Single‐nucleotide polymorphism discovery and panel characterization in the African forest elephant

The continuing decline in forest elephant (Loxodonta cyclotis) numbers due to poaching and habitat reduction is driving the search for new tools to inform management and conservation. For dense rainforest species, basic ecological data on populations and threats can be challenging and expensive to collect, impeding conservation action in the field. As such, genetic monitoring is being increasingly implemented to complement or replace more burdensome field techniques. Single‐nucleotide polymorphisms (SNPs) are particularly cost‐effective and informative markers that can be used for a range of practical applications, including population census, assessment of human impact on social and genetic structure, and investigation of the illegal wildlife trade. SNP resources for elephants are scarce, but next‐generation sequencing provides the opportunity for rapid, inexpensive generation of SNP markers in nonmodel species. Here, we sourced forest elephant DNA from 23 samples collected from 10 locations within Gabon, Central Africa, and applied double‐digest restriction‐site‐associated DNA (ddRAD) sequencing to discover 31,851 tags containing SNPs that were reduced to a set of 1,365 high‐quality candidate SNP markers. A subset of 115 candidate SNPs was then selected for assay design and validation using 56 additional samples. Genotyping resulted in a high conversion rate (93%) and a low per allele error rate (0.07%). This study provides the first panel of 107 validated SNP markers for forest elephants. This resource presents great potential for new genetic tools to produce reliable data and underpin a step‐change in conservation policies for this elusive species.     

SNP discovery in nonmodel organisms: strand bias and base‐substitution errors reduce conversion rates

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep‐sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize ‘bycatch’—polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand‐bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single‐copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.     

Low rates of hybridization between European wildcats and domestic cats in a human‐dominated landscape

Hybridization between wild species and their domestic congeners is considered a major threat for wildlife conservation. Genetic integrity of the European wildcat, for instance, is a concern as they are outnumbered by domestic cats by several orders of magnitude throughout its range. We genotyped 1,071 individual wildcat samples obtained from hair traps and roadkills collected across the highly fragmented forests of western Central Europe, in Germany and Luxembourg, to assess domestic cat introgression in wildcats in human‐dominated landscapes. Analyses using a panel of 75 autosomal SNPs suggested a low hybridization rate, with 3.5% of wildcat individuals being categorized as F1, F2, or backcrosses to either parental taxon. We report that results based on a set of SNPs were more consistent than on a set of 14 microsatellite markers, showed higher accuracy to detect hybrids and their class in simulation analyses, and were less affected by underlying population structure. Our results strongly suggest that very high hybridization rates previously reported for Central Europe may be partly due to inadequate choice of markers and/or sampling design. Our study documents that an adequately selected SNP panel for hybrid detection may be used as an alternative to commonly applied microsatellite markers, including studies relying on noninvasively collected samples. In addition, our finding of overall low hybridization rates in Central European wildcats provides an example of successful wildlife coexistence in human‐dominated, fragmented landscapes.     

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.     

Genotyping‐in‐Thousands by sequencing (GT‐seq) panel development and application to minimally invasive DNA samples to support studies in molecular ecology

Minimally invasive sampling (MIS) is widespread in wildlife studies; however, its utility for massively parallel DNA sequencing (MPS) is limited. Poor sample quality and contamination by exogenous DNA can make MIS challenging to use with modern genotyping‐by‐sequencing approaches, which have been traditionally developed for high‐quality DNA sources. Given that MIS is often more appropriate in many contexts, there is a need to make such samples practical for harnessing MPS. Here, we test the ability for Genotyping‐in‐Thousands by sequencing (GT‐seq), a multiplex amplicon sequencing approach, to effectively genotype minimally invasive cloacal DNA samples collected from the Western Rattlesnake (Crotalus oreganus), a threatened species in British Columbia, Canada. As there was no previous genetic information for this species, an optimized panel of 362 SNPs was selected for use with GT‐seq from a de novo restriction site‐associated DNA sequencing (RADseq) assembly. Comparisons of genotypes generated within and among RADseq and GT‐seq for the same individuals found low rates of genotyping error (GT‐seq: 0.50%; RADseq: 0.80%) and discordance (2.57%), the latter likely due to the different genotype calling models employed. GT‐seq mean genotype discordance between blood and cloacal swab samples collected from the same individuals was also minimal (1.37%). Estimates of population diversity parameters were similar across GT‐seq and RADseq data sets, as were inferred patterns of population structure. Overall, GT‐seq can be effectively applied to low‐quality DNA samples, minimizing the inefficiencies presented by exogenous DNA typically found in minimally invasive samples and continuing the expansion of molecular ecology and conservation genetics in the genomics era.     

