InDelGT: An integrated pipeline for extracting indel genotypes for genetic mapping in a hybrid population using next-generation sequencing data

Zhiliang Pan; Jinpeng Zhang; Shengjun Bai; Zhiting Li; Chunfa Tong

doi:10.1002/aps3.11499

InDelGT: An integrated pipeline for extracting indel genotypes for genetic mapping in a hybrid population using next-generation sequencing data

Appl Plant Sci. 2022 Oct 27;10(6):e11499. doi: 10.1002/aps3.11499. eCollection 2022 Nov-Dec.

Authors

Zhiliang Pan¹, Jinpeng Zhang¹, Shengjun Bai¹, Zhiting Li¹, Chunfa Tong¹

Affiliation

¹ Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry Nanjing Forestry University Nanjing 210037 China.

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).

Keywords: genetic mapping population; genotype calling; insertion/deletion polymorphism (indel); next‐generation sequencing (NGS).