Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat

Soil salinity can impose substantial stress on plant growth and cause significant yield losses. Crop varieties tolerant to salinity stress are needed to sustain yields in saline soils. This requires effective genotyping and phenotyping of germplasm pools to identify novel genes and QTL conferring salt tolerance that can be utilised in crop breeding schemes. We investigated a globally diverse collection of 580 wheat accessions for their growth response to salinity using automated digital phenotyping performed under controlled environmental conditions. The results show that digitally collected plant traits, including digital shoot growth rate and digital senescence rate, can be used as proxy traits for selecting salinity-tolerant accessions. A haplotype-based genome-wide association study was conducted using 58,502 linkage disequilibrium-based haplotype blocks derived from 883,300 genome-wide SNPs and identified 95 QTL for salinity tolerance component traits, of which 54 were novel and 41 overlapped with previously reported QTL. Gene ontology analysis identified a suite of candidate genes for salinity tolerance, some of which are already known to play a role in stress tolerance in other plant species. This study identified wheat accessions that utilise different tolerance mechanisms and which can be used in future studies to investigate the genetic and genic basis of salinity tolerance. Our results suggest salinity tolerance has not arisen from or been bred into accessions from specific regions or groups. Rather, they suggest salinity tolerance is widespread, with small-effect genetic variants contributing to different levels of tolerance in diverse, locally adapted germplasm.

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.

Exploring haplotype block structure, runs of homozygosity, and effective population size among dairy cattle breeds of India

The present study aimed to explore haplotype structure, runs of homozygosity (ROH), effective population size and persistence of gametic phase among three indigenous dairy cattle breeds, viz., Sahiwal (n = 19), Tharparkar (n = 17), and Gir (n = 16) by using BovineHD single nucleotide polymorphism (SNP) genotyping assay. The filtered SNPs after quality control ranged from 44% in Sahiwal to 53% in Gir. The highest number of haplotype blocks was observed in Tharparkar (15,640) and the lowest in Sahiwal (8027) spanning 17.3% and 7.8% of genome, respectively. The average block length was found close to 26 kb which suggests that multiple recombination events fragmented the ancestral haplotypes into smaller sizes. Gir cattle had the largest number of runs of homozygosity (ROH) regions (1762) followed by Tharparkar (1528) and Sahiwal (1138). Without pedigree information, inbreeding coefficients estimated from ROH (F_ROH) revealed that Gir had the highest F_ROH (0.099) proposing more inbreeding rate in this population. Effective population size (N_e) decreased slowly over the last 60 generations and at 13 generations ago; N_e was estimated as 70 for all the three dairy breeds. The highest gametic phase correlation (r = 0.78) was observed for Sahiwal and Tharparkar breed pair suggesting formulation of multi-breed reference population for successful implementation of genomic selection among dairy breeds. The decline in effective population size among native Indian cattle breeds may help in formulating strategies for conservation and genetic improvement of native germplasm for future use.

The growth hormone gene polymorphism and its relationship to performance and carcass features in Egyptian Awassi lambs

The main purpose of the existing experiment was to assess the allelic and genotypic polymorphisms of the Growth hormone (GH) gene and its correlation with growth indices, efficiency of consumed feed, some body indices and carcass traits of the Egyptian Awassi sheep. Forty Egyptian Awassi male lambs were selected for their growing indices (post-weaning daily gain, marketing weight, and weaning weight), feed efficiency (consumed feed and of consumed feed), body conformational indicators (skeletal muscle index, relative body index, body mass index, and body index), and carcass features (dressing %, hot carcass weight, fore-legs %, neck %, loin %, ribs %, abdominal fat %, Tail % and hind-legs %). The polymerase chain reaction-restricted fragment length polymorphism (PCR-RFLP) tool was applied to detect the genotypic and allelic GH gene polymorphisms properties. The PCR-RFLP analysis identified three main genotypes (AA, AB and BB) and two main alleles (A and B). The GH genotype (AA or AB) exhibited moderate significant influence (P < 0.05) on marketing weight, Loin% and Tail%. Also, genotype (AB or BB) of expressed GH gene significantly (P < 0.01) influence on consumed feed, post-weaning daily gain, neck% and body mass index, whereas, it had no influence on the phenotypic values of the other characteristics investigated. The presence of the A allele in the genotype was markedly associated (P < 0.01) with consumed feed, body mass index and post-weaning daily growth; conversely, the presence of the B allele in the genotype was significantly related (P < 0.05) with marketing weight, loin %, and tail %. While, GH gene expression was revealed to be highly significant (P < 0.01) in relation to post-weaning daily growth, feed intake, and neck %. According to the findings, determining the associations between GH gene variation and growth, efficiency of consumed feed, body measurements, and carcass features of Egyptian Awassi sheep and applying marker assisted selection with the GH gene to improve these traits is warranted and will be of significant economic value to sheep production.

Gene-Based Genome-Wide Association Study Identified Genes for Agronomic Traits in Maize

A gene integrates the effects of all SNPs in its sequence span, which benefits the genome-wide association study. To explore gene-level variations affecting economic traits in maize, we extended the SNP-based GWAS analysis software Single-RunKing developed by our team to gene-based GWAS, which used the FaST-LMM algorithm to convert the linear mixed model into simple linear model association analysis. An F-test statistic was formulated to test and identify candidate genes. We compared the statistical efficiency of using 80% principal components (EPC), the first principal component (FPC), and all SNP markers (ALLSNP) as independent variables, which predecessors commonly used to integrate SNPs and represent genes. With a Huazhong Agricultural University (HAU) genomic dataset of 2.65M SNPs from 540 maize plants, 34,774 genes were annotated across the whole genome. Genome-wide association studies with 20 agronomic traits were performed using the software developed here. Another maize dataset from the Ames panel (AP) was also analyzed. The EPC method fits the model well and has good statistical efficiency. It not only overcomes the false negative problem when using all SNP markers for analysis (ALLSNP) but also solves the false positive problem of its corresponding simple linear model method EPCLM. Compared with FPC, the EPC method has higher statistical efficiency. A total of 132 quantitative trait genes (QTG) were identified for the 20 traits from HAU maize dataset and one trait of AP maize.

