Identification of genomic regions related to tenderness in Nellore beef cattle

2017 ◽  
Vol 8 (s1) ◽  
pp. s42-s44 ◽  
Author(s):  
M. E. Carvalho ◽  
F. S. Baldi ◽  
M. H. A. Santana ◽  
R. V. Ventura ◽  
G. A. Oliveira ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Genome Wide Association Study ◽  
Additive Genetic Variance ◽  
Single Step ◽  
Meat Tenderness ◽  
Beef Tenderness ◽  
Genome Wide ◽  
Quality Grade ◽  
Nellore Cattle ◽  
Genomic Regions

The aim of this study was to identify genomic regions that associated with beef tenderness in Nellore cattle. Phenotypes were obtained according to the standard USDA Quality Grade (1999). Data from 909 genotyped Nellore bulls were used in the Genome-Wide Association Study (GWAS) undertaken using a single-step approach including also a pedigree file composed of 6276 animals. The analyses were performed using the Blupf90 software, estimating the effect of genomic windows of 10 consecutive markers. The GWAS results identified 18 genomic regions located on 14 different chromosomes (1, 4, 6, 7, 8, 10, 18, 19, 20, 21, 22, 25, 26 and 29), which explained more than 1% of the total additive genetic variance; several candidate genes were located in these regions including SLC2A9, FRAS1, ANXA3, FAM219A, DNAI, AVEN, SHISA7, UBE2S, CDC42EP5, CNTN3, C16orf96, UBALD1, MGRN1 and SNORA1 With the single-step GWAS, it was possible to identify regions and genes related to meat tenderness in Nellore beef cattle.

scholarly journals Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle

Animals ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1836
Author(s):  
Masoumeh Naserkheil ◽  
Abolfazl Bahrami ◽  
Deukhwan Lee ◽  
Hossein Mehrban
Keyword(s):  
Beef Cattle ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Additive Genetic Variance ◽  
Carcass Traits ◽  
Single Step ◽  
Bipartite Networks ◽  
Muscle Area ◽  
Eye Muscle ◽  
Network Analyses

In recent years, studies on the biological mechanisms underlying complex traits have been facilitated by innovations in high-throughput genotyping technology. We conducted a weighted single-step genome-wide association study (WssGWAS) to evaluate backfat thickness, carcass weight, eye muscle area, marbling score, and yearling weight in a cohort of 1540 Hanwoo beef cattle using BovineSNP50 BeadChip. The WssGWAS uncovered thirty-three genomic regions that explained more than 1% of the additive genetic variance, mostly located on chromosomes 6 and 14. Among the identified window regions, seven quantitative trait loci (QTL) had pleiotropic effects and twenty-six QTL were trait-specific. Significant pathways implicated in the measured traits through Gene Ontology (GO) term enrichment analysis included the following: lipid biosynthetic process, regulation of lipid metabolic process, transport or localization of lipid, regulation of growth, developmental growth, and multicellular organism growth. Integration of GWAS results of the studied traits with pathway and network analyses facilitated the exploration of the respective candidate genes involved in several biological functions, particularly lipid and growth metabolism. This study provides novel insight into the genetic bases underlying complex traits and could be useful in developing breeding schemes aimed at improving growth and carcass traits in Hanwoo beef cattle.

17 Genome-wide Association Study for Heat Stress Tolerance in Swine Using Weighted Single-step GBLUP

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 8-8
Author(s):  
Gabriella R Dodd ◽  
Breno O Fragomeni ◽  
Kent A Gray ◽  
Yijian Huang
Keyword(s):  
Heat Stress ◽  
Association Study ◽  
Stress Tolerance ◽  
Genetic Correlation ◽  
Genome Wide Association Study ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Heat Stress Tolerance ◽  
Genomic Regions

