Computational framework for mapping composite traits

WANG Jing, ZHU Sheng, LI Jiahui, ZHANG Li, ZHANG Meng, JIANG Libo, HUANG Minren, WU Rongling

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2018, Vol. 42 ›› Issue (04) : 89-96.

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南京林业大学学报（自然科学版）
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JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2018, Vol. 42 ›› Issue (04) : 89-96. DOI: 10.3969/j.issn.1000-2006.201702035

Computational framework for mapping composite traits

  • WANG Jing1, ZHU Sheng2, LI Jiahui1, ZHANG Li1, ZHANG Meng1, JIANG Libo1*, HUANG Minren2, WU Rongling1
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Abstract

Abstract: 【Objective】Composite traits are widely used in breeding. Currently, QTL(quantitative trait locus)mapping methods of composite traits only use a single phenotypic value, which is simply derived from a mathematical expression of two or more component traits. These approaches ignored the inherent biological mechanism of phenotype formation, which affects the precision of QTL mapping for composite traits.【Method】For the whole genome sequencing data, we present a new statistical infrastructure for QTL mapping that takes into account biological characteristics of composite traits. This method, termed composite traits mapping model(CTM), integrates different components within genetic mapping through mathematical relationships of composite traits.【Result】To validate the applicability of CTM, we applied it to analyze volume growth data of poplar and identified specific loci that were responsible for the volume growth. Compared with traditional methods for QTL mapping of composite traits, more significant loci were detected CTM exhibited a better performance. The computer simulation showed that CTM is a powerful model for mapping composite traits and the increase in sample size and heritability can increase the accuracy of parameter estimation. 【Conclusion】CTM is a useful tool for QTL mapping of composite traits, thus facilitating our understanding of the genetic architecture of composite traits.

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WANG Jing, ZHU Sheng, LI Jiahui, ZHANG Li, ZHANG Meng, JIANG Libo, HUANG Minren, WU Rongling. Computational framework for mapping composite traits[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2018, 42(04): 89-96 https://doi.org/10.3969/j.issn.1000-2006.201702035

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