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A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G, and FOXP3 in intramuscular fat deposition of beef cattle
被引:65
作者:
Ramayo-Caldas, Y.
[1
,2
,3
,4
]
Fortes, M. R. S.
[5
]
Hudson, N. J.
[1
,2
]
Porto-Neto, L. R.
[1
,2
]
Bolormaa, S.
[6
]
Barendse, W.
[1
,2
]
Kelly, M.
[5
]
Moore, S. S.
[5
]
Goddard, M. E.
[6
,7
]
Lehnert, S. A.
[1
,2
]
Reverter, A.
[1
,2
]
机构:
[1] CSIRO Food Futures Flagship, Brisbane, Qld 4067, Australia
[2] CSIRO Anim Food & Hlth Sci, Brisbane, Qld 4067, Australia
[3] Univ Autonoma Barcelona, Fac Vet, Dept Ciencia Anim & Aliments, Bellaterra 08193, Spain
[4] INRA, Genet Anim & Biol Integrat GABI UMR1313, F-78352 Jouy En Josas, France
[5] Univ Queensland, Queensland Alliance Agr & Food Innovat, Ctr Anim Sci, St Lucia, Qld 4062, Australia
[6] Victorian Dept Environm & Primary Ind, Bundoora, Vic 3083, Australia
[7] Univ Melbourne, Sch Land & Environm, Parkville, Vic 3010, Australia
关键词:
association weight matrix;
beef quality;
fat deposition;
genomewide association study;
marbling;
MEAT QUALITY TRAITS;
GENOME-WIDE ASSOCIATION;
RESIDUAL FEED-INTAKE;
PHENOTYPIC CHARACTERIZATION;
SKELETAL-MUSCLE;
TRANSCRIPTION FACTOR;
ACID-COMPOSITION;
T-CELLS;
CARCASS TRAITS;
EXPRESSION;
D O I:
10.2527/jas.2013-7484
中图分类号:
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号:
0905 ;
摘要:
High intramuscular fat (IMF) awards price premiums to beef producers and is associated with meat quality and flavor. Studying gene interactions and pathways that affect IMF might unveil causative physiological mechanisms and inform genomic selection, leading to increased accuracy of predictions of breeding value. To study gene interactions and pathways, a gene network was derived from genetic markers associated with direct measures of IMF, other fat phenotypes, feedlot performance, and a number of meat quality traits relating to body conformation, development, and metabolism that might be plausibly expected to interact with IMF biology. Marker associations were inferred from genomewide association studies (GWAS) based on high density genotypes and 29 traits measured on 10,181 beef cattle animals from 3 breed types. For the network inference, SNP pairs were assessed according to the strength of the correlation between their additive association effects across the 29 traits. The co-association inferred network was formed by 2,434 genes connected by 28,283 edges. Topological network parameters suggested a highly cohesive network, in which the genes are strongly functionally interconnected. Pathway and network analyses pointed towards a trio of transcription factors (TF) as key regulators of carcass IMF: PPARG-C1A, HNF4G, and FOXP3. Importantly, none of these genes would have been deemed as significantly associated with IMF from the GWAS. Instead, a total of 313 network genes show significant co-association with the 3 TF. These genes belong to a wide variety of biological functions, canonical pathways, and genetic networks linked to IMF-related phenotypes. In summary, our GWAS and network predictions are supported by the current literature and suggest a cooperative role for the 3 TF and other interacting genes including CAPN6, STC2, MAP2K4, EYA1, COPS5, XKR4, NR2E1, TOX, ATF1, ASPH, TGS1, and TTPA as modulators of carcass and meat quality traits in beef cattle.
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页码:2832 / 2845
页数:14
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