Abstract The purpose of this study was to perform a genome-wide association study to determine the genomic regions associated with heat stress tolerance in swine as well as analyze the accuracy of prediction. Phenotypic information on carcass weight was available for 227,043 individuals from commercial farms in North Carolina and Missouri. Individuals were a commercial cross of a Duroc sire and a dam resulting from a Landrace and Large White cross. Genotypic information was available for 8,232 animals with 33,581 SNP. The pedigree file contained 553,448 animals. A 78 on the Temperature Humidity Index (THI) was used as a threshold for heat stress. A two-trait analysis was used with the phenotypes heat stress (trait one) and non-heat stress (trait two). Variance components were calculated via AIREML and breeding values were calculated using single step GBLUP (ssGBLUP). The heritability for trait one and two were calculated at 0.25 and 0.20, respectively, and the genetic correlation was calculated as 0.63. Validation was calculated for 163 genotyped sires with progeny in the last generation. The GEBV of complete data was used as the benchmark, and the accuracy was determined as the correlation between the GEBV of the reduced and complete data for the validation sires. Weighted ssGBLUP did not increase the accuracies, both methods showed a maximum accuracy of 0.32 for trait one and 0.54 for trait two. Manhattan Plots for trait one, trait two, and the difference between the two were created from the results of the two-trait analysis. Windows explaining around 1% of the genetic variance were identified. The only difference between the two traits was a peak at chromosome 14. The genetic correlation suggests different mechanisms for growth under heat stress. The GWAS results show that both traits are highly polygenic, with few genomic regions explaining more than 1% of variance.

Genome-wide association study identified genomic regions and putative candidate genes affecting meat color traits in Nellore cattle

Meat Science ◽  
2021 ◽  
Vol 171 ◽  
pp. 108288
Author(s):  
N.A. Marín-Garzón ◽  
A.F.B. Magalhães ◽  
L.F.M Mota ◽  
L.F.S. Fonseca ◽  
L.A.L. Chardulo ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Meat Color ◽  
Genome Wide ◽  
Color Traits ◽  
Nellore Cattle ◽  
Genomic Regions

PSXI-4 Genome-Wide association study for muscle visual score in Nellore cattle raised in pasture-based systems

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 246-246
Author(s):  
Victor B Pedrosa ◽  
Pamela Machado ◽  
Rafaela Martins ◽  
Marcio Silva ◽  
Luis Fernando Pinto ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Additive Genetic Variance ◽  
Genome Wide Association ◽  
Zebu Cattle ◽  
Visual Score ◽  
Genome Wide ◽  
A Genome ◽  
Nellore Cattle

Abstract Visual scoring traits have been proposed as an alternative to evaluate body composition of Zebu cattle near the slaughter season when phenotyping technologies are not available. Considering the increased demand for high-quality animal protein in developing countries, there is a need to genetically improve body muscle (MUSC) in Zebu cattle (Bos taurus indicus), especially in animals raised in pasture-based systems. Therefore, our main objectives were to estimate genetic parameters, perform a genome-wide association study based on the single-step GBLUP approach (ssGWAS), and identify candidate genes and metabolic pathways related to MUSC in Nellore cattle. A total of 20,808 Nellore animals born between 2009 and 2018 were visually score at 18 months of age and 2,775 of these animals were also genotyped using the GGP-Indicus 35K SNP panel (33,247 SNPs after quality control). Heritability was estimated based on the REML approach and the model included the effects of age at measurement as covariable and the contemporary group (farm, birth season, management group and sex). The ssGWAS was performed using the BLUPF90 family programs. The identification of candidate genes was performed through the Ensembl database incorporated in the BioMart tool. MUSC is heritable (0.38) and can be improved through selection. Nineteen genomic regions (explaining 38.12% of the total additive genetic variance) located on BTA1, BTA7, BTA9, BTA16, and BTA21 and harboring 19 candidate genes were identified. The main genes identified were SEMA6A, TIAM2, UNC5A, and UIMC1, which are related to the metabolism of energy, growth, homeostasis and axonogenesis, and therefore, muscle development. These findings contribute to a better understanding of the molecular mechanisms over the gene expression of muscle visual score in Nellore cattle, and the polymorphisms located in these genes can be incorporated in commercial genotyping platforms to improve the accuracy of imputation and genomic evaluations for body and carcass traits.

scholarly journals Weighted Single-Step Genome-Wide Association Study for Growth Traits in Chinese Simmental Beef Cattle

Genes ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 189 ◽  
Author(s):  
Zhanwei Zhuang ◽  
Lingyang Xu ◽  
Jie Yang ◽  
Huijiang Gao ◽  
Lupei Zhang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Association Study ◽  
Muscle Development ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Single Step ◽  
Genome Wide Association ◽  
Meat Production ◽  
Genome Wide

