Dataset Information

Scanning and Filling: Ultra-Dense SNP Genotyping Combining Genotyping-By-Sequencing, SNP Array and Whole-Genome Resequencing Data.

ABSTRACT: Genotyping-by-sequencing (GBS) represents a highly cost-effective high-throughput genotyping approach. By nature, however, GBS is subject to generating sizeable amounts of missing data and these will need to be imputed for many downstream analyses. The extent to which such missing data can be tolerated in calling SNPs has not been explored widely. In this work, we first explore the use of imputation to fill in missing genotypes in GBS datasets. Importantly, we use whole genome resequencing data to assess the accuracy of the imputed data. Using a panel of 301 soybean accessions, we show that over 62,000 SNPs could be called when tolerating up to 80% missing data, a five-fold increase over the number called when tolerating up to 20% missing data. At all levels of missing data examined (between 20% and 80%), the resulting SNP datasets were of uniformly high accuracy (96-98%). We then used imputation to combine complementary SNP datasets derived from GBS and a SNP array (SoySNP50K). We thus produced an enhanced dataset of >100,000 SNPs and the genotypes at the previously untyped loci were again imputed with a high level of accuracy (95%). Of the >4,000,000 SNPs identified through resequencing 23 accessions (among the 301 used in the GBS analysis), 1.4 million tag SNPs were used as a reference to impute this large set of SNPs on the entire panel of 301 accessions. These previously untyped loci could be imputed with around 90% accuracy. Finally, we used the 100K SNP dataset (GBS + SoySNP50K) to perform a GWAS on seed oil content within this collection of soybean accessions. Both the number of significant marker-trait associations and the peak significance levels were improved considerably using this enhanced catalog of SNPs relative to a smaller catalog resulting from GBS alone at ?20% missing data. Our results demonstrate that imputation can be used to fill in both missing genotypes and untyped loci with very high accuracy and that this leads to more powerful genetic analyses.

SUBMITTER: Torkamaneh D

PROVIDER: S-EPMC4498655 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Scanning and Filling: Ultra-Dense SNP Genotyping Combining Genotyping-By-Sequencing, SNP Array and Whole-Genome Resequencing Data.

Torkamaneh Davoud D Belzile Francois F

PloS one 20150710 7

Genotyping-by-sequencing (GBS) represents a highly cost-effective high-throughput genotyping approach. By nature, however, GBS is subject to generating sizeable amounts of missing data and these will need to be imputed for many downstream analyses. The extent to which such missing data can be tolerated in calling SNPs has not been explored widely. In this work, we first explore the use of imputation to fill in missing genotypes in GBS datasets. Importantly, we use whole genome resequencing data ...[more]

PMID: 26161900

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Project description:BackgroundA whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNP-based linkage map of an apple rootstock progeny.ResultsOf the 7,867 Malus SNP markers on the array, 1,823 (23.2%) were heterozygous in one of the two parents of the progeny, 1,007 (12.8%) were heterozygous in both parental genotypes, whilst just 2.8% of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the 'Golden Delicious' genome sequence. A total of 311 markers (13.7% of all mapped markers) mapped to positions that conflicted with their predicted positions on the 'Golden Delicious' pseudo-chromosomes, indicating the presence of paralogous genomic regions or mis-assignments of genome sequence contigs during the assembly and anchoring of the genome sequence.ConclusionsWe incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the 'Golden Delicious' reference sequence will assist in the continued improvement of the genome sequence assembly for that variety.

Project description:BackgroundChina has the richest local chicken breeding resources in the world and is the world's second largest producer of meat-type chickens. Development of a moderate-density SNP array for genetic analysis of chickens and breeding of meat-type chickens taking utility of those resources is urgently needed for conventional farms, breeding industry, and research areas.ResultsEight representative local breeds or commercial broiler lines with 3 pools of 48 individuals within each breed/line were sequenced and supplied the major SNPs resource. There were 7.09 million - 9.41 million SNPs detected in each breed/line. After filtering using multiple criteria such as preferred incorporation of trait-related SNPs and uniformity of distribution across the genome, 52.18 K SNPs were selected in the final array. It consists of: (i) 19.22 K SNPs from the genomes of yellow-feathered, cyan-shank partridge and white-feathered chickens; (ii) 5.98 K SNPs related to economic traits from the Illumina 60 K SNP Bead Chip, which were found as significant associated SNPs with 15 traits in a Beijing-You crossed Cobb F2 resource population by genome-wide association study analysis; (iii) 7.63 K SNPs from 861 candidate genes of economic traits; (iv) the 0.94 K SNPs related to residual feed intake; and (v) 18.41 K from chicken SNPdb. The polymorphisms of 9 extra local breeds and 3 commercial lines were examined with this array, and 40 K - 47 K SNPs were polymorphic (with minor allele frequency > 0.05) in those breeds. The MDS result showed that those breeds can be clearly distinguished by this newly developed genotyping array.ConclusionsWe successfully developed a 55K genotyping array by using SNPs segregated from typical local breeds and commercial lines. Compared to the existing Affy 600 K and Illumina 60 K arrays, there were 21,41 K new SNPs included on our Affy 55K array. The results of the 55K genotyping data can therefore be imputed to high-density SNPs genotyping data. The array offers a wide range of potential applications such as genomic selection breeding, GWAS of interested traits, and investigation of diversity of different chicken breeds.

