Construction and analysis of high-density linkage map using high-throughput sequencing data.

Dongyuan Liu,Hongkun Zheng,Huaping Zeng,Long Huang,Xiaowen Sun,Min Liu,Chouxian Ma,Hui Liu,Dejing Deng,Huaigen Xin,Xilin Hou,Jun Song,Chunhua Xu,Weiguo Hong,Xiaowu Wang,Chunyu Liu

doi:10.1371/journal.pone.0098855

Abstract

Linkage maps enable the study of important biological questions. The construction of high-density linkage maps appears more feasible since the advent of next-generation sequencing (NGS), which eases SNP discovery and high-throughput genotyping of large population. However, the marker number explosion and genotyping errors from NGS data challenge the computational efficiency and linkage map quality of linkage study methods. Here we report the HighMap method for constructing high-density linkage maps from NGS data. HighMap employs an iterative ordering and error correction strategy based on a k-nearest neighbor algorithm and a Monte Carlo multipoint maximum likelihood algorithm. Simulation study shows HighMap can create a linkage map with three times as many markers as ordering-only methods while offering more accurate marker orders and stable genetic distances. Using HighMap, we constructed a common carp linkage map with 10,004 markers. The singleton rate was less than one-ninth of that generated by JoinMap4.1. Its total map distance was 5,908 cM, consistent with reports on low-density maps. HighMap is an efficient method for constructing high-density, high-quality linkage maps from high-throughput population NGS data. It will facilitate genome assembling, comparative genomic analysis, and QTL studies. HighMap is available at http://highmap.biomarker.com.cn/.

Highlights

Linkage maps, especially high-density ones, play an important role in the study of genetics and genomics
To assess data utilization of HighMap, simulation data were generated from a full-sib family consisting of 200 offsprings
We intended to develop a method that can efficiently utilize next-generation sequencing (NGS) data and ease the construction of highdensity and high-quality linkage map. The challenges of such an effort are associated with the marker density explosion and potential genotyping errors, which involve sequencing depth and sequence heterozygosity

Summary

Introduction

Especially high-density ones, play an important role in the study of genetics and genomics. The genotyping approaches based on NGS, such as SLAF-seq (specific-locus amplified fragment sequencing) [10], RAD (restriction site associated DNA) genotyping [11], and genotyping-by-sequencing [12] are even capable of discovering and genotyping hundreds of thousands of genetic markers throughout the genome at relatively low cost [13]. These revolutionary advances in genotyping technologies provide exciting opportunities to economically construct increasingly dense maps [10,14,15]. The marker density explosion leads to the exponential increase in computational intensity [22]

Methods

Results

Conclusion