Genome-Wide Associative Study of Phenotypic Parameters of the 3D Body Model of Aberdeen Angus Cattle with Multiple Depth Cameras

Simple Summary

This article aims to develop a new approach to the lifetime evaluation of cattle by 3-D visualization of economic-biological and genetic features. The following indicators were selected as phenotypic features: chest width and chest girth retrieved by 3-D model and meat output on the bones. Correlation analysis showed a reliable positive relationship between chest width and meat output on the bones, which can potentially be used for lifetime evaluation of meat productivity of animals. Genome-wide associations analysis revealed the following potential loci of quantitative traits on cattle chromosomes for chest width, chest girth, and meat output on bones.

Abstract

In beef cattle breeding, genome-wide association studies (GWAS) using single nucleotide polymorphisms (SNPs) arrays can reveal many loci of various production traits, such as growth, productivity, and meat quality. With the development of genome sequencing technologies, new opportunities are opening up for more accurate identification of areas associated with these traits. This article aims to develop a novel approach to the lifetime evaluation of cattle by 3-D visualization of economic-biological and genetic features. The purpose of this study was to identify significant variants underlying differences in the qualitative characteristics of meat, using imputed data on the sequence of the entire genome. Samples of biomaterial of young Aberdeen-Angus breed cattle (n = 96) were the material for carrying out genome-wide SNP genotyping. Genotyping was performed using a high-density DNA chip Bovine GPU HD BeadChip (Illumina Inc., San Diego, CA, USA), containing ~150 thousand SNPs. The following indicators were selected as phenotypic features: chest width and chest girth retrieved by 3-D model and meat output on the bones. Correlation analysis showed a reliable positive relationship between chest width and meat output on the bones, which can potentially be used for lifetime evaluation of meat productivity of animals.

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.

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.

Challenging Sustainable and Innovative Technologies in Cheese Production: A Review

It is well known that cheese yield and quality are affected by animal genetics, milk quality (chemical, physical, and microbiological), production technology, and the type of rennet and dairy cultures used in production. Major differences in the same type of cheese (i.e., hard cheese) are caused by the rennet and dairy cultures, which affect the ripening process. This review aims to explore current technological advancements in animal genetics, methods for the isolation and production of rennet and dairy cultures, along with possible applications of microencapsulation in rennet and dairy culture production, as well as the challenge posed to current dairy technologies by the preservation of biodiversity. Based on the reviewed scientific literature, it can be concluded that innovative approaches and the described techniques can significantly improve cheese production.

Distribution of Copy Number Variation in SYT11 Gene and Its Association with Growth Conformation Traits in Chinese Cattle

Simple Summary

It is known that many different breeds of cattle are widely distributed in China. However, due to a lengthy selection of draught direction, there are obvious shortcomings in Chinese cattle, such as less meat production, slow weight gain, poor meat quality, and a lack of specialized beef cattle breeds. Animal breeding heavily benefits from molecular technologies, among which molecular genetic markers were widely used to improve the economic traits of beef cattle. Because the copy number variation (CNV) involves a longer DNA sequence or even the entire functional gene, it may have a greater impact on the phenotype. Recent studies have indicated that CNVs are widespread in the Chinese cattle genome. By investigating the effects of CNVs on gene expression and cattle traits, we aim to find those genomic variations which could significantly affect cattle traits, and which could provide a basis for genetic selection and molecular breeding of local Chinese cattle.

Abstract

Currently, studies of the SYT11 gene mainly focus on neurological diseases such as schizophrenia and Parkinson’s disease. However, some studies have shown that the C2B domain of SYT11 can interact with RISC components and affect the gene regulation of miRNA, which is important for cell differentiation, proliferation, and apoptosis, and therefore has an impact on muscle growth and development in animals. The whole-genome resequencing data detected a CNV in the SYT11 gene, and this may affect cattle growth traits. In this study, CNV distribution of 672 individuals from four cattle breeds, Yunling, Pinan, Xianan, and Qinchuan, were detected by qPCR. The relationship between CNV, gene expression and growth traits was further investigated. The results showed that the proportion of multiple copy types was the largest in all cattle breeds, but there were some differences among different breeds. The normal type had higher gene expression than the abnormal copy type. The CNVs of the SYT11 gene were significantly correlated with body length, cannon circumference, chest depth, rump length, and forehead size of Yunling cattle, and was significantly correlated with the bodyweight of Xianan cattle, respectively. These data improve our understanding of the effects of CNV on cattle growth traits. Our results suggest that the CNV of SYT11 gene is a protentional molecular marker, which may be used to improve growth traits in Chinese cattle.

A SNP-based GWAS and functional haplotype-based GWAS of flag leaf-related traits and their influence on the yield of bread wheat (Triticum aestivum L.)

The genetic architecture of five flag leaf morphology traits was dissected by the functional haplotype-based GWAS and a standard SNP-based GWAS in a diverse population consisting of 197 varieties. Flag leaf morphology (FLM) is a critical factor affecting plant architecture and grain yield in wheat. The genetic architecture of FLM traits has been extensively studied with QTL mapping in bi-parental populations, while few studies exploited genome-wide association studies (GWAS) in diverse populations. In this study, a panel of 197 elite and historical varieties from China was evaluated for five FLM traits including the length (FLL), width (FLW), ratio (FLR), area (FLA) and angle (FLANG) as well as yield in nine environments. Based on the phenotypic correlation between yield and FLL (-0.43), FLA (- 0.32) and FLW (0.11), an empirical FLM index combining the three FLM traits proved to be a good predictor for yield. Two GWAS approaches were applied to dissect the genetic architecture of five FLM traits with a Wheat660K SNP array. The functional haplotype-based GWAS revealed 6, 5 and 7 QTL for FLANG, FLL and FLR, respectively, whereas two QTL for FLW and one for FLR were identified by the standard SNP-based GWAS. Due to co-localization, there were 18 independent QTL and 10 of them were close to known ones. One co-localized QTL on chromosome 5A was associated with FLL, FLANG and FLR. Moreover, both GWAS approaches identified a novel QTL for FLR on chromosome 6B which was not reported in previous studies. This study provides new insights into the relationship between FLM and yield and broadens our understanding of the genetic architecture of FLM traits in wheat.

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.