Characterization of polyploid wheat genomic diversity using a high‐density 90 000 single nucleotide polymorphism array

High‐density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene‐associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome‐wide distributed SNPs that are represented in populations of diverse geographical origin. We used density‐based spatial clustering algorithms to enable high‐throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model‐free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low‐intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.     

Finding the right coverage: the impact of coverage and sequence quality on single nucleotide polymorphism genotyping error rates

Restriction‐enzyme‐based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction‐enzyme‐based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother–offspring dyads of Hoffman's two‐toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference‐aligned and de novo‐assembled data sets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo‐assembled data sets. For example, coverage ≥5 yielded median genotyping error rates of ≥0.03 and ≥0.11 in reference‐aligned and de novo‐assembled data sets, respectively. Genotyping error rates declined to ≤0.01 in reference‐aligned data sets with a coverage ≥30, but remained ≥0.04 in the de novo‐assembled data sets. We observed approximately 10‐ and 13‐fold declines in the number of loci sampled in the reference‐aligned and de novo‐assembled data sets when coverage was increased from ≥5 to ≥30 at quality score ≥30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the trade‐off between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction‐enzyme‐based SNP studies.     

Discovery and development of exome‐based,co‐dominant single nucleotide polymorphism markers in hexaploid wheat (Triticum aestivum L.)

Globally, wheat is the most widely grown crop and one of the three most important crops for human and livestock feed. However, the complex nature of the wheat genome has, until recently, resulted in a lack of single nucleotide polymorphism (SNP)‐based molecular markers of practical use to wheat breeders. Recently, large numbers of SNP‐based wheat markers have been made available via the use of next‐generation sequencing combined with a variety of genotyping platforms. However, many of these markers and platforms have difficulty distinguishing between heterozygote and homozygote individuals and are therefore of limited use to wheat breeders carrying out commercial‐scale breeding programmes. To identify exome‐based co‐dominant SNP‐based assays, which are capable of distinguishing between heterozygotes and homozygotes, we have used targeted re‐sequencing of the wheat exome to generate large amounts of genomic sequences from eight varieties. Using a bioinformatics approach, these sequences have been used to identify 95 266 putative single nucleotide polymorphisms, of which 10 251 were classified as being putatively co‐dominant. Validation of a subset of these putative co‐dominant markers confirmed that 96% were true polymorphisms and 65% were co‐dominant SNP assays. The new co‐dominant markers described here are capable of genotypic classification of a segregating locus in polyploid wheat and can be used on a variety of genotyping platforms; as such, they represent a powerful tool for wheat breeders. These markers and related information have been made publically available on an interactive web‐based database to facilitate their use on genotyping programmes worldwide.     

The easy road to genome‐wide medium density SNP screening in a non‐model species: development and application of a 10 K SNP‐chip for the house sparrow (Passer domesticus)

With the advent of next generation sequencing, new avenues have opened to study genomics in wild populations of non‐model species. Here, we describe a successful approach to a genome‐wide medium density Single Nucleotide Polymorphism (SNP) panel in a non‐model species, the house sparrow (Passer domesticus), through the development of a 10 K Illumina iSelect HD BeadChip. Genomic DNA and cDNA derived from six individuals were sequenced on a 454 GS FLX system and generated a total of 1.2 million sequences, in which SNPs were detected. As no reference genome exists for the house sparrow, we used the zebra finch (Taeniopygia guttata) reference genome to determine the most likely position of each SNP. The 10 000 SNPs on the SNP‐chip were selected to be distributed evenly across 31 chromosomes, giving on average one SNP per 100 000 bp. The SNP‐chip was screened across 1968 individual house sparrows from four island populations. Of the original 10 000 SNPs, 7413 were found to be variable, and 99% of these SNPs were successfully called in at least 93% of all individuals. We used the SNP‐chip to demonstrate the ability of such genome‐wide marker data to detect population sub‐division, and compared these results to similar analyses using microsatellites. The SNP‐chip will be used to map Quantitative Trait Loci (QTL) for fitness‐related phenotypic traits in natural populations.     

