High density genome wide genotyping-by-sequencing and association identifies common and low frequency SNPs, and novel candidate genes influencing cow milk traits

Networks of human milk microbiota are associated with host genomics, childhood asthma, and allergic sensitization

The human milk microbiota (HMM) is thought to influence the long-term health of offspring. However, its role in asthma and atopy and the impact of host genomics on HMM composition remain unclear. Through the CHILD Cohort Study, we followed 885 pregnant mothers and their offspring from birth to 5 years and determined that HMM was associated with maternal genomics and prevalence of childhood asthma and allergic sensitization (atopy) among human milk-fed infants. Network analysis identified modules of correlated microbes in human milk that were associated with subsequent asthma and atopy in preschool-aged children. Moreover, reduced alpha-diversity and increased Lawsonella abundance in HMM were associated with increased prevalence of childhood atopy. Genome-wide association studies (GWASs) identified maternal genetic loci (e.g., ADAMTS8, NPR1, and COTL1) associated with HMM implicated with asthma and atopy, notably Lawsonella and alpha-diversity. Thus, our study elucidates the role of host genomics on the HMM and its potential impact on childhood asthma and atopy.

Detection and evaluation of parameters influencing the identification of heterozygous-enriched regions in Holstein cattle based on SNP chip or whole-genome sequence data

BACKGROUND

A heterozygous-enriched region (HER) is a genomic region with high variability generated by factors such as balancing selection, introgression, and admixture processes. In this study, we evaluated the genomic background of HERs and the impact of different parameters (i.e., minimum number of SNPs in a HER, maximum distance between two consecutive SNPs, minimum length of a HER, maximum number of homozygous allowed in a HER) and scenarios [i.e., different SNP panel densities and whole-genome sequence (WGS)] on the detection of HERs. We also compared HERs characterized in Holstein cattle with those identified in Angus, Jersey, and Norwegian Red cattle using WGS data.

RESULTS

The parameters used for the identification of HERs significantly impact their detection. The maximum distance between two consecutive SNPs did not impact HERs detection as the same average of HERs (269.31 ± 787.00) was observed across scenarios. However, the minimum number of markers, maximum homozygous markers allowed inside a HER, and the minimum length size impacted HERs detection. For the minimum length size, the 10 Kb scenario showed the highest average number of HERs (1,364.69 ± 1,483.64). The number of HERs decreased as the minimum number of markers increased (621.31 ± 1,271.83 to 6.08 ± 21.94), and an opposite pattern was observed for the maximum homozygous markers allowed inside a HER (54.47 ± 195.51 to 494.89 ± 1,169.35). Forty-five HER islands located in 23 chromosomes with high Tajima's D values and differential among the observed and estimated heterozygosity were detected in all evaluated scenarios, indicating their ability to potentially detect regions under balancing selection. In total, 3,440 markers and 28 genes previously related to fertility (e.g., TP63, ZSCAN23, NEK5, ARHGAP44), immunity (e.g., TP63, IGC, ARHGAP44), residual feed intake (e.g., MAYO9A), stress sensitivity (e.g., SERPINA6), and milk fat percentage (e.g., NOL4) were identified. When comparing HER islands among breeds, there were substantial overlaps between Holstein with Angus (95.3%), Jersey (94.3%), and Norwegian Red cattle (97.1%), indicating conserved HER across taurine breeds.

CONCLUSIONS

The detection of HERs varied according to the parameters used, but some HERs were consistently identified across all scenarios. Heterozygous genotypes observed across generations and breeds appear to be conserved in HERs. The results presented could serve as a guide for defining HERs detection parameters and further investigating their biological roles in future studies.

Whole-genome resequencing of native and imported dairy goat identifies genes associated with productivity and immunity

Understanding the differences in genetic variation between local Chinese dairy goat breeds and imported breeds can help germplasm innovation and molecular breeding. However, the research is limited in this area. In this study, whole-genome resequencing data from 134 individuals of both local and imported dairy goat breeds were analyzed, and their differences in genomic genetic variation, genetic diversity, and population structure were subsequently identified. We also screened candidate genes associated with important traits of dairy goats such as milk production (STK3, GHR, PRELID3B), reproduction (ATP5E), growth and development (CTSZ, GHR), and immune function (CTSZ, NELFCD). Furthermore, we examined allele frequency distributions for the genes of interest and found significant differences between the two populations. This study provides valuable resources for the study of genetic diversity in dairy goats and lays the foundation for the selective breeding of dairy goats in the future.

Signatures of positive selection after the introduction of genomic selection in the Finnish Ayrshire population

The Finnish Ayrshire (FAY) belongs to the Nordic Red breeds and is characterized by high milk yield, high milk components, good fertility, and functional conformation. The FAY breeding program is based on genomic selection. Despite the benefits of selection on breeding values, autozygosity in the genome may increase due to selection, and increased autozygosity may cause inbreeding depression in selected traits. However, there is lack of studies concerning selection signatures in the FAY after genomic selection introduction. The aim of this study was to identify signatures of selection in FAY after the introduction of genomic selection. Genomic data included 45,834 SNPs. The genotyped animals were divided into 2 groups: animals born before genomic selection introduction (6,108 cows) and animals born after genomic selection introduction (47,361 cows). We identified the selection signatures using 3 complementary methods: 2 based on identification of selection signatures from runs of homozygosity (ROH) islands and one based on the decay of site-specific extended haplotype between populations at SNP sites (Rsb). In total, we identified 34 ROH islands on chromosomes 1, 3, 6, 8, 12-15, 17, 19, 22, and 26 in FAY animals born before genomic selection (between 1980 and 2011) and 30 ROH islands on chromosomes 1-3, 13-17, 22, and 25-26 in FAY animals born after genomic selection introduction (between 2015 and 2020). We additionally detected 22 ΔROH islands on chromosomes 2-3, 11, 13, 14, 16, 18, 20, and 25-26. Finally, a total of 31 Rsb regions on chromosomes 2, 3, 14, 18, 20, and 25 were identified. Based on the results, genomic selection has favored certain alleles and haplotypes on genomic regions related to traits relevant in the FAY breeding program: milk production, fertility, growth, beef production traits, and feed efficiency. Several genes related to these traits (e.g., PLA2G4A, MECR, CHUK, COX15, RICTOR, SHISA9, and SEMA4G) overlapped or partially overlapped the observed selection signature regions. The association of genotypes within these regions and their effects on traits relevant in the FAY breeding program should be studied and genetic regions undergoing selection monitored in the FAY population.

Whole Genome Scan Uncovers Candidate Genes Related to Milk Production Traits in Barka Cattle

In this study, our primary aim was to explore the genomic landscape of Barka cattle, a breed recognized for high milk production in a semi-arid environment, by focusing on genes with known roles in milk production traits. We employed genome-wide analysis and three selective sweep detection methods (ZFST, θπ ratio, and ZHp) to identify candidate genes associated with milk production and composition traits. Notably, ACAA1, P4HTM, and SLC4A4 were consistently identified by all methods. Functional annotation highlighted their roles in crucial biological processes such as fatty acid metabolism, mammary gland development, and milk protein synthesis. These findings contribute to understanding the genetic basis of milk production in Barka cattle, presenting opportunities for enhancing dairy cattle production in tropical climates. Further validation through genome-wide association studies and transcriptomic analyses is essential to fully exploit these candidate genes for selective breeding and genetic improvement in tropical dairy cattle.

Unraveling genomic diversity and positive selection signatures of Qaidam cattle through whole-genome re-sequencing

Qaidam cattle are a typical Chinese native breed inhabiting northwest China. They bear the characteristics of high cold and roughage tolerance, low-oxygen adaptability and good meat quality. To analyze the genetic diversity of Qaidam cattle, 60 samples were sequenced using whole-genome resequencing technology, along with 192 published sets of whole-genome sequencing data of Indian indicine cattle, Chinese indicine cattle, North Chinese cattle breeds, East Asian taurine cattle, Eurasian taurine cattle and European taurine cattle as controls. It was found that Qaidam cattle have rich genetic diversity in Bos taurus, but the degree of inbreeding is also high, which needs further protection. The phylogenetic analysis, principal component analysis and ancestral component analysis showed that Qaidam cattle mainly originated from East Asian taurine cattle. Qaidam cattle had a closer genetic relationship with the North Chinese cattle breeds and the least differentiation from Mongolian cattle. Annotating the selection signals obtained by composite likelihood ratio, nucleotide diversity analysis, integrated haplotype score, genetic differentiation index, genetic diversity ratio and cross-population extended haplotype homozygosity methods, several genes associated with immunity, reproduction, meat, milk, growth and adaptation showed strong selection signals. In general, this study provides genetic evidence for understanding the germplasm characteristics of Qaidam cattle. At the same time, it lays a foundation for the scientific and reasonable protection and utilization of genetic resources of Chinese local cattle breeds, which has great theoretical and practical significance.

