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Research Article | Open Access

Genetic mapping of quantitative trait loci in crops

Yang Xu, Pengcheng Li, Zefeng Yang, Chenwu Xu( )
Jiangsu Provincial Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of Ministry of Education, Yangzhou University, Yangzhou 225009, China

Peer review under responsibility of Crop Science Society of China and Institute of Crop Science, CAAS.

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Abstract

Dissecting the genetic architecture of complex traits is an ongoing challenge for geneticists. Two complementary approaches for genetic mapping, linkage mapping and association mapping have led to successful dissection of complex traits in many crop species. Both of these methods detect quantitative trait loci (QTL) by identifying marker–trait associations, and the only fundamental difference between them is that between mapping populations, which directly determine mapping resolution and power. Based on this difference, we first summarize in this review the advances and limitations of family-based mapping and natural population-based mapping instead of linkage mapping and association mapping. We then describe statistical methods used for improving detection power and computational speed and outline emerging areas such as large-scale meta-analysis for genetic mapping in crops. In the era of next-generation sequencing, there has arisen an urgent need for proper population design, advanced statistical strategies, and precision phenotyping to fully exploit high-throughput genotyping.

Keywords

Meta-analysisGenotyping by sequencingMAGIC populationMixed linear modelFamily-based mappingNatural population-based mapping

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The Crop Journal
Volume 5 Issue 2,
April 2017
Pages 175-184
DOI: 10.1016/j.cj.2016.06.003
Cite this article:
Xu Y, Li P, Yang Z, et al. Genetic mapping of quantitative trait loci in crops. The Crop Journal, 2017, 5(2): 175-184. https://doi.org/10.1016/j.cj.2016.06.003

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Received: 12 May 2016
Revised: 20 June 2016
Accepted: 11 July 2016
Published: 21 July 2016
© 2016 Crop Science Society of China and Institute of Crop Science, CAAS.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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