Genome wide analysis of fertility and production traits in Italian Holstein cattle

Identifying Regions of the Genome Associated with Conception Rate to the First Service in Holstein Heifers Bred by Artificial Insemination and as Embryo Transfer Recipients

Heifer conception rate to the first service (HCR1) is defined as the number of heifers that become pregnant to the first breeding service compared to the heifers bred. This study aimed to identify loci associated and gene sets enriched for HCR1 for heifers that were bred by artificial insemination (AI, n = 2829) or were embryo transfer (ET, n = 2086) recipients, by completing a genome-wide association analysis and gene set enrichment analysis using SNP data (GSEA-SNP). Three unique loci, containing four positional candidate genes, were associated (p < 1 × 10-5) with HCR1 for ET recipients, while the GSEA-SNP identified four gene sets (NES ≥ 3) and sixty-two leading edge genes (LEGs) enriched for HCR1. While no loci were associated with HCR1 bred by AI, one gene set and twelve LEGs were enriched (NES ≥ 3) for HCR1 with the GSEA-SNP. This included one gene (PKD2) shared between HCR1 AI and ET services. Identifying loci associated or enriched for HCR1 provides an opportunity to use them as genomic selection tools to facilitate the selection of cattle with higher reproductive efficiency, and to better understand embryonic loss.

Genome-wide association and functional annotation analysis for the calving interval in Nellore cattle

Calving interval (CI) measures the number of days between two consecutive calves of the same cow, and previous studies based on phenotype and pedigree data reported low heritability for this trait. However, the genetic architecture of CI in the Nellore breed was not evaluated based on genomic data. Thus, this study aimed to estimate the heritability based on genomic data and carry out a genome-wide association study (GWAS) for CI in the Nellore breed, using 12,599 pedigree records, 5078 CI records, and 3818 animals genotyped with 50k SNPchip panel. Both quality control and GWAS were performed in BLUPF90 family packages, which use the single-step genomic best linear unbiased predictor (ssGBLUP) method. The average CI was 427.6 days, with a standard deviation of 106.9 and a total range of 270-730 days. The heritability estimate was 0.04 ± 0.04. The p-values of GWAS analysis resulted in a genomic inflation factor (lambda) of 1.08. The only significant SNP (rs136725686) at the genome-wide level (p-value = 1.53E-06) was located on BTA13. Other 19 SNPs were significant at the chromosome-wide level, distributed on BTA1, 2, 3, 6, 10, 13, 14, 17, 18, 22, and 26. Functional annotation analysis found thirty-six protein-coding genes, including genes related to cell cycle (RAD21, BCAR3), oocyte function (LHX8, CLPX, UTP23), immune system (TXK, TEC, NFATC2), endocrine function (LRRFIP2, GPR158), estrous cycle (SLC38A7), and female fertility (CCK, LYZL4, TRAK1, FOXP1, STAC). Therefore, CI is a complex trait with small heritability in Nellore cattle, and various biological processes may be involved with the genetic architecture of CI in Nellore cattle.

The Anti-Müllerian Hormone as Endocrine and Molecular Marker Associated with Reproductive Performance in Holstein Dairy Cows Exposed to Heat Stress

Anti-Müllerian hormone (AMH) is proposed as a biomarker for fertility in cattle, yet this associative relationship appears to be influenced by heat stress (HS). The objective was to test serum AMH and AMH-related single nucleotide polymorphisms (SNPs) as markers potentially predictive of reproductive traits in dairy cows experiencing HS. The study included 300 Holstein cows that were genotyped using BovineSNP50 (54,000 SNP). A genome-wide association study was then executed. Nine intragenic SNPs within the pathways that influence the AMH gene were found important with multiple comparisons adjustment tests (p < 1.09 × 10-6). A further validation study was performed in an independent Holstein cattle population, which was divided into moderate (MH; n = 152) and severe heat-stressed (SH; n = 128) groups and then subjected to a summer reproductive management program. Serum AMH was confirmed as a predictor of fertility measures (p < 0.05) in MH but not in the SH group. Cows were genotyped, which revealed four SNPs as predictive markers for serum AMH (p < 0.01), reproductive traits (p < 0.01), and additional physiological variables (p < 0.05). These SNPs were in the genes AMH, IGFBP1, LGR5, and TLR4. In conclusion, serum AMH concentrations and AMH polymorphisms are proposed as predictive markers that can be used in conjunction with genomic breeding value approaches to improve reproductive performance in Holstein cows exposed to summer HS conditions.

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.

Genome-wide identification and annotation of SNPs and their mapping in candidate genes related to milk production and fertility traits in Badri cattle

This study was conducted in Badri cattle using a double digest restriction-site associated DNA sequencing approach. The study aimed to identify and annotate high confidence single nucleotide polymorphisms (SNPs) and their mapping in candidate genes related to production and fertility in dairy cattle. A total of 7,168,552 genome-wide SNPs were initially identified in Badri cattle by alignment with the Bos indicus reference genome. After filtration of SNPs, 65,483 high confidence SNPs were retained and further used for downstream analysis. Annotation of high confidence SNPs revealed 99.197% SNPs had modifier impact, 0.326% SNPs were low impact, 0.036% were high impact, and 0.441% were moderate impact SNPs. Most SNPs in Badri cattle were found in intergenic, transcript and intronic regions. The candidate genes for milk production PRKCE, ABCG2, GHR, EPS8, CAST and NRXN1 were found to harbour maximum high confidence variants. Among candidate genes for fertility in cattle, ATP2B1, SOX5, WDR27, ARHGAP12, CACNA1D, ANKRD6, GRIA3, ZNF521 and CAST822 have maximum high confidence variants mapped in them. The SNPs found mapped in the candidate genes will be important genetic tools in the search for phenotype-modifying nucleotide changes and will aid in formulating relevant genetic improvement programmes for dairy cattle.