Polymorphisms of CYP7A1 and HADHB Genes and Their Effects on Milk Production Traits in Chinese Holstein Cows

Our preliminary research proposed the cytochrome P450 family 7 subfamily A member 1 (CYP7A1) and hydroxyacyl-coenzyme A dehydrogenase trifunctional multienzyme complex beta subunit (HADHB) genes as candidates for association with milk-production traits in dairy cattle because of their differential expression across different lactation stages in the liver tissues of Chinese Holstein cows and their potential roles in lipid metabolism. Hence, we identified single-nucleotide polymorphisms (SNPs) of the CYP7A1 and HADHB genes and validated their genetic effects on milk-production traits in a Chinese Holstein population with the goal of providing valuable genetic markers for genomic selection (GS) in dairy cattle, This study identified five SNPs, 14:g.24676921A>G, 14:g.24676224G>A, 14:g.24675708G>T, 14:g.24665961C>T, and 14:g.24664026A>G, in the CYP7A1 gene and three SNPs, 11:g.73256269T>C, 11:g.73256227A>C, and 11:g.73242290C>T, in HADHB. The single-SNP association analysis revealed significant associations (p value ≤ 0.0461) between the eight SNPs of CYP7A1 and HADHB genes and 305-day milk, fat and protein yields. Additionally, using Haploview 4.2, we found that the five SNPs of CYP7A1 formed two haplotype blocks and that the two SNPs of HADHB formed one haplotype block; notably, all three haplotype blocks were also significantly associated with milk, fat and protein yields (p value ≤ 0.0315). Further prediction of transcription factor binding sites (TFBSs) based on Jaspar software (version 2023) showed that the 14:g.24676921A>G, 14:g.24675708G>T, 11:g.73256269T>C, and 11:g.73256227A>C SNPs could alter the 5' terminal TFBS of the CYP7A1 and HADHB genes. The 14:g.24665961C>T SNP caused changes in the structural stability of the mRNA for the CYP7A1 gene. These alterations have the potential to influence gene expression and, consequently, the phenotype associated with milk-production traits. In summary, we have confirmed the genetic effects of CYP7A1 and HADHB genes on milk-production traits in dairy cattle and identified potential functional mutations that we suggest could be used for GS of dairy cattle and in-depth mechanistic studies of animals.

Phenotypic and genetic characterization of unexplored, potential cattle population of Madhya Pradesh

Bawri or Garri, a non-descript cattle population managed under an extensive system in Madhya Pradesh state of India, was identified and characterized both genetically and phenotypically to check whether or not it can be recognised as a breed. The cattle have white and gray colour and are medium sized with 122.5 ± 7.5 cm and 109.45 ± 0.39 cm height at withers in male and female, respectively. Double-digest restriction site associated DNA (ddRAD) sequencing was employed to identify ascertainment bias free SNPs representing the entire genome cost effectively; resulting in calling 1,156,650 high quality SNPs. Observed homozygosity was 0.76, indicating Bawri as a quite unique population. However, the inbreeding coefficient was 0.025, indicating lack of selection. SNPs found here can be used in GWAS and genetic evaluation programs. Considering the uniqueness of Bawri cattle, it can be registered as a breed for its better genetic management.

Polymorphism of ADAM12, DPP6 and PRKN genes and their associations with milk production traits in Holstein

Milk production traits as the most important economic traits of dairy cows, they directly reflect the benefits of breeding and the economic benefits of pasture. In this study, A disintegrin and metalloproteinase-12 (ADAM12), Parkinson's disease gene 2 (PRKN) and dipeptidyl peptidase-like protein subtype 6 (DPP6) polymorphism in 384 Chinese Holstein cows were detected by time-of-flight mass spectrometry and through statistical analysis using software such as Popgene 32, SAS 9.4 and Origin 2022, the relationship between single nucleotide polymorphisms (SNPs) of three genes with four milk production traits such as daily milk yield (DMY), milk fat percentage (MFP), milk protein percentage (MPP) and somatic cell score (SCS) was verified at molecular level. The results showed that four polymorphic loci (116,467,133, 116,604,487, 116,618,268 and 116,835,111) of DPP6 gene, two polymorphic loci (97,665,052 and 97,159,837) of PRKN gene and two polymorphic loci (45,542,714 and 45,553,888) of ADAM12 gene were detected. PRKN-97665052, DPP6-116467133, ADAM12-45553888, DPP6-116604487 and DPP6-116835111 were all in Hardy-Weinberg equilibrium state (p > .05). ADAM12-45542714, PRKN-97159837 and PRKN-97665052 were moderately polymorphic (0.25 ≤ PIC <0.50) in Holstein. It is evident that the selection potential and genetic variation of these five loci are relatively large, and the genetic richness is relatively high. The correlation analysis of different genotypes between these eight loci and milk production traits of Holstein showed that ADAM12-45542714 and DPP6-116835111 (p < .01) had an extremely significant effects on the DMY of Chinese Holstein in Ningxia, while PRKN-97665052 had an extremely significant effect on MFP (p < .01). The effect of PRKN-97665052 and DPP6-116467133 on MPP of Holstein were extremely significant (p < .01). DPP6-116618268 had an extremely significant effect on the SCS of Holstein in Ningxia (p < .01), and AA genotype individuals showed a higher SCS than GG genotype individuals; the other two loci (ADAM12-45553888 and DPP6-116604487) had no significant effects on milk production traits of Holstein (p > .05). In addition, through the joint analysis of DPP6, PRKN and ADAM12 gene loci, it was found that the interaction effect between the three gene loci could significantly affect the DMY, SCS (p < .01) and MPP (p < .05). In conclusion, several different loci of DPP6, PRKN and ADAM12 genes can affect the milk production traits of Holstein to different degrees. PRKN, DPP6 and ADAM12 genes can be used as potential candidate genes for milk production traits of Holstein for marker-assisted selection, providing theoretical basis for breeding of Holstein.

Selective Sweeps in Cattle Genomes in Response to the Influence of Urbanization and Environmental Contamination

A genomic study was conducted to identify the effects of urbanization and environmental contaminants with heavy metals on selection footprints in dairy cattle populations reared in the megacity of Bengaluru, South India. Dairy cattle reared along the rural-urban interface of Bengaluru with/without access to roughage from public lakeshores were selected. The genotyped animals were subjected to the cross-population-extended haplotype homozygosity (XP-EHH) methodology to infer selection sweeps caused by urbanization (rural, mixed, and urban) and environmental contamination with cadmium and lead. We postulated that social-ecological challenges contribute to mechanisms of natural selection. A number of selection sweeps were identified when comparing the genomes of cattle located in rural, mixed, or urban regions. The largest effects were identified on BTA21, displaying pronounced peaks for selection sweeps for all three urbanization levels (urban_vs_rural, urban_vs_mixed and rural_vs_mixed). Selection sweeps are located in chromosomal segments in close proximity to the genes lrand rab interactor 3 (RIN3), solute carrier family 24 member 4 (SLC24A4), tetraspanin 3 (TSPAN3), and proline-serine-threonine phosphatase interacting protein 1 (PSTPIP1). Functional enrichment analyses of the selection sweeps for all three comparisons revealed a number of gene ontology (GO) and KEGG terms, which were associated with reproduction, metabolism, and cell signaling-related functional mechanisms. Likewise, a number of the chromosomal segments under selection were observed when creating cattle groups according to cadmium and lead contaminations. Stronger and more intense positive selection sweeps were observed for the cadmium contaminated group, i.e., signals of selection on BTA 16 and BTA19 in close proximity to genes regulating the somatotropic axis (growth factor receptor bound protein 2 (GRB2) and cell ion exchange (chloride voltage-gated channel 6 (CLCN6)). A few novel, so far uncharacterized genes, mostly with effects on immune physiology, were identified. The lead contaminated group revealed sweeps which were annotated with genes involved in carcass traits (TNNC2, SLC12A5, and GABRA4), milk yield (HTR1D, SLCO3A1, TEK, and OPCML), reproduction (GABRA4), hypoxia/stress response (OPRD1 and KDR), cell adhesion (PCDHGC3), inflammatory response (ADORA2A), and immune defense mechanism (ALCAM). Thus, the findings from this study provide a deeper insight into the genomic regions under selection under the effects of urbanization and environmental contamination.

Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows

The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.

Genomic Regions Associated with Milk Composition and Fertility Traits in Spring-Calved Dairy Cows in New Zealand

The objective of this study was to identify genomic regions and genes that are associated with the milk composition and fertility traits of spring-calved dairy cows in New Zealand. Phenotypic data from the 2014–2015 and 2021–2022 calving seasons in two Massey University dairy herds were used. We identified 73 SNPs that were significantly associated with 58 potential candidate genes for milk composition and fertility traits. Four SNPs on chromosome 14 were highly significant for both fat and protein percentages, and the associated genes were DGAT1, SLC52A2, CPSF1, and MROH1. For fertility traits, significant associations were detected for intervals from the start of mating to first service, the start of mating to conception, first service to conception, calving to first service, and 6-wk submission, 6-wk in-calf, conception to first service in the first 3 weeks of the breeding season, and not in calf and 6-wk calving rates. Gene Ontology revealed 10 candidate genes (KCNH5, HS6ST3, GLS, ENSBTAG00000051479, STAT1, STAT4, GPD2, SH3PXD2A, EVA1C, and ARMH3) that were significantly associated with fertility traits. The biological functions of these genes are related to reducing the metabolic stress of cows and increasing insulin secretion during the mating period, early embryonic development, foetal growth, and maternal lipid metabolism during the pregnancy period.

