2015
DOI: 10.4238/2015.december.1.30
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A genome-wide association study of growth trait-related single nucleotide polymorphisms in Chinese Yancheng chickens

Abstract: ABSTRACT. Chicken (Gallus gallus) growth traits are important economic traits, and many studies have been conducted on genetic selection for body weight. However, most of these studies have detected functional chromosome mutations or regions by conventional molecular markers or gene chips. In this study, we performed a new genome-wide association study using specific-locus amplified fragment sequencing (SLAFseq) technology in purebred Yancheng chickens. Single nucleotide polymorphisms (SNPs) that were signific… Show more

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Cited by 27 publications
(21 citation statements)
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References 32 publications
(30 reference statements)
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“…Sewalem et al used an F 2 chicken population from a cross of a broiler sire-line and an egg laying (White Leghorn) line to identify QTLs on Chr1, -2, -4, -7, -8, and -13 that affected BW, and Chr4 had the largest single additive effect (Sewalem et al 2002). Researchers identified QTLs on Chr4 that affected growth performance in different varieties and populations (Brandt et al 2017;Jin et al 2015;Li et al 2018), such as a White Leghorn × Rhode Island Red cross (Sasaki et al 2004), a Silky Fowl × White Plymouth Rock cross (Gu et al 2011), Beijing-You chickens (Liu et al 2013), and a population of purebred white layers (WLA) with White Leghorn origin (Lyu et al 2018). In this study, 17 phenotypes, including BW8, BW12, SL12, CWe and the weight of several internal organs, were mapped on Chr4, indicating that genes on Chr4 may have large effects on BW.…”
Section: Figmentioning
confidence: 99%
“…Sewalem et al used an F 2 chicken population from a cross of a broiler sire-line and an egg laying (White Leghorn) line to identify QTLs on Chr1, -2, -4, -7, -8, and -13 that affected BW, and Chr4 had the largest single additive effect (Sewalem et al 2002). Researchers identified QTLs on Chr4 that affected growth performance in different varieties and populations (Brandt et al 2017;Jin et al 2015;Li et al 2018), such as a White Leghorn × Rhode Island Red cross (Sasaki et al 2004), a Silky Fowl × White Plymouth Rock cross (Gu et al 2011), Beijing-You chickens (Liu et al 2013), and a population of purebred white layers (WLA) with White Leghorn origin (Lyu et al 2018). In this study, 17 phenotypes, including BW8, BW12, SL12, CWe and the weight of several internal organs, were mapped on Chr4, indicating that genes on Chr4 may have large effects on BW.…”
Section: Figmentioning
confidence: 99%
“…Reproduction traits are controlled by quantitative trait loci, and a genome-wide scan is an effective approach that can be used to gain an understanding of these complex traits. As a statistical tool, GWAS is one of the most effective methods for identifying important SNP and functional genes that affect quantitative traits ( Jin, et al., 2015 ). The technique is more efficient at identifying genetic characteristics for economic traits than the candidate gene approach.…”
Section: Introductionmentioning
confidence: 99%
“…Besnier et al (2011) found that QTLs in the region 169-175 Mb on GGA1 had an effect on BW56. Jin et al (2015) found that 18 SNPs reached 5% Bonferroni genome-wide significance with growth traits in Yancheng chickens, and these SNPs, which were located on four different chromosomes and in a region of 72.3-82.1 Mb on GGA4, had a significant effect on growth traits. In the present study, six SNPs significantly associated with BWF were detected on GGA1, of which two (173.0-175.2 Mb) were within the region where SNPs were identified by Xie et al (2012) and Besnier et al (2011).…”
Section: Egg Numbermentioning
confidence: 99%
“…Genome-wide association studies (GWAS) are used to identify SNPs and functional genes that affect quantitative traits (Jin et al, 2015). This technique is more efficient at identifying genetic characteristics for economic traits than the candidate gene approach.…”
Section: Introductionmentioning
confidence: 99%