Improving the genetic process of growth traits is one of the major goals in the beef cattle industry, as it can increase meat production and reduce the cost of raising animals. Although several quantitative trait loci affecting growth traits in beef cattle have been identified, the genetic architecture of these economically important traits remains elusive. This study aims to map single nucleotide polymorphisms (SNPs) and genes associated with birth weight (BW), yearling weight (YW), average daily gain from birth to yearling (BYADG), and body weight at the age of 18 months (18MW) in a Chinese Simmental beef cattle population using a weighted, single-step, genome-wide association study (wssGWAS). Phenotypic and pedigree data from 6022 animals and genotypes from 744 animals (596,297 SNPs) were used for an association analysis. The results showed that 66 genomic windows explained 1.01–20.15% of the genetic variance for the four examined traits, together with the genes near the top SNP within each window. Furthermore, the identified genomic windows (>1%) explained 50.56%, 57.71%, 61.78%, and 37.82% of the genetic variances for BW, YW, BYADG, and 18MW, respectively. Genes with potential functions in muscle development and regulation of cell growth were highlighted as candidates for growth traits in Simmental cattle (SQOR and TBCB for BW, MYH10 for YW, RLF for BYADG, and ARHGAP31 for 18MW). Moreover, we found 40 SNPs that had not previously been identified as being associated with growth traits in cattle. These findings will further advance our understanding of the genetic basis for growth traits and will be useful for the molecular breeding of BW, YW, BYADG, and 18MW in the context of genomic selection in beef cattle.

Weighted single‐step genome‐wide association study and pathway analyses for feed efficiency traits in Nellore cattle

2020 ◽  
Vol 138 (1) ◽  
pp. 23-44 ◽  
Author(s):  
Ludmilla C. Brunes ◽  
Fernando Baldi ◽  
Fernando B. Lopes ◽  
Raysildo B. Lôbo ◽  
Rafael Espigolan ◽  
...  
Keyword(s):  
Association Study ◽  
Feed Efficiency ◽  
Genome Wide Association Study ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Nellore Cattle ◽  
Pathway Analyses

scholarly journals A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

Animals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 500
Author(s):  
Hadi Atashi ◽  
Mazdak Salavati ◽  
Jenne De Koster ◽  
Mark Crowe ◽  
Geert Opsomer ◽  
...  
Keyword(s):  
Genetic Variance ◽  
Genome Wide Association Study ◽  
Additive Genetic Variance ◽  
Genomic Region ◽  
Single Step ◽  
Calving Interval ◽  
Alanine Transport ◽  
A Genome ◽  
Estimated Breeding Values ◽  
Genomic Regions

The aim of the present study was to identify genomic region(s) associated with the length of the calving interval in primiparous (n = 6866) and multiparous (n = 5071) Holstein cows. The single nucleotide polymorphism (SNP) solutions were estimated using a weighted single-step genomic best linear unbiased prediction (WssGBLUP) approach and imputed high-density panel (777 k) genotypes. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. The results showed that the accuracies of GEBVs with WssGBLUP improved by +5.4 to +5.7, (primiparous cows) and +9.4 to +9.7 (multiparous cows) percent points over accuracies from the pedigree-based BLUP. The most accurate genomic evaluation was provided at the second iteration of WssGBLUP, which was used to identify associated genomic regions using a windows-based GWAS procedure. The proportion of additive genetic variance explained by windows of 50 consecutive SNPs (with an average of 165 Kb) was calculated and the region(s) that accounted for equal to or more than 0.20% of the total additive genetic variance were used to search for candidate genes. Three windows of 50 consecutive SNPs (BTA3, BTA6, and BTA7) were identified to be associated with the length of the calving interval in primi- and multiparous cows, while the window with the highest percentage of explained genetic variance was located on BTA3 position 49.42 to 49.52 Mb. There were five genes including ARHGAP29, SEC24D, METTL14, SLC36A2, and SLC36A3 inside the windows associated with the length of the calving interval. The biological process terms including alanine transport, L-alanine transport, proline transport, and glycine transport were identified as the most important terms enriched by the genes inside the identified windows.

scholarly journals Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

2021 ◽  
Vol 7 (11) ◽  
pp. eabd1239
Author(s):  
Mark Simcoe ◽  
Ana Valdes ◽  
Fan Liu ◽  
Nicholas A. Furlotte ◽  
David M. Evans ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Color Variation ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Melanin Pigmentation ◽  
Eye Color ◽  
Human Eye ◽  
Genome Wide ◽  
Genomic Regions

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

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