Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping

Analysis of 206 whole-genome resequencing reveals selection signatures associated with breed-specific traits in Hu sheep

As an invaluable Chinese sheep germplasm resource, Hu sheep are renowned for their high fertility and beautiful wavy lambskins. Their distinctive characteristics have evolved over time through a combination of artificial and natural selection. Identifying selection signatures in Hu sheep can provide a straightforward insight into the mechanism of selection and further uncover the candidate genes associated with breed-specific traits subject to selection. Here, we conducted whole-genome resequencing on 206 Hu sheep individuals, each with an approximate 6-fold depth of coverage. And then we employed three complementary approaches, including composite likelihood ratio, integrated haplotype homozygosity score and the detection of runs of homozygosity, to detect selection signatures. In total, 10 candidate genomic regions displaying selection signatures were simultaneously identified by multiple methods, spanning 88.54 Mb. After annotating, these genomic regions harbored collectively 92 unique genes. Interestingly, 32 candidate genes associated with reproduction were distributed in nine genomic regions detected. Out of them, two stood out as star candidates: BMPR1B and GNRH2, both of which have documented associations with fertility, and a HOXA gene cluster (HOXA1-5, HOXA9, HOXA10, HOXA11 and HOXA13) had also been linked to fertility. Additionally, we identified other genes that are related to hair follicle development (LAMTOR3, EEF1A2), ear size (HOXA1, KCNQ2), fat tail formation (HOXA10, HOXA11), growth and development (FAF1, CCNDBP1, GJB2, GJA3), fat deposition (ACOXL, JAZF1, HOXA3, HOXA4, HOXA5, EBF4), immune (UBR1, FASTKD5) and feed intake (DAPP1, RNF17, NPBWR2). Our results offer novel insights into the genetic mechanisms underlying the selection of breed-specific traits in Hu sheep and provide a reference for sheep genetic improvement programs.

Livestock species as emerging models for genomic imprinting

Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.

Revelation of genetic diversity and genomic footprints of adaptation in Indian pig breeds

In the present study, the genetic diversity measures among four Indian domestic breeds of pig namely Agonda Goan, Ghurrah, Ghungroo, and Nicobari, of different agro-climatic regions of country were explored and compared with European commercial breeds, European wild boar and Chinese domestic breeds. The double digest restriction site-associated DNA sequencing (ddRADseq) data of Indian pigs (102) and Landrace (10 animals) were generated and whole genome sequencing data of exotic pigs (60 animals) from public data repository were used in the study. The principal component analysis (PCA), admixture analysis and phylogenetic analysis revealed that Indian breeds were closer in ancestry to Chinese breeds than European breeds. European breeds exhibited highest genetic diversity measures among all the considered breeds. Among Indian breeds, Agonda Goan and Ghurrah were found to be more genetically diverse than Nicobari and Ghungroo. The selection signature regions in Indian pigs were explored using iHS and XP-EHH, and during iHS analysis, it was observed that genes related to growth, reproduction, health, meat quality, sensory perception and behavior were found to be under selection pressure in Indian pig breeds. Strong selection signatures were recorded in 24.25-25.25 Mb region of SSC18, 123.25-124 Mb region of SSC15 and 118.75-119.5 Mb region of SSC2 in most of the Indian breeds upon pairwise comparison with European commercial breeds using XP-EHH. These regions were harboring some important genes such as EPHA4 for thermotolerance, TAS2R16, FEZF1, CADPS2 and PTPRZ1 for adaptability to scavenging system of rearing, TRIM36 and PGGT1B for disease resistance and CCDC112, PIAS1, FEM1B and ITGA11 for reproduction.

Preselecting Variants from Large-Scale Genome-Wide Association Study Meta-Analyses Increases the Genomic Prediction Accuracy of Growth and Carcass Traits in Large White Pigs

Preselected variants associated with the trait of interest from genome-wide association studies (GWASs) are available to improve genomic prediction in pigs. The objectives of this study were to use preselected variants from a large GWAS meta-analysis to assess the impact of single-nucleotide polymorphism (SNP) preselection strategies on genome prediction of growth and carcass traits in pigs. We genotyped 1018 Large White pigs using medium (50k) SNP arrays and then imputed SNPs to sequence level by utilizing a reference panel of 1602 whole-genome sequencing samples. We tested the effects of different proportions of selected top SNPs across different SNP preselection strategies on genomic prediction. Finally, we compared the prediction accuracies by employing genomic best linear unbiased prediction (GBLUP), genomic feature BLUP and three weighted GBLUP models. SNP preselection strategies showed an average improvement in accuracy ranging from 0.3 to 2% in comparison to the SNP chip data. The accuracy of genomic prediction exhibited a pattern of initial increase followed by decrease, or continuous decrease across various SNP preselection strategies, as the proportion of selected top SNPs increased. The highest level of prediction accuracy was observed when utilizing 1 or 5% of top SNPs. Compared with the GBLUP model, the utilization of estimated marker effects from a GWAS meta-analysis as SNP weights in the BLUP|GA model improved the accuracy of genomic prediction in different SNP preselection strategies. The new SNP preselection strategies gained from this study bring opportunities for genomic prediction in limited-size populations in pigs.

Integration of non-additive genome-wide association study with a multi-tissue transcriptome analysis of growth and carcass traits in Duroc pigs

Growth and carcass traits are of economic importance in the pig production, which affect pork quality and profitability of finishing pig production. This study used whole-genome and transcriptome sequencing technologies to identify potential candidate genes affecting growth and carcass traits in Duroc pigs. The medium (50-60 k) single nucleotide polymorphism (SNP) arrays of 4 154 Duroc pigs from three populations were imputed to whole-genome sequence data, yielding 10 463 227 markers on 18 autosomes. The dominance heritabilities estimated for growth and carcass traits ranged from 0.000 ± 0.041 to 0.161 ± 0.054. Using non-additive genome-wide association study (GWAS), we identified 80 dominance quantitative trait loci for growth and carcass traits at genome-wide significance (false discovery rate < 5%), 15 of which were also detected in our additive GWAS. After fine mapping, 31 candidate genes for dominance GWAS were annotated, and 8 of them were highlighted that have been previously reported to be associated with growth and development (e.g. SNX14, RELN and ENPP2), autosomal recessive diseases (e.g. AMPH, SNX14, RELN and CACNB4) and immune response (e.g. UNC93B1 and PPM1D). By integrating the lead SNPs with RNA-seq data of 34 pig tissues from the Pig Genotype-Tissue Expression project (https://piggtex.farmgtex.org/), we found that the rs691128548, rs333063869, and rs1110730611 have significantly dominant effects for the expression of SNX14, AMPH and UNC93B1 genes in tissues related to growth and development for pig, respectively. Finally, the identified candidate genes were significantly enriched for biological processes involved in the cell and organ development, lipids catabolic process and phosphatidylinositol 3-kinase signalling (P < 0.05). These results provide new molecular markers for meat production and quality selection of pig as well as basis for deciphering the genetic mechanisms of growth and carcass traits.

Genome-wide association study reveals candidate genes for pollution excreta traits in pigs

Excreta traits comprise a very important characteristic in breeding that have been neglected for a long time. With the growth of intensive pig farming, plenty of environment problems have been raised, and people have begun to pay attention to pig excreta behaviors from genetics and breeding perspectives. However, the genetic architecture of excreta traits remains unclear. To investigate the genetic architecture of excreta traits in pigs, eight excreta traits and feed conversion ratio (FCR) were analyzed in this study. We performed genome-wide association studies (GWASs) on 213 Yorkshire pigs and estimated genetic parameters for a total number of 290 pigs, comprising 213 Yorkshire, 52 Landrace and 25 Duroc. After analysis, eight and 22 genome-wide significant SNPs were detected for FCR and the eight excreta traits in single-trait GWASs separately, and 18 were detected in a multi-trait meta-analysis for excreta traits, six of which were detected in both the single-trait and the multi-trait GWAS. Eighty, 182 and 133 genes were detected within 1 Mb of the genome-wide significant SNPs for FCR, excreta traits and multi-trait meta-analysis, respectively. Five candidate genes (BCKDC, DBT, ANKRD7, SHPRH and HCRT) with biochemical and physiological effects relevant to feed efficiency and excreta traits might be interesting markers for future breeding. Meanwhile, functional enrichment analysis indicates that most of the significant pathways are associated with the glutathione catabolic process, DNA topological change and replication fork protection complex. This study reveals the architecture of excreta traits in commercial pigs and offers an opportunity for decreasing the pollution from excreta using genomic selection in pigs.

