SNP development from RNA‐seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA‐seq is one such technique for the discovery of SNPs and development of markers for large‐scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black‐faced blenny), a small rocky‐shore fish from the Mediterranean Sea. RNA‐seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time‐consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.     

A 34K SNP genotyping array for Populus trichocarpa: Design,application to the study of natural populations and transferability to other Populus species

Genetic mapping of quantitative traits requires genotypic data for large numbers of markers in many individuals. For such studies, the use of large single nucleotide polymorphism (SNP) genotyping arrays still offers the most cost‐effective solution. Herein we report on the design and performance of a SNP genotyping array for Populus trichocarpa (black cottonwood). This genotyping array was designed with SNPs pre‐ascertained in 34 wild accessions covering most of the species latitudinal range. We adopted a candidate gene approach to the array design that resulted in the selection of 34 131 SNPs, the majority of which are located in, or within 2 kb of, 3543 candidate genes. A subset of the SNPs on the array (539) was selected based on patterns of variation among the SNP discovery accessions. We show that more than 95% of the loci produce high quality genotypes and that the genotyping error rate for these is likely below 2%. We demonstrate that even among small numbers of samples (n = 10) from local populations over 84% of loci are polymorphic. We also tested the applicability of the array to other species in the genus and found that the number of polymorphic loci decreases rapidly with genetic distance, with the largest numbers detected in other species in section Tacamahaca. Finally, we provide evidence for the utility of the array to address evolutionary questions such as intraspecific studies of genetic differentiation, species assignment and the detection of natural hybrids.     

SNP discovery in wild and domesticated populations of blue catfish,Ictalurus furcatus,using genotyping‐by‐sequencing and subsequent SNP validation

Blue catfish, Ictalurus furcatus, are valued in the United States as a trophy fishery for their capacity to reach large sizes, sometimes exceeding 45 kg. Additionally, blue catfish × channel catfish (I. punctatus) hybrid food fish production has recently increased the demand for blue catfish broodstock. However, there has been little study of the genetic impacts and interaction of farmed, introduced and stocked populations of blue catfish. We utilized genotyping‐by‐sequencing (GBS) to capture and genotype SNP markers on 190 individuals from five wild and domesticated populations (Mississippi River, Missouri, D&B, Rio Grande and Texas). Stringent filtering of SNP‐calling parameters resulted in 4275 SNP loci represented across all five populations. Population genetics and structure analyses revealed potential shared ancestry and admixture between populations. We utilized the Sequenom MassARRAY to validate two multiplex panels of SNPs selected from the GBS data. Selection criteria included SNPs shared between populations, SNPs specific to populations, number of reads per individual and number of individuals genotyped by GBS. Putative SNPs were validated in the discovery population and in two additional populations not used in the GBS analysis. A total of 64 SNPs were genotyped successfully in 191 individuals from nine populations. Our results should guide the development of highly informative, flexible genotyping multiplexes for blue catfish from the larger GBS SNP set as well as provide an example of a rapid, low‐cost approach to generate and genotype informative marker loci in aquatic species with minimal previous genetic information.     

Power of a dual‐use SNP panel for pedigree reconstruction and population assignment

The use of high‐throughput, low‐density sequencing approaches has dramatically increased in recent years in studies of eco‐evolutionary processes in wild populations and domestication in commercial aquaculture. Most of these studies focus on identifying panels of SNP loci for a single downstream application, whereas there have been few studies examining the trade‐offs for selecting panels of markers for use in multiple applications. Here, we detail the use of a bioinformatic workflow for the development of a dual‐purpose SNP panel for parentage and population assignment, which included identifying putative SNP loci, filtering for the most informative loci for the two tasks, designing effective multiplex PCR primers, optimizing the SNP panel for performance, and performing quality control steps for downstream applications. We applied this workflow to two adjacent Alaskan Sockeye Salmon populations and identified a GTseq panel of 142 SNP loci for parentage and 35 SNP loci for population assignment. Only 50–75 panel loci were necessary for >95% accurate parentage, whereas population assignment success, with all 172 panel loci, ranged from 93.9% to 96.2%. Finally, we discuss the trade‐offs and complexities of the decision‐making process that drives SNP panel development, optimization, and testing.     

