| Title |
Genome-wide association study on chicken carcass traits using sequence data imputed from SNP array
|
|---|---|
| Published in |
Journal of Applied Genetics, June 2018
|
| DOI | 10.1007/s13353-018-0448-3 |
| Pubmed ID | |
| Authors |
Shuwen Huang, Yingting He, Shaopan Ye, Jiaying Wang, Xiaolong Yuan, Hao Zhang, Jiaqi Li, Xiquan Zhang, Zhe Zhang |
| Abstract |
Chicken carcass traits are economically important for the chicken industry. Detecting which genes affect chicken carcass traits is of great benefit to the genetic improvement of this important agricultural species. To investigate the genetic mechanism of carcass traits in chickens, we carried out a genome-wide association study (GWAS). A total of 435 Chinese indigenous chickens were phenotyped for carcass weight (CW), eviscerated weight with giblets (EWG), and eviscerated weight (EW) after slaughter at 91 days and were genotyped using a 600-K single nucleotide polymorphism (SNP) genotyping array. Twenty-four birds were selected for sequencing, and the 600 K SNP panel data were imputed to sequence data with the 24 birds as the reference. Univariate GWASs were performed with GEMMA software using the whole genome sequence data imputed from SNP chip data. Finally, 3, 25, and 63 suggestively significant SNPs were identified to be associated with carcass weight (CW), eviscerated weight with giblets (EWG), and eviscerated weight (EW), respectively. Six candidate genes, RNF219, SCEL, MYCBP2, ETS1, APLP2, and PRDM10 were detected. SCEL and MYCBP2 were potentially associated with these three traits, RNF219 and APLP2 were potentially associated with EWG and EW, and ETS1 and PRDM10 were only potentially associated with EWG and EW, respectively. Compared with forefathers' research, 10 reported QTLs associated with CW were located within a 5-Mb distance near the SNPs with P value lower than 1×10-5. This study enriched the knowledge of the genetic mechanisms of chicken carcass traits. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 14% |
| Student > Master | 3 | 14% |
| Student > Bachelor | 2 | 10% |
| Other | 1 | 5% |
| Lecturer | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 8 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 24% |
| Biochemistry, Genetics and Molecular Biology | 4 | 19% |
| Unspecified | 1 | 5% |
| Computer Science | 1 | 5% |
| Psychology | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 7 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 March 2023.
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#6,942,504
of 24,220,739 outputs
Outputs from Journal of Applied Genetics
#61
of 410 outputs
Outputs of similar age
#115,693
of 332,915 outputs
Outputs of similar age from Journal of Applied Genetics
#2
of 7 outputs
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