A Large-Scale Genome-Wide Association Study of Epistasis Effects of Production Traits and Daughter Pregnancy Rate in U.S. Holstein Cattle

Epistasis is widely considered important, but epistasis studies lag those of SNP effects. Genome-wide association study (GWAS) using 76,109 SNPs and 294,079 first-lactation Holstein cows was conducted for testing pairwise epistasis effects of five production traits and three fertility traits: milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FPC), protein percentage (PPC), and daughter pregnancy rate (DPR). Among the top 50,000 pairwise epistasis effects of each trait, the five production traits had large chromosome regions with intra-chromosome epistasis. The percentage of inter-chromosome epistasis effects was 1.9% for FPC, 1.6% for PPC, 10.6% for MY, 29.9% for FY, 39.3% for PY, and 84.2% for DPR. Of the 50,000 epistasis effects, the number of significant effects with log10(1/p) ≥ 12 was 50,000 for FPC and PPC, and 10,508, 4763, 4637 and 1 for MY, FY, PY and DPR, respectively, and A × A effects were the most frequent epistasis effects for all traits. Majority of the inter-chromosome epistasis effects of FPC across all chromosomes involved a Chr14 region containing DGAT1, indicating a potential regulatory role of this Chr14 region affecting all chromosomes for FPC. The epistasis results provided new understanding about the genetic mechanism underlying quantitative traits in Holstein cattle.

Prospecting genomic regions associated with milk production traits in Egyptian buffalo

The objectives of the current study were to detect putative genomic loci and to identify candidate genes associated with milk production traits in Egyptian buffalo. A total number of 161 479 daily milk yield (DMY) records and 60 318 monthly measures for fat and protein percentages (FP and PP, respectively), along with fat and protein yields (FY and PY, respectively) from 1670 animals were used. Genotyping was performed using Axiom® Buffalo Genotyping 90 K array. Genome-wide association study (GWAS) for each trait was performed using PLINK. After Bonferroni correction, 47 SNPs were associated with one or more milk production traits. These SNPs were distributed over 36 quantitative trait loci (QTL) and located on 20 buffalo chromosomes (BBU). For the 47 SNPs, one was overlapped for three traits (DMY, FY, and PY), six were associated with two traits (one for PP and PY and five for FY and PY) while the rest were associated with only one trait. Out of 36 identified QTL, eleven were overlapped with previously reported loci in buffalo and/or cattle populations. Some of these SNPs are placed within or close to potential candidate genes, for example: TPD52, ZBTB10, RALYL and SNX16 on BBU15, ADGRD1 on BBU17, ESRRG on BBU5 and GRIP1 on BBU4. This is the first reported study between genome-wide markers and milk components in Egyptian buffalo. Our findings provide useful information to explore the genetic mechanisms and relevant genes contributing to the variation in milk production traits. Further confirmation studies with larger population size are necessary to validate the findings and detect the causal genetic variants.

Genome-Wide Association Analysis for Tuber Dry Matter and Oxidative Browning in Water Yam (Dioscorea alata L.)

Yam (Dioscorea spp.) is a nutritional and medicinal staple tuber crop grown in the tropics and sub-tropics. Among the food yam species, water yam (Dioscorea alata L.) is the most widely distributed and cultivated species worldwide. Tuber dry matter content (DMC) and oxidative browning (OxB) are important quality attributes that determine cultivar acceptability in water yam. This study used a single nucleotide polymorphism (SNP) assay from a diversity arrays technology (DArT) platform for a genome-wide association study (GWAS) of the two quality traits in a panel of 100 water yam clones grown in three environments. The marker-trait association analysis identified significant SNPs associated with tuber DMC on chromosomes 6 and 19 and with OxB on chromosome 5. The significant SNPs cumulatively explained 45.87 and 12.74% of the total phenotypic variation for the tuber DMC and OxB, respectively. Gene annotation for the significant SNP loci identified important genes associated in the process of the proteolytic modification of carbohydrates in the dry matter accumulation pathway as well as fatty acid β-oxidation in peroxisome for enzymatic oxidation. Additional putative genes were also identified in the peak SNP sites for both tuber dry matter and enzymatic oxidation with unknown functions. The results of this study provide valuable insight for further dissection of the genetic architecture of tuber dry matter and enzymatic oxidation in water yam. They also highlight SNP variants and genes useful for genomics-informed selection decisions in the breeding process for improving food quality traits in water yam.

Ancestral Haplotype Mapping for GWAS and Detection of Signatures of Selection in Admixed Dairy Cattle of Kenya

Understanding the genetic structure of adaptation and productivity in challenging environments is necessary for designing breeding programs that suit such conditions. Crossbred dairy cattle in East Africa resulting from over 60 years of crossing exotic dairy breeds with indigenous cattle plus inter se matings form a highly variable admixed population. This population has been subject to natural selection in response to environmental stresses, such as harsh climate, low-quality feeds, poor management, and strong disease challenge. Here, we combine two complementary sets of analyses, genome-wide association (GWA) and signatures of selection (SoS), to identify genomic regions that contribute to variation in milk yield and/or contribute to adaptation in admixed dairy cattle of Kenya. Our GWA separates SNP effects due to ancestral origin of alleles from effects due to within-population linkage disequilibrium. The results indicate that many genomic regions contributed to the high milk production potential of modern dairy breeds with no region having an exceptional effect. For SoS, we used two haplotype-based tests to compare haplotype length variation within admixed and between admixed and East African Shorthorn Zebu cattle populations. The integrated haplotype score (iHS) analysis identified 16 candidate regions for positive selection in the admixed cattle while the between population Rsb test detected 24 divergently selected regions in the admixed cattle compared to East African Shorthorn Zebu. We compare the results from GWA and SoS in an attempt to validate the most significant SoS results. Only four candidate regions for SoS intersect with GWA regions using a low stringency test. The identified SoS candidate regions harbored genes in several enriched annotation clusters and overlapped with previously found QTLs and associations for different traits in cattle. If validated, the GWA and SoS results indicate potential for SNP-based genomic selection for genetic improvement of smallholder crossbred cattle.

Genome-wide association studies of lactation yields of milk, fat, protein and somatic cell score in New Zealand dairy goats

Background

Identifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations. Genome-wide association studies were implemented to detect genetic regions that are significantly associated with effects on lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS) in New Zealand dairy goats.

