A genome-wide association study of growth and fatness traits in two pig populations with different genetic backgrounds

Genome-wide association study provided insights into the polled phenotype and polled intersex syndrome (PIS) in goats

BACKGROUND

Breeding polled goats is a welfare-friendly approach for horn removal in comparison to invasive methods. To gain a comprehensive understanding of the genetic basis underlying polledness in goats, we conducted whole-genome sequencing of 106 Xinong Saanen dairy goats, including 33 horned individuals, 70 polled individuals, and 3 polled intersexuality syndrome (PIS) individuals.

METHODS

The present study employed a genome-wide association study (GWAS) and linkage disequilibrium (LD) analysis to precisely map the genetic locus underlying the polled phenotype in goats.

RESULTS

The analysis conducted in our study revealed a total of 320 genome-wide significant single nucleotide polymorphisms (SNPs) associated with the horned/polled phenotype in goats. These SNPs exhibited two distinct peaks on chromosome 1, spanning from 128,817,052 to 133,005,441 bp and from 150,336,143 to 150,808,639 bp. The present study identified three genome-wide significant SNPs, namely Chr1:129789816, Chr1:129791507, and Chr1:129791577, as potential markers of PIS-affected goats. The results of our LD analysis suggested a potential association between MRPS22 and infertile intersex individuals, as well as a potential association between ERG and the polled trait in goats.

CONCLUSION

We have successfully identified three marker SNPs closely linked to PIS, as well as several candidate genes associated with the polled trait in goats. These results may contribute to the development of SNP chips for early prediction of PIS in goats, thereby facilitating breeding programs aimed at producing fertile herds with polled traits.

Additive and Dominance Genome-Wide Association Studies Reveal the Genetic Basis of Heterosis Related to Growth Traits of Duhua Hybrid Pigs

Heterosis has been extensively used for pig genetic breeding and production, but the genetic basis of heterosis remains largely elusive. Crossbreeding between commercial and native breeds provides a good model to parse the genetic basis of heterosis. This study uses Duhua hybrid pigs, a crossbreed of Duroc and Liangguang small spotted pigs, as materials to explore the genetic basis underlying heterosis related to growth traits at the genomic level. The mid-parent heterosis (MPH) analysis showed heterosis of this Duhua offspring on growth traits. In this study, we examined the impact of additive and dominance effects on 100 AGE (age adjusted to 100 kg) and 100 BF (backfat thickness adjusted to 100 kg) of Duhua hybrid pigs. Meanwhile, we successfully identified SNPs associated with growth traits through both additive and dominance GWASs (genome-wide association studies). These findings will facilitate the subsequent in-depth studies of heterosis in the growth traits of Duhua pigs.

Association of a genetic variant in angiopoietin-like 3 with serum HDL-C and risk of cardiovascular disease: A study of the MASHAD cohort over 6 years

BACKGROUND

Loss-of-function (LOF) variants of the angiopoietin-like 3 (ANGPTL3) gene are reported to be associated with serum triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) concentrations and thereby affect the risk of cardiovascular disease (CVD).

OBJECTIVE

In the present study, we examined the association of rs10789117 in the ANGPTL 3 gene locus and the risk of CVD in the group of people who were part of the Mashhad-Stroke and Heart-Atherosclerotic-Disorders (MASHAD) cohort.

METHODS

One thousand and two healthy individuals enrolled in this study of whom 849 subjects were healthy and 153 subjects developed CVD outcomes after 6 years of follow-up. After a 12-h overnight fasting, 20 mL of blood samples were collected for the measurement of fasting blood glucose and lipid profile. DNA was extracted, and the Tetra-ARMS PCR (amplification refractory mutation system) was used for genotyping of rs10789117 in the ANGPTL3 gene. The genotype frequencies of the variant of rs10789117 in the ANGPTL3 gene were estimated using χ2 tests. Eventually, the statistical analysis was done by SPSS version 20.

RESULTS

Individuals with AC/CC genotypes (rs10789117) were found to have to greater risk of CVD events compared to AA genotype (OR = 1.43, 95%CI = 1.01-2.02, p = 0.041). There was a 1.3-fold increase in cardiovascular events in individuals carrying the C allele of rs10789117 variant compared to non-carriers (OR = 1.32, 95%CI = 1.06-1.72, p value = 0.038). There were significant differences between different genotypes for serum triglyceride levels within the control group, but this difference was not significant in the group with CVD. Moreover, there was a significant association between CC genotype and CVD risk in the individuals with a normal serum HDL-C.

CONCLUSION

We have found that a rs10789117 C>A in ANGPTL3 gene polymorphism was associated with incident CVD events, and this may be of value as a risk stratification biomarker in CVD in the Iranian population.

A meta-analysis of genetic and phenotypic diversity of European local pig breeds reveals genomic regions associated with breed differentiation for production traits

BACKGROUND

Intense selection of modern pig breeds has resulted in genetic improvement of production traits while the performance of local pig breeds has remained lower. As local pig breeds have been bred in extensive systems, they have adapted to specific environmental conditions, resulting in a rich genotypic and phenotypic diversity. This study is based on European local pig breeds that have been genetically characterized using DNA-pool sequencing data and phenotypically characterized using breed level phenotypes related to stature, fatness, growth, and reproductive performance traits. These data were analyzed using a dedicated approach to detect signatures of selection linked to phenotypic traits in order to uncover potential candidate genes that may underlie adaptation to specific environments.

RESULTS

Analysis of the genetic data of European pig breeds revealed four main axes of genetic variation represented by the Iberian and three modern breeds (i.e. Large White, Landrace, and Duroc). In addition, breeds clustered according to their geographical origin, for example French Gascon and Basque breeds, Italian Apulo Calabrese and Casertana breeds, Spanish Iberian, and Portuguese Alentejano breeds. Principal component analysis of the phenotypic data distinguished the larger and leaner breeds with better growth potential and reproductive performance from the smaller and fatter breeds with low growth and reproductive efficiency. Linking the signatures of selection with phenotype identified 16 significant genomic regions associated with stature, 24 with fatness, 2 with growth, and 192 with reproduction. Among them, several regions contained candidate genes with possible biological effects on stature, fatness, growth, and reproductive performance traits. For example, strong associations were found for stature in two regions containing, respectively, the ANXA4 and ANTXR1 genes, for fatness in a region containing the DNMT3A and POMC genes and for reproductive performance in a region containing the HSD17B7 gene.

