Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep

Copy number variations affecting growth curve parameters in a crossbred chicken population

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

Structural variant landscapes reveal convergent signatures of evolution in sheep and goats

BACKGROUND

Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution.

RESULTS

We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats.

CONCLUSIONS

Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.

Insight into the current genomic diversity, conservation status and population structure of Tunisian Barbarine sheep breed

Local livestock breeds play a crucial role in global biodiversity, connecting natural and human-influenced environments and contributing significantly to ecosystem services. While commercial breeds dominate industrial systems, local livestock breeds in developing countries, like Barbarine sheep in Tunisia, are vital for food security and community maintenance. The Tunisian Barbarine sheep, known for its adaptability and distinctive fat-tailed morphology, faces challenges due to historical crossbreeding. In this study, the Illumina Ovine SNP50K BeadChip array was used to perform a genome-wide characterization of Tunisian Barbarine sheep to investigate its genetic diversity, the genome structure, and the relationship within the context of Mediterranean breeds. The results show moderate genetic diversity and low inbreeding. Runs of Homozygosity analysis find genomic regions linked to important traits, including fat tail characteristics. Genomic relationship analysis shows proximity to Algerian thin-tailed breeds, suggesting crossbreeding impacts. Admixture analysis reveals unique genetic patterns, emphasizing the Tunisian Barbarine's identity within the Mediterranean context and its closeness to African breeds. Current results represent a starting point for the creation of monitoring and conservation plans. In summary, despite genetic dilution due to crossbreeding, the identification of genomic regions offers crucial insights for conservation. The study confirms the importance of preserving unique genetic characteristics of local breeds, particularly in the face of ongoing crossbreeding practices and environmental challenges. These findings contribute valuable insights for the sustainable management of this unique genetic reservoir, supporting local economies and preserving sheep species biodiversity.

Comparative lipidome study of maternal plasma, milk, and lamb plasma in sheep

Lipids play a critical role in neonate development and breastmilk is the newborn's major source of lipids. Milk lipids directly influence the neonate plasma lipid profile. The milk lipidome is dynamic, influenced by maternal factors and related to the maternal plasma lipidome. The close inter-relationship between the maternal plasma, milk and neonate plasma lipidomes is critical to understanding maternal-child health and nutrition. In this exploratory study, lipidomes of blood and breast milk from Suffolk sheep and matched lamb blood (n = 13), were profiled on day 34 post birth by untargeted mass spectrometry. Comparative multivariate analysis of the three matrices identified distinct differences in lipids and class of lipids amongst them. Paired analysis identified 346 differential lipids (DL) and 31 correlated lipids (CL) in maternal plasma and milk, 340 DL and 32 CL in lamb plasma and milk and 295 DL and 16 CL in maternal plasma and lamb plasma. Conversion of phosphatidic acid to phosphatidyl inositol was the most active pathway in lamb plasma compared to maternal plasma. This exploratory study illustrates the partitioning of lipids across maternal plasma, milk and lamb plasma and the dynamic relationship between them, reiterating the need to study these three matrices as one biological system.

Genome-Wide Detection of Copy Number Variations Associated with Miniature Features in Horses

Copy number variations (CNVs) are crucial structural genomic variants affecting complex traits in humans and livestock animals. The current study was designed to conduct a comprehensive comparative copy number variation analysis among three breeds, Debao (DB), Baise (BS), and Warmblood (WB), with a specific focus on identifying genomic regions associated with miniature features in horses. Using whole-genome next-generation resequencing data, we identified 18,974 CNVs across 31 autosomes. Among the breeds, we found 4279 breed-specific CNV regions (CNVRs). Baise, Debao, and Warmblood displayed 2978, 986, and 895 distinct CNVRs, respectively, with 202 CNVRs shared across all three breeds. After removing duplicates, we obtained 1545 CNVRs from 26 horse genomes. Functional annotation reveals enrichment in biological functions, including antigen processing, cell metabolism, olfactory conduction, and nervous system development. Debao horses have 970 genes overlapping with CNVRs, possibly causing their small size and mountainous adaptations. We also found that the genes GHR, SOX9, and SOX11 may be responsible for the miniature features of the Debao horse by analyzing their overlapping CNVRs. Overall, this study offers valuable insights into the widespread presence of CNVs in the horse genome. The findings contribute to mapping horse CNVs and advance research on unique miniature traits observed in the Debao horse.