Intermuscular adipose tissue in metabolic disease

Intermuscular adipose tissue (IMAT) is a distinct adipose depot described in early reports as a 'fatty replacement' or 'muscle fat infiltration' that was linked to ageing and neuromuscular disease. Later studies quantifying IMAT with modern in vivo imaging methods (computed tomography and magnetic resonance imaging) revealed that IMAT is proportionately higher in men and women with type 2 diabetes mellitus and the metabolic syndrome than in people without these conditions and is associated with insulin resistance and poor physical function with ageing. In parallel, agricultural research has provided extensive insight into the role of IMAT and other muscle lipids in muscle (that is, meat) quality. In addition, studies using rodent models have shown that IMAT is a bona fide white adipose tissue depot capable of robust triglyceride storage and turnover. Insight into the importance of IMAT in human biology has been limited by the dearth of studies on its biological properties, that is, the quality of IMAT. However, in the past few years, investigations have begun to determine that IMAT has molecular and metabolic features that distinguish it from other adipose tissue depots. These studies will be critical to further decipher the role of IMAT in health and disease and to better understand its potential as a therapeutic target.

DNA methylation and waist-to-hip ratio: an epigenome-wide association study in Chinese monozygotic twins

PURPOSE

Epigenetic signatures such as DNA methylation may be associated with specific obesity traits. We performed an epigenome-wide association study (EWAS) by combining with the waist-to-hip ratio (WHR)-discordant monozygotic (MZ) twin design in an attempt to identify genetically independent DNA methylation marks associated with abdominal obesity in Northern Han Chinese and to determine the causation underlying.

METHODS

A total of 60 WHR discordant MZ twin pairs were selected from the Qingdao Twin Registry, China. Generalized estimated equation (GEE) model was used to regress the methylation level of CpG sites on WHR. The Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was used to assess the temporal relationship between methylation and WHR. Gene expression analysis was conducted to validate the results of differentially methylated analyses.

RESULTS

EWAS identified 92 CpG sites with the level of P < 10^- 4 which were annotated to 32 genes, especially CADPS2, TUSC5, ZCCHC14, CORO7, COL23A1, CACNA1C, CYP26B1, and BCAT1. ICE FALCON showed significant causality between DNA methylation of several genes and WHR (P < 0.05). In region-based analysis, 14 differentially methylated regions (DMRs) located at 15 genes (slk-corrected P < 0.05) were detected. The gene expression analysis identified the significant correlation between expression levels of 5 differentially methylated genes and WHR (P < 0.05).

CONCLUSIONS

Our study identifies the associations between specific epigenetic variations and WHR in Northern Han Chinese. These DNA methylation signatures may have value as diagnostic biomarkers and provide novel insights into the molecular mechanisms of pathogenesis.

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.

Lost pigs of Angola: Whole genome sequencing reveals unique regions of selection with emphasis on metabolism and feed efficiency

Angola, in the western coast of Africa, has been through dramatic social events that have led to the near-disappearance of native swine populations, and the recent introduction of European exotic breeds has also contributed to the erosion of this native swine repertoire. In an effort to investigate the genetic basis of native pigs in Angola (ANG) we have generated whole genomes from animals of a remote local pig population in Huambo province, which we have compared with 78 genomes of European and Asian pig breeds as well as European and Asian wild boars that are currently in public domain. Analyses of population structure showed that ANG pigs grouped within the European cluster and were clearly separated from Asian pig breeds. Pairwise F_ST ranged from 0.14 to 0.26, ANG pigs display lower levels of genetic differentiation towards European breeds. Finally, we have identified candidate regions for selection using a complementary approach based on various methods. All results suggest that selection towards feed efficiency and metabolism has occurred. Moreover, all analysis identified CDKAL1 gene, which is related with insulin and cholesterol metabolism, as a candidate gene overlapping signatures of selection unique to ANG pigs. This study presents the first assessment of the genetic relationship between ANG pigs and other world breeds and uncovers selection signatures that may indicate adaptation features unique to this important genetic resource.

Genome-Wide Association Study Reveals Additive and Non-Additive Effects on Growth Traits in Duroc Pigs

Growth rate plays a critical role in the pig industry and is related to quantitative traits controlled by many genes. Here, we aimed to identify causative mutations and candidate genes responsible for pig growth traits. In this study, 2360 Duroc pigs were used to detect significant additive, dominance, and epistatic effects associated with growth traits. As a result, a total number of 32 significant SNPs for additive or dominance effects were found to be associated with various factors, including adjusted age at a specified weight (AGE), average daily gain (ADG), backfat thickness (BF), and loin muscle depth (LMD). In addition, the detected additive significant SNPs explained 2.49%, 3.02%, 3.18%, and 1.96% of the deregressed estimated breeding value (DEBV) variance for AGE, ADG, BF, and LMD, respectively, while significant dominance SNPs could explain 2.24%, 13.26%, and 4.08% of AGE, BF, and LMD, respectively. Meanwhile, a total of 805 significant epistatic effects SNPs were associated with one of ADG, AGE, and LMD, from which 11 sub-networks were constructed. In total, 46 potential genes involved in muscle development, fat deposition, and regulation of cell growth were considered as candidates for growth traits, including CD55 and NRIP1 for AGE and ADG, TRIP11 and MIS2 for BF, and VRTN and ZEB2 for LMD, respectively. Generally, in this study, we detected both new and reported variants and potential candidate genes for growth traits of Duroc pigs, which might to be taken into account in future molecular breeding programs to improve the growth performance of pigs.

Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency

Despite the significant improvement of feed efficiency (FE) in pigs over the past decades, feed costs remain a major challenge for producers profitability. Improving FE is a top priority for the global swine industry. A deeper understanding of the biology underlying FE is crucial for making progress in genetic improvement of FE traits. This review comprehensively discusses the topics related to the FE in pigs including: measurements, genetics, genomics, biological pathways and the advanced technologies and methods involved in FE improvement. We first provide an update of heritability for different FE indicators and then characterize the correlations of FE traits with other economically important traits. Moreover, we present the quantitative trait loci (QTL) and possible candidate genes associated with FE in pigs and outline the most important biological pathways related to the FE traits in pigs. Finally, we present possible ways to improve FE in swine including the implementation of genomic selection, new technologies for measuring the FE traits, and the potential use of genome editing and omics technologies.

Applications of Omics Technology for Livestock Selection and Improvement

Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals’ actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions.

Adipocytes-derived exosomal microRNA-1224 inhibits M2 macrophage polarization in obesity-induced adipose tissue inflammation via MSI2-mediated Wnt/β-catenin axis

SCOPE

Phenotypic switch of macrophage polarization in adipose tissue has been associated with obesity-induced adipose tissue inflammation (OATI). Therefore, we aimed to explore the possible mechanism of adipocytes-derived exosomes (ADEs) carrying microRNA-1224 (miR-1224) in M2 macrophage polarization of OATI.