Genome-wide association study and functional annotation analyses for nitrogen efficiency index and its composition traits in dairy cattle

The aims of this study were (1) to identify genomic regions associated with a N efficiency index (NEI) and its composition traits and (2) to analyze the functional annotation of identified genomic regions. The NEI included N intake (NINT1), milk true protein N (MTPN1), milk urea N yield (MUNY1) in primiparous cattle, and N intake (NINT2+), milk true protein N (MTPN2+), and milk urea N yield (MUNY2+) in multiparous cattle (2 to 5 parities). The edited data included 1,043,171 records on 342,847 cows distributed in 1,931 herds. The pedigree consisted of 505,125 animals (17,797 males). Data of 565,049 SNPs were available for 6,998 animals included in the pedigree (5,251 females and 1,747 males). The SNP effects were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of about 240 kb) was calculated. The top 3 genomic regions explaining the largest rate of the total additive genetic variance of the NEI and its composition traits were selected for candidate gene identification and quantitative trait loci (QTL) annotation. The selected genomic regions explained from 0.17% (MTPN2+) to 0.58% (NEI) of the total additive genetic variance. The largest explanatory genomic regions of NEI, NINT1, NINT2+, MTPN1, MTPN2+, MUNY1, and MUNY2+ were Bos taurus autosome 14 (1.52-2.09 Mb), 26 (9.24-9.66 Mb), 16 (75.41-75.51 Mb), 6 (8.73-88.92 Mb), 6 (8.73-88.92 Mb), 11 (103.26-103.41 Mb), 11 (103.26-103.41 Mb). Based on the literature, gene ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction, 16 key candidate genes were identified for NEI and its composition traits, which are mainly expressed in the milk cell, mammary, and liver tissues. The number of enriched QTL related to NEI, NINT1, NINT2+, MTPN1, and MTPN2+ were 41, 6, 4, 11, 36, 32, and 32, respectively, and most of them were related to the milk, health, and production classes. In conclusion, this study identified genomic regions associated with NEI and its composition traits, and identified key candidate genes describing the genetic mechanisms of N use efficiency-related traits. Furthermore, the NEI reflects not only its composition traits but also the interactions among them.

A Random Forest-Based Genome-Wide Scan Reveals Fertility-Related Candidate Genes and Potential Inter-Chromosomal Epistatic Regions Associated With Age at First Calving in Nellore Cattle

This study aimed to perform a genome-wide association analysis (GWAS) using the Random Forest (RF) approach for scanning candidate genes for age at first calving (AFC) in Nellore cattle. Additionally, potential epistatic effects were investigated using linear mixed models with pairwise interactions between all markers with high importance scores within the tree ensemble non-linear structure. Data from Nellore cattle were used, including records of animals born between 1984 and 2015 and raised in commercial herds located in different regions of Brazil. The estimated breeding values (EBV) were computed and used as the response variable in the genomic analyses. After quality control, the remaining number of animals and SNPs considered were 3,174 and 360,130, respectively. Five independent RF analyses were carried out, considering different initialization seeds. The importance score of each SNP was averaged across the independent RF analyses to rank the markers according to their predictive relevance. A total of 117 SNPs associated with AFC were identified, which spanned 10 autosomes (2, 3, 5, 10, 11, 17, 18, 21, 24, and 25). In total, 23 non-overlapping genomic regions embedded 262 candidate genes for AFC. Enrichment analysis and previous evidence in the literature revealed that many candidate genes annotated close to the lead SNPs have key roles in fertility, including embryo pre-implantation and development, embryonic viability, male germinal cell maturation, and pheromone recognition. Furthermore, some genomic regions previously associated with fertility and growth traits in Nellore cattle were also detected in the present study, reinforcing the effectiveness of RF for pre-screening candidate regions associated with complex traits. Complementary analyses revealed that many SNPs top-ranked in the RF-based GWAS did not present a strong marginal linear effect but are potentially involved in epistatic hotspots between genomic regions in different autosomes, remarkably in the BTAs 3, 5, 11, and 21. The reported results are expected to enhance the understanding of genetic mechanisms involved in the biological regulation of AFC in this cattle breed.

Identifying pleiotropic variants and candidate genes for fertility and reproduction traits in Holstein cattle via association studies based on imputed whole-genome sequence genotypes

Background

Genetic progress for fertility and reproduction traits in dairy cattle has been limited due to the low heritability of most indicator traits. Moreover, most of the quantitative trait loci (QTL) and candidate genes associated with these traits remain unknown. In this study, we used 5.6 million imputed DNA sequence variants (single nucleotide polymorphisms, SNPs) for genome-wide association studies (GWAS) of 18 fertility and reproduction traits in Holstein cattle. Aiming to identify pleiotropic variants and increase detection power, multiple-trait analyses were performed using a method to efficiently combine the estimated SNP effects of single-trait GWAS based on a chi-square statistic.

Results

There were 87, 72, and 84 significant SNPs identified for heifer, cow, and sire traits, respectively, which showed a wide and distinct distribution across the genome, suggesting that they have relatively distinct polygenic nature. The biological functions of immune response and fatty acid metabolism were significantly enriched for the 184 and 124 positional candidate genes identified for heifer and cow traits, respectively. No known biological function was significantly enriched for the 147 positional candidate genes found for sire traits. The most important chromosomes that had three or more significant QTL identified are BTA22 and BTA23 for heifer traits, BTA8 and BTA17 for cow traits, and BTA4, BTA7, BTA17, BTA22, BTA25, and BTA28 for sire traits. Several novel and biologically important positional candidate genes were strongly suggested for heifer (SOD2, WTAP, DLEC1, PFKFB4, TRIM27, HECW1, DNAH17, and ADAM3A), cow (ANXA1, PCSK5, SPESP1, and JMJD1C), and sire (ELMO1, CFAP70, SOX30, DGCR8, SEPTIN14, PAPOLB, JMJD1C, and NELL2) traits.

Conclusions

These findings contribute to better understand the underlying biological mechanisms of fertility and reproduction traits measured in heifers, cows, and sires, which may contribute to improve genomic evaluation for these traits in dairy cattle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08555-z.

Identification of Homozygous Regions With Adverse Effects on the Five Economic Traits of Duroc Pigs

Runs of homozygosity (ROH) are widely used to estimate genomic inbreeding, which is linked to inbreeding depression on phenotypes. However, the adverse effects of specific homozygous regions on phenotypic characteristics are rarely studied in livestock. In this study, the 50 K SNP data of 3,770 S21 Duroc (American origin) and 2,096 S22 Duroc (Canadian origin) pigs were used to investigate the harmful ROH regions on five economic traits. The results showed that the two Duroc lines had different numbers and distributions of unfavorable ROHs, which may be related to the different selection directions and intensities between the two lines. A total of 114 and 58 ROH segments were found with significant adverse effects on the economic traits of S21 and S22 pigs, respectively. Serval pleiotropic ROHs were detected to reduce two or multiple phenotypic performances in two Duroc populations. Candidate genes in these shared regions were mainly related to growth, fertility, immunity, and fat deposition. We also observed that some ROH genotypes may cause opposite effects on different traits. This study not only enhances our understanding of the adverse effects of ROH on phenotypes, but also indicates that ROH information could be incorporated into breeding programs to estimate and control the detrimental effects of homozygous regions.