Increasing the accuracy of genomic prediction in pure‐bred Limousin beef cattle by including cross‐bred Limousin data and accounting for an F94L variant in MSTN

Explicitly fitting effects for major genes or QTL that account for a large percentage of variation in a whole genomic prediction model may increase prediction accuracy. This study compared approaches to account for a major effect of an F94L variant in the MSTN gene within the genomic prediction using bovine whole‐genomic SNP markers. Among the beef cattle breeds, Limousin have been known to have an F94L variant that is not present in Angus. The reference population in this study consisted of 3060 beef cattle including pure‐bred Limousin (PL), cross‐bred Limousin with Angus (LF) and pure‐bred Angus, genotyped using a BovineSNP50 BeadChip and directly for the MSTN‐F94L variant. We compared prediction accuracies in PL animals using the three datasets from only the PL population, admixed PL and LF (AL) or multibreed analysis using all of the PL, LF and Angus (MB) population according to four‐fold cross‐validation after K‐means clustering. The MSTN‐F94L variant was the most strongly associated with five traits (birth weight, calving ease direct, milk, weaning weight and yield grade) among the 13 measured traits in PL and AL populations. Fitting the MSTN‐F94L variant as a random effect, the genomic prediction accuracies for birth weight increased by 2.7% in PL, by 2.2% in AL and by 3.2% in MB. Prediction accuracies for five traits increased in the MB analysis. Fitting MSTN‐F94L as a fixed effect in PL, AL and MB analyses resulted in increased prediction accuracy in PL for eight traits. Prediction accuracies can be improved by including a causal variant in genomic evaluation compared with simply using whole‐genome SNP markers. Fitting the causal variant as a fixed effect along with markers fitted as random effects resulted in greater prediction accuracies for most traits. Causal variants should be genotyped along with SNP markers.     

Discovery and characterization of novel genetic markers for use in the management of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi)

The Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) is threatened by habitat destruction, over‐harvest and hybridization with nonnative trout. Currently, three Geographic Management Units (GMUs) are recognized within the taxon. Here, we describe a suite of 68 single‐nucleotide polymorphism (SNP) genetic markers for use in the study and management of Lahontan cutthroat trout and a closely related subspecies, the Paiute cutthroat trout (O. c. seleneris). These include markers variable within the two subspecies (n = 35), diagnostic for the two subspecies (n = 23) and diagnostic for Yellowstone cutthroat trout (O. c. bouvieri) and other closely related subspecies (n = 10). Sixty‐three markers were discovered by Sanger sequencing of 171 EST loci in an ascertainment panel including Lahontan cutthroat trout from four populations representing all GMUs. Five markers were identified in a secondary sequencing effort with a single population of Lahontan cutthroat trout. TaqMan assays were validated on six Lahontan cutthroat trout populations and a diverse panel of other trout. Over 90% of the markers variable in Lahontan cutthroat trout were polymorphic in at least two populations, and 66% were variable within all three GMUs. All Lahontan diagnostic markers were also fixed for the Lahontan allele in Paiute cutthroat trout. Most of the Yellowstone diagnostic markers can also be used for this purpose in other cutthroat trout subspecies. This is the first set of SNP markers to be developed for Lahontan cutthroat trout, and will be an important tool for conservation and management.     

Haplotype‐based genotyping‐by‐sequencing in oat genome research

In a de novo genotyping‐by‐sequencing (GBS) analysis of short, 64‐base tag‐level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag‐level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635‐line diversity panel were used to infer chromosome‐level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high‐resolution genome analysis and genomic selection in oats. A combined genome‐wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component‐based genome‐wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS‐derived markers facilitate genome analysis and genomic selection in oat.     

Genome‐wide detection of genetic loci and candidate genes for teat number and body conformation traits at birth in Chinese Sushan pigs

Body conformation at birth and teat number are economically important traits in the pig industry, as these traits are usually explored to evaluate the growth and reproductive potential of piglets. To detect genetic loci and candidate genes for these traits, we performed a GWAS on 269 pigs from a recently developed Chinese breed (Sushan) using 38  128 informative SNPs on the Affymetrix Porcine SNP 55K Array. In total, we detected one genome‐wide significant (P = 1.31e‐6) SNP for teat number on chromosome X and 15 chromosome‐wide significant SNPs for teat number, body weight, body length, chest circumference and cannon circumference at birth on chromosomes 1, 3, 4, 6, 7, 9, 10, 13, 14, 15, 17 and 18. The most significant SNP had an additive effect of 0.74 × total teat number, explaining 20% of phenotypic variance. Five significant SNPs resided in the previously reported quantitative trait loci for these traits and seven significant SNPs had a pleiotropic effect on multiple traits. Intriguingly, 12 of the genes nearest to the significant SNPs are functionally related to body conformation and teat number traits, including SPRED2, MKX, TMSB4X and ESR1. GO analysis revealed that candidate genes proximal to the significant SNPs were enriched in the G‐protein coupled receptor and steroid hormone‐mediated signaling pathway. Our findings shed light on the genetic basis of the measured traits and provide molecular markers especially for the genetic improvement of teat number in Sushan and related pigs.     