CONCLUSIONS

In this study on European local pig breeds, we used a dedicated approach for detecting signatures of selection that were supported by phenotypic data at the breed level to identify potential candidate genes that may have adapted to different living environments and production systems.

Genomic Association Analysis of Growth and Backfat Traits in Large White Pigs

The pig industry is significantly influenced by complex traits such as growth rate and fat deposition, which have substantial implications for economic returns. Over the years, remarkable genetic advancements have been achieved through intense artificial selection to enhance these traits in pigs. In this study, we aimed to investigate the genetic factors that contribute to growth efficiency and lean meat percentages in Large White pigs. Specifically, we focused on analyzing two key traits: age at 100 kg live weight (AGE100) and backfat thickness at 100 kg (BF100), in three distinct Large White pig populations-500 Canadian, 295 Danish, and 1500 American Large White pigs. By employing population genomic techniques, we observed significant population stratification among these pig populations. Utilizing imputed whole-genome sequencing data, we conducted single population genome-wide association studies (GWAS) as well as a combined meta-analysis across the three populations to identify genetic markers associated with the aforementioned traits. Our analyses highlighted several candidate genes, such as CNTN1-which has been linked to weight loss in mice and is potentially influential for AGE100-and MC4R, which is associated with obesity and appetite and may impact both traits. Additionally, we identified other genes-namely, PDZRN4, LIPM, and ANKRD22-which play a partial role in fat growth. Our findings provide valuable insights into the genetic basis of these important traits in Large White pigs, which may inform breeding strategies for improved production efficiency and meat quality.

Association of Novel C319T Variant of PITX2 Gene 3'UTR Region With Reproductive Performance in Awassi Sheep

Several genes influence sheep's reproductive performance, among them the paired-like homeodomain transcription factor 2 (PITX2) gene. Thus, this study aimed to examine whether the variability within the PITX2 gene is associated with the reproductive performance of Awassi ewes. A total of 123 single-progeny ewes and 109 twin ewes were used to extract genomic DNA. An amplicon of 4 sequence fragments from exons 2, 4, 5 (upstream portion), and 5 (downstream portion) of the PITX2 gene was generated by polymerase chain reaction (PCR), 228, 304, 381, and 382 bp, respectively. Three genotypes of 382 bp amplicons were identified: CC, CT, and TT. Sequence analysis revealed a novel mutation in the CT genotype 319C > T. Statistical analysis revealed that single-nucleotide polymorphism (SNP) 319C > T was associated with reproductive performance. Single-nucleotide polymorphism 319C > T-carrying ewes had significantly (P ⩽ .01) lower litter sizes, twinning rates, lambing rates, and more days to lambing than those carrying CT and CC genotypes. Based on a logistic regression analysis, it was confirmed that the 319C > T SNP decreased litter size. Ewes with TT genotype produced fewer lambs than ewes with CT and CC genotypes. According to these results, the variant 319C> T SNP negatively affects the reproductive performance of Awassi sheep. Ewes carrying the 319C > T SNP have a lower litter size and are less prolific than those without the SNP.

Genome-wide association studies for additive and dominance effects for body composition traits in commercial crossbred Piétrain pigs

Fat depth (FD) and muscle depth (MD) are economically important traits and used to estimate carcass lean content (LMP), which is one of the main breeding objectives in pig breeding programmes. We assessed the genetic architectures of body composition traits for additive and dominance effects in commercial crossbred Piétrain pigs using both 50 K array and sequence genotypes. We first performed a genome-wide association study (GWAS) using single-marker association analysis with a false discovery rate of 0.1. Then, we estimated the additive and dominance effects of the most significant variant in the quantitative trait loci (QTL) regions. It was investigated whether the use of whole-genome sequence (WGS) will improve the QTL detection (both additive and dominance) with a higher power compared with lower density SNP arrays. Our results showed that more QTL regions were detected by WGS compared with 50 K array (n = 54 vs. n = 17). Of the novel associated regions associated with FD and LMP and detected by WGS, the most pronounced peak was on SSC13, situated at ~116-118, 121-127 and 129-134 Mbp. Additionally, we found that only additive effects contributed to the genetic architecture of the analysed traits and no significant dominance effects were found for the tested SNPs at QTL regions, regardless of panel density. The associated SNPs are located in or near several relevant candidate genes. Of these genes, GABRR2, GALR1, RNGTT, CDH20 and MC4R have been previously reported as being associated with fat deposition traits. However, the genes on SSC1 (ZNF292, ORC3, CNR1, SRSF12, MDN1, TSHZ1, RELCH and RNF152) and SSC18 (TTC26 and KIAA1549) have not been reported previously to our best knowledge. Our current findings provide insights into the genomic regions influencing composition traits in Piétrain pigs.

Integrating genome-wide association studies and population genomics analysis reveals the genetic architecture of growth and backfat traits in pigs

Growth and fat deposition are complex traits, which can affect economical income in the pig industry. Due to the intensive artificial selection, a significant genetic improvement has been observed for growth and fat deposition in pigs. Here, we first investigated genomic-wide association studies (GWAS) and population genomics (e.g., selection signature) to explore the genetic basis of such complex traits in two Large White pig lines (n = 3,727) with the GeneSeek GGP Porcine HD array (n = 50,915 SNPs). Ten genetic variants were identified to be associated with growth and fatness traits in two Large White pig lines from different genetic backgrounds by performing both within-population GWAS and cross-population GWAS analyses. These ten significant loci represented eight candidate genes, i.e., NRG4, BATF3, IRS2, ANO1, ANO9, RNF152, KCNQ5, and EYA2. One of them, ANO1 gene was simultaneously identified for both two lines in BF100 trait. Compared to single-population GWAS, cross-population GWAS was less effective for identifying SNPs with population-specific effect, but more powerful for detecting SNPs with population-shared effects. We further detected genomic regions specifically selected in each of two populations, but did not observe a significant enrichment for the heritability of growth and backfat traits in such regions. In summary, the candidate genes will provide an insight into the understanding of the genetic architecture of growth-related traits and backfat thickness, and may have a potential use in the genomic breeding programs in pigs.