Genome-wide identification of candidate copy number polymorphism genes associated with complex traits of Tibetan-sheep

Copy number variation (CNV) is a genetic structural polymorphism important for phenotypic diversity and important economic traits of livestock breeds, and it plays an important role in the desired genetic variation. This study used whole genome sequencing to detect the CNV variation in the genome of 6 local Tibetan sheep groups. We detected 69,166 CNV events and 7230 copy number variable regions (CNVRs) after merging the overlapping CNVs, accounting for 2.72% of the reference genome. The CNVR length detected ranged from 1.1 to 1693.5 Kb, with a total length of 118.69 Mb and an average length of 16.42 Kb per CNVR. Functional GO cluster analysis showed that the CNVR genes were mainly involved in sensory perception systems, response to stimulus, and signal transduction. Through CNVR-based Vst analysis, we found that the CACNA2D3 and CTBP1 genes related to hypoxia adaptation, the HTR1A gene related to coat color, and the TRNAS-GGA and PIK3C3 genes related to body weight were all strongly selected. The findings of our study will contribute novel insights into the genetic structural variation underlying hypoxia adaptation and economically important traits in Tibetan sheep.

Genome-Wide Signal Selection Analysis Revealing Genes Potentially Related to Sheep-Milk-Production Traits

Natural selection and domestication have shaped modern sheep populations into a vast range of phenotypically diverse breeds. Among these breeds, dairy sheep have a smaller population than meat sheep and wool sheep, and less research is performed on them, but the lactation mechanism in dairy sheep is critically important for improving animal-production methods. In this study, whole-genome sequences were generated from 10 sheep breeds, including 57 high-milk-yield sheep and 44 low-milk-yield sheep, to investigate the genetic signatures of milk production in dairy sheep, and 59,864,820 valid SNPs (Single Nucleotide Polymorphisms) were kept after quality control to perform population-genetic-structure analyses, gene-detection analyses, and gene-function-validation analyses. For the population-genetic-structure analyses, we carried out PCA (Principal Component Analysis), as well as neighbor-joining tree and structure analyses to classify different sheep populations. The sheep used in our study were well distributed in ten groups, with the high-milk-yield-group populations close to each other and the low-milk-yield-group populations showing similar classifications. To perform an exact signal-selection analysis, we used three different methods to find SNPs to perform gene-annotation analyses within the 995 common regions derived from the fixation index (F_ST), nucleotide diversity (Ɵπ), and heterozygosity rate (ZHp) results. In total, we found 553 genes that were located in these regions. These genes mainly participate in the protein-binding pathway and the nucleoplasm-interaction pathway, as revealed by the GO- and KEGG-function-enrichment analyses. After the gene selection and function analyses, we found that FCGR3A, CTSK, CTSS, ARNT, GHR, SLC29A4, ROR1, and TNRC18 were potentially related to sheep-milk-production traits. We chose the strongly selected genes, FCGR3A, CTSK, CTSS, and ARNT during the signal-selection analysis to perform a RT-qPCR (Reale time Quantitative Polymerase Chain Reaction) experiment to validate their expression-level relationship with milk production, and the results showed that FCGR3A has a significant negative relationship with sheep-milk production, while other three genes did not show any positive or negative relations. In this study, it was discovered and proven that the candidate gene FCGR3A potentially contributes to the milk production of dairy sheep and a basis was laid for the further study of the genetic mechanism underlying the strong milk-production traits of sheep.

Whole-genome resequencing reveals genetic diversity and selection characteristics of dairy goat

The dairy goat is one of the earliest dairy livestock species, which plays an important role in the economic development, especially for developing countries. With the development of agricultural civilization, dairy goats have been widely distributed across the world. However, few studies have been conducted on the specific characteristics of dairy goat. In this study, we collected the whole-genome data of 89 goat individuals by sequencing 48 goats and employing 41 publicly available goats, including five dairy goat breeds (Saanen, Nubian, Alpine, Toggenburg, and Guanzhong dairy goat; n = 24, 15, 11, 6, 6), and three goat breeds (Guishan goat, Longlin goat, Yunshang Black goat; n = 6, 15, 6). Through compared the genomes of dairy goat and non-dairy goat to analyze genetic diversity and selection characteristics of dairy goat. The results show that the eight goats could be divided into three subgroups of European, African, and Chinese indigenous goat populations, and we also found that Australian Nubian, Toggenburg, and Australian Alpine had the highest linkage disequilibrium, the lowest level of nucleotide diversity, and a higher inbreeding coefficient, indicating that they were strongly artificially selected. In addition, we identified several candidate genes related to the specificity of dairy goat, particularly genes associated with milk production traits (GHR, DGAT2, ELF5, GLYCAM1, ACSBG2, ACSS2), reproduction traits (TSHR, TSHB, PTGS2, ESR2), immunity traits (JAK1, POU2F2, LRRC66). Our results provide not only insights into the evolutionary history and breed characteristics of dairy goat, but also valuable information for the implementation and improvement of dairy goat cross breeding program.

