Highly efficientde novomutant identification in aSorghum bicolorTILLING population using the ComSeq approach

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Abstract

Screening large populations for carriers of known orde novorare single nucleotide polymorphisms (SNPs) is required both in Targeting induced local lesions in genomes (TILLING) experiments in plants and in screening of human populations. We previously suggested an approach that combines the mathematical field of compressed sensing with next-generation sequencing to allow such large-scale screening. Based on pooled measurements, this method identifies multiple carriers of heterozygous or homozygous rare alleles while using only a small fraction of resources. Its rigorous mathematical foundations allow scalable and robust detection, and provide error correction and resilience to experimental noise. Here we present a large-scale experimental demonstration of our computational approach, in which we targeted a TILLING population of 1024Sorghum bicolorlines to detect carriers ofde novoSNPs whose frequency was less than 0.1%, using only 48 pools. Subsequent validation confirmed that all detected lines were indeed carriers of the predicted mutations. This novel approach provides a highly cost-effective and robust tool for biologists and breeders to allow identification of novel alleles and subsequent functional analysis.

Significance Statement

To improve plant productivity, it is desirable to develop more efficient methods to enrich the allelic repertoire used for breeding. Here, using compressed sequencing (ComSeq) with a Sorghum bicolor TILLING population, we detected and validated carriers of rare de novo SNPs.

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