EFFICIENT ALLELE MINING IN A MODEL SEQUENCED CROP VIA THE COMPRESSED SEQUENCING APPROACH
Plant Stress and Germplasm Development Research
2012 Annual Report
1a.Objectives (from AD-416):
1. To validate if compressed sensing (CS) strategy can be used to analyze next generation sequencing data to identify known mutations in the sorghum library.
2. To explore CS strategy for allele mining in a few genes involved in drought tolerance.
1b.Approach (from AD-416):
The Co-PI (Xin) has created a pedigreed collection of 3,400 sorhgum mutant lines displaying many stress response and developmental phonotypes. The PI, Noami Shental, from the Computer Science Department, the Open University of Israel developed the compressed mutations. Pools of genomic DNA from the sorghum mutation library will be sequenced and analyzed with compressed sensing strategy to identify known mutations and new mutations in genes involved in drought tolerance.
The goal of the project is to identify rare mutation with next-generation sequencing. The role of ARS is to provide genomic DNA to the Massachusetts Institute of Technology (MIT) for sequencing and data analysis. With the BARD support, we have hired 2 summer student workers and a visiting scientist from Israel. We have processed 6000 lines for genomic DNA needed for the project. The DNA will be diluted to the required concentration and delivered to MIT.