scholarly journals Associations between polymorphisms of SLC22A7, NGFR, ARNTL and PPP2R2B genes and Milk production traits in Chinese Holstein

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruike Jia ◽  
Yihan Fu ◽  
Lingna Xu ◽  
Houcheng Li ◽  
Yanhua Li ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Association Analysis ◽  
Milk Yield ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Protein Percentage ◽  
Fat Yield ◽  
Percentage Protein

Abstract Background Our preliminary work confirmed that, SLC22A7 (solute carrier family 22 member 7), NGFR (nerve growth factor receptor), ARNTL (aryl hydrocarbon receptor nuclear translocator like) and PPP2R2B (protein phosphatase 2 regulatory subunit Bβ) genes were differentially expressed in dairy cows during different stages of lactation, and involved in the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, so we considered these four genes as the candidates affecting milk production traits. In this study, we detected polymorphisms of the four genes and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population. Results By resequencing the whole coding region and part of the flanking region of SLC22A7, NGFR, ARNTL and PPP2R2B, we totally found 20 SNPs, of which five were located in SLC22A7, eight in NGFR, three in ARNTL, and four in PPP2R2B. Using Haploview4.2, we found three haplotype blocks including five SNPs in SLC22A7, eight in NGFR and three in ARNTL. Single-SNP association analysis showed that 19 out of 20 SNPs were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage in the first and second lactations (P < 0.05). Haplotype-based association analysis showed that the three haplotypes were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.05). Further, we used SOPMA software to predict a SNP, 19:g.37095131C > T in NGFR, changed the structure of NGFR protein. In addition, we used Jaspar software to found that four SNPs, 19:g.37113872C > G,19:g.37113157C > T, and 19:g.37112276C > T in NGFR and 15:g.39320936A > G in ARNTL, could change the transcription factor binding sites and might affect the expression of the corresponding genes. These five SNPs might be the potential functional mutations for milk production traits in dairy cattle. Conclusions In summary, we proved that SLC22A7, NGFR, ARNTL and PPP2R2B have significant genetic effects on milk production traits. The valuable SNPs can be used as candidate genetic markers for genomic selection of dairy cattle, and the effects of these SNPs on other traits need to be further verified.

Using quantile regression for fitting lactation curve in dairy cows

2019 ◽  
Vol 86 (1) ◽  
pp. 19-24
Author(s):  
Hossein Naeemipour Younesi ◽  
Mohammad Mahdi Shariati ◽  
Saeed Zerehdaran ◽  
Mehdi Jabbari Nooghabi ◽  
Peter Løvendahl
Keyword(s):  
Quantile Regression ◽  
Dairy Cows ◽  
Milk Production ◽  
Milk Yield ◽  
Information Criterion ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Protein Percentage ◽  
Breeding Center

AbstractThe main objective of this study was to compare the performance of different ‘nonlinear quantile regression’ models evaluated at theτth quantile (0·25, 0·50, and 0·75) of milk production traits and somatic cell score (SCS) in Iranian Holstein dairy cows. Data were collected by the Animal Breeding Center of Iran from 1991 to 2011, comprising 101 051 monthly milk production traits and SCS records of 13 977 cows in 183 herds. Incomplete gamma (Wood), exponential (Wilmink), Dijkstra and polynomial (Ali & Schaeffer) functions were implemented in the quantile regression. Residual mean square, Akaike information criterion and log-likelihood from different models and quantiles indicated that in the same quantile, the best models were Wilmink for milk yield, Dijkstra for fat percentage and Ali & Schaeffer for protein percentage. Over all models the best model fit occurred at quantile 0·50 for milk yield, fat and protein percentage, whereas, for SCS the 0·25th quantile was best. The best model to describe SCS was Dijkstra at quantiles 0·25 and 0·50, and Ali & Schaeffer at quantile 0·75. Wood function had the worst performance amongst all traits. Quantile regression is specifically appropriate for SCS which has a mixed multimodal distribution.

scholarly journals Genetic Effects of LPIN1 Polymorphisms on Milk Production Traits in Dairy Cattle

Genes ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 265 ◽  
Author(s):  
Bo Han ◽  
Yuwei Yuan ◽  
Ruobing Liang ◽  
Yanhua Li ◽  
Lin Liu ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Genetic Effects ◽  
Production Traits ◽  
Milk Production Traits ◽  
Association Analyses ◽  
Protein Percentage ◽  
Haplotype Blocks ◽  
Flanking Region ◽  
Fat Yield

