Data/hora: 10/06/2024 18:34:49

Biblioteca(s): | Embrapa Florestas; Embrapa Gado de Leite.
Data corrente: | 17/05/2017
Data da última atualização: | 27/01/2023
Autoria: | SILVA, F. F. e; ZAMBRANO, M. F. B.; VARONA, L.; GLÓRIA, L. S.; LOPES, P. S.; SILVA, M. V. G. B.; ARBEX, W. A.; LÁZARO, S. F.; RESENDE, M. D. V. de; GUIMARÃES, S. E. F.
Afiliação: | Fabyano Fonseca e Silva, UFV/VIÇOSA; Maria Fernanda Betancur Zambrano, UFV/VIÇOSA; Luis Varona, University of Zaragoza; Leonardo Siqueira Glória, UFV/VIÇOSA; Paulo Sávio Lopes, UFV; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; WAGNER ANTONIO ARBEX, CNPGL; Sirlene Fernandes Lázaro, UFV/VIÇOSA; MARCOS DEON VILELA DE RESENDE, CNPF; Simone Eliza Facioni Guimarães, UFV/VIÇOSA.
Título: | Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves.
Ano de publicação: | 2017
Fonte/Imprenta: | Scientia Agricola, v. 74, n. 1, 2017.
Páginas: | 7 P.

Idioma:

Inglês
Português

Conteúdo:

Genome association analyses have been successful in identifying quantitative trait
loci (QTLs) for pig body weights measured at a single age. However, when considering the whole
weight trajectories over time in the context of genome association analyses, it is important to
look at the markers that affect growth curve parameters. The easiest way to consider them is
via the two-step method, in which the growth curve parameters and marker effects are estimated
separately, thereby resulting in a reduction of the statistical power and the precision of
estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint
modeling of the individual growth curves and marker effects. Our aim was to propose a genome
association analysis for growth curves in pigs based on NMM as well as to compare it with the
traditional two-step method. In addition, we also aimed to identify the nearest candidate genes
related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a
higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct
way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all
significant SNPs from the two-step method were also reported in the NMM analysis. The ontology
of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs
(simultaneously affecting A and K) allows us to make inferences with regards to their contribution
to the pig growth process in the population studied.

Palavras-Chave: | Longitudinal data; SNP markers.
Thesaurus Nal: | body weight.

Categoria do assunto:

--
L Ciência Animal e Produtos de Origem Animal

URL: | http://ainfo.cnptia.embrapa.br/digital/bitstream/item/161512/1/Cnpgl-2017-SciAgric-Silva-Genome.pdf
Registro original: | Embrapa Gado de Leite (CNPGL)

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