Population genetic structure analysis and identification of backfat thickness loci of Chinese synthetic Yunan pigs

Yunan is a crossed lean meat pig breed in China. Backfat thickness is the gold standard for carcass quality grading. However, over 14 years after breed registration, the backfat of Yunan thickened and the consistency of backfat thickness decreased. Meanwhile, no genetic study has been ever performed on Yunan population. So, in this study we collected all the 120 nucleus individuals of Yunan and recorded six backfat traits of them, carried out population genetic structure analysis, selection signals analysis and genome-wide association study of Yunan pigs with the help of their founder population Duroc and Chinese native Huainan pigs, to determine the genomic loci on backfat of Yunan. Genetic diversity indexes suggested Yunan pigs had no inbreeding risk while population genetic structure showed they had few molecular pedigrees and were stratified. A total of 71 common selection signals affecting growth and fat deposition were detected by F_ST and XP-CLR methods. 34 significant loci associated with six backfat traits were detected, among which a 1.40 Mb region on SSC4 (20.03–21.43 Mb) were outstanding as the strong region underlying backfat. This region was common with the results of selection signature analysis, former reported QTLs for backfat and was common for different kinds of backfat traits at different development stage. ENPP2, EXT1 and SLC30A8 genes around were fat deposition related genes and were of Huainan pig’s origin, among which Type 2 diabetes related gene SLC30A8 was the most reasonable for being in a 193.21 Kb haplotype block of the 1.40 Mb region. Our results had application value for conservation, mating and breeding improvement of backfat thickness of Yunan pigs and provided evidence for a human function gene might be reproduced in pigs.

Genome-Wide Association Study of Growth Traits in a Four-Way Crossbred Pig Population

Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to analyze ten growth traits on 223 four-way intercross pigs. A total of 227,921 highly consistent single nucleotide polymorphisms (SNPs) uniformly dispersed throughout the entire genome were used to conduct GWAS. A total of 53 SNPs were identified for ten growth traits using the mixed linear model (MLM), of which 18 SNPs were located in previously reported quantitative trait loci (QTL) regions. Two novel QTLs on SSC4 and SSC7 were related to average daily gain from 30 to 60 kg (ADG30–60) and body length (BL), respectively. Furthermore, 13 candidate genes (ATP5O, GHRHR, TRIM55, EIF2AK1, PLEKHA1, BRAP, COL11A2, HMGA1, NHLRC1, SGSM1, NFATC2, MAML1, and PSD3) were found to be associated with growth traits in pigs. The GWAS findings will enhance our comprehension of the genetic architecture of growth traits. We suggested that these detected SNPs and corresponding candidate genes might provide a biological foundation for improving the growth and production performance of pigs in swine breeding.

Genome-wide association study identifying genetic variants associated with carcass backfat thickness, lean percentage and fat percentage in a four-way crossbred pig population using SLAF-seq technology

Background

Carcass backfat thickness (BFT), carcass lean percentage (CLP) and carcass fat percentage (CFP) are important to the commercial pig industry. Nevertheless, the genetic architecture of BFT, CLP and CFP is still elusive. Here, we performed a genome-wide association study (GWAS) based on specific-locus amplified fragment sequencing (SLAF-seq) to analyze seven fatness-related traits, including five BFTs, CLP, and CFP on 223 four-way crossbred pigs.

Results

A total of 227, 921 highly consistent single nucleotide polymorphisms (SNPs) evenly distributed throughout the genome were used to perform GWAS. Using the mixed linear model (MLM), a total of 20 SNP loci significantly related to these traits were identified on ten Sus scrofa chromosomes (SSC), of which 10 SNPs were located in previously reported quantitative trait loci (QTL) regions. On SSC7, two SNPs (SSC7:29,503,670 and rs1112937671) for average backfat thickness (ABFT) exceeded 1% and 10% Bonferroni genome-wide significance levels, respectively. These two SNP loci were located within an intron region of the COL21A1 gene, which was a protein-coding gene that played an important role in the porcine backfat deposition by affecting extracellular matrix (ECM) remodeling. In addition, based on the other three significant SNPs on SSC7, five candidate genes, ZNF184, ZNF391, HMGA1, GRM4 and NUDT3 were proposed to influence BFT. On SSC9, two SNPs for backfat thickness at 6–7 ribs (67RBFT) and one SNP for CLP were in the same locus region (19 kb interval). These three SNPs were located in the PGM2L1 gene, which encoded a protein that played an indispensable role in glycogen metabolism, glycolysis and gluconeogenesis as a key enzyme. Finally, one significant SNP on SSC14 for CLP was located within the PLBD2 gene, which participated in the lipid catabolic process.

Conclusions

A total of two regions on SSC7 and SSC9 and eight potential candidate genes were found for fatness-related traits in pigs. The results of this GWAS based on SLAF-seq will greatly advance our understanding of the genetic architecture of BFT, CLP, and CFP traits. These identified SNP loci and candidate genes might serve as a biological basis for improving the important fatness-related traits of pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08827-8.

