scholarly journals Identification of candidate genes on the basis of SNP by time-lagged heat stress interactions for milk production traits in German Holstein cattle

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258216
Author(s):  
Kathrin Halli ◽  
Seyi Fridaius Vanvanhossou ◽  
Mehdi Bohlouli ◽  
Sven König ◽  
Tong Yin
Keyword(s):  
Immune Response ◽  
Heat Stress ◽  
Candidate Genes ◽  
Milk Production ◽  
Variance Components ◽  
In Utero ◽  
Potential Candidate ◽  
Production Traits ◽  
Milk Production Traits ◽  
Time Lagged

The aim of this study was to estimate genotype by time-lagged heat stress (HS) variance components as well as main and interaction SNP-marker effects for maternal HS during the last eight weeks of cow pregnancy, considering milk production traits recorded in the offspring generation. The HS indicator was the temperature humidity index (THI) for each week. A dummy variable with the code = 1 for the respective week for THI ≥ 60 indicated HS, otherwise, for no HS, the code = 0 was assigned. The dataset included test-day and lactation production traits from 14,188 genotyped first parity Holstein cows. After genotype quality control, 41,139 SNP markers remained for the genomic analyses. Genomic animal models without (model VC_nHS) and with in-utero HS effects (model VC_wHS) were applied to estimate variance components. Accordingly, for genome-wide associations, models GWA_nHS and GWA_wHS, respectively, were applied to estimate main and interaction SNP effects. Common genomic and residual variances for the same traits were very similar from models VC_nHS and VC_wHS. Genotype by HS interaction variances varied, depending on the week with in-utero HS. Among all traits, lactation milk yield with HS from week 5 displayed the largest proportion for interaction variances (0.07). For main effects from model GWA_wHS, 380 SNPs were suggestively associated with all production traits. For the SNP interaction effects from model GWA_wHS, we identified 31 suggestive SNPs, which were located in close distance to 62 potential candidate genes. The inferred candidate genes have various biological functions, including mechanisms of immune response, growth processes and disease resistance. Two biological processes excessively represented in the overrepresentation tests addressed lymphocyte and monocyte chemotaxis, ultimately affecting immune response. The modelling approach considering time-lagged genotype by HS interactions for production traits inferred physiological mechanisms being associated with health and immunity, enabling improvements in selection of robust animals.

Prospecting genomic regions associated with milk production traits in Egyptian buffalo

2020 ◽  
pp. 1-8
Author(s):  
Hamdy Abdel-Shafy ◽  
Mohamed A. A. Awad ◽  
Hussein El-Regalaty ◽  
S. E.-D. El-Assal ◽  
Samy Abou-Bakr
Keyword(s):  
Candidate Genes ◽  
Milk Production ◽  
Genome Wide Association Study ◽  
Potential Candidate ◽  
Production Traits ◽  
Milk Production Traits ◽  
Genome Wide ◽  
Reported Study ◽  
Daily Milk Yield ◽  
Egyptian Buffalo

Abstract The objectives of the current study were to detect putative genomic loci and to identify candidate genes associated with milk production traits in Egyptian buffalo. A total number of 161 479 daily milk yield (DMY) records and 60 318 monthly measures for fat and protein percentages (FP and PP, respectively), along with fat and protein yields (FY and PY, respectively) from 1670 animals were used. Genotyping was performed using Axiom® Buffalo Genotyping 90 K array. Genome-wide association study (GWAS) for each trait was performed using PLINK. After Bonferroni correction, 47 SNPs were associated with one or more milk production traits. These SNPs were distributed over 36 quantitative trait loci (QTL) and located on 20 buffalo chromosomes (BBU). For the 47 SNPs, one was overlapped for three traits (DMY, FY, and PY), six were associated with two traits (one for PP and PY and five for FY and PY) while the rest were associated with only one trait. Out of 36 identified QTL, eleven were overlapped with previously reported loci in buffalo and/or cattle populations. Some of these SNPs are placed within or close to potential candidate genes, for example: TPD52, ZBTB10, RALYL and SNX16 on BBU15, ADGRD1 on BBU17, ESRRG on BBU5 and GRIP1 on BBU4. This is the first reported study between genome-wide markers and milk components in Egyptian buffalo. Our findings provide useful information to explore the genetic mechanisms and relevant genes contributing to the variation in milk production traits. Further confirmation studies with larger population size are necessary to validate the findings and detect the causal genetic variants.

scholarly journals Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle

2020 ◽  
Vol 52 (1) ◽  
Author(s):  
Thierry Tribout ◽  
Pascal Croiseau ◽  
Rachel Lefebvre ◽  
Anne Barbat ◽  
Mekki Boussaha ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Candidate Genes ◽  
Milk Production ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Milk Production Traits ◽  
Udder Health ◽  
Gwas Approach

Abstract Background Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows. Results Bull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits. Conclusions Using this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

A functional genomics approach to evaluate candidate genes located in a QTL interval for milk production traits on BTA6

2009 ◽  
Vol 40 (4) ◽  
pp. 492-498 ◽  
Author(s):  
P. A. Sheehy ◽  
L. G. Riley ◽  
H. W. Raadsma ◽  
P. Williamson ◽  
P. C. Wynn
Keyword(s):  
Functional Genomics ◽  
Candidate Genes ◽  
Milk Production ◽  
Production Traits ◽  
Milk Production Traits

scholarly journals Genetic Markers Associated with Milk Production Traits in Dairy Cattle

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1018
Author(s):  
Yulin Ma ◽  
Muhammad Zahoor Khan ◽  
Jianxin Xiao ◽  
Gibson Maswayi Alugongo ◽  
Xu Chen ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Dna Sequencing ◽  
Candidate Genes ◽  
Genetic Markers ◽  
Milk Production ◽  
Production Traits ◽  
Rna Seq ◽  
Milk Production Traits ◽  
Generation Interval ◽  
Current Review