Assessment of genetic diversity and population structure in cultured Australian Pacific oysters

The recent development of Pacific oyster (Crassostrea gigas) SNP genotyping arrays has allowed detailed characterisation of genetic diversity and population structure within and between oyster populations. It also raises the potential of harnessing genomic selection for genetic improvement in oyster breeding programmes. The aim of this study was to characterise a breeding population of Australian oysters through genotyping and analysis of 18 027 SNPs, followed by comparison with genotypes of oyster sampled from Europe and Asia. This revealed that the Australian populations had similar population diversity (H_E) to oysters from New Zealand, the British Isles, France and Japan. Population divergence was assessed using PCA of genetic distance and revealed that Australian oysters were distinct from all other populations tested. Australian Pacific oysters originate from planned introductions sourced from three Japanese populations. Approximately 95% of these introductions were from geographically, and potentially genetically, distinct populations from the Nagasaki oysters assessed in this study. Finally, in preparation for the application of genomic selection in oyster breeding programmes, the strength of LD was evaluated and subsets of loci were tested for their ability to accurately infer relationships. Weak LD was observed on average; however, SNP subsets were shown to accurately reconstitute a genomic relationship matrix constructed using all loci. This suggests that low‐density SNP panels may have utility in the Australian population tested, and the findings represent an important first step towards the design and implementation of genomic approaches for applied breeding in Pacific oysters.     

Cross‐platform compatibility of de novo‐aligned SNPs in a nonmodel butterfly genus

High‐throughput sequencing methods for genotyping genome‐wide markers are being rapidly adopted for phylogenetics of nonmodel organisms in conservation and biodiversity studies. However, the reproducibility of SNP genotyping and degree of marker overlap or compatibility between datasets from different methodologies have not been tested in nonmodel systems. Using double‐digest restriction site‐associated DNA sequencing, we sequenced a common set of 22 specimens from the butterfly genus Speyeria on two different Illumina platforms, using two variations of library preparation. We then used a de novo approach to bioinformatic locus assembly and SNP discovery for subsequent phylogenetic analyses. We found a high rate of locus recovery despite differences in library preparation and sequencing platforms, as well as overall high levels of data compatibility after data processing and filtering. These results provide the first application of NGS methods for phylogenetic reconstruction in Speyeria and support the use and long‐term viability of SNP genotyping applications in nonmodel systems.     

Resistance gene enrichment sequencing (RenSeq) enables reannotation of the NB‐LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations

RenSeq is a NB‐LRR (nucleotide binding‐site leucine‐rich repeat) gene‐targeted, Resistance gene enrichment and sequencing method that enables discovery and annotation of pathogen resistance gene family members in plant genome sequences. We successfully applied RenSeq to the sequenced potato Solanum tuberosum clone DM, and increased the number of identified NB‐LRRs from 438 to 755. The majority of these identified R gene loci reside in poorly or previously unannotated regions of the genome. Sequence and positional details on the 12 chromosomes have been established for 704 NB‐LRRs and can be accessed through a genome browser that we provide. We compared these NB‐LRR genes and the corresponding oligonucleotide baits with the highest sequence similarity and demonstrated that ~80% sequence identity is sufficient for enrichment. Analysis of the sequenced tomato S. lycopersicum ‘Heinz 1706’ extended the NB‐LRR complement to 394 loci. We further describe a methodology that applies RenSeq to rapidly identify molecular markers that co‐segregate with a pathogen resistance trait of interest. In two independent segregating populations involving the wild Solanum species S. berthaultii (Rpi‐ber2) and S. ruiz‐ceballosii (Rpi‐rzc1), we were able to apply RenSeq successfully to identify markers that co‐segregate with resistance towards the late blight pathogen Phytophthora infestans. These SNP identification workflows were designed as easy‐to‐adapt Galaxy pipelines.     

