Combined GWAS and 'guilt by association'-based prioritization analysis identifies functional candidate genes for body size in sheep

Integrated multi-omics analysis and functional validation uncovers RPL26 roles in regulating growth traits of Asian water buffaloes (Bubalus bubalis)

BACKGROUND

Asian water buffaloes (Bubalus bubalis) in the Yangtze River Basin of China are the important meat provider for local residents because of its outstanding body size. Several previous studies have highlighted their genetic basis of growth characteristics, but the crucial genes regulating growth traits via multi-layer omics are still rarely investigated.

RESULTS

We conducted a comprehensive multi-omics analysis integrating blood and muscle transcriptome, plasma metabolome, rumen fluid metagenome, and genome of Haizi water buffaloes. Of note, ribosomal protein L26 (RPL26) located in the evolutionary selection regions associated with body sizes is the top differentially expressed gene (DEG) in both blood and muscle tissues. Further metabolomics and metagenomics identified growth-related molecular biomarkers (myristicin and Bacteroidales) and microbiological composition (Bacteroides and Prevotella). Leveraging cattle quantitative trait loci (QTLs) and genotype-tissue expression (CattleGTEx) databases, we found the significant correlations of QTL_180979 on RPL26 and two identified cis-eQTLs in muscle tissue in the upstream of RPL26 with weight gain. The follow-up cell assay validations confirmed the regulation roles of RPL26 in cell cycle, apoptosis, and differentiation, where the low RPL26 expressions enhanced the antiapoptotic ability and promoted the differentiation of myoblasts into myotubes markedly.

CONCLUSIONS

Our study illustrates RPL26 roles in regulating growth traits via both integrated multi-omics analysis and functional validations that suggests the further applications of RPL26 for growth trait selection of water buffaloes.

Genetic diversity and adaptability of native sheep breeds from different climatic zones

To better understand the genetic architecture and adaptability of native sheep, 22 breeds were genotyped using ovine50K SNP chips. Eleven additional populations from open-source repositories were included. Cross population Extended Haplotype Homozygosity (XP-EHH) and Relative Scaled Haplotype Homozygosity (Rsb) haplotype-based approaches were used to identify genetic variations influencing the adaptation of local sheep breeds to different climatic zones. The results indicate that all breeds exhibited high but declining genetic diversity levels, with a larger proportion of genetic variation explained by development history and refined by geographical origin, as shown by principal component analysis and Neighbor Net graphs. Admixture analysis revealed high admixture levels in European and North African breeds. Using XP-EHH and Rsb methods, 371 genes were putatively under selection, with only nine common among all population pairs, highlighting unique adaptability. Most identified genes, including Interleukin (IL) and cluster differentiation (CD) gene families underlie immune responses, emphasizing their role in resilience to climate change effects. These findings support that indigenous sheep breeds have retained significant genetic diversity, but improper genetic management may threaten it. Additionally, the research emphasizes that indigenous sheep breeds' unique adaptability to specific climatic zones makes them valuable genetic assets for developing climate-resilient breeds.

Genome-Wide Runs of Homozygosity Reveal Inbreeding Levels and Trait-Associated Candidate Genes in Diverse Sheep Breeds

BACKGROUND

Quantifying and controlling the inbreeding level in livestock populations is crucial for the long-term sustainability of animal husbandry. However, the extent of inbreeding has not been fully understood in sheep populations on a global scale.

METHODS

Here, we analyzed high-depth genomes of 210 sheep from 20 worldwide breeds to identify the pattern and distribution of genome-wide runs of homozygosity (ROH) and detect candidate selected genes in ROH islands for agronomic and phenotypic traits.

RESULTS

Leveraging whole-genome sequencing data, we found a large number of short ROH (e.g., <1.0 Mb) in all breeds and observed the overall higher values of ROH statistics and inbreeding coefficient in European breeds than in Asian breeds and Dorper sheep. We identified some well-known candidate genes (e.g., CAMK4, HOXA gene family, ALOX12, FGF11, and MTOR) and 40 novel genes (e.g., KLHL1, FGFRL1, WDR62, GDF6, KHDRBS2, and PAX1) that are functionally associated with fecundity, body size, and wool-related traits in sheep. Based on the candidate genes, we revealed different genetic bases for the fecundity traits of European and Asian sheep.

CONCLUSIONS

This study improves the resolution of ROH detection and provides new insights into genomic inbreeding and trait architecture in sheep as well as useful markers for future breeding practice.

Whole-genome sequencing reveals copy number variations and their associations with body weight and size traits at slaughter in Lion-head geese

Copy number variation (CNV) is an important type of genetic variations contributing to phenotypic differences in animals and may serve as an alternative molecular marker to single nucleotide polymorphism (SNP) for molecular breeding. We used whole-genome sequencing data to investigate the characteristic of CNVs and their associations with body weight and size traits for 504 120-day Lion-head geese. We detected 1,184,695 CNVs which consisted of 1,148,401 deletions and 36,294 duplications. Based on these CNVs, we obtained 8,043 CNV regions (CNVRs) including 7,578 deletions, 228 duplications and 237 mixeds, which covered 7.76% of the reference genome. The 81.03% of CNVRs had the length ranging from 50bp to1000bp. We filtered 8,767 high-quality genotyped CNVs (7,960 deletions and 807 duplications) to conduct the association analysis of the body weight and 11 body size traits with these CNVs. We found 42 chromosome-wide significant CNVs, among which 40 were novel, and 2 CNVs had the high linkage disequilibrium (r2>0.20) with adjacent SNPs with chromosome-wide significance. According to these significant CNVs, we annotated 47 genes. Among these genes, CEP112, TOM1L1 and STX8 simultaneously influenced body weight and other body size traits, which was worthy of further study.

Genome-wide association study identifies candidate genes affecting body conformation traits of Zhongwei goat

BACKGROUND

Identifying markers or genes crucial for growth traits in Zhongwei goats is pivotal for breeding. Pinpointing genetic factors linked to body size gain enhances breeding efficiency and economic value. In this study, we used the MGISEQ-T7 platform to re-sequence 240 Zhongwei goats (133 male; 107 female) belonging to 5 metrics of growth traits at different growth stages (40 days and 6 months, here in after referred to as 40d and 6 m), namely, Body Weight (BW), Body Height (BH), Body Length (BL), Chest Circumference (CC), Tube Circumference (TC) were examined. A Genome-wide association study (GWAS) was conducted to identify candidate genes associated with the five indicators of body conformation traits, thereby establishing a foundation for subsequent investigations into the biological functions of these genes.

RESULTS

A total of 19.89 Tb of raw data was generated with an average sequencing depth of about 20×. After quality control, 15,958,716 SNPs were available for the analysis. A total of 342 genome-wide significant SNPs were obtained. Among them, in the two physiological stages of 40d and 6 m, 147 and 32 SNPs were significantly associated with BW; 1 and 4 SNPs were significantly associated with BH; 19 and 6 SNPs were significantly associated with BL; 33 and 64 SNPs were significantly associated with CC, 34 and 2 SNPs were significantly associated with TC. These SNPs were annotated to 425 candidate genes. Finally, A total of 39 candidate genes are closely related to biological processes such as skeletal muscle development, skeletal formation, carcass quality, and embryonic development, where ADIPOQ, CCDD39, PTPRT, ZNF215, VRTN, ABCD4, DLST, ADAMTS2, ROBO1, AKAP13, AQPI, SOX2, and AHSG were identified as an important component of the genetic framework that may control somatic conformational traits in Zhongwei goats. which warrants further investigation and review. We verified the polymorphism of 11 SNPs by KASP, and found that Chr13_g.11,700,438 A > G, Chr15_g.37,120,328 A > G, Chr6_g.7,209,383 C > T, Chr20_g.51277932T > A, Chr19_g.17,078,199 A > G, and Chr1_g.79,943,276 C > T were significantly genotyped in verified populations (P < 0.001).

CONCLUTION

It is the first GWAS study to analyze genomic data from 40d and 6 m of Zhongwei goats to understand the molecular genetic mechanisms of growth. Our research identified a series of SNPs and candidate genes associated with growth traits, which could assist us in developing the meat production trait in Zhongwei goats.