Four novel candidate causal variants for deficient homozygous haplotypes in Holstein cattle

Mendelian variants can determine both insemination success and neonatal survival and thus influence fertility and rearing success of cattle. We present 24 deficient homozygous haplotype regions in the Holstein population of Switzerland and provide an overview of the previously identified haplotypes in the global Holstein breed. This study encompasses massive genotyping, whole-genome sequencing (WGS) and phenotype association analyses. We performed haplotype screenings on almost 53 thousand genotyped animals including 114 k SNP data with two different approaches. We revealed significant haplotype associations to several survival, birth and fertility traits. Within haplotype regions, we mined WGS data of hundreds of bovine genomes for candidate causal variants, which were subsequently evaluated by using a custom genotyping array in several thousand breeding animals. With this approach, we confirmed the known deleterious SMC2:p.Phe1135Ser missense variant associated with Holstein haplotype (HH) 3. For two previously reported deficient homozygous haplotypes that show negative associations to female fertility traits, we propose candidate causative loss-of-function variants: the HH13-related KIR2DS1:p.Gln159* nonsense variant and the HH21-related NOTCH3:p.Cys44del deletion. In addition, we propose the RIOX1:p.Ala133_Glu142del deletion as well as the PCDH15:p.Leu867Val missense variant to explain the unexpected low number of homozygous haplotype carriers for HH25 and HH35, respectively. In conclusion, we demonstrate that with mining massive SNP data in combination with WGS data, we can map several haplotype regions and unravel novel recessive protein-changing variants segregating at frequencies of 1 to 5%. Our findings both confirm previously identified loci and expand the spectrum of undesired alleles impairing reproduction success in Holstein cattle, the world's most important dairy breed.

Identification of unique ROH regions with unfavorable effects on production and fertility traits in Canadian Holsteins

Background

The advent of genomic information and the reduction in the cost of genotyping have led to the use of genomic information to estimate genomic inbreeding as an alternative to pedigree inbreeding. Using genomic measures, effects of genomic inbreeding on production and fertility traits have been observed. However, there have been limited studies on the specific genomic regions causing the observed negative association with the trait of interest. Our aim was to identify unique run of homozygosity (ROH) genotypes present within a given genomic window that display negative associations with production and fertility traits and to quantify the effects of these identified ROH genotypes.

Methods

In total, 50,575 genotypes based on a 50K single nucleotide polymorphism (SNP) array and 259,871 pedigree records were available. Of these 50,575 genotypes, 46,430 cows with phenotypic records for production and fertility traits and having a first calving date between 2008 and 2018 were available. Unique ROH genotypes identified using a sliding-window approach were fitted into an animal mixed model as fixed effects to determine their effect on production and fertility traits.

Results

In total, 133 and 34 unique ROH genotypes with unfavorable effects were identified for production and fertility traits, respectively, at a 1% genome-wise false discovery rate. Most of these ROH regions were located on bovine chromosomes 8, 13, 14 and 19 for both production and fertility traits. For production traits, the average of all the unfavorably identified unique ROH genotypes effects were estimated to decrease milk yield by 247.30 kg, fat yield by 11.46 kg and protein yield by 8.11 kg. Similarly, for fertility traits, an average 4.81-day extension in first service to conception, a 0.16 increase in number of services, and a − 0.07 incidence in 56-day non-return rate were observed. Furthermore, a ROH region located on bovine chromosome 19 was identified that, when homozygous, had a negative effect on production traits. Signatures of selection proximate to this region have implicated GH1 as a potential candidate gene, which encodes the growth hormone that binds the growth hormone receptor. This observed negative effect could be a consequence of unfavorable alleles in linkage disequilibrium with favorable alleles.

Conclusions

ROH genotypes with unfavorable effects on production and fertility traits were identified within and across multiple traits on most chromosomes. These identified ROH genotypes could be included in mate selection programs to minimize their frequency in future generations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00660-z.

Single-step genomic best linear unbiased predictor genetic parameter estimations and genome-wide associations for milk fatty acid profiles, interval from calving to first insemination, and ketosis in Holstein cattle

Milk fatty acids (FA) have been suggested as biomarkers for early-lactation metabolic diseases and for female fertility status. The aim of the present study was to infer associations between FA, the metabolic disorder ketosis (KET), and the interval from calving to first insemination (ICF) genetically and genomically. In this regard, we focused on a single-step genomic BLUP approach, allowing consideration of genotyped and ungenotyped cows simultaneously. The phenotypic data set considered 38,375 first-lactation Holstein cows, kept in 45 large-scale co-operator herds from 2 federal states in Germany. The calving years for these cows were from 2014 to 2017. Concentrations in milk from the first official milk recording test-day for saturated, unsaturated (UFA), monounsaturated (MUFA), polyunsaturated, palmitic, and stearic (C18:0) FA were determined via Fourier-transform infrared spectroscopy. Ketosis was defined as a binary trait according to a veterinarian diagnosis key, considering diagnoses within a 6-wk interval after calving. A subset of 9,786 cows was genotyped for 40,989 SNP markers. Variance components and heritabilities for all Gaussian distributed FA and for ICF, and for binary KET were estimated by applying single-step genomic BLUP single-trait linear and threshold models, respectively. Genetic correlations were estimated in series of bivariate runs. Genomic breeding values for the single-step genomic BLUP estimations were dependent traits in single-step GWAS. Heritabilities for FA were moderate in the range from 0.09 to 0.20 (standard error = 0.02-0.03), but quite small for ICF (0.08, standard error = 0.01) and for KET (0.05 on the underlying liability scale, posterior standard deviation = 0.02). Genetic correlations between KET and UFA, MUFA, and C18:0 were large (0.74 to 0.85, posterior standard deviation = 0.14-0.19), and low positive between KET and ICF (0.17, posterior standard deviation = 0.22). Genetic correlations between UFA, MUFA, and C18:0 with ICF ranged from 0.34 to 0.46 (standard error = 0.12). In single-step GWAS, we identified a large proportion of overlapping genomic regions for the different FA, especially for UFA and MUFA, and for saturated and palmitic FA. One identical significantly associated SNP was identified for C18:0 and KET on BTA 15. However, there was no genomic segment simultaneously significantly affecting all trait categories ICF, FA, and KET. Nevertheless, some of the annotated potential candidate genes DGKA, IGFBP4, and CXCL8 play a role in lipid metabolism and fertility mechanisms, and influence production diseases in early lactation. Genetic and genomic associations indicate that Fourier-transform infrared spectroscopy FA concentrations in milk from the first official test-day are valuable predictors for KET and for ICF.

