High-throughput Genotyping Arrays Research Articles

Development of a next generation SNP genotyping array for wheat.

High-throughput genotyping arrays have provided a cost-effective, reliable and interoperable system for genotyping hexaploid wheat and its relatives. Existing, highly cited arrays including our 35K Wheat Breeder's array and the Illumina 90K array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in wheat sequencing has given us access to a vast pool of SNP diversity, whilst technological improvements have allowed us to fit significantly more probes onto a 384-well format Axiom array than previously possible. Here we describe a novel Axiom genotyping array, the 'Triticum aestivum Next Generation' array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins 'Core Collection'. We used a novel haplotype optimization approach to select SNPs with the highest combined varietal discrimination and a design iteration step to test and replace SNPs which failed to convert to reliable markers. The final design with 43 372 SNPs contains a combination of haplotype-optimized novel SNPs and legacy cross-platform markers. We show that this design has an improved distribution of SNPs compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous array. We also demonstrate the improved performance of TaNGv1.1 for Genome-wide association studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available with supporting marker annotations and initial genotyping results freely available.

Low-Cost High-Throughput Genotyping for Diagnosing Familial Hypercholesterolemia.

Familial hypercholesterolemia (FH) is a common but underdiagnosed genetic disorder characterized by high low-density lipoprotein cholesterol levels and premature cardiovascular disease. Current sequencing methods to diagnose FH are expensive and time-consuming. In this study, we evaluated the accuracy of a low-cost, high-throughput genotyping array for diagnosing FH. An Illumina Global Screening Array was customized to include probes for 636 variants, previously classified as FH-causing variants. First, its theoretical coverage was assessed in all FH variant carriers diagnosed through next-generation sequencing between 2016 and 2022 in the Netherlands (n=1772). Next, the performance of the array was validated in another sample of FH variant carriers previously identified in the Dutch FH cascade screening program (n=1268). The theoretical coverage of the array for FH-causing variants was 91.3%. Validation of the array was assessed in a sample of 1268 carriers of whom 1015 carried a variant in LDLR, 250 in APOB, and 3 in PCSK9. The overall sensitivity was 94.7% and increased to 98.2% after excluding participants with variants not included in the array design. Copy number variation analysis yielded a 89.4% sensitivity. In 18 carriers, the array identified a total of 19 additional FH-causing variants. Subsequent DNA analysis confirmed 5 of the additionally identified variants, yielding a false-positive result in 16 subjects (1.3%). The FH genotyping array is a promising tool for genetically diagnosing FH at low costs and has the potential to greatly increase accessibility to genetic testing for FH. Continuous customization of the array will further improve its performance.

CAS Array: design and assessment of a genotyping array for Chinese biobanking.

Chronic diseases are becoming a critical challenge to the aging Chinese population. Biobanks with extensive genomic and environmental data offer opportunities to elucidate the complex gene-environment interactions underlying their aetiology. Genome-wide genotyping array remains an efficient approach for large-scale genomic data collection. However, most commercial arrays have reduced performance for biobanking in the Chinese population. Deep whole-genome sequencing data from 2641 Chinese individuals were used as a reference to develop the CAS array, a custom-designed genotyping array for precision medicine. Evaluation of the array was performed by comparing data from 384 individuals assayed both by the array and whole-genome sequencing. Validation of its mitochondrial copy number estimating capacity was conducted by examining its association with established covariates among 10162 Chinese elderly. The CAS Array adopts the proven Axiom technology and is restricted to 652429 single-nucleotide polymorphism (SNP) markers. Its call rate of 99.79% and concordance rate of 99.89% are both higher than for commercial arrays. Its imputation-based genome coverage reached 98.3% for common SNPs and 63.0% for low-frequency SNPs, both comparable to commercial arrays with larger SNP capacity. After validating its mitochondrial copy number estimates, we developed a publicly available software tool to facilitate the array utility. Based on recent advances in genomic science, we designed and implemented a high-throughput and low-cost genotyping array. It is more cost-effective than commercial arrays for large-scale Chinese biobanking.