An imputation-based genome-wide association study for growth and fatness traits in Sujiang pigs

Sujiang pigs are a synthetic breed derived from Jiangquhai, Fengjing, and Duroc pigs. In this study, we sequenced the genome of 62 pigs with a coverage depth of 10× to 20×, including 27 Sujiang and 35 founder breed pigs, and we collected 360 global pigs' genome sequence data from public databases including 39 Duroc pigs. We obtained a high-quality variant dataset of 365 Sujiang pigs by imputing the porcine 80 K single nucleotide polymorphism (SNP) Beadchip to the whole-genome scale with a total of 422 pigs as a reference panel. A dataset of 365 imputated Sujiang pigs was used to perform single-trait genome-wide association study (GWAS) and meta-analyses for growth and fatness traits. Single-trait GWAS identified 1 907, 18, and 14 SNPs surpassing the suggestively significant threshold for backfat thickness, chest circumference, and chest width, respectively. Meta-analyses identified 2 400 genome-wide significant SNPs and 520 suggestively significant SNPs for backfat thickness and chest circumference, and 719 genome-wide significant SNPs and 1 225 suggestively significant SNPs for all seven traits. According to the meta-analysis of backfat thickness and chest circumference, a remarkable region of 2.69 Mb on Sus scrofa chromosome 4 containing FAM110B, IMPAD1, LYN, MOS, PENK, PLAG1, SDR16C5 and XKR4 was identified as a candidate region. The haplotype heat map of the 2.69 Mb region verified that Sujiang pigs were derived from Duroc and Chinese indigenous pigs, especially Jiangquhai pigs. The Kruskal-Wallis test showed that haplotypes of the 2.69 Mb region significantly affected backfat thickness and chest circumference traits. We then focused on PLAG1, an important growth-related gene, and identified two synonymous SNPs with obvious differences among different breeds in the PLAG1 gene. We then performed genotyping of 365 Sujiang, 150 Duroc, 95 Jiangquhai, and 100 Fengjing pigs to confirm the above result and verified that the two variants significantly affected phenotypes of growth and fatness traits. Our findings not only provide insights into the genetic architecture of porcine growth and fatness traits but also provide potential markers for selective breeding of these traits in Sujiang pigs.

Identification of key candidate genes for wing length-related traits by whole-genome resequencing in 772 geese

1. A total of 772, 420-day-old Xingguo gray geese (XGG) were sequenced using a low-depth (~1×) whole-genome resequencing strategy to reveal the genetic mechanism of wing length-related traits by genome-wide association analysis (GWAS).2. The results showed that 119 SNPs had genome-wide significance for wing length in five regions of chromosome 4, of which the most significant locus (P=7.95E-11) was located upstream of RBM47 and explained 7.3% of phenotypic variation.3. A total of 219 SNPs located on chromosome 4 that were associated with 2-joint-wing length, of which four SNPs reached the genome-wide significant level. However, for the length of 1-joint-wing and primary feather, we did not detect any associated locus.4. Six promising candidate genes, RBM47, SLAIN2, GRXCR1, SLC10A4, APBB2 and NSUN7 on chromosome 4, may play an important role in the growth and development of feathers, muscles and bones.

Transcriptome Analysis Reveals the Differentially Expressed Genes Associated with Growth in Guangxi Partridge Chickens

The Guangxi Partridge chicken is a well-known chicken breed in southern China with good meat quality, which has been bred as a meat breed to satisfy the increased demand of consumers. Compared with line D whose body weight is maintained at the average of the unselected group, the growth rate and weight of the selected chicken group (line S) increased significantly after breeding for four generations. Herein, transcriptome analysis was performed to identify pivotal genes and signal pathways of selective breeding that contributed to potential mechanisms of growth and development under artificial selection pressure. The average body weight of line S chickens was 1.724 kg at 90 d of age, which showed a significant increase at 90 d of age than line D chickens (1.509 kg), although only the internal organ ratios of lung and kidney changed after standardizing by body weight. The myofiber area and myofiber density of thigh muscles were affected by selection to a greater extent than that of breast muscle. We identified 51, 210, 31, 388, and 100 differentially expressed genes (DEGs) in the hypothalamus, pituitary, breast muscle, thigh muscle, and liver between the two lines, respectively. Several key genes were identified in the hypothalamus-pituitary-muscle axis, such as FST, THSB, PTPRJ, CD36, PITX1, PITX2, AMPD1, PRKAB1, PRKAB2, and related genes for muscle development, which were attached to the cytokine–cytokine receptor interaction signaling pathway, the PPAR signaling pathway, and lipid metabolism. However, signaling molecular pathways and the cell community showed that elevated activity in the liver of line S fowl was mainly involved in focal adhesion, ECM-receptor interaction, cell adhesion molecules, and signal transduction. Collectively, muscle development, lipid metabolism, and several signaling pathways played crucial roles in the improving growth performance of Guangxi Partridge chickens under artificial selection for growth rate. These results support further study of the adaptation of birds under selective pressure.

Genome-wide association study reveals candidate genes relevant to body weight in female turkeys (Meleagris gallopavo)

The underlying genetic mechanisms affecting turkey growth traits have not been widely investigated. Genome-wide association studies (GWAS) is a powerful approach to identify candidate regions associated with complex phenotypes and diseases in livestock. In the present study, we performed GWAS to identify regions associated with 18-week body weight in a turkey population. The data included body weight observations for 24,989 female turkeys genotyped based on a 65K SNP panel. The analysis was carried out using a univariate mixed linear model with hatch-week-year and the 2 top principal components fitted as fixed effects and the accumulated polygenic effect of all markers captured by the genomic relationship matrix as random. Thirty-three significant markers were observed on 1, 2, 3, 4, 7 and 12 chromosomes, while 26 showed strong linkage disequilibrium extending up to 410 kb. These significant markers were mapped to 37 genes, of which 13 were novel. Interestingly, many of the investigated genes are known to be involved in growth and body weight. For instance, genes AKR1D1, PARP12, BOC, NCOA1, ADCY3 and CHCHD7 regulate growth, body weight, metabolism, digestion, bile acid biosynthetic and development of muscle cells. In summary, the results of our study revealed novel candidate genomic regions and candidate genes that could be managed within a turkey breeding program and adapted in fine mapping of quantitative trait loci to enhance genetic improvement in this species.