Investigation of growth traits in Turkish Merino lambs using multi-locus GWAS approaches: Middle Anatolian Merino

This study explored the genetic basis of growth traits in Middle Anatolian Merino lambs using multi-locus genome-wide association study (GWAS) analyses. Descriptive statistics indicated moderate heritability (h² = 0.363) for birth weight (BW) and (h² = 0.309) for weaning weight (WW), both statistically significant (p < 0.001). Strong genetic correlations were observed between WW and BW (rG = 0.922) and WW and Kleiber ratio (KR, rG = 0.896), implying that simultaneous improvements may be possible through targeted selection. Five multi-locus methods (mrMLM, FASTmrMLM, pLARmEB, FASTmrEMMA, and ISIS EM-BLASSO) were used to identify the polygenic basis of the traits. For BW and WW, 20 and 18 significant SNPs (LOD ≥ 5) were detected, respectively, with some SNPs co-detected by multiple methods. In contrast, only 10 significant SNPs were identified for KR, all exclusively by the ISIS EM-BLASSO approach. Pathway analyses within ± 100 Kb of associated SNPs revealed genes and pathways influencing these traits, which could be leveraged in future breeding programs for enhanced growth performance. The identified SNPs, particularly those associated with BW and WW traits, could facilitate genomic selection if validated in larger and more diverse populations.

The Evolution and Role of Molecular Tools in Measuring Diversity and Genomic Selection in Livestock Populations (Traditional and Up-to-Date Insights): A Comprehensive Exploration

Distinctive molecular approaches and tools, particularly high-throughput SNP genotyping, have been applied to determine and discover SNPs, potential genes of interest, indicators of evolutionary selection, genetic abnormalities, molecular indicators, and loci associated with quantitative traits (QTLs) in various livestock species. These methods have also been used to obtain whole-genome sequencing (WGS) data, enabling the implementation of genomic selection. Genomic selection allows for selection decisions based on genomic-estimated breeding values (GEBV). The estimation of GEBV relies on the calculation of SNP effects using prediction equations derived from a subset of individuals in the reference population who possess both SNP genotypes and phenotypes for target traits. Compared to traditional methods, modern genomic selection methods offer advantages for sex-limited traits, low heritability traits, late-measured traits, and the potential to increase genetic gain by reducing generation intervals. The current availability of high-density genotyping and next-generation sequencing data allow for genome-wide scans for selection. This investigation provides an overview of the essential role of advanced molecular tools in studying genetic diversity and implementing genomic selection. It also highlights the significance of adaptive selection in light of new high-throughput genomic technologies and the establishment of selective comparisons between different genomes. Moreover, this investigation presents candidate genes and QTLs associated with various traits in different livestock species, such as body conformation, meat production and quality, carcass characteristics and composition, milk yield and composition, fertility, fiber production and characteristics, and disease resistance.

Genetic Foundations of Nellore Traits: A Gene Prioritization and Functional Analyses of Genome-Wide Association Study Results

The main goal of this study was to pinpoint functional candidate genes associated with multiple economically important traits in Nellore cattle. After quality control, 1830 genomic regions sourced from 52 scientific peer-reviewed publications were used in this study. From these, a total of 8569 positional candidate genes were annotated for reproduction, 11,195 for carcass, 5239 for growth, and 3483 for morphological traits, and used in an over-representation analysis. The significant genes (adjusted p-values < 0.05) identified in the over-representation analysis underwent prioritization analyses, and enrichment analysis of the prioritized over-represented candidate genes was performed. The prioritized candidate genes were GFRA4, RFWD3, SERTAD2, KIZ, REM2, and ANKRD34B for reproduction; RFWD3, TMEM120A, MIEF2, FOXRED2, DUSP29, CARHSP1, OBI1, JOSD1, NOP58, and LOXL1-AS1 for the carcass; ANKRD34B and JOSD1 for growth traits; and no genes were prioritized for morphological traits. The functional analysis pinpointed the following genes: KIZ (plays a crucial role in spindle organization, which is essential in forming a robust mitotic centrosome), DUSP29 (involved in muscle cell differentiation), and JOSD1 (involved in protein deubiquitination, thereby improving growth). The enrichment of the functional candidate genes identified in this study highlights that these genes play an important role in the expression of reproduction, carcass, and growth traits in Nellore cattle.

A High-Quality Blue Whale Genome, Segmental Duplications, and Historical Demography

The blue whale, Balaenoptera musculus, is the largest animal known to have ever existed, making it an important case study in longevity and resistance to cancer. To further this and other blue whale-related research, we report a reference-quality, long-read-based genome assembly of this fascinating species. We assembled the genome from PacBio long reads and utilized Illumina/10×, optical maps, and Hi-C data for scaffolding, polishing, and manual curation. We also provided long read RNA-seq data to facilitate the annotation of the assembly by NCBI and Ensembl. Additionally, we annotated both haplotypes using TOGA and measured the genome size by flow cytometry. We then compared the blue whale genome with other cetaceans and artiodactyls, including vaquita (Phocoena sinus), the world's smallest cetacean, to investigate blue whale's unique biological traits. We found a dramatic amplification of several genes in the blue whale genome resulting from a recent burst in segmental duplications, though the possible connection between this amplification and giant body size requires further study. We also discovered sites in the insulin-like growth factor-1 gene correlated with body size in cetaceans. Finally, using our assembly to examine the heterozygosity and historical demography of Pacific and Atlantic blue whale populations, we found that the genomes of both populations are highly heterozygous and that their genetic isolation dates to the last interglacial period. Taken together, these results indicate how a high-quality, annotated blue whale genome will serve as an important resource for biology, evolution, and conservation research.

Predicting cell-type specific disease genes of diabetes with the biological network

Type 2 diabetes (T2D) is a chronic condition that can lead to significant harm, such as heart disease, kidney disease, nerve damage, and blindness. Although T2D-related genes have been identified through Genome-wide association studies (GWAS) and various computational methods, the biological mechanism of T2D at the cell type level remains unclear. Exploring cell type-specific genes related to T2D is essential to understand the cellular mechanisms underlying the disease. To address this issue, we introduce DiGCellNet (predicting Disease Genes with Cell type specificity based on biological Networks), a model that integrates graph convolutional network (GCN) and multi-task learning (MTL) to predict T2D-associated cell type-specific genes based on the biological network. Our work represents the first attempt to predict cell type-specific disease genes using GCN and MTL. We evaluate our approach by predicting genes specific to four cell types and demonstrate that the proposed DiGCellNet outperforms other models that combine node embeddings with traditional machine learning algorithms. Moreover, DiGCellNet successfully identifies CALM1 as a gene specific to beta cell type in T2D cases, and this association is confirmed using an independent dataset. The code is available at https://github.com/23AIBox/23AIBox-DiGCellNet.

A mutation in POLR2A gene associated with body size traits in Dezhou donkeys revealed with GWAS

The Dezhou donkey is a famous local donkey breed in China. The aim of the present study was to identify the genes associated with the body size traits of the Dezhou donkey and facilitate the breeding activities of the donkeys. A total of 349 donkeys from 2 generations (113 individuals in F0 and 236 in F1) were analyzed with restriction-site-associated DNA sequencing. A genome-wide association study revealed that the region between 13.7 and 15.6 Mb of chromosome 13 is significantly associated with body sizes. Candidate genes related to body size development, including POLR2A, CHRNB1, FGF11, and ZBTB4, were identified. The results of GO and KEGG analysis indicated that the genes involved in many GO terms were related to metabolic processes and developmental processes. Additionally, a T>C mutation (Chr13:14312485) was found at intron 10 of the POLR2A gene. The association analysis showed significant differences among genotypes for the size traits. The body size of the individuals with the TT genotype was significantly higher than that with the CC genotype. The results showed that the polymorphism of POLR2A has the potential to be used as a marker in the breeding programs of the Dezhou donkeys.

Genomic association using principal components of morphometric traits in horses: identification of genes related to bone growth

The measurement of morphometric traits in horses is important for determining breed qualification and is one of the main selection criteria for the species. The development of an index (HPC) that consists of principal components weighted by additive genetic values allows to explore the most relevant relationships using a reduced number of variables that explain the greatest amount of variation in the data. Genome-wide association studies (GWAS) using HPC are a relatively new approach that permits to identify regions related to a set of traits. The aim of this study was to perform GWAS using HPC for 15 linear measurements as the explanatory variable in order to identify associated genomic regions and to elucidate the biological mechanisms linked to this index in Campolina horses. For GWAS, weighted single-step GBLUP was applied to HPC. The eight genomic windows that explained the highest proportion of additive genetic variance were identified. The sum of the additive variance explained by the eight windows was 95.89%. Genes involved in bone and cartilage development were identified (SPRY2, COL9A2, MIR30C, HEYL, BMP8B, LTBP1, FAM98A, and CRIM1). They represent potential positional candidates for the HPC of the linear measurements evaluated. The HPC is an efficient alternative to reduce the 15 usually measured traits in Campolina horses. Moreover, candidate genes inserted in region that explained high additive variance of the HPC were identified and might be fine-mapped for searching putative mutation/markers.