Transcriptome Profile in Dairy Cows Resistant or Sensitive to Milk Fat Depression

Feeding linseed to dairy cows results in milk fat depression (MFD), but there is a wide range of sensitivity among cows. The objectives of this study were to identify target genes containing SNP that may play a key role in the regulation of milk fat synthesis in cows resistant or sensitive to MFD. Four cows were selected from a dairy farm after a switch from a control diet to a linseed-rich diet; two were resistant to MFD with a high milk fat content in the control (4.06%) and linseed-rich (3.90%) diets; and two were sensitive to MFD with the milk fat content decreasing after the change from the control (3.87%) to linseed-rich (2.52%) diets. Transcriptome and SNP discovery analyses were performed using RNA-sequencing technology. There was a large number of differentially expressed genes in the control (n = 1316) and linseed-rich (n = 1888) diets. Of these, 15 genes were detected as key gene regulators and harboring SNP in the linseed-rich diet. The selected genes MTOR, PDPK1, EREG, NOTCH1, ZNF217 and TGFB3 may form a network with a principal axis PI3K/Akt/MTOR/SREBP1 involved in milk fat synthesis and in the response to diets that induced MFD. These 15 genes are novel candidate genes to be involved in the resistance or sensitivity of dairy cows to milk fat depression.

Genome-wide association study revealed suggestive QTLs for production and reproduction traits in Indian Murrah buffalo

The present study was aimed to identify the genome-wide SNPs associated with production and reproduction traits in 96 Indian Murrah buffalo genotyped based on ddRAD approach using Genome-Wide Association Study (GWAS) along with phenotypes of contemporary animals using mixed linear model for production and reproduction traits. A total of 27,735 SNPs identified using ddRAD approach in 96 Indian Murrah buffaloes were used for GWAS. A total of 28 SNPs were found to be associated with production and reproductive traits. Among these, 14 SNPs were present in the intronic region of AK5, BACH2, DIRC2, ECPAS, MPZL1, MYO16, QRFPR, RASGRF1, SLC9A4, TANC1, and TRIM67 genes and one SNP in long non-coding region of LOC102414911. Out of these 28 SNPs, 9 SNPs were found to have pleiotropic effect over milk production traits and were present in chromosome number BBU 1, 2, 4, 6, 9, 10, 12, 19, and 20. SNPs in the intronic region of AK5, TRIM67 genes were found to be associated with milk production traits. Eleven and five SNPs in the intergenic region were associated with milk production and reproduction traits respectively. The above genomic information may be used for selection of Murrah animals for genetic improvement.

Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data

Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.

Efficiency of genotyping by sequencing in inferring genomic relatedness and molecular insights into fat tail selection in Tunisian sheep

In developing countries, the use of simple and cost-efficient molecular technology is crucial for genetic characterization of local animal resources and better development of conservation strategies. The genotyping by sequencing (GBS) technique, also called restriction enzyme- reduced representational sequencing, is an efficient, cost-effective method for simultaneous discovery and genotyping of many markers. In the present study, we applied a two-enzyme GBS protocol (PstI/MspI) to discover and genotype SNP markers among 197 Tunisian sheep samples. A total of 100 333 bi-allelic SNPs were discovered and genotyped with an SNP call rate of 0.69 and mean sample depth 3.33. The genomic relatedness between 183 samples grouped the samples perfectly to their populations and pointed out a high genetic relatedness of inbred subpopulation reflecting the current adopted reproductive strategies. The genome-wide association study contrasting fat vs. thin-tailed breeds detected 41 significant variants including a peak positioned on OAR20. We identified FOXC1, GMDS, VEGFA, OXCT1, VRTN and BMP2 as the most promising for sheep tail-type trait. The GBS data have been useful to assess the population structure and improve our understanding of the genomic architecture of distinctive characteristics shaped by selection pressure in local sheep breeds. This study successfully investigates a cost-efficient method to discover genotypes, assign populations and understand insights into sheep adaptation to arid area. GBS could be of potential utility in livestock species in developing/emerging countries.

Genomic diversity and relationship analyses of endangered German Black Pied cattle (DSN) to 68 other taurine breeds based on whole-genome sequencing

German Black Pied cattle (Deutsches Schwarzbuntes Niederungsrind, DSN) are an endangered dual-purpose cattle breed originating from the North Sea region. The population comprises about 2,500 cattle and is considered one of the ancestral populations of the modern Holstein breed. The current study aimed at defining the breeds closest related to DSN cattle, characterizing their genomic diversity and inbreeding. In addition, the detection of selection signatures between DSN and Holstein was a goal. Relationship analyses using fixation index (F_ST), phylogenetic, and admixture analyses were performed between DSN and 68 other breeds from the 1000 Bull Genomes Project. Nucleotide diversity, observed heterozygosity, and expected heterozygosity were calculated as metrics for genomic diversity. Inbreeding was measured as excess of homozygosity (F_Hom) and genomic inbreeding (F_RoH) through runs of homozygosity (RoHs). Region-wide F_ST and cross-population-extended haplotype homozygosity (XP-EHH) between DSN and Holstein were used to detect selection signatures between the two breeds, and RoH islands were used to detect selection signatures within DSN and Holstein. DSN showed a close genetic relationship with breeds from the Netherlands, Belgium, Northern Germany, and Scandinavia, such as Dutch Friesian Red, Dutch Improved Red, Belgian Red White Campine, Red White Dual Purpose, Modern Angler, Modern Danish Red, and Holstein. The nucleotide diversity in DSN (0.151%) was higher than in Holstein (0.147%) and other breeds, e.g., Norwegian Red (0.149%), Red White Dual Purpose (0.149%), Swedish Red (0.149%), Hereford (0.145%), Angus (0.143%), and Jersey (0.136%). The F_Hom and F_RoH values in DSN were among the lowest. Regions with high F_ST between DSN and Holstein, significant XP-EHH regions, and RoH islands detected in both breeds harbor candidate genes that were previously reported for milk, meat, fertility, production, and health traits, including one QTL detected in DSN for endoparasite infection resistance. The selection signatures between DSN and Holstein provide evidence of regions responsible for the dual-purpose properties of DSN and the milk type of Holstein. Despite the small population size, DSN has a high level of diversity and low inbreeding. F_ST supports its relatedness to breeds from the same geographic origin and provides information on potential gene pools that could be used to maintain diversity in DSN.

Analyses of circRNAs profiles of the lactating and nonlactating crops in pigeon (Columba livia)

Pigeon has the specific biological ability to produce pigeon milk (also known as crop milk) by its crop. Circular RNAs (circRNAs) are important noncoding RNAs acting as the sponges of miRNAs, but the molecular mechanism of circRNAs regulating crop milk production has not been reported in pigeon. We compared expression profiles of crops during lactating and nonlactating crops, and networks of competing endogenous RNAs (ceRNAs) were constructed. The results showed a total of 8,723 circRNAs were identified, and there were 770 differentially expressed circRNAs (DECs) between these two different periods of crops. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that the host genes of DECs were enriched in GnRH, MAPK, Insulin, Wnt, and AMPK signaling pathways. Furthermore, gga_circ_0000300 interacted with miR-92-2-5p, which targeted genes participating in lactation and milk composition synthesis. Gga_circ_0003018, gga_circ_0003019 and gga_circ_0003020 could bind with let-7c-5p regulating SOCS3 in crop milk production. These findings provide the circRNAs expression profiles and facilitate the analysis of molecular mechanism of crop milk production in pigeon.

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 second-parity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from -0.61 to -0.41 and from -0.55 to -0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.

Genome-wide association analysis of milk production, somatic cell score, and body conformation traits in Holstein cows

Milk production and body conformation traits are critical economic traits for dairy cows. To understand the basic genetic structure for those traits, a genome wide association study was performed on milk yield, milk fat yield, milk fat percentage, milk protein yield, milk protein percentage, somatic cell score, body form composite index, daily capacity composite index, feed, and leg conformation traits, based on the Illumina Bovine HD100k BeadChip. A total of 57, 12 and 26 SNPs were found to be related to the milk production, somatic cell score and body conformation traits in the Holstein cattle. Genes with pleiotropic effect were also found in this study. Seven significant SNPs were associated with multi-traits and were located on the PLEC, PLEKHA5, TONSL, PTGER4, and LCORL genes. In addition, some important candidate genes, like GPAT3, CEBPB, AGO2, SLC37A1, and FNDC3B, were found to participate in fat metabolism or mammary gland development. These results can be used as candidate genes for milk production, somatic cell score, and body conformation traits of Holstein cows, and are helpful for further gene function analysis to improve milk production and quality.