Copy number variant-based genome wide association study reveals immune-related genes associated with parasite resistance in a heritage sheep breed from the United States

Florida Native is a heritage sheep breed in the United States and expresses superior ability to regulate gastrointestinal nematodes. The objective of the present study was to investigate the importance of copy number variants (CNVs) on resistance to natural Haemonchus contortus infections. A total of 300 Florida Native sheep were evaluated. Phenotypic records included fecal egg count (FEC, eggs/gram), FAMACHA© score, percentage cell volume (PCV, %), body condition score (BCS) and average daily gain (ADG, kg). Sheep were genotyped using the GGP Ovine 50K single nucleotide polymorphism (SNP) chip. Log ratios from 45.2 k SNP markers spanning the entire genome were utilized for CNV detection. After quality control, 261 animals with CNVs and phenotypic records were used for the association testing. Association tests were carried out using correlation-trend test and principal component analysis correction to identify CNVs associated with FEC, FAMACHA©, PCV, BCS and ADG. Significant CNVs were detected when their adjusted p-value was <.05 after FDR correction. A total of 8124 CNVs were identified, which gave 246 non-overlapping CNVs. Fourteen CNVs were significantly associated with FEC and PCV. CNVs associated with FEC overlapped 14 Quantitative Trait Locus previously associated with H. contortus resistance. Our study demonstrated for the first time that CNVs could be potentially involved with parasite resistance in Florida Native sheep. Immune-related genes such as CCL1, CCL2, CCL8, CCL11, NOS2, TNF, CSF3 and STAT3 genes could play an important role for controlling H. contortus resistance. These genes could be potentially utilized as candidate markers for selection of parasite resistance in this breed.

Genome-wide evaluation of copy gain and loss variations in three Afghan sheep breeds

Copy number variation (CNV) is one of the main sources of variation between different individuals that has recently attracted much researcher interest as a major source for heritable variation in complex traits. The aim of this study was to identify CNVs in Afghan indigenous sheep consisting of three Arab, Baluchi, and Gadik breeds using genomic arrays containing 53,862 single nucleotide polymorphism (SNP) markers. Data were analyzed using the Hidden Markov Model (HMM) of PennCNV software. In this study, out of 45 sheep studied, 97.8% (44 animals) have shown CNVs. In total, 411 CNVs were observed for autosomal chromosomes and the entire sequence length of around 144 Mb was identified across the genome. The average number of CNVs per each sheep was 9.13. The identified CNVs for Arab, Baluchi, and Gadik breeds were 306, 62, and 43, respectively. After merging overlapped regions, a total of 376 copy number variation regions (CNVR) were identified, which are 286, 50, and 40 for Arab, Baluchi, and Gadik breeds, respectively. Bioinformatics analysis was performed to identify the genes and QTLs reported in these regions and the biochemical pathways involved by these genes. The results showed that many of these CNVRs overlapped with the genes or QTLs that are associated with various pathways such as immune system development, growth, reproduction, and environmental adaptions. Furthermore, to determine a genome-wide pattern of selection signatures in Afghan sheep breeds, the unbiased estimates of FST was calculated and the results indicated that 37 of the 376 CNVRs (~ 10%) have been also under selection signature, most of those overlapped with the genes influencing production, reproduction and immune system. Finally, the statistical methods used in this study was applied in an external dataset including 96 individuals of the Iranian sheep breed. The results indicated that 20 of the 114 CNVRs (18%) identified in Iranian sheep breed were also identified in our study, most of those overlapped with the genes influencing production, reproduction and immune system. Overall, this is the first attempts to develop the genomic map of loss and gain variation in the genome of Afghan indigenous sheep breeds, and may be important to shed some light on the genomic regions associated with some economically important traits in these breeds.

