Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.

Genetic architecture of branch traits has large influences on the morphological structure, photosynthetic capacity, planting density, and yield of Upland cotton (Gossypium hirsutum L.). This research aims to reveal the genetic effects of six branch traits, including bottom fruit branch node number (...

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Main Authors: Yongjun Mei, Jiwen Yu, Angli Xue, Shuli Fan, Meizhen Song, Chaoyou Pang, Wenfeng Pei, Shuxun Yu, Jun Zhu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5266336?pdf=render
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spelling doaj-e95786fdb2ee4851979513acc6ea46b42020-11-25T01:45:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01121e016281510.1371/journal.pone.0162815Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.Yongjun MeiJiwen YuAngli XueShuli FanMeizhen SongChaoyou PangWenfeng PeiShuxun YuJun ZhuGenetic architecture of branch traits has large influences on the morphological structure, photosynthetic capacity, planting density, and yield of Upland cotton (Gossypium hirsutum L.). This research aims to reveal the genetic effects of six branch traits, including bottom fruit branch node number (BFBNN), bottom fruit branch length (BFBL), middle fruit branch node number (MFBNN), middle fruit branch length (MFBL), upper fruit branch node number (UFBNN), and upper fruit branch length (UFBL). Association mapping was conducted for these traits of 39 lines and their 178 F1 hybrids in three environments. There were 20 highly significant Quantitative Trait SSRs (QTSs) detected by mixed linear model approach analyzing a full genetic model with genetic effects of additive, dominance, epistasis and their environment interaction. The phenotypic variation explained by genetic effects ranged from 32.64 ~ 91.61%, suggesting these branch traits largely influenced by genetic factors.http://europepmc.org/articles/PMC5266336?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Yongjun Mei
Jiwen Yu
Angli Xue
Shuli Fan
Meizhen Song
Chaoyou Pang
Wenfeng Pei
Shuxun Yu
Jun Zhu
spellingShingle Yongjun Mei
Jiwen Yu
Angli Xue
Shuli Fan
Meizhen Song
Chaoyou Pang
Wenfeng Pei
Shuxun Yu
Jun Zhu
Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.
PLoS ONE
author_facet Yongjun Mei
Jiwen Yu
Angli Xue
Shuli Fan
Meizhen Song
Chaoyou Pang
Wenfeng Pei
Shuxun Yu
Jun Zhu
author_sort Yongjun Mei
title Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.
title_short Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.
title_full Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.
title_fullStr Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.
title_full_unstemmed Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.
title_sort dissecting genetic network of fruit branch traits in upland cotton by association mapping using ssr markers.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description Genetic architecture of branch traits has large influences on the morphological structure, photosynthetic capacity, planting density, and yield of Upland cotton (Gossypium hirsutum L.). This research aims to reveal the genetic effects of six branch traits, including bottom fruit branch node number (BFBNN), bottom fruit branch length (BFBL), middle fruit branch node number (MFBNN), middle fruit branch length (MFBL), upper fruit branch node number (UFBNN), and upper fruit branch length (UFBL). Association mapping was conducted for these traits of 39 lines and their 178 F1 hybrids in three environments. There were 20 highly significant Quantitative Trait SSRs (QTSs) detected by mixed linear model approach analyzing a full genetic model with genetic effects of additive, dominance, epistasis and their environment interaction. The phenotypic variation explained by genetic effects ranged from 32.64 ~ 91.61%, suggesting these branch traits largely influenced by genetic factors.
url http://europepmc.org/articles/PMC5266336?pdf=render
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