METHODS AND RESULTS

We developed miR-1224-knockout (miR-1224-KO) mice for this study, and isolated primary adipocytes from high-fat diet (HFD) or normal diet (SD)-fed mice. ADEs were extracted and cocultured with bone marrow-derived macrophages (BMDMs). The macrophagic crown-like structures (CLS) and M1 and M2 phenotype macrophages in epididymal white adipose tissue (epiWAT) were observed by immunohistochemistry and flow cytometry. The obtained data indicated that miR-1224 was highly expressed in adipose tissues and adipocytes of obese mice. miR-1224 knockout decreased CLS number and increased M2 macrophages polarization in epiWAT. In addition, miR-1224 could be transferred to BMDMs via ADEs, which targeted musashi RNA binding protein 2 (MSI2) expression and inactivated Wnt/β-catenin pathway, inhibiting macrophage M2 polarization and promoting inflammatory factor release.

CONCLUSION

Exosomal miR-1224 derived by adipocytes targets MSI2 and blocks the Wnt/β-catenin pathway, which inhibits macrophage M2 polarization and promotes inflammatory factor release, ultimately promoting OATI. This article is protected by copyright. All rights reserved.

MicroRNAs signatures associated with vulnerability to food addiction in mice and humans

Food addiction is characterized by a loss of behavioral control over food intake and is associated with obesity and other eating disorders. The mechanisms underlying this behavioral disorder are largely unknown. We aimed to investigate the changes in miRNA expression promoted by food addiction in animals and humans and their involvement in the mechanisms underlying the behavioral hallmarks of this disorder. We found sharp similitudes between miRNA signatures in the medial prefrontal cortex (mPFC) of our animal cohort and circulating miRNA levels in our human cohort, which allowed us to identify several miRNAs of potential interest in the development of this disorder. Tough decoy (TuD) inhibition of miRNA-29c-3p in the mouse mPFC promoted persistence of the response and enhanced vulnerability to developing food addiction, whereas miRNA-665-3p inhibition promoted compulsion-like behavior and also enhanced food addiction vulnerability. In contrast, we found that miRNA-137-3p inhibition in the mPFC did not lead to the development of food addiction. Therefore, miRNA-29c-3p and miRNA-665-3p could be acting as protective factors with regard to food addiction. We believe the elucidation of these epigenetic mechanisms will lead to advances toward identifying innovative biomarkers and possible future interventions for food addiction and related disorders based on the strategies now available to modify miRNA activity and expression.

Genome-wide analysis of runs of homozygosity in Italian Mediterranean buffalo

Runs of homozygosity (ROH) are a powerful tool to explore patterns of genomic inbreeding in animal populations and detect signatures of selection. The present study used ROH analysis to evaluate the genome-wide patterns of homozygosity, inbreeding levels, and distribution of ROH islands using the SNP data sets from 899 Mediterranean buffaloes. A total of 42,433 ROH segments were identified, with an average of 47.20 segments per individual. The ROH comprising mostly shorter segments (1-4 Mb) accounted for approximately 72.29% of all ROH. In contrast, the larger ROH (>8 Mb) class accounted for only 7.97% of all ROH segments. Estimated inbreeding coefficients from ROH (F_ROH) ranged from 0.0201 to 0.0371. Pearson correlations between F_ROH and genomic relationship matrix increased with the increase of ROH length. We identified ROH hotspots in 12 genomic regions, located on chromosomes 1, 2, 3, 5, 17, and 19, harboring a total of 122 genes. Protein-protein interaction (PPI) analysis revealed the clustering of these genes into 7 PPI networks. Many genes located in these regions were associated with different production traits. In addition, 5 ROH islands overlapped with cattle quantitative trait loci that were mainly associated with milk traits. These findings revealed the genome-wide autozygosity patterns and inbreeding levels in Mediterranean buffalo. Our study identified many candidate genes related to production traits that could be used to assist in selective breeding for genetic improvement of buffalo.

Genomic Basis of Striking Fin Shapes and Colors in the Fighting Fish

Resolving the genomic basis underlying phenotypic variations is a question of great importance in evolutionary biology. However, understanding how genotypes determine the phenotypes is still challenging. Centuries of artificial selective breeding for beauty and aggression resulted in a plethora of colors, long-fin varieties, and hyper-aggressive behavior in the air-breathing Siamese fighting fish (Betta splendens), supplying an excellent system for studying the genomic basis of phenotypic variations. Combining whole-genome sequencing, quantitative trait loci mapping, genome-wide association studies, and genome editing, we investigated the genomic basis of huge morphological variation in fins and striking differences in coloration in the fighting fish. Results revealed that the double tail, elephant ear, albino, and fin spot mutants each were determined by single major-effect loci. The elephant ear phenotype was likely related to differential expression of a potassium ion channel gene, kcnh8. The albinotic phenotype was likely linked to a cis-regulatory element acting on the mitfa gene and the double-tail mutant was suggested to be caused by a deletion in a zic1/zic4 coenhancer. Our data highlight that major loci and cis-regulatory elements play important roles in bringing about phenotypic innovations and establish Bettas as new powerful model to study the genomic basis of evolved changes.

A Systematic Review of Genomic Regions and Candidate Genes Underlying Behavioral Traits in Farmed Mammals and Their Link with Human Disorders

Simple Summary

This study is a comprehensive review of genomic regions associated with animal behavior in farmed mammals (beef and dairy cattle, pigs, and sheep) which contributes to a better understanding of the biological mechanisms influencing the target indicator trait and to gene expression studies by suggesting genes likely controlling the trait, and it will be useful in optimizing genomic predictions of breeding values incorporating biological information. Behavioral mechanisms are complex traits, genetically controlled by multiple genes spread across the whole genome. The majority of the genes identified in cattle, pigs, and sheep in association with a plethora of behavioral measurements (e.g., temperament, terrain use, milking speed, tail biting, and sucking reflex) are likely controlling stimuli reception (e.g., olfactory), internal recognition of stimuli (e.g., neuroactive ligand–receptor interaction), and body response to a stimulus (e.g., blood pressure, fatty acidy metabolism, hormone signaling, and inflammatory pathways). Six genes were commonly identified between cattle and pigs. About half of the genes for behavior identified in farmed mammals were also identified in humans for behavioral, mental, and neuronal disorders. Our findings indicate that the majority of the genes identified are likely controlling animal behavioral outcomes because their biological functions as well as potentially differing allele frequencies between two breed groups (subjectively) clustered based on their temperament characteristics.

Abstract

The main objectives of this study were to perform a systematic review of genomic regions associated with various behavioral traits in the main farmed mammals and identify key candidate genes and potential causal mutations by contrasting the frequency of polymorphisms in cattle breeds with divergent behavioral traits (based on a subjective clustering approach). A total of 687 (cattle), 1391 (pigs), and 148 (sheep) genomic regions associated with 37 (cattle), 55 (pigs), and 22 (sheep) behavioral traits were identified in the literature. In total, 383, 317, and 15 genes overlap with genomic regions identified for cattle, pigs, and sheep, respectively. Six common genes (e.g., NR3C2, PITPNM3, RERG, SPNS3, U6, and ZFAT) were found for cattle and pigs. A combined gene-set of 634 human genes was produced through identified homologous genes. A total of 313 out of 634 genes have previously been associated with behavioral, mental, and neurologic disorders (e.g., anxiety and schizophrenia) in humans. Additionally, a total of 491 candidate genes had at least one statistically significant polymorphism (p-value < 0.05). Out of those, 110 genes were defined as having polymorphic regions differing in greater than 50% of exon regions. Therefore, conserved genomic regions controlling behavior were found across farmed mammal species and humans.

The distribution of runs of homozygosity in the genome of river and swamp buffaloes reveals a history of adaptation, migration and crossbred events

Background

Water buffalo is one of the most important livestock species in the world. Two types of water buffalo exist: river buffalo (Bubalus bubalis bubalis) and swamp buffalo (Bubalus bubalis carabanensis). The buffalo genome has been recently sequenced, and thus a new 90 K single nucleotide polymorphism (SNP) bead chip has been developed. In this study, we investigated the genomic population structure and the level of inbreeding of 185 river and 153 swamp buffaloes using runs of homozygosity (ROH). Analyses were carried out jointly and separately for the two buffalo types.

