Identification of loci and genes for growth related traits from a genome-wide association study in a slow- × fast-growing broiler chicken cross

Genetic architecture of body weight, carcass, and internal organs traits of Ghanaian local chickens

Information on the genetic architecture of the production traits of indigenous African chicken is limited. We performed a genome-wide association study using imputed Affymetrix Axiom® 600K SNP-chip genotypes on 1,113 chickens from three agroecological zones of Ghana. After quality control, a total of 382,240 SNPs remained. Variance components and heritabilities for some growth, carcass and internal organ traits were estimated. The genetic and phenotypic correlations among these traits were also estimated. The estimated heritabilities of body weight at week 22 (BW22), average daily gain (ADG), dressed weight, breast weight, thigh weight, wing weight, drumstick weight, and neck weight were high and ranged from 0.50 to 0.69. Estimates of heritabilities for head weight, shank weight, and gizzard weight were moderate (0.31-0.35) while those of liver weight, back weight, dressing percentage, and heart weight were low (0.13-0.21). The estimated heritabilities of dressed weight, breast weight, wing weight, drumstick weight, neck weight, shank weight, and gizzard weight, corrected for BW22, were moderate (0.29-0.38), while the remaining traits had low heritability estimates (0.13-0.21). A total of 58 1-Mb SNP windows on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, 13, 18, and 33 each explained more than 1% of the genetic variance for at least one of these traits. These genomic regions contained many genes previously reported to have effects on growth, carcass, and internal organ traits of chickens, including EMX2, CALCUL1, ACVR1B, CACNB1, RB1, MLNR, FOXO1, NCARPG, LCORL, LAP3, LDB2, KPNA3, and CAB39L. The moderate to high heritability estimates and high positive genetic correlations suggest that BW22, ADG, dressed weight, breast weight, thigh weight, wing weight, drumstick weight, and neck weight could be improved through selective breeding.

Exploring the growth trait molecular markers in two sheep breeds based on Genome-wide association analysis

Growth traits are quantitative traits controlled by multiple micro-effect genes. we identified molecular markers related to sheep growth traits, which formed the basis of molecular breeding. In this study, we randomly selected 100 Qira Black sheep and 84 German Merino sheep for the blood collection the jugular vein to genotype by using the Illumina Ovine SNP 50K Bead Chip. quality control criteria for statistical analysis were: rejection detection rate < 90% and minimum allele frequency (MAF) < 5%. Then, we performed Genome-wide association studies (GWAS) on sheep body weight, body height, body length, and chest circumference using mixed linear models. After getting 55 SNPs with significant correlation, they were annotated by reference genome of Ovis aries genome (Oar_v4.0) and We obtained a total of 84 candidate genes associated with production traits (BMPR1B, HSD17B3, TMEM63C, etc.). We selected BMPR1B for population validation and found a correlation between the FecB locus and body weight traits. Therefore, this study not only supplements the existing knowledge of molecular markers of sheep growth traits, but also has important theoretical significance and reference value for the mining of functional genes of sheep growth traits.

Identification of New Genes and Genetic Variant Loci Associated with Breast Muscle Development in the Mini-Cobb F2 Chicken Population Using a Genome-Wide Association Study

Native chicken has become a favorite choice for consumers in many Asian countries recently, not only for its potential nutritional value but also for its deep ties to local food culture. However, low growth performance and limited meat production restrict their economic potential. Conducting a genome-wide association study (GWAS) for chicken-breast muscle development will help identify loci or candidate genes for different traits and potentially provide new insight into this phenotype in chickens and other species. To improve native chicken growth performance, especially breast muscle development, we performed a GWAS to explore the potential genetic mechanisms of breast muscle development in an F2 population constructed by reciprocal crosses between a fast-growing broiler chicken (Cobb500) and a slow-growing native chicken (Daweishan mini chicken). The results showed that 11 SNPs, which exceeded the 10% genome significance level (p = 1.79 × 10-8) were considered associated with breast muscle development traits, where six SNPS, NC_006126.5: g.3138376T>G, NC_006126.5: g.3138452A>G, NC_006088.5: g.73837197A>G, NC_006088.5: g.159574275A>G, NC_006089.5: g.80832197A>G, and NC_006127.5: g.48759869G>T was first identified in this study. In total, 13 genes near the SNPs were chosen as candidate genes, and none of them had previously been studied for their role in breast muscle development. After grouping the F2 population according to partial SNPs, significant differences in breast muscle weight were found among different genotypes (p < 0.05), and the expression levels of ALOX5AP, USPL1, CHRNA9, and EFNA5 among candidate genes were also significantly different (p < 0.05). The results of this study will contribute to the future exploration of the potential genetic mechanisms of breast muscle development in domestic chickens and also support the expansion of the market for native chicken in the world.