Methods

A total of 4,840 goats were genotyped with the Caprine 50 K SNP chip (Illumina Inc., San Diego, CA). After quality filtering, 3,732 animals and 41,989 SNPs were analysed assuming an additive linear model. Four GWAS models were performed, a single-SNP additive linear model and three multi-SNP BayesC models. For the single-SNP GWAS, SNPs were fitted individually as fixed covariates, while the BayesC models fit all SNPs simultaneously as random effects. A cluster of significant SNPs were used to define a haplotype block whose alleles were fitted as covariates in a Bayesian model. The corresponding diplotypes of the haplotype block were then fit as class variables in another Bayesian model.

Results

Across all four traits, a total of 43 genome-wide significant SNPs were detected from the SNP GWAS. At a genome-wide significance level, the single-SNP analysis identified a cluster of variants on chromosome 19 associated with MY, FY, PY, and another cluster on chromosome 29 associated with SCS. Significant SNPs mapped in introns of candidate genes (45%), in intergenic regions (36%), were 0-5 kb upstream or downstream of the closest gene (14%) or were synonymous substitutions (5%). The most significant genomic window was located on chromosome 19 explaining up to 9.6% of the phenotypic variation for MY, 8.1% for FY, 9.1% for PY and 1% for SCS.

Conclusions

The quantitative trait loci for yield traits on chromosome 19 confirms reported findings in other dairy goat populations. There is benefit to be gained from using these results for genomic selection to improve milk production in New Zealand dairy goats.

Selecting Closely-Linked SNPs Based on Local Epistatic Effects for Haplotype Construction Improves Power of Association Mapping

Genome-wide association studies (GWAS) have gained central importance for the identification of candidate loci underlying complex traits. Single nucleotide polymorphism (SNP) markers are mostly used as genetic variants for the analysis of genotype-phenotype associations in populations, but closely linked SNPs that are grouped into haplotypes are also exploited. The benefit of haplotype-based GWAS approaches vs. SNP-based approaches is still under debate because SNPs in high linkage disequilibrium provide redundant information. To overcome some constraints of the commonly-used haplotype-based GWAS in which only consecutive SNPs are considered for haplotype construction, we propose a new method called functional haplotype-based GWAS (FH GWAS). FH GWAS is featured by combining SNPs into haplotypes based on the additive and epistatic effects among SNPs. Such haplotypes were termed functional haplotypes (FH). As shown by simulation studies, the FH GWAS approach clearly outperformed the SNP-based approach unless the minor allele frequency of the SNPs making up the haplotypes is low and the linkage disequilibrium between them is high. Applying FH GWAS for the trait flowering time in a large Arabidopsis thaliana population with whole-genome sequencing data revealed its potential empirically. FH GWAS identified all candidate regions which were detected in SNP-based and two other haplotype-based GWAS approaches. In addition, a novel region on chromosome 4 was solely detected by FH GWAS. Thus both the results of our simulation and empirical studies demonstrate that FH GWAS is a promising method and superior to the SNP-based approach even if almost complete genotype information is available.

Genome-wide association study of milk and reproductive traits in dual-purpose Xinjiang Brown cattle

Background

Dual-purpose cattle are more adaptive to environmental challenges than single-purpose dairy or beef cattle. Balance among milk, reproductive, and mastitis resistance traits in breeding programs is therefore more critical for dual-purpose cattle to increase net income and maintain well-being. With dual-purpose Xinjiang Brown cattle adapted to the Xinjiang Region in northwestern China, we conducted genome-wide association studies (GWAS) to dissect the genetic architecture related to milk, reproductive, and mastitis resistance traits. Phenotypic data were collected for 2410 individuals measured during 1995–2017. By adding another 445 ancestors, a total of 2855 related individuals were used to derive estimated breeding values for all individuals, including the 2410 individuals with phenotypes. Among phenotyped individuals, we genotyped 403 cows with the Illumina 150 K Bovine BeadChip.

Results

GWAS were conducted with the FarmCPU (Fixed and random model circulating probability unification) method. We identified 12 markers significantly associated with six of the 10 traits under the threshold of 5% after a Bonferroni multiple test correction. Seven of these SNPs were in QTL regions previously identified to be associated with related traits. One identified SNP, BovineHD1600006691, was significantly associated with both age at first service and age at first calving. This SNP directly overlapped a QTL previously reported to be associated with calving ease. Within 160 Kb upstream and downstream of each significant SNP identified, we speculated candidate genes based on functionality. Four of the SNPs were located within four candidate genes, including CDH2, which is linked to milk fat percentage, and GABRG2, which is associated with milk protein yield.

Conclusions

These findings are beneficial not only for breeding through marker-assisted selection, but also for genome editing underlying the related traits to enhance the overall performance of dual-purpose cattle.

Association of lipid-related genes implicated in conceptus elongation with female fertility traits in dairy cattle

Elongation of the preimplantation conceptus is a requirement for pregnancy success in ruminants, and failures in this process are highly associated with subfertility in dairy cattle. Identifying genetic markers that are related to early conceptus development and survival and utilizing these markers in selective breeding can improve the reproductive efficiency of dairy herds. Here, we evaluated the association of 1,679 SNP markers within or close to 183 candidate genes involved in lipid metabolism of the elongating conceptus with different fertility traits in US Holstein cattle. A total of 27,371 bulls with predicted transmitting ability records for daughter pregnancy rate, cow conception rate, and heifer conception rate were used as the discovery population. The associations found in the discovery population were validated using 2 female populations (1,122 heifers and 2,138 lactating cows) each with 4 fertility traits, including success to first insemination, number of services per conception, age at first conception for heifers, or days open for cows. Marker effects were estimated using a linear mixed model with SNP genotype as a linear covariate and a random polygenic effect. After multiple testing correction, 39 SNP flagging 27 candidate genes were associated with at least one fertility trait in the discovery population. Of these 39 markers, 3 SNP were validated in the heifer population and 4 SNP were validated in the cow population. The 3 SNP validated in heifers are located within or near genes CAT, MYOF, and RBP4, and the 4 SNP validated in lactating cows are located within or close to genes CHKA, GNAI1, and HMOX2. These validated genes seem to be relevant for reducing pregnancy losses, and the SNP within these genes are excellent candidates for inclusion in genomic tests to improve reproductive performance in dairy cattle.

Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.

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.

Across-breed validation study confirms and identifies new loci associated with sexual precocity in Brahman and Nellore cattle

The aim of this study was to identify candidate regions associated with sexual precocity in Bos indicus. Nellore and Brahman were set as validation and discovery populations, respectively. SNP selected in Brahman to validate in Nellore were from gene regions affecting reproductive traits (G1) and significant SNP (p ≤ 10^-3 ) from a meta-analysis (G2). In the validation population, early pregnancy (EP) and scrotal circumference (SC) were evaluated. To perform GWAS in validation population, we used regression and Bayes C. SNP with p ≤ 10^-3 in regression and Bayes factor ≥3 in Bayes C were deemed significant. Significant SNP (for EP or SC) or SNP in their ±250 Kb vicinity region, which were in at least one discovery set (G1 or G2), were considered validated. SNP identified in both G1 and G2 were considered candidate. For EP, 145 SNP were validated in G1 and 41 in G2, and for SC, these numbers were 14 and 2. For EP, 21 candidate SNP were detected (G1 and G2). For SC, no candidate SNP were identified. Validated SNP and their vicinity region were located close to quantitative trait loci or genes related to reproductive traits and were enriched in gene ontology terms related to reproductive success. These are therefore strong candidate regions for sexual precocity in Nellore and Brahman.

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.

Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle

We performed genome-wide association analyses for milk, fat, and protein yields and somatic cell score based on lactation stages in the first 3 parities of Canadian Ayrshire, Holstein, and Jersey cattle. The genome-wide association analyses were performed considering 3 different lactation stages for each trait and parity: from 5 to 95, from 96 to 215, and from 216 to 305 d in milk. Effects of single nucleotide polymorphisms (SNP) for each lactation stage, trait, parity, and breed were estimated by back-solving the direct breeding values estimated using the genomic best linear unbiased predictor and single-trait random regression test-day models containing only the fixed population average curve and the random genomic curves. To identify important genomic regions related to the analyzed lactation stages, traits, parities and breeds, moving windows (SNP-by-SNP) of 20 adjacent SNP explaining more than 0.30% of total genetic variance were selected for further analyses of candidate genes. A lower number of genomic windows with a relatively higher proportion of the explained genetic variance was found in the Holstein breed compared with the Ayrshire and Jersey breeds. Genomic regions associated with the analyzed traits were located on 12, 8, and 15 chromosomes for the Ayrshire, Holstein, and Jersey breeds, respectively. Especially for the Holstein breed, many of the identified candidate genes supported previous reports in the literature. However, well-known genes with major effects on milk production traits (e.g., diacylglycerol O-acyltransferase 1) showed contrasting results among lactation stages, traits, and parities of different breeds. Therefore, our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the analyzed traits across breeds, parities, and lactation stages. Further functional studies are needed to validate our findings in independent populations.

Invited review: Advances and applications of random regression models: From quantitative genetics to genomics

An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM). Random regression models enable fitting random genetic and environmental effects over time, which results in higher accuracy of estimated breeding values compared with other statistical approaches. In addition, RRM provide insights about temporal variation of biological processes and the physiological implications underlying the studied traits. Despite the fact that genomic information has substantially contributed to increase the rates of genetic progress for a variety of economically important traits in several livestock species, less attention has been given to longitudinal traits in recent years. However, including genomic information to evaluate longitudinal traits using RRM is a feasible alternative to yield more accurate selection and culling decisions, because selection of young animals may be based on the complete pattern of the production curve with higher accuracy compared with the use of traditional parent average (i.e., without genomic information). Moreover, RRM can be used to estimate SNP effects over time in genome-wide association studies. Thus, by analyzing marker associations over time, regions with higher effects at specific points in time are more likely to be identified. Despite the advances in applications of RRM in genetic evaluations, more research is needed to successfully combine RRM and genomic information. Future research should provide a better understanding of the temporal variation of biological processes and their physiological implications underlying the longitudinal traits.

Effects of a novel missense polymorphism within the SIGLEC5 gene on fertility traits in Holstein-Friesian cattle

The aim of the study was to find functional polymorphism within two exons of the SIGLEC5 (sialic acid-binding Ig-like lectin-5) gene and to examine its effects on the production and fertility traits of cows and bulls. Two hundred seventytwo Holstein-Friesian cows and 574 bulls were included in the study. Novel missense polymorphism (A > G) within exon 3 causing substitution of amino acid arginine by glutamate in position 260 of SIGLEC5 protein (R260Q) was identified by sequencing and digestion by restriction enzyme Msp I. Basic production and fertility traits of cows and estimated breeding values (EBV) of bulls were analysed. The study demonstrated a significant association of SIGLEC5 R260Q polymorphism with days open and calving interval in cows as well as with breeding value for calving interval in bulls. An opposite effect of SIGLEC5 alleles for production and fertility traits was observed: the allele G increased the breeding value for the protein yield, while the allele A increased the breeding value for the calving interval. The current study suggests the involvement of SIGLEC5 R260Q polymorphism in biological processes related to fertility traits. This finding can be applied as a biomarker for a genetic improvement programme in Holstein-Friesian cattle.

The use of mid-infrared spectra to map genes affecting milk composition

The aim of this study was to investigate the feasibility of using mid-infrared (MIR) spectroscopy analysis of milk samples to increase the power and precision of genome-wide association studies (GWAS) for milk composition and to better distinguish linked quantitative trait loci (QTL). To achieve this goal, we analyzed phenotypic data of milk composition traits, related MIR spectra, and genotypic data comprising 626,777 SNP on 5,202 Holstein, Jersey, and crossbred cows. We performed a conventional GWAS on protein, lactose, fat, and fatty acid concentrations in milk, a GWAS on individual MIR wavenumbers, and a partial least squares regression (PLS), which is equivalent to a multi-trait GWAS, exploiting MIR data simultaneously to predict SNP genotypes. The PLS detected most of the QTL identified using single-trait GWAS, usually with a higher significance value, as well as previously undetected QTL for milk composition. Each QTL tends to have a different pattern of effects across the MIR spectrum and this explains the increased power. Because SNP tracking different QTL tend to have different patterns of effect, it was possible to distinguish closely linked QTL. Overall, the results of this study suggest that using MIR data through either GWAS or PLS analysis applied to genomic data can provide a powerful tool to distinguish milk composition QTL.