Results

The SNP bead chip detected in swamp about one-third of the SNPs identified in the river type. In total, 18,116 ROH were detected in the combined data set (17,784 SNPs), and 16,251 of these were unique. ROH were present in both buffalo types mostly detected (~ 59%) in swamp buffalo. The number of ROH per animal was larger and genomic inbreeding was higher in swamp than river buffalo. In the separated datasets (46,891 and 17,690 SNPs for river and swamp type, respectively), 19,760 and 10,581 ROH were found in river and swamp, respectively. The genes that map to the ROH islands are associated with the adaptation to the environment, fitness traits and reproduction.

Conclusions

Analysis of ROH features in the genome of the two water buffalo types allowed their genomic characterization and highlighted differences between buffalo types and between breeds. A large ROH island on chromosome 2 was shared between river and swamp buffaloes and contained genes that are involved in environmental adaptation and reproduction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00616-3.

Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs

Feed efficiency (FE) is a key trait in pig production, as improvement in FE has positive economic and environmental impact. FE is a complex phenotype and testing animals for FE is costly. Therefore, there has been a desire to find functionally relevant single nucleotide polymorphisms (SNPs) as biomarkers, to improve our biological understanding of FE as well as accuracy of genomic prediction for FE. We have performed a cis- and trans- eQTL (expression quantitative trait loci) analysis, in a population of Danbred Durocs (N = 11) and Danbred Landrace (N = 27) using both a linear and ANOVA model based on muscle tissue RNA-seq. We analyzed a total of 1425x19179 or 2.7x10⁷ Gene-SNP combinations in eQTL detection models for FE. The 1425 genes were from RNA-Seq based differential gene expression analyses using 25880 genes related to FE and additionally combined with mitochondrial genes. The 19179 SNPs were from applying stringent quality control and linkage disequilibrium filtering on genotype data using a GGP Porcine HD 70k SNP array. We applied 1000 fold bootstrapping and enrichment analysis to further validate and analyze our detected eQTLs. We identified 13 eQTLs with FDR < 0.1, affecting several genes found in previous studies of commercial pig breeds. Examples include MYO19, CPT1B, ACSL1, IER5L, CPT1A, SUCLA2, CSRNP1, PARK7 and MFF. The bootstrapping results showed statistically significant enrichment (p-value<2.2x10^-16) of eQTLs with p-value < 0.01 in both cis and trans-eQTLs. Enrichment analysis of top trans-eQTLs revealed high enrichment for gene categories and gene ontologies associated with genomic context and expression regulation. This included transcription factors (p-value = 1.0x10^-13), DNA-binding (GO:0003677, p-value = 8.9x10^-14), DNA-binding transcription factor activity (GO:0003700,) nucleus gene (GO:0005634, p-value<2.2x10^-16), negative regulation of expression (GO:0010629, p-value<2.2x10^-16). These results would be useful for future genome assisted breeding of pigs to improve FE, and in the improved understanding of the functional mechanism of trans eQTLs.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Genomics of Heat Tolerance in Reproductive Performance Investigated in Four Independent Maternal Lines of Pigs

Improving swine climatic resilience through genomic selection has the potential to minimize welfare issues and increase the industry profitability. The main objective of this study was to investigate the genetic and genomic determinism of tolerance to heat stress in four independent purebred populations of swine. Three female reproductive traits were investigated: total number of piglets born (TNB), number of piglets born alive (NBA) and average birth weight (ABW). More than 80,000 phenotypic and 12,000 genotyped individuals were included in this study. Genomic random-regression models were fitted regressing the phenotypes of interest on a set of 95 environmental covariates extracted from public weather station records. The models yielded estimates of (genomic) reactions norms for individual pigs, as indicator of heat tolerance. Heat tolerance is a heritable trait, although the heritabilities are larger under comfortable than heat-stress conditions (larger than 0.05 vs. 0.02 for TNB; 0.10 vs. 0.05 for NBA; larger than 0.20 vs. 0.10 for ABW). TNB showed the lowest genetic correlation (-38%) between divergent climatic conditions, being the trait with the strongest impact of genotype by environment interaction, while NBA and ABW showed values slightly negative or equal to zero reporting a milder impact of the genotype by environment interaction. After estimating genetic parameters, a genome-wide association study was performed based on the single-step GBLUP method. Heat tolerance was observed to be a highly polygenic trait. Multiple and non-overlapping genomic regions were identified for each trait based on the genomic breeding values for reproductive performance under comfortable or heat stress conditions. Relevant regions were found on chromosomes (SSC) 1, 3, 5, 6, 9, 11, and 12, although there were important regions across all autosomal chromosomes. The genomic region located on SSC9 appears to be of particular interest since it was identified for two traits (TNB and NBA) and in two independent populations. Heat tolerance based on reproductive performance indicators is a heritable trait and genetic progress for heat tolerance can be achieved through genetic or genomic selection. Various genomic regions and candidate genes with important biological functions were identified, which will be of great value for future functional genomic studies.

Multi-breed genome-wide association studies across countries for electronically recorded behavior traits in local dual-purpose cows

Basic bovine behavior is a crucial parameter influencing cattle domestication. In addition, behavior has an impact on cattle productivity, welfare and adaptation. The aim of the present study was to infer quantitative genetic and genomic mechanisms contributing to natural dual-purpose cow behavior in grazing systems. In this regard, we genotyped five dual-purpose breeds for a dense SNP marker panel from four different European countries. All cows from the across-country study were equipped with the same electronic recording devices. In this regard, we analyzed 97,049 longitudinal sensor behavior observations from 319 local dual-purpose cows for rumination, feeding, basic activity, high active, not active and ear temperature. According to the specific sensor behaviors and following a welfare protocol, we computed two different welfare indices. For genomic breed characterizations and multi-breed genome-wide association studies, sensor traits and test-day production records were merged with 35,826 SNP markers per cow. For the estimation of variance components, we used the pedigree relationship matrix and a combined similarity matrix that simultaneously included both pedigree and genotypes. Heritabilities for feeding, high active and not active were in a moderate range from 0.16 to 0.20. Estimates were very similar from both relationship matrix-modeling approaches and had quite small standard errors. Heritabilities for the remaining sensor traits (feeding, basic activity, ear temperature) and welfare indices were lower than 0.09. Five significant SNPs on chromosomes 11, 17, 27 and 29 were associated with rumination, and two different SNPs significantly influenced the sensor traits “not active” (chromosome 13) and “feeding” (chromosome 23). Gene annotation analyses inferred 22 potential candidate genes with a false discovery rate lower than 20%, mostly associated with rumination (13 genes) and feeding (8 genes). Mendelian randomization based on genomic variants (i.e., the instrumental variables) was used to infer causal inference between an exposure and an outcome. Significant regression coefficients among behavior traits indicate that all specific behavioral mechanisms contribute to similar physiological processes. The regression coefficients of rumination and feeding on milk yield were 0.10 kg/% and 0.12 kg/%, respectively, indicating their positive influence on dual-purpose cow productivity. Genomically, an improved welfare behavior of grazing cattle, i.e., a higher score for welfare indices, was significantly associated with increased fat and protein percentages.

