Development and validation of the Axiom®Apple480K SNP genotyping array

Cultivated apple (Malus × domestica Borkh.) is one of the most important fruit crops in temperate regions, and has great economic and cultural value. The apple genome is highly heterozygous and has undergone a recent duplication which, combined with a rapid linkage disequilibrium decay, makes it difficult to perform genome‐wide association (GWA) studies. Single nucleotide polymorphism arrays offer highly multiplexed assays at a relatively low cost per data point and can be a valid tool for the identification of the markers associated with traits of interest. Here, we describe the development and validation of a 487K SNP Affymetrix Axiom^® genotyping array for apple and discuss its potential applications. The array has been built from the high‐depth resequencing of 63 different cultivars covering most of the genetic diversity in cultivated apple. The SNPs were chosen by applying a focal points approach to enrich genic regions, but also to reach a uniform coverage of non‐genic regions. A total of 1324 apple accessions, including the 92 progenies of two mapping populations, have been genotyped with the Axiom^®Apple480K to assess the effectiveness of the array. A large majority of SNPs (359 994 or 74%) fell in the stringent class of poly high resolution polymorphisms. We also devised a filtering procedure to identify a subset of 275K very robust markers that can be safely used for germplasm surveys in apple. The Axiom^®Apple480K has now been commercially released both for public and proprietary use and will likely be a reference tool for GWA studies in apple.     

Sequence‐based SNP genotyping in durum wheat

Marker development for marker‐assisted selection in plant breeding is increasingly based on next‐generation sequencing (NGS). However, marker development in crops with highly repetitive, complex genomes is still challenging. Here we applied sequence‐based genotyping (SBG), which couples AFLP^®‐based complexity reduction to NGS, for de novo single nucleotide polymorphisms (SNP) marker discovery in and genotyping of a biparental durum wheat population. We identified 9983 putative SNPs in 6372 contigs between the two parents and used these SNPs for genotyping 91 recombinant inbred lines (RILs). Excluding redundant information from multiple SNPs per contig, 2606 (41%) markers were used for integration in a pre‐existing framework map, resulting in the integration of 2365 markers over 2607 cM. Of the 2606 markers available for mapping, 91% were integrated in the pre‐existing map, containing 708 SSRs, DArT markers, and SNPs from CRoPS technology, with a map‐size increase of 492 cM (23%). These results demonstrate the high quality of the discovered SNP markers. With this methodology, it was possible to saturate the map at a final marker density of 0.8 cM/marker. Looking at the binned marker distribution (Figure 2), 63 of the 268 10‐cM bins contained only SBG markers, showing that these markers are filling in gaps in the framework map. As to the markers that could not be used for mapping, the main reason was the low sequencing coverage used for genotyping. We conclude that SBG is a valuable tool for efficient, high‐throughput and high‐quality marker discovery and genotyping for complex genomes such as that of durum wheat.     

Characterization of a Wheat Breeders’ Array suitable for high‐throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivum)

Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism‐based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high‐density Affymetrix Axiom^® genotyping array (the Wheat Breeders’ Array), in a high‐throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders’ Array is also suitable for generating high‐density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site ‘CerealsDB’.     

High-Throughput SNP Discovery and Genotyping for Constructing a Saturated Linkage Map of Chickpea (Cicer arietinum L.)

The present study reports the large-scale discovery of genome-wide single-nucleotide polymorphisms (SNPs) in chickpea, identified mainly through the next generation sequencing of two genotypes, i.e. Cicer arietinum ICC4958 and its wild progenitor C. reticulatum PI489777, parents of an inter-specific reference mapping population of chickpea. Development and validation of a high-throughput SNP genotyping assay based on Illumina''s GoldenGate Genotyping Technology and its application in building a high-resolution genetic linkage map of chickpea is described for the first time. In this study, 1022 SNPs were identified, of which 768 high-confidence SNPs were selected for designing the custom Oligo Pool All (CpOPA-I) for genotyping. Of these, 697 SNPs could be successfully used for genotyping, demonstrating a high success rate of 90.75%. Genotyping data of the 697 SNPs were compiled along with those of 368 co-dominant markers mapped in an earlier study, and a saturated genetic linkage map of chickpea was constructed. One thousand and sixty-three markers were mapped onto eight linkage groups spanning 1808.7 cM (centiMorgans) with an average inter-marker distance of 1.70 cM, thereby representing one of the most advanced maps of chickpea. The map was used for the synteny analysis of chickpea, which revealed a higher degree of synteny with the phylogenetically close Medicago than with soybean. The first set of validated SNPs and map resources developed in this study will not only facilitate QTL mapping, genome-wide association analysis and comparative mapping in legumes but also help anchor scaffolds arising out of the whole-genome sequencing of chickpea.     

