Construction and analysis of high-density linkage map using high-throughput sequencing data.
Dongyuan Liu1, Chouxian Ma1, Weiguo Hong1
1Biomarker Technologies Corporation, Beijing, China.
Plos One
|June 7, 2014
Summary
HighMap is a new method for building high-density genetic linkage maps using next-generation sequencing (NGS) data. It improves marker accuracy and map quality, facilitating genome assembly and QTL studies.
Area of Science:
- Genetics
- Bioinformatics
- Genomics
Background:
- Linkage maps are crucial for biological research.
- Next-generation sequencing (NGS) facilitates high-density linkage map construction.
- NGS data presents challenges in marker number and genotyping errors, impacting computational efficiency and map quality.
Purpose of the Study:
- To develop an efficient and accurate method for constructing high-density linkage maps from NGS data.
- To address the computational and quality challenges posed by NGS data in linkage mapping.
Main Methods:
- HighMap employs an iterative ordering and error correction strategy.
- Utilizes a k-nearest neighbor algorithm and Monte Carlo multipoint maximum likelihood algorithm.
- Designed for high-throughput population NGS data.
Main Results:
- HighMap generates linkage maps with significantly more markers than ordering-only methods.
- Achieves more accurate marker orders and stable genetic distances.
- Constructed a common carp linkage map with 10,004 markers and a reduced singleton rate compared to JoinMap4.1.
Conclusions:
- HighMap is an efficient method for high-density, high-quality linkage map construction from NGS data.
- Facilitates genome assembly, comparative genomic analysis, and quantitative trait locus (QTL) studies.
- Provides a valuable tool for genetic research using large population NGS data.