Our initial RNA sequencing work identified that lipin 1 (LPIN1) was differentially expressed during dry period, early lactation, and peak of lactation in dairy cows, and it was enriched into the fat metabolic Gene Ontology (GO) terms and pathways, thus we considered LPIN1 as the candidate gene for milk production traits. In this study, we detected the polymorphisms of LPIN1 and verified their genetic effects on milk yield and composition in a Chinese Holstein cow population. We found seven SNPs by re-sequencing the entire coding region and partial flanking region of LPIN1, including one in 5′ flanking region, four in exons, and two in 3′ flanking region. Of these, four SNPs, c.637T > C, c.708A > G, c.1521C > T, and c.1555A > C, in the exons were predicted to result in the amino acid replacements. With the Haploview 4.2, we found that seven SNPs in LPIN1 formed two haplotype blocks (D′ = 0.98–1.00). Single-SNP association analyses showed that SNPs were significantly associated with milk yield, fat yield, fat percentage, or protein yield in the first or second lactation (p = < 0.0001–0.0457), and only g.86049389C > T was strongly associated with protein percentage in both lactations (p = 0.0144 and 0.0237). The haplotype-based association analyses showed that the two haplotype blocks were significantly associated with milk yield, fat yield, protein yield, or protein percentage (p = < 0.0001–0.0383). By quantitative real-time PCR (qRT-PCR), we found that LPIN1 had relatively high expression in mammary gland and liver tissues. Furthermore, we predicted three SNPs, c.637T > C, c.708A > G, and c.1521C > T, using SOPMA software, changing the LPIN1 protein structure that might be potential functional mutations. In summary, we demonstrated the significant genetic effects of LPIN1 on milk production traits, and the identified SNPs could serve as genetic markers for dairy breeding.

AGPAT3 Gene polymorphisms are associated with milk production traits in Chinese Holstein cows

2021 ◽  
pp. 1-6
Author(s):  
Xiaomei Sun ◽  
Yan Liang ◽  
Qisong Gao ◽  
Jiahe Guo ◽  
Cheng Tang ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Urea Nitrogen ◽  
Protein Percentage ◽  
Milk Urea ◽  
Milk Urea Nitrogen

Abstract The current study reports the identification of previously undiscovered single-nucleotide polymorphisms (SNPs) in the bovine AGPAT3 gene and further investigates their associations with milk production traits. Our results demonstrate that the major allele C of the SNP g.12264 C > T is positively correlated with test-day milk yield, protein percentage and 305-day milk yield. Importantly, in silico analysis showed that the C/T transition at this locus gives rise to two new transcription factor binding sites (TFBS), E2F1 and Nkx3-2. Polymorphism g.18658 G > A was the only SNP associated with milk urea nitrogen (MUN) with the G allele related to an increase in milk urea nitrogen as well as fat percentage. The GG genotype of SNP g.28731 A > G was associated with the highest fat and protein percentage and lowest 305-day milk yield and somatic cell score (SCS). The association between AGPAT3 locus and milk production traits could be utilized in marker-assisted selection for the genetic improvement of milk production traits and, probably in conjunction with other traits, for selection to improve fitness of dairy cattle.

EFFECTS OF TOTAL ENVIRONMENTAL CHANGE ON MILK PRODUCTION

1978 ◽  
Vol 58 (4) ◽  
pp. 631-637
Author(s):  
JOHN HODGES ◽  
P. G. HILEY ◽  
J. FROESE
Keyword(s):  
Environmental Change ◽  
Milk Production ◽  
Milk Yield ◽  
Initial Increase ◽  
Fat Percentage ◽  
Gradual Decline ◽  
Protein Percentage ◽  
Coefficients Of Variation ◽  
Change Period ◽  
Percentage Protein

The effects on production of moving a herd of 27 Ayrshire milking cows from one environment to a totally different one, with changed methods of feeding, milking and housing, were studied. Following a pre-change period of 105 days, during which each cow was recorded on alternate days for yield of milk and fat, lactose and protein percentages, the immediate effects of the change, the recovery if any, and permanent changes in production were analyzed over a 19-day period. All traits were affected in mean levels, except protein percentage. Milk yield fell by 2.6 kg (13.0%), fat percentage increased by 0.43 units (10.0%), and lactose percentage fell by 0.23 units (4.8%). Protein percentage was unaltered throughout. Milk yield and lactose percentage did not change after the immediate drop. Fat percentage returned linearly from the initial increase, to expectation at 11 days after the change, and continued to decline for another 8 days. The variances of all the traits were temporarily inflated by factors of 2,5,3 and 3 for milk yield, fat percentage, protein percentage and lactose percentage, respectively. The gradual decline to normal, pre-change variance levels took 7–8 days for compositional traits and 10 days for milk yield. Estimates of these means, variances and coefficients of variation are given.

