Generating High Density, Low Cost Genotype Data in Soybean [Glycine max (L.) Merr.]

Abstract

Obtaining genome-wide genotype information for millions of SNPs in soybean [Glycine max (L.) Merr.] often involves completely resequencing a line at 5X or greater coverage.Currently, hundreds of soybean lines have been resequenced at high depth levels with their data deposited in the NCBI short read achieve. This publicly available dataset may be leveraged as an imputation reference panel in combination with skim (low coverage) sequencing of new soybean genotypes to economically obtain high-density SNP information. Ninety-nine soybean lines resequenced at an average of 17.1X were used to generate a reference panel, with over 10 million SNPs called using GATK's Haplotype Caller tool. Whole genome resequencing at approximately 1X depth was performed on 114 previously ungenotyped experimental soybean lines. Coverages down to 0.1X were analyzed by randomly subsetting raw reads from the original 1X sequence data. SNPs discovered in the reference panel were genotyped in the experimental lines after aligning to the soybean reference genome, and missing markers imputed using Beagle 4.1. Sequencing depth of the experimental lines could be reduced to 0.3X while still retaining an accuracy of 97.8%. Accuracy was inversely related to minor allele frequency, and highly correlated with marker linkage disequilibrium. The high accuracy of skim sequencing combined with imputation provides a low cost method for obtaining dense genotypic information that can be used for various genomics applications in soybean.

The haplotype-based analysis ofAegilops tauschiiintrogression into hard red winter wheat and its impact on productivity traits

“…Imputation of markers from whole genome sequenced reference panels into skim-sequenced inference populations is increasingly becoming a common practice in plant breeding program due to its cost-effectiveness (Happ et al, 2019;Jessen et al, 2020). Our study demonstrates the utility of this strategy for detecting introgression in the wheat genome and contributes to developing genomic resources for deploying wild relative diversity in wheat breeding programs.…”

A bumper crop of SNPs in soybean through high‐density genotyping‐by‐sequencing (HD‐GBS)

“…To achieve a higher density of marker coverage than GBS or arrays, but at a lower cost than WGRS, Happ et al . (2019) used skim sequencing, WGRS performed at a decreased depth of coverage (0.1× to 1×), combined with imputation of missing data to capture a large number (up to ~1.3M) SNPs. Alternatively, Boudhrioua et al .…”

“…Although affordable, the latter genotyping technologies do not yield a sufficient number of SNPs to ensure the capture of all haplotypes across the entire genome. Extremely low‐depth sequencing (<1×) such as Skim‐Seq (Happ et al ., 2019) offers an interesting alternative to capture ~1M SNPs in soybean, but cost‐effective NGS library preparation and downstream data analysis (e.g. accurate missing data imputation) remain challenging.…”

“…To achieve a higher density of marker coverage than GBS or arrays, but at a lower cost than WGRS, Happ et al (2019) used skim sequencing, WGRS performed at a decreased depth of coverage (0.19 to 19), combined with imputation of missing data to capture a large number (up to~1.3M) SNPs. Alternatively, Boudhrioua et al (2020) relied on a low-cost GBS scan followed by imputation of over 4M SNPs from a reference panel of related elite soybean lines to achieve dense genome coverage at low cost.…”

Montagem >i<De novo>/i< de genomas contrastantes de soja para estudo da resistência ao complexo de percevejos

“…Com a crescente disponibilidade de dados genéticos e fenotípicos, melhoristas têm em mãos valiosos dados que podem ser aplicados ao melhoramento genético através de estudos de associação genômica ampla, seleção genômica e edição genética (Hu et al, 2018 (Happ et al, 2019); (Valliyodan et al, 2016). Foram obtidos um total de 335.229 indels únicos na IAC-100 e 248.725 indels compartilhados com CD-215.…”