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information

Alpine Merino Sheep is a novel breed reared from Australian Merino Sheep as the father and Gansu Alpine Fine-Wool Sheep as the mother, living all year in cold and arid alpine areas with exceptional wool quality and meat performance. Body weight is an important economic trait of the Alpine Merino Sheep, but there is limited research on identifying the genes associated with live weight in the 14th month for improving the accuracy of the genomic prediction of this trait. Therefore, this study's sample comprised 1310 Alpine Merino Sheep ewes, and the Fine Wool Sheep 50K Panel was used for genome-wide association study (GWAS) analysis to identify candidate genes. Moreover, the trial population (1310 ewes) in this study was randomly divided into two groups. One group was used as the population for GWAS analysis and screened for the most significant top 5%, top 10%, top 15%, and top 20% SNPs to obtain prior marker information. The other group was used to estimate the genetic parameters based on the weight assigned by heritability combined with different prior marker information. The aim of this study was to compare the accuracy of genomic breeding value estimation when combined with prior marker information from GWAS analysis with the optimal linear unbiased prediction method for genome selection (GBLUP) for the breeding value of target traits. Finally, the accuracy was evaluated using the five-fold cross-validation method. This research provides theoretical and technical support to improve the accuracy of sheep genome selection and better guide breeding. The results demonstrated that eight candidate genes were associated with GWAS analysis, and the gene function query and literature search results suggested that FAM184B, NCAPG, MACF1, ANKRD44, DCAF16, FUK, LCORL, and SYN3 were candidate genes affecting live weight in the 14th month (WT), which regulated the growth of muscle and bone in sheep. In genome selection analysis, the heritability of GBLUP to calculate the WT was 0.335-0.374, the accuracy after five-fold cross-verification was 0.154-0.190, and after assigning different weights to the top 5%, top 10%, top 15%, and top 20% of the GWAS results in accordance with previous information to construct the G matrix, the accuracy of the WT in the GBLUP model was improved by 2.59-7.79%.

NCAPG Regulates Myogenesis in Sheep, and SNPs Located in Its Putative Promoter Region Are Associated with Growth and Development Traits

Previously, NCAPG was identified as a candidate gene associated with sheep growth traits. This study aimed to investigate the direct role of NCAPG in regulating myogenesis in embryonic myoblast cells and to investigate the association between single-nucleotide polymorphisms (SNPs) in its promoter region and sheep growth traits. The function of NCAPG in myoblast proliferation and differentiation was detected after small interfering RNAs (siRNAs) knocked down the expression of NCAPG. Cell proliferation was detected using CCK-8 assay, EdU proliferation assay, and flow cytometry cell cycle analysis. Cell differentiation was detected via cell immunofluorescence and the quantification of myogenic regulatory factors (MRFs). SNPs in the promoter region were detected using Sanger sequencing and genotyped using the improved multiplex ligation detection reaction (iMLDR®) technique. As a result, a notable decrease (p < 0.01) in the percentage of EdU-positive cells in the siRNA-694-treated group was observed. A significant decrease (p < 0.01) in cell viability after treatment with siRNA-694 for 48 h and 72 h was detected using the CCK-8 method. The quantity of S-phase cells in the siRNA-694 treatment group was significantly decreased (p < 0.01). After interfering with NCAPG in myoblasts during induced differentiation, the relative expression levels of MRFs were markedly (p < 0.05 or p < 0.01) reduced compared with the control group on days 5-7. The myoblast differentiation in the siRNA-694 treatment group was obviously suppressed compared with the control group. SNP1, SNP2, SNP3, and SNP4 were significantly (p < 0.05) associated with all traits except body weight measured at birth and one month of age. SNP5 was significantly (p < 0.05) associated with body weight, body height, and body length in six-month-old sheep. In conclusion, interfering with NCAPG can inhibit the proliferation and differentiation of ovine embryonic myoblasts. SNPs in its promoter region can serve as potential useful markers for selecting sheep growth traits.

Accurate haplotype construction and detection of selection signatures enabled by high quality pig genome sequences

High-quality whole-genome resequencing in large-scale pig populations with pedigree structure and multiple breeds would enable accurate construction of haplotype and robust selection-signature detection. Here, we sequence 740 pigs, combine with 149 of our previously published resequencing data, retrieve 207 resequencing datasets, and form a panel of worldwide distributed wild boars, aboriginal and highly selected pigs with pedigree structures, amounting to 1096 genomes from 43 breeds. Combining with their haplotype-informative reads and pedigree structure, we accurately construct a panel of 1874 haploid genomes with 41,964,356 genetic variants. We further demonstrate its valuable applications in GWAS by identifying five novel loci for intramuscular fat content, and in genomic selection by increasing the accuracy of estimated breeding value by 36.7%. In evolutionary selection, we detect MUC13 gene under a long-term balancing selection, as well as NPR3 gene under positive selection for pig stature. Our study provides abundant genomic variations for robust selection-signature detection and accurate haplotypes for deciphering complex traits in pigs.

Feet and legs malformation in Nellore cattle: genetic analysis and prioritization of GWAS results

Beef cattle affected by feet and legs malformations (FLM) cannot perform their productive and reproductive functions satisfactorily, resulting in significant economic losses. Accelerated weight gain in young animals due to increased fat deposition can lead to ligaments, tendon and joint strain and promote gene expression patterns that lead to changes in the normal architecture of the feet and legs. The possible correlated response in the FLM due to yearling weight (YW) selection suggest that this second trait could be used as an indirect selection criterion. Therefore, FLM breeding values and the genetic correlation between FLM and yearling weight (YW) were estimated for 295,031 Nellore animals by fitting a linear-threshold model in a Bayesian approach. A genome-wide association study was performed to identify genomic windows and positional candidate genes associated with FLM. The effects of single nucleotide polymorphisms (SNPs) on FLM phenotypes (affected or unaffected) were estimated using the weighted single-step genomic BLUP method, based on genotypes of 12,537 animals for 461,057 SNPs. Twelve non-overlapping windows of 20 adjacent SNPs explaining more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of candidate genes identified six genes (ATG7, EXT1, ITGA1, PPARD, SCUBE3, and SHOX) that may play a role in FLM expression due to their known role in skeletal muscle development, aberrant bone growth, lipid metabolism, intramuscular fat deposition and skeletogenesis. Identifying genes linked to foot and leg malformations enables selective breeding for healthier herds by reducing the occurrence of these conditions. Genetic markers can be used to develop tests that identify carriers of these mutations, assisting breeders in making informed breeding decisions to minimize the incidence of malformations in future generations, resulting in greater productivity and animal welfare.

Copy Number Variation Discovery in South African Nguni-Sired and Bonsmara-Sired Crossbred Cattle

Crossbreeding forms part of Climate-Smart beef production and is one of the strategies to mitigate the effects of climate change. Two Nguni-sired and three Bonsmara-sired crossbred animals underwent whole genome sequencing. Following quality control and file preparation, the sequence data were investigated for genome-wide copy number variation (CNV) using the panelcn.MOPS tool. A total of 355 CNVs were identified in the crossbreds, of which 274 were unique in Bonsmara-sired crossbreds and 81 unique in the Nguni-sired crossbreds. Genes that differed in copy number in both crossbreds included genes related to growth (SCRN2, LOC109572916) and fertility-related factors (RPS28, LOC1098562432, LOC109570037). Genes that were present only in the Bonsmara-sired crossbreds included genes relating to lipid metabolism (MAF1), olfaction (LOC109569114), body size (HES7), immunity (LOC10957335, LOC109877039) and disease (DMBT1). Genes that were present only in the Nguni-sired crossbreds included genes relating to ketosis (HMBOX1) and amino acid transport (LOC109572916). Results of this study indicate that Nguni and Bonsmara cattle can be utilized in crossbreeding programs as they may enhance the presence of economically important traits associated with both breeds. This will produce crossbred animals that are good meat producers, grow faster, have high fertility, strong immunity and a better chance of producing in South Africa's harsh climate conditions. Ultimately, this study provides new genetic insights into the adaptability of Nguni and Bonsmara crossbred cattle.