Genome‐wide association study for body weight in cattle populations from Siberia

Body weight is a complex trait in cattle associated with commonly used commercial breeding measurements related to growth. Although many quantitative trait loci (QTL) for body weight have been identified in cattle so far, searching for genetic determinants in different breeds or environments is promising. Therefore, we carried out a genome‐wide association study (GWAS) in two cattle populations from the Russian Federation (Siberian region) using the GGP HD150K array containing 139 376 single nucleotide polymorphism (SNP) markers. Association tests for 107 550 SNPs left after filtering revealed five statistically significant SNPs on BTA5, considering a false discovery rate of less than 0.05. The chromosomal region containing these five SNPs contains the CCND2 gene, which was previously associated with average daily weight gain and body mass index in US beef cattle populations and in humans respectively. Our study is the first GWAS for body weight in beef cattle populations from the Russian Federation. The results provided here suggest that, despite the existence of breed‐ and species‐specific QTL, the genetic architecture of body weight could be evolutionarily conserved in mammals.     

Single nucleotide polymorphism discovery in albacore and Atlantic bluefin tuna provides insights into worldwide population structure

The optimal management of the commercially important, but mostly over‐exploited, pelagic tunas, albacore (Thunnus alalunga Bonn., 1788) and Atlantic bluefin tuna (BFT; Thunnus thynnus L., 1758), requires a better understanding of population structure than has been provided by previous molecular methods. Despite numerous studies of both species, their population structures remain controversial. This study reports the development of single nucleotide polymorphisms (SNPs) in albacore and BFT and the application of these SNPs to survey genetic variability across the geographic ranges of these tunas. A total of 616 SNPs were discovered in 35 albacore tuna by comparing sequences of 54 nuclear DNA fragments. A panel of 53 SNPs yielded F_ST values ranging from 0.0 to 0.050 between samples after genotyping 460 albacore collected throughout the distribution of this species. No significant heterogeneity was detected within oceans, but between‐ocean comparisons (Atlantic, Pacific and Indian oceans along with Mediterranean Sea) were significant. Additionally, a 17‐SNP panel was developed in Atlantic BFT by cross‐species amplification in 107 fish. This limited number of SNPs discriminated between samples from the two major spawning areas of Atlantic BFT (F_ST = 0.116). The SNP markers developed in this study can be used to genotype large numbers of fish without the need for standardizing alleles among laboratories.     

Characterizing genic and nongenic molecular markers: comparison of microsatellites and SNPs

The implications of transitioning to single nucleotide polymorphism (SNPs) from microsatellite markers (MSs) have been investigated in a number of population genetics studies, but the effect of genomic location on the amount of information each type of marker reveals has not been explored in detail. We developed novel SNP markers flanking 1 kb regions of 13 genic (within gene or <1 kb away from gene) and 13 nongenic (>10 kb from annotated gene) MSs in the threespine stickleback genome to obtain comparable data for both types of markers. We analysed patterns of genetic diversity and divergence on various geographic scales after converting the SNP loci within each genomic region into haplotypes. Marker type (SNP haplotype or MS) and location (genic or nongenic) significantly affected most estimates of population diversity and divergence. Between‐lineage divergence was significantly higher in SNP haplotypes (genic and nongenic), however, within‐lineage divergence was similar between marker types. Most divergence and diversity measures were uncorrelated between markers, except for population differentiation which was correlated between MSs and SNP haplotypes (both genic and nongenic). Broad‐scale population structure and assignment were similarly resolved by both marker types, however, only the MSs were able to delimit fine‐scale population structuring, particularly when genic and nongenic markers were combined. These results demonstrate that estimates of genetic variability and differentiation among populations can be strongly influenced by marker type, their genomic location in relation to genes and by the interaction of these two factors. This highlights the importance of having an awareness of the inherent strengths and limitations associated with different molecular tools to select the most appropriate methods for accurately addressing various ecological and evolutionary questions.     

Immunochip analysis identifies association of the RAD50/IL13 region with human longevity

Human longevity is characterized by a remarkable lack of confirmed genetic associations. Here, we report on the identification of a novel locus for longevity in the RAD50/IL13 region on chromosome 5q31.1 using a combined European sample of 3208 long‐lived individuals (LLI) and 8919 younger controls. First, we performed a large‐scale association study on 1458 German LLI (mean age 99.0 years) and 6368 controls (mean age 57.2 years) by targeting known immune‐associated loci covered by the Immunochip. The analysis of 142 136 autosomal single nucleotide polymorphisms (SNPs) revealed an Immunochip‐wide significant signal (P_Immunochip = 7.01 × 10^–9) for the SNP rs2075650 in the TOMM40/APOE region, which has been previously described in the context of human longevity. To identify novel susceptibility loci, we selected 15 markers with P_Immunochip < 5 × 10^–4 for replication in two samples from France (1257 LLI, mean age 102.4 years; 1811 controls, mean age 49.1 years) and Denmark (493 LLI, mean age 96.2 years; 740 controls, mean age 63.1 years). The association at SNP rs2706372 replicated in the French study collection and showed a similar trend in the Danish participants and was also significant in a meta‐analysis of the combined French and Danish data after adjusting for multiple testing. In a meta‐analysis of all three samples, rs2706372 reached a P‐value of P_{Immunochip+Repl} = 5.42 × 10^?7 (OR = 1.20; 95% CI = 1.12–1.28). SNP rs2706372 is located in the extended RAD50/IL13 region. RAD50 seems a plausible longevity candidate due to its involvement in DNA repair and inflammation. Further studies are needed to identify the functional variant(s) that predispose(s) to a long and healthy life.     

