paul Newcombe, Ezequiel Anokian, Daniel Leongamornlert, Ali Amin Al Olama, Christopher Haiman, Ros Eeles, David Conti, The PRACTICAL/ELLIPSE Consortium. Bayesian fine-mapping using summary data of 145,000 subjects refines common risk associations, discovers secondary signals and novel candidate genes for prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1296. doi:10.1158/1538-7445.AM2017-1296

Evaluation of Bovine High-Density SNP Genotyping Array in Indigenous Dairy Cattle Breeds

ABSTRACTIn total 52 samples of Sahiwal (19), Tharparkar (17), and Gir (16) were genotyped by using BovineHD SNP chip to analyze minor allele frequency (MAF), genetic diversity, and linkage disequilibrium among these cattle. The common SNPs of BovineHD and 54K SNP Chips were also extracted and evaluated for their performance. Only 40%−50% SNPs of these arrays was found informative for genetic analysis in these cattle breeds. The overall mean of MAF for SNPs of BovineHD SNPChip was 0.248 ± 0.006, 0.241 ± 0.007, and 0.242 ± 0.009 in Sahiwal, Tharparkar and Gir, respectively, while that for 54K SNPs was on lower side. The average Reynold’s genetic distance between breeds ranged from 0.042 to 0.055 based on BovineHD Beadchip, and from 0.052 to 0.084 based on 54K SNP Chip. The estimates of genetic diversity based on HD and 54K chips were almost same and, hence, low density chip seems to be good enough to decipher genetic diversity of these cattle breeds. The linkage disequilibrium started decaying (r2 < 0.2) at 140 kb inter-marker distance and, hence, a 20K low density customized SNP array from HD chip could be designed for genomic selection in these cattle else the 54K Bead Chip as such will be useful.

Towards a whole-genome sequence for rye (Secale cereale L.).

We report on a whole-genome draft sequence of rye (Secale cereale L.). Rye is a diploid Triticeae species closely related to wheat and barley, and an important crop for food and feed in Central and Eastern Europe. Through whole-genome shotgun sequencing of the 7.9-Gbp genome of the winter rye inbred line Lo7 we obtained a de novo assembly represented by 1.29 million scaffolds covering a total length of 2.8Gbp. Our reference sequence represents nearly the entire low-copy portion of the rye genome. This genome assembly was used to predict 27784 rye gene models based on homology to sequenced grass genomes. Through resequencing of 10 rye inbred lines and one accession of the wild relative S.vavilovii, we discovered more than 90 million single nucleotide variants and short insertions/deletions in the rye genome. From these variants, we developed the high-density Rye600k genotyping array with 600843 markers, which enabled anchoring the sequence contigs along a high-density genetic map and establishing a synteny-based virtual gene order. Genotyping data were used to characterize the diversity of rye breeding pools and genetic resources, and to obtain a genome-wide map of selection signals differentiating the divergent gene pools. This rye whole-genome sequence closes a gap in Triticeae genome research, and will be highly valuable for comparative genomics, functional studies and genome-based breeding in rye.

High-Density SNP Genotyping Array for Hexaploid Wheat and Its Relatives.

A lack of genetic diversity between wheat breeding lines has been recognized as a significant block to future yield increases. Wheat breeding and prebreeding strategies are increasingly using material from wheat ancestors or wild relatives to reintroduce diversity. Where molecular markers are polymorphic between the host and introgressed material, they may be used to track the size and location of the introgressed material through generations of backcrossing. To generate markers for this purpose, sequence capture targeted resequencing was carried out for a range of wheat varieties, wheat relatives, and wheat progenitors. From these sequences, putative SNPs were identified and used to generate the Axiom® Wheat HD array. A selection of varieties representing a selection of elite wheat breeding material, progenitor species, and wild relatives were used to validate the array. The procedures used are described here in detail.