A simple method to score single nucleotide polymorphisms based on allele‐specific PCR and primer‐induced fragment‐length variation

We describe a simple protocol to genotype single nucleotide polymorphisms (SNPs), which combines allele‐specific polymerase chain reaction (PCR) with fragment‐length analysis. Three primers are used in the PCR: two allele‐specific forward primers with a length‐difference and one reverse primer. The forward primers induce a length‐difference between the SNP‐variants, which can be assessed with standard fragment‐length analyses. We designed primers for 21 SNPs, and codominance was achieved for 76% of these SNPs. An inexpensive and flexible laser‐detection scoring protocol can be achieved with multiplex scoring and by incorporating the M13(‐21) genotyping method.     

Development and preliminary evaluation of a genomewide single nucleotide polymorphisms resource generated by RAD‐seq for the small yellow croaker (Larimichthys polyactis)

Recent advances in high‐throughput sequencing technologies have offered the possibility to generate genomewide sequence data to delineate previously unidentified genetic structure, obtain more accurate estimates of demographic parameters and to evaluate potential adaptive divergence. Here, we identified 27 556 single nucleotide polymorphisms for the small yellow croaker (Larimichthys polyactis) using restriction‐site‐associated DNA (RAD) sequencing of 24 individuals from two populations. Significant sources of genetic variation were identified, with an average nucleotide diversity (π) of 0.00105 ± 0.000425 across individuals, and long‐term effective population size was thus estimated to range between 26 172 and 261 716. According to the results, no differentiation between the two populations was detected based on the SNP data set of top quality score per contig or neutral loci. However, the two analysed populations were highly differentiated based on SNP data set of both top F_ST value per contig and the outlier SNPs. Moreover, local adaptation was highlighted by an F_ST‐based outlier tests implemented in LOSITAN and a total of 538 potentially locally selected SNPs were identified. blast2go annotation of contigs containing the outlier SNPs yielded hits for 37 (66%) of 56 significant blastx matches. Candidate genes for local adaptation constituted a wide array of biological functions, including cellular response to oxidative stress, actin filament binding, ion transmembrane transport and synapse assembly. The generated SNP resources in this study provided a valuable tool for future population genetics and genomics studies of L. polyactis.     

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.     

High‐throughput genomics in sorghum: from whole‐genome resequencing to a SNP screening array

With its small, diploid and completely sequenced genome, sorghum (Sorghum bicolor L. Moench) is highly amenable to genomics‐based breeding approaches. Here, we describe the development and testing of a robust single‐nucleotide polymorphism (SNP) array platform that enables polymorphism screening for genome‐wide and trait‐linked polymorphisms in genetically diverse S. bicolor populations. Whole‐genome sequences with 6× to 12× coverage from five genetically diverse S. bicolor genotypes, including three sweet sorghums and two grain sorghums, were aligned to the sorghum reference genome. From over 1 million high‐quality SNPs, we selected 2124 Infinium Type II SNPs that were informative in all six source genomes, gave an optimal Assay Design Tool (ADT) score, had allele frequencies of 50% in the six genotypes and were evenly spaced throughout the S. bicolor genome. Furthermore, by phenotype‐based pool sequencing, we selected an additional 876 SNPs with a phenotypic association to early‐stage chilling tolerance, a key trait for European sorghum breeding. The 3000 attempted bead types were used to populate half of a dual‐species Illumina iSelect SNP array. The array was tested using 564 Sorghum spp. genotypes, including offspring from four unrelated recombinant inbred line (RIL) and F₂ populations and a genetic diversity collection. A high call rate of over 80% enabled validation of 2620 robust and polymorphic sorghum SNPs, underlining the efficiency of the array development scheme for whole‐genome SNP selection and screening, with diverse applications including genetic mapping, genome‐wide association studies and genomic selection.     

