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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Plant Stress and Germplasm Development Research » Research » Publications at this Location » Publication #327160
Title: Highly efficient de novo mutant identification in a sorghum bicolor tilling population using the ComSeq approach

Author
item NIDA, HABTE - Hebrew University
item BLUM, SHULA - Hebrew University
item ESPOSITO, DINA - Columbia University
item SRIVASTAVA, DHRUV - Hebrew University
item ELBAUM, ROVKA - Hebrew University
item Xin, Zhanguo
item ERLICH, YANIV - Columbia University
item FRIDMAN, EYAL - Hebrew University
item SHENTAL, NOAM - Hebrew University

Submitted to: Plant Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/1/2016
Publication Date: 3/9/2016
Citation: Nida, H., Blum, S., Esposito, D., Srivastava, D., Elbaum, R., Xin, Z., Erlich, Y., Fridman, E., Shental, N. 2016. Highly efficient de novo mutant identification in a sorghum bicolor tilling population using the ComSeq approach. Plant Journal. 86:349-359.

Interpretive Summary: The PSGD developed sorghum mutant population consisting of 6,400 pedigreed lines. A core collection of 256 lines were sequenced that produced 1.8 million canonical GC to AT mutations covering 95% of the genes in sorghum genome. Over 74% of the genes harbor major disruptive mutation. Even with this vast resource, there is still an urgent need to search mutant series through Targeting induced local lesions IN genomes (TILLING). Screening large populations for carriers of known or de novo rare SNPs in plants and animal populations is expensive and time-consuming. We formerly suggested an approach that combines the celebrated mathematical field of compressed sensing with next generation sequencing to allow such large-scale screening. Based on pooled measurements the method can identify multiple carriers of either heterozygous or homozygous rare alleles while taking only a small fraction of resources. Its rigorous mathematical foundations allow scalable and robust detection providing error correction and resilience to experimental problems. This study presents a first experimental demonstration of our computational approach in which we target a TILLING population of 1024 Sorghum bicolor lines to detect carriers of de novo SNPs whose frequency was less than 0.1%, using merely 48 pools. Subsequent validation has shown that all detected lines were indeed carriers of the predicted mutations. This novel approach adds a highly cost-effective tool for biologists and breeders to allow functional analysis and identification of novel alleles. This method will allow the screen mutant series in sorghum from the remaining 6000 sorghum mutant lines that are not covered the 256 core sequenced lines and enable fast identification of target mutations to accelerate sorghum improvement.

Technical Abstract: Screening large populations for carriers of known or de novo rare SNPs is required both in Targeting induced local lesions IN genomes (TILLING) experiments in plants and analogously in screening human populations. We formerly suggested an approach that combines the celebrated mathematical field of compressed sensing with next generation sequencing to allow such large scale screening. Based on pooled measurements the method can identify multiple carriers of either heterozygous or homozygous rare alleles while taking only a small fraction of resources. Its rigorous mathematical foundations allow scalable and robust detection providing error correction and resilience to experimental problems. This study presents a first experimental demonstration of our computational approach in which we target a TILLING population of 1024 Sorghum bicolor lines to detect carriers of de novo SNPs whose frequency was less than 0.1%, using merely 48 pools. Subsequent validation has shown that all detected lines were indeed carriers of the predicted mutations. This novel approach adds a highly cost-effective tool for biologists and breeders to allow functional analysis and identification of novel alleles.