DGAT1 polymorphism in Riverine buffalo, Swamp buffalo and crossbred buffalo

2018 ◽  
Vol 85 (4) ◽  
pp. 412-415 ◽  
Author(s):  
Jun Li ◽  
Shenhe Liu ◽  
Zipeng Li ◽  
Shujun Zhang ◽  
Guohua Hua ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Buffalo Milk ◽  
Production Performance ◽  
Production Traits ◽  
Coding Region ◽  
Fat Percentage ◽  
Protein Percentage ◽  
Dgat1 Gene ◽  
Swamp Buffalo

This Research Communication describes the polymorphisms in the coding region of DGAT1 gene in Riverine buffalo, Swamp buffalo and crossbred buffalo, and associations between polymorphisms and milk production performance in Riverine buffalo. Two polymorphisms of DGAT1were identified, located in exon 13 and exon 17, respectively. The distribution of the genotypes of the two SNP loci in different buffalo population varied, especially the polymorphism located in exon 13 which was not found in the Swamp buffalo. Moreover, SNP located in exon 17 was a nonsynonymous switch resulting in the animo acid sequence changed from an arginine (Arg) to a histidine (His) at position 484. Both SNPs were in Hardy–Weinberg equilibrium, and the polymorphism of g.8330T>C in the exon 13 was significantly associated with peak milk yield, total milk yield and protein percentage. The C variant was associated with an increase in milk yield and peak yield but less in protein percentage compared with the T variant. The polymorphisms of g.9046T>C in exon 17 were significantly associated with fat percentage, in that the buffaloes with TT genotype had a significantly higher fat percentage than those with CC genotype. These findings reveal the difference in the genetic evolution of the DGAT1 between Riverine buffalo and Swamp buffalo, and provide evidence that the DGAT1 gene has potential effects for Riverine buffalo milk production traits, which can be used as a candidate gene for marker-assisted selection in buffalo breeding.

Association of bovineCD4andSTAT5bsingle nucleotide polymorphisms with somatic cell scores and milk production traits in Chinese Holsteins

2011 ◽  
Vol 78 (2) ◽  
pp. 242-249 ◽  
Author(s):  
Yanghua He ◽  
Qin Chu ◽  
Peipei Ma ◽  
Yachun Wang ◽  
Qin Zhang ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Somatic Cell ◽  
Milk Production ◽  
Milk Yield ◽  
Milk Fat ◽  
Protein Yield ◽  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Milk Production Traits ◽  
Chinese Holstein

CD4+T cells play a key role in the immune response of pathogen-induced mastitis in dairy cattle. Mammary gland factor STAT5b is involved in the regulation of CD4+T cell differentiation during inflammatory response and milk production. Little is known about the genetic variation effects of bovineCD4andSTAT5bgenes on somatic cell score (SCS) and milk production traits in dairy cattle. The aim of the study was to investigate the single nucleotide polymorphisms (SNPs) of bovineCD4andSTAT5bin Chinese Holsteins and to analyse their association with estimated breeding values (EBVs) for SCS and milk production traits. In the present study, SNPs ofCD4(NC_007303 g.13598C>T) andSTAT5b(NC_007317 g.31562 T>C) were identified and genotyped in Chinese Holstein population. The results showed that both SNPs were significantly associated with the EBVs for milk yield and protein yield in Chinese Holstein cows, and the SNP inCD4was associated with the EBV for SCS (P<0·01). The additive effect ofCD4SNP on protein yield was significant (P<0·05), and the dominant effect ofSTAT5bSNP was significant on milk yield and protein yield (P<0·01). Cows with combination genotype C7 (CCTT:CD4g.13598C>T andSTAT5bg.31562 T>C) had the highest SCS EBV but lower milk yield, while cows with C2 (TTTC) produced more milk, fat and protein than the other eight combination genotypes. These results suggested that the SNPs inCD4andSTAT5bmay be potential genetic markers for SCS and milk/protein yields selecting and warrant further functional research.

scholarly journals Comparison of different statistical-genetic approaches of QTL detection by Evaluating results from a real dairy cattle data set

2003 ◽  
Vol 46 (5) ◽  
pp. 413-423
Author(s):  
G. Freyer ◽  
C. Kühn ◽  
R. Weikard
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Real Data ◽  
Genetic Models ◽  
Production Traits ◽  
Cattle Population ◽  
Qtl Detection ◽  
Milk Production Traits ◽  
Data Set ◽  
Fat Yield

