Genetic parameters and genome-wide association studies for mozzarella and milk production traits, lactation length, and lactation persistency in Murrah buffaloes.

Genetic and genomic analyses of longitudinal traits related to milk production efficiency are paramount for optimizing water buffaloes breeding schemes. Therefore, this study aimed to (1) compare single-trait random regression models under a single-step genomic BLUP setting based on alternative covariance functions (i.e., Wood, Wilmink, and Ali and Schaeffer) to describe milk (MY), fat (FY), protein (PY), and mozzarella (MZY) yields, fat-to-protein ratio (FPR), somatic cell score (SCS), lactation length (LL), and lactation persistency (LP) in Murrah dairy buffaloes (Bubalus bubalis); (2) combine the best functions for each trait under a multiple-trait framework; (3) estimate time-dependent SNP effects for all the studied longitudinal traits; and (4) identify the most likely candidate genes associated with the traits. A total of 323,140 test-day records from the first lactation of 4,588 Murrah buffaloes were made available for the study. The model included the average curve of the population nested within herd-year-season of calving, systematic effects of number of milkings per day, and age at first calving as linear and quadratic covariates, and additive genetic, permanent environment, and residual as random effects. The Wood model had the best goodness of fit based on the deviance information criterion and posterior model probabilities for all traits. Moderate heritabilities were estimated over time for most traits (0.30 ± 0.02 for MY; 0.26 ± 0.03 for FY; 0.45 ± 0.04 for PY; 0.28 ± 0.05 for MZY; 0.13 ± 0.02 for FPR; and 0.15 ± 0.03 for SCS). The heritability estimates for LP ranged from 0.38 ± 0.02 to 0.65 ± 0.03 depending on the trait definition used. Similarly, heritabilities estimated for LL ranged from 0.10 ± 0.01 to 0.14 ± 0.03. The genetic correlation estimates across days in milk (DIM) for all traits ranged from -0.06 (186-215 DIM for MY-SCS) to 0.78 (66-95 DIM for PY-MZY). The SNP effects calculated for the random regression model coefficients were used to estimate the SNP effects throughout the lactation curve (from 5 to 305 d). Numerous relevant genomic regions and candidate genes were identified for all traits, confirming their polygenic nature. The candidate genes identified contribute to a better understanding of the genetic background of milk-related traits in Murrah buffaloes and reinforce the value of incorporating genomic information in their breeding programs.

Evaluation of performance and estimation of genetic parameters for milk yield and reproductive traits in Awassi and Asaf sheep breeds and crosses in the Palestinian territory.

This study aimed to estimate genetic parameters, including heritability and repeatability, for milk yield and prolificacy in sheep. It included 3682 records from 1837 ewes across various breeds: Awassi, Assaf, and Awassi x Assaf crosses, two Awassi lines: Improved Awassi, AFEC Awassi. The study measured total milk yield (TMY), yield up to 120 days (TMY120), and yield up to 150 days (TMY150), alongside reproductive traits: litter size (LS), number of lambs born alive (NLBA), and lambing interval (LI). The analysis utilized a mixed model and the REML procedure to estimate genetic parameters. Results indicated that litter size (LS) had no significant impact on milk traits, whereas breed, location, ewe parity, and lambing season showed significant effects. Lactation length also significantly influenced TMY. For reproductive traits, treatment was significant for NLBA, with location associated with breed, parity, and season affecting all traits. Heritability estimates for TMY ranged from 0.00 in Awassi x Assaf crosses to 0.11 in Awassi, and for TMY120 and TMY150, from 0.00 in Awassi x Assaf crosses to 0.16 in Awassi. Estimates for LS and NLBA varied similarly. The heritability for LI was 0.03 in Awassi and zero in other breeds and crosses. The findings suggest that in the northern West Bank regions of Nablus and Jenin, Assaf or Awassi x Assaf breeds are preferable. The study underscores the importance of comprehensive performance and pedigree recording for effective sheep farm management.

Single nucleotide polymorphisms in the bovine SLC2A12 and SLC5A1 glucose transporter genes - the effect on gene expression and milk traits of Holstein Friesian cows.

In this study, novel single nucleotide polymorphisms (SNPs) were found in the 5'-regulatory regions (promoters) of the bovine glucose transporter (GT) genes SLC2A12 and SLC5A1. These polymorphisms were shown to associate with certain milk production traits in HF cows, including milk yield, milk composition, and somatic cell count. It was shown that the SNP g.-671C > G (NC_037336.1: g.72224078C > G) in the SLC2A12 gene could be an effective marker of cattle production traits and that genotypes CC and CG are associated with the best productivity. The polymorphisms found in the SLC5A1 gene promoter also influenced milk production traits in HF cows, albeit to a lesser extent, and we propose that these polymorphisms could be useful as genetic markers for milk production traits in marker-assisted selection (MAS); however, this must be confirmed on larger populations of cattle. In addition, the presence of polymorphisms within promoter regions appears to affect the expression of GT genes in the cow mammary gland and modify transcription factor (TF) binding capacity.

A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle.

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

Understanding the phenotypic and genetic background of the lactose content in Sarda dairy sheep.

Lactose, the principal carbohydrate found in milk, plays an important role in the physiological processes of milk production because it is related to milk volume, and it is responsible for the osmotic equilibrium between blood and milk in the mammary gland. In this study, factors affecting lactose content (LC) in sheep milk are investigated. For this purpose, 2,358 test-day records were sampled from 509 ewes (3-7 records per animal). The LC and other main milk traits were analyzed using a mixed linear model that included days in milk (DIM) class, parity, lambing month, and type of lambing as fixed effects and animal, permanent environment, and flock test day as random effects. The pedigree-based approach was used to estimate the heritability and repeatability of LC. Moreover, the genomic background of LC was investigated through a GWAS. The LC was affected by all tested factors (i.e., DIM class, parity, lambing month, and type of lambing). Low heritability (0.10 ± 0.05) and moderate repeatability (0.42 ± 0.02) were estimated for LC. High negative genetic correlations were estimated between LC and NaCl (-0.99 ± 0.01) and between LC and somatic cell count (-0.94 ± 0.05). Only 2 markers passed the chromosome-wide Bonferroni threshold. Results of the present study, although obtained on a relatively small sample, suggest the possibility to include LC in the breeding programs, particularly because of its strong relationship with NaCl and somatic cell count.

Copy number variation of the USP16 gene and its association with milk traits in Chinese Holstein cattle.

Copy number variations (CNVs) were similar to single nucleotide polymorphisms (SNPs) and insertion-deletion (InDel), regarded as genetic variations in many species. CNV is defined as the variable change of DNA segment length compared with the reference genome, including gains or losses from 50 bp to several mega bases. The functions of USP16 gene are diverse, such as regulating the cell cycle, DNA damage, histone H2A deubiquitination or mitotic nuclear division. To analyze the relationship between CNV of USP16 gene and milk traits in Chinese Holstein, we used qPCR to detect the individuals of Chinese Holstein (n = 180). The results showed that the effect of USP16 gene CNV on daily milk yield and fat percentage had significant difference (p < 0.05). The gain was the advantage type in daily milk yield and the loss was the advantage type in fat percentage. Therefore, CNV of USP16 gene is an important factor of milk traits in Chinese Holstein. Meanwhile, it may be used as a molecular marker for assisted selection of milk traits in Chinese Holstein, which provides a theoretical basis for the genetic improvement of cow breeds in China.

A 67-bp variable duplication in the promoter region of the ADIPOQ is associated with milk traits in Xinjiang brown cattle.

Adiponectin, also known as ADIPOQ, is a hormone protein secreted by adipocytes. The ADIPOQ gene is expressed primarily in adipose tissue, and the encoded protein circulates in the bloodstream and has the potential to regulate both animal fat metabolism and hormone production. Our previous work uncovered a 67-bp variable duplication in the promoter region of ADIPOQ, which reduced the basal transcriptional activity of ADIPOQ in the 3T3_L1 cell and also inhibits the ADIPOQ mRNA expression in adipose tissue. Accordingly, the present study aimed to identify the relationship between the 67-bp structural variations in ADIPOQ promoter region and the milk traits of Xinjiang brown cattle (XJBC). The results revealed two genotypes, DD and ID, in the XJBC, and minor allelic frequency (MAF) for the 'I' allele was more than 1%. Moreover, the association analysis revealed that the 67-bp duplication in the promoter region of the ADIPOQ gene was significantly correlated with the 305 days of milk production volume, fat yield, and milk fat percentage in the XJBC (p < 0.05). These results obtained in this study suggested that the identified variable duplication could be considered as the potential genetic marker for improving milk traits of XJBC.

A molecular marker of milk composition traits in NCAM2 gene of Chinese Holstein.

The aim of this study was to detect the novel copy number variation (CNV) locus of NCAM2 gene in Chinese Holstein, and to analyze the effect of the novel CNV locus in NCAM2 gene on milk composition traits. The novel CNV locus of NCAM2 gene in 310 Chinese Holstein was detected by real-time quantitative fluorescent PCR (qPCR) and association analysis was performed between the novel CNV locus in NCAM2 gene and milk composition traits in Chinese Holstein. There are three CNV types of NCAM2 gene in Chinese Holstein: gain (increased copy number), median (normal copy number) and loss (deleted copy number). Statistical analysis revealed that there was a significant association between CNV types and milk fat rate (p < 0.05). Moreover, we also discovered that the milk production and milk protein rate of gain type is higher than that of loss type, but that of mediate type is lower than that of loss type. However, in terms of somatic cell score, loss type is higher than that of gain type, but that of mediate type is lower than that of gain type. These observations suggested that gain type can be used as a candidate molecular genetic marker of milk fat rate.HighlightsThe CNVs of the NCAM2 gene were detected and validated in Chinese Holstein.The type of CNV was successfully implemented using qPCR.The statistical analysis indicated that the CNV of the NCAM2 gene are significantly associated with milk fat rate.

Comparison of phenotypic and heterotic effects affecting milk yield, composition and udder morphometry of Hair and F1, F2 and G1 generation cross-breeds of Alpine × Hair and Saanen × Hair dairy goats in a semi-intensive system.

This study was conducted to compare milk yield, milk components and udder traits of Hair goat, F1, F2 and G1 generation cross-breeds of Alpine × Hair and Saanen × Hair goats under a semi-intensive system. The effects of genotype, parity, flock and year on milk production, physical and chemical compositions were almost all significant (between p < 0.05 and p < 0.001). The F1, F2 and G1 generations produced 24 and 44% higher (p < 0.001) lactation milk yield (LMY), 12 and 35% (p < 0.001) fat yield and 19 and 35% (p < 0.001) protein yield than Hair goat. Positive heterosis was found in milk production and contents both Alpine × Hair F1 (AHF1) and Saanen × Hair F1 (SHF1) generations. The heterotic effect of the LMY was significant in the SHF1 generation (p < 0.05), but not in the AHF1 generation. The highest correlation was found between LMY and udder circumference and then udder volume (p < 0.001; r = from 0.34 to 0.75). The coefficient of determination of the obtained equation for the estimation of the LMY in the Hair and cross-bred goats ranged from 0.48 to 0.71. These results showed that as the level of cross-breeding increased in this semi-intensive system, better quality dairy products can be obtained from goats, and udder measurements can be a helpful tool in estimating milk yield, thus reducing the pressure on the ecosystem. Thus, it was concluded that with better modelling of environmental variations, milk production characteristics of local goats can be increased much faster by cross-breeding, especially at the F1 and G1 generation cross-breed levels.

Genome-wide analysis of homozygosity regions in european simmental bulls.

The study of Runs of Homozygosity (ROH) is a useful approach for the characterization of the genome of livestock populations. Due to their high relationship with autozygosity, ROH allow to make inference about population genetic history, to estimate the level of inbreeding, to assess within breed heterogeneity and to detect the footprints of selection on livestock genomes. Aim of this study was to investigate the distribution of runs of homozygosity in bulls belonging to five European Simmental populations and to assess the relationship between three production traits (milk yield, fat and protein contents) and autozygosity. ROH count, distribution and ROH-based coefficient of inbreeding (FROH ) were calculated for 3,845 Simmental bulls of five different European countries: Austria (AT), Switzerland (CH), Czech Republic (CZ), Germany (DE) and Italy (IT). Average values of ROH number per animal, and total genome length covered by ROH were 77.8 ± 20.7 and 205 ± 74.4 Mb, respectively. Bulls from AT, DE and IT exhibited similar ROH characteristics. Swiss animals showed the highest (12.6%), while CZ the lowest (4.6%) FROH coefficient. The relationship between ROH occurrence and milk production traits was investigated through a genome-wide ROH-traits association analysis (GWRA). A total of 34 regions previously associated with milk traits (yield and/or composition) were identified by GWRA. Results of the present research highlight a mixed genetic background in the 5 European Simmental populations, with the possible presence of three subgroups. Moreover, a strong relationship between autozygosity and production traits has been detected.

Association analysis between FASN genotype and milk traits in Mediterranean buffalo and its expression among different buffalo tissues.

Fatty acid synthase (FASN) is a multifunctional protein that catalyzes the synthesis of long-chain saturated fatty acid. In this study, we identified the single nucleotide polymorphisms (SNPs), and their association with milk traits in Mediterranean buffalo, and the expression of FASN gene in different tissues was measured. Nine SNPs (g.-1640G > A, g.-1099C > T, g.1095C > A, g.3221G > A, g.4762G > A, g.5299G > A, g.7164G > A, g.7272 T > C, and g.8927 T > C) were identified by DNA pooled sequencing and then genotyped. Seven identified SNPs except g.3221G > A and g.8927 T > C were found significantly associated with both fat and protein percentage, and also the g.7164G > A and g.8927 T > C had significant association with peak milk yield and protein percentage, respectively. One haplotype block was successfully constructed by linkage disequilibrium (LD) analysis and it showed a significant association with both fat percentage and protein percentage. Expression of FASN gene was found in almost all the buffalo tissues including mammary gland, heart, liver, spleen, lung, kidney, uterus, and ovary, and to be highest in lung and mammary gland. Our findings suggest that polymorphisms in the buffalo FASN gene are associated with milk production traits and can be used as a candidate gene for milk traits and marker-assisted selection in buffalo breeding program.

Variation in the yak lipin-1 gene and its association with milk traits.

The aim of this research was to identify variation in the yak lipin-1 gene (LPIN1) and determine whether this variation affects milk traits. PCR-single stranded conformational polymorphism (PCR-SSCP) analysis was used to detect variation in the 5' untranslated region of LPIN1 in 500 yaks from four populations: Tianzhu white yaks, Qinghai yaks, wild × domestic-cross yaks and Gannan yaks. Four unique PCR-SSCP patterns, representing four different DNA sequence variants (named A, B, C and D), were observed. These contained six single nucleotide polymorphisms. Female Gannan yaks with BC genotype produced milk with a higher fat content (P < 0.001) and total milk solids (P < 0.001), than those with the AA, AB and BB genotypes. These results would suggest that LPIN1 is having an effect on yak milk fat synthesis.

Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle.

BACKGROUND: Genome-wide association studies (GWAS) have been successfully implemented in cattle research and breeding. However, moving from the associations to identify the causal variants and reveal underlying mechanisms have proven complicated. In dairy cattle populations, we face a challenge due to long-range linkage disequilibrium (LD) arising from close familial relationships in the studied individuals. Long range LD makes it difficult to distinguish if one or multiple quantitative trait loci (QTL) are segregating in a genomic region showing association with a phenotype. We had two objectives in this study: 1) to distinguish between multiple QTL segregating in a genomic region, and 2) use of external information to prioritize candidate genes for a QTL along with the candidate variants. RESULTS: We observed fixing the lead SNP as a covariate can help to distinguish additional close association signal(s). Thereafter, using the mammalian phenotype database, we successfully found candidate genes, in concordance with previous studies, demonstrating the power of this strategy. Secondly, we used variant annotation information to search for causative variants in our candidate genes. The variant information successfully identified known causal mutations and showed the potential to pinpoint the causative mutation(s) which are located in coding regions. CONCLUSIONS: Our approach can distinguish multiple QTL segregating on the same chromosome in a single analysis without manual input. Moreover, utilizing information from the mammalian phenotype database and variant effect predictor as post-GWAS analysis could benefit in candidate genes and causative mutations finding in cattle. Our study not only identified additional candidate genes for milk traits, but also can serve as a routine method for GWAS in dairy cattle.

Assessing the accuracy of prediction for milk fatty acids by using a small reference population of tropical Holstein cows.

