PNGSeqR: An R Package for Rapid Candidate Gene Selection through Pooled Next-Generation Sequencing
Sihan Zhen,
Hongwei Zhang,
Yuxin Xie,
Song Zhang,
Yan Chen,
Riliang Gu,
Sanzhen Liu,
Xuemei Du,
Junjie Fu
Affiliations
Sihan Zhen
Seed Science and Technology Research Center, Beijing Innovation Center for Seed Technology (MOA), Beijing Key Laboratory for Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
Hongwei Zhang
Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Yuxin Xie
Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Song Zhang
Seed Science and Technology Research Center, Beijing Innovation Center for Seed Technology (MOA), Beijing Key Laboratory for Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
Yan Chen
Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Riliang Gu
Seed Science and Technology Research Center, Beijing Innovation Center for Seed Technology (MOA), Beijing Key Laboratory for Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
Sanzhen Liu
Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
Xuemei Du
Seed Science and Technology Research Center, Beijing Innovation Center for Seed Technology (MOA), Beijing Key Laboratory for Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
Junjie Fu
Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Although bulked segregant analysis (BSA) has been used extensively in genetic mapping, user-friendly tools which can integrate current algorithms for researchers with no background in bioinformatics are scarce. To address this issue, we developed an R package, PNGSeqR, which takes single-nucleotide polymorphism (SNP) markers from next-generation sequencing (NGS) data in variant call format (VCF) as the input file, provides four BSA algorithms to indicate the magnitude of genome-wide signals, and rapidly defines the candidate region through the permutation test and fractile quantile. Users can choose the analysis methods according to their data and experimental design. In addition, it also supports differential expression gene analysis (DEG) and gene ontology analysis (GO) to prioritize the target gene. Once the analysis is completed, the plots can conveniently be exported.