Tool for genomic selection and breeding to evolutionary adaptation: Development of a 100K single nucleotide polymorphism array for the honey bee

High‐throughput high‐density genotyping arrays continue to be a fast, accurate, and cost‐effective method for genotyping thousands of polymorphisms in high numbers of individuals. Here, we have developed a new high‐density SNP genotyping array (103,270 SNPs) for honey bees, one of the most ecologically and economically important pollinators worldwide. SNPs were detected by conducting whole‐genome resequencing of 61 honey bee drones (haploid males) from throughout Europe. Selection of SNPs for the chip was done in multiple steps using several criteria. The majority of SNPs were selected based on their location within known candidate regions or genes underlying a range of honey bee traits, including hygienic behavior against pathogens, foraging, and subspecies. Additionally, markers from a GWAS of hygienic behavior against the major honey bee parasite Varroa destructor were brought over. The chip also includes SNPs associated with each of three major breeding objectives—honey yield, gentleness, and Varroa resistance. We validated the chip and make recommendations for its use by determining error rates in repeat genotypings, examining the genotyping performance of different tissues, and by testing how well different sample types represent the queen's genotype. The latter is a key test because it is highly beneficial to be able to determine the queen's genotype by nonlethal means. The array is now publicly available and we suggest it will be a useful tool in genomic selection and honey bee breeding, as well as for GWAS of different traits, and for population genomic, adaptation, and conservation questions.     

New resources for genetic studies in Populus nigra: genome‐wide SNP discovery and development of a 12k Infinium array

Whole genome resequencing of 51 Populus nigra (L.) individuals from across Western Europe was performed using Illumina platforms. A total number of 1 878 727 SNPs distributed along the P. nigra reference sequence were identified. The SNP calling accuracy was validated with Sanger sequencing. SNPs were selected within 14 previously identified QTL regions, 2916 expressional candidate genes related to rust resistance, wood properties, water‐use efficiency and bud phenology and 1732 genes randomly spread across the genome. Over 10 000 SNPs were selected for the construction of a 12k Infinium Bead‐Chip array dedicated to association mapping. The SNP genotyping assay was performed with 888 P. nigra individuals. The genotyping success rate was 91%. Our high success rate was due to the discovery panel design and the stringent parameters applied for SNP calling and selection. In the same set of P. nigra genotypes, linkage disequilibrium throughout the genome decayed on average within 5–7 kb to half of its maximum value. As an application test, ADMIXTURE analysis was performed with a selection of 600 SNPs spread throughout the genome and 706 individuals collected along 12 river basins. The admixture pattern was consistent with genetic diversity revealed by neutral markers and the geographical distribution of the populations. These newly developed SNP resources and genotyping array provide a valuable tool for population genetic studies and identification of QTLs through natural‐population based genetic association studies in P. nigra.     

A resource of single‐nucleotide polymorphisms for rainbow trout generated by restriction‐site associated DNA sequencing of doubled haploids

Salmonid genomes are considered to be in a pseudo‐tetraploid state as a result of a genome duplication event that occurred between 25 and 100 Ma. This situation complicates single‐nucleotide polymorphism (SNP) discovery in rainbow trout as many putative SNPs are actually paralogous sequence variants (PSVs) and not simple allelic variants. To differentiate PSVs from simple allelic variants, we used 19 homozygous doubled haploid (DH) lines that represent a wide geographical range of rainbow trout populations. In the first phase of the study, we analysed SbfI restriction‐site associated DNA (RAD) sequence data from all the 19 lines and selected 11 lines for an extended SNP discovery. In the second phase, we conducted the extended SNP discovery using PstI RAD sequence data from the selected 11 lines. The complete data set is composed of 145 168 high‐quality putative SNPs that were genotyped in at least nine of the 11 lines, of which 71 446 (49%) had minor allele frequencies (MAF) of at least 18% (i.e. at least two of the 11 lines). Approximately 14% of the RAD SNPs in this data set are from expressed or coding rainbow trout sequences. Our comparison of the current data set with previous SNP discovery data sets revealed that 99% of our SNPs are novel. In the support files for this resource, we provide annotation to the positions of the SNPs in the working draft of the rainbow trout reference genome, provide the genotypes of each sample in the discovery panel and identify SNPs that are likely to be in coding sequences.     