Genome-wide elucidation of CNV regions and their association with production and reproduction traits in composite Vrindavani cattle

The present study was aimed to analyze the genome-wide copy number variations (CNVs) in Vrindavani composite cattle and concatenate them into CNV regions (CNVRs), and finally test the association of CNVRs with different production and reproduction traits. Genotypic data, generated on BovineSNP50 Beadchip (v3) array for 96 Vrindavani animals, was used to elucidate the CNVs at the genome level. Intensity data covering over 53,218 SNP genotypes on bovine genome was used. Algorithm based on Hidden Markov Model was employed in PennCNV program to detect, normalize and filter CNVs across the genome. 252 putative CNVs, detected via PennCNV program, in different individuals were concatenated into 71 CNV regions (CNVRs) using CNVRuler program. Association of CNVRs with important (re)production traits in Vrindavani animals was assessed using linear regression. Five CNVRs were found to be significantly associated with ten important (re)production traits. The genes harbored in these regions provided useful insights into the association of CNVRs with genes and ultimately the variation at phenotype level. Important genes that overlapped with CNVRs included WASHC4, HS6ST3, MBNL2, TOLLIP, PIDD1 and TSPAN4. Furthermore, the CNVRs were found to overlap with important QTLs available in AnimalQTL database which affect milk yield and composition along with reproduction and immune function traits. The copy number states of three enes were validated using digital droplet PCR technique. The results from the present study significantly enhance the understanding about CNVs in Vrindavani cattle and should help establish its CNV map. The study will also enable further investigation on association of these variants with important traits of economic interest including disease incidence.

Genome-wide identification of copy number variation and association with fat deposition in thin and fat-tailed sheep breeds

Copy number variants (CNVs) are a type of genetic polymorphism which contribute to phenotypic variation in several species, including livestock. In this study, we used genomic data of 192 animals from 3 Iranian sheep breeds including 96 Baluchi sheep and 47 Lori-Bakhtiari sheep as fat-tailed breeds and 47 Zel sheep as thin-tailed sheep breed genotyped with Illumina OvineSNP50K Beadchip arrays. Also, for association test, 70 samples of Valle del Belice sheep were added to the association test as thin-tailed sheep breed. PennCNV and CNVRuler software were, respectively, used to study the copy number variation and genomic association analyses. We detected 573 and 242 CNVs in the fat and thin tailed breeds, respectively. In terms of CNV regions (CNVRs), these represented 328 and 187 CNVRs that were within or overlapping with 790 known Ovine genes. The CNVRs covered approximately 73.85 Mb of the sheep genome with average length 146.88 kb, and corresponded to 2.6% of the autosomal genome sequence. Five CNVRs were randomly chosen for validation, of which 4 were experimentally confirmed using Real time qPCR. Functional enrichment analysis showed that genes harbouring CNVs in thin-tailed sheep were involved in the adaptive immune response, regulation of reactive oxygen species biosynthetic process and response to starvation. In fat-tailed breeds these genes were involved in cellular protein modification process, regulation of heart rate, intestinal absorption, olfactory receptor activity and ATP binding. Association test identified one copy gained CNVR on chromosomes 6 harbouring two protein-coding genes HGFAC and LRPAP1. Our findings provide information about genomic structural changes and their association to the interested traits including fat deposition and environmental compatibility in sheep.

Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed

Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation.

CNV detection and their association with growth, efficiency and carcass traits in Santa Inês sheep

Copy number variations (CNV) are an important source of genetic variation. CNV has been increasingly studied and frequently associated with diseases and productive traits in livestock animals. However, CNV-based genome-wide association studies (GWAS) in Santa Inês sheep, one of the principal sheep breeds in Brazil, have not yet been reported. Thus, the aim of this study was to investigate the association between CNV and growth, efficiency and carcass traits in sheep. The Illumina OvineSNP50 BeadChip array was used to detect CNV in 491 Santa Inês individuals. Then, CNV-based GWAS was performed with a linear mixed model approach considering a genomic relationship matrix, for ten traits: (1) growth: body weight at three (W3) and six (W6) months of age; (2) efficiency: residual feed intake (RFI) and feed efficiency (FE) and (3) carcass: external carcass length (ECL), leg length (LL), carcass yield (CY), commercial cuts weight (CCW), loin eye area (LEA) and subcutaneous fat thickness (SFT). We identified 1,167 autosomal CNV in 438 sheep, with 294 non-redundant CNV, ranging from 21.8 to 861.9 kb, merged into 216 distinct copy number variation regions (CNVRs). One significant CNV segment (p_FDR -value<0.05) in OAR3 was associated with CY, while another significant CNV in OAR6 was associated with RFI. Additionally, another 5 CNV segments were considered relevant for investigation in the future studies. The significant segments overlapped 4 QTLs and spanned 8 genes, including the SPAST, TGFA and ADGRL3 genes, involved in cell differentiation and energy metabolism. Therefore, the results of the present study increase knowledge about CNV in sheep, their possible impacts on productive traits, and provide information for future investigations, being especially useful for those interested in structural variations in the sheep genome.

Identification of Copy Number Variations and Genetic Diversity in Italian Insular Sheep Breeds

Copy number variants (CNVs) are one of the major contributors to genetic diversity and phenotypic variation in livestock. The aim of this work is to identify CNVs and perform, for the first time, a CNV-based population genetics analysis with five Italian sheep breeds (Barbaresca, Comisana, Pinzirita, Sarda, and Valle del Belìce). We identified 10,207 CNVs with an average length of 1.81 Mb. The breeds showed similar mean numbers of CNVs, ranging from 20 (Sarda) to 27 (Comisana). A total of 365 CNV regions (CNVRs) were determined. The length of the CNVRs varied among breeds from 2.4 Mb to 124.1 Mb. The highest number of shared CNVRs was between Comisana and Pinzirita, and only one CNVR was shared among all breeds. Our results indicated that segregating CNVs expresses a certain degree of diversity across all breeds. Despite the low/moderate genetic differentiation among breeds, the different approaches used to disclose the genetic relationship showed that the five breeds tend to cluster in distinct groups, similar to the previous studies based on single-nucleotide polymorphism markers. Gene enrichment was described for the 37 CNVRs selected, considering the top 10%. Out of 181 total genes, 67 were uncharacterized loci. Gene Ontology analysis showed that several of these genes are involved in lipid metabolism, immune response, and the olfactory pathway. Our results corroborated previous studies and showed that CNVs represent valuable molecular resources for providing useful information for separating the population and could be further used to explore the function and evolutionary aspect of sheep genome.

Copy number variants in genomes of local sheep breeds from Russia

Copy number variants (CNVs) are genomic structural variations that contribute to many adaptive and economically important traits in livestock. In this study, we detected CNVs in 354 animals from 16 Russian indigenous sheep breeds and analysed their possible functional roles. Our analysis of the entire sample set resulted in 4527 CNVs forming 1450 CNV regions (CNVRs). When constructing CNVRs for individual breeds, a total of 2715 regions ranging from 88 in Groznensk to 337 in Osetin breeds were identified. To make interbreed CNVR frequency comparison possible, we also identified core CNVRs using CNVs with overlapping chromosomal locations found in different breeds. This resulted in 137 interbreed CNVRs with frequency >15% in at least one breed. Functional enrichment analysis of genes affected by CNVRs in individual breeds revealed 12 breeds with significant enrichments in olfactory perception, PRAME family proteins, and immune response. Function of genes affected by interbreed and breed-specific CNVRs revealed candidates related to domestication, adaptation to high altitudes and cold climates, reproduction, parasite resistance, milk and meat qualities, wool traits, fat storage, and fat metabolism. Our work is the first attempt to uncover and characterise the CNV makeup of Russian indigenous sheep breeds. Further experimental and functional validation of CNVRs would help in developing new and improving existing sheep breeds.

Genome-Wide Assessment Characteristics of Genes Overlapping Copy Number Variation Regions in Duroc Purebred Population

Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.

GWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and k-mers

The development of improved methods for genome-wide association studies (GWAS) for genetics of quantitative traits has been an active area of research during the last 25 years. This activity initially started with the use of mixed linear model (MLM), which was variously modified. During the last decade, however, with the availability of high throughput next generation sequencing (NGS) technology, development and use of pangenomes and novel markers including structural variations (SVs) and k-mers for GWAS has taken over as a new thrust area of research. Pangenomes and SVs are now available in humans, livestock, and a number of plant species, so that these resources along with k-mers are being used in GWAS for exploring additional genetic variation that was hitherto not available for analysis. These developments have resulted in significant improvement in GWAS methodology for detection of marker-trait associations (MTAs) that are relevant to human healthcare and crop improvement.

Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds

This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.