Genetic dissection of drought tolerance in chickpea (Cicer arietinum L.)

Key message

Analysis of phenotypic data for 20 drought tolerance traits in 1–7 seasons at 1–5 locations together with genetic mapping data for two mapping populations provided 9 QTL clusters of which one present on CaLG04 has a high potential to enhance drought tolerance in chickpea improvement.

Abstract

Chickpea (Cicer arietinum L.) is the second most important grain legume cultivated by resource poor farmers in the arid and semi-arid regions of the world. Drought is one of the major constraints leading up to 50 % production losses in chickpea. In order to dissect the complex nature of drought tolerance and to use genomics tools for enhancing yield of chickpea under drought conditions, two mapping populations—ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261) segregating for drought tolerance-related root traits were phenotyped for a total of 20 drought component traits in 1–7 seasons at 1–5 locations in India. Individual genetic maps comprising 241 loci and 168 loci for ICCRIL03 and ICCRIL04, respectively, and a consensus genetic map comprising 352 loci were constructed (http://cmap.icrisat.ac.in/cmap/sm/cp/varshney/). Analysis of extensive genotypic and precise phenotypic data revealed 45 robust main-effect QTLs (M-QTLs) explaining up to 58.20 % phenotypic variation and 973 epistatic QTLs (E-QTLs) explaining up to 92.19 % phenotypic variation for several target traits. Nine QTL clusters containing QTLs for several drought tolerance traits have been identified that can be targeted for molecular breeding. Among these clusters, one cluster harboring 48 % robust M-QTLs for 12 traits and explaining about 58.20 % phenotypic variation present on CaLG04 has been referred as “QTL-hotspot”. This genomic region contains seven SSR markers (ICCM0249, NCPGR127, TAA170, NCPGR21, TR11, GA24 and STMS11). Introgression of this region into elite cultivars is expected to enhance drought tolerance in chickpea.     

QTL‐seq for rapid identification of candidate genes for 100‐seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea

Terminal drought is a major constraint to chickpea productivity. Two component traits responsible for reduction in yield under drought stress include reduction in seeds size and root length/root density. QTL‐seq approach, therefore, was used to identify candidate genomic regions for 100‐seed weight (100SDW) and total dry root weight to total plant dry weight ratio (RTR) under rainfed conditions. Genomewide SNP profiling of extreme phenotypic bulks from the ICC 4958 × ICC 1882 population identified two significant genomic regions, one on CaLG01 (1.08 Mb) and another on CaLG04 (2.7 Mb) linkage groups for 100SDW. Similarly, one significant genomic region on CaLG04 (1.10 Mb) was identified for RTR. Comprehensive analysis revealed four and five putative candidate genes associated with 100SDW and RTR, respectively. Subsequently, two genes (Ca_04364 and Ca_04607) for 100SDW and one gene (Ca_04586) for RTR were validated using CAPS/dCAPS markers. Identified candidate genomic regions and genes may be useful for molecular breeding for chickpea improvement.     

Genomewide single nucleotide polymorphism discovery in Atlantic salmon (Salmo salar): validation in wild and farmed American and European populations

A considerable number of single nucleotide polymorphisms (SNPs) are required to elucidate genotype–phenotype associations and determine the molecular basis of important traits. In this work, we carried out de novo SNP discovery accounting for both genome duplication and genetic variation from American and European salmon populations. A total of 9 736 473 nonredundant SNPs were identified across a set of 20 fish by whole‐genome sequencing. After applying six bioinformatic filtering steps, 200 K SNPs were selected to develop an Affymetrix Axiom^® myDesign Custom Array. This array was used to genotype 480 fish representing wild and farmed salmon from Europe, North America and Chile. A total of 159 099 (79.6%) SNPs were validated as high quality based on clustering properties. A total of 151 509 validated SNPs showed a unique position in the genome. When comparing these SNPs against 238 572 markers currently available in two other Atlantic salmon arrays, only 4.6% of the SNP overlapped with the panel developed in this study. This novel high‐density SNP panel will be very useful for the dissection of economically and ecologically relevant traits, enhancing breeding programmes through genomic selection as well as supporting genetic studies in both wild and farmed populations of Atlantic salmon using high‐resolution genomewide information.     