Abstract. Recent reports on estimating QTL positions and effects on milk production traits show several chromosomal regions, for example on BTA6, being putative QTL regions, for milk yield and traits of ingredients. The statistical methods and genetic models on which these results were based on, show different advantages and limits. Thus, it is sometimes difficult to compare and evaluate such results. Confirmation studies are inevitable, before drawing conclusions towards finemapping analyses or practical use of such results. We compared three published approaches, realizing up to five different genetic models of QTL estimation analysing the traits fat yield (kg) and fat content (%) based on a real data set of five granddaughter families from the German Holstein dairy cattle population. The marker map contained 16 microsatellite markers, distributed across chromosome BTA6. The focus was mainly on the most likely map positions of the putative QTL and on its character. The significant results obtained from using different methods and adapting several genetic models were conclusive and comparable to QTL positions reported elsewhere.

Effect of Breed and Some Non - Genetic Factors on Milk Production and Some Proportions of Its Chemical Components in Two Breeds of Local Sheep

2020 ◽  
Vol 10 (1) ◽  
pp. 227-231
Author(s):  
Rahman Hussein AL-Qasimi ◽  
Shatha Mohammed Abbas ◽  
Allawi L.D. AL-Khauzai
Keyword(s):  
Milk Production ◽  
Genetic Factors ◽  
Chemical Components ◽  
Lactation Period ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Awassi Sheep ◽  
Total Milk ◽  
Milk Components

The study was carried out on 19 ewes of local Awassi sheep and 12ewes local Arabi sheep in the Al-kafeel sheep station Karbala, to determine the effect of breed and some non-genetic factors such as (sex of the lamb, type of birth, age and weight of ewes at birth) on daily and total milk production and lactation period and some of milk components (fat, protein and lactose). The results showed that a significant effect (P <0.05) of the breed on milk production traits where Awassi sheep recorded the highest mean (0.91 kg , 101.63 kg , 104.86 day) compared to the Arabi sheep she was means (0.77 kg , 88.15 kg , 99.15 day) respectively. As well as in proportions of milk components with mean( 5.1 , 4.90 , 5.51) % respectively compared to the Arabi sheep (4.70 . 4.20 . 4.89) ewes with male lambs also exceeded superior ewes with female lambs in daily and total milk production and the lactation period the sex of the lamb did not affect the proportions of milk components the weight of the ewes had a significant effect (P <0.05) in milk production attributes with superior weight of ewes on lower ewes and did not affect the proportions of milk ingredients except for lactose. The type of birth and the age of the ewes did not have a significant effect in all the studied traits except for the superiority (P<0.05) of young ewes on age ewes in the fat percentage of milk.

An association analysis between PRL genotype and milk production traits in Italian Mediterranean river buffalo

2017 ◽  
Vol 84 (4) ◽  
pp. 430-433 ◽  
Author(s):  
Jun Li ◽  
Aixin Liang ◽  
Zipeng Li ◽  
Chao Du ◽  
Guohua Hua ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Milk Fat ◽  
Fat Content ◽  
Phenotypic Variance ◽  
River Buffalo ◽  
Production Traits ◽  
Milk Production Traits ◽  
Exon 2 ◽  
Mediterranean River

This Research Communication describes the association between genetic variation within the prolactin (PRL) gene and the milk production traits of Italian Mediterranean river buffalo (Bufala mediterranea Italiana). High resolution melting (HRM) techniques were developed for genotyping 465 buffaloes. The association of genetic polymorphism with milk production traits was performed and subsequently the effects of parity and calving season were evaluated. Single nucleotide polymorphisms (SNPs) were identified at exons 2 and 5 and at introns 1 and 2. All the SNPs were in Hardy–Weinberg equilibrium, and statistical analysis showed that the polymorphism of intron1 was significantly (P < 0·05) associated with milk yield, milk protein content and peak milk yield. The average contribution of the intron1 genotype (r2intron1) to total phenotypic variance in milk production traits was 0·09, and the TT genotype showed lower values than CC and CT genotypes. A nonsynonymous SNP was identified in exon 2, which resulted in an amino acid change from arginine to cysteine. Moreover, the polymorphism of exon 2 was associated significantly with milk fat content (P < 0·05), and the buffaloes with TT genotype showed higher total fat content than the buffaloes with CT genotype. These findings provide evidence that polymorphisms of the buffalo PRL gene are associated with milk production traits and PRL can be used as a candidate gene for marker-assisted selection in Italian Mediterranean river buffalo breeding.

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