Genome-Wide Detection of Copy Number Variations and Their Association With Distinct Phenotypes in the World's Sheep

Copy number variations (CNVs) are a major source of structural variation in mammalian genomes. Here, we characterized the genome-wide CNV in 2059 sheep from 67 populations all over the world using the Ovine Infinium HD (600K) SNP BeadChip. We tested their associations with distinct phenotypic traits by conducting multiple independent genome-wide tests. In total, we detected 7547 unique CNVs and 18,152 CNV events in 1217 non-redundant CNV regions (CNVRs), covering 245 Mb (∼10%) of the whole sheep genome. We identified seven CNVRs with frequencies correlating to geographical origins and 107 CNVRs overlapping 53 known quantitative trait loci (QTLs). Gene ontology and pathway enrichment analyses of CNV-overlapping genes revealed their common involvement in energy metabolism, endocrine regulation, nervous system development, cell proliferation, immune, and reproduction. For the phenotypic traits, we detected significantly associated (adjusted P < 0.05) CNVRs harboring functional candidate genes, such as SBNO2 for polycerate; PPP1R11 and GABBR1 for tail weight; AKT1 for supernumerary nipple; CSRP1, WNT7B, HMX1, and FGFR3 for ear size; and NOS3 and FILIP1 in Wadi sheep; SNRPD3, KHDRBS2, and SDCCAG3 in Hu sheep; NOS3, BMP1, and SLC19A1 in Icelandic; CDK2 in Finnsheep; MICA in Romanov; and REEP4 in Texel sheep for litter size. These CNVs and associated genes are important markers for molecular breeding of sheep and other livestock species.

Detection of genomic regions underlying milk production traits in Valle del Belice dairy sheep using regional heritability mapping

The aim of this study was to identify genomic regions underlying milk production traits in the Valle del Belice dairy sheep using regional heritability mapping (RHM). Repeated measurements for milk yield (MY), fat percentage and yield (F% and FY) and protein percentage and yield (P% and PY), collected over a period of 6 years (2006–2012) on 481 Valle del Belice ewes, were used for the analysis. Animals were genotyped with the Illumina 50k SNP chip. Variance components, heritabilities and repeatabilities within and across lactations were estimated, fitting parity, litter size, season of lambing and fortnights in milk, as fixed; and additive genetic, permanent environment within and across lactations, flock by test‐day interaction and residual as random effects. For the RHM analysis, the model included the same fixed and random effects as before, plus an additional regional genomic additive effect (specific for the region being tested) as random. While the whole genomic additive effect was estimated using the genomic relationship matrix (GRM) constructed from all SNPs, the regional genomic additive effect was estimated from a GRM matrix constructed from the SNPs within each region. Heritability estimates ranged between 0.06 and 0.15, with repeatabilities being between 0.14 and 0.24 across lactations and between 0.23 and 0.39 within lactation for all milk production traits. A substantial effect of flock‐test‐day on milk production traits was also estimated. Significant genomic regions at either genome‐wide (p < .05) or suggestive (i.e., one false positive per genome scan) level were identified on chromosome (OAR) 2, 3 and 20 for F% and on OAR3 for P%, with the regions on OAR3 in common between the two traits. Our results confirmed the role of LALBA and AQP genes, on OAR3, as candidate genes for milk production traits in sheep.

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

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

Functional characterization of Copy Number Variations regions in Djallonké sheep

A total of 184 Djallonké (West African Dwarf) sheep of Burkina Faso were analysed for Copy Number Variations (CNV) using Ovine 50 K SNP BeadChip genotyping data and two different CNV calling platforms: PennCNV and QuantiSNP. Analyses allowed to identify a total of 63 candidate Copy Number Variations Regions (CNVR) on 11 different ovine chromosomes covering about 82.5 Mb of the sheep genome. Gene-annotation enrichment analysis allowed to identify a total of 751 potential candidate ovine genes located in the candidate CNVR bounds. Functional annotation allowed to identify five statistically significant Functional Clusters (FC; enrichment factor > 1.3) involving 61 candidate genes. All genes forming significantly enriched FC were located on ovine chromosome (OAR) 21. FC1 (22 genes including PAG4 and PAG6) and FC5 (three genes: CTSC, CTSW and CTSF), coding proteases (peptidases and cathepsins, respectively), were involved in reproductive performance and modulation of gestation. Both FC3 and FC4 were involved in inflammatory and immunologic response through coding serum amyloid A and B-box-type zinc finger proteins, respectively. Finally, FC2 consisted of 27 genes (including OR10G6 and OR8B8) involved in olfactory receptor activity, key for animals adapting to new food resources. CNVR identified on at least 15% of individuals were considered CNVR hotspots and further overlapped with previously reported quantitative trait loci (QTL). CNVR hotspots spanning genes putatively involved with lipid metabolism (SKP1, TCF7, JADE2, UBE2B and SAR1B) and differential expression in mammary gland (SEC24A and CDKN2AIPNL) on OAR5 and dairy traits (CCDC198 and SLC35F4) on OAR7 overlapped with QTL associated with lipid metabolism, milk protein yield and milk fat percentage. Information obtained from local sheep populations naturally adapted to harsh environments contributes to increase our understanding of the genomic importance of CNV.