Single‐nucleotide polymorphism discovery and diversity in the model legume Medicago truncatula

Extensive genomic resources are available in the model legume Medicago truncatula. Here, we present the discovery and design of the first array of single‐nucleotide polymorphism (SNP) markers in M. truncatula through large‐scale Sanger resequencing of genomic fragments spanning the genome, in a diverse panel of 16 M. truncatula accessions. Both anonymous fragments and fragments targeting candidate genes for flowering phenology and symbiosis were surveyed for nucleotide variation in almost 230 kb of unique genomic regions. A set of 384 SNP markers was designed for an Illumina's GoldenGate assay, genotyped on a collection of 192 inbred lines (CC192) representing the geographical range of the species and used to survey the diversity of two natural populations. Finally, 86% of the tested SNPs were of high quality and exhibited polymorphism in the CC192 collection. Even at the population level, we detected polymorphism for more than 50% of the selected SNPs. Analysis of the allele frequency spectrum in the CC192 showed a reduced ascertainment bias, mostly limited to very rare alleles (frequency <0.01). The substantial polymorphism detected at the species and population levels, the high marker quality and the potential to survey large samples of individuals make this set of SNP markers a valuable tool to improve our understanding of the effect of demographic and selective factors that shape the natural genetic diversity within the selfing species Medicago truncatula.     

Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering

Pedigree and sibship reconstruction are important methods in quantifying relationships and fitness of individuals in natural populations. Current methods employ a Markov chain‐based algorithm to explore plausible possible pedigrees iteratively. This provides accurate results, but is time‐consuming. Here, we develop a method to infer sibship and paternity relationships from half‐sibling arrays of known maternity using hierarchical clustering. Given 50 or more unlinked SNP markers and empirically derived error rates, the method performs as well as the widely used package Colony, but is faster by two orders of magnitude. Using simulations, we show that the method performs well across contrasting mating scenarios, even when samples are large. We then apply the method to open‐pollinated arrays of the snapdragon Antirrhinum majus and find evidence for a high degree of multiple mating. Although we focus on diploid SNP data, the method does not depend on marker type and as such has broad applications in nonmodel systems.     

Fast and cost‐effective single nucleotide polymorphism (SNP) detection in the absence of a reference genome using semideep next‐generation Random Amplicon Sequencing (RAMseq)

Biodiversity has suffered a dramatic global decline during the past decades, and monitoring tools are urgently needed providing data for the development and evaluation of conservation efforts both on a species and on a genetic level. However, in wild species, the assessment of genetic diversity is often hampered by the lack of suitable genetic markers. In this article, we present Random Amplicon Sequencing (RAMseq), a novel approach for fast and cost‐effective detection of single nucleotide polymorphisms (SNPs) in nonmodel species by semideep sequencing of random amplicons. By applying RAMseq to the Eurasian otter (Lutra lutra), we identified 238 putative SNPs after quality filtering of all candidate loci and were able to validate 32 of 77 loci tested. In a second step, we evaluated the genotyping performance of these SNP loci in noninvasive samples, one of the most challenging genotyping applications, by comparing it with genotyping results of the same faecal samples at microsatellite markers. We compared (i) polymerase chain reaction (PCR) success rate, (ii) genotyping errors and (iii) Mendelian inheritance (population parameters). SNPs produced a significantly higher PCR success rate (75.5% vs. 65.1%) and lower mean allelic error rate (8.8% vs. 13.3%) than microsatellites, but showed a higher allelic dropout rate (29.7% vs. 19.8%). Genotyping results showed no deviations from Mendelian inheritance in any of the SNP loci. Hence, RAMseq appears to be a valuable tool for the detection of genetic markers in nonmodel species, which is a common challenge in conservation genetic studies.     

A large‐scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.