TMT based deep proteome analysis of buffalo mammary epithelial cells and identification of novel protein signatures during lactogenic differentiation

The lactating mammary gland harbours numerous matured alveoli with their lumen surrounded by differentiated mammary epithelial cells (MECs), which are exclusively involved in milk synthesis and secretion. Buffalo (Bubalus bubalis) is the second major milk-producing animal, and its physiology is different from cattle. The complete protein machinery involved in MECs differentiation is still not defined in ruminants, in particular, buffalo. Therefore, we have studied the differential expression of regulated proteins in the in vitro grown buffalo MECs (BuMECs) at different time points (on 3, 6, 12, and 15 days) of their differentiation in the presence of lactogenic hormones. TMT-based MS analysis identified 4,934 proteins; of them, 681 were differentially expressed proteins (DEPs). The principal component analysis suggested a highly heterogeneous expression of DEPs at the four-time points of hormone treatment, with most of them (307) attained the highest expression on 12 days. Bioinformatics analysis revealed the association of DEPs with 24 KEGG pathways. We observed few new proteins, namely ABCA13, IVL, VPS37, CZIB, RFX7, Rab5, TTLL12, SMEK1, GDI2, and TMEM131 in BuMECs. The function of one of the highly upregulated proteins, namely involucrin in the differentiation of BuMECs was confirmed based on biochemical inhibition assay. The results further conclude that the proteins with higher abundance can be considered as the potential biomarkers for differentiation, and they may have a significant association with the lactation process in buffalo too. The proteome dataset obtained can be used to understand the species-specific variations among other lactating animals.

Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle

Simple Summary

Milk production traits that are economically important in the dairy industry have been considered the main selection criteria for breeding. The present genome-wide association study was performed to identify chromosomal loci and candidate genes with potential effects on milk production phenotypes in a Korean Holstein population. A total of eight significant quantitative trait locus regions were identified for milk yield (Bos taurus autosome (BTA) 7 and 14), adjusted 305-d fat yield (BTA 3, 5, and 14), adjusted 305-d protein yield (BTA 8), and somatic cell score (BTA 8 and 23) of milk production traits. Furthermore, we discovered three main candidate genes (diacylglycerol O-acyltransferase 1 (DGAT1), phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) through bioinformatics analysis. These genes may help to understand better the underlying genetic and molecular mechanisms for milk production phenotypes in the Korean Holstein population.

Abstract

We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein 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.

Identification of Loci and Pathways Associated with Heifer Conception Rate in U.S. Holsteins

Heifer conception rate (HCR) is defined as the percentage of inseminated heifers that become pregnant at each service. The genome-wide association analyses in this study focused on identifying the loci associated with Holstein heifer (n = 2013) conception rate at first service (HCR1) and the number of times bred (TBRD) to achieve a pregnancy. There were 348 unique loci associated (p < 5 × 10⁻⁸) with HCR1 and 615 unique loci associated (p < 5 × 10⁻⁸) with TBRD. The two phenotypes shared 302 loci, and 56 loci were validated in independent cattle populations. There were 52 transcription factor binding sites (TFBS) and 552 positional candidate genes identified in the HCR1- and TBRD-associated loci. The positional candidate genes and the TFBS associated with HCR1 and TBRD were used in the ingenuity pathway analysis (IPA). In the IPA, 11 pathways, 207 master regulators and 11 upstream regulators were associated (p < 1.23 × 10⁻⁵) with HCR1 and TBRD. The validated loci associated with both HCR1 and TBRD make good candidates for genomic selection and further investigations to elucidate the mechanisms associated with subfertility and infertility.

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

The aim of the present study was to identify genomic region(s) associated with the length of the calving interval in primiparous (n = 6866) and multiparous (n = 5071) Holstein cows. The single nucleotide polymorphism (SNP) solutions were estimated using a weighted single-step genomic best linear unbiased prediction (WssGBLUP) approach and imputed high-density panel (777 k) genotypes. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. The results showed that the accuracies of GEBVs with WssGBLUP improved by +5.4 to +5.7, (primiparous cows) and +9.4 to +9.7 (multiparous cows) percent points over accuracies from the pedigree-based BLUP. The most accurate genomic evaluation was provided at the second iteration of WssGBLUP, which was used to identify associated genomic regions using a windows-based GWAS procedure. The proportion of additive genetic variance explained by windows of 50 consecutive SNPs (with an average of 165 Kb) was calculated and the region(s) that accounted for equal to or more than 0.20% of the total additive genetic variance were used to search for candidate genes. Three windows of 50 consecutive SNPs (BTA3, BTA6, and BTA7) were identified to be associated with the length of the calving interval in primi- and multiparous cows, while the window with the highest percentage of explained genetic variance was located on BTA3 position 49.42 to 49.52 Mb. There were five genes including ARHGAP29, SEC24D, METTL14, SLC36A2, and SLC36A3 inside the windows associated with the length of the calving interval. The biological process terms including alanine transport, L-alanine transport, proline transport, and glycine transport were identified as the most important terms enriched by the genes inside the identified windows.

A genome-wide association study of reproduction traits in four pig populations with different genetic backgrounds

Objective

Genome-wide association study and two meta-analysis based on GWAS performed to explore the genetic mechanism underlying variation in pig number born alive (NBA) and total number born (TNB).

Methods

Single trait GWAS and two meta-analysis (single-trait meta analysis and multi-trait meta analysis) were used in our study for NBA and TNB on 3,121 Yorkshires from 4 populations, including three different American Yorkshire populations (n = 2,247) and one British Yorkshire populations (n = 874).

Results

The result of single trait GWAS showed that no significant associated single nucleotide polymorphisms (SNPs) were identified. Using single-trait meta analysis and multi-trait meta analysis within populations, 11 significant loci were identified associated with target traits. Spindlin 1, vascular endothelial growth factor A, forkhead box Q1, msh homeobox 1, and LHFPL tetraspan submily member 3 are five functionally plausible candidate genes for NBA and TNB. Compared to the single population GWAS, single-trait Meta analysis can improve the detection power to identify SNPs by integrating information of multiple populations. The multiple-trait analysis reduced the power to detect trait-specific loci but enhanced the power to identify the common loci across traits.