Screening Indels from the whole genome to identify the candidates and their association with economic traits in several goat breeds

In the present study, the re-sequencing of our previous whole-genome sequencing (WGS) for selected individuals of Dazu-black goat (DBG) and Inner-Mongolia Cashmere goat (IMCG) breeds was used to detect and compare the differentiation in Indels depending on the reference genome of goat. Then, three selected candidate Indels rs668795676, rs657996810, and rs669452874 of the three genes SUFU, SYCP2L and GLIPR1L1, respectively, have been chosen, based on the results of prior GWAS across the genome, and examined for their association with body weight and dimensions (body height, body length, heart girth, chest width, cannon circumference, and chest depth) by kompetitive allele specific PCR assay for 342 goats from the three studied goat breeds (DBG, n = 203; ♂99, ♀104), IMCG (n = 65; 15♂, 50♀), and Hechuan white goat (HWG, n = 74; 34♂, 40♀) breeds. The analysis of 192.747 Gb WGS revealed an average 334,151 Indels in the whole genome of DBG and IMCG breeds. Chromosome 1 had a maximum number of mutations (Indels) of 58,497 and 55,527 for IMCG and DBG, respectively, while chromosome 25 had the least number of mutations of 15,680 and 16,103 for IMCG and DBG, respectively. The majority of Indels were either Ins or Del of short fragments of 1-5 bp, which covered 79.06 and 71.78% of the total number of Indels mutations in IMCG and DBG, respectively. Comparing the differences of Indels between the studied goat breeds revealed 100 and 110 unique Indels for IMCG and DBG, respectively. The Indels loci in the intron region were unique for both studied goat breeds which were related to 30 and 38 candidate genes in IMCG and DBG, respectively, including SUFU, SYCP2L, and GLIPR1L1 genes. Concerning rs669452874 locus, body height and body length of Del/Del genotype in DBG were significantly higher (P < 0.05) than that of Ins/Del genotype, while body height and body length of Del/Del genotype in IMCG were significantly higher (P < 0.01) than those of Ins/Ins genotype, whereas body height and body length and heart girth of Del/Del genotype in HWG were significantly higher (P < 0.01) than those of the Ins/Del and Ins/Ins genotypes. Thus, Del/Del genotype of rs669452874 locus can be used as a candidate molecular marker related to the body dimensions in the studied goat breeds.

Genomic Regions Associated with Wool, Growth and Reproduction Traits in Uruguayan Merino Sheep

The aim of this study was to identify genomic regions and genes associated with the fiber diameter (FD), clean fleece weight (CFW), live weight (LW), body condition score (BCS), pregnancy rate (PR) and lambing potential (LP) of Uruguayan Merino sheep. Phenotypic records of approximately 2000 mixed-age ewes were obtained from a Merino nucleus flock. Genome-wide association studies were performed utilizing single-step Bayesian analysis. For wool traits, a total of 35 genomic windows surpassed the significance threshold (PVE ≥ 0.25%). The proportion of the total additive genetic variance explained by those windows was 4.85 and 9.06% for FD and CFW, respectively. There were 42 windows significantly associated with LWM, which collectively explained 43.2% of the additive genetic variance. For BCS, 22 relevant windows accounted for more than 40% of the additive genetic variance, whereas for the reproduction traits, 53 genomic windows (24 and 29 for PR and LP, respectively) reached the suggestive threshold of 0.25% of the PVE. Within the top 10 windows for each trait, we identified several genes showing potential associations with the wool (e.g., IGF-1, TGFB2R, PRKCA), live weight (e.g., CAST, LAP3, MED28, HERC6), body condition score (e.g., CDH10, TMC2, SIRPA, CPXM1) or reproduction traits (e.g., ADCY1, LEPR, GHR, LPAR2) of the mixed-age ewes.

Genome-wide association studies uncover genes associated with litter traits in the pig

Litter traits are critical economic variables in the pig industry as they represent a production indicator that can serve to determine sow fertility. In this study, a genome-wide association study on litter traits, including total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), and piglet uniformity (PU), was carried out on two pig breeds (Yorkshire and Landrace). A total of 3 637 pigs of both breeds were genotyped using the GeneSeek GGP Porcine 50K SNP BeadChip. A mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) were employed in the genome-wide association studies for litter traits using combined data from the two pig breeds and data from each breed separately. Additionally, the heritability of traits was estimated using three methods-pedigree-based best linear unbiased prediction (PBLUP), genomic best linear unbiased prediction (GBLUP), and single-step best linear unbiased prediction (ssGBLUP)-and was found to lie between 0.065 and 0.1289, 0.0478 and 0.0938, 0.0793 and 0.0935, 0.1862 and 0.2163, and 0.0327 and 0.0419 for TNB, NBA, LBW, ABW, and PU, respectively. We also compared the genomic prediction accuracies and unbiasedness for litter traits of the three BLUP models. Our results indicated that the ssGBLUP method provided higher predictive accuracies and more rational unbiasedness compared with the PBLUP and GBLUP methodologies. Furthermore, based on their possible roles, eight candidate genes (INHBA, LEPR, HDHD2, CTNND2, RNF216, HMX1, PAPPA2, and NTN1) were identified as being linked with litter traits. In the middle of the test, these genes were found to be connected with pig metabolism and ovulation rate. Our results provide the insights into the genetic architecture of litter traits in pigs, and the potential single nucleotide polymorphisms (SNPs) and candidate genes identified may benefit economic profits in pig-breeding industry and contribute to improve litter traits.

A 7-nt nucleotide sequence variant within the sheep KDM3B gene affects female reproduction traits

Lysine demethylase 3B (KDM3B) gene is a histone demethylase, demonstrating specific demethylation of the histone H3 lysine 9. It was detected as a sheep reproductive candidate gene by genome-wide scans, and related studies also showed its significance in female reproductive process. However, rare study researched its polymorphism. Herein, we hypothesized that the polymorphisms of KDM3B gene were associated with sheep reproduction traits. A 7-nt nucleotide sequence variant (rs1088697156) within KDM3B gene was identified in a total of 888 individuals, including the Australian White (AUW) sheep and Lanzhou Fat-tailed (LFT) sheep. II (insertion/insertion) and ID (insertion/deletion) genotypes of 7-nt variant were detected, which were at Hardy-Weinberg equilibrium (HWE) in detected breeds. Association analysis illustrated the 7-nt variant was significantly associated with the litter size, duration of pregnancy, live lamb number, live lamb rate, stillbirth number, stillbirth rate of average and different parity (P < 0.05) in AUW sheep. Moreover, 'ID' was the dominant genotype with excellent consistency in reproductive traits. It is instrumental to select individuals with ID genotype for improving the sheep reproduction traits. These findings suggest that the 7-nt variant within KDM3B gene can be used as a candidate marker of reproduction traits for sheep breeding improvement by marker-assisted selection.

Genetic Parameters and Genomic Regions Underlying Growth and Linear Type Traits in Akkaraman Sheep

In the current study, the genetic architecture of growth and linear type traits were investigated in Akkaraman sheep. Estimations of genomic heritability, genetic correlations, and phenotypic correlations were implemented for 17 growth and linear type traits of 473 Akkaraman lambs by the univariate and multivariate analysis of animal mixed models. Correspondingly, moderate heritability estimates, as well as high and positive genetic/phenotypic correlations were found between growth and type traits. On the other hand, 2 genome-wide and 19 chromosome-wide significant single nucleotide polymorphisms were found to be associated with the traits as a result of animal mixed model-based genome-wide association analyses. Accordingly, we propose several genes located on different chromosomes (e.g., PRDM2, PTGDR, PTPRG, KCND2, ZNF260, CPE, GRID2, SCD5, SPIDR, ZNF407, HCN3, TMEM50A, FKBP1A, TLE4, SP1, SLC44A1, and MYOM3) as putative quantitative trait loci for the 22 growth and linear type traits studied. In our study, specific genes (e.g., TLE4, PTGDR, and SCD5) were found common between the traits studied, suggesting an interplay between the genetic backgrounds of these traits. The fact that four of the proposed genes (TLE4, MYOM3, SLC44A1, and TMEM50A) are located on sheep chromosome 2 confirms the importance of these genomic regions for growth and morphological structure in sheep. The results of our study are therefore of great importance for the development of efficient selection indices and marker-assisted selection programs, as well as for the understanding of the genetic architecture of growth and linear traits in sheep.