Single‐nucleotide polymorphism discovery in Leptographium longiclavatum,a mountain pine beetle‐associated symbiotic fungus,using whole‐genome resequencing

Single‐nucleotide polymorphisms (SNPs) are rapidly becoming the standard markers in population genomics studies; however, their use in nonmodel organisms is limited due to the lack of cost‐effective approaches to uncover genome‐wide variation, and the large number of individuals needed in the screening process to reduce ascertainment bias. To discover SNPs for population genomics studies in the fungal symbionts of the mountain pine beetle (MPB), we developed a road map to discover SNPs and to produce a genotyping platform. We undertook a whole‐genome sequencing approach of Leptographium longiclavatum in combination with available genomics resources of another MPB symbiont, Grosmannia clavigera. We sequenced 71 individuals pooled into four groups using the Illumina sequencing technology. We generated between 27 and 30 million reads of 75 bp that resulted in a total of 1, 181 contigs longer than 2 kb and an assembled genome size of 28.9 Mb (N₅₀ = 48 kb, average depth = 125x). A total of 9052 proteins were annotated, and between 9531 and 17 266 SNPs were identified in the four pools. A subset of 206 genes (containing 574 SNPs, 11% false positives) was used to develop a genotyping platform for this species. Using this roadmap, we developed a genotyping assay with a total of 147 SNPs located in 121 genes using the Illumina^® Sequenom iPLEX Gold. Our preliminary genotyping (success rate = 85%) of 304 individuals from 36 populations supports the utility of this approach for population genomics studies in other MPB fungal symbionts and other fungal nonmodel species.     

Development,validation and genetic analysis of a large soybean SNP genotyping array

Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under‐use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high‐density genetic mapping and genome‐wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome‐wide association analyses. More than four million high‐quality SNPs identified from high‐depth genome re‐sequencing of 16 soybean accessions and low‐depth genome re‐sequencing of 31 soybean accessions were used to select 180 961 SNPs for creation of the Axiom^® SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170 223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene‐rich chromosomal regions suggest that this array may be suitable for genome‐wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.     

EST-derived genic molecular markers: development and utilization for generating an advanced transcript map of chickpea

Well-saturated linkage maps especially those based on expressed sequence tag (EST)-derived genic molecular markers (GMMs) are a pre-requisite for molecular breeding. This is especially true in important legumes such as chickpea where few simple sequence repeats (SSR) and even fewer GMM-based maps have been developed. Therefore, in this study, 2,496 ESTs were generated from chickpea seeds and utilized for the development of 487 novel EST-derived functional markers which included 125 EST-SSRs, 151 intron targeted primers (ITPs), 109 expressed sequence tag polymorphisms (ESTPs), and 102 single nucleotide polymorphisms (SNPs). Whereas EST-SSRs, ITPs, and ESTPs were developed by in silico analysis of the developed EST sequences, SNPs were identified by allele resequencing and their genotyping was performed using the Illumina GoldenGate Assay. Parental polymorphism was analyzed between C. arietinum ICC4958 and C. reticulatum PI489777, parents of the reference chickpea mapping population, using a total of 872 markers: 487 new gene-based markers developed in this study along with 385 previously published markers, of which 318 (36.5%) were found to be polymorphic and were used for genotyping. The genotypic data were integrated with the previously published data of 108 markers and an advanced linkage map was generated that contained 406 loci distributed on eight linkage groups that spanned 1,497.7 cM. The average marker density was 3.68 cM and the average number of markers per LG was 50.8. Among the mapped markers, 303 new genomic locations were defined that included 177 gene-based and 126 gSSRs (genomic SSRs) thereby producing the most advanced gene-rich map of chickpea solely based on co-dominant markers.     

