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Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle.

Crispim AC, Kelly MJ, Guimarães SE, Fonseca e Silva F, Fortes MR, Wenceslau RR, Moore S - PLoS ONE (2015)

Bottom Line: One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively.The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1).Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.

View Article: PubMed Central - PubMed

Affiliation: Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.

ABSTRACT
Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.

No MeSH data available.


Manhattan plots for the growth curve parameter mature weight (A) in Brahman cattle.Chromosomes 1 to 29 and X are shown, separated by alternating colors. The corresponding horizontal lines indicate the genome-wide significance levels for both traits.
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pone.0139906.g001: Manhattan plots for the growth curve parameter mature weight (A) in Brahman cattle.Chromosomes 1 to 29 and X are shown, separated by alternating colors. The corresponding horizontal lines indicate the genome-wide significance levels for both traits.

Mentions: The Manhattan plots pointed 167 and 262 significant SNPs associated with mature weight (A) and maturity rate (K), respectively (Fig 1 and Fig 2). The peak that was observed for A was composed of 44 significant SNPs, which started from 13417489 to 114954346 bp on BTA6, and the SNP with the lowest p-value was located at 97907606 bp. In spite of K, Manhattan plots indicated 64 significant SNPs at BTA20, starting from 1876553 to 69791421 bp, and the SNP with the lowest p value was located at 11089453 bp.


Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle.

Crispim AC, Kelly MJ, Guimarães SE, Fonseca e Silva F, Fortes MR, Wenceslau RR, Moore S - PLoS ONE (2015)

Manhattan plots for the growth curve parameter mature weight (A) in Brahman cattle.Chromosomes 1 to 29 and X are shown, separated by alternating colors. The corresponding horizontal lines indicate the genome-wide significance levels for both traits.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4622042&req=5

pone.0139906.g001: Manhattan plots for the growth curve parameter mature weight (A) in Brahman cattle.Chromosomes 1 to 29 and X are shown, separated by alternating colors. The corresponding horizontal lines indicate the genome-wide significance levels for both traits.
Mentions: The Manhattan plots pointed 167 and 262 significant SNPs associated with mature weight (A) and maturity rate (K), respectively (Fig 1 and Fig 2). The peak that was observed for A was composed of 44 significant SNPs, which started from 13417489 to 114954346 bp on BTA6, and the SNP with the lowest p-value was located at 97907606 bp. In spite of K, Manhattan plots indicated 64 significant SNPs at BTA20, starting from 1876553 to 69791421 bp, and the SNP with the lowest p value was located at 11089453 bp.

Bottom Line: One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively.The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1).Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.

View Article: PubMed Central - PubMed

Affiliation: Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.

ABSTRACT
Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.

No MeSH data available.