Identification of quantitative trait loci for milk protein percentage in Murrah buffaloes

Milk protein is an important constituent of milk in buffaloes and is moderately heritable. The milk protein percentage varies significantly between breeds/herds/species. Buffaloes can be selected for higher milk protein percentage and this paper provides QTLs for marker assisted selection in buffaloes. The milk protein percentage records on 2,028 daughters belonging to 12 half sib families were analyzed for the identification of QTLs on 8 chromosomes in buffaloes using chromosome scans. The single marker analysis revealed 74 markers to be associated with milk protein percentage in 12 sire families. When common markers were removed from the analysis, 51 markers remained. The Interval mapping using R/qtl identified 69 QTLs in 12 half sib families on 8 chromosomes of buffalo. The meta QTL analysis defined 25 consensus QTL regions in buffaloes for milk protein percentage. Most of the QTLs identified have been reported for cattle however few new chromosomal locations were also identified to be associated with milk protein percentage in buffaloes. Comparative genomics revealed 1117 genes underlying the QTL regions associated with milk protein percentage. Among these, 109 genes were directly associated with protein metabolism. The protein-protein interaction among the genes and gene ontology analysis and pathways have been identified. These 109 genes have potential to be candidate genes for milk protein percentage in buffaloes.

Integrative analysis of APOL3 gene CNV for adult cattle stature

Copy number variations (CNVs) have been identified as another important structural variation of genome. In recent years, a large amount of CNVRs have been identified in humans and animals. However, association and dosage effects studies of CNVs are very limited. Apolipoprotein L3 (APOL3) gene plays a central role in modulating gene transcription and is located within a CNVR that encompasses quantitative trait locis (QTLs) for economic traits like meat quality. Herein, we analyzed the CNV polymorphism of APOL3 in 421 individuals from five distinct cattle breeds, and then correlated their genotypes with growth traits. Association analysis revealed that the APOL3 CNV was significantly associated with hip height and cannon circumference of Xianan (XN) cattle (P < .01), and visibly associated with body slanting length and hucklebone width of Pinan (PN) cattle (P < .05). Overall, the data provide evidence for the functional role of APOL3 CNV and a basis for future applications in cattle breeding.

A Large-Scale Genome-Wide Association Study in U.S. Holstein Cattle

Genome-wide association study (GWAS) is a powerful approach to identify genomic regions and genetic variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. We conducted a large-scale GWAS using 294,079 first-lactation Holstein cows and identified new additive and dominance effects on five production traits, three fertility traits, and somatic cell score. Four chromosomes had the most significant SNP effects on the five production traits, a Chr14 region containing DGAT1 mostly had positive effects on fat yield and negative effects on milk and protein yields, the 88.07-89.60 Mb region of Chr06 with SLC4A4, GC, NPFFR2, and ADAMTS3 for milk and protein yields, the 30.03-36.67 Mb region of Chr20 with C6 and GHR for milk yield, and the 88.19-88.88 Mb region with ABCC9 as well as the 91.13-94.62 Mb region of Chr05 with PLEKHA5, MGST1, SLC15A5, and EPS8 for fat yield. For fertility traits, the SNP in GC of Chr06, and the SNPs in the 65.02-69.43 Mb region of Chr01 with COX17, ILDR1, and KALRN had the most significant effects for daughter pregnancy rate and cow conception rate, whereas SNPs in AFF1 of Chr06, the 47.54-52.79 Mb region of Chr07, TSPAN4 of Chr29, and NPAS1 of Chr18 had the most significant effects for heifer conception rate. For somatic cell score, GC of Chr06 and PRLR of Chr20 had the most significant effects. A small number of dominance effects were detected for the production traits with far lower statistical significance than the additive effects and for fertility traits with similar statistical significance as the additive effects. Analysis of allelic effects revealed the presence of uni-allelic, asymmetric, and symmetric SNP effects and found the previously reported DGAT1 antagonism was an extreme antagonistic pleiotropy between fat yield and milk and protein yields among all SNPs in this study.

Increasing accuracy of genomic selection in presence of high density marker panels through the prioritization of relevant polymorphisms

BACKGROUND

It becomes clear that the increase in the density of marker panels and even the use of sequence data didn't result in any meaningful increase in the accuracy of genomic selection (GS) using either regression (RM) or variance component (VC) approaches. This is in part due to the limitations of current methods. Association model are well over-parameterized and suffer from severe co-linearity and lack of statistical power. Even when the variant effects are not directly estimated using VC based approaches, the genomic relationships didn't improve after the marker density exceeded a certain threshold. SNP prioritization-based fixation index (F_ST) scores were used to track the majority of significant QTL and to reduce the dimensionality of the association model.

RESULTS

Two populations with average LD between adjacent markers of 0.3 (P1) and 0.7 (P2) were simulated. In both populations, the genomic data consisted of 400 K SNP markers distributed on 10 chromosomes. The density of simulated genomic data mimics roughly 1.2 million SNP markers in the bovine genome. The genomic relationship matrix (G) was calculated for each set of selected SNPs based on their F_ST score and similar numbers of SNPs were selected randomly for comparison. Using all 400 K SNPs, 46% of the off-diagonal elements (OD) were between - 0.01 and 0.01. The same portion was 31, 23 and 16% when 80 K, 40 K and 20 K SNPs were selected based on F_ST scores. For randomly selected 20 K SNP subsets, around 33% of the OD fell within the same range. Genomic similarity computed using SNPs selected based on F_ST scores was always higher than using the same number of SNPs selected randomly. Maximum accuracies of 0.741 and 0.828 were achieved when 20 and 10 K SNPs were selected based on F_ST scores in P₁ and P₂, respectively.

CONCLUSIONS

Genomic similarity could be maximized by the decrease in the number of selected SNPs, but it also leads to a decrease in the percentage of genetic variation explained by the selected markers. Finding the balance between these two parameters could optimize the accuracy of GS in the presence of high density marker panels.