Genetic testing for familial hypercholesterolemia using low-cost high-throughput microarray-based genotyping

Background and Aims : Familial hypercholesterolemia (FH) is an autosomal dominant disorder characterized by elevated low-density lipoprotein cholesterol (LDL-C) levels and premature cardiovascular disease (CVD). Current methods for genetically confirming FH are expensive and time-consuming. In this study we set out to validate a low cost, high throughput genotyping array, dubbed GOALL-GSA_v1, developed to detect known FH-causing single-nucleotide variants (SNVs), small indels and copy number variations (CNV) (∼€30 per sample) in a cohort of genetically diagnosed FH patients.

Evidence of rare misassemblies in the bovine reference genome revealed by population genetic metrics.

Creation of the bovine reference assembly paved the way to develop the high-throughput genotyping arrays of the single nucleotide polymorphisms (SNPs) based on the available map coordinates that facilitated major advances in gene mapping and selection programs. The assembly flaws, however, may cause false results in the downstream gene mapping studies. The most recent bovine reference genome (ARS-UCD1.2) is built on the long-read sequences that provides improved quality and continuity. By applying population genetic metrics in this study, we aimed to evaluate the map coordinates to which SNP markers were assigned. We employed a three-step approach by combining the recombination and linkage disequilibrium analyses to test if the markers fit into the assigned physical map coordinates. We applied the method to the bovine 50k array in a large pedigree of Holstein cattle and revealed a panel of 65 candidate markers, most of which were re-located either on a different chromosome or re-mapped as far as several million base pairs away on the same chromosome. This list of candidates accounts for 0.1% of the SNPs in the widely used 50k genotyping array and we foresee a reasonably larger set of markers being misplaced in the BovineHD 700K BeadChip. We suggest pre-removal of the candidate misplaced markers to reduce false signals in association mapping studies.

Polygenic risk score: a useful clinical instrument for disease prediction and risk categorization

Genetic information is one of the essential components of precision medicine. Over the past decade, substantial progress has been made, such as low-cost, high-throughput genotyping arrays, advances in statistical techniques, and progressively larger discovery datasets, enabling the discovery of alleles contributing to common diseases, such as coronary artery disease and type 2 diabetes. The polygenic risk score (PRS) represents the aggregate contribution of numerous common genetic variants, individually conferring small to moderate effects, and can be used as a marker of genetic risk for major chronic diseases. PRSs can be obtained from early childhood, and only one measurement is needed to determine the score. PRSs can potentially be used for triage of further investigations to confirm disease susceptibility and to optimize individualized preventive strategies for high-risk disease groups. We provide an overview and commentary on important advances in deriving and validating PRSs, as well as the implementation of PRSs for clinically useful purposes.

Development and Evaluation of a High-Throughput Single-Nucleotide Polymorphism Array for Large Yellow Croaker (Larimichthys crocea).

High-density single-nucleotide polymorphism (SNP) genotyping array is an essential tool for genetic analyses of animals and plants. Large yellow croaker (Larimichthys crocea) is one of the most commercially important marine fish species in China. Although plenty of SNPs have been identified in large yellow croaker, no high-throughput genotyping array is available. In this study, a high-throughput SNP array named NingXin-I with 600K SNPs was developed and evaluated. A set of 82 large yellow croakers were collected from different locations of China and re-sequenced. A total of 9.34M SNPs were identified by mapping sequence reads to the large yellow croaker reference genome. About 1.98M candidate SNPs were selected for further analyses by using criteria such as SNP quality score and conversion performance in the final array. Finally, 579.5K SNPs evenly distributed across the large yellow croaker genome with an average spacing of 1.19 kb were proceeded to array production. The performance of NingXin-I array was evaluated in 96 large yellow croaker individuals from five populations, and 83.38% SNPs on the array were polymorphic sites. A further test of the NingXin-I array in five closely related species in Sciaenidae identified 26.68–56.23% polymorphic SNP rate across species. A phylogenetic tree inferred by using the genotype data generated by NingXin-I confirmed the phylogenetic distance of the species in Sciaenidae. The performance of NingXin-I in large yellow croaker and the other species in Sciaenidae suggested high accuracy and broad application. The NingXin-I array should be valuable for quantitative genetic studies, such as genome-wide association studies (GWASs), high-density linkage map construction, haplotype analysis, and genome-based selection.