Genome-wide association and genotype by environment interactions for growth traits in U.S. Red Angus cattle

Background

Genotypic information produced from single nucleotide polymorphism (SNP) arrays has routinely been used to identify genomic regions associated with complex traits in beef and dairy cattle. Herein, we assembled a dataset consisting of 15,815 Red Angus beef cattle distributed across the continental U.S. and a union set of 836,118 imputed SNPs to conduct genome-wide association analyses (GWAA) for growth traits using univariate linear mixed models (LMM); including birth weight, weaning weight, and yearling weight. Genomic relationship matrix heritability estimates were produced for all growth traits, and genotype-by-environment (GxE) interactions were investigated.

Results

Moderate to high heritabilities with small standard errors were estimated for birth weight (0.51 ± 0.01), weaning weight (0.25 ± 0.01), and yearling weight (0.42 ± 0.01). GWAA revealed 12 pleiotropic QTL (BTA6, BTA14, BTA20) influencing Red Angus birth weight, weaning weight, and yearling weight which met a nominal significance threshold (P ≤ 1e-05) for polygenic traits using 836K imputed SNPs. Moreover, positional candidate genes associated with Red Angus growth traits in this study (i.e., LCORL, LOC782905, NCAPG, HERC6, FAM184B, SLIT2, MMRN1, KCNIP4, CCSER1, GRID2, ARRDC3, PLAG1, IMPAD1, NSMAF, PENK, LOC112449660, MOS, SH3PXD2B, STC2, CPEB4) were also previously associated with feed efficiency, growth, and carcass traits in beef cattle. Collectively, 14 significant GxE interactions were also detected, but were less consistent among the investigated traits at a nominal significance threshold (P ≤ 1e-05); with one pleiotropic GxE interaction detected on BTA28 (24 Mb) for Red Angus weaning weight and yearling weight.

Conclusions

Sixteen well-supported QTL regions detected from the GWAA and GxE GWAA for growth traits (birth weight, weaning weight, yearling weight) in U.S. Red Angus cattle were found to be pleiotropic. Twelve of these pleiotropic QTL were also identified in previous studies focusing on feed efficiency and growth traits in multiple beef breeds and/or their composites. In agreement with other beef cattle GxE studies our results implicate the role of vasodilation, metabolism, and the nervous system in the genetic sensitivity to environmental stress.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08667-6.

Weighted Single-Step Genome-Wide Association Study Uncovers Known and Novel Candidate Genomic Regions for Milk Production Traits and Somatic Cell Score in Valle del Belice Dairy Sheep

Simple Summary

Milk production is the most economically crucial dairy sheep trait and constitutes the major genetic enhancement purpose via selective breeding. Also, mastitis is one of the most frequently encountered diseases, having a significant impact on animal welfare, milk yield, and quality. The aim of this study was to identify genomic region(s) associated with the milk production traits and somatic cell score (SCS) in Valle del Belice sheep using single-step genome-wide association (ssGWA) and genotyping data from medium density SNP panels. We identified several genomic regions (OAR1, OAR2, OAR3, OAR4, OAR6, OAR9, and OAR25) and candidate genes implicated in milk production traits and SCS. Our findings offer new insights into the genetic basis of milk production traits and SCS in dairy sheep.

Abstract

The objective of this study was to uncover genomic regions explaining a substantial proportion of the genetic variance in milk production traits and somatic cell score in a Valle del Belice dairy sheep. Weighted single-step genome-wide association studies (WssGWAS) were conducted for milk yield (MY), fat yield (FY), fat percentage (FAT%), protein yield (PY), protein percentage (PROT%), and somatic cell score (SCS). In addition, our aim was also to identify candidate genes within genomic regions that explained the highest proportions of genetic variance. Overall, the full pedigree consists of 5534 animals, of which 1813 ewes had milk data (15,008 records), and 481 ewes were genotyped with a 50 K single nucleotide polymorphism (SNP) array. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. We considered the top 10 genomic regions in terms of their explained genomic variants as candidate window regions for each trait. The results showed that top ranked genomic windows (1 Mb windows) explained 3.49, 4.04, 5.37, 4.09, 3.80, and 5.24% of the genetic variances for MY, FY, FAT%, PY, PROT%, and total SCS, respectively. Among the candidate genes found, some known associations were confirmed, while several novel candidate genes were also revealed, including PPARGC1A, LYPLA1, LEP, and MYH9 for MY; CACNA1C, PTPN1, ROBO2, CHRM3, and ERCC6 for FY and FAT%; PCSK5 and ANGPT1 for PY and PROT%; and IL26, IFNG, PEX26, NEGR1, LAP3, and MED28 for SCS. These findings increase our understanding of the genetic architecture of six examined traits and provide guidance for subsequent genetic improvement through genome selection.

Genome-wide investigations reveal the population structure and selection signatures of Nigerian cattle adaptation in the sub-Saharan tropics

Background

Cattle are considered to be the most desirable livestock by small scale farmers. In Africa, although comprehensive genomic studies have been carried out on cattle, the genetic variations in indigenous cattle from Nigeria have not been fully explored. In this study, genome-wide analysis based on genotyping-by-sequencing (GBS) of 193 Nigerian cattle was used to reveal new insights on the history of West African cattle and their adaptation to the tropical African environment, particularly in sub-Saharan region. 

Results

The GBS data were evaluated against whole-genome sequencing (WGS) data and high rate of variant concordance between the two platforms was evident with high correlated genetic distance matrices genotyped by both methods suggestive of the reliability of GBS applicability in population genetics. The genetic structure of Nigerian cattle was observed to be homogenous and unique from other African cattle populations. Selection analysis for the genomic regions harboring imprints of adaptation revealed genes associated with immune responses, growth and reproduction, efficiency of feeds utilization, and heat tolerance. Our findings depict potential convergent adaptation between African cattle, dogs and humans with adaptive genes SPRY2 and ITGB1BP1 possibly involved in common physiological activities.

Conclusion

The study presents unique genetic patterns of Nigerian cattle which provide new insights on the history of cattle in West Africa based on their population structure and the possibility of parallel adaptation between African cattle, dogs and humans in Africa which require further investigations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08512-w.

Genome-wide detection of selective signals for fecundity traits in goats (Capra hircus)

Fecundity in livestock is an economically important complex quantitative trait that is influenced by both genetics and the environment. However, the underlying genetic mechanism of reproductive performance in goats has not been well investigated. To investigate the genomic basis of fecundity in goats, genomic sequencing data of the Jining grey goat (a high prolificacy breed in China) were collected, as well as data for other commonly available goat breeds, and a mass of genomic variants were generated after variation calling. We screened the Jining grey goat (20 individuals) using a selective sweep with the Asian wild goat population (5 individuals), and potential candidate genes were proposed, such as STIM1, ESR1, LRRC14B and SLC9A3. Among, STIM1 is a most promising one associated with high reproductive capacity. When compared to Chinese domestic goats with low fecundity (17 individuals), the genes including MLLT10, SPIRE2, TCF25, ZNF276 and FANCA were screened, and the SPIRE2 gene was thought to be associated with fecundity traits. Meanwhile, the functional enrichment of these candidate genes revealed that they were involved in biological processes of mammary gland morphogenesis, uterus development, gastrulation, mesoderm morphogenesis and formation, and blood vessel development, which might undergo natural or artificial selection during reproductive trait formation in goats. Thus, our findings could enrich the genetic basis of reproductive trait selection during goat domestication, which may serve to improve goat breeding practices.

Evaluation of candidate genotype of GH gene associated with growth, production and reproduction traits in Dairy Cows

Growth hormone (GH) is a major regulator of postnatal growth and metabolism in mammals and plays a critical role in growth, production and fertility in cattle. The present study was conducted in dairy cattle to find the association of g.48769565 C>T mutation with growth, production and reproduction traits in Sahiwal and Hardhenu cattle. PCR-RFLP was performed to genotype g.48769565 C>T mutation using the MspI restriction enzyme in our resource cattle population. In Hardhenu cattle, the frequencies of C and T alleles were 0.59 and 0.41 respectively while genotypic frequencies were 0.06, 0.36 and 0.58 for CC,CT and TT respectively. The frequencies of the C and T allele were 0.24 and 0.76 respectively in Sahiwal cattle and it was observed that highest frequency was forTT genotype (0.58) and lowest for CC genotype (0.06). Chi-square analysis showed that g.48769565C>T SNP loci did not meet with the Hardy-Weinberg equilibrium (p< 0.01) in Sahiwal cattle. From the least-squares analysis, it was observed that CC genotype was significantly associated with total Milk Yield (TMY), 300 days milk yield (300D MY), lactation length (LL), Dry period (DP) and Artificial insemination (AI)/conception (p<0.05). We also observed a significant association (p<0.05) of genotype CT with 3-month calves body weight. Cows with TT genotype revealed comparatively revealed favourable service period (SP) and calving interval (CI) in both Hardhenu and Sahiwal. These observed differences in their allelic and genotypic frequencies in association with the traitsunderlying production and fertility can be utilized for genetic improvement in dairy cattle.