Project description:BACKGROUND:In forest trees, genetic markers have been used to understand the genetic architecture of natural populations, identify quantitative trait loci, infer gene function, and enhance tree breeding. Recently, new, efficient technologies for genotyping thousands to millions of single nucleotide polymorphisms (SNPs) have finally made large-scale use of genetic markers widely available. These methods will be exceedingly valuable for improving tree breeding and understanding the ecological genetics of Douglas-fir, one of the most economically and ecologically important trees in the world. RESULTS:We designed SNP assays for 55,766 potential SNPs that were discovered from previous transcriptome sequencing projects. We tested the array on ~ 2300 related and unrelated coastal Douglas-fir trees (Pseudotsuga menziesii var. menziesii) from Oregon and Washington, and 13 trees of interior Douglas-fir (P. menziesii var. glauca). As many as ~ 28 K SNPs were reliably genotyped and polymorphic, depending on the selected SNP call rate. To increase the number of SNPs and improve genome coverage, we developed protocols to 'rescue' SNPs that did not pass the default Affymetrix quality control criteria (e.g., 97% SNP call rate). Lowering the SNP call rate threshold from 97 to 60% increased the number of successful SNPs from 20,669 to 28,094. We used a subset of 395 unrelated trees to calculate SNP population genetic statistics for coastal Douglas-fir. Over a range of call rate thresholds (97 to 60%), the median call rate for SNPs in Hardy-Weinberg equilibrium ranged from 99.2 to 99.7%, and the median minor allele frequency ranged from 0.198 to 0.233. The successful SNPs also worked well on interior Douglas-fir. CONCLUSIONS:Based on the original transcriptome assemblies and comparisons to version 1.0 of the Douglas-fir reference genome, we conclude that these SNPs can be used to genotype about 10 K to 15 K loci. The Axiom genotyping array will serve as an excellent foundation for studying the population genomics of Douglas-fir and for implementing genomic selection. We are currently using the array to construct a linkage map and test genomic selection in a three-generation breeding program for coastal Douglas-fir.

Project description:High-density SNP arrays for genome-wide assessment of allelic variation have made high resolution genetic characterization of crop germplasm feasible. A medium density array for apple, the IRSC 8K SNP array, has been successfully developed and used for screens of bi-parental populations. However, the number of robust and well-distributed markers contained on this array was not sufficient to perform genome-wide association analyses in wider germplasm sets, or Pedigree-Based Analysis at high precision, because of rapid decay of linkage disequilibrium. We describe the development of an Illumina Infinium array targeting 20K SNPs. The SNPs were predicted from re-sequencing data derived from the genomes of 13 Malus × domestica apple cultivars and one accession belonging to a crab apple species (M. micromalus). A pipeline for SNP selection was devised that avoided the pitfalls associated with the inclusion of paralogous sequence variants, supported the construction of robust multi-allelic SNP haploblocks and selected up to 11 entries within narrow genomic regions of ±5 kb, termed focal points (FPs). Broad genome coverage was attained by placing FPs at 1 cM intervals on a consensus genetic map, complementing them with FPs to enrich the ends of each of the chromosomes, and by bridging physical intervals greater than 400 Kbps. The selection also included ∼3.7K validated SNPs from the IRSC 8K array. The array has already been used in other studies where ∼15.8K SNP markers were mapped with an average of ∼6.8K SNPs per full-sib family. The newly developed array with its high density of polymorphic validated SNPs is expected to be of great utility for Pedigree-Based Analysis and Genomic Selection. It will also be a valuable tool to help dissect the genetic mechanisms controlling important fruit quality traits, and to aid the identification of marker-trait associations suitable for the application of Marker Assisted Selection in apple breeding programs.

Dataset Information

Scanning and Filling: Ultra-Dense SNP Genotyping Combining Genotyping-By-Sequencing, SNP Array and Whole-Genome Resequencing Data.

Publications

Scanning and Filling: Ultra-Dense SNP Genotyping Combining Genotyping-By-Sequencing, SNP Array and Whole-Genome Resequencing Data.

Similar Datasets

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