Investigating the influence of mtDNA and nuclear encoded mitochondrial variants on high intensity interval training outcomes

Mitochondria supply intracellular energy requirements during exercise. Specific mitochondrial haplogroups and mitochondrial genetic variants have been associated with athletic performance, and exercise responses. However, these associations were discovered using underpowered, candidate gene approaches, and consequently have not been replicated. Here, we used whole-mitochondrial genome sequencing, in conjunction with high-throughput genotyping arrays, to discover novel genetic variants associated with exercise responses in the Gene SMART (Skeletal Muscle Adaptive Response to Training) cohort (n = 62 completed). We performed a Principal Component Analysis of cohort aerobic fitness measures to build composite traits and test for variants associated with exercise outcomes. None of the mitochondrial genetic variants but eight nuclear encoded variants in seven separate genes were found to be associated with exercise responses (FDR < 0.05) (rs11061368: DIABLO, rs113400963: FAM185A, rs6062129 and rs6121949: MTG2, rs7231304: AFG3L2, rs2041840: NDUFAF7, rs7085433: TIMM23, rs1063271: SPTLC2). Additionally, we outline potential mechanisms by which these variants may be contributing to exercise phenotypes. Our data suggest novel nuclear-encoded SNPs and mitochondrial pathways associated with exercise response phenotypes. Future studies should focus on validating these variants across different cohorts and ethnicities.

Genome-wide Analyses Identifies Known and New Markers Responsible of Chicken Plumage Color.

Simple SummaryIn order to assess sources of variation related to Polverara breed plumage color (black vs. white), we carried out genome-wide analyses to identify the genomic regions involved in this trait. The present work has revealed new candidate genes involved in the phenotypic variability in local chicken populations. These results also contribute insights into the genetic basis for plumage color in poultry, and confirm the great complexity of the mechanisms that control this trait.Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

Genome-wide Genotyping of Cerebral Cavernous Malformation Type 1 Individuals to Identify Genetic Modifiers of Disease Severity.

Familial cerebral cavernous malformation type 1 (CCM1) is an autosomal dominant disease caused by mutations in the Krev Interaction Trapped 1 (KRIT1/CCM1) gene, and characterized by brain lesions that can cause hemorrhagic strokes, seizures, and neurological deficits. Carriers of the same genetic mutation can present with variable symptoms and severity of disease, suggesting the influence of modifier factors. Genetic modifiers of CCM1 disease severity have been recently identified and included common genetic variants in inflammatory, immune response, and oxidative stress genes and pathways. Here, we describe the genotyping of CCM1 patients with the same gene mutation (Q455X) using a high-throughput genotyping array optimized for individuals of Hispanic/Latino ancestry. We then review the quality control steps following the genome-wide genotyping. Genome-wide genotyping of larger cohorts of CCM1 patients might reveal additional genetic variants contributing to the disease severity of CCM1.

Development and characterisation of interspecific hybrid lines with genome-wide introgressions from Triticum timopheevii in a hexaploid wheat background

BackgroundTriticum timopheevii (2n = 4x = 28; AtAtGG), is an important source for new genetic variation for wheat improvement with genes for potential disease resistance and salt tolerance. By generating a range of interspecific hybrid lines, T. timopheevii can contribute to wheat’s narrow gene-pool and be practically utilised in wheat breeding programmes. Previous studies that have generated such introgression lines between wheat and its wild relatives have been unable to use high-throughput methods to detect the presence of wild relative segments in such lines.ResultsA whole genome introgression approach, exploiting homoeologous recombination in the absence of the Ph1 locus, has resulted in the transfer of different chromosome segments from both the At and G genomes of T. timopheevii into wheat. These introgressions have been detected and characterised using single nucleotide polymorphism (SNP) markers present on a high-throughput Axiom® Genotyping Array. The analysis of these interspecific hybrid lines has resulted in the detection of 276 putative unique introgressions from T. timopheevii, thereby allowing the generation of a genetic map of T. timopheevii containing 1582 SNP markers, spread across 14 linkage groups representing each of the seven chromosomes of the At and G genomes of T. timopheevii. The genotyping of the hybrid lines was validated through fluorescence in situ hybridisation (FISH). Comparative analysis of the genetic map of T. timopheevii and the physical map of the hexaploid wheat genome showed that synteny between the two species is highly conserved at the macro-level and confirmed the presence of inter- and intra-genomic translocations within the At and G genomes of T. timopheevii that have been previously only detected through cytological techniques.ConclusionsIn this work, we report a set of SNP markers present on a high-throughput genotyping array, able to detect the presence of T. timopheevii in a hexaploid wheat background making it a potentially valuable tool for marker assisted selection (MAS) in wheat pre-breeding programs. These valuable resources of high-density molecular markers and wheat-T. timopheevii hybrid lines will greatly enhance the work being undertaken for wheat improvement through wild relative introgressions.