Identify known and novel candidate genes associated with backfat thickness in Duroc pigs by large-scale genome-wide association analysis

Backfat thickness (BFT) is complex and economically important traits in the pig industry, since it reflects fat deposition and can be used to measure the carcass lean meat percentage in pigs. In this study, all 6,550 pigs were genotyped using the Geneseek Porcine 50K SNP Chip to identify SNPs related to BFT and to search for candidate genes through genome-wide association analysis in two Duroc populations. In total, 80 SNPs, including 39 significant and 41 suggestive SNPs, and 6 QTLs were identified significantly associated with the BFT. In addition, 9 candidate genes, including a proven major gene MC4R, 3 important candidate genes (RYR1, HMGA1, and NUDT3) which were previously described as related to BFT, and 5 novel candidate genes (SIRT2, NKAIN2, AMH, SORCS1, and SORCS3) were found based on their potential functional roles in BFT. The functions of candidate genes and gene set enrichment analysis indicate that most important pathways are related to energy homeostasis and adipogenesis. Finally, our data suggest that most of the candidate genes can be directly used for genetic improvement through molecular markers, except that the MC4R gene has an antagonistic effect on growth rate and carcass lean meat percentage in breeding. Our results will advance our understanding of the complex genetic architecture of BFT traits and laid the foundation for additional genetic studies to increase carcass lean meat percentage of pig through marker-assisted selection and/or genomic selection.

Identification of candidate genomic regions for chicken egg number traits based on genome-wide association study

Background

Since the domestication of chicken, various breeds have been developed for food production, entertainment, and so on. Compared to indigenous chicken breeds which generally do not show elite production performance, commercial breeds or lines are selected intensely for meat or egg production. In the present study, in order to understand the molecular mechanisms underlying the dramatic differences of egg number between commercial egg-type chickens and indigenous chickens, we performed a genome-wide association study (GWAS) in a mixed linear model.

Results

We obtained 148 single nucleotide polymorphisms (SNPs) associated with egg number traits (57 significantly, 91 suggestively). Among them, 4 SNPs overlapped with previously reported quantitative trait loci (QTL), including 2 for egg production and 2 for reproductive traits. Furthermore, we identified 32 candidate genes based on the function of the screened genes. These genes were found to be mainly involved in regulating hormones, playing a role in the formation, growth, and development of follicles, and in the development of the reproductive system. Some genes such as NELL2 (neural EGFL like 2), KITLG (KIT ligand), GHRHR (Growth hormone releasing hormone receptor), NCOA1 (Nuclear receptor coactivator 1), ITPR1 (inositol 1, 4, 5-trisphosphate receptor type 1), GAMT (guanidinoacetate N-methyltransferase), and CAMK4 (calcium/calmodulin-dependent protein kinase IV) deserve our attention and further study since they have been reported to be closely related to egg production, egg number and reproductive traits. In addition, the most significant genomic region obtained in this study was located at 48.61–48.84 Mb on GGA5. In this region, we have repeatedly identified four genes, in which YY1 (YY1 transcription factor) and WDR25 (WD repeat domain 25) have been shown to be related to oocytes and reproductive tissues, respectively, which implies that this region may be a candidate region underlying egg number traits.

Conclusion

Our study utilized the genomic information from various chicken breeds or populations differed in the average annual egg number to understand the molecular genetic mechanisms involved in egg number traits. We identified a series of SNPs, candidate genes, or genomic regions that associated with egg number, which could help us in developing the egg production trait in chickens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07755-3.

Genome-wide association studies of preweaning growth and in vivo carcass composition traits in Esme sheep

Sheep are considered as a major contributor of global food security. Moreover, sheep preweaning growth traits as well as in vivo carcass composition traits such as ultrasonic measurements of Longissimus dorsi muscle depth (UMD) and back-fat thickness (UFD) are crucially important indicators of meat yield and hot carcass composition. Despite their relative importance for productivity and profitability of a sheep production system, detected QTL for these traits are quite scarce. Therefore, we implemented GWAS for these traits using animal mixed model-based association approach provided by GenABEL in Esme sheep. Three genome-wide and 14 individual chromosome-wide associated SNPs were discovered. As a result, ESRP1, LOC105613082, ZNF641, DUSP5, TEAD1, SMOX, PTPRT, RALYL, POM121C, PHIP, LOC101106051, ZIM3, PEG3, TRPC7, FBXL4, LOC105610397, LOC105616489 and DNAAF2 were suggested as candidates. Some of the discovered genes and involved pathways were already annotated to contribute growth and development in various species including human, mice and cattle. All in all, the results of this study are expected to strongly contribute to shed a light on the underlying molecular mechanisms behind growth and carcass composition traits, with potential implications on studies aiming faster genetic improvement, targeted low-resolution SNP panel designs and genome-editing studies.

A further look at quantitative trait loci for growth and fatness traits in a White Duroc × Erhualian F3 intercross population

Genetic analysis of porcine growth and fatness traits is beneficial to the swine industry and provides a reference to understand human obesity. Here, we obtained 29 growth and fatness traits for 473 individuals from a White Duroc × Erhualian F₃ intercross population. Basic statistical analyses showed that: (1) Positive correlations between different-stage body weights were detected, the shorter the time interval the stronger the correlation. (2) Strong correlations existed in the paired fatness traits. (3) With the growth of age, the correlation between fatness and body weight was increasing. All pigs were genotyped by Illumina 50 K SNP chips and their whole-genome genotypes were imputed referred to 109 re-sequencing data. We performed common and imputation-based GWASs for these traits. Two genome-wide significant loci on swine chromosome (SSC) 4 and 7 were repeatedly detected. The strongest association (P = 3.24 × 10^-19) was detected at 31.96 Mb on SSC7 for leaf fat weight. On this locus, seven major haplotypes were identified, of which two were novel and had an increasing-fatness effect. In the imputation-based GWAS, three new loci were identified. Our findings provide further insights into and enhance our understanding of genetic mechanism of porcine growth and fat deposition.