Significance testing and genomic inflation factor using high-density genotypes or whole-genome sequence data

Significance testing for genome‐wide association study (GWAS) with increasing SNP density up to whole‐genome sequence data (WGS) is not straightforward, because of strong LD between SNP and population stratification. Therefore, the objective of this study was to investigate genomic control and different significance testing procedures using data from a commercial pig breeding scheme. A GWAS was performed in GCTA with data of 4,964 Large White pigs using medium density, high density or imputed whole‐genome sequence data, fitting a genomic relationship matrix based on a leave‐one–chromosome‐out approach to account for population structure. Subsequently, genomic inflation factors were assessed on whole‐genome level and the chromosome level. To establish a significance threshold, permutation testing, Bonferroni corrections using either the total number of SNPs or the number of independent chromosome fragments, and false discovery rates (FDR) using either the Benjamini–Hochberg procedure or the Benjamini and Yekutieli procedure were evaluated. We found that genomic inflation factors did not differ between different density genotypes but do differ between chromosomes. Also, the leave‐one‐chromosome‐out approach for GWAS or using the pedigree relationships did not account appropriately for population stratification and gave strong genomic inflation. Regarding different procedures for significance testing, when the aim is to find QTL regions that are associated with a trait of interest, we recommend applying the FDR following the Benjamini and Yekutieli approach to establish a significance threshold that is adjusted for multiple testing. When the aim is to pinpoint a specific mutation, the more conservative Bonferroni correction based on the total number of SNPs is more appropriate, till an appropriate method is established to adjust for the number of independent tests.

Genomic Analysis Reveals Specific Patterns of Homozygosity and Heterozygosity in Inbred Pigs

The inbred strain of miniature pig is an ideal model for biomedical research due to its high level of homozygosity. In this study, we investigated genetic diversity, relatedness, homozygosity, and heterozygosity using the Porcine SNP60K BeadChip in both inbred and non-inbred Wuzhishan pigs (WZSPs). Our results from multidimensional scaling, admixture, and phylogenetic analyses indicated that the inbred WZSP, with its unique genetic properties, can be utilized as a novel genetic resource for pig genome studies. Inbreeding depression and run of homozygosity (ROH) analyses revealed an average of 61 and 12 ROH regions in the inbred and non-inbred genomes of WZSPs, respectively. By investigating ROH number, length, and distribution across generations, we further briefly studied the impacts of recombination and demography on ROH in these WZSPs. Finally, we explored the SNPs with higher heterozygosity across generations and their potential functional implications in the inbred WZSP. We detected 56 SNPs showing constant heterozygosity with He = 1 across six generations in inbred pigs, while only one was found in the non-inbred population. Among these SNPs, we observed nine SNPs located in swine RefSeq genes, which were found to be involved in signaling and immune processes. Together, our findings indicate that the inbred-specific pattern of homozygosity and heterozygosity in inbred pigs can offer valuable insights for elucidating the mechanisms of inbreeding in farm animals.

New world goat populations are a genetically diverse reservoir for future use

Western hemisphere goats have European, African and Central Asian origins, and some local or rare breeds are reported to be adapted to their environments and economically important. By-in-large these genetic resources have not been quantified. Using 50 K SNP genotypes of 244 animals from 12 goat populations in United States, Costa Rica, Brazil and Argentina, we evaluated the genetic diversity, population structure and selective sweeps documenting goat migration to the "New World". Our findings suggest the concept of breed, particularly among "locally adapted" breeds, is not a meaningful way to characterize goat populations. The USA Spanish goats were found to be an important genetic reservoir, sharing genomic composition with the wild ancestor and with specialized breeds (e.g. Angora, Lamancha and Saanen). Results suggest goats in the Americas have substantial genetic diversity to use in selection and promote environmental adaptation or product driven specialization. These findings highlight the importance of maintaining goat conservation programs and suggest an awaiting reservoir of genetic diversity for breeding and research while simultaneously discarding concerns about breed designations.

Guanidinoacetic Acid Regulates Myogenic Differentiation and Muscle Growth Through miR-133a-3p and miR-1a-3p Co-mediated Akt/mTOR/S6K Signaling Pathway

Guanidinoacetic acid (GAA), an amino acid derivative that is endogenous to animal tissues including muscle and nerve, has been reported to enhance muscular performance. MicroRNA (miRNA) is a post-transcriptional regulator that plays a key role in nutrient-mediated myogenesis. However, the effects of GAA on myogenic differentiation and skeletal muscle growth, and the potential regulatory mechanisms of miRNA in these processes have not been elucidated. In this study, we investigated the effects of GAA on proliferation, differentiation, and growth in C2C12 cells and mice. The results showed that GAA markedly inhibited the proliferation of myoblasts, along with the down-regulation of cyclin D1 (CCND1) and cyclin dependent kinase 4 (CDK4) mRNA expression, and the upregulation of cyclin dependent kinase inhibitor 1A (P21) mRNA expression. We also demonstrated that GAA treatment stimulated myogenic differentiation 1 (MyoD) and myogenin (MyoG) mRNA expression, resulting in an increase in the myotube fusion rate. Meanwhile, GAA supplementation promoted myotube growth through increase in total myosin heavy chain (MyHC) protein level, myotubes thickness and gastrocnemius muscle cross-sectional area. Furthermore, small RNA sequencing revealed that a total of eight miRNAs, including miR-133a-3p and miR-1a-3p cluster, showed differential expression after GAA supplementation. To further study the function of miR-133a-3p and miR-1a-3p in GAA-induced skeletal muscle growth, we transfected miR-133a-3p and miR-1a-3p mimics into myotube, which also induced muscle growth. Through bioinformatics and a dual-luciferase reporter system, the target genes of miR-133a-3p and miR-1a-3p were determined. These two miRNAs were shown to modulate the Akt/mTOR/S6K signaling pathway by restraining target gene expression. Taken together, these findings suggest that GAA supplementation can promote myoblast differentiation and skeletal muscle growth through miR-133a-3p- and miR-1a-3p-induced activation of the AKT/mTOR/S6K signaling pathway.

Genomic analysis reveals genes affecting distinct phenotypes among different Chinese and western pig breeds

The differences in artificial and natural selection have been some of the factors contributing to phenotypic diversity between Chinese and western pigs. Here, 830 individuals from western and Chinese pig breeds were genotyped using the reduced-representation genotyping method. First, we identified the selection signatures for different pig breeds. By comparing Chinese pigs and western pigs along the first principal component, the growth gene IGF1R; the immune genes IL1R1, IL1RL1, DUSP10, RAC3 and SWAP70; the meat quality-related gene SNORA50 and the olfactory gene OR1F1 were identified as candidate differentiated targets. Further, along a principal component separating Pudong White pigs from others, a potential causal gene for coat colour (EDNRB) was discovered. In addition, the divergent signatures evaluated by F_st within Chinese pig breeds found genes associated with the phenotypic features of coat colour, meat quality and feed efficiency among these indigenous pigs. Second, admixture and genomic introgression analysis were performed. Shan pigs have introgressed genes from Berkshire, Yorkshire and Hongdenglong pigs. The results of introgression mapping showed that this introgression conferred adaption to the local environment and coat colour of Chinese pigs and the superior productivity of western pigs.

An Epigenome-Wide Association Study of Obesity-Related Traits

We conducted an epigenome-wide association study on obesity-related traits. We used data from 2 prospective, population-based cohort studies: the Rotterdam Study (RS) (2006-2013) and the Atherosclerosis Risk in Communities (ARIC) Study (1990-1992). We used the RS (n = 1,450) as the discovery panel and the ARIC Study (n = 2,097) as the replication panel. Linear mixed-effect models were used to assess the cross-sectional associations between genome-wide DNA methylation in leukocytes and body mass index (BMI) and waist circumference (WC), adjusting for sex, age, smoking, leukocyte proportions, array number, and position on array. The latter 2 variables were modeled as random effects. Fourteen 5'-C-phosphate-G-3' (CpG) sites were associated with BMI and 26 CpG sites with WC in the RS after Bonferroni correction (P < 1.07 × 10-7), of which 12 and 13 CpGs were replicated in the ARIC Study, respectively. The most significant novel CpGs were located on the Musashi RNA binding protein 2 gene (MSI2; cg21139312) and the leucyl-tRNA synthetase 2, mitochondrial gene (LARS2; cg18030453) and were associated with both BMI and WC. CpGs at BRDT, PSMD1, IFI44L, MAP1A, and MAP3K5 were associated with BMI. CpGs at LGALS3BP, MAP2K3, DHCR24, CPSF4L, and TMEM49 were associated with WC. We report novel associations between methylation at MSI2 and LARS2 and obesity-related traits. These results provide further insight into mechanisms underlying obesity-related traits, which can enable identification of new biomarkers in obesity-related chronic diseases.

