Genome-wide association study in an F2 Duroc x Pietrain resource population for economically important meat quality and carcass traits

2017 ◽  
Vol 95 (2) ◽  
pp. 545 ◽  
Author(s):  
S. Casiró ◽  
D. Velez-Irizarry ◽  
C. W. Ernst ◽  
N. E. Raney ◽  
R. O. Bates ◽  
...  

2017 ◽  
Vol 95 (2) ◽  
pp. 545-558 ◽  
Author(s):  
S. Casiró ◽  
D. Velez-Irizarry ◽  
C. W. Ernst ◽  
N. E. Raney ◽  
R. O. Bates ◽  
...  


Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 1068
Author(s):  
Xue Yang ◽  
Feilong Deng ◽  
Zhoulin Wu ◽  
Shi-Yi Chen ◽  
Yu Shi ◽  
...  

Growth, carcass characteristics and meat quality are the most important traits used in the rabbit industry. Identification of the candidate markers and genes significantly associated with these traits will be beneficial in rabbit breeding. In this study, we enrolled 465 rabbits, including 16 male Californian rabbits and 17 female Kangda5 line rabbits as the parental generation, along with their offspring (232 male and 200 female), in a genome-wide association study (GWAS) based on SLAF-seq technology. Bodyweight at 35, 42, 49, 56, 63 and 70 d was recorded for growth traits; and slaughter liveweight (84 d) and dressing out percentage were measured as carcass traits; and cooking loss and drip loss were measured as meat quality traits. A total of 5,223,720 SLAF markers were obtained by digesting the rabbit genome using RsaI + EcoRV-HF® restriction enzymes. After quality control, a subset of 317,503 annotated single-nucleotide polymorphisms (SNPs) was retained for subsequent analysis. A total of 28, 81 and 10 SNPs for growth, carcass and meat quality traits, respectively, were identified based on genome-wide significance (p < 3.16 × 10−7). Additionally, 16, 71 and 9 candidate genes were identified within 100 kb upstream or downstream of these SNPs. Further analysis is required to determine the biological roles of these candidate genes in determining rabbit growth, carcass traits and meat quality.



2011 ◽  
Vol 89 (8) ◽  
pp. 2297-2309 ◽  
Author(s):  
S. Bolormaa ◽  
L. R. Porto Neto ◽  
Y. D. Zhang ◽  
R. J. Bunch ◽  
B. E. Harrison ◽  
...  


Genes ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 551
Author(s):  
Swati Srivastava ◽  
Krishnamoorthy Srikanth ◽  
Sohyoung Won ◽  
Ju-Hwan Son ◽  
Jong-Eun Park ◽  
...  

Hanwoo, is the most popular native beef cattle in South Korea. Due to its extensive popularity, research is ongoing to enhance its carcass quality and marbling traits. In this study we conducted a haplotype-based genome-wide association study (GWAS) by constructing haplotype blocks by three methods: number of single nucleotide polymorphisms (SNPs) in a haplotype block (nsnp), length of genomic region in kb (Len) and linkage disequilibrium (LD). Significant haplotype blocks and genes associated with them were identified for carcass traits such as BFT (back fat thickness), EMA (eye Muscle area), CWT (carcass weight) and MS (marbling score). Gene-set enrichment analysis and functional annotation of genes in the significantly-associated loci revealed candidate genes, including PLCB1 and PLCB4 present on BTA13, coding for phospholipases, which might be important candidates for increasing fat deposition due to their role in lipid metabolism and adipogenesis. CEL (carboxyl ester lipase), a bile-salt activated lipase, responsible for lipid catabolic process was also identified within the significantly-associated haplotype block on BTA11. The results were validated in a different Hanwoo population. The genes and pathways identified in this study may serve as good candidates for improving carcass traits in Hanwoo cattle.



2012 ◽  
Vol 8 (6) ◽  
pp. 870-881 ◽  
Author(s):  
Weizhen Luo ◽  
Shaokang Chen ◽  
Duxue Cheng ◽  
Ligang Wang ◽  
Yong Li ◽  
...  


2014 ◽  
Vol 46 (1) ◽  
pp. 12 ◽  
Author(s):  
Marie-Pierre Sanchez ◽  
Thierry Tribout ◽  
Nathalie Iannuccelli ◽  
Marcel Bouffaud ◽  
Bertrand Servin ◽  
...  


PLoS ONE ◽  
2011 ◽  
Vol 6 (7) ◽  
pp. e21872 ◽  
Author(s):  
Xiaorong Gu ◽  
Chungang Feng ◽  
Li Ma ◽  
Chi Song ◽  
Yanqiang Wang ◽  
...  






PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e64047 ◽  
Author(s):  
Junwu Ma ◽  
Jie Yang ◽  
Lisheng Zhou ◽  
Zhiyan Zhang ◽  
Huanban Ma ◽  
...  


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