Copy number variation: Characteristics, evolutionary and pathological aspects

Copy number variants (CNVs) were the subject of extensive research in the past years. They are common features of the human genome that play an important role in evolution, contribute to population diversity, development of certain diseases, and influence host–microbiome interactions. CNVs have found application in the molecular diagnosis of many diseases and in non-invasive prenatal care, but their full potential is only emerging. CNVs are expected to have a tremendous impact on screening, diagnosis, prognosis, and monitoring of several disorders, including cancer and cardiovascular disease. Here, we comprehensively review basic definitions of the term CNV, outline mechanisms and factors involved in CNV formation, and discuss their evolutionary and pathological aspects. We suggest a need for better defined distinguishing criteria and boundaries between known types of CNVs.

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

Simple Summary

Understanding the genetic architecture underlying milk production traits in cattle is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we performed a genome-wide association study for milk production and quality traits in Holstein cattle. In the total of ten significant single-nucleotide polymorphisms (SNPs) associated with milk fat and protein, six are located in previously reported quantitative traits locus (QTL) regions. The study not only identified the effect of DGAT1 gene on milk fat and protein but also found several novel candidate genes. In addition, some pleiotropic SNPs and QTLs were identified that associated with more than two traits, these results could provide some basis for molecular breeding in dairy cattle.

Abstract

High-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk-related traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production and quality traits in Holstein cattle population from China. These traits included milk yield, fat, and protein. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a linear mixed model. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten single-nucleotide polymorphisms (SNPs) were detected above the genome-wide significant threshold (p < 4.0 × 10⁻⁷), including six located in previously reported quantitative traits locus (QTL) regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The study not only identified the effect of DGAT1 gene on milk fat and protein, but also discovered novel genetic loci and candidate genes related to milk traits. These novel genetic loci would be an important basis for molecular breeding in dairy cattle.

Genomic Structural Diversity in Local Goats: Analysis of Copy-Number Variations

Simple Summary

Copy-number variations (CNVs) are one of the widely dispersed forms of structural variations in mammalian genomes and are known to be present in genomic regions that regulate important physiological functions. In this study, CNV detection was performed starting from genotypic data of 120 individuals, belonging to four Sicilian dairy goat breeds, genotyped with the Illumina GoatSNP50 BeadChip array. Using PennCNV software, a total of 702 CNVs were identified in 107 individuals. These were merged in 75 CNV regions (CNVRs), i.e., regions containing CNVs overlapped by at least 1 base pair. Functional annotation of the CNVRs allowed the identification of 139 genes/loci within the most frequent CNVRs, which are involved in local adaptation, mild behaviour, immune response, reproduction, and olfactory receptors. This study provides insights into the genomic variations within these Italian goat breeds and should be of value for future studies to identify the relationships between this type of genetic variation and phenotypic traits.

Abstract

Copy-number variations (CNVs) are one of the widely dispersed forms of structural variations in mammalian genomes, and are present as deletions, insertions, or duplications. Only few studies have been conducted in goats on CNVs derived from SNP array data, and many local breeds still remain uncharacterized, e.g., the Sicilian goat dairy breeds. In this study, CNV detection was performed, starting from the genotypic data of 120 individuals, belonging to four local breeds (Argentata dell’Etna, Derivata di Siria, Girgentana, and Messinese), genotyped with the Illumina GoatSNP50 BeadChip array. Overall, 702 CNVs were identified in 107 individuals using PennCNV software based on the hidden Markov model algorithm. These were merged in 75 CNV regions (CNVRs), i.e., regions containing CNVs overlapped by at least 1 base pair, while 85 CNVs remained unique. The part of the genome covered by CNV events was 35.21 Mb (1.2% of the goat genome length). Functional annotation of the CNVRs allowed the identification of 139 genes/loci within the most frequent CNVRs that are involved in local adaptations, such as coat colour (ADAMTS20 and EDNRA), mild behaviour (NR3C2), immune response (EXOC3L4 and TNFAIP2), reproduction (GBP1 and GBP6), and olfactory receptors (OR7E24). This study provides insights into the genomic variations for these Sicilian dairy goat breeds and should be of value for future studies to identify the relationships between this type of genetic variation and phenotypic traits.