Genetic diversity and divergence among Korean cattle breeds assessed using a BovineHD single-nucleotide polymorphism chip

Objective

In Korea, there are three main cattle breeds, which are distinguished by coat color: Brown Hanwoo (BH), Brindle Hanwoo (BRH), and Jeju Black (JB). In this study, we sought to compare the genetic diversity and divergence among there Korean cattle breeds using a BovineHD chip genotyping array.

Methods

Sample data were collected from 168 cattle in three populations of BH (48 cattle), BRH (96 cattle), and JB (24 cattle). The single-nucleotide polymorphism (SNP) genotyping was performed using the Illumina BovineHD SNP 777K Bead chip.

Results

Heterozygosity, used as a measure of within-breed genetic diversity, was higher in BH (0.293) and BRH (0.296) than in JB (0.266). Linkage disequilibrium decay was more rapid in BH and BRH than in JB, reaching an average r² value of 0.2 before 26 kb in BH and BRH, whereas the corresponding value was reached before 32 kb in JB. Intra-population, inter-population, and Fst analyses were used to identify candidate signatures of positive selection in the genome of a domestic Korean cattle population and 48, 11, and 11 loci were detected in the genomic region of the BRH breed, respectively. A Neighbor-Joining phylogenetic tree showed two main groups: a group comprising BH and BRH on one side and a group containing JB on the other. The runs of homozygosity analysis between Korean breeds indicated that the BRH and JB breeds have high inbreeding within breeds compared with BH. An analysis of differentiation based on a high-density SNP chip showed differences between Korean cattle breeds and the closeness of breeds corresponding to the geographic regions where they are evolving.

Conclusion

Our results indicate that although the Korean cattle breeds have common features, they also show reliable breed diversity.

A genome scan for selection signatures in Taihu pig breeds using next-generation sequencing

Taihu pig breeds are the most prolific breeds of swine in the world, and they also have superior economic traits, including high resistance to disease, superior meat quality, high resistance to crude feed and a docile temperament. The formation of these phenotypic characteristics is largely a result of long-term artificial or natural selection. Therefore, exploring selection signatures in the genomes of the Taihu pigs will help us to identify porcine genes related to productivity traits, disease and behaviour. In this study, we used both intra-population (Relative Extend Haplotype Homozygosity Test (REHH)) and inter-population (the Cross-Population Extend Haplotype Homozygosity Test (XPEHH); F-STATISTICS, F ST ) methods to detect genomic regions that might be under selection process in Taihu pig breeds. As a result, we found 282 (REHH) and 112 (XPEHH) selection signature candidate regions corresponding to 159.78 Mb (6.15%) and 62.29 Mb (2.40%) genomic regions, respectively. Further investigations of the selection candidate regions revealed that many genes under these genomic regions were related to reproductive traits (such as the TLR9 gene), coat colour (such as the KIT gene) and fat metabolism (such as the CPT1A and MAML3 genes). Furthermore, gene enrichment analyses showed that genes under the selection candidate regions were significantly over-represented in pathways related to diseases, such as autoimmune thyroid and asthma diseases. In conclusion, several candidate genes potentially under positive selection were involved in characteristics of Taihu pig. These results will further allow us to better understand the mechanisms of selection in pig breeding.

Genetic Architecture of Feeding Behavior and Feed Efficiency in a Duroc Pig Population

Increasing feed efficiency is a major goal of breeders as it can reduce production cost and energy consumption. However, the genetic architecture of feeding behavior and feed efficiency traits remains elusive. To investigate the genetic architecture of feed efficiency in pigs, three feeding behavior traits (daily feed intake, number of daily visits to feeder, and duration of each visit) and two feed efficiency traits (feed conversion ratio and residual feed intake) were considered. We performed genome-wide association studies (GWASs) of the five traits using a population of 1,008 Duroc pigs genotyped with an Illumina Porcine SNP50K BeadChip. A total of 9 genome-wide (P < 1.54E-06) and 35 suggestive (P < 3.08E-05) single nucleotide polymorphisms (SNPs) were detected. Two pleiotropic quantitative trait loci (QTLs) on SSC 1 and SSC 7 were found to affect more than one trait. Markers WU_10.2_7_18377044 and DRGA0001676 are two key SNPs for these two pleiotropic QTLs. Marker WU_10.2_7_18377044 on SSC 7 contributed 2.16 and 2.37% of the observed phenotypic variance for DFI and RFI, respectively. The other SNP DRGA0001676 on SSC 1 explained 3.22 and 5.46% of the observed phenotypic variance for FCR and RFI, respectively. Finally, functions of candidate genes and gene set enrichment analysis indicate that most of the significant pathways are associated with hormonal and digestive gland secretion during feeding. This study advances our understanding of the genetic mechanisms of feeding behavior and feed efficiency traits and provide an opportunity for increasing feeding efficiency using marker-assisted selection or genomic selection in pigs.

EPS-LASSO: test for high-dimensional regression under extreme phenotype sampling of continuous traits

Motivation

Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g. the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown.

Results

We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors.

Availability and implementation

The source code is available at https://github.com/xu1912/EPSLASSO.

Supplementary information

Supplementary data are available at Bioinformatics online.

Integrative approach using liver and duodenum RNA-Seq data identifies candidate genes and pathways associated with feed efficiency in pigs

This study aims identifying candidate genes and pathways associated with feed efficiency (FE) in pigs. Liver and duodenum transcriptomes of 37 gilts showing high and low residual feed intake (RFI) were analysed by RNA-Seq. Gene expression data was explored through differential expression (DE) and weighted gene co-expression network analyses. DE analysis revealed 55 and 112 differentially regulated genes in liver and duodenum tissues, respectively. Clustering genes according to their connectivity resulted in 23 (liver) and 25 (duodenum) modules of genes with a co-expression pattern. Four modules, one in liver (with 444 co-expressed genes) and three in duodenum (gathering 37, 126 and 41 co-expressed genes), were significantly associated with FE indicators. Intra-module analyses revealed tissue-specific candidate genes; 12 of these genes were also identified as DE between individuals with high and low RFI. Pathways enriched by the list of genes showing DE and/or belonging to FE co-expressed modules included response to oxidative stress, inflammation, immune response, lipid metabolism and thermoregulation. Low overlapping between genes identified in duodenum and liver tissues was observed but heat shock proteins were associated to FE in both tissues. Our results suggest tissue-specific rather than common transcriptome regulatory processes associated with FE in pigs.

Genome-wide association analysis reveals genetic loci and candidate genes for feeding behavior and eating efficiency in Duroc boars

Efficient use of feed resources is a challenge in the pork industry because the largest variability in expenditure is attributed to the cost of fodder. Efficiency of feeding is directly related to feeding behavior. In order to identify genomic regions controlling feeding behavior and eating efficiency traits, 338 Duroc boars were used in this study. The Illumina Porcine SNP60K BeadChip was used for genotyping. Data pertaining to individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of daily visits to feeder (NVD), average duration of each visit (TPV), mean feed intake per visit (FPV), mean feed intake rate (FR), and feed conversion ratio (FCR) were collected for these pigs. Despite the limited sample size, the genome-wide association study was acceptable to detect candidate regions association with feeding behavior and eating efficiency traits in pigs. We detected three genome-wide (P < 1.40E-06) and 11 suggestive (P < 2.79E-05) single nucleotide polymorphism (SNP)-trait associations. Six SNPs were located in genomic regions where quantitative trait loci (QTLs) have previously been reported for feeding behavior and eating efficiency traits in pigs. Five candidate genes (SERPINA3, MYC, LEF1, PITX2, and MAP3K14) with biochemical and physiological roles that were relevant to feeding behavior and eating efficiency were discovered proximal to significant or suggestive markers. Gene ontology analysis indicated that most of the candidate genes were involved in the development of the hypothalamus (GO:0021854, P < 0.0398). Our results provide new insights into the genetic basis of feeding behavior and eating efficiency in pigs. Furthermore, some significant SNPs identified in this study could be incorporated into artificial selection programs for Duroc-related pigs to select for increased feeding efficiency.

Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle

Background

Single nucleotide polymorphism (SNP) arrays for domestic cattle have catalyzed the identification of genetic markers associated with complex traits for inclusion in modern breeding and selection programs. Using actual and imputed Illumina 778K genotypes for 3887 U.S. beef cattle from 3 populations (Angus, Hereford, SimAngus), we performed genome-wide association analyses for feed efficiency and growth traits including average daily gain (ADG), dry matter intake (DMI), mid-test metabolic weight (MMWT), and residual feed intake (RFI), with marker-based heritability estimates produced for all traits and populations.

Results

Moderate and/or large-effect QTL were detected for all traits in all populations, as jointly defined by the estimated proportion of variance explained (PVE) by marker effects (PVE ≥ 1.0%) and a nominal P-value threshold (P ≤ 5e-05). Lead SNPs with PVE ≥ 2.0% were considered putative evidence of large-effect QTL (n = 52), whereas those with PVE ≥ 1.0% but < 2.0% were considered putative evidence for moderate-effect QTL (n = 35). Identical or proximal lead SNPs associated with ADG, DMI, MMWT, and RFI collectively supported the potential for either pleiotropic QTL, or independent but proximal causal mutations for multiple traits within and between the analyzed populations. Marker-based heritability estimates for all investigated traits ranged from 0.18 to 0.60 using 778K genotypes, or from 0.17 to 0.57 using 50K genotypes (reduced from Illumina 778K HD to Illumina Bovine SNP50). An investigation to determine if QTL detected by 778K analysis could also be detected using 50K genotypes produced variable results, suggesting that 50K analyses were generally insufficient for QTL detection in these populations, and that relevant breeding or selection programs should be based on higher density analyses (imputed or directly ascertained).

Conclusions

Fourteen moderate to large-effect QTL regions which ranged from being physically proximal (lead SNPs ≤ 3Mb) to fully overlapping for RFI, DMI, ADG, and MMWT were detected within and between populations, and included evidence for pleiotropy, proximal but independent causal mutations, and multi-breed QTL. Bovine positional candidate genes for these traits were functionally conserved across vertebrate species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3754-y) contains supplementary material, which is available to authorized users.

RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle

Background

The selective breeding of cattle with high-feed efficiencies (FE) is an important goal of beef and dairy cattle producers. Global gene expression patterns in relevant tissues can be used to study the functions of genes that are potentially involved in regulating FE. In the present study, high-throughput RNA sequencing data of liver biopsies from 19 dairy cows were used to identify differentially expressed genes (DEGs) between high- and low-FE groups of cows (based on Residual Feed Intake or RFI). Subsequently, a profile of the pathways connecting the DEGs to FE was generated, and a list of candidate genes and biomarkers was derived for their potential inclusion in breeding programmes to improve FE.

Results

The bovine RNA-Seq gene expression data from the liver was analysed to identify DEGs and, subsequently, identify the molecular mechanisms, pathways and possible candidate biomarkers of feed efficiency. On average, 57 million reads (short reads or short mRNA sequences < ~200 bases) were sequenced, 52 million reads were mapped, and 24,616 known transcripts were quantified according to the bovine reference genome. A comparison of the high- and low-RFI groups revealed 70 and 19 significantly DEGs in Holstein and Jersey cows, respectively. The interaction analysis (high vs. low RFI x control vs. high concentrate diet) showed no interaction effects in the Holstein cows, while two genes showed interaction effects in the Jersey cows. The analyses showed that DEGs act through certain pathways to affect or regulate FE, including steroid hormone biosynthesis, retinol metabolism, starch and sucrose metabolism, ether lipid metabolism, arachidonic acid metabolism and drug metabolism cytochrome P450.

Conclusion

We used RNA-Seq-based liver transcriptomic profiling of high- and low-RFI dairy cows in two breeds and identified significantly DEGs, their molecular mechanisms, their interactions with other genes and functional enrichments of different molecular pathways. The DEGs that were identified were the CYP’s and GIMAP genes for the Holstein and Jersey cows, respectively, which are related to the primary immunodeficiency pathway and play a major role in feed utilization and the metabolism of lipids, sugars and proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3622-9) contains supplementary material, which is available to authorized users.

The use of multiple imputation for the accurate measurements of individual feed intake by electronic feeders

Obtaining accurate individual feed intake records is the key first step in achieving genetic progress toward more efficient nutrient utilization in pigs. Feed intake records collected by electronic feeding systems contain errors (erroneous and abnormal values exceeding certain cutoff criteria), which are due to feeder malfunction or animal-feeder interaction. In this study, we examined the use of a novel data-editing strategy involving multiple imputation to minimize the impact of errors and missing values on the quality of feed intake data collected by an electronic feeding system. Accuracy of feed intake data adjustment obtained from the conventional linear mixed model (LMM) approach was compared with 2 alternative implementations of multiple imputation by chained equation, denoted as MI (multiple imputation) and MICE (multiple imputation by chained equation). The 3 methods were compared under 3 scenarios, where 5, 10, and 20% feed intake error rates were simulated. Each of the scenarios was replicated 5 times. Accuracy of the alternative error adjustment was measured as the correlation between the true daily feed intake (DFI; daily feed intake in the testing period) or true ADFI (the mean DFI across testing period) and the adjusted DFI or adjusted ADFI. In the editing process, error cutoff criteria are used to define if a feed intake visit contains errors. To investigate the possibility that the error cutoff criteria may affect any of the 3 methods, the simulation was repeated with 2 alternative error cutoff values. Multiple imputation methods outperformed the LMM approach in all scenarios with mean accuracies of 96.7, 93.5, and 90.2% obtained with MI and 96.8, 94.4, and 90.1% obtained with MICE compared with 91.0, 82.6, and 68.7% using LMM for DFI. Similar results were obtained for ADFI. Furthermore, multiple imputation methods consistently performed better than LMM regardless of the cutoff criteria applied to define errors. In conclusion, multiple imputation is proposed as a more accurate and flexible method for error adjustments in feed intake data collected by electronic feeders.

Genome-wide DNA methylation in saliva and body size of adolescent girls

Aim: We performed an epigenome-wide association study within the Finnish Health in Teens cohort to identify differential DNA methylation and its association with BMI in adolescents. Materials & methods: Differential DNA methylation analyses of 3.1 million CpG sites were performed in saliva samples from 50 lean and 50 heavy adolescent girls by genome-wide targeted bisulfite-sequencing. Results: We identified 100 CpG sites with p-values < 0.000524, seven regions by ‘bumphunting’ and five CpG islands that differed significantly between the two groups. The ten CpG sites and regions most strongly associated with BMI substantially overlapped with obesity- and insulin-related genes, including MC2R, IGFBPL1, IP6K1 and IGF2BP1. Conclusion: Our findings suggest an association between the saliva methylome and BMI in adolescence.