Design and characterization of an 87k SNP genotyping array for Arctic charr (Salvelinus alpinus).

We have generated a high-density, high-throughput genotyping array for characterizing genome-wide variation in Arctic charr (Salvelinus alpinus). Novel single nucleotide polymorphisms (SNPs) were identified in charr from the Fraser, Nauyuk and Tree River aquaculture strains, which originated from northern Canada and fish from Iceland using high coverage sequencing, reduced representation sequencing and RNA-seq datasets. The array was designed to capture genome-wide variation from a diverse suite of Arctic charr populations. Cross validation of SNPs from various sources and comparison with previously published Arctic charr SNP data provided a set of candidate SNPs that generalize across populations. Further candidate SNPs were identified based on minor allele frequency, association with RNA transcripts, even spacing across intergenic regions and association with the sex determining (sdY) gene. The performance of the 86,503 SNP array was assessed by genotyping Fraser, Nauyuk and Tree River strain individuals, as well as wild Icelandic Arctic charr. Overall, 63,060 of the SNPs were polymorphic within at least one group and 36.8% were unique to one of the four groups, suggesting that the array design allows for characterization of both within and across population genetic diversity. The concordance between sdY markers and known phenotypic sex indicated that the array can accurately determine the sex of individuals based on genotype alone. The Salp87k genotyping array provides researchers and breeders the opportunity to analyze genetic variation in Arctic charr at a more detailed level than previously possible.

Detection of T. urartu Introgressions in Wheat and Development of a Panel of Interspecific Introgression Lines.

Tritcum urartu (2n = 2x = 14, AuAu), the A genome donor of wheat, is an important source for new genetic variation for wheat improvement due to its high photosynthetic rate and disease resistance. By facilitating the generation of genome-wide introgressions leading to a variety of different wheat–T. urartu translocation lines, T. urartu can be practically utilized in wheat improvement. Previous studies that have generated such introgression lines have been unable to successfully use cytological methods to detect the presence of T. urartu in these lines. Many have, thus, used a variety of molecular markers with limited success due to the low-density coverage of these markers and time-consuming nature of the techniques rendering them unsuitable for large-scale breeding programs. In this study, we report the generation of a resource of single nucleotide polymorphic (SNP) markers, present on a high-throughput SNP genotyping array, that can detect the presence of T. urartu in a hexaploid wheat background making it a potentially valuable tool in wheat pre-breeding programs. A whole genome introgression approach has resulted in the transfer of different chromosome segments from T. urartu into wheat which have then been detected and characterized using these SNP markers. The molecular analysis of these wheat-T. urartu recombinant lines has resulted in the generation of a genetic map of T. urartu containing 368 SNP markers, spread across all seven chromosomes of T. urartu. Comparative analysis of the genetic map of T. urartu and the physical map of the hexaploid wheat genome showed that synteny between the two species is highly conserved at the macro-level and confirmed the presence of the 4/5 translocation in T. urartu also present in the A genome of wheat. A panel of 17 wheat-T. urartu recombinant lines, which consisted of introgressed segments that covered the whole genome of T. urartu, were also selected for self-fertilization to provide a germplasm resource for future trait analysis. This valuable resource of high-density molecular markers specifically designed for detecting wild relative chromosomes and a panel of stable interspecific introgression lines will greatly enhance the efficiency of wheat improvement through wild relative introgressions.

High throughput SNP discovery and genotyping in hexaploid wheat.

Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.

Wheat genetic resources in the post-genomics era: promise and challenges.

Wheat genetic resources have been used for genetic improvement since 1876, when Stephen Wilson (Transactions and Proceedings of the Botanical Society of Edinburgh 12: 286) consciously made the first wide hybrid involving wheat and rye in Scotland. Wide crossing continued with sporadic attempts in the first half of 19th century and became a sophisticated scientific discipline during the last few decades with considerable impact in farmers' fields. However, a large diversity of untapped genetic resources could contribute in meeting future wheat production challenges. Recently the complete reference genome of hexaploid (Chinese Spring) and tetraploid (Triticum turgidum ssp. dicoccoides) wheat became publicly available coupled with on-going international efforts on wheat pan-genome sequencing. We anticipate that an objective appraisal is required in the post-genomics era to prioritize genetic resources for use in the improvement of wheat production if the goal of doubling yield by 2050 is to be met. Advances in genomics have resulted in the development of high-throughput genotyping arrays, improved and efficient methods of gene discovery, genomics-assisted selection and gene editing using endonucleases. Likewise, ongoing advances in rapid generation turnover, improved phenotyping, envirotyping and analytical methods will significantly accelerate exploitation of exotic genes and increase the rate of genetic gain in breeding. We argue that the integration of these advances will significantly improve the precision and targeted identification of potentially useful variation in the wild relatives of wheat, providing new opportunities to contribute to yield and quality improvement, tolerance to abiotic stresses, resistance to emerging biotic stresses and resilience to weather extremes.

Development and Evaluation of a Barley 50k iSelect SNP Array.

High-throughput genotyping arrays continue to be an attractive, cost-effective alternative to sequencing based approaches. We have developed a new 50k Illumina Infinium iSelect genotyping array for barley, a cereal crop species of major international importance. The majority of SNPs on the array have been extracted from variants called in exome capture data of a wide range of European barley germplasm. We used the recently published barley pseudomolecule assembly to map the exome capture data, which allowed us to generate markers with accurate physical positions and detailed gene annotation. Markers from an existing and widely used barley 9k Infinium iSelect array were carried over onto the 50k chip for backward compatibility. The array design featured 49,267 SNP markers that converted into 44,040 working assays, of which 43,461 were scorable in GenomeStudio. Of the working assays, 6,251 are from the 9k iSelect platform. We validated the SNPs by comparing the genotype calls from the new array to legacy datasets. Rates of agreement averaged 98.1 and 93.9% respectively for the legacy 9k iSelect SNP set (Comadran et al., 2012) and the exome capture SNPs. To test the utility of the 50k chip for genetic mapping, we genotyped a segregating population derived from a Golden Promise × Morex cross (Liu et al., 2014) and mapped over 14,000 SNPs to genetic positions which showed a near exact correspondence to their known physical positions. Manual adjustment of the cluster files used by the interpreting software for genotype scoring improved results substantially, but migration of cluster files between sites led to a deterioration of results, suggesting that local adjustment of cluster files is required on a site-per-site basis. Information relating to the markers on the chip is available online at https://ics.hutton.ac.uk/50k.

IPSCORE: A Resource of 222 iPSC Lines Enabling Functional Characterization of Genetic Variation across a Variety of Cell Types.

SummaryLarge-scale collections of induced pluripotent stem cells (iPSCs) could serve as powerful model systems for examining how genetic variation affects biology and disease. Here we describe the iPSCORE resource: a collection of systematically derived and characterized iPSC lines from 222 ethnically diverse individuals that allows for both familial and association-based genetic studies. iPSCORE lines are pluripotent with high genomic integrity (no or low numbers of somatic copy-number variants) as determined using high-throughput RNA-sequencing and genotyping arrays, respectively. Using iPSCs from a family of individuals, we show that iPSC-derived cardiomyocytes demonstrate gene expression patterns that cluster by genetic background, and can be used to examine variants associated with physiological and disease phenotypes. The iPSCORE collection contains representative individuals for risk and non-risk alleles for 95% of SNPs associated with human phenotypes through genome-wide association studies. Our study demonstrates the utility of iPSCORE for examining how genetic variants influence molecular and physiological traits in iPSCs and derived cell lines.