Genome-Wide Detection of CNVs and Association With Body Weight in Sheep Based on 600K SNP Arrays

Copy number variations (CNVs) are important genomic structural variations and can give rise to significant phenotypic diversity. Herein, we used high-density 600K SNP arrays to detect CNVs in two synthetic lines of sheep (DS and SHH) and in Hu sheep (a local Chinese breed). A total of 919 CNV regions (CNVRs) were detected with a total length of 48.17 Mb, accounting for 1.96% of the sheep genome. These CNVRs consisted of 730 gains, 102 losses, and 87 complex CNVRs. These CNVRs were significantly enriched in the segmental duplication (SD) region. A CNVR-based cluster analysis of the three breeds revealed that the DS and SHH breeds share a close genetic relationship. Functional analysis revealed that some genes in these CNVRs were also significantly enriched in the olfactory transduction pathway (oas04740), including members of the OR gene family such as OR6C76, OR4Q2, and OR4K14. Using association analyses and previous gene annotations, we determined that a subset of identified genes was likely to be associated with body weight, including FOXF2, MAPK12, MAP3K11, STRBP, and C14orf132. Together, these results offer valuable information that will guide future efforts to explore the genetic basis for body weight in sheep.

Genome-wide selective sweep analysis of the high-altitude adaptability of yaks by using the copy number variant

The domestic yak (Bos grunniens) from the Qinghai-Tibet Plateau is an important animal model in high-altitude adaptation studies. Here, we performed the genome-wide selective sweep analysis to identify the candidate copy number variation (CNV) for the high-altitude adaptation of yaks. A total of 531 autosomal CNVs were determined from 29 yak genome-wide resequencing data (15 high- and 14 low-altitude distributions) by using a CNV caller with a CNV identification interval > 5 kb, CNV silhouette score > 0.7, and minimum allele frequency > 0.05. Most high-frequency CNVs were located at the exonic (44.63%) and intergenic (46.52%) regions. In accordance with the results of the selective sweep analysis, 7 candidate CNVs were identified from the interaction of the top 20 CNVs with highest divergence from the F _ST and V _ST between the low (LA) and high (HA) altitudes. Five genes (i.e., GRIK4, IFNLR1, LOC102275985, GRHL3, and LOC102275713) were also annotated from the seven candidate CNVs and their upstream and downstream ranges at 300 kb. GRIK4, IFNLR1, and LOC102275985 were enriched in five known signal pathways, namely, glutamatergic synapse, JAK-STAT signaling pathway, cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and olfactory transduction. These pathways are involved in the environmental adaptability and various physiological functions of animals, especially the physiological regulation under a hypoxic environment. The results of this study advanced the understanding of CNV as an important genomic structure variant type that contributes to HA adaptation and helped further explain the molecular mechanisms underlying the altitude adaptability of yaks.

Selection signature analysis reveals genes underlying sheep milking performance

Sheep milk is the most important feed resource for newborn lambs and an important food resource for humans. Sheep milk production and ingredients are influenced by genetic and environmental factors. In this study, we implemented selection signature analysis using Illumina Ovine SNP50 BeadChip data of 78 meat Lacaune and 103 milk Lacaune sheep, which have similar genetic backgrounds, from the Sheep HapMap project to identify candidate genes related to ovine milk traits. Since different methods can detect different variation types and complement each other, we used a haplotype-based method (hapFLK) to implement selection signature analysis. The results revealed six selection signature regions showing signs of being selected ( P < 0.001 ): chromosomes 1, 2, 3, 6, 13 and 18. In addition, 38 quantitative trait loci (QTLs) related to sheep milk performance were identified in selection signature regions, which contain 334 candidate genes. Of those, SUCNR1 (succinate receptor 1) and PPARGC1A (PPARG coactivator 1 alpha) may be the most significant genes that affect sheep milking performance, which supply a significant indication for future studies to investigate candidate genes that play an important role in milk production and quality.