Short communication: Replication of genome-wide association studies for milk production traits in Chinese Holstein by an efficient rotated linear mixed model

Milk is regarded as an important nutrient for humans, and Chinese Holstein cows provide high-quality milk for billions of Chinese people. Therefore, detecting quantitative trait nucleotides (QTN) or candidate genes for milk production traits in Chinese Holstein is important. In this study, we performed genome-wide association studies (GWAS) in a Chinese Holstein population of 6,675 cows and 71,633 SNP using deregressed proofs (DRP) as phenotypes to replicate our previous study in a population of 1,815 cows and 39,163 SNP using estimated breeding values (EBV) as phenotypes. The associations between 3 milk production traits-milk yield (MY), fat percentage (FP), and protein percentage (PP)-and the SNP were determined by using an efficient rotated linear mixed model, which benefits from linear transformations of genomic estimated values and Eigen decomposition of the genomic relationship matrix algorithm. In total, we detected 94 SNP that were significantly associated with one or more milk production traits, including 7 SNP for MY, 76 for FP, and 36 for PP; 87% of these SNP were distributed across Bos taurus autosomes 14 and 20. In total, 83 SNP were found to be located within the reported quantitative trait loci (QTL) regions, and one novel segment (between 1.41 and 1.49 Mb) on chromosome 14 was significantly associated with FP, which could be an important candidate QTL region. In addition, the detected intervals were narrowed down from the reported regions harboring causal variants. The top significant SNP for the 3 traits was ARS-BFGL-NGS-4939, which is located within the DGAT1 gene. Five detected genes (CYHR1, FOXH1, OPLAH, PLEC, VPS28) have effects on all 3 traits. Our study provides a suite of QTN, candidate genes, and a novel QTL associated with milk production traits, and thus forms a solid basis for genomic selection and molecular breeding for milk production traits in Chinese Holstein.

Genome-wide association study for longevity in the Holstein cattle population

Longevity is one of the most important traits determining dairy cow profitability. In the last decades dairy cows suffered a lowering in the age at culling. With the aim to identify the genes involved in longevity, dates of birth, yields, dates of calving during lifespan and culling dates were collected for 946 culled cows which had been genotyped with the Bovine High Density panel. Using the GenABEL package in R, genome-wide association analysis was performed on three potential traits of longevity: (1) 'days in production,' (2) 'days in herd,' (3) number of calvings over lifespan.' Five genome-wide significant single nucleotide polymorphisms (SNPs) associated with all three longevity traits were detected. Several consecutive SNPs identified on chromosomes 16 and 30 indicated the presence of two suggestive quantitative trait loci (QTL). The genes comprised in the QTL regions had biological functions related to fertility, reproductive disorders, heat stress and welfare of cows. These findings might contribute to improving breeding strategies to improve longevity.

Genetics and genomics of reproductive disorders in Canadian Holstein cattle

In Canada, reproductive disorders known to affect the profitability of dairy cattle herds have been recorded by producers on a voluntary basis since 2007. Previous studies have shown the feasibility of using producer-recorded health data for genetic evaluations. Despite low heritability estimates and limited availability of phenotypic information, sufficient genetic variation has been observed for those traits to indicate that genetic progress, although slow, can be achieved. Pedigree- and genomic-based analyses were performed on producer-recorded health data of reproductive disorders, including retained placenta (RETP), metritis (METR), and cystic ovaries (CYST) using traditional BLUP and single-step genomic BLUP. Genome-wide association studies and functional analyses were carried out to unravel significant genomic regions and biological pathways, and to better understand the genetic mechanisms underlying RETP, METR, and CYST. Heritability estimates (posterior standard deviation in parentheses) were 0.02 (0.003), 0.01 (0.004), and 0.02 (0.003) for CYST, METR, and RETP, respectively. A moderate to strong genetic correlation of 0.69 (0.102) was found between METR and RETP. Averaged over all traits, sire proof reliabilities increased by approximately 11 percentage points with the incorporation of genomic data using a multiple-trait linear model. Biological pathways and associated genes underlying the studied traits were identified and will contribute to a better understanding of the biology of these 3 health disorders in dairy cattle.

Detection of genome-wide structural variations in the Shanghai Holstein cattle population using next-generation sequencing

Objective

The Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction.

Methods

In our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA).

Results

The average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle.

Conclusion

Structural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience.

Genome-wide mapping of quantitative trait loci in admixed populations using mixed linear model and Bayesian multiple regression analysis

Background

Population stratification and cryptic relationships have been the main sources of excessive false-positives and false-negatives in population-based association studies. Many methods have been developed to model these confounding factors and minimize their impact on the results of genome-wide association studies. In most of these methods, a two-stage approach is applied where: (1) methods are used to determine if there is a population structure in the sample dataset and (2) the effects of population structure are corrected either by modeling it or by running a separate analysis within each sub-population. The objective of this study was to evaluate the impact of population structure on the accuracy and power of genome-wide association studies using a Bayesian multiple regression method.

Methods

We conducted a genome-wide association study in a stochastically simulated admixed population. The genome was composed of six chromosomes, each with 1000 markers. Fifteen segregating quantitative trait loci contributed to the genetic variation of a quantitative trait with heritability of 0.30. The impact of genetic relationships and breed composition (BC) on three analysis methods were evaluated: single marker simple regression (SMR), single marker mixed linear model (MLM) and Bayesian multiple-regression analysis (BMR). Each method was fitted with and without BC. Accuracy, power, false-positive rate and the positive predictive value of each method were calculated and used for comparison.

Results

SMR and BMR, both without BC, were ranked as the worst and the best performing approaches, respectively. Our results showed that, while explicit modeling of genetic relationships and BC is essential for models SMR and MLM, BMR can disregard them and yet result in a higher power without compromising its false-positive rate.

Conclusions

This study showed that the Bayesian multiple-regression analysis is robust to population structure and to relationships among study subjects and performs better than a single marker mixed linear model approach.