Conclusion

In total, our findings identified novel genes to be validated as candidates for NBA and TNB in pigs. Also, it enabled us to enlarge population size by including multiple populations with different genetic backgrounds and increase the power of GWAS by using meta analysis.

Genome wide association study of test days and 305 days milk yield in crossbred cattle

The present study was conducted to identify SNPs associated with test days and 305 days milk production at genome level after correcting for the non-genetic factors affecting these traits in crossbred (Vrindavani) cattle. Crossbred cattle (96) were genotyped using double digestion genotyping-by-sequencing technique for genome wide association study (GWAS) with first lactation milk production traits. The effect of season was significant on TD36, TD66 and TD96. Initial quality control for genotyping call rate, Hardy-Weinberg equilibrium and minor allele frequency were achieved by using PLINK tool. SNPs (9638) were retained for ascertaining GWAS with first lactation milk production traits and was accomplished by regressing SNPs on first lactation milk traits using PLINK. Total 23, 28, 112, 3, 13 and 5 SNPs were found to be significantly associated with AVDY, PY, TD36, TD66, TD96 and FL305MY, respectively. Most of the SNPs were located within KIRREL3 or near to it on chromosome 29, followed by LRRC3 and TSPEAR on chromosome 1. Three SNPs (NC_007299.6_145850854, NC_007328.5_26544467 and NC_007328.5_26544511) were significantly associated with all milk production traits. Our findings revealed majority of significant SNPs for milk traits were located within non-coding genomic regions.

Identification of genetic markers associated with milk production traits in Chinese Holstein cattle based on post genome-wide association studies

With the rapid development of dairy industry, the breeding process of dairy cows has been accelerated. In previous genome-wide association studies (GWAS), a large number of genetic markers have been reported which may contribute to the selection of Holstein populations with superior milk-producing traits, but they remain to be further verified before practical application. In this study, 90 single nucleotide polymorphisms (SNPs) were selected, which were reported to be significantly associated with five milk production traits, including 305-day milk yield (305MY), 305-day milk fat percent (305FC), 305-day milk protein percent (305PC), 305-day milk fat yield (305FY) and 305-day milk protein yield (305PY). Effective 305-day data and fresh DNA samples were obtained from 295 healthy cows with gestational age of 1-4. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) was used to perform precise genotyping of these loci, followed by site association and haplotype analysis. Results showed that 36 out of 90 loci were supported to be used as genetic markers. In particular, several novel and effective haplotypes were also presented. Overall, our results verified tens of useful markers and provided a basis for further development of breeding strategies.

SNV discovery and functional candidate gene identification for milk composition based on whole genome resequencing of Holstein bulls with extremely high and low breeding values

We have sequenced the whole genomes of eight proven Holstein bulls from the four half-sib or full-sib families with extremely high and low estimated breeding values (EBV) for milk protein percentage (PP) and fat percentage (FP) using Illumina re-sequencing technology. Consequently, 2.3 billion raw reads were obtained with an average effective depth of 8.1×. After single nucleotide variant (SNV) calling, total 10,961,243 SNVs were identified, and 57,451 of them showed opposite fixed sites between the bulls with high and low EBVs within each family (called as common differential SNVs). Next, we annotated the common differential SNVs based on the bovine reference genome, and observed that 45,188 SNVs (78.70%) were located in the intergenic region of genes and merely 11,871 SNVs (20.67%) located within the protein-coding genes. Of them, 13,099 common differential SNVs that were within or close to protein-coding genes with less than 5 kb were chosen for identification of candidate genes for milk compositions in dairy cattle. By integrated analysis of the 2,657 genes with the GO terms and pathways related to protein and fat metabolism, and the known quantitative trait loci (QTLs) for milk protein and fat traits, we identified 17 promising candidate genes: ALG14, ATP2C1, PLD1, C3H1orf85, SNX7, MTHFD2L, CDKN2D, COL5A3, FDX1L, PIN1, FIG4, EXOC7, LASP1, PGS1, SAO, GPLD1 and MGEA5. Our findings provided an important foundation for further study and a prompt for molecular breeding of dairy cattle.

Validation of 46 loci associated with female fertility traits in cattle

Background

Subfertility is one challenge facing the dairy industry as the average Holstein heifer conception rate (HCR), the proportion of heifers that conceive and maintain a pregnancy per breeding, is estimated at 55–60%. Of the loci associated with HCR, few have been validated in an independent cattle population, limiting their usefulness for selection or furthering our understanding of the mechanisms involved in successful pregnancy. Therefore, the objectives here were to identify loci associated with HCR: 1) to the first artificial insemination (AI) service (HCR1), 2) to repeated AI services required for a heifer to conceive (TBRD) and 3) to validate loci previously associated with fertility. Breeding and health records from 3359 Holstein heifers were obtained after heifers were bred by AI at observed estrus, with pregnancy determined at day 35 via palpation. Heifer DNA was genotyped using the Illumina BovineHD BeadChip, and genome-wide association analyses (GWAA) were performed with additive, dominant and recessive models using the Efficient Mixed Model Association eXpedited (EMMAX) method with a relationship matrix for two phenotypes. The HCR1 GWAA compared heifers that were pregnant after the first AI service (n = 497) to heifers that were open following the first AI service (n = 405), which included those that never conceived. The TBRD GWAA compared only those heifers which did conceive, across variable numbers of AI service (n = 712). Comparison of loci previously associated with fertility, HCR1 or TBRD were considered the same locus for validation when in linkage disequilibrium (D’ > 0.7).

Results

The HCR1 GWAA identified 116, 187 and 28 loci associated (P < 5 × 10^− 8) in additive, dominant and recessive models, respectively. The TBRD GWAA identified 235, 362, and 69 QTL associated (P < 5 × 10^− 8) with additive, dominant and recessive models, respectively. Loci previously associated with fertility were in linkage disequilibrium with 22 loci shared with HCR1 and TBRD, 5 HCR1 and 19 TBRD loci.

Conclusions

Loci associated with HCR1 and TBRD that have been identified and validated can be used to improve HCR through genomic selection, and to better understand possible mechanisms associated with subfertility.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5935-3) contains supplementary material, which is available to authorized users.