Identification of selection signatures in Iranian dromedary and Bactrian camels using whole genome sequencing data

The Old World camels play an important role as one of the main food sources in large parts of Asia and Africa. Natural selection combined with artificial selection by human has affected parts of the domestic animal genome for adapting them to their habitats and meeting human needs. Here, we used whole genome sequencing data of 34 camels (including 14 dromedaries and 20 Bactrian camels) to identify the genomic signature of selection in the Iranian dromedary (ID) and Bactrian camels (IB). To detect the mentioned regions, we used two methods including population differentiation index (Fst) and cross-population extended haplotype homozygosity (XP-EHH) with 50 kb sliding window and 25 kb step size. Based on gene ontology analysis on the candidate genes identified for IB camels, we found GO terms associated with lung development, nervous system development, immune system and behavior. Also, we identified several genes related to body thermoregulation (ZNF516), meat quality (ANK1 and HSPA13), and high-altitude adaptation (OPA1) for IB camels. In the list of detected candidate genes under selection in ID camels, the genes related to energy metabolism (BDH1), reproduction (DLG1, IMMP2L and FRASI), long-term memory (GRIA1), kidney (SLC12A1), lung development (EMILIN2 and FBN1) and immunity (SOCS2, JAK1, NRROS and SENP1) were found. Our findings, along with further studies in this field, will strengthen our knowledge about the effect of selection on the camelid genome under different geographical, climatic and even cultural conditions.

Whole Genome Sequencing Analysis to Identify Candidate Genes Associated With the rib eye Muscle Area in Hu Sheep

In sheep meat production, the rib eye area is an important index to evaluate carcass traits. However, conventional breeding programs have led to slow genetic progression in rib eye muscle area. Operationalizing molecular marker assisted breeding is an optimized breeding method that might improve this situation. Therefore, the present study used whole genome sequencing data to excavate candidate genes associated with the rib eye muscle. Male Hu lambs (n = 776) with pedigrees and 274 lambs with no pedigree were included. The genetic parameters of the rib eye area were estimated using a mixed linear mixed model. The rib eye area showed medium heritability (0.32 ± 0.13). Whole-genome sequencing of 40 large rib eye sheep [17.97 ± 1.14, (cm²)] and 40 small rib eye sheep [7.89 ± 0.79, (cm²)] was performed. Case-control genome-wide association studies and the fixation index identified candidate rib eye-associated genes. Seven single nucleotide polymorphisms (SNPs) in six genes (ALS2, ST6GAL2, LOC105611989, PLXNA4, DPP6, and COL12A1) were identified as candidates. The study population was expanded to 1050 lambs to perform KASPar genotyping on five SNPs, which demonstrated that SNPs in LOC105611989, DPP6, and COL12A1 correlated significantly with the rib eye area, which could be used as genetic markers for molecular breeding of the rib eye area. The results provided genetic parameters estimated on the rib eye area and information for breeding based on carcass traits in Hu sheep.

Unravelling the effect of environment on the genome of Sarda breed ewes using Runs of Homozygosity

Natural adaptation and artificial selection have shaped the genome of modern livestock breeds. Among SNP-based metrics that are used to detect signatures of selection at genome-wide level, runs of homozygosity (ROH) are getting increasing popularity. In this paper, ROH distribution and features of a sample of 823 Sarda breed ewes farmed at different levels of altitude are analysed to investigate the effect of the environment on the patterns of homozygosity. A total of 46,829 (33,087 unique) ROH were detected. OAR2 exhibited the largest average number of ROH per animal. The most frequent ROH (OAR27, 38.9-44.2 Mb) was shared by 327. ROH length was statistically affected (p < 0.001) by both the altitude and temperature of the place where the flock was located. The highest probability of a SNP falling in a ROH was observed for hill ewes, whereas the smallest one for mountain. A total of 457 SNP exceeded the 99th percentile of the ROH count per SNP distribution and were considered significant. These markers mapped in eight chromosomes and they clustered into 17 ROH islands, where 80 candidate genes were mapped. Results of this study highlighted differences in the ROH distribution and features among sheep farmed in flocks located at different levels of altitude, confirming the role of environmental adaptability in shaping the genome of this breed.

Screen of small fragment mutations within the sheep thyroid stimulating hormone receptor gene associated with litter size

The thyroid stimulating hormone receptor (TSHR), a glycoprotein hormone receptor, plays an important role in metabolic regulation and photoperiod control in the time of reproduction in birds and mammals. Previous genome-wide association studies revealed that the TSHR gene was related to reproduction and its function was identified in female reproduction, but rare studies reported the polymorphism of TSHR gene. However, the molecular mutations of the TSHR gene in sheep have not been reported so far. Herein, we explored potential polymorphisms of the sheep TSHR gene, and a 29 bp nucleotide sequence variant (rs1089565492) was identified in the AUW sheep. There were three genotypes of the 29 bp variant locus detected which named 'II' 'DD' and 'ID' been identified. Association analysis results showed the 29 bp variant was significantly associated with the litter size of the AUW sheep (p < 0.05). This finding suggests that the 29 bp nucleotide sequence variant within TSHR gene could be a candidate marker of reproduction traits for sheep breeding improving through the marker-assisted selection (MAS).

The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock

Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.

Detection and Visualization of Heterozygosity-Rich Regions and Runs of Homozygosity in Worldwide Sheep Populations

In this study, we chose 17 worldwide sheep populations of eight breeds, which were intensively selected for different purposes (meat, milk, or wool), or locally-adapted breeds, in order to identify and characterize factors impacting the detection of runs of homozygosity (ROH) and heterozygosity-rich regions (HRRs) in sheep. We also applied a business intelligence (BI) tool to integrate and visualize outputs from complementary analyses. We observed a prevalence of short ROH, and a clear distinction between the ROH profiles across populations. The visualizations showed a fragmentation of medium and long ROH segments. Furthermore, we tested different scenarios for the detection of HRR and evaluated the impact of the detection parameters used. Our findings suggest that HRRs are small and frequent in the sheep genome; however, further studies with higher density SNP chips and different detection methods are suggested for future research. We also defined ROH and HRR islands and identified common regions across the populations, where genes related to a variety of traits were reported, such as body size, muscle development, and brain functions. These results indicate that such regions are associated with many traits, and thus were under selective pressure in sheep breeds raised for different purposes. Interestingly, many candidate genes detected within the HRR islands were associated with brain integrity. We also observed a strong association of high linkage disequilibrium pattern with ROH compared with HRR, despite the fact that many regions in linkage disequilibrium were not located in ROH regions.

Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

BACKGROUND

Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW).

RESULTS

Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from - 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans.

CONCLUSIONS

Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.

Single-nucleotide polymorphism detecting of some candidate genes related to lipid metabolism in Booroola Merino-Afshari sheep by Bayesian model averaging

This study was designed to identify single-nucleotide polymorphisms (SNPs) of some candidate genes related to lipid metabolism and their association with carcass fat in male crossbred lambs. Hence, 96 of almost 11-month-old Booroola Merino-Afshari crossbred lambs (first-generation backcross) were used by considering their phenotypic carcass traits. Then, DNA was extracted and DNA targets were amplified using designed specific primers by PCR procedure. Identification of potential SNPs was done by a direct sequencing method for LEP, FABP4, DGAT1, GH, and TRIB3 genes using the sequencing-RFLP procedure. Then, the most probable statistical models based on additive and genotypic effects of identified SNPs in each trait were obtained by the Bayesian model averaging (BMA) approach of R software (Ver. 3.3.1) to assess the association of SNPs with traits. Detected SNPs in this study included two SNPs in exon 3 of LEP, one SNP in exon 2 of TRIB3, one SNP in intron 2 of FABP4, one SNP in 5' UTR of DGAT1, and two SNPs in 3' UTR of GH genes. For carcass weight trait, one of the identified SNP genotypes in the LEP (c.587G > A) had a higher probability in the model. Carcass weight of lambs with GA genotype was 2.46 kg heavier than GG genotype. Also, two genes of TRIB3 and GH2 had the highest probability in the models of fat tail and waste weight, respectively. Based on the results, these polymorphisms can be used in the marker-assisted selection of breeding programs and designing DNA chips for genomic selection.

The GWAS Analysis of Body Size and Population Verification of Related SNPs in Hu Sheep

Body size is an important indicator of growth and health in sheep. In the present study, we performed Genome-Wide Association Studies (GWAS) to detect significant single-nucleotide polymorphisms (SNPs) associated with Hu sheep's body size. After genotyping parental (G1) and offspring (G2) generation of the nucleus herd for meat production of Hu sheep and conducting GWAS on the body height, chest circumference, body length, tail length, and tail width of the two groups, 5 SNPs associated with body height and 4 SNPs correlated with chest circumference were identified at the chromosomal significance level. No SNPs were significantly correlated to body length, tail length, and width. Four out of the 9 SNPs were found to be located within the 4 genes. KITLG and CADM2 are considered as candidate functional genes related to body height; MCTP1 and COL4A6 are candidate functional genes related to chest circumference. The 9 SNPs found in GWAS were verified using the G3 generation of the nucleus herd for meat production. Nine products were amplified around the 9 sites, and 29 SNPs were found; 3 mutation sites, G > C mutation at 134 bp downstream of s554331, T > G mutation at 19 bp upstream of s26859.1, and A > G mutation at 81 bp downstream of s26859.1, were significantly correlated to the body height. Dual-luciferase reporter gene experiments showed that the 3 SNPs could significantly impact dual-luciferase and gene transcription activity.

Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals

Simple Summary

Skeletal muscle mass is an important economic trait, and muscle development and growth is a crucial factor to supply enough meat for human consumption. Thus, understanding (candidate) genes regulating skeletal muscle development is crucial for understanding molecular genetic regulation of muscle growth and can be benefit the meat industry toward the goal of increasing meat yields. During the past years, significant progress has been made for understanding these mechanisms, and thus, we decided to write a comprehensive review covering regulators and (candidate) genes crucial for muscle development and growth in farm animals. Detection of these genes and factors increases our understanding of muscle growth and development and is a great help for breeders to satisfy demands for meat production on a global scale.

Abstract

Farm-animal species play crucial roles in satisfying demands for meat on a global scale, and they are genetically being developed to enhance the efficiency of meat production. In particular, one of the important breeders’ aims is to increase skeletal muscle growth in farm animals. The enhancement of muscle development and growth is crucial to meet consumers’ demands regarding meat quality. Fetal skeletal muscle development involves myogenesis (with myoblast proliferation, differentiation, and fusion), fibrogenesis, and adipogenesis. Typically, myogenesis is regulated by a convoluted network of intrinsic and extrinsic factors monitored by myogenic regulatory factor genes in two or three phases, as well as genes that code for kinases. Marker-assisted selection relies on candidate genes related positively or negatively to muscle development and can be a strong supplement to classical selection strategies in farm animals. This comprehensive review covers important (candidate) genes that regulate muscle development and growth in farm animals (cattle, sheep, chicken, and pig). The identification of these genes is an important step toward the goal of increasing meat yields and improves meat quality.

Genome-Wide Association Study-Based Identification of SNPs and Haplotypes Associated With Goose Reproductive Performance and Egg Quality

Geese are one of the most economically important waterfowl. However, the low reproductive performance and egg quality of geese hinder the development of the goose industry. The identification and application of genetic markers may improve the accuracy of beneficial trait selection. To identify the genetic markers associated with goose reproductive performance and egg quality traits, we performed a genome-wide association study (GWAS) for body weight at birth (BBW), the number of eggs at 48 weeks of age (EN48), the number of eggs at 60 weeks of age (EN60) and egg yolk color (EYC). The GWAS acquired 2.896 Tb of raw sequencing data with an average depth of 12.44× and identified 9,279,339 SNPs. The results of GWAS showed that 26 SNPs were significantly associated with BBW, EN48, EN60, and EYC. Moreover, five of these SNPs significantly associated with EN48 and EN60 were in a haplotype block on chromosome 35 from 4,512,855 to 4,541,709 bp, oriented to TMEM161A and another five SNPs significantly correlated to EYC were constructed in haplotype block on chromosome 5 from 21,069,009 to 21,363,580, which annotated by TMEM161A, CALCR, TFPI2, and GLP1R. Those genes were enriched in epidermal growth factor-activated receptor activity, regulation of epidermal growth factor receptor signaling pathway. The SNPs, haplotype markers, and candidate genes identified in this study can be used to improve the accuracy of marker-assisted selection for the reproductive performance and egg quality traits of geese. In addition, the candidate genes significantly associated with these traits may provide a foundation for better understanding the mechanisms underlying reproduction and egg quality in geese.

Expression quantitative trait loci in sheep liver and muscle contribute to variations in meat traits

Background

Variants that regulate transcription, such as expression quantitative trait loci (eQTL), have shown enrichment in genome-wide association studies (GWAS) for mammalian complex traits. However, no study has reported eQTL in sheep, although it is an important agricultural species for which many GWAS of complex meat traits have been conducted. Using RNA sequence data produced from liver and muscle from 149 sheep and imputed whole-genome single nucleotide polymorphisms (SNPs), our aim was to dissect the genetic architecture of the transcriptome by associating sheep genotypes with three major molecular phenotypes including gene expression (geQTL), exon expression (eeQTL) and RNA splicing (sQTL). We also examined these three types of eQTL for their enrichment in GWAS of multi-meat traits and fatty acid profiles.

Results

Whereas a relatively small number of molecular phenotypes were significantly heritable (h² > 0, P < 0.05), their mean heritability ranged from 0.67 to 0.73 for liver and from 0.71 to 0.77 for muscle. Association analysis between molecular phenotypes and SNPs within ± 1 Mb identified many significant cis-eQTL (false discovery rate, FDR < 0.01). The median distance between the eQTL and transcription start sites (TSS) ranged from 68 to 153 kb across the three eQTL types. The number of common variants between geQTL, eeQTL and sQTL within each tissue, and the number of common variants between liver and muscle within each eQTL type were all significantly (P < 0.05) larger than expected by chance. The identified eQTL were significantly (P < 0.05) enriched in GWAS hits associated with 56 carcass traits and fatty acid profiles. For example, several geQTL in muscle mapped to the FAM184B gene, hundreds of sQTL in liver and muscle mapped to the CAST gene, and hundreds of sQTL in liver mapped to the C6 gene. These three genes are associated with body composition or fatty acid profiles.

Conclusions

We detected a large number of significant eQTL and found that the overlap of variants between eQTL types and tissues was prevalent. Many eQTL were also QTL for meat traits. Our study fills a gap in the knowledge on the regulatory variants and their role in complex traits for the sheep model.

Using Interactome Big Data to Crack Genetic Mysteries and Enhance Future Crop Breeding

The functional genes underlying phenotypic variation and their interactions represent "genetic mysteries". Understanding and utilizing these genetic mysteries are key solutions for mitigating the current threats to agriculture posed by population growth and individual food preferences. Due to advances in high-throughput multi-omics technologies, we are stepping into an Interactome Big Data era that is certain to revolutionize genetic research. In this article, we provide a brief overview of current strategies to explore genetic mysteries. We then introduce the methods for constructing and analyzing the Interactome Big Data and summarize currently available interactome resources. Next, we discuss how Interactome Big Data can be used as a versatile tool to dissect genetic mysteries. We propose an integrated strategy that could revolutionize genetic research by combining Interactome Big Data with machine learning, which involves mining information hidden in Big Data to identify the genetic models or networks that control various traits, and also provide a detailed procedure for systematic dissection of genetic mysteries,. Finally, we discuss three promising future breeding strategies utilizing the Interactome Big Data to improve crop yields and quality.

Identifying functionally relevant candidate genes for inflexible ethanol intake in mice and humans using a guilt-by-association approach

Gene prioritization approaches are useful tools to explore and select candidate genes in transcriptome studies. Knowing the importance of processes such as neuronal activity, intracellular signal transduction, and synapse plasticity to the development and maintenance of compulsive ethanol drinking, the aim of the present study was to explore and identify functional candidate genes associated with these processes in an animal model of inflexible pattern of ethanol intake. To do this, we applied a guilt-by-association approach, using the GUILDify and ToppGene software, in our previously published microarray data from the prefrontal cortex (PFC) and striatum of inflexible drinker mice. We then tested some of the prioritized genes that showed a tissue-specific pattern in postmortem brain tissue (PFC and nucleus accumbens (NAc)) from humans with alcohol use disorder (AUD). In the mouse brain, we prioritized 44 genes in PFC and 26 in striatum, which showed opposite regulation patterns in PFC and striatum. The most prioritized of them (i.e., Plcb1 and Prkcb in PFC, and Dnm2 and Lrrk2 in striatum) were associated with synaptic neuroplasticity, a neuroadaptation associated with excessive ethanol drinking. The identification of transcription factors among the prioritized genes suggests a crucial role for Irf4 in the pattern of regulation observed between PFC and striatum. Lastly, the differential transcription of IRF4 and LRRK2 in PFC and nucleus accumbens in postmortem brains from AUD compared to control highlights their involvement in compulsive ethanol drinking in humans and mice.

