InDelGT: An integrated pipeline for extracting indel genotypes for genetic mapping in a hybrid population using next‐generation sequencing data
2022
Zhiliang Pan | Jinpeng Zhang | Shengjun Bai | Zhiting Li | Chunfa Tong
Abstract Premise Although several software packages are available for genotyping insertion/deletion (indel) polymorphisms in genomes using next‐generation sequencing data, simultaneously calling indel genotypes across many individuals for use in genetic mapping remains challenging. Methods and Results We present an integrated pipeline, InDelGT, for the extraction of indel genotypes from a segregating population such as backcross or F2 lines, or from an F1 cross between outbred species. The InDelGT algorithm is implemented in three steps: generating an indel catalog, calling indel genotypes, and analyzing indel segregation. We demonstrated the use of the pipeline with an example data set from an F1 hybrid population of Populus and successfully constructed the two parental genetic linkage maps. Conclusions InDelGT is a practical tool that can quickly genotype a large number of indel markers within a population following Mendelian segregation. The InDelGT pipeline is freely available on GitHub (https://github.com/tongchf/InDelGT).
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