A haplotype of the ANGPTL3 gene is associated with CVD risk, diabetes mellitus, hypertension, obesity, metabolic syndrome, and dyslipidemia

SUBJECT

There have been a few studies on the association between the angiopoietin-like 3 (ANGPTL3) single nucleotide polymorphisms (SNPs) and the risk of cardiovascular disease (CVD). But there is no consensus about the association of ANGPTL3 haplotypes and cardiometabolic disorders. We aimed to determine the association of three variants of the ANGPTL3 gene and CVD risk factors, which included: diabetes mellitus, hypertension, obesity, metabolic syndrome, and dyslipidaemia in the MASHAD population cohort.

METHOD

DNA extraction and genotyping were undertaken in1002 individuals who were recruited as part of the Mashhad-Stroke and Heart-Atherosclerotic-Disorders (MASHAD) cohort. The association between the rs1748195, rs11207997, and rs10789117 variants with CVD event following 6 years follow-up and individual CVD risk factors were assessed using multivariate analysis.

RESULT

Individuals with a GTC haplotype had a reduced risk of CVD, dyslipidaemia, obesity, and DM. Moreover, we found that of all 8 haplotypes, the CTC was associated with a 1.5-fold higher risk of HTN. Carriers of an uncommon allele of the ANGPTL3 gene had a lower risk of obesity, HTN, MetS and DM (rs10789117), and in those with the rs1748195 variant there was a lower risk of obesity compared to the wild-type genotype.

CONCLUSION

We found that the GTC and CTC haplotypes of the ANGPTL3 gene may help identify individuals with a genetic susceptibility to cardiometabolic disorders.

Weighted Single-Step GWAS Identified Candidate Genes Associated with Growth Traits in a Duroc Pig Population

Growth traits are important economic traits of pigs that are controlled by several major genes and multiple minor genes. To better understand the genetic architecture of growth traits, we performed a weighted single-step genome-wide association study (wssGWAS) to identify genomic regions and candidate genes that are associated with days to 100 kg (AGE), average daily gain (ADG), backfat thickness (BF) and lean meat percentage (LMP) in a Duroc pig population. In this study, 3945 individuals with phenotypic and genealogical information, of which 2084 pigs were genotyped with a 50 K single-nucleotide polymorphism (SNP) array, were used for association analyses. We found that the most significant regions explained 2.56–3.07% of genetic variance for four traits, and the detected significant regions (>1%) explained 17.07%, 18.59%, 23.87% and 21.94% for four traits. Finally, 21 genes that have been reported to be associated with metabolism, bone growth, and fat deposition were treated as candidate genes for growth traits in pigs. Moreover, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses implied that the identified genes took part in bone formation, the immune system, and digestion. In conclusion, such full use of phenotypic, genotypic, and genealogical information will accelerate the genetic improvement of growth traits in pigs.

A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

Background

Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs.

Results

In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development.

Conclusions

We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

Genome-wide association studies for growth-related traits in a crossbreed pig population

Growth-related traits are important economic traits in the pig industry that directly influence pork production efficiency. To detect quantitative trait loci and candidate genes affecting growth traits, genome-wide association studies were performed for backfat thickness (BF) and loin muscle depth (LMD) in 370 Chuying-black pigs using Illumina PorcineSNP50 BeadChip array. We totally identified 14 BF-associated SNPs, which included 11 genome-wide SNPs (P < 1.39E-06) and 3 chromosome-wide suggestive SNPs (P < 2.79E-05) and for LMD, 9 SNPs surpassed the genome-wide significant threshold (P < 1.39E-06). These SNPs explained 30.33 and 27.51% phenotypic variance for BF and LMD respectively. Furthermore, 14 and 9 genes nearest to the significant SNPs were selected to be candidate genes, including MAGED1, GPHN, CCSER1, and GUCY2D for BF and PARM1, COL18A1, HSF5, and SCML2 genes for LMD. One significant SNP, which explained 6.07% of phenotypic variance for BF, mapped to a pleiotropic quantitative trait locus with a 494-kb interval. Together, the SNPs and candidate genes identified in this study will advance our understanding of the complex genetic architecture of BF and LMD traits, and they will also provide important clues for future implementation of a genomic selection program in Chuying-black pigs.

Transcriptomic comparison of liver tissue between Anqing six-end-white pigs and Yorkshire pigs based on RNA sequencing

Chinese indigenous pig and Western commercial pig breeds show different patterns of lipid metabolism, fat deposition, and fatty acid composition; for these reasons, they have become vitally important models of energy metabolism and obesity in humans. To compare the mechanisms underlying lipid metabolism between Yorkshire pigs (lean type) and Anqing six-end-white pigs (obese type), the liver transcriptomes of six castrated boars with a body weight of approximately 100 kg (three Yorkshire and three Anqing) were analyzed by RNA-seq. The total number of reads produced for each liver sample ranged from 47.05 to 62.6 million. Among 362 differentially expressed genes, 142 were up-regulated and 220 were down-regulated in Anqing six-end-white pigs. Based on these data, 79 GO terms were significantly enriched. The top 10 (the 10 with lowest corrected P-value) significantly enriched GO terms were identified, including lipid metabolic process and carboxylic acid metabolic process. Pathway analysis revealed three significantly enriched KEGG pathways including PPAR signaling pathway, steroid hormone biosynthesis, and retinol metabolism. Based on protein–protein interaction networks, multiple genes responsible for lipid metabolism were identified, such as PCK1, PPARA, and CYP7A1, and these were considered promising candidate genes that could affect porcine liver lipid metabolism and fat deposition. Our results provide abundant transcriptomic information that will be useful for animal breeding and biomedical research.