Single‐nucleotide polymorphism discovery and validation in high‐density SNP array for genetic analysis in European white oaks

An Illumina Infinium SNP genotyping array was constructed for European white oaks. Six individuals of Quercus petraea and Q. robur were considered for SNP discovery using both previously obtained Sanger sequences across 676 gene regions (1371 in vitro SNPs) and Roche 454 technology sequences from 5112 contigs (6542 putative in silico SNPs). The 7913 SNPs were genotyped across the six parental individuals, full‐sib progenies (one within each species and two interspecific crosses between Q. petraea and Q. robur) and three natural populations from south‐western France that included two additional interfertile white oak species (Q. pubescens and Q. pyrenaica). The genotyping success rate in mapping populations was 80.4% overall and 72.4% for polymorphic SNPs. In natural populations, these figures were lower (54.8% and 51.9%, respectively). Illumina genotype clusters with compression (shift of clusters on the normalized x‐axis) were detected in ~25% of the successfully genotyped SNPs and may be due to the presence of paralogues. Compressed clusters were significantly more frequent for SNPs showing a priori incorrect Illumina genotypes, suggesting that they should be considered with caution or discarded. Altogether, these results show a high experimental error rate for the Infinium array (between 15% and 20% of SNPs potentially unreliable and 10% when excluding all compressed clusters), and recommendations are proposed when applying this type of high‐throughput technique. Finally, results on diversity levels and shared polymorphisms across targeted white oaks and more distant species of the Quercus genus are discussed, and perspectives for future comparative studies are proposed.     

Development of marker sets useful in the early selection of <Emphasis Type="Italic">Ren4</Emphasis> powdery mildew resistance and seedlessness for table and raisin grape breeding

The single, dominant powdery mildew resistance locus Ren4 from Vitis romanetii prevents hyphal growth by Erysiphe necator. Previously, we showed that when introgressed into V. vinifera in the modified BC₂ population 03-3004, Ren4 was linked with the simple sequence repeat marker VMC7f2 on chromosome 18—a marker that is associated with multiple disease resistance and seedlessness. However, in the current study, this marker was monomorphic in related breeding populations 05-3010 and 07-3553. To enhance marker-assisted selection at this locus, we developed multiplexed SNP markers using three approaches: conversion of bulked segregant analysis AFLP markers, sequencing of candidate genes and regions flanking known V. vinifera SNPs, and hybridization to the Vitis9KSNP genotyping array. The Vitis9KSNP array was more cost-efficient than all other approaches tested for marker discovery and genotyping, enabling the genotyping of 1317 informative SNPs within the span of 1 week and at a cost of 11 cents per SNP. From a total of 1,446 high quality, informative markers segregating in 03-3004, we developed a haplotype signature of 15 multiplexed SNP markers linked with Ren4 in 03-3004, 5 of which were linked in 05-3010, and 6 of which were linked in 07-3553. Two of these populations segregated for seedlessness, which was tightly linked with Ren4 in 03-3004 (2 cM) but not in 05-3010 (22 cM). Chromosomal rearrangements were detected among these three populations and the reference genome PN40024. Since this is the first application of the Vitis9KSNP array in a breeding program, some suggestions are provided for application of genotyping arrays. Our results provide novel markers for tracking and pyramiding this unique resistance gene and for further functional characterization of this region on chromosome 18 encoding multiple disease resistance and seedlessness.     

Development of an integrated 200K SNP genotyping array and application for genetic mapping,genome assembly improvement and genome wide association studies in pear (Pyrus)