A genome-wide detection of selection signatures in conserved and commercial pig breeds maintained in Poland

BACKGROUND

Identification of selection signatures can provide a direct insight into the mechanism of artificial selection and allow further disclosure of the candidate genes related to the animals' phenotypic variation. Domestication and subsequent long-time selection have resulted in extensive phenotypic changes in domestic pigs, involving a number of traits, like behavior, body composition, disease resistance, reproduction and coat color. In this study, based on genotypes obtained from PorcineSNP60 Illumina assay we attempt to detect both diversifying and within-breed selection signatures in 530 pigs belonging to four breeds: Polish Landrace, Puławska, Złotnicka White and Złotnicka Spotted, of which the last three are a subject of conservative breeding and substantially represent the native populations.

RESULTS

A two largely complementary statistical methods were used for signatures detection, including: pairwise F_ST and relative extended haplotype homozygosity (REHH) test. Breed-specific diversifying selection signals included several genes involved in processes connected with fertility, growth and metabolism which are potentially responsible for different phenotypes of the studied breeds. The diversifying selection signals also comprised PPARD gene that was previously found to have a large effect on the shape of the external ear in pigs or two genes encoding neuropeptide Y receptors (Y2 and Y5) involved in fat deposition and stress response which are important features differentiating the studied breeds. REHH statistics allowed detecting several within-breed selection signatures overlapping with genes connected with a range of functions including, among others: metabolic pathways, immune system response or implantation and development of the embryo.

CONCLUSIONS

The study provides many potential candidate genes with implication for traits selected in the individual breeds and gives strong basis for further studies aiming at identification of sources of variation among the studied pig breeds.

Ovarian transcriptomic analysis reveals the alternative splicing events associated with fecundity in different sheep breeds

Alternative splicing (AS) is one of the most common mechanisms that accounts for the greater macromolecular and cellular complexity of higher eukaryotic organisms. This study focused on the splicing events in the ovaries of different sheep breeds, namely the Han and Dorset breeds. Of the groups studied, cassette splicing events accounted for the maximum number of the AS events with significant differences, whereas the splicing events that were mutually exclusive with introns accounted for the smallest proportion of splicing events. Greater than 1000 AS events with significant differences were identified between the Han BB and Dorset sheep. The number of AS events with significant differences between Han ++ and Dorset sheep, however, was fewer than that of the comparison of Han BB and Dorset sheep. Seven randomly selected genes with AS events were detected in this study and were validated by reverse transcription-polymerase chain reaction (RT-PCR). Furthermore, there are many genes which were common to the two genotype groups (Han BB and Dorset sheep, as well as the Han ++ and Dorset sheep). In addition, genes detected in the present study were involved in different pathways, including the pathways related with fertility or fecundity. The present study could provide the detailed understanding on the mechanisms of alternative splicing events associated with fecundity in different sheep breeds.

The relationship between serum anti-Müllerian hormone concentrations and fertility, and genome-wide associations for anti-Müllerian hormone in Holstein cows

The objectives of this study were to (1) evaluate factors associated with variation in circulating anti-Müllerian hormone (AMH) concentrations, (2) establish an optimum AMH threshold predictive of pregnancy to first artificial insemination (P/AI), (3) examine the relationship between AMH and fertility (P/AI, pregnancy loss between 30 and 60 d after artificial insemination, and pregnancy risk up to 250 d postpartum), and (4) identify quantitative trait loci associated with phenotypic variation of AMH concentrations in dairy cows. Serum AMH concentrations (pg/mL) were determined at 7 ± 2.4 d postpartum in 647 lactating Holstein cows (213 primiparous, 434 multiparous) from 1 research and 6 commercial dairy herds in Alberta, Canada. Of these, 589 cows were genotyped on the 26K Bovine BeadChip (Neogen Inc., Lincoln, NE) and subsequently imputed to the Illumina Bovine High Density BeadChip (Illumina, San Diego, CA) for genome-wide association analysis for variation in serum AMH concentrations. Factors associated with variation in serum AMH concentrations and the relationship between categories of AMH and aforementioned fertility outcomes were evaluated only in a subset of 460 cows that had a complete data set available. The overall mean (±standard error of the mean), median, minimum, and maximum AMH concentrations were 191.1 ± 6.3, 151.7, 13.9, and 1,879.0 pg/mL, respectively. The AMH concentrations were not associated with herd, precalving body condition score, postpartum week, and season of sampling; the lactation number, however, had a quadratic relationship with serum AMH concentrations (116.2, 204.9 204.5, and 157.9 pg/mL for first, second, third, and ≥fourth lactation, respectively). The optimum AMH threshold predictive of P/AI could not be established because the receiver operating characteristic curve analysis model was nonsignificant. Categories of AMH [low (<83.0 pg/mL; n = 92), intermediate (≥83.0 to ≤285.0 pg/mL; n = 276), and high (>285.0 pg/mL; n = 92) based on lowest 20%, intermediate 60%, and highest 20% serum AMH) had no associations with P/AI (34, 43, and 40%), pregnancy loss between 30 and 60 d after artificial insemination (20, 12, and 8%), or pregnancy risk up to 250 d postpartum. One candidate gene associated with AMH production [AMH gene on Bos taurus autosome (BTA) 7] and 4 candidate genes related to embryo development (SCAI and PPP6C genes on BTA11 and FGF18 and EEF2K genes on BTA20 and BTA25, respectively) were in linkage disequilibrium with single nucleotide polymorphisms associated with phenotypic variation in serum AMH in dairy cows.

Genome-wide association studies of fertility and calving traits in Brown Swiss cattle using imputed whole-genome sequences

Background

The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants.

We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from ~1000–5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs.

Results

We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle.

Conclusion

The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4308-z) contains supplementary material, which is available to authorized users.

Population structure and genomic inbreeding in nine Swiss dairy cattle populations

BACKGROUND

Domestication, breed formation and intensive selection have resulted in divergent cattle breeds that likely exhibit their own genomic signatures. In this study, we used genotypes from 27,612 autosomal single nucleotide polymorphisms to characterize population structure based on 9214 sires representing nine Swiss dairy cattle populations: Brown Swiss (BS), Braunvieh (BV), Original Braunvieh (OB), Holstein (HO), Red Holstein (RH), Swiss Fleckvieh (SF), Simmental (SI), Eringer (ER) and Evolèner (EV). Genomic inbreeding (F ROH) and signatures of selection were determined by calculating runs of homozygosity (ROH). The results build the basis for a better understanding of the genetic development of Swiss dairy cattle populations and highlight differences between the original populations (i.e. OB, SI, ER and EV) and those that have become more popular in Switzerland as currently reflected by their larger populations (i.e. BS, BV, HO, RH and SF).

