Dataset Information

Dense genotyping-by-sequencing linkage maps of two Synthetic W7984×Opata reference populations provide insights into wheat structural diversity.

ABSTRACT: Wheat (Triticum aestivum) genetic maps are a key enabling tool for genetic studies. We used genotyping-by-sequencing-(GBS) derived markers to map recombinant inbred line (RIL) and doubled haploid (DH) populations from crosses of W7984 by Opata, and used the maps to explore features of recombination control. The RIL and DH populations, SynOpRIL and SynOpDH, were composed of 906 and 92 individuals, respectively. Two high-density genetic linkage framework maps were constructed of 2,842 and 2,961?cM, harboring 3,634 and 6,580 markers, respectively. Using imputation, we added 43,013 and 86,042 markers to the SynOpRIL and SynOpDH maps. We observed preferential recombination in telomeric regions and reduced recombination in pericentromeric regions. Recombination rates varied between subgenomes, with the D genomes of the two populations exhibiting the highest recombination rates of 0.26-0.27?cM/Mb. QTL mapping identified two additive and three epistatic loci associated with crossover number. Additionally, we used published POPSEQ data from SynOpDH to explore the structural variation in W7984 and Opata. We found that chromosome 5AS is missing from W7984. We also found 2,332 variations larger than 100?kb. Structural variants were more abundant in distal regions, and overlapped 9,196 genes. The two maps provide a resource for trait mapping and genomic-assisted breeding.

SUBMITTER: Gutierrez-Gonzalez JJ

PROVIDER: S-EPMC6370774 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dense genotyping-by-sequencing linkage maps of two Synthetic W7984×Opata reference populations provide insights into wheat structural diversity.

Gutierrez-Gonzalez Juan J JJ Mascher Martin M Poland Jesse J Muehlbauer Gary J GJ

Scientific reports 20190211 1

Wheat (Triticum aestivum) genetic maps are a key enabling tool for genetic studies. We used genotyping-by-sequencing-(GBS) derived markers to map recombinant inbred line (RIL) and doubled haploid (DH) populations from crosses of W7984 by Opata, and used the maps to explore features of recombination control. The RIL and DH populations, SynOpRIL and SynOpDH, were composed of 906 and 92 individuals, respectively. Two high-density genetic linkage framework maps were constructed of 2,842 and 2,961 cM ...[more]

PMID: 30741967

Similar Datasets

Project description:BackgroundGenotyping-by-sequencing (GBS) provides affordable methods for genotyping hundreds of individuals using millions of markers. However, this challenges bioinformatic procedures that must overcome possible artifacts such as the bias generated by polymerase chain reaction duplicates and sequencing errors. Genotyping errors lead to data that deviate from what is expected from regular meiosis. This, in turn, leads to difficulties in grouping and ordering markers, resulting in inflated and incorrect linkage maps. Therefore, genotyping errors can be easily detected by linkage map quality evaluations.ResultsWe developed and used the Reads2Map workflow to build linkage maps with simulated and empirical GBS data of diploid outcrossing populations. The workflows run GATK, Stacks, TASSEL, and Freebayes for single-nucleotide polymorphism calling and updog, polyRAD, and SuperMASSA for genotype calling, as well as OneMap and GUSMap to build linkage maps. Using simulated data, we observed which genotype call software fails in identifying common errors in GBS sequencing data and proposed specific filters to better handle them. We tested whether it is possible to overcome errors in a linkage map using genotype probabilities from each software or global error rates to estimate genetic distances with an updated version of OneMap. We also evaluated the impact of segregation distortion, contaminant samples, and haplotype-based multiallelic markers in the final linkage maps. Through our evaluations, we observed that some of the approaches produce different results depending on the dataset (dataset dependent) and others produce consistent advantageous results among them (dataset independent).ConclusionsWe set as default in the Reads2Map workflows the approaches that showed to be dataset independent for GBS datasets according to our results. This reduces the number of required tests to identify optimal pipelines and parameters for other empirical datasets. Using Reads2Map, users can select the pipeline and parameters that best fit their data context. The Reads2MapApp shiny app provides a graphical representation of the results to facilitate their interpretation.

Dataset Information

Dense genotyping-by-sequencing linkage maps of two Synthetic W7984×Opata reference populations provide insights into wheat structural diversity.

Publications

Dense genotyping-by-sequencing linkage maps of two Synthetic W7984×Opata reference populations provide insights into wheat structural diversity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets