In silico identification of variations in microRNAs with a potential impact on dairy traits using whole ruminant genome SNP datasets

MicroRNAs are small noncoding RNAs that have important roles in the lactation process and milk biosynthesis. Some polymorphisms have been studied in various livestock species from the perspective of pathology or production traits. To target variants that could be the causal variants of dairy traits, genetic variants of microRNAs expressed in the mammary gland or present in milk and localized in dairy quantitative trait loci (QTLs) were investigated in bovine, caprine, and ovine species. In this study, a total of 59,124 (out of 28 millions), 13,427 (out of 87 millions), and 4761 (out of 38 millions) genetic variants in microRNAs expressed in the mammary gland or present in milk were identified in bovine, caprine, and ovine species, respectively. A total of 4679 of these detected bovine genetic variants are located in dairy QTLs. In caprine species, 127 genetic variants are localized in dairy QTLs. In ovine species, no genetic variant was identified in dairy QTLs. This study leads to the detection of microRNA genetic variants of interest in the context of dairy production, taking advantage of whole genome data to identify microRNA genetic variants expressed in the mammary gland and localized in dairy QTLs.

Estimation of Population-Specific Genetic Parameters Important for Long-Term Optimum Contribution Selection—Case Study on a Dairy Istrian Sheep Breed

The Istrian sheep breed has been subjected to selection for dairy traits for more than two decades. However, a detailed study of some important population-specific parameters such as effective population size (Ne) and connectedness between flocks has never been carried out. The aim of the study was to examine the above parameters in dairy Istrian sheep subjected to a national selection program. The Ne was estimated as the mean rate of increase in coancestry, and connectedness was determined using four different statistics. The Ne was estimated at 73 animals with pedigree constraints imposed on 4 equivalent generations and 3 full generations. Analysis of ΔNe (“sliding window approach”) revealed a negative ΔNe indicating a progressive loss of genetic variability (ΔNeNEG≥4 = −6.6, p < 0.01; ΔNeNFG≥3 = −4.9, p > 0.05). The overall connectedness (r¯ ~ 0.0001) was below the acceptable level for unbiased ranking of the animals belonging to different flocks (ri,j = 0.05). OCS appears to be the best option for the long-term survival (self-sufficiency) of the breed, but genetic links between flocks need to be strengthened to allow unbiased ranking of the animals based on the estimated breeding values.

Novel Genes Associated with Dairy Traits in Sarda Sheep

The aim of the present research was to analyze the variability of 45 SNPs from different genes involved in metabolism and innate immunity to perform an association analysis with the milk yield, composition and milk coagulation traits. A population of 1112 Sarda breed sheep was sampled. Genotyping was generated by a TaqMan Open ArrayTM. Thirty out of the 45 SNPs were polymorphic, and 12 displayed a minor allele frequency higher than 0.05. An association analysis showed that the variability at genes PRKAG3 and CD14 was significantly associated with the daily milk yield. The variability at PRKAG3 was also associated with the protein and casein content, somatic cell score and bacterial score. The variation at the PRKAA2 gene was associated with the milk lactose concentration. The SNPs at CD14 were also associated with the traditional milk coagulation properties, while the SNPs at GHR and GHRHR were associated with kSR, a derived coagulation parameter related to the rate of syneresis. The information provided here is new and increases our knowledge of genotype–phenotype interactions in sheep. Our findings might be useful in appropriate breeding schemes to be set up for the Sarda sheep breed, but these should be confirmed by further studies, possibly performed on independent populations.

Estimation of Non-Genetic Parameters for Reproduction and Production Traits of Holstein Friesian Dairy Herd at Elfora Cheffa Dairy Farm, Amhara Region, Ethiopia

Background:- The study was conducted at Cheffa dairy farm with the objective of estimating the effects of none-genetic factors on Age at First Service (AFS), Age at First Calving (AFC), Calving Interval (CI), Days Open (DO), Number of Service per Conception (NSC), Lactation Length (LL) and adjusted 305 days milk yield (305-dMY). A total of 2343 records were collected from 123 cows and 13 sires' progenies having greater than 93.75 % HF blood levels through the period from 1996 to 2014 for evaluation. Independent variables were birth year and season, calving year and season and parity while AFS, AFC, CI, DO, NSC, LL and 305-dMY were dependent variables. SAS Version 9.1 software used for data analysis. Results:- The results indicated that year of birth had highly significant (p<0.01) and significant (p<0.05) effect on AFS and AFC respectively. Year of calving had highly significant (p<0.01) effect on CI and 305-dMY and significant (p<0.05) effect on DO and NSC. Season of calving had significant (p<0.05) effect on CI and 305-dMY. Longest records of CI and highest records of 305-dMY were exhibited in short rain season while, shortest and lowest records of CI and 305-dMY were recorded in dry and long rain seasons respectively. Parity had highly significant (p<0.01) effect on CI, DO, NSC and 305-dMY and significant (p<0.05) effect on LL. Longest value of CI, DO and LL were observed in 1st parity and highest value of NSC and highest value of 305-dMY were recorded in 7th and 5th parity respectively. The shortest value of CI, DO, LL and lowest value of 305-dMY was recorded in 9th parity while shortest value of NSC was recorded in 1st parity. Conclusions:- This study revealed, genetic performance of dairy breed in the study area was influenced by environment but selecting adapted animal from the herd and better management may improve all aspect of productivity. Hence, well record keeping, better management practice, non-genetic performance evaluation of economically important dairy traits and investigation of selection index were a prerequisite to improvement productivity of the herd and to run profitable dairy enterprise.