Genetic mapping of Pinus flexilis major gene (Cr4) for resistance to white pine blister rust using transcriptome-based SNP genotyping.

BackgroundLinkage of DNA markers with phenotypic traits provides essential information to dissect clustered genes with potential phenotypic contributions in a target genome region. Pinus flexilis E. James (limber pine) is a keystone five-needle pine species in mountain-top ecosystems of North America. White pine blister rust (WPBR), caused by a non-native fungal pathogen Cronartium ribicola (J.C. Fisch.), has resulted in mortality in this conifer species and is still spreading through the distribution. The objective of this research was to develop P. flexilis transcriptome-wide single nucleotide polymorphism (SNP) markers using RNA-seq analysis for genetic mapping of the major gene (Cr4) that confers complete resistance to C. ribicola.ResultsNeedle tissues of one resistant and two susceptible seedling families were subjected to RNA-seq analysis. In silico SNP markers were uncovered by mapping the RNA-seq reads back to the de novo assembled transcriptomes. A total of 110,573 in silico SNPs and 2,870 indels were identified with an average of 3.7 SNPs per Kb. These SNPs were distributed in 17,041 unigenes. Of these polymorphic P. flexilis unigenes, 6,584 were highly conserved as compared to the genome sequence of P. taeda L (loblolly pine). High-throughput genotyping arrays were designed and were used to search for Cr4-linked genic SNPs in megagametophyte populations of four maternal trees by haploid-segregation analysis. A total of 32 SNP markers in 25 genes were localized on the Cr4 linkage group (LG). Syntenic relationships of this Cr4-LG map with the model conifer species P. taeda anchored Cr4 on Pinus consensus LG8, indicating that R genes against C. ribicola have evolved independently in different five-needle pines. Functional genes close to Cr4 were annotated and their potential roles in Cr4-mediated resistance were further discussed.ConclusionsWe demonstrated a very effective, low-cost strategy for developing a SNP genetic map of a phenotypic trait of interest. SNP discovery through transcriptome comparison was integrated with high-throughput genotyping of a small set of in silico SNPs. This strategy may be applied to mapping any trait in non-model plant species that have complex genomes. Whole transcriptome sequencing provides a powerful tool for SNP discovery in conifers and other species with complex genomes, for which sequencing and annotation of complex genomes is still challenging. The genic SNP map for the consensus Cr4-LG may help future molecular breeding efforts by enabling both Cr4 positional characterization and selection of this gene against WPBR.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3079-2) contains supplementary material, which is available to authorized users.

Understanding and utilizing crop genome diversity via high-resolution genotyping.

High-resolution genome analysis technologies provide an unprecedented level of insight into structural diversity across crop genomes. Low-cost discovery of sequence variation has become accessible for all crops since the development of next-generation DNA sequencing technologies, using diverse methods ranging from genome-scale resequencing or skim sequencing, reduced-representation genotyping-by-sequencing, transcriptome sequencing or sequence capture approaches. High-density, high-throughput genotyping arrays generated using the resulting sequence data are today available for the assessment of genomewide single nucleotide polymorphisms in all major crop species. Besides their application in genetic mapping or genomewide association studies for dissection of complex agronomic traits, high-density genotyping arrays are highly suitable for genomic selection strategies. They also enable description of crop diversity at an unprecedented chromosome-scale resolution. Application of population genetics parameters to genomewide diversity data sets enables dissection of linkage disequilibrium to characterize loci underlying selective sweeps. High-throughput genotyping platforms simultaneously open the way for targeted diversity enrichment, allowing rejuvenation of low-diversity chromosome regions in strongly selected breeding pools to potentially reverse the influence of linkage drag. Numerous recent examples are presented which demonstrate the power of next-generation genomics for high-resolution analysis of crop diversity on a subgenomic and chromosomal scale. Such studies give deep insight into the history of crop evolution and selection, while simultaneously identifying novel diversity to improve yield and heterosis.

SP0108 Next Generation Sequencing and Related Technologies, A Way Forward for Arthritis?

The publication of the human genome sequence in 2001 represented one of the major milestones in the history of biology and much effort has since been devoted to describing and...