Genetic Parameter Estimation and Genome-Wide Association Study-Based Loci Identification of Milk-Related Traits in Chinese Holstein

Accurately estimating the genetic parameters and revealing more genetic variants underlying milk production and quality are conducive to the genetic improvement of dairy cows. In this study, we estimate the genetic parameters of five milk-related traits of cows-namely, milk yield (MY), milk fat percentage (MFP), milk fat yield (MFY), milk protein percentage (MPP), and milk protein yield (MPY)-based on a random regression test-day model. A total of 95,375 test-day records of 9,834 cows in the lower reaches of the Yangtze River were used for the estimation. In addition, genome-wide association studies (GWASs) for these traits were conducted, based on adjusted phenotypes. The heritability, as well as the standard errors, of MY, MFP, MFY, MPP, and MPY during lactation ranged from 0.22 ± 0.02 to 0.31 ± 0.04, 0.06 ± 0.02 to 0.15 ± 0.03, 0.09 ± 0.02 to 0.28 ± 0.04, 0.07 ± 0.01 to 0.16 ± 0.03, and 0.14 ± 0.02 to 0.27 ± 0.03, respectively, and the genetic correlations between different days in milk (DIM) within lactations decreased as the time interval increased. Two, six, four, six, and three single nucleotide polymorphisms (SNPs) were detected, which explained 5.44, 12.39, 8.89, 10.65, and 7.09% of the phenotypic variation in MY, MFP, MFY, MPP, and MPY, respectively. Ten Kyoto Encyclopedia of Genes and Genomes pathways and 25 Gene Ontology terms were enriched by analyzing the nearest genes and genes within 200 kb of the detected SNPs. Moreover, 17 genes in the enrichment results that may play roles in milk production and quality were selected as candidates, including CAMK2G, WNT3A, WNT9A, PLCB4, SMAD9, PLA2G4A, ARF1, OPLAH, MGST1, CLIP1, DGAT1, PRMT6, VPS28, HSF1, MAF1, TMEM98, and F7. We hope that this study will provide useful information for in-depth understanding of the genetic architecture of milk production and quality traits, as well as contribute to the genomic selection work of dairy cows in the lower reaches of the Yangtze River.

Comparison of Genotype Imputation for SNP Array and Low-Coverage Whole-Genome Sequencing Data

Genotype imputation is the term used to describe the process of inferring unobserved genotypes in a sample of individuals. It is a key step prior to a genome-wide association study (GWAS) or genomic prediction. The imputation accuracy will directly influence the results from subsequent analyses. In this simulation-based study, we investigate the accuracy of genotype imputation in relation to some factors characterizing SNP chip or low-coverage whole-genome sequencing (LCWGS) data. The factors included the imputation reference population size, the proportion of target markers /SNP density, the genetic relationship (distance) between the target population and the reference population, and the imputation method. Simulations of genotypes were based on coalescence theory accounting for the demographic history of pigs. A population of simulated founders diverged to produce four separate but related populations of descendants. The genomic data of 20,000 individuals were simulated for a 10-Mb chromosome fragment. Our results showed that the proportion of target markers or SNP density was the most critical factor affecting imputation accuracy under all imputation situations. Compared with Minimac4, Beagle5.1 reproduced higher-accuracy imputed data in most cases, more notably when imputing from the LCWGS data. Compared with SNP chip data, LCWGS provided more accurate genotype imputation. Our findings provided a relatively comprehensive insight into the accuracy of genotype imputation in a realistic population of domestic animals.

Detection of candidate genes affecting milk production traits in sheep using whole-genome sequencing analysis

BACKGROUND

Artificial and natural selection for important economic traits and genetic adaptation of the populations to specific environments have led to the changes on the sheep genome. Recent advances in genome sequencing methods have made it possible to use comparative genomics tools to identify genes under selection for traits of economic interest in domestic animals.

OBJECTIVES

In this study, we compared the genomes of Assaf and Awassi sheep breeds with those of the Cambridge, Romanov and British du cher sheep breeds to explore positive selection signatures for milk traits using nucleotide diversity (Pi) and FST statistical methods.

METHODS

Genome sequences from fourteen sheep with a mean sequence depth of 9.32X per sample were analysed, and a total of 23 million single nucleotide polymorphisms (SNPs) were called and applied for this study. Genomic clustering of breeds was identified using ADMIXTURE software. The FST and Pi values for each SNP were computed between population A (Assaf and Awassi) and population B (Cambridge, British du cher, and Romanov).

RESULTS

The results of the PCA grouped two classes for these five dairy sheep breeds. The selection signatures analysis displayed 735 and 515 genes from FST and nucleotide diversity (Pi) statistical methods, respectively. Among all these, 12 genes were shared between the two approaches. The most conspicuous genes were related to milk traits, including ST3GAL1 (the synthesis of oligosacáridos), CSN1S1 (milk protein), CSN2 (milk protein), OSBPL8 (fatty acid traits), SLC35A3 (milk fat and protein percentage), VPS13B (total milk production, fat yield, and protein yield), DPY19L1 (peak yield), CCDC152 (lactation persistency and somatic cell count), NT5DC1 (lactation persistency), P4HTM (test day protein), CYTH4 (FAT Production) and METRNL (somatic cell), U1 (milk traits), U6 (milk traits) and 5S_RRNA (milk traits).

CONCLUSIONS

The findings provide new insight into the genetic basis of sheep milk properties and can play a role in designing sheep breeding programs incorporating genomic information.

Whole Genome Methylation Analysis Reveals Role of DNA Methylation in Cow's Ileal and Ileal Lymph Node Responses to Mycobacterium avium subsp. paratuberculosis Infection

Johne's Disease (JD), caused by Mycobacterium avium subsp paratuberculosis (MAP), is an incurable disease of ruminants and other animal species and is characterized by an imbalance of gut immunity. The role of MAP infection on the epigenetic modeling of gut immunity during the progression of JD is still unknown. This study investigated the DNA methylation patterns in ileal (IL) and ileal lymph node (ILLN) tissues from cows diagnosed with persistent subclinical MAP infection over a one to 4 years period. DNA samples from IL and ILLN tissues from cows negative (MAPneg) (n = 3) or positive for MAP infection (MAPinf) (n = 4) were subjected to whole genome bisulfite sequencing. A total of 11,263 and 62,459 differentially methylated cytosines (DMCs), and 1259 and 8086 differentially methylated regions (DMRs) (FDR<0.1) were found between MAPinf and MAPneg IL and ILLN tissues, respectively. The DMRs were found on 394 genes (denoted DMR genes) in the IL and on 1305 genes in the ILLN. DMR genes with hypermethylated promoters/5'UTR [3 (IL) and 88 (ILLN)] or hypomethylated promoters/5'UTR [10 (IL) and 25 (ILLN)] and having multiple functions including response to stimulus/immune response (BLK, BTC, CCL21, AVPR1A, CHRNG, GABRA4, TDGF1), cellular processes (H2AC20, TEX101, GLA, NCKAP5L, RBM27, SLC18A1, H2AC20BARHL2, NLGN3, SUV39H1, GABRA4, PPA1, UBE2D2) and metabolic processes (GSTO2, H2AC20, SUV39H1, PPA1, UBE2D2) are potential DNA methylation candidate genes of MAP infection. The ILLN DMR genes were enriched for more biological process (BP) gene ontology (GO) terms (n = 374), most of which were related to cellular processes (27.6%), biological regulation (16.6%), metabolic processes (15.4%) and response to stimulus/immune response (8.2%) compared to 75 BP GO terms (related to cellular processes, metabolic processes and transport, and system development) enriched for IL DMR genes. ILLN DMR genes were enriched for more pathways (n = 47) including 13 disease pathways compared with 36 enriched pathways, including 7 disease/immune pathways for IL DMR genes. In conclusion, the results show tissue specific responses to MAP infection with more epigenetic changes (DMCs and DMRs) in the ILLN than in the IL tissue, suggesting that the ILLN and immune processes were more responsive to regulation by methylation of DNA relative to IL tissue. Our data is the first to demonstrate a potential role for DNA methylation in the pathogenesis of MAP infection in dairy cattle.

