NDLI: The Negative Correlation between Fiber Color and Quality Traits Revealed by QTL Analysis.

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Jie Sun Xiongming Du Hongjie Feng Lixue Guo Gaskin Wang Junling Sun Zhaoe Pan Shoupu He Heqin Zhu
Abstract	Naturally existing colored cotton was far from perfection due to having genetic factors for lower yield, poor fiber quality and monotonous color. These factors posed a challenge to colored cotton breeding and innovation. To identify novel quantitative trait loci (QTL) for fiber color along with understanding of correlation between fiber color and quality in colored cotton, a RIL and two F2 populations were generated from crosses among Zong128 (Brown fiber cotton) and two white fiber cotton lines which were then analyzed in four environments. Two stable and major QTLs (qLC-7-1, qFC-7-1) for fiber lint and fuzz color were detected accounting for 16.01%-59.85% of the phenotypic variation across multiple generations and environments. Meanwhile, some minor QTLs were also identified on chromosomes 5, 14, 21 and 24 providing low phenotypic variation (<5%) from only F2 populations, not from the RILs population. Especially, a multiple-effect locus for fiber color and quality has been detected between flanking markers NAU1043 and NAU3654 on chromosome 7 (A genome) over multiple environments. Of which, qLC-7-1, qFC-7-1 were responsible for positive effects and improved fiber color in offsprings. Meanwhile, the QTLs (qFL-7-1, qFU-7-1, qFF-7-1, qFE-7-1, and qFS-7-1) for fiber quality had negative effects and explained 2.19%-8.78% of the phenotypic variation. This multiple-effect locus for fiber color and quality may reveal the negative correlation between the two types of above traits, so paving the way towards cotton genetic improvement.
e-ISSN	19326203
DOI	10.1371/journal.pone.0129490
Journal	PLoS ONE
Issue Number	6
Volume Number	10
Language	English
Publisher	Public Library of Science (PLoS)
Publisher Date	2015-01-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Medicine Science
Content Type	Text
Resource Type	Article

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