RESULTS

The levels of genetic diversity were highest and lowest in the SF and BS breeds, respectively. Based on F ST values, we conclude that, among all pairwise comparisons, BS and HO (0.156) differ more than the other pairs of populations. The original Swiss cattle populations OB, SI, ER, and EV are clearly genetically separated from the Swiss cattle populations that are now more common and represented by larger numbers of cows. Mean levels of F ROH ranged from 0.027 (ER) to 0.091 (BS). Three of the original Swiss cattle populations, ER (F ROH: 0.027), OB (F ROH: 0.029), and SI (F ROH: 0.039), showed low levels of genomic inbreeding, whereas it was much higher in EV (F ROH: 0.074). Private signatures of selection for the original Swiss cattle populations are reported for BTA4, 5, 11 and 26.

CONCLUSIONS

The low levels of genomic inbreeding observed in the original Swiss cattle populations ER, OB and SI compared to the other breeds are explained by a lesser use of artificial insemination and greater use of natural service. Natural service results in more sires having progeny at each generation and thus this breeding practice is likely the major reason for the remarkable levels of genetic diversity retained within these populations. The fact that the EV population is regionally restricted and its small census size of herd-book cows explain its high level of genomic inbreeding.

Genome-wide Association Studies for Female Fertility Traits in Chinese and Nordic Holsteins

Reduced female fertility could cause considerable economic loss and has become a worldwide problem in the modern dairy industry. The objective of this study was to detect quantitative trait loci (QTL) for female fertility traits in Chinese and Nordic Holsteins using various strategies. First, single-trait association analyses were performed for female fertility traits in Chinese and Nordic Holsteins. Second, the SNPs with P-value < 0.005 discovered in Chinese Holsteins were validated in Nordic Holsteins. Third, the summary statistics from single-trait association analyses were combined into meta-analyses to: (1) identify common QTL for multiple fertility traits within each Holstein population; (2) detect SNPs which were associated with a female fertility trait across two Holstein populations. A large numbers of QTL were discovered or confirmed for female fertility traits. The QTL segregating at 31.4~34.1 Mb on BTA13, 48.3~51.9 Mb on BTA23 and 34.0~37.6 Mb on BTA28 shared between Chinese and Nordic Holsteins were further ascertained using a validation approach and meta-analyses. Furthermore, multiple novel variants identified in Chinese Holsteins were validated with Nordic data as well as meta-analyses. The genes IL6R, SLC39A12, CACNB2, ZEB1, ZMIZ1 and FAM213A were concluded to be strong candidate genes for female fertility in Holsteins.

Association of single nucleotide polymorphisms in candidate genes previously related to genetic variation in fertility with phenotypic measurements of reproductive function in Holstein cows

Many genetic markers related to health or production traits are not evaluated in populations independent of the discovery population or related to phenotype. Here we evaluated 68 single nucleotide polymorphisms (SNP) in candidate genes previously associated with genetic merit for fertility and production traits for association with phenotypic measurements of fertility in a population of Holstein cows that was selected based on predicted transmitting ability (PTA) for daughter pregnancy rate (DPR; high, ≥1, n = 989; low, ≤ -1.0, n = 1,285). Cows with a high PTA for DPR had higher pregnancy rate at first service, fewer services per conception, and fewer days open than cows with a low PTA for DPR. Of the 68 SNP, 11 were associated with pregnancy rate at first service, 16 with services per conception, and 19 with days open. Single nucleotide polymorphisms in 12 genes (BDH2, BSP3, CAST, CD2, CD14, FUT1, FYB, GCNT3, HSD17B7, IBSP, OCLN, and PCCB) had significant associations with 2 fertility traits, and SNP in 4 genes (CSPP1, FCER1G, PMM2, and TBC1D24) had significant associations with each of the 3 traits. Results from this experiment were compared with results from 2 earlier studies in which the SNP were associated with genetic estimates of fertility. One study involved the same animals as used here, and the other study was of an independent population of bulls. A total of 13 SNP associated with 1 or more phenotypic estimates of fertility were directionally associated with genetic estimates of fertility in the same cow population. Moreover, 14 SNP associated with reproductive phenotype were directionally associated with genetic estimates of fertility in the bull population. Nine SNP (located in BCAS, BSP3, CAST, FUT1, HSD17B7, OCLN, PCCB, PMM2, and TBC1D24) had a directional association with fertility in all 3 studies. Examination of the function of the genes with SNP associated with reproduction in more than one study indicates the importance of steroid hormones and immune function as determinants of reproductive function. All but 1 of the 68 evaluated SNP were variable in 11 breeds besides Holstein, indicating the potential effects of these SNP on reproductive function across breeds of cattle.

Whole-Genome Resequencing of Holstein Bulls for Indel Discovery and Identification of Genes Associated with Milk Composition Traits in Dairy Cattle

The use of whole-genome resequencing to obtain more information on genetic variation could produce a range of benefits for the dairy cattle industry, especially with regard to increasing milk production and improving milk composition. In this study, we sequenced the genomes of eight Holstein bulls from four half- or full-sib families, with high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage at an average effective depth of 10×, using Illumina sequencing. Over 0.9 million nonredundant short insertions and deletions (indels) [1–49 base pairs (bp)] were obtained. Among them, 3,625 indels that were polymorphic between the high and low groups of bulls were revealed and subjected to further analysis. The vast majority (76.67%) of these indels were novel. Follow-up validation assays confirmed that most (70%) of the randomly selected indels represented true variations. The indels that were polymorphic between the two groups were annotated based on the cattle genome sequence assembly (UMD3.1.69); as a result, nearly 1,137 of them were found to be located within 767 annotated genes, only 5 (0.138%) of which were located in exons. Then, by integrated analysis of the 767 genes with known quantitative trait loci (QTL); significant single-nucleotide polymorphisms (SNPs) previously identified by genome-wide association studies (GWASs) to be associated with bovine milk protein and fat traits; and the well-known pathways involved in protein, fat synthesis, and metabolism, we identified a total of 11 promising candidate genes potentially affecting milk composition traits. These were FCGR2B, CENPE, RETSAT, ACSBG2, NFKB2, TBC1D1, NLK, MAP3K1, SLC30A2, ANGPT1 and UGDH. Our findings provide a basis for further study and reveal key genes for milk composition traits in dairy cattle.