Whole Genome DNA Methylation Variations in Mammary Gland Tissues from Holstein Cattle Producing Milk with Various Fat and Protein Contents

Milk fat and protein contents are among key elements of milk quality, and they are attracting more attention in response to consumers' demand for high-quality dairy products. To investigate the potential regulatory roles of DNA methylation underlying milk component yield, whole genome bisulfite sequencing was employed to profile the global DNA methylation patterns of mammary gland tissues from 17 Canada Holstein cows with various milk fat and protein contents. A total of 706, 2420 and 1645 differentially methylated CpG sites (DMCs) were found between high vs. low milk fat (HMF vs. LMF), high vs. low milk protein (HMP vs. LMP), and high vs. low milk fat and protein (HMFP vs. LMFP) groups, respectively (q value < 0.1). Twenty-seven, 56 and 67 genes harboring DMCs in gene regions (denoted DMC genes) were identified for HMF vs. LMF, HMP vs. LMP and HMFP vs. LMFP, respectively. DMC genes from HMP vs. LMP and HMFP vs. LMFP comparisons were significantly overrepresented in GO terms related to aerobic electron transport chain and/or mitochondrial ATP (adenosine triphosphate) synthesis coupled electron transport. A total of 83 (HMF vs. LMF), 708 (HMP vs. LMP) and 408 (HMFP vs. LMFP) DMCs were co-located with 87, 147 and 158 quantitative trait loci (QTL) for milk component and yield traits, respectively. In conclusion, the identified methylation changes are potentially involved in the regulation of milk fat and protein yields, as well as the variation in reported co-located QTLs.

Genome-wide association study on milk production and somatic cell score for Thai dairy cattle using weighted single-step approach with random regression test-day model

Genome-wide association studies are a powerful tool to identify genomic regions and variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. The objectives of this study were to identify genomic regions as well as genes and pathways associated with the first-lactation milk, fat, protein, and total solid yields; fat, protein, and total solid percentage; and somatic cell score (SCS) in a Thai dairy cattle population. Effects of SNPs were estimated by a weighted single-step GWAS, which back-solved the genomic breeding values predicted using single-step genomic BLUP (ssGBLUP) fitting a single-trait random regression test-day model. Genomic regions that explained at least 0.5% of the total genetic variance were selected for further analyses of candidate genes. Despite the small number of genotyped animals, genomic predictions led to an improvement in the accuracy over the traditional BLUP. Genomic predictions using weighted ssGBLUP were slightly better than the ssGBLUP. The genomic regions associated with milk production traits contained 210 candidate genes on 19 chromosomes [Bos taurus autosome (BTA) 1 to 7, 9, 11 to 16, 20 to 21, 26 to 27 and 29], whereas 21 candidate genes on 3 chromosomes (BTA 11, 16, and 21) were associated with SCS. Many genomic regions explained a small fraction of the genetic variance, indicating polygenic inheritance of the studied traits. Several candidate genes coincided with previous reports for milk production traits in Holstein cattle, especially a large region of genes on BTA14. We identified 141 and 5 novel genes related to milk production and SCS, respectively. These novel genes were also found to be functionally related to heat tolerance (e.g., SLC45A2, IRAG1, and LOC101902172), longevity (e.g., SYT10 and LOC101903327), and fertility (e.g., PAG1). These findings may be attributed to indirect selection in our population. Identified biological networks including intracellular cell transportation and protein catabolism implicate milk production, whereas the immunological pathways such as lymphocyte activation are closely related to SCS. Further studies are required to validate our findings before exploiting them in genomic selection.

Relationship between polymorphism within Peptidoglycan Recognition Protein 1 gene (PGLYRP1) and somatic cell counts in milk of Holstein cows

Bovine peptidoglycan recognition protein 1 (PGLYRP1) is an important receptor that binds to murein peptidoglycans (PGN) of Gram-positive and Gram-negative bacteria and is, therefore, involved in innate immunity. The SNP T>C rs68268284 located in the 1st exon of the PGLYRP1 gene was identified by the PCR-RFLP method in a population of 319 Holstein cows. Somatic cell count (SCC) was measured 7–10 times in each of three completed lactations to investigate whether the PGLYRP1 polymorphism is associated with SCC. Using the GLM model, it was found that cows with the TT genotype showed significantly lower somatic cell counts than those with the CC genotype during the first lactation (P = 0.023). Moreover, during lactations 1–2 and 1–3, cows with the TT genotype reveal significantly lower SCC than CT heterozygotes, at P = 0.025 and P = 0.006, respectively. Computer-aided analysis showed that rs68268284 polymorphism could modify the PGLYRP1 functions because the mutated residue is located in a domain that is important for the binding of other molecules.

Evolutionary Analysis of OAT Gene Family in River and Swamp Buffalo: Potential Role of SLCO3A1 Gene in Milk Performance

The organic anion transporter (OAT) family is the subfamily of the solute carrier (SLC) superfamily, which plays a vital role in regulating essential nutrients in milk. However, little is known about the members’ identification, evolutionary basis, and function characteristics of OAT genes associated with milk performance in buffalo. Comparative genomic analyses were performed to identify the potential role of buffalo OAT genes in milk performance in this study. The results showed that a total of 10 and 7 OAT genes were identified in river buffalo and swamp buffalo, respectively. These sequences clustered into three groups based on their phylogenetic relationship and had similar motif patterns and gene structures in the same groups. Moreover, the river-specific expansions and homologous loss of OAT genes occurred in the two buffalo subspecies during the evolutionary process. Notably, the duplicated SLCO3A1 gene specific to river buffalo showed higher expression level in mammary gland tissue than that of swamp buffalo. These findings highlight some promising candidate genes that could be potentially utilized to accelerate the genetic progress in buffalo breeding programs. However, the identified candidate genes require further validation in a larger cohort for use in the genomic selection of buffalo for milk production.

Genome-Wide Scanning for Signatures of Selection Revealed the Putative Genomic Regions and Candidate Genes Controlling Milk Composition and Coat Color Traits in Sahiwal Cattle

Background

In the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip.

Result

De-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected p-value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (PDGFRA, KIT, and KDR), facial pigmentation (LEF), milk fat percent (MAP3K1, HADH, CYP2U1, and SGMS2), sperm membrane integrity (OSTC), lactation persistency (MRPS30, NNT, CCL28, HMGCS1, NIM1K, ZNF131, and CCDC152), milk yield (GHR and ZNF469), reproduction (NKX2-1 and DENND1A), and bovine tuberculosis susceptibility (RNF144B and PAPSS1). Further analysis of candidate gene prioritization identified four hub genes, viz., KIT, KDR, MAP3K1, and LEF, which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent.

Conclusion

The key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle.

Response to Oxidative Burst-Induced Hypoxia Is Associated With Macrophage Inflammatory Profiles as Revealed by Cellular Genome-Wide Association

Background

In mammalian species, hypoxia is a prominent feature of inflammation. The role of hypoxia in regulating macrophage responses via alteration in metabolic pathways is well established. Recently, oxidative burst-induced hypoxia has been shown in murine macrophages after phagocytosis. Despite the available detailed information on the regulation of macrophage function at transcriptomic and epigenomic levels, the association of genetic polymorphism and macrophage function has been less explored. Previously, we have shown that host genetics controls approximately 80% of the variation in an oxidative burst as measured by nitric oxide (NO^-). Further studies revealed two clusters of transcription factors (hypoxia-related and inflammatory-related) are under the genetic control that shapes macrophages’ pro-inflammatory characteristics.

Material and Methods

In the current study, the association between 43,066 autosomal Single Nucleic Polymorphism (SNPs) and the ability of MDMs in production of NO^- in response to E. coli was evaluated in 58 Holstein cows. The positional candidate genes near significant SNPs were selected to perform functional analysis. In addition, the interaction between the positional candidate genes and differentially expressed genes from our previous study was investigated.

Results

Sixty SNPs on 22 chromosomes of the bovine genome were found to be significantly associated with NO^- production of macrophages. The functional genomic analysis showed a significant interaction between positional candidate genes and mitochondria-related differentially expressed genes from the previous study. Further examination showed 7 SNPs located in the vicinity of genes with roles in response to hypoxia, shaping approximately 73% of the observed individual variation in NO^- production by MDM. Regarding the normoxic condition of macrophage culture in this study, it was hypothesized that oxidative burst is responsible for causing hypoxia at the cellular level.

Conclusion

The results suggest that the genetic polymorphism via regulation of response to hypoxia is a candidate step that perhaps shapes macrophage functional characteristics in the pathway of phagocytosis leading to oxidative burst, hypoxia, cellular response to hypoxia and finally the pro-inflammatory responses. Since all cells in one individual carry the same alleles, the effect of genetic predisposition of sensitivity to hypoxia will likely be notable on the clinical outcome to a broad range of host-pathogen interactions.

Identification of genes affecting milk fat and fatty acid composition in Vrindavani crossbred cattle using 50 K SNP-Chip

The aim of this study was to identify candidate genes associated with milk fat per cent and fatty acid (FA) composition in Vrindavani cattle using the Illumina 50 K single-nucleotide polymorphism (SNP) array. After quality control, a total of 41,427 informative and high-quality SNPs were used for a genome-wide association study (GWAS) for milk fat percentage and 16 different types of fatty acids. Lactation stage, parity, test day milk yield, and proportion of exotic inheritance were included as fixed effects in the GWAS model. A total of 67 genome-wide significant (P < 1.20 × 10^-06) SNPs and 176 suggestive significant (P < 2.41 × 10^-05) SNPs were identified. Out of these, 15 SNPs were associated with more than one trait. The strongest associations were found on BTA14 for milk fat percentage and on BTA2 and BTA16 for polyunsaturated fatty acids. Several significant SNPs were identified close to or within the genes ELOVL6, FABP4, PMP2, PLIN1, MFGE8, GHRL2, and LDLRAD3 which are known to be associated with fat percentage and FA composition in dairy cattle breeds. This study is a step forward to better characterize the molecular mechanisms of phenotypic variation in milk fatty acids in a taurine-indicine composite cattle breed reared in tropical environments.

