TY - GEN
T1 - A mapping-by-sequencing tool for searching causative genes in mutants
AU - Jia, Shangang
AU - Holding, David
AU - Zhang, Chi
N1 - Funding Information:
Corresponding author: David Holding. This work was supported by UNL Center for Plant Science Innovation Program of Excellence and UNL Department of Agronomy and Horticulture and by the Agriculture and Food Research Initiative competitive grant no. 2013-02278 of the USDA National Institute of Food and Agriculture.
Funding Information:
ACKNOWLEDGMENT The computing work in this project was supported by the Holland Computing Center of the University of Nebraska. This work was supported by the UNL Center for Plant Science Innovation Program of Excellence and the UNL Department of Agronomy and Horticulture and by the Agriculture and Food Research Initiative competitive grant no. 2013-02278 of the USDA National Institute of Food and Agriculture.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/27
Y1 - 2017/9/27
N2 - Bulk segregation analysis mapping is a widely used approach in functional genomics, especially now that low sequencing costs make mapping-by-sequencing realistic. However, the huge data processing required is not trivial. To help in this regard, we utilized our population of maize kernel mutants to develop a new mapping-by-sequencing analysis software tool, (MSA), to identify causative genes based on the DNA and RNA level variations in mutant pools. It is designed to identify the association regions, which show linkage disequilibrium to causative mutations, and place linkage peaks on the chromosomes. The method involves the comparison of mutant and normal pools of F2 individuals, and the parents for F2s can be also used alongside the two pools. It allows simultaneous analysis of multiple mutants and multiple normal samples, which can reduce the noise to make linkage peaks.
AB - Bulk segregation analysis mapping is a widely used approach in functional genomics, especially now that low sequencing costs make mapping-by-sequencing realistic. However, the huge data processing required is not trivial. To help in this regard, we utilized our population of maize kernel mutants to develop a new mapping-by-sequencing analysis software tool, (MSA), to identify causative genes based on the DNA and RNA level variations in mutant pools. It is designed to identify the association regions, which show linkage disequilibrium to causative mutations, and place linkage peaks on the chromosomes. The method involves the comparison of mutant and normal pools of F2 individuals, and the parents for F2s can be also used alongside the two pools. It allows simultaneous analysis of multiple mutants and multiple normal samples, which can reduce the noise to make linkage peaks.
KW - BSR-seq
KW - bulk segregation analysis
KW - causative mutation
KW - mapping-by-sequencing
KW - mutant
UR - http://www.scopus.com/inward/record.url?scp=85033710360&partnerID=8YFLogxK
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U2 - 10.1109/EIT.2017.8053381
DO - 10.1109/EIT.2017.8053381
M3 - Conference contribution
AN - SCOPUS:85033710360
T3 - IEEE International Conference on Electro Information Technology
SP - 338
EP - 340
BT - 2017 IEEE International Conference on Electro Information Technology, EIT 2017
PB - IEEE Computer Society
T2 - 2017 IEEE International Conference on Electro Information Technology, EIT 2017
Y2 - 14 May 2017 through 17 May 2017
ER -