Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Nov 6;20(1):83.
doi: 10.1186/s12863-019-0783-3.

Unraveling genomic associations with feed efficiency and body weight traits in chickens through an integrative approach

Gabriel Costa Monteiro Moreira  1 , Mirele Daiana Poleti  2 , Fábio Pértille  1 , Clarissa Boschiero  1 , Aline Silva Mello Cesar  1 , Thaís Fernanda Godoy  1 , Mônica Corrêa Ledur  3 , James M Reecy  4 , Dorian J Garrick  5 , Luiz Lehmann Coutinho  6
Affiliations

Unraveling genomic associations with feed efficiency and body weight traits in chickens through an integrative approach

Gabriel Costa Monteiro Moreira et al. BMC Genet. .

Abstract

Background: Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations.

Results: Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1-4, 6-7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens.

Conclusions: The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs.

Keywords: GWAS; Genomic heritability; Genotypic data; performance traits.

PubMed Disclaimer

Conflict of interest statement

Dr. James Reecy is a member of the editorial board (Associate Editor) of BMC Genetics. The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Manhattan plots of the posterior means of the percentage of genetic variance explained by each 1 Mb SNP window across the 28 autosomal chromosomes for all the performance traits analyzed. The title of each graph indicates the corresponding phenotype: feed intake (FI), feed conversion (FC), feed efficiency (FE), weight gain (WG), body weight at hatch (BW1); body weight at 35 days of age (BW35); body weight at 41 days of age (BW41). The X-axis represents the ordered chromosomes, and Y-axis shows the proportion of genetic variance explained by each window from Bayes B analysis. Red lines indicate the threshold to deem significant SNP windows (0.53%)
See this image and copyright information in PMC

References

    1. Berri C, Wacrenier N, Millet N, Le Bihan-Duval E. Effect of selection for improved body composition on muscle and meat characteristics of broilers from experimental and commercial lines. Poult Sci. 2001;80:833–838. doi: 10.1093/ps/80.7.833. - DOI - PubMed
    1. Moreira G. C. M., Godoy T. F., Boschiero C., Gheyas A., Gasparin G., Andrade S. C. S., Paduan M., Montenegro H., Burt D. W., Ledur M. C., Coutinho L. L. Variant discovery in a QTL region on chromosome 3 associated with fatness in chickens. Animal Genetics. 2015;46(2):141–147. doi: 10.1111/age.12263. - DOI - PubMed
    1. Mebratie W, Reyer H, Wimmers K, Bovenhuis H, Jensen J. Genome wide association study of body weight and feed efficiency traits in a commercial broiler chicken population, a re-visitation. Sci. Rep. Nature Publishing Group; 2019 [cited 2019 Sep 8];9:922 Available from: http://www.nature.com/articles/s41598-018-37216-z - PMC - PubMed
    1. Gao N, Li J, He J, Xiao G, Luo Y, Zhang H, et al. Improving accuracy of genomic prediction by genetic architecture based priors in a Bayesian model. BMC Genet. [Internet]. BioMed Central; 2015 [cited 2019 Jun 3];16:120. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26466667. - PMC - PubMed
    1. Wolc A., Kranis A., Arango J., Settar P., Fulton J.E., O'Sullivan N.P., Avendano A., Watson K.A., Hickey J.M., de los Campos G., Fernando R.L., Garrick D.J., Dekkers J.C.M. Implementation of genomic selection in the poultry industry. Animal Frontiers. 2016;6(1):23–31. doi: 10.2527/af.2016-0004. - DOI

Publication types