Increasing milk production is one of the key concerns in animal production. Traditional breeding has gotten limited achievement in the improvement of milk production because of its moderate heritability. Milk production traits are controlled by many genes. Thus, identifying candidate genes associated with milk production traits may provide information that can be used to enhance the accuracy of animal selection for moderately heritable traits like milk production. The genomic selection can enhance the accuracy and intensity of selection and shortening the generation interval. The genetic progress of economically important traits can be doubled with the accuracy of selection and shortening of generation interval. Genome-wide association studies (GWAS) have made possible the screening of several single nucleotide polymorphisms (SNPs) in genes associated with milk production traits in dairy cattle. In addition, RNA-sequencing is another well-established tool used to identify genes associated with milk production in dairy cattle. Although it has been widely accepted that these three methods (GWAS, RNA-seq and DNA sequencing) are considered the first step in the screening of genes, however, the outcomes from GWAS, DNA-sequencing and RNA-seq still need further verification for the establishment of bonafide causal variants via genetic replication as well as functional validation. In the current review, we have highlighted genetic markers identified (2010-to date) for their associations with milk production traits in dairy cattle. The information regarding candidate genes associated with milk production traits provided in the current review could be helpful to select the potential genetic markers for the genetic improvement of milk production traits in dairy cattle.

scholarly journals Ten Genetic Loci Identified for Milk Yield, Fat, and Protein in Holstein Cattle

2020 ◽  
Author(s):  
Liyuan Liu ◽  
Jinghang Zhou ◽  
Chunpeng James Chen ◽  
Juan Zhang ◽  
Wan Wen ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Production ◽  
Milk Yield ◽  
Genetic Variants ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Genome Wide

AbstractHigh-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk production traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production traits in Holstein cattle population from China. These traits included milk yield, protein yield, fat yields; fat percentage and protein percentages. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a mixed linear model for individuals with and without phenotypic data. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the Fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten SNPs was detected above the genome-wide significant threshold, including six located in previously reported QTL regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The most significant SNP is on DGAT1 gene affecting milk fat and protein percentage. These genetic variants and candidate genes would be valuable resources to enhance dairy cattle breeding.

Study on candidate genes for milk production traits of Red Chittagong Cattle

2020 ◽  
Vol 26 (1-2) ◽  
pp. 1-7
Author(s):  
MP Mostari ◽  
MYA Khan
Keyword(s):  
Candidate Genes ◽  
Milk Production ◽  
Milk Fat ◽  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Milk Production Traits ◽  
Single Nucleotide ◽  
Lactating Cows ◽  
Pooled Dna ◽  
Fat Yield

The study was carried out on Stearoyl-CoA desaturase (SCD,) diacylglycerolacyltransferase-1 (DGAT1) and ATP-binding cassette G2 (ABCG2) genes which are responsible for variation in milk production traits (milk yield, fat yield, protein yield, and SNF yield) in cattle. These genes were used as candidate genes in Red Chittagong Cattle (RCC) breed of Bangladesh Livestock Research Institute (BLRI) herd for detection of single nucleotide polymorphisms (SNPs) causing variation in milk production traits. Focusing on the effects of SNPs on milk production traits, phenotypic variation within RCC breed was identified and categorized based on milk production traits. Average lactation yield varied from 527 to 1436 kg (n=29) per lactation. About 18% of lactating cows showed an average of >1000 kg per lactation. Average fat percent ranged from 4.71 to 6.25 (n=15). Eighteen (18) set of primers were designed to amplify targeted regions of SCD, DGAT1 and ABCG2 genes, where 8 set from DGAT1, 6 set from SCD and 4 set from ABCG2 gene. Pooled DNA from 50 RCC cows and 5 RCC bulls were used in sequencing. In sequence analysis, the SCD, DGAT1 and ABCG2 alleles found fixed in RCC. This study suggests an evidence that RCC breed has fixed alleles with respect to SCD, DGAT1 and ABCG2 genes reported to be responsible for higher milk fat yield, higher fat and protein percent. Bang. J. Livs. Res. Vol. 26 (1&2), 2019: P. 1-7

Meta-analysis of mammary RNA seq datasets reveals the molecular understanding of bovine lactation biology

Genome ◽  
2019 ◽  
Vol 62 (7) ◽  
pp. 489-501
Author(s):  
Periyasamy Vijayakumar ◽  
Sanniyasi Bakyaraj ◽  
Arunasalam Singaravadivelan ◽  
Thangavelu Vasanthakumar ◽  
Ramalingam Suresh
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Milk Production ◽  
Meta Analysis ◽  
Mammary Tissue ◽  
Secretory Cells ◽  
Molecular Pathways ◽  
Production Traits ◽  
Rna Seq ◽  
Milk Production Traits

A better understanding of the biology of lactation, both in terms of gene expression and the identification of candidate genes for the production of milk and its components, is made possible by recent advances in RNA seq technology. The purpose of this study was to understand the synthesis of milk components and the molecular pathways involved, as well as to identify candidate genes for milk production traits within whole mammary transcriptomic datasets. We performed a meta-analysis of publically available RNA seq transcriptome datasets of mammary tissue/milk somatic cells. In total, 11 562 genes were commonly identified from all RNA seq based mammary gland transcriptomes. Functional annotation of commonly expressed genes revealed the molecular processes that contribute to the synthesis of fats, proteins, and lactose in mammary secretory cells and the molecular pathways responsible for milk synthesis. In addition, we identified several candidate genes responsible for milk production traits and constructed a gene regulatory network for RNA seq data. In conclusion, this study provides a basic understanding of the lactation biology of cows at the gene expression level.

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