Pear (Pyrus; 2n = 34), the third most important temperate fruit crop, has great nutritional and economic value. Despite the availability of many genomic resources in pear, it is challenging to genotype novel germplasm resources and breeding progeny in a timely and cost‐effective manner. Genotyping arrays can provide fast, efficient and high‐throughput genetic characterization of diverse germplasm, genetic mapping and breeding populations. We present here 200K AXIOM^® PyrSNP, a large‐scale single nucleotide polymorphism (SNP) genotyping array to facilitate genotyping of Pyrus species. A diverse panel of 113 re‐sequenced pear genotypes was used to discover SNPs to promote increased adoption of the array. A set of 188 diverse accessions and an F₁ population of 98 individuals from ‘Cuiguan’ × ‘Starkrimson’ was genotyped with the array to assess its effectiveness. A large majority of SNPs (166 335 or 83%) are of high quality. The high density and uniform distribution of the array SNPs facilitated prediction of centromeric regions on 17 pear chromosomes, and significantly improved the genome assembly from 75.5% to 81.4% based on genetic mapping. Identification of a gene associated with flowering time and candidate genes linked to size of fruit core via genome wide association studies showed the usefulness of the array in pear genetic research. The newly developed high‐density SNP array presents an important tool for rapid and high‐throughput genotyping in pear for genetic map construction, QTL identification and genomic selection.     

Rapid identification of homozygosity and site of wild relative introgressions in wheat through chromosome‐specific KASP genotyping assays

For future food security, it is important that wheat, one of the most widely consumed crops in the world, can survive the threat of abiotic and biotic stresses. New genetic variation is currently being introduced into wheat through introgressions from its wild relatives. For trait discovery, it is necessary that each introgression is homozygous and hence stable. Breeding programmes rely on efficient genotyping platforms for marker‐assisted selection (MAS). Recently, single nucleotide polymorphism (SNP)‐based markers have been made available on high‐throughput Axiom^® SNP genotyping arrays. However, these arrays are inflexible in their design and sample numbers, making their use unsuitable for long‐term MAS. SNPs can potentially be converted into Kompetitive allele‐specific PCR (KASP?) assays that are comparatively cost‐effective and efficient for low‐density genotyping of introgression lines. However, due to the polyploid nature of wheat, KASP assays for homoeologous SNPs can have difficulty in distinguishing between heterozygous and homozygous hybrid lines in a backcross population. To identify co‐dominant SNPs, that can differentiate between heterozygotes and homozygotes, we PCR‐amplified and sequenced genomic DNA from potential single‐copy regions of the wheat genome and compared them to orthologous copies from different wild relatives. A panel of 620 chromosome‐specific KASP assays have been developed that allow rapid detection of wild relative segments and provide information on their homozygosity and site of introgression in the wheat genome. A set of 90 chromosome‐nonspecific assays was also produced that can be used for genotyping introgression lines. These multipurpose KASP assays represent a powerful tool for wheat breeders worldwide.     

RNA‐Seq bulked segregant analysis enables the identification of high‐resolution genetic markers for breeding in hexaploid wheat

The identification of genetic markers linked to genes of agronomic importance is a major aim of crop research and breeding programmes. Here, we identify markers for Yr15, a major disease resistance gene for wheat yellow rust, using a segregating F₂ population. After phenotyping, we implemented RNA sequencing (RNA‐Seq) of bulked pools to identify single‐nucleotide polymorphisms (SNP) associated with Yr15. Over 27 000 genes with SNPs were identified between the parents, and then classified based on the results from the sequenced bulks. We calculated the bulk frequency ratio (BFR) of SNPs between resistant and susceptible bulks, selecting those showing sixfold enrichment/depletion in the corresponding bulks (BFR > 6). Using additional filtering criteria, we reduced the number of genes with a putative SNP to 175. The 35 SNPs with the highest BFR values were converted into genome‐specific KASP assays using an automated bioinformatics pipeline (PolyMarker) which circumvents the limitations associated with the polyploid wheat genome. Twenty‐eight assays were polymorphic of which 22 (63%) mapped in the same linkage group as Yr15. Using these markers, we mapped Yr15 to a 0.77‐cM interval. The three most closely linked SNPs were tested across varieties and breeding lines representing UK elite germplasm. Two flanking markers were diagnostic in over 99% of lines tested, thus providing a reliable haplotype for marker‐assisted selection in these breeding programmes. Our results demonstrate that the proposed methodology can be applied in polyploid F₂ populations to generate high‐resolution genetic maps across target intervals.     