Major quantitative trait loci influencing milk production and conformation traits in Guernsey dairy cattle detected on Bos taurus autosome 19

The goal of this study was to identify potential quantitative trait loci (QTL) for 27 production, fitness, and conformation traits of Guernsey cattle through genome-wide association (GWA) analyses, with extra emphasis on BTA19, where major QTL were observed for several traits. Animals' de-regressed predicted transmitting abilities (PTA) from the December 2018 traditional US evaluation were used as phenotypes. All of the Guernsey cattle included in the QTL analyses were predictor animals in the reference population, ranging from 1,077 to 1,685 animals for different traits. Single-trait GWA analyses were carried out by a mixed-model approach for all 27 traits using imputed high-density genotypes. A major QTL was detected on BTA19, influencing several milk production traits, conformation traits, and livability of Guernsey cattle, and the most significant SNP lie in the region of 26.2 to 28.3 Mb. The myosin heavy chain 10 (MYH10) gene residing within this region was found to be highly associated with milk production and body conformation traits of dairy cattle. After the initial GWA analyses, which suggested that many significant SNP are in linkage with one another, conditional analyses were used for fine mapping. The top significant SNP on BTA19 were fixed as covariables in the model, one at a time, until no more significant SNP were detected on BTA19. After this fine-mapping approach was applied, only 1 significant SNP was detected on BTA19 for most traits, but multiple, independent significant SNP were found for protein yield, dairy form, and stature. In addition, the haplotype that hosts the major QTL on BTA19 was traced to a US Guernsey born in 1954. The haplotype is common in the breed, indicating a long-term influence of this QTL on the US Guernsey population.

A multi-breed GWAS for morphometric traits in four Beninese indigenous cattle breeds reveals loci associated with conformation, carcass and adaptive traits

BACKGROUND

Specific adaptive features including disease resistance and growth abilities in harsh environments are attributed to indigenous cattle breeds of Benin, but these breeds are endangered due to crossbreeding. So far, there is a lack of systematic trait recording, being the basis for breed characterizations, and for structured breeding program designs aiming on conservation. Bridging this gap, own phenotyping for morphological traits considered measurements for height at withers (HAW), sacrum height (SH), heart girth (HG), hip width (HW), body length (BL) and ear length (EL), including 449 cattle from the four indigenous Benin breeds Lagune, Somba, Borgou and Pabli. In order to utilize recent genomic tools for breed characterizations and genetic evaluations, phenotypes for novel traits were merged with high-density SNP marker data. Multi-breed genetic parameter estimations and genome-wide association studies (GWAS) for the six morphometric traits were carried out. Continuatively, we aimed on inferring genomic regions and functional loci potentially associated with conformation, carcass and adaptive traits.

RESULTS

SNP-based heritability estimates for the morphometric traits ranged between 0.46 ± 0.14 (HG) and 0.74 ± 0.13 (HW). Phenotypic and genetic correlations ranged from 0.25 ± 0.05 (HW-BL) to 0.89 ± 0.01 (HAW-SH), and from 0.14 ± 0.10 (HW-BL) to 0.85 ± 0.02 (HAW-SH), respectively. Three genome-wide and 25 chromosome-wide significant SNP positioned on different chromosomes were detected, located in very close chromosomal distance (±25 kb) to 15 genes (or located within the genes). The genes PIK3R6 and PIK3R1 showed direct functional associations with height and body size. We inferred the potential candidate genes VEPH1, CNTNAP5, GYPC for conformation, growth and carcass traits including body weight and body fat deposition. According to their functional annotations, detected potential candidate genes were associated with stress or immune response (genes PTAFR, PBRM1, ADAMTS12) and with feed efficiency (genes MEGF11 SLC16A4, CCDC117).

CONCLUSIONS

Accurate measurements contributed to large SNP heritabilities for some morphological traits, even for a small mixed-breed sample size. Multi-breed GWAS detected different loci associated with conformation or carcass traits. The identified potential candidate genes for immune response or feed efficiency indicators reflect the evolutionary development and adaptability features of the breeds.

All sheeps and sizes: a genetic investigation of mature body size across sheep breeds reveals a polygenic nature

Mature body size is genetically correlated with growth rate, an important economic trait in the sheep industry. Mature body size has been studied extensively in humans as well as cattle and other domestic animal populations but not in sheep. Six‐hundred and sixteen ewes, across 22 breeds, were measured for 28 linear measurements representing various skeletal parts. PCA from these measures generated principal components 1 and 2 which represented 66 and 7% of the phenotypic variation respectively. Two‐hundred and twenty sheep were genotyped on the Illumina Ovine HD beadchip for a GWAS investigating mature body size and linear body measurements. Forty‐six (Bonferroni P < 0.05) SNP associations across 14 chromosomes were identified utilizing principal component 1, representing overall body size, revealing mature body size to have fewer loci of large effect than other domestic species such as dogs and horses. Genome‐wide associations for individual linear measures identified major quantitative trait loci for withers height and ear length. Withers height was associated (Bonferroni P < 0.05) with 12 SNPs across six chromosomes whereas ear length was associated with a single locus on chromosome 3, containing MSRB3. This analysis identified several loci known to be associated with mature body size in other species such as NCAPG, LCORL, and HMGA2. Mature body size is more polygenic in sheep than other domesticated species, making the development of genomic selection for the trait the most efficient option for maintaining or reducing mature body size in sheep.

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

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

Genome-Wide Association Study Using Individual Single-Nucleotide Polymorphisms and Haplotypes for Erythrocyte Traits in Alpine Merino Sheep

Adaptation to high-altitude hypoxia is essential for domestic animals, such as yak, Tibetan chicken, and Tibetan sheep, living on high plateaus, as it ensures efficient oxygen absorption and utilization. Red blood cells are the primary medium for transporting oxygen in the blood. However, little is known about the genetic mechanism of erythrocyte traits. Genome-wide association studies (GWASs) based on single markers or haplotypes have identified potential mechanisms for genetic variation and quantitative traits. To identify loci associated with erythrocyte traits, we performed a GWAS based on the method of the single marker and haplotype in 498 Alpine Merino sheep for six erythrocyte traits: red blood cell count (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and RBC volume distribution width coefficient of variation (RWD_CV). Forty-two significant single-nucleotide polymorphisms (SNPs) associated with the six erythrocyte traits were detected by means of a single-marker GWAS, and 34 significant haplotypes associated with five erythrocyte traits were detected by means of haplotype analysis. We identified six genes (DHCR24, SPATA9, FLI1, PLCB1, EFNB2, and SH2B3) as potential genes of interest via gene function annotations, location, and expression variation. In particular, FLI1 and PLCB1 were associated with hematopoiesis and erythropoiesis, respectively. These results provide a theoretical basis for analyzing erythrocyte traits and high-altitude hypoxia adaptation in Alpine Merino sheep and will be a useful reference for future studies of plateau-dwelling livestock.

Deciphering the mode of action and position of genetic variants impacting on egg number in broiler breeders

Background

Aim of the present study was first to identify genetic variants associated with egg number (EN) in female broilers, second to describe the mode of their gene action (additive and/or dominant) and third to provide a list with implicated candidate genes for the trait. A number of 2586 female broilers genotyped with the high density (~ 600 k) SNP array and with records on EN (mean = 132.4 eggs, SD = 29.8 eggs) were used. Data were analyzed with application of additive and dominant multi-locus mixed models.

Results

A number of 7 additive, 4 dominant and 6 additive plus dominant marker-trait significant associations were detected. A total number of 57 positional candidate genes were detected within 50 kb downstream and upstream flanking regions of the 17 significant markers. Functional enrichment analysis pinpointed two genes (BHLHE40 and CRTC1) to be involved in the ‘entrainment of circadian clock by photoperiod’ biological process. Gene prioritization analysis of the positional candidate genes identified 10 top ranked genes (GDF15, BHLHE40, JUND, GDF3, COMP, ITPR1, ELF3, ELL, CRLF1 and IFI30). Seven prioritized genes (GDF15, BHLHE40, JUND, GDF3, COMP, ELF3, CRTC1) have documented functional relevance to reproduction, while two more prioritized genes (ITPR1 and ELL) are reported to be related to egg quality in chickens.

Conclusions

Present results have shown that detailed exploration of phenotype-marker associations can disclose the mode of action of genetic variants and help in identifying causative genes associated with reproductive traits in the species.