Genome-wide association study identifies loci associated with milk leukocyte phenotypes following experimental challenge with Streptococcus uberis

Mastitis is a detrimental disease in the dairy industry that decreases milk quality and costs upwards of $2 billion annually. Often, mastitis results from bacteria entering the gland through the teat opening. Streptococcus uberis is responsible for a high percentage of subclinical and clinical mastitis. Following an intramammary experimental challenge with S. uberis on Holstein cows (n = 40), milk samples were collected and somatic cell counts (SCC) were determined by the Dairy Herd Improvement Association Laboratory. Traditional genome-wide association studies (GWAS) have utilized test day SCC or SCC lactation averages to identify loci of interest. Our approach utilizes SCC collected following a S. uberis experimental challenge to generate three novel phenotypes: (1) area under the curve (AUC) of SCC for 0-7 days and (2) 0-28 days post-challenge; and (3) when SCC returned to below 200,000 cells/mL post-challenge (< 21 days, 21-28 days, or > 28 days). Polymorphisms were identified using Illumina's BovineSNP50 v2 DNA BeadChip. Associations were tested using Plink software and identified 16 significant (p < 1.0 × 10^-4) single-nucleotide polymorphisms (SNPs) across the phenotypes. Most significant SNPs were in genes linked to cell signaling, migration, and apoptosis. Several have been recognized in relation to infectious processes (ATF7, SGK1, and PACRG), but others less so (TRIO, GLRA1, CELSR2, TIAM2, CPE). Further investigation of these genes and their roles in inflammation (e.g., SCC) can provide potential targets that influence resolution of mammary gland infection. Likewise, further investigation of the identified SNP with mastitis and other disease phenotypes can provide greater insight to the potential of these SNP as genetic markers.

Eigen decomposition expedites longitudinal genome-wide association studies for milk production traits in Chinese Holstein

Background

Pseudo-phenotypes, such as 305-day yields, estimated breeding values or deregressed proofs, are usually used as response variables for genome-wide association studies (GWAS) of milk production traits in dairy cattle. Computational inefficiency challenges the direct use of test-day records for longitudinal GWAS with large datasets.

Results

We propose a rapid longitudinal GWAS method that is based on a random regression model. Our method uses Eigen decomposition of the phenotypic covariance matrix to rotate the data, thereby transforming the complex mixed linear model into weighted least squares analysis. We performed a simulation study that showed that our method can control type I errors well and has higher power than a longitudinal GWAS method that does not include time-varied additive genetic effects. We also applied our method to the analysis of milk production traits in the first three parities of 6711 Chinese Holstein cows. The analysis for each trait was completed within 1 day with known variances. In total, we located 84 significant single nucleotide polymorphisms (SNPs) of which 65 were within previously reported quantitative trait loci (QTL) regions.

Conclusions

Our rapid method can control type I errors in the analysis of longitudinal data and can be applied to other longitudinal traits. We detected QTL that were for the most part similar to those reported in a previous study in Chinese Holstein. Moreover, six additional SNPs for fat percentage and 13 SNPs for protein percentage were identified by our method. These additional 19 SNPs could be new candidate quantitative trait nucleotides for milk production traits in Chinese Holstein.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0383-0) contains supplementary material, which is available to authorized users.

Use of meta-analyses and joint analyses to select variants in whole genome sequences for genomic evaluation: An application in milk production of French dairy cattle breeds

As a result of the 1000 Bull Genome Project, it has become possible to impute millions of variants, with many of these potentially causative for traits of interest, for thousands of animals that have been genotyped with medium-density chips. This enormous source of data opens up very interesting possibilities for the inclusion of these variants in genomic evaluations. However, for computational reasons, it is not possible to include all variants in genomic evaluation procedures. One potential approach could be to select the most relevant variants based on the results of genome-wide association studies (GWAS); however, the identification of causative mutations is still difficult with this method, partly because of weak imputation accuracy for rare variants. To address this problem, this study assesses the ability of different approaches based on multi-breed GWAS (joint and meta-analyses) to identify single-nucleotide polymorphisms (SNP) for use in genomic evaluation in the 3 main French dairy cattle breeds. A total of 6,262 Holstein bulls, 2,434 Montbéliarde bulls, and 2,175 Normande bulls with daughter yield deviations for 5 milk production traits were imputed for 27 million variants. Within-breed and joint (including all 3 breeds) GWAS were performed and 3 models of meta-analysis were tested: fixed effect, random effect, and Z-score. Comparison of the results of within- and multi-breed GWAS showed that most of the quantitative trait loci identified using within-breed approaches were also found with multi-breed methods. However, the most significant variants identified in each region differed depending on the method used. To determine which approach highlighted the most predictive SNP for each trait, we used a marker-assisted best unbiased linear prediction model to evaluate lists of SNP generated by the different GWAS methods; each list contained between 25 and 2,000 candidate variants per trait, which were identified using a single within- or multi-breed GWAS approach. Among all the multi-breed methods tested in this study, variant selection based on meta-analysis (fixed effect) resulted in the most-accurate genomic evaluation (+1 to +3 points compared with other multi-breed approaches). However, the accuracies of genomic evaluation were always better when variants were selected using the results of within-breed GWAS. As has generally been found in studies of quantitative trait loci, these results suggest that part of the genetic variance of milk production traits is breed specific in Holstein, Montbéliarde, and Normande cattle.

Associations of GBP2 gene copy number variations with growth traits and transcriptional expression in Chinese cattle

Copy number variations (CNVs) recently have been recognized as another important genetic variability followed single nucleotide polymorphisms (SNPs). The guanylate binding protein 2 (GBP2) gene plays an important role in cell proliferation. This study was performed to determine the presence of GBP2 CNV (relative to Angus cattle) in 466 individuals representing six main cattle breeds from China, identify its relationship with growth, and explore the biological effects of gene expression. There were two CNV regions in the GBP2 gene, for three types, CNV1 loss type (relative to Angus cattle) was more frequent in XN than other breeds, and CNV2 loss type (relative to Angus cattle) was more frequent in XN and CDM than other breeds. Though the GBP2 gene copy number presented no correlation with the transcriptional expression of JX (P > .05), but the transcriptional expression in heart is higher than other tissues, and the copy number in muscles and fat of JX is higher than others breeds. Statistical analysis revealed that the GBP2 gene CNV1 and CNV2 were significantly associated with growth traits (P < .05). In conclusion, this research established the correlations between CNVs of GBP2 gene and growth traits in different cattle breeds, and our results suggested that the CNVs in GBP2 gene may be considered markers for the molecular breeding of Chinese beef cattle.

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.