The climatic and genetic heritage of Italian goat breeds with genomic SNP data

Local adaptation of animals to the environment can abruptly become a burden when faced with rapid climatic changes such as those foreseen for the Italian peninsula over the next 70 years. Our study investigates the genetic structure of the Italian goat populations and links it with the environment and how genetics might evolve over the next 50 years. We used one of the largest national datasets including > 1000 goats from 33 populations across the Italian peninsula collected by the Italian Goat Consortium and genotyped with over 50 k markers. Our results showed that Italian goats can be discriminated in three groups reflective of the Italian geography and its geo-political situation preceding the country unification around two centuries ago. We leveraged the remarkable genetic and geographical diversity of the Italian goat populations and performed landscape genomics analysis to disentangle the relationship between genotype and environment, finding 64 SNPs intercepting genomic regions linked to growth, circadian rhythm, fertility, and inflammatory response. Lastly, we calculated the hypothetical future genotypic frequencies of the most relevant SNPs identified through landscape genomics to evaluate their long-term effect on the genetic structure of the Italian goat populations. Our results provide an insight into the past and the future of the Italian local goat populations, helping the institutions in defining new conservation strategy plans that could preserve their diversity and their link to local realities challenged by climate change.

Identification of Genomic Regions Associated with Concentrations of Milk Fat, Protein, Urea and Efficiency of Crude Protein Utilization in Grazing Dairy Cows

The objective of this study was to identify genomic regions associated with milk fat percentage (FP), crude protein percentage (CPP), urea concentration (MU) and efficiency of crude protein utilization (ECPU: ratio between crude protein yield in milk and dietary crude protein intake) using grazing, mixed-breed, dairy cows in New Zealand. Phenotypes from 634 Holstein Friesian, Jersey or crossbred cows were obtained from two herds at Massey University. A subset of 490 of these cows was genotyped using Bovine Illumina 50K SNP-chips. Two genome-wise association approaches were used, a single-locus model fitted to data from 490 cows and a single-step Bayes C model fitted to data from all 634 cows. The single-locus analysis was performed with the Efficient Mixed-Model Association eXpedited model as implemented in the SVS package. Single nucleotide polymorphisms (SNPs) with genome-wide association p-values ≤ 1.11 × 10⁻⁶ were considered as putative quantitative trait loci (QTL). The Bayes C analysis was performed with the JWAS package and 1-Mb genomic windows containing SNPs that explained > 0.37% of the genetic variance were considered as putative QTL. Candidate genes within 100 kb from the identified SNPs in single-locus GWAS or the 1-Mb windows were identified using gene ontology, as implemented in the Ensembl Genome Browser. The genes detected in association with FP (MGST1, DGAT1, CEBPD, SLC52A2, GPAT4, and ACOX3) and CPP (DGAT1, CSN1S1, GOSR2, HERC6, and IGF1R) were identified as candidates. Gene ontology revealed six novel candidate genes (GMDS, E2F7, SIAH1, SLC24A4, LGMN, and ASS1) significantly associated with MU whose functions were in protein catabolism, urea cycle, ion transportation and N excretion. One novel candidate gene was identified in association with ECPU (MAP3K1) that is involved in post-transcriptional modification of proteins. The findings should be validated using a larger population of New Zealand grazing dairy cows.

Identification of SNPs Associated with Somatic Cell Score in Candidate Genes in Italian Holstein Friesian Bulls

Mastitis is an infectious disease affecting the mammary gland, leading to inflammatory reactions and to heavy economic losses due to milk production decrease. One possible way to tackle the antimicrobial resistance issue stemming from antimicrobial therapy is to select animals with a genetic resistance to this disease. Therefore, aim of this study was to analyze the genetic variability of the SNPs found in candidate genes related to mastitis resistance in Holstein Friesian bulls. Target regions were amplified, sequenced by Next-Generation Sequencing technology on the Illumina® MiSeq, and then analyzed to find correlation with mastitis related phenotypes in 95 Italian Holstein bulls chosen with the aid of a selective genotyping approach. On a total of 557 detected mutations, 61 showed different genotype distribution in the tails of the deregressed EBVs for SCS and 15 were identified as significantly associated with the phenotype using two different approaches. The significant SNPs were identified in intergenic or intronic regions of six genes, known to be key components in the immune system (namely CXCR1, DCK, NOD2, MBL2, MBL1 and M-SAA3.2). These SNPs could be considered as candidates for a future genetic selection for mastitis resistance, although further studies are required to assess their presence in other dairy cattle breeds and their possible negative correlation with other traits.

Brown Fat-Activating Lipokine 12,13-diHOME in Human Milk Is Associated With Infant Adiposity

CONTEXT

Little is known about the specific breastmilk components responsible for protective effects on infant obesity. Whether 12,13-dihydroxy-9Z-octadecenoic acid (12,13-diHOME), an oxidized linoleic acid metabolite and activator of brown fat metabolism, is present in human milk, or linked to infant adiposity, is unknown.

OBJECTIVE

To examine associations between concentrations of 12,13-diHOME in human milk and infant adiposity.

DESIGN

Prospective cohort study from 2015 to 2019, following participants from birth to 6 months of age.

SETTING

Academic medical centers.

PARTICIPANTS

Volunteer sample of 58 exclusively breastfeeding mother-infant pairs; exclusion criteria included smoking, gestational diabetes, and health conditions with the potential to influence maternal or infant weight gain.

MAIN OUTCOME MEASURES

Infant anthropometric measures including weight, length, body mass index (BMI), and body composition at birth and at 1, 3, and 6 months postpartum.

RESULTS

We report for the first time that 12,13-diHOME is present in human milk. Higher milk 12,13-diHOME level was associated with increased weight-for-length Z-score at birth (β = 0.5742, P = 0.0008), lower infant fat mass at 1 month (P = 0.021), and reduced gain in BMI Z-score from 0 to 6 months (β = -0.3997, P = 0.025). We observed similar associations between infant adiposity and milk abundance of related oxidized linoleic acid metabolites 12,13-Epoxy-9(Z)-octadecenoic acid (12,13-epOME) and 9,10-Dihydroxy-12-octadecenoic acid (9,10-diHOME), and metabolites linked to thermogenesis including succinate and lyso-phosphatidylglycerol 18:0. Milk abundance of 12,13-diHOME was not associated with maternal BMI, but was positively associated with maternal height, milk glucose concentration, and was significantly increased after a bout of moderate exercise.

CONCLUSIONS

We report novel associations between milk abundance of 12,13-diHOME and adiposity during infancy.

Unravelling the Role of Rumen Microbial Communities, Genes, and Activities on Milk Fatty Acid Profile Using a Combination of Omics Approaches

Milk products are an important component of human diets, with beneficial effects for human health, but also one of the major sources of nutritionally undesirable saturated fatty acids (SFA). Recent discoveries showing the importance of the rumen microbiome on dairy cattle health, metabolism and performance highlight that milk composition, and potentially milk SFA content, may also be associated with microorganisms, their genes and their activities. Understanding these mechanisms can be used for the development of cost-effective strategies for the production of milk with less SFA. This work aimed to compare the rumen microbiome between cows producing milk with contrasting FA profile and identify potentially responsible metabolic-related microbial mechanisms. Forty eight Holstein dairy cows were fed the same total mixed ration under the same housing conditions. Milk and rumen fluid samples were collected from all cows for the analysis of fatty acid profiles (by gas chromatography), the abundances of rumen microbiome communities and genes (by whole-genome-shotgun metagenomics), and rumen metabolome (using 500 MHz nuclear magnetic resonance). The following groups: (i) 24 High-SFA (66.9-74.4% total FA) vs. 24 Low-SFA (60.2-66.6%% total FA) cows, and (ii) 8 extreme High-SFA (69.9-74.4% total FA) vs. 8 extreme Low-SFA (60.2-64.0% total FA) were compared. Rumen of cows producing milk with more SFA were characterized by higher abundances of the lactic acid bacteria Lactobacillus, Leuconostoc, and Weissella, the acetogenic Proteobacteria Acetobacter and Kozakia, Mycobacterium, two fungi (Cutaneotrichosporon and Cyphellophora), and at a lesser extent Methanobrevibacter and the protist Nannochloropsis. Cows carrying genes correlated with milk FA also had higher concentrations of butyrate, propionate and tyrosine and lower concentrations of xanthine and hypoxanthine in the rumen. Abundances of rumen microbial genes were able to explain between 76 and 94% on the variation of the most abundant milk FA. Metagenomics and metabolomics analyses highlighted that cows producing milk with contrasting FA profile under the same diet, also differ in their rumen metabolic activities in relation to adaptation to reduced rumen pH, carbohydrate fermentation, and protein synthesis and metabolism.