Detecting novel Indel variants within the GHR gene and their associations with growth traits in Luxi Blackhead sheep

The growth hormone is important in the regulation of metabolism and energy homeostasis and acts through a growth hormone receptor (GHR). In this work, genetic variations within the ovine GHR gene were identified and tested for associations with body morphometric traits in Chinese Luxi Blackhead (LXBH) sheep. Novel deletion loci in the LXBH GHR gene included P2-del-23 bp and P8-del-23 bp indel variants. The polymorphic information content (PIC) was 0.329 in P2-del-23 bp and 0.257 in P8-del-23 bp. Moreover, both indel polymorphisms were not at Hardy-Weinberg equilibrium (p < 0.05) in the LXBH population. Statistical analyses revealed that the P2-del-23 bp and P8-del-23 bp indels were significantly associated (p < 0.05) with several growth traits in rams and ewes, including body weight, body height, chest depth, chest width, chest circumference, cannon circumference, paunch girth and hip width. Among the tested sheep, the body traits of those with genotype DD were superior to those with II and ID genotypes, suggesting that the 'D' allele was responsible for the positive effects on growth traits. Thus, these results indicate that the P2-del-23 bp and P8-del-23 bp indel sites and the DD genotype can be useful in marker-assisted selection in sheep.

Whole-genome sequencing of European autochthonous and commercial pig breeds allows the detection of signatures of selection for adaptation of genetic resources to different breeding and production systems

Background

Natural and artificial directional selection in cosmopolitan and autochthonous pig breeds and wild boars have shaped their genomes and resulted in a reservoir of animal genetic diversity. Signatures of selection are the result of these selection events that have contributed to the adaptation of breeds to different environments and production systems. In this study, we analysed the genome variability of 19 European autochthonous pig breeds (Alentejana, Bísara, Majorcan Black, Basque, Gascon, Apulo-Calabrese, Casertana, Cinta Senese, Mora Romagnola, Nero Siciliano, Sarda, Krškopolje pig, Black Slavonian, Turopolje, Moravka, Swallow-Bellied Mangalitsa, Schwäbisch-Hällisches Schwein, Lithuanian indigenous wattle and Lithuanian White old type) from nine countries, three European commercial breeds (Italian Large White, Italian Landrace and Italian Duroc), and European wild boars, by mining whole-genome sequencing data obtained by using a DNA-pool sequencing approach. Signatures of selection were identified by using a single-breed approach with two statistics [within-breed pooled heterozygosity (H_P) and fixation index (F_ST)] and group-based F_ST approaches, which compare groups of breeds defined according to external traits and use/specialization/type.

Results

We detected more than 22 million single nucleotide polymorphisms (SNPs) across the 23 compared populations and identified 359 chromosome regions showing signatures of selection. These regions harbour genes that are already known or new genes that are under selection and relevant for the domestication process in this species, and that affect several morphological and physiological traits (e.g. coat colours and patterns, body size, number of vertebrae and teats, ear size and conformation, reproductive traits, growth and fat deposition traits). Wild boar related signatures of selection were detected across all the genome of several autochthonous breeds, which suggests that crossbreeding (accidental or deliberate) occurred with wild boars.

Conclusions

Our findings provide a catalogue of genetic variants of many European pig populations and identify genome regions that can explain, at least in part, the phenotypic diversity of these genetic resources.

Genome-Wide Scan for Runs of Homozygosity Identifies Candidate Genes Related to Economically Important Traits in Chinese Merino

Simple Summary

Runs of homozygosity (ROH) are commonly used to estimate inbreeding coefficients and identify selection signatures in livestock population. The present study determined ROH patterns, estimated the inbreeding levels, and identified the genome regions with high ROH frequency (ROH hotspots) in Chinese Merino. Our results showed that the genome of Chinese Merino harbored lower ROH abundance. Moreover, the inbreeding levels were relatively low. Thirteen ROH hotspots consisting of 190 genes were identified. The ROH hotspots overlapped the selective signatures might be associated with body size, horn traits, immune traits and environment adaption. These findings could contribute to an optimum breeding program by identifying the candidate genes related to economically traits in Chinese Merino.

Abstract

In this study, we estimated the number, length, and frequency of runs of homozygosity (ROH) in 635 Chinese Merino and identified genomic regions with high ROH frequency using the OvineSNP50 whole-genome genotyping array. A total of 6039 ROH exceeding 1 Mb were detected in 634 animals. The average number of ROH in each animal was 9.23 and the average length was 5.87 Mb. Most of the ROH were less than 10 Mb, accounting for 88.77% of the total number of detected ROH. In addition, Ovies aries chromosome (OAR) 21 and OAR3 exhibited the highest and lowest coverage of chromosomes by ROH, respectively. OAR1 displayed the highest number of ROH, while the lowest number of ROH was found on OAR24. An inbreeding coefficient of 0.023 was calculated from ROH greater than 1 Mb. Thirteen regions on chromosomes 1, 2, 3, 5, 6, 10, 11, and 16 were found to contain ROH hotspots. Within the genome regions of OAR6 and OAR11, NCAPG/LCORL, FGF11 and TP53 were identified as the candidate genes related to body size, while the genome region of OAR10 harbored RXFP2 gene responsible for the horn trait. These findings indicate the adaptive to directional trait selection in Chinese Merino.

Review on Genomic Regions and Candidate Genes Associated with Economically Important Production and Reproduction Traits in Sheep (Ovies aries)

Sheep (Ovis aries) is one of the most economically, culturally, and socially important domestic animals. They are reared primarily for meat, milk, wool, and fur production. Sheep were reared using natural selection for a long period of time to offer these traits. In fact, this production system has been slowing the productivity and production potential of the sheep. To improve production efficiency and productivity of this animal through genetic improvement technologies, understanding the genetic background of traits such as body growth, weight, carcass quality, fat percent, fertility, milk yield, wool quality, horn type, and coat color is essential. With the development and utilization of animal genotyping technologies and gene identification methods, many functional genes and genetic variants associated with economically important phenotypic traits have been identified and annotated. This is useful and presented an opportunity to increase the pace of animal genetic gain. Quantitative trait loci and genome wide association study have been playing an important role in identifying candidate genes and animal characterization. This review provides comprehensive information on the identified genomic regions and candidate genes associated with production and reproduction traits, and gene function in sheep.

Recent advances in understanding genetic variants associated with growth, carcass and meat productivity traits in sheep (Ovis aries): an update

Identification of quantitative trait loci (QTLs) and candidate genes that affect growth intensity is a prerequisite for the marker-assisted selection of economically important traits. The number of QTL studies on sheep is relatively small in comparison to those on cattle and pigs. The current QTL sheep database - Sheep QTLdb - contains information on 1658 QTLs for 225 different traits. A few genes and markers associated with growth, carcass and meat productivity traits have been reported. The information about QTLs from the Sheep QTLdb cannot be directly used in marker-assisted selection due to the lack of essential information such as effective and reference alleles, the effect direction etc., and it requires manual curation and validation. In this study we performed a comprehensive search for QTLs focusing on single nucleotide polymorphisms (SNPs) associated with growth and meat traits in sheep. The database contains information about 156 SNP-trait associations (123 unique SNPs) and a list of 165 associated genes. The updated information is freely available at https://github.com/Defrag1236/Ovines_2018 (last access: 18 September 2019). This information can be useful for further association studies and preliminary estimation of genetic variability for economically important traits in different breeds.

Runs of homozygosity and signatures of selection: a comparison among eight local Swiss sheep breeds

A dataset consisting of 787 animals with high-density SNP chip genotypes (346 774 SNPs) and 939 animals with medium-density SNP chip genotypes (33 828 SNPs) from eight indigenous Swiss sheep breeds was analyzed to characterize population structure, quantify genomic inbreeding based on runs of homozygosity and identify selection signatures. In concordance with the recent known history of these breeds, the highest genetic diversity was observed in Engadine Red sheep and the lowest in Valais Blacknose sheep. Correlation between F_PED and F_ROH was around 0.50 and thereby lower than that found in similar studies in cattle. Mean F_ROH estimates from medium-density data and HD data were highly correlated (0.95). Signatures of selection and candidate gene analysis revealed that the most prominent signatures of selection were found in the proximity of genes associated with body size (NCAPG, LCORL, LAP3, SPP1, PLAG1, ALOX12, TP53), litter size (SPP1), milk production (ABCG2, SPP1), coat color (KIT, ASIP, TBX3) and horn status (RXFP2). For the Valais Blacknose sheep, the private signatures in proximity of genes/QTL influencing body size, coat color and fatty acid composition were confirmed based on runs of homozygosity analysis. These private signatures underline the genetic uniqueness of the Valais Blacknose sheep breed. In conclusion, we identified differences in the genetic make-up of Swiss sheep breeds, and we present relevant candidate genes responsible for breed differentiation in locally adapted breeds.