Functional SNPs of INCENP Affect Semen Quality by Alternative Splicing Mode and Binding Affinity with the Target Bta-miR-378 in Chinese Holstein Bulls

Inner centromere protein (INCENP) plays an important role in mitosis and meiosis as the main member of chromosomal passenger protein complex (CPC). To investigate the functional markers of the INCENP gene associated with semen quality, the single nucleotide polymorphisms (SNPs) g.19970 A>G and g.34078 T>G were identified and analyzed. The new splice variant INCENP-TV is characterized by the deletion of exon 12. The g.19970 A>G in the exonic splicing enhancer (ESE) motif region results in an aberrant splice variant by constructing two minigene expression vectors using the pSPL3 exon capturing vector and transfecting vectors into MLTC-1 cells. INCENP-TV was more highly expressed than INCENP-reference in adult bull testes. The g.34078 T>G located in the binding region of bta-miR-378 could affect the expression of INCENP, which was verified by luciferase assay. To analyze comprehensively the correlation of SNPs with sperm quality, haplotype combinations constructed by g.19970 A>G and g.34078 T>G, as well as g.-692 C>T and g.-556 G>T reported in our previous studies, were analyzed. The bulls with H1H12 and H2H2 exhibited a higher ejaculate volume than those with H2H10 and H9H12, respectively (P < 0.05). Bulls with H11H11 and H2H10 exhibited higher initial sperm motility than those with H2H2 (P < 0.05). The expression levels of INCENP in bulls with H1H12 and H11H11 were significantly higher than those in bulls with H9H12 (P < 0.05), as determined by qRT-PCR. Findings suggest that g.19970 A>G and g.34078 T>G in INCENP both of which appear to change the molecular and biological characteristics of the mRNA transcribed from the locus may serve as a biomarkers of male bovine fertility by affecting alternative splicing mode and binding affinity with the target bta-miR-378.

Synergies between assisted reproduction technologies and functional genomics

This review, is a synopsis of advanced reproductive technologies in farm animals, including the discussion of their limiting factors as revealed by the study of offspring derived from embryos produced in vitro and through cloning. These studies show that the problems of epigenetic mis-programming, which were reported in the initial stages of assisted reproduction, still persist. The importance of whole-genome analyses, including the methylome and transcriptome, in improving embryo biotechnologies in farm animals, are discussed. Genome editing approaches for the improvement of economically-relevant traits in farm animals are also described. Efficient farm animal embryo biotechnologies, including cloning and the most recent technologies such as genome editing, will effectively complement the latest strategies to accelerate genetic improvement of farm animals.

Population-genetic properties of differentiated copy number variations in cattle

While single nucleotide polymorphism (SNP) is typically the variant of choice for population genetics, copy number variation (CNV) which comprises insertion, deletion and duplication of genomic sequence, is an informative type of genetic variation. CNVs have been shown to be both common in mammals and important for understanding the relationship between genotype and phenotype. However, CNV differentiation, selection and its population genetic properties are not well understood across diverse populations. We performed a population genetics survey based on CNVs derived from the BovineHD SNP array data of eight distinct cattle breeds. We generated high resolution results that show geographical patterns of variations and genome-wide admixture proportions within and among breeds. Similar to the previous SNP-based studies, our CNV-based results displayed a strong correlation of population structure and geographical location. By conducting three pairwise comparisons among European taurine, African taurine, and indicine groups, we further identified 78 unique CNV regions that were highly differentiated, some of which might be due to selection. These CNV regions overlapped with genes involved in traits related to parasite resistance, immunity response, body size, fertility, and milk production. Our results characterize CNV diversity among cattle populations and provide a list of lineage-differentiated CNVs.

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

BACKGROUND

The Nordic Red Cattle consisting of three different populations from Finland, Sweden and Denmark are under a joint breeding value estimation system. The long history of recording of production and health traits offers a great opportunity to study production traits and identify causal variants behind them. In this study, we used whole genome sequence level data from 4280 progeny tested Nordic Red Cattle bulls to scan the genome for loci affecting milk, fat and protein yields.

RESULTS

Using a genome-wise significance threshold, regions on Bos taurus chromosomes 5, 14, 23, 25 and 26 were associated with fat yield. Regions on chromosomes 5, 14, 16, 19, 20 and 25 were associated with milk yield and chromosomes 5, 14 and 25 had regions associated with protein yield. Significantly associated variations were found in 227 genes for fat yield, 72 genes for milk yield and 30 genes for protein yield. Ingenuity Pathway Analysis was used to identify networks connecting these genes displaying significant hits. When compared to previously mapped genomic regions associated with fertility, significantly associated variations were found in 5 genes common for fat yield and fertility, thus linking these two traits via biological networks.

CONCLUSION

This is the first time when whole genome sequence data is utilized to study genomic regions affecting milk production in the Nordic Red Cattle population. Sequence level data offers the possibility to study quantitative traits in detail but still cannot unambiguously reveal which of the associated variations is causative. Linkage disequilibrium creates difficulties to pinpoint the causative genes and variations. One solution to overcome these difficulties is the identification of the functional gene networks and pathways to reveal important interacting genes as candidates for the observed effects. This information on target genomic regions may be exploited to improve genomic prediction.

Genome-Wide Analysis Reveals Novel Regulators of Growth in Drosophila melanogaster

Organismal size depends on the interplay between genetic and environmental factors. Genome-wide association (GWA) analyses in humans have implied many genes in the control of height but suffer from the inability to control the environment. Genetic analyses in Drosophila have identified conserved signaling pathways controlling size; however, how these pathways control phenotypic diversity is unclear. We performed GWA of size traits using the Drosophila Genetic Reference Panel of inbred, sequenced lines. We find that the top associated variants differ between traits and sexes; do not map to canonical growth pathway genes, but can be linked to these by epistasis analysis; and are enriched for genes and putative enhancers. Performing GWA on well-studied developmental traits under controlled conditions expands our understanding of developmental processes underlying phenotypic diversity.

Genetic studies in Drosophila have elucidated conserved signaling pathways and environmental factors that together control organismal size. In humans, hundreds of genes are associated with height variation, but these associations have not been performed in a controlled environment. As a result we are still lacking an understanding of the mechanisms creating size variability within a species. Here, under carefully controlled environmental conditions, we identify naturally occurring genetic variants that are associated with size diversity in Drosophila. We identify a cluster of associations close to the kek1 locus, a well-characterized growth regulator, but otherwise find that most variants are located in or close to genes that do not belong to the conserved pathways but may interact with these in a biological network. We validate 33 novel growth regulatory genes that participate in diverse cellular processes, most notably cellular metabolism and cell polarity. This study is the first genome-wide association analysis of natural variants underlying size in Drosophila and our results complement the knowledge we have accumulated on this trait from mutational studies of single genes.