Literature DB >> 18492652

QTLs detected in a multigenerational resource chicken population.

Gil Atzmon1, Shula Blum, Marc Feldman, Avigdor Cahaner, Uri Lavi, Jossi Hillel.   

Abstract

The genetic structure of resource populations affects the power of tests to detect associations between DNA markers and complex traits. Following a chicken interline cross (White Plymouth Rock background), we produced a multigenerational resource population based on 4 pedigreed generations. In this large sibship, 265 parents have been genotyped, and their 3317 progenies have been phenotyped for BW21, BW42, breast meat weight, fat pad weight, and egg production. We developed an approach to increase test power by imposing several ways of validation including the minimization of false-positive associations. Some of our detected associations were in agreement with QTLs previously reported in the literature. A large fraction of the 81 screened markers was found to be associated with quantitative traits. We examined 729 associations, of which 150 (21%) were significant, and of these, 54 are supported by the literature. These 54 associations were identified by 42 markers (some of which are linked to each other). This finding not only supports the results obtained in our resource population but may also give some indication about their general properties.

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Year:  2008        PMID: 18492652     DOI: 10.1093/jhered/esn030

Source DB:  PubMed          Journal:  J Hered        ISSN: 0022-1503            Impact factor:   2.645


  8 in total

1.  A genome-wide scan of selective sweeps in two broiler chicken lines divergently selected for abdominal fat content.

Authors:  Hui Zhang; Shou-Zhi Wang; Zhi-Peng Wang; Yang Da; Ning Wang; Xiao-Xiang Hu; Yuan-Dan Zhang; Yu-Xiang Wang; Li Leng; Zhi-Quan Tang; Hui Li
Journal:  BMC Genomics       Date:  2012-12-15       Impact factor: 3.969

2.  Genome-wide association study of 8 carcass traits in Jinghai Yellow chickens using specific-locus amplified fragment sequencing technology.

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Journal:  Poult Sci       Date:  2016-03       Impact factor: 3.352

3.  Genome-wide association study of body weight in chicken F2 resource population.

Authors:  Xiaorong Gu; Chungang Feng; Li Ma; Chi Song; Yanqiang Wang; Yang Da; Huifang Li; Kuanwei Chen; Shaohui Ye; Changrong Ge; Xiaoxiang Hu; Ning Li
Journal:  PLoS One       Date:  2011-07-14       Impact factor: 3.240

4.  Genome-wide interval mapping using SNPs identifies new QTL for growth, body composition and several physiological variables in an F2 intercross between fat and lean chicken lines.

Authors:  Olivier Demeure; Michel J Duclos; Nicola Bacciu; Guillaume Le Mignon; Olivier Filangi; Frédérique Pitel; Anne Boland; Sandrine Lagarrigue; Larry A Cogburn; Jean Simon; Pascale Le Roy; Elisabeth Le Bihan-Duval
Journal:  Genet Sel Evol       Date:  2013-09-30       Impact factor: 4.297

5.  Genome-wide association analysis of egg production performance in chickens across the whole laying period.

Authors:  Zhuang Liu; Ning Yang; Yiyuan Yan; Guangqi Li; Aiqiao Liu; Guiqin Wu; Congjiao Sun
Journal:  BMC Genet       Date:  2019-08-14       Impact factor: 2.797

6.  Genome-Wide Association Studies and Haplotype-Sharing Analysis Targeting the Egg Production Traits in Shaoxing Duck.

Authors:  Wenwu Xu; Zhenzhen Wang; Yuanqi Qu; Qingyi Li; Yong Tian; Li Chen; Jianhong Tang; Chengfeng Li; Guoqin Li; Junda Shen; Zhengrong Tao; Yongqing Cao; Tao Zeng; Lizhi Lu
Journal:  Front Genet       Date:  2022-03-28       Impact factor: 4.599

7.  Detection of QTL controlling feed efficiency and excretion in chickens fed a wheat-based diet.

Authors:  Sandrine Mignon-Grasteau; Nicole Rideau; Irène Gabriel; Céline Chantry-Darmon; Marie-Yvonne Boscher; Nadine Sellier; Marie Chabault; Elisabeth Le Bihan-Duval; Agnès Narcy
Journal:  Genet Sel Evol       Date:  2015-09-25       Impact factor: 4.297

8.  Variance Component Quantitative Trait Locus Analysis for Body Weight Traits in Purebred Korean Native Chicken.

Authors:  Muhammad Cahyadi; Hee-Bok Park; Dong-Won Seo; Shil Jin; Nuri Choi; Kang-Nyeong Heo; Bo-Seok Kang; Cheorun Jo; Jun-Heon Lee
Journal:  Asian-Australas J Anim Sci       Date:  2016-01       Impact factor: 2.509

  8 in total

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