Identification of the sex‐determining region in flathead grey mullet (Mugil cephalus)

Elucidation of the sex‐determination mechanism in flathead grey mullet (Mugil cephalus) is required to exploit its economic potential by production of genetically determined monosex populations and application of hormonal treatment to parents rather than to the marketed progeny. Our objective was to construct a first‐generation linkage map of the M. cephalus in order to identify the sex‐determining region and sex‐determination system. Deep‐sequencing data of a single male was assembled and aligned to the genome of Nile tilapia (Oreochromis niloticus). A total 245 M. cephalus microsatellite markers were designed, spanning the syntenic tilapia genome assembly at intervals of 10 Mb. In the mapping family of full‐sib progeny, 156 segregating markers were used to construct a first‐generation linkage map of 24 linkage groups (LGs), corresponding to the number of chromosomes. The linkage map spanned approximately 1200 cM with an average inter‐marker distance of 10.6 cM. Markers segregating on LG9 in two independent mapping families showed nearly complete concordance with gender (R² = 0.95). The sex determining locus was fine mapped within an interval of 8.6 cM on LG9. The sex of offspring was determined only by the alleles transmitted from the father, thus indicating an XY sex‐determination system.     

SNP‐based heritability and genetic architecture of tarsal osteochondrosis in North American Standardbred horses

Osteochondrosis is a common developmental orthopedic disease characterized by a failure of endochondral ossification. Standardbred horses are recognized as being predisposed to tarsal osteochondrosis. Prior heritability estimates for tarsal osteochondrosis in European Standardbreds and related trotting breeds have been based on pedigree data and range from 17–29%. Here, we report on genetic architecture and heritability based on high‐density genotyping data in a cohort of North American Standardbreds (n = 479) stringently phenotyped for tarsal osteochondrosis. Whole‐genome array genotyping data were imputed to ~2 million single nucleotide polymorphisms (SNPs). SNP‐based heritability of osteochondrosis in this population was explained by 2326 SNPs. The majority of these SNPs (86.6%) had small effects, whereas fewer SNPs had moderate or large effects (10% and 2.9% respectively), which is consistent with a polygenic/complex disease. Heritability was estimated at 0.24 ± 0.16 using two methods of restricted maximum likelihood analysis, as implemented in gcta (with and without a weighted relatedness matrix) and ldak software. Estimates were validated using bootstrapping. Heritability estimates were within the range previously reported and suggest that osteochondrosis is moderately heritable but that a significant portion of disease risk is due to environmental factors and/or genotype × environment interactions. Future identification of the genes/variants that have the most impact on disease risk may allow early recognition of high‐risk individuals.     

Evaluating the effective numbers of independent tests and significant <Emphasis Type="Italic">p</Emphasis>-value thresholds in commercial genotyping arrays and public imputation reference datasets

Current genome-wide association studies (GWAS) use commercial genotyping microarrays that can assay over a million single nucleotide polymorphisms (SNPs). The number of SNPs is further boosted by advanced statistical genotype-imputation algorithms and large SNP databases for reference human populations. The testing of a huge number of SNPs needs to be taken into account in the interpretation of statistical significance in such genome-wide studies, but this is complicated by the non-independence of SNPs because of linkage disequilibrium (LD). Several previous groups have proposed the use of the effective number of independent markers (M _e) for the adjustment of multiple testing, but current methods of calculation for M _e are limited in accuracy or computational speed. Here, we report a more robust and fast method to calculate M _e. Applying this efficient method [implemented in a free software tool named Genetic type 1 error calculator (GEC)], we systematically examined the M _e, and the corresponding p-value thresholds required to control the genome-wide type 1 error rate at 0.05, for 13 Illumina or Affymetrix genotyping arrays, as well as for HapMap Project and 1000 Genomes Project datasets which are widely used in genotype imputation as reference panels. Our results suggested the use of a p-value threshold of ~10⁻⁷ as the criterion for genome-wide significance for early commercial genotyping arrays, but slightly more stringent p-value thresholds ~5 × 10⁻⁸ for current or merged commercial genotyping arrays, ~10⁻⁸ for all common SNPs in the 1000 Genomes Project dataset and ~5 × 10⁻⁸ for the common SNPs only within genes.     

Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome‐wide association study using high‐density SNPs

Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton‐producing and cotton‐consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome‐wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high‐density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single‐nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty‐eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high‐resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.