Expression Analysis of the PITX2 Gene and Associations between Its Polymorphisms and Body Size and Carcass Traits in Chickens

Simple Summary

The Wuliang Mountain Black-bone chicken is a Chinese indigenous breed with good meat quality and strong resistance to disease. Like most of the other Chinese domestic breeds, it has a much slower early growth rate compared with foreign chicken breeds. Therefore, the genetic selection of body size and carcass traits is still the focus of Chinese indigenous chicken breeding. The paired-like homeodomain transcription factor 2 (PITX2) gene, an important transcription factor, plays an important role during the development of the eye, heart, skeletal muscle and other tissues in mammals. In chicken, the PITX2 gene affects the late myogenic differentiation of the limb. The objectives of this study were to detect the expression of the PITX2 gene and analyze the associations between the polymorphisms in the exons of the PITX2 gene and body size as well as carcass traits in chickens. The results could contribute to Chinese chicken breeding based on marker assisted-selection.

Abstract

PITX2 is expressed in and plays an important role in myocytes of mice, and it has effects on late myogenic differentiation in chickens. However, the expression profile and polymorphisms of PITX2 remain unclear in chickens. Therefore, the aim of the present study was to detect its expression and investigate single nucleotide polymorphisms (SNPs) within its exons and then to evaluate whether these polymorphisms affect body size as well as carcass traits in chickens. The expression analysis showed that the expression level of chicken PITX2 mRNA in the leg muscle and hypophysis was significantly higher (p < 0.01) than those in other tissues. The results of polymorphisms analysis identified two SNPs (i.e., g.9830C > T and g.10073C > T) in exon 1 and 10 SNPs (i.e., g.12713C > T, g.12755C > T, g.12938G > A, g. 3164C > T, g.13019G > A, g.13079G > A, g.13285G > A, g.13335G > A, g.13726A > G and g.13856C > T) in exon 3, including four novel SNPs (i.e., g.9830C > T, g.12713C > T, g.12938G > A and g.13856C > T). In the loci of g.10073C > T and g.12713C > T, chickens with the CT genotype had the highest (p < 0.05 or p < 0.01) breast depth and breast angle, respectively. For the locus of g.13335G > A, chickens with the GG genotype had the highest (p < 0.05 or p < 0.01) breast angle and shank circumference. For the locus of g.13726A > G, chickens with the GG genotype had the highest breast width, fossil keel bone length and shank circumference. The locus of g.12713A > G had significant effects on the PITX2 mRNA expression level in leg muscle. The H1H7 diplotype showed the highest shank circumference, and the H2H8 diplotype showed the highest breast muscle rate. The present research suggested that polymorphisms of the exons of the PITX2 gene were significantly associated with the body size and carcass traits of Wuliang Mountain Black-bone chickens and the PITX2 gene could be a potential candidate gene for molecular marker-aided selection in Wuliang Mountain Black-bone chickens and other chicken breeds.

Transcriptome analysis reveals corresponding genes and key pathways involved in heat stress in Hu sheep

Heat stress (HS) seriously affects animal performance. In view of global warming, it is essential to understand the regulatory mechanisms by which animals adapt to heat stress. In this study, our aim was to explore the genes and pathways involved in heat stress in sheep. To this end, we used transcriptome analysis to understand the molecular responses to heat stress and thereby identify means to protect sheep from heat shock. To obtain an overview of the effects of heat stress on sheep, we used the hypothalamus for transcriptome sequencing and identified differentially expressed genes (DEGs; false discovery rate (FDR) < 0.01; fold change > 2) during heat stress. A total of 1423 DEGs (1122 upregulated and 301 downregulated) were identified and classified into Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Heat stress triggered dramatic and complex alterations in gene expression in the hypothalamus. We hypothesized that heat stress induced apoptosis and dysfunction in cells and vital organs and affected growth, development, reproduction, and circadian entrainment via the calcium signaling pathway, which influences ribosome assembly and function. Real-time PCR was used to evaluate the expression of the genes regulating important biological functions or whose expression profiles were significantly changed after acute heat stress (FDR < 0.01; fold change > 4), and the results showed that the expression patterns of these genes were consistent with the results of transcriptome sequencing, indicating that the credibility of the sequencing results. Our data indicated that heat stress induced calcium dyshomeostasis, blocked biogenesis, caused ROS accumulation, impaired the antioxidant system and innate defense, and induced apoptosis through the P53 signaling pathway activated by PEG3, decreased growth and development, and enhanced organ damage. These data is very important and helpful to elucidate the molecular mechanism of heat stress and finally to find ways to deal with heat stress damage in sheep.

GWAS on Imputed Whole-Genome Resequencing From Genotyping-by-Sequencing Data for Farrowing Interval of Different Parities in Pigs

The whole-genome sequencing (WGS) data can potentially discover all genetic variants. Studies have shown the power of WGS for genome-wide association study (GWAS) lies in the ability to identify quantitative trait loci and nucleotides (QTNs). However, the resequencing of thousands of target individuals is expensive. Genotype imputation is a powerful approach for WGS and to identify causal mutations. This study aimed to evaluate the imputation accuracy from genotyping-by-sequencing (GBS) to WGS in two pig breeds using a resequencing reference population and to detect single-nucleotide polymorphisms (SNPs) and candidate genes for farrowing interval (FI) of different parities using the data before and after imputation for GWAS. Six hundred target pigs, 300 Landrace and 300 Large White pigs, were genotyped by GBS, and 60 reference pigs, 20 Landrace and 40 Large White pigs, were sequenced by whole-genome resequencing. Imputation for pigs was conducted using Beagle software. The average imputation accuracy (allelic R ²) from GBS to WGS was 0.42 for Landrace pigs and 0.45 for Large White pigs. For Landrace pigs (Large White pigs), 4,514,934 (5,533,290) SNPs had an accuracy >0.3, resulting an average accuracy of 0.73 (0.72), and 2,093,778 (2,468,645) SNPs had an accuracy >0.8, resulting an average accuracy of 0.94 (0.93). Association studies with data before and after imputation were performed for FI of different parities in two populations. Before imputation, 18 and 128 significant SNPs were detected for FI in Landrace and Large White pigs, respectively. After imputation, 125 and 27 significant SNPs were identified for dataset with an accuracy >0.3 and 0.8 in Large White pigs, and 113 and 18 SNPs were found among imputed sequence variants. Among these significant SNPs, six top SNPs were detected in both GBS data and imputed WGS data, namely, SSC2: 136127645, SSC5: 103426443, SSC6: 27811226, SSC10: 3609429, SSC14: 15199253, and SSC15: 150297519. Overall, many candidate genes could be involved in FI of different parities in pigs. Although imputation from GBS to WGS data resulted in a low imputation accuracy, association analyses with imputed WGS data were optimized to detect QTNs for complex trait. The obtained results provide new insight into genotype imputation, genetic architecture, and candidate genes for FI of different parities in Landrace and Large White pigs.