Genome-Wide Association Study towards Genomic Predictive Power for High Production and Quality of Milk in American Alpine Goats

This paper reports an exploratory study based on quantitative genomic analysis in dairy traits of American Alpine goats. The dairy traits are quality-determining components in goat milk, cheese, ice cream, etc. Alpine goat phenotypes for quality components have been routinely recorded for many years and deposited in the Council on Dairy Cattle Breeding (CDCB) repository. The data collected were used to conduct an exploratory genome-wide association study (GWAS) from 72 female Alpine goats originating from locations throughout the U.S. Genotypes were identified with the Illumina Goat 50K single-nucleotide polymorphisms (SNP) BeadChip. The analysis used a polygenic model where the dropping criterion was a call rate≥0.95. The initial dataset was composed of ~60,000 rows of SNPs and 21 columns of phenotypic traits and composed of 53,384 scaffolds containing other informative data points used for genomic predictive power. Phenotypic association with the 50K BeadChip revealed 26,074 reads of candidate genes. These candidate genes segregated as separate novel SNPs and were identified as statistically significant regions for genome and chromosome level trait associations. Candidate genes associated differently for each of the following phenotypic traits: test day milk yield (13,469 candidate genes), test day protein yield (25,690 candidate genes), test day fat yield (25,690 candidate genes), percentage protein (25,690 candidate genes), percentage fat (25,690 candidate genes), and percentage lactose content (25,690 candidate genes). The outcome of this study supports elucidation of novel genes that are important for livestock species in association to key phenotypic traits. Validation towards the development of marker-based selection that provides precision breeding methods will thereby increase the breeding value.

Biodiversity and dairy traits of indigenous milk lactic acid bacteria grown in presence of the main grape polyphenols

ABSTRACT The present work was developed to select lactic acid bacteria (LAB) to be used as starter cultures in functional cheese production. The indigenous milk LAB populations were isolated from fermented raw ewes’ milks (four bulks) added with 0.5 mg/mL of nine polyphenols commonly found in winery by-products. After 48 h of fermentation, all milks were characterized by an increase of LAB levels of about 3–4 Log cycles. All different colonies were purified and characterized for the main physiological and biochemical traits and then differentiated genetically at strain level and identified. Ten species belonging to the LAB genera Lactobacillus, Streptococcus, Enterococcus, Leuconostoc and Lactococcus were identified. Only Lactococcus lactis and Leuconostoc mesenteroides strains were evaluated for the technological traits including acidification and autolytic kinetics, diacetyl formation, exopolysaccharide production and generation of antimicrobial compounds. A total of four strains (Mise36, Mise94 Mise169 and Mise190) belonging to Lc. lactis displayed potential for production of cheeses containing grape polyphenols.

Estimation of genetic parameters for dairy traits using repeatability animal models based on test-day data for Alpine goat in Croatia

The objective of this study was to estimate genetic parameters for daily milk yield (DMY), fat (FC), and protein content (PC) using 329.022 test-day records of 23.756 Alpine does. Single trait repeatability animal model was applied. Parity, litter size, season, and lactation stage (Ali-Schaeffer’s curve) were fitted in the fixed, while herd, herd-test-day, permanent environment (within lactations) and additive genetic effect in the random part of the model. Variance components were estimated using Residual Maximum Likelihood Method in the VCE-6 program. Additive genetic effect explained 23 %, 16 % and 25 % of DMY, FC and PC variability which is in general agreement with numerous previous reports for dairy goat breeds. Among the non-genetic effects, herd explained 24 %, 12 %, and 9 %, herd-test-day 17 %, 29 %, and 30 %, and permanent environment 16 %, 3 %, and 5 % of DMY, FC and PC variability, respectively. The estimated parameters and developed single trait repeatability test-day models will serve as a basic tool in BLUP based genetic evaluation of Alpine breed in Croatia.