Finding invisible quantitative trait loci with missing data.

Iulian Gabur,Christian Obermeier,Harmeet S Chawla,Vinod Kumar,Susann Volkmann,Xiwei Liu,Emmanuelle Dryzska,Sébastien Faure,Andreas Von Tiedemann,Christophe Jestin,Régine Delourme,Rod Snowdon,Frank Breuer

doi:10.1111/pbi.12942

Abstract

SummaryEvolutionary processes during plant polyploidization and speciation have led to extensive presence–absence variation (PAV) in crop genomes, and there is increasing evidence that PAV associates with important traits. Today, high‐resolution genetic analysis in major crops frequently implements simple, cost‐effective, high‐throughput genotyping from single nucleotide polymorphism (SNP) hybridization arrays; however, these are normally not designed to distinguish PAV from failed SNP calls caused by hybridization artefacts. Here, we describe a strategy to recover valuable information from single nucleotide absence polymorphisms (SNaPs) by population‐based quality filtering of SNP hybridization data to distinguish patterns associated with genuine deletions from those caused by technical failures. We reveal that including SNaPs in genetic analyses elucidate segregation of small to large‐scale structural variants in nested association mapping populations of oilseed rape (Brassica napus), a recent polyploid crop with widespread structural variation. Including SNaP markers in genomewide association studies identified numerous quantitative trait loci, invisible using SNP markers alone, for resistance to two major fungal diseases of oilseed rape, Sclerotinia stem rot and blackleg disease. Our results indicate that PAV has a strong influence on quantitative disease resistance in B. napus and that SNaP analysis using cost‐effective SNP array data can provide extensive added value from ‘missing data’. This strategy might also be applicable for improving the precision of genetic mapping in many important crop species.

Highlights

Structural variation in genomes of humans, animals and plants is an essential class of genetic polymorphism that is today commonly used for genomic analysis (Dolatabadian et al, 2017)
insertions and deletions (InDels) have been defined as short presence–absence polymorphisms spanning from 1 to 50 bp, whereas copy number variation (CNV) results from gain or losses of larger DNA segments ranging from a few nucleotides to several kb of DNA in the size range of genes
From failed single nucleotide polymorphism (SNP) calls to single nucleotide absence polymorphism markers

Summary

Introduction

Structural variation in genomes of humans, animals and plants is an essential class of genetic polymorphism that is today commonly used for genomic analysis (Dolatabadian et al, 2017). In recent years genetic diversity for structural genome variation in the form of InDels, CNV and PAV have been investigated widely in humans (Iafrate et al, 2004), bacteria (Arrach et al, 2008), animals (Graubert et al, 2007; Guryev et al, 2008; Snijders et al, 2005; Wilson et al, 2006) and plants (Batley et al, 2003; Hurgobin et al, 2017; Qian et al, 2016; Schiessl et al, 2017; Springer et al, 2009; Stein et al, 2017). Detection of PAV in GBS and skim-sequencing datasets can be complicated by difficulties in distinguishing genuine deletions from regions with insufficient sequence coverage, along with bioinformatic challenges associated with haplotype imputation

Results

Discussion

Conclusion