Meta-analysis of genome-wide association studies for loin muscle area and loin muscle depth in two Duroc pig populations

Loin muscle area (LMA) and loin muscle depth (LMD) are important traits influencing the production performance of breeding pigs. However, the genetic architecture of these two traits is still poorly understood. To discern the genetic architecture of LMA and LMD, a material consisting of 6043 Duroc pigs belonging to two populations with different genetic backgrounds was collected and applied in genome-wide association studies (GWAS) with a genome-wide distributed panel of 50K single nucleotide polymorphisms (SNPs). To improve the power of detection for common SNPs, we conducted a meta-analysis in these two pig populations and uncovered additional significant SNPs. As a result, we identified 75 significant SNPs for LMA and LMD on SSC6, 7, 12, 16, and 18. Among them, 25 common SNPs were associated with LMA and LMD. One pleiotropic quantitative trait locus (QTL), which was located on SSC7 with a 283 kb interval, was identified to affect LMA and LMD. Marker ALGA0040260 is a key SNP for this QTL, explained 1.77% and 2.48% of the phenotypic variance for LMA and LMD, respectively. Another genetic region on SSC16 (709 kb) was detected and displayed prominent association with LMA and the peak SNP, WU_10.2_16_35829257, contributed 1.83% of the phenotypic variance for LMA. Further bioinformatics analysis determined eight promising candidate genes (GCLC, GPX8, DAXX, FGF21, TAF11, SPDEF, NUDT3, and PACSIN1) with functions in glutathione metabolism, adipose and muscle tissues development and lipid metabolism. This study provides the first GWAS for the LMA and LMD of Duroc breed to analyze the underlying genetic variants through a large sample size. The findings further advance our understanding and help elucidate the genetic architecture of LMA, LMD and growth-related traits in pigs.

Identifying Selection Signatures for Backfat Thickness in Yorkshire Pigs Highlights New Regions Affecting Fat Metabolism

Identifying the genetic basis of improvement in pigs contributes to our understanding of the role of artificial selection in shaping the genome. Here we employed the Cross Population Extended Haplotype Homozogysity (XPEHH) and the Wright's fixation index (F_ST) methods to detect trait-specific selection signatures by making phenotypic gradient differential population pairs, and then attempted to map functional genes of six backfat thickness traits in Yorkshire pigs. The results indicate that a total of 283 and 466 single nucleotide polymorphisms (SNPs) were identified as trait-specific selection signatures using F_ST and XPEHH, respectively. Functional annotation suggested that the genes overlapping with the trait-specific selection signatures such as OSBPL8, ASAH2, SMCO2, GBE1, and ABL1 are responsible for the phenotypes including fat metabolism, lean body mass and fat deposition, and transport in mouse. Overall, the study developed the methods of gene mapping on the basis of identification of selection signatures. The candidate genes putatively associated with backfat thickness traits can provide important references and fundamental information for future pig-breeding programs.

Identification and Functional Prediction of Long Intergenic Non-coding RNAs Related to Subcutaneous Adipose Development in Pigs

An increasing number of studies have shown that long intergenic non-coding RNAs (lincRNAs) are a very important class of non-coding RNAs that plays a vital role in many biological processes. Adipose tissue is an important place for storing energy, but few studies on lincRNAs were related to pig subcutaneous fat development. Here, we used published RNA-seq data from subcutaneous adipose tissue of Italian Large White pigs and identified 252 putative lincRNAs, wherein 34 were unannotated. These lincRNAs had relatively shorter length, lower number of exons, and lower expression level compared with protein-coding transcripts. Gene ontology and pathway analysis indicated that the adjacent genes of lincRNAs were involved in lipid metabolism. In addition, differentially expressed lincRNAs (DELs) between low and high backfat thickness pigs were identified. Through the detection of quantitative trait locus (QTL), DELs were mainly located in QTLs related to adipose development. Based on the expression correlation of DEL genes and their differentially expressed potential target genes, we constructed a co-expression network and a potential pathway of DEL's effect on lipid metabolism. Our study identified and analyzed lincRNAs in subcutaneous adipose tissue, and results suggested that lincRNAs may be involved in the regulation of subcutaneous fat development. Our findings provided new insights into the biological function of porcine lincRNAs.

Effects of genetic variations within goat PITX2 gene on growth traits and mRNA expression

Paired-like homeodomain 2 (PITX2), a key gene in hypothalamic-pituitary-adrena axis, influences animal growth and development. The objective of this study was to identify the association of the functional genetic variations within goat PITX2 gene with growth traits and mRNA expression levels. According to the reported single nucleotide polymorphisms (SNPs) information in Guanzhong dairy goat (GZDG), we identified genotypes of the known SNPs in Hainan black goat (HNBG). Association analysis uncovered that the SNPs of AC_000163: g.18117T > C, g.18161C > G and g.18353T > C loci were significantly associated with several growth traits (e.g., body height and body length) in HNBG and GZDG breeds. According to the quantitative real-time PCR assay, β-Actin and ribosomal protein L19 (RPL19) were the most stable expressed housekeeping genes in heart and skeletal muscle, respectively; meanwhile, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was the most stable expressed housekeeping gene in the other tissues. Based on the best housekeeping gene of varied tissues, we found the different genotypes of above loci were significantly associated with PITX2 mRNA expression in heart, muscle and small intestine. Briefly, the genetic variants of goat PITX2 associating with mRNA expression affected growth traits significantly, which would benefit for goat breeding in the future.