Fatty acids (FA) have been related to effects on human health, sensory quality and shelf life of dairy products, cow's health and methane emission. However, despite their importance, they are not regularly measured in all dairy herds yet, which can affect the accuracy of estimated breeding values (EBV) for these traits. In this case, an alternative is to use genomic selection. Thus, the aim was to assess the use of genomic information in the genetic evaluation for milk traits in a tropical Holstein population. Monthly records (n = 36,457) of milk FA percentage, daily milk yield and quality traits from 4,203 cows as well as the genotypes of 755 of these cows for 57,368 single nucleotide polymorphisms (SNP) were used. Polygenic and genomic-polygenic models were applied for EBV prediction, and both models were compared through the EBV accuracy calculated from the prediction error and Spearman's correlation among EBV rankings. Prediction accuracy was assessed by using cross-validation. In this case, the accuracy was the correlation between the genomic breeding values (GEBV) obtained as the sum of SNP effects and the EBV obtained in the polygenic model in each validation group. For all traits, the use of the genomic-polygenic model did not alter the animals' ranking, with correlations higher than 0.87. Nevertheless, through this model, the accuracy increased from 1.5% to 6.8% compared to the polygenic model. The correlations between GEBV and EBV varied from 0.52 to 0.68. Therefore, the use of a small group of genotyped cows in the genetic evaluation can increase the accuracy of EBV for milk FA and other traditional milk traits.

Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle.

BACKGROUND: Genome-wide association studies (GWAS) have been successfully implemented in cattle research and breeding. However, moving from the associations to identifying the causal variants and revealing underlying mechanisms have proven complicated. In dairy cattle populations, we face a challenge due to long-range linkage disequilibrium (LD) arising from close familial relationships in the studied individuals. Long range LD makes it difficult to distinguish if one or multiple quantitative trait loci (QTL) are segregating in a genomic region showing association with a phenotype. We had two objectives in this study: 1) to distinguish between multiple QTL segregating in a genomic region, and 2) use of external information to prioritize candidate genes for a QTL along with the candidate variant. RESULTS: We observed fixing the lead SNP as a covariate can help to distinguish additional close association signal(s). Thereafter, using the mammalian phenotype database, we successfully found candidate genes, in concordance with previous studies, demonstrating the power of this strategy. Secondly, we used variant annotation information to search for causative variants in our candidate genes. The variant information successfully identified known causal mutations and showed the potential to pinpoint the causative mutation(s) which are located in coding regions. CONCLUSIONS: Our approach can distinguish multiple QTL segregating on the same chromosome in a single analysis without manual input. Moreover, utilizing information from the mammalian phenotype database and variant effect predictor as post-GWAS analysis could benefit in candidate genes and causative mutations finding in cattle. Our study not only identified additional candidate genes for milk traits, but also can serve as a routine method for GWAS in dairy cattle.

Highly accurate sequence imputation enables precise QTL mapping in Brown Swiss cattle.

BACKGROUND: Within the last few years a large amount of genomic information has become available in cattle. Densities of genomic information vary from a few thousand variants up to whole genome sequence information. In order to combine genomic information from different sources and infer genotypes for a common set of variants, genotype imputation is required. RESULTS: In this study we evaluated the accuracy of imputation from high density chips to whole genome sequence data in Brown Swiss cattle. Using four popular imputation programs (Beagle, FImpute, Impute2, Minimac) and various compositions of reference panels, the accuracy of the imputed sequence variant genotypes was high and differences between the programs and scenarios were small. We imputed sequence variant genotypes for more than 1600 Brown Swiss bulls and performed genome-wide association studies for milk fat percentage at two stages of lactation. We found one and three quantitative trait loci for early and late lactation fat content, respectively. Known causal variants that were imputed from the sequenced reference panel were among the most significantly associated variants of the genome-wide association study. CONCLUSIONS: Our study demonstrates that whole-genome sequence information can be imputed at high accuracy in cattle populations. Using imputed sequence variant genotypes in genome-wide association studies may facilitate causal variant detection.

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

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 (r 2 intron1) 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.

Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants.

BACKGROUND: The Nordic Red Cattle consisting of three different populations from Finland, Sweden and Denmark are under a joint breeding value estimation system. The long history of recording of production and health traits offers a great opportunity to study production traits and identify causal variants behind them. In this study, we used whole genome sequence level data from 4280 progeny tested Nordic Red Cattle bulls to scan the genome for loci affecting milk, fat and protein yields. RESULTS: Using a genome-wise significance threshold, regions on Bos taurus chromosomes 5, 14, 23, 25 and 26 were associated with fat yield. Regions on chromosomes 5, 14, 16, 19, 20 and 25 were associated with milk yield and chromosomes 5, 14 and 25 had regions associated with protein yield. Significantly associated variations were found in 227 genes for fat yield, 72 genes for milk yield and 30 genes for protein yield. Ingenuity Pathway Analysis was used to identify networks connecting these genes displaying significant hits. When compared to previously mapped genomic regions associated with fertility, significantly associated variations were found in 5 genes common for fat yield and fertility, thus linking these two traits via biological networks. CONCLUSION: This is the first time when whole genome sequence data is utilized to study genomic regions affecting milk production in the Nordic Red Cattle population. Sequence level data offers the possibility to study quantitative traits in detail but still cannot unambiguously reveal which of the associated variations is causative. Linkage disequilibrium creates difficulties to pinpoint the causative genes and variations. One solution to overcome these difficulties is the identification of the functional gene networks and pathways to reveal important interacting genes as candidates for the observed effects. This information on target genomic regions may be exploited to improve genomic prediction.