Comparative accuracies of genetic values predicted for economically important milk traits, genome-wide association, and linkage disequilibrium patterns of Canadian Holstein cows

Genomic selection methodologies and genome-wide association studies use powerful statistical procedures that correlate large amounts of high-density SNP genotypes and phenotypic data. Actual 305-d milk (MY), fat (FY), and protein (PY) yield data on 695 cows and 76,355 genotyping-by-sequencing-generated SNP marker genotypes from Canadian Holstein dairy cows were used to characterize linkage disequilibrium (LD) structure of Canadian Holstein cows. Also, the comparison of pedigree-based BLUP, genomic BLUP (GBLUP), and Bayesian (BayesB) statistical methods in the genomic selection methodologies and the comparison of Bayesian ridge regression and BayesB statistical methods in the genome-wide association studies were carried out for MY, FY, and PY. Results from LD analysis revealed that as marker distance decreases, LD increases through chromosomes. However, unexpected high peaks in LD were observed between marker pairs with larger marker distances on all chromosomes. The GBLUP and BayesB models resulted in similar heritability estimates through 10-fold cross-validation for MY and PY; however, the GBLUP model resulted in higher heritability estimates than BayesB model for FY. The predictive ability of GBLUP model was significantly lower than that of BayesB for MY, FY, and PY. Association analyses indicated that 28 high-effect markers and markers on Bos taurus autosome 14 located within 6 genes (DOP1B, TONSL, CPSF1, ADCK5, PARP10, and GRINA) associated significantly with FY.

Inbreeding coefficients and runs of homozygosity islands in Brazilian water buffalo

Characterization of autozygosity is relevant to monitor genetic diversity and manage inbreeding levels in breeding programs. Identification of autozygosity hotspots can unravel genomic regions targeted by selection for economically important traits and can help identify candidate genes for selection. In this study, we estimated the inbreeding levels of a Brazilian population of Murrah buffalo undergoing selection for milk production traits, particularly milk yield. We also studied the distribution of runs of homozygosity (ROH) islands and identified putative genes and quantitative trait loci (QTL) under selection. We genotyped 422 Murrah buffalo for 51,611 SNP; 350 of these had ROH longer than 10 Mb, indicating the occurrence of inbreeding in the last 5 generations. The mean length of the ROH per animal was 4.28 ± 1.85 Mb. Inbreeding coefficients were calculated from the genomic relationship matrix, the pedigree, and the ROH, with estimates varying between 0.242 and 0.035. Inbreeding estimates from the pedigree had a low correlation with the genomic estimates, and estimates from the genomic relationship matrix were much higher than those from the pedigree or the ROH. Signatures of selection were identified in 6 genomic regions, located on chromosomes 1, 2, 3, 5, 16, and 18, encompassing a total of 190 genes and 174 QTL. Many of the genes (e.g., APRT and ACSF3) and QTL identified are related to milk production traits, such as milk yield, milk fat yield and percentage, and milk protein yield and percentage. Other genes are associated with reproduction and immune response traits as well as morphological aspects of the buffalo species. Inbreeding levels in this population are still low but are increasing due to selection and should be managed to avoid future losses due to inbreeding depression. The proximity of genes linked to milk production traits with genes associated with reproduction and immune system traits suggests the need to include these latter genes in the breeding program to avoid negatively affecting them due to selection for production traits.

Population demographic history and population structure for Pakistani Nili-Ravi breeding bulls based on SNP genotyping to identify genomic regions associated with male effects for milk yield and body weight

The domestic Nili-Ravi water buffalo (Bubalus bubalis) is the best dairy animal contributing 68% to total milk production in Pakistan. In this study, we identified genome-wide single nucleotide polymorphisms (SNPs) to estimate various population genetic parameters such as diversity, pairwise population differentiation, linkage disequilibrium (LD) distribution and for genome-wide association study for milk yield and body weight traits in the Nili-Ravi dairy bulls that they may pass on to their daughters who are retained for milking purposes. The genotyping by sequencing approach revealed 13,039 reference genome-anchored SNPs with minor allele frequency of 0.05 among 167 buffalos. Population structure analysis revealed that the bulls were grouped into two clusters (K = 2), which indicates the presence of two different lineages in the Pakistani Nili-Ravi water buffalo population, and we showed the extent of admixture of these two lineages in our bull collection. LD analysis revealed 4169 significant SNP associations, with an average LD decay of 90 kb for these buffalo genome. Genome-wide association study involved a multi-locus mixed linear model for milk yield and body weight to identify genome-wide male effects. Our study further illustrates the utility of the genotyping by sequencing approach for identifying genomic regions to uncover additional demographic complexity and to improve the complex dairy traits of the Pakistani Nili-Ravi water buffalo population that would provide the lot of economic benefits to dairy industry.

Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis

Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (F_ST) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.

GWAS-Based Identification of New Loci for Milk Yield, Fat, and Protein in Holstein Cattle

High-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk-related traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production and quality traits in Holstein cattle population from China. These traits included milk yield, fat, and protein. 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 linear mixed model. 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 single-nucleotide polymorphisms (SNPs) were detected above the genome-wide significant threshold (p < 4.0 × 10-7), including six located in previously reported quantitative traits locus (QTL) regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The study not only identified the effect of DGAT1 gene on milk fat and protein, but also discovered novel genetic loci and candidate genes related to milk traits. These novel genetic loci would be an important basis for molecular breeding in dairy cattle.

Genome-Wide Association Study and Pathway Analysis for Female Fertility Traits in Iranian Holstein Cattle

Female fertility is an important trait that contributes to cow’s profitability and it can be improved by genomic information. The objective of this study was to detect genomic regions and variants affecting fertility traits in Iranian Holstein cattle. A data set comprised of female fertility records and 3,452,730 pedigree information from Iranian Holstein cattle were used to predict the breeding values, which were then employed to estimate the de-regressed proofs (DRP) of genotyped animals. A total of 878 animals with DRP records and 54k SNP markers were utilized in the genome-wide association study (GWAS). The GWAS was performed using a linear regression model with SNP genotype as a linear covariate. The results showed that an SNP on BTA19, ARS-BFGL-NGS-33473, was the most significant SNP associated with days from calving to first service. In total, [69] significant SNPs were located within 27 candidate genes. Novel potential candidate genes include OSTN, DPP6, EphA5, CADPS2, Rfc1, ADGRB3, Myo3a, C10H14orf93, KIAA1217, RBPJL, SLC18A2, GARNL3, NCALD, ASPH, ASIC2, OR3A1, CHRNB4, CACNA2D2, DLGAP1, GRIN2A and ME3. These genes are involved in different pathways relevant to female fertility and other characteristics in mammals. Gene set enrichment analysis showed that thirteen GO terms had significant overrepresentation of genes statistically associated with female fertility traits. The results of network analysis identified CCNB1 gene as a hub gene in the progesterone-mediated oocyte maturation pathway, significantly associated with age at first calving. The candidate genes identified in this study can be utilized in genomic tests to improve reproductive performance in Holstein cattle.

Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds

Background

Sequence-based genome-wide association studies (GWAS) provide high statistical power to identify candidate causal mutations when a large number of individuals with both sequence variant genotypes and phenotypes is available. A meta-analysis combines summary statistics from multiple GWAS and increases the power to detect trait-associated variants without requiring access to data at the individual level of the GWAS mapping cohorts. Because linkage disequilibrium between adjacent markers is conserved only over short distances across breeds, a multi-breed meta-analysis can improve mapping precision.

Results

To maximise the power to identify quantitative trait loci (QTL), we combined the results of nine within-population GWAS that used imputed sequence variant genotypes of 94,321 cattle from eight breeds, to perform a large-scale meta-analysis for fat and protein percentage in cattle. The meta-analysis detected (p ≤ 10⁻⁸) 138 QTL for fat percentage and 176 QTL for protein percentage. This was more than the number of QTL detected in all within-population GWAS together (124 QTL for fat percentage and 104 QTL for protein percentage). Among all the lead variants, 100 QTL for fat percentage and 114 QTL for protein percentage had the same direction of effect in all within-population GWAS. This indicates either persistence of the linkage phase between the causal variant and the lead variant across breeds or that some of the lead variants might indeed be causal or tightly linked with causal variants. The percentage of intergenic variants was substantially lower for significant variants than for non-significant variants, and significant variants had mostly moderate to high minor allele frequencies. Significant variants were also clustered in genes that are known to be relevant for fat and protein percentages in milk.

Conclusions

Our study identified a large number of QTL associated with fat and protein percentage in dairy cattle. We demonstrated that large-scale multi-breed meta-analysis reveals more QTL at the nucleotide resolution than within-population GWAS. Significant variants were more often located in genic regions than non-significant variants and a large part of them was located in potentially regulatory regions.