Detection and characterization of SNPs useful for identity control and parentage testing in major European dairy breeds

We propose the use of single nucleotide polymorphisms (SNPs) instead of polymorphic microsatellite markers for individual identification and parentage control in cattle. To this end, we present an initial set of 37 SNP markers together with a gender-specific SNP for identity control and parentage testing in the Holstein, Fleckvieh and Braunvieh breeds. To obtain suitable SNPs, a total of 91.13 kb of random genomic DNA was screened yielding 531 SNPs. These, and 43 previously identified SNPs, were subjected to the following selection criteria: (1) the frequency of the minor allele must be larger than 0.1 in at least two of the three examined breeds, and (2) markers should not be linked closely. Allele frequencies were estimated by analysing sequencing traces of pooled DNA or by genotyping individual DNA samples. The selected SNP loci were physically mapped by radiation hybrid mapping or by fluorescence in situ hybridization, and tested against the neutral mutation hypothesis. The presented marker set theoretically allows probabilities of identity less than 10(-13) for individual verification and exclusion powers exceeding 99.99% for parentage testing.     

Single nucleotide polymorphism‐based dispersal estimates using noninvasive sampling

Quantifying dispersal within wild populations is an important but challenging task. Here we present a method to estimate contemporary, individual‐based dispersal distance from noninvasively collected samples using a specialized panel of 96 SNPs (single nucleotide polymorphisms). One main issue in conducting dispersal studies is the requirement for a high sampling resolution at a geographic scale appropriate for capturing the majority of dispersal events. In this study, fecal samples of brown bear (Ursus arctos) were collected by volunteer citizens, resulting in a high sampling resolution spanning over 45,000 km² in Gävleborg and Dalarna counties in Sweden. SNP genotypes were obtained for unique individuals sampled (n = 433) and subsequently used to reconstruct pedigrees. A Mantel test for isolation by distance suggests that the sampling scale was appropriate for females but not for males, which are known to disperse long distances. Euclidean distance was estimated between mother and offspring pairs identified through the reconstructed pedigrees. The mean dispersal distance was 12.9 km (SE 3.2) and 33.8 km (SE 6.8) for females and males, respectively. These results were significantly different (Wilcoxon's rank‐sum test: P‐value = 0.02) and are in agreement with the previously identified pattern of male‐biased dispersal. Our results illustrate the potential of using a combination of noninvasively collected samples at high resolution and specialized SNPs for pedigree‐based dispersal models.     

The Wheat 660K SNP array demonstrates great potential for marker‐assisted selection in polyploid wheat

The rapid development and application of molecular marker assays have facilitated genomic selection and genome‐wide linkage and association studies in wheat breeding. Although PCR‐based markers (e.g. simple sequence repeats and functional markers) and genotyping by sequencing have contributed greatly to gene discovery and marker‐assisted selection, the release of a more accurate and complete bread wheat reference genome has resulted in the design of single‐nucleotide polymorphism (SNP) arrays based on different densities or application targets. Here, we evaluated seven types of wheat SNP arrays in terms of their SNP number, distribution, density, associated genes, heterozygosity and application. The results suggested that the Wheat 660K SNP array contained the highest percentage (99.05%) of genome‐specific SNPs with reliable physical positions. SNP density analysis indicated that the SNPs were almost evenly distributed across the whole genome. In addition, 229 266 SNPs in the Wheat 660K SNP array were located in 66 834 annotated gene or promoter intervals. The annotated genes revealed by the Wheat 660K SNP array almost covered all genes revealed by the Wheat 35K (97.44%), 55K (99.73%), 90K (86.9%) and 820K (85.3%) SNP arrays. Therefore, the Wheat 660K SNP array could act as a substitute for other 6 arrays and shows promise for a wide range of possible applications. In summary, the Wheat 660K SNP array is reliable and cost‐effective and may be the best choice for targeted genotyping and marker‐assisted selection in wheat genetic improvement.