Goat casein genotypes are associated with milk production traits in the Sarda breed.

The aim of the current work was to analyze, in the Sarda breed goat, genetic polymorphism within the casein genes and to assess their influence on milk traits. Genetic variants at the CSN1S1, CSN2, CSN1S2 and CSN3 gene loci were investigated using PCR-based methods, cloning and sequencing. Strong alleles prevailed at the CSN1S1 gene locus and defective alleles also were revealed. Null alleles were evidenced at each calcium-sensitive gene locus. At the CSN3 gene locus, we observed a prevalence of the CSN3 A and B alleles; the occurrence of rare alleles such as CSN3 B'', C, C', D, E and M; and the CSN3 S allele (GenBank KF644565) described here for the first time in Capra hircus. Statistical analysis showed that all genes, except CSN3, significantly influenced milk traits. The CSN1S1 BB and AB genotypes were associated with the highest percentages of protein (4.41 and 4.40 respectively) and fat (5.26 and 5.34 respectively) (P < 0.001). A relevant finding was that CSN2 and CSN1S2 genotypes affected milk protein content and yield. The polymorphism of the CSN2 gene affected milk protein percentage with the highest values recorded in the CSN2 AA goats (4.35, at P < 0.001). The CSN1S2 AC goats provided the highest fat (51.02 g/day) and protein (41.42 g/day) (P < 0.01) production. This information can be incorporated into selection schemes for the Sarda breed goat.

CSN1S1, CSN3 and LPL: Three Validated Gene Polymorphisms Useful for More Sustainable Dairy Production in the Mediterranean River Buffalo.

The search for DNA polymorphisms useful for the genetic improvement of dairy farm animals has spanned more than 40 years, yielding relevant findings in cattle for milk traits, where the best combination of alleles for dairy processing has been found in casein genes and in DGAT1. Nowadays, similar results have not yet been reached in river buffaloes, despite the availability of advanced genomic technologies and accurate phenotype records. The aim of the present study was to investigate and validate the effect of four single nucleotide polymorphisms (SNP) in the CSN1S1, CSN3, SCD and LPL genes on seven milk traits in a larger buffalo population. These SNPs have previously been reported to be associated with, or affect, dairy traits in smaller populations often belonging to one farm. A total of 800 buffaloes were genotyped. The following traits were individually recorded, monthly, throughout each whole lactation period from 2010 to 2021: daily milk yield (dMY, kg), protein yield (dPY, kg) and fat yield (dFY, kg), fat and protein contents (dFP, % and dPP, %), somatic cell count (SCC, 103 cell/mL) and urea (mg/dL). A total of 15,742 individual milk test day records (2496 lactations) were available for 680 buffalo cows, with 3.6 ± 1.7 parities (from 1 to 13) and an average of 6.1 ± 1.2 test day records per lactation. Three out four SNPs in the CSN1S1, CSN3 and LPL genes were associated with at least one of analyzed traits. In particular, the CSN1S1 (AJ005430:c.578C>T) gave favorable associations with all yield traits (dMY, p = 0.022; dPY, p = 0.014; dFY, p = 0.029) and somatic cell score (SCS, p = 0.032). The CSN3 (HQ677596: c.536C>T) was positively associated with SCS (p = 0.005) and milk urea (p = 0.04). Favorable effects on daily milk yield (dMY, p = 0.028), fat (dFP, p = 0.027) and protein (dPP, p = 0.050) percentages were observed for the LPL. Conversely, the SCD did not show any association with milk traits. This is the first example of a confirmation study carried out in the Mediterranean river buffalo for genes of economic interest in the dairy field, and it represents a very important indication for the preselection of young bulls destined for breeding programs aimed at more sustainable dairy production.