Identification of protein-damaging mutations in 10 swine taste receptors and 191 appetite-reward genes

Background

Taste receptors (TASRs) are essential for the body’s recognition of chemical compounds. In the tongue, TASRs sense the sweet and umami and the toxin-related bitter taste thus promoting a particular eating behaviour. Moreover, their relevance in other organs is now becoming evident. In the intestine, they regulate nutrient absorption and gut motility. Upon ligand binding, TASRs activate the appetite-reward circuitry to signal the nervous system and keep body homeostasis. With the aim to identify genetic variation in the swine TASRs and in the genes from the appetite and the reward pathways, we have sequenced the exons of 201 TASRs and appetite-reward genes from 304 pigs belonging to ten breeds, wild boars and to two phenotypically extreme groups from a F₂ resource with data on growth and fat deposition.

Results

We identified 2,766 coding variants 395 of which were predicted to have a strong impact on protein sequence and function. 334 variants were present in only one breed and at predicted alternative allele frequency (pAAF) ≥ 0.1. The Asian pigs and the wild boars showed the largest proportion of breed specific variants. We also compared the pAAF of the two F₂ groups and found that variants in TAS2R39 and CD36 display significant differences suggesting that these genes could influence growth and fat deposition. We developed a 128-variant genotyping assay and confirmed 57 of these variants.

Conclusions

We have identified thousands of variants affecting TASRs as well as genes involved in the appetite and the reward mechanisms. Some of these genes have been already associated to taste preferences, appetite or behaviour in humans and mouse. We have also detected indications of a potential relationship of some of these genes with growth and fat deposition, which could have been caused by changes in taste preferences, appetite or reward and ultimately impact on food intake. A genotyping array with 57 variants in 31 of these genes is now available for genotyping and start elucidating the impact of genetic variation in these genes on pig biology and breeding.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2972-z) contains supplementary material, which is available to authorized users.

A GWA study reveals genetic loci for body conformation traits in Chinese Laiwu pigs and its implications for human BMI

Pigs share numerous physiological and phenotypic similarities with human and thus have been considered as a good model in nonrodent mammals for the study of genetic basis of human obesity. Researches on candidate genes for obesity traits have successfully identified some common genes between humans and pigs. However, few studies have assessed how many similarities exist between the genetic architecture of obesity in pigs and humans by large-scale comparative genomics. Here, we performed a genome-wide association study (GWAS) using the porcine 60 K SNP Beadchip for BMI and other four conformation traits at three different ages in a Chinese Laiwu pig population, which shows a large variability in fat deposition. In total, 35 SNPs were found to be significant at Bonferroni-corrected 5 % chromosome-wise level (P = 2.13 × 10^-5) and 88 SNPs had suggestive (P < 10^-4) association with the conformation traits. Some SNPs showed age-dependent association. Intriguingly, out of 32 regions associated with BMI in pigs, 18 were homologous with the loci for BMI in humans. Furthermore, five closest genes to GWAS peaks including HIF1AN, SMYD3, COX10, SLMAP, and GBE1 have been already associated with BMI in humans, which makes them very promising candidates for these QTLs. The result of GO analysis provided strong support to the fact that mitochondria and synapse play important roles in obesity susceptibility, which is consistent with previous findings on human obesity, and it also implicated new gene sets related to chromatin modification and Ig-like C2-type 5 domain. Therefore, these results not only provide new insights into the genetic architecture of BMI in pigs but also highlight that humans and pigs share the significant overlap of obesity-related genes.

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research

Obesity is a condition in which excess body fat has accumulated over an extent that increases the risk of many chronic diseases. The current clinical classification of obesity is based on measurement of body mass index (BMI), waist-hip ratio, and body fat percentage. However, these measurements do not account for the wide individual variations in fat distribution, degree of fatness or health risks, and genetic variants identified in the genome-wide association studies (GWAS). In this review, we will address this important issue with the introduction of phenome, phenomics, and phenome-wide association study (PheWAS). We will discuss the new paradigm shift from GWAS to PheWAS in obesity research. In the era of precision medicine, phenomics and PheWAS provide the required approaches to better definition and classification of obesity according to the association of obese phenome with their unique molecular makeup, lifestyle, and environmental impact.

Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare

In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.

Efficient Boar Semen Production and Genetic Contribution: The Impact of Low-Dose Artificial Insemination on Fertility

Diluting semen from high fertile breeding boars, and by that inseminating many sows, is the core business for artificial insemination (AI) companies worldwide. Knowledge about fertility results is the reason by which an AI company can lower the concentration of a dose. Efficient use of AI boars with high genetic merit by decreasing the number of sperm cells per insemination dose is important to maximize dissemination of the genetic progress made in the breeding nucleus. However, a potential decrease in fertility performance in the field should be weighed against the added value of improved genetics and, in general, is not tolerated in commercial production. This overview provides some important aspects that influence the impact of low-dose AI on fertility: (i) the importance of monitoring field fertility, (ii) the need for accurate and precise semen assessment, (iii) the parameters that are taken into account, (iv) the application of information from genetic and genomic selection and (v) the optimization when using different AI techniques. Efficient semen production, processing and insemination in combination with increasing use of genetic and genomic applications result in maximum impact of genetic trend.

Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq

Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI). Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg) until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg). Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) genes, transcription factors (TF), and genes associated with RFI from a genome-wide association study (GWAS). Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05), -1.08 finishing period feed conversion ratio (P = 0.01), +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04), +28.8 kg final body weight (P = 0.01), -12.9 feed bunk visits per day (P = 0.02) with +0.60 min/visit duration (P = 0.01), and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03). RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other traits and gene co-expression networks.

A genomewide association study of feed efficiency and feeding behaviors at two fattening stages in a White Duroc × Erhualian F population

Feeding efficiency is a multifactorial and economically important trait in pigs. Genetic improvement of feeding efficiency will greatly benefit the pig industry. In the past decades, the hog market weight has increased worldwide. However, whether the genetic architecture of feeding efficiency is same or not at early and late fattening periods is unclear. To map genomic regions for feed efficiency and feeding behavior traits at early (n ≥ 384) and late (n ≥ 334) growth stages in pigs, we performed genomewide association studies for feed to gain ratio (FCR), residual feed intake (RFI), daily feed intake, daily visit times, daily feeding time (DFT), feed intake per second (FIPS), and feed intake per visit during 3 periods (2 stages and overall) in a White Duroc × Erhualian F2 intercross population. Six chromosomal regions showed significant association with these traits, of which 4 loci were reported for the first time. Our results confirmed the QTL of FCR around 34 Mb on SSC7 and RFI around 134 Mb on SSC12. Of note, 2 regions were associated with more than 1 trait. One was around 36 Mb on SSC7, and there were 47 and 67 SNP associated with FCR from 120 to 210 and from 120 to 240 d, respectively. The top SNP is located in a 2.88-Mb linkage disequilibrium (LD) block that harbors 44 genes. We propose the high mobility group AT-hook 1 gene as a plausible candidate gene in this region. The other was evidenced around 53 Mb on SSC12, which had multiple association signals for DFT and FIPS. The top SNP is located in a 211-kb LD block that harbors only 1 annotated gene, WSCD1, which encodes a protein with sulfotransferase activity and involves the glucose metabolism and, therefore, appears to be a plausible candidate gene. Except the region on SSC12 associated with DFT at both stages, the rest of the regions associated with the traits at only 1 stage, so the genetic architectures of the 2 stages are not same.

Unraveling the swine genome: implications for human health

The pig was first used in biomedical research in ancient Greece and over the past few decades has quickly grown into an important biomedical research tool. Pigs have genetic and physiological traits similar to humans, which make them one of the most useful and versatile animal models. Owing to these similarities, data generated from porcine models are more likely to lead to viable human treatments than those from murine work. In addition, the similarity in size and physiology to humans allows pigs to be used for many experimental approaches not feasible in mice. Research areas that employ pigs range from neonatal development to translational models for cancer therapy. Increasing numbers of porcine models are being developed since the release of the swine genome sequence, and the development of additional porcine genomic and epigenetic resources will further their use in biomedical research.