RecombineX: A generalized computational framework for automatic high-throughput gamete genotyping and tetrad-based recombination analysis

PLoS Genet. 2022 May 9;18(5):e1010047. doi: 10.1371/journal.pgen.1010047. eCollection 2022 May.

Abstract

Meiotic recombination is an essential biological process that ensures faithful chromosome segregation and promotes parental allele shuffling. Tetrad analysis is a powerful approach to quantify the genetic makeups and recombination landscapes of meiotic products. Here we present RecombineX (https://github.com/yjx1217/RecombineX), a generalized computational framework that automates the full workflow of marker identification, gamete genotyping, and tetrad-based recombination profiling based on any organism or genetic background with batch processing capability. Aside from conventional reference-based analysis, RecombineX can also perform analysis based on parental genome assemblies, which facilitates analyzing meiotic recombination landscapes in their native genomic contexts. Additional features such as copy number variation profiling and missing genotype inference further enhance downstream analysis. RecombineX also includes a dedicate module for simulating the genomes and reads of recombinant tetrads, which enables fine-tuned simulation-based hypothesis testing. This simulation module revealed the power and accuracy of RecombineX even when analyzing tetrads with very low sequencing depths (e.g., 1-2X). Tetrad sequencing data from the budding yeast Saccharomyces cerevisiae and green alga Chlamydomonas reinhardtii were further used to demonstrate the accuracy and robustness of RecombineX for organisms with both small and large genomes, manifesting RecombineX as an all-around one stop solution for future tetrad analysis. Interestingly, our re-analysis of the budding yeast tetrad sequencing data with RecombineX and Oxford Nanopore sequencing revealed two unusual structural rearrangement events that were not noticed before, which exemplify the occasional genome instability triggered by meiosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • DNA Copy Number Variations*
  • Genotype
  • Germ Cells
  • Homologous Recombination
  • Meiosis* / genetics
  • Saccharomyces cerevisiae / genetics

Grants and funding

This work is supported by National Natural Science Foundation of China (32070592 to J.-X. Y. and 32000395 to J. L.), Guangdong Basic and Applied Basic Research Foundation (2019A1515110762 to J.-X. Y), Guangdong Pearl River Talents Program (2019QN01Y183 to J.-X. Y), Microsoft Azure Research Award (CRM:074871 to J.-X. Y.), ANR (ANR-15-IDEX-01 and ANR-20-CE13-0010 to G. L.; ANR-18-CE12-0013 to B. L.), Fondation pour la Recherche Médicale (EQU202003010413 to G. L), and Guangzhou Municipal Science and Technology Bureau (202102020938 to J. L.), respectively. The funders have not played any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.