Large-Scale Whole Genome Sequencing Study Reveals Genetic Architecture and Key Variants for Breast Muscle Weight in Native Chickens

Breast muscle weight (BrW) is one of the most important economic traits in chicken, and directional breeding for that results in both phenotypic and genetic changes. The Jingxing yellow chicken, including an original (without human-driven selection) line and a selected line (based on selection for increased intramuscular fat content), were used to dissect the genetic architecture and key variants associated with BrW. We detected 1069 high-impact single nucleotide polymorphisms (SNPs) with high conserved score and significant frequency difference between two lines. Based on the annotation result, the ECM-receptor interaction and fatty acid biosynthesis were enriched, and muscle-related genes, including MYOD1, were detected. By performing genome-wide association study for the BrW trait, we defined a major haplotype and two conserved SNPs that affected BrW. By integrated genomic and transcriptomic analysis, IGF2BP1 was identified as the crucial gene associated with BrW. In conclusion, these results offer a new insight into chicken directional selection and provide target genetic markers by which to improve chicken BrW.

Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing

Background

Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features.

Results

We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model.

Conclusions

A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00672-9.

Genome-Wide Association Study Identifies 12 Loci Associated with Body Weight at Age 8 Weeks in Korean Native Chickens

Meat from Korean native chickens (KNCs) has high consumer demand; however, slow growth performance and high variation in body weight (BW) of KNCs remain an issue. Genome-wide association study (GWAS) is a powerful method to identify quantitative trait-associated genomic loci. A GWAS, based on a large-scale KNC population, is needed to identify underlying genetic mechanisms related to its growth traits. To identify BW-associated genomic regions, we performed a GWAS using the chicken 60K single nucleotide polymorphism (SNP) panel for 1328 KNCs. BW was measured at 8 weeks of age, from 2018 to 2020. Twelve SNPs were associated with BW at the suggestive significance level (p < 2.95 × 10⁻⁵) and located near or within 11 candidate genes, including WDR37, KCNIP4, SLIT2, PPARGC1A, MYOCD and ADGRA3. Gene set enrichment analysis based on the GWAS results at p < 0.05 (1680 SNPs) showed that 32 Gene Ontology terms and two Kyoto Encyclopedia of Genes and Genomes pathways, including regulation of transcription, motor activity, the mitogen-activated protein kinase signaling pathway, and tight junction, were significantly enriched (p < 0.05) for BW-associated genes. These pathways are involved in cell growth and development, related to BW gain. The identified SNPs are potential biomarkers in KNC breeding.

Identification of Major Loci and Candidate Genes for Meat Production-Related Traits in Broilers

Background

Carcass traits are crucial characteristics of broilers. However, the underlying genetic mechanisms are not well understood. In the current study, significant loci and major-effect candidate genes affecting nine carcass traits related to meat production were analyzed in 873 purebred broilers using an imputation-based genome-wide association study.

Results

The heritability estimates of nine carcass traits, including carcass weight, thigh muscle weight, and thigh muscle percentage, were moderate to high and ranged from 0.21 to 0.39. Twelve genome-wide significant SNPs and 118 suggestively significant SNPs of 546,656 autosomal variants were associated with carcass traits. All SNPs for six weight traits (body weight at 42 days of age, carcass weight, eviscerated weight, whole thigh weight, thigh weight, and thigh muscle weight) were clustered around the 24.08 Kb region (GGA24: 5.73–5.75 Mb) and contained only one candidate gene (DRD2). The most significant SNP, rs15226023, accounted for 4.85–7.71% of the estimated genetic variance of the six weight traits. The remaining SNPs for carcass composition traits (whole thigh percentage and thigh percentage) were clustered around the 42.52 Kb region (GGA3: 53.03–53.08 Mb) and contained only one candidate gene (ADGRG6). The most significant SNP in this region, rs13571431, accounted for 11.89–13.56% of the estimated genetic variance of two carcass composition traits. Some degree of genetic differentiation in ADGRG6 between large and small breeds was observed.

Conclusion

We identified one 24.08 Kb region for weight traits and one 42.52 Kb region for thigh-related carcass traits. DRD2 was the major-effect candidate gene for weight traits, and ADGRG6 was the major-effect candidate gene for carcass composition traits. Our results supply essential information for causative mutation identification of carcass traits in broilers.

Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals

Simple Summary

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

Abstract

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

Identification of new genes and quantitative trait locis associated with growth curve parameters in F2 chicken population using genome-wide association study

The markers which are correlated with the growth curve parameters help in understanding the characteristics of individual growth during the rearing of livestock. This study aimed to identify a set of biomarkers through a GWAS for growth curve parameters in crossbred chickens using the Illumnia 60K chicken SNP Beadchip. Growth data were collected from a total of 301 birds from cross of a broiler line and native chickens. Using the Gompertz-Laird model, two growth curve parameters, the instantaneous growth rate per day (L) and the coefficient of relative growth or maturing index (k), were estimated. The L and k were used to estimate five derived parameters, namely asymptotic (mature) body weight, body weight at inflection point, age at the inflection point, average growth rate and maximum growth rate. These parameters were considered as phenotypic values in the GWAS based on generalized linear models. The results of the GWAS indicated 21 significant markers, which were located near or within 46 genes. A number of these genes, such as GH, RET, GRB14, FTSJ3 and CCK, are important for growth and meat quality in chickens, and some of them are growth related in other species such as sheep and cattle (GPI, XIRP2, GALNTL6, BMS1, THSD4, TRHDE, SHISA9, ACSL6 and DYNC1LI2). The other genes are associated with developmental biological pathways. These genes are particuarly related to body weight, average daily gain and growth QTL. The results of this study can shed light on the genetic mechanism of biological functions of growth factors in broiler chickens, which is useful for developing management practices and accelerating genetic progress in breeding programs.

Genome-wide association study of shank length and diameter at different developmental stages in chicken F2 resource population

In order to find SNPs and genes affecting shank traits, we performed a GWAS in a chicken F2 population of eight half-sib families from five hatches derived from reciprocal crosses between an Arian fast-growing line and an Urmia indigenous slow-growing chicken. A total of 308 birds were genotyped using a 60K chicken SNP chip. Shank traits including shank length and diameter were measured weekly from birth to 12 weeks of age. A generalized linear model and a compressed mixed linear model (CMLM) were applied to achieve the significant regions. The value of the average genomic inflation factor (λ statistic) of the CMLM model (0.99) indicated that the CMLM was more effective than the generalized linear model in controlling the population structure. The genes surrounding significant SNPs and their biological functions were identified from NCBI, Ensembl and UniProt databases. The results indicated that 12 SNPs at 12 different ages passed the LD-adjusted 5% Bonferroni significant threshold. Two SNPs were significant for shank length and nine SNPs were significant for shank diameter. The significant SNPs were located near to or inside 11 candidate genes. The results showed that a number of significant SNPs in the middle ages were higher than the rest. The MXRA8 gene was related to the significant SNP at week 1 that promotes proliferation of growth plate chondrocytes. A unique SNP of Gga_rs16689511 located on chicken Z chromosome within the LOC101747628 gene was related to shank length at three different ages of birds (weeks 8, 9 and 11). The significant SNPs for shank diameter were found at weeks 4 and 7 (four and five SNPs respectively). The identifications of SNPs and genes here could contribute to a better understanding of the genetic control of shank traits in chicken.

Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle

Background

Body size traits as one of the main breeding selection criteria was widely used to monitor cattle growth and to evaluate the selection response. In this study, body size was defined as body height (BH), body length (BL), hip height (HH), heart size (HS), abdominal size (AS), and cannon bone size (CS). We performed genome-wide association studies (GWAS) of these traits over the course of three growth stages (6, 12 and 18 months after birth) using three statistical models, single-trait GWAS, multi-trait GWAS and LONG-GWAS. The Illumina Bovine HD 770 K BeadChip was used to identify genomic single nucleotide polymorphisms (SNPs) in 1217 individuals.

Results

In total, 19, 29, and 10 significant SNPs were identified by the three models, respectively. Among these, 21 genes were promising candidate genes, including SOX2, SNRPD1, RASGEF1B, EFNA5, PTBP1, SNX9, SV2C, PKDCC, SYNDIG1, AKR1E2, and PRIM2 identified by single-trait analysis; SLC37A1, LAP3, PCDH7, MANEA, and LHCGR identified by multi-trait analysis; and P2RY1, MPZL1, LINGO2, CMIP, and WSCD1 identified by LONG-GWAS.

Conclusions

Multiple association analysis was performed for six growth traits at each growth stage. These findings offer valuable insights for the further investigation of potential genetic mechanism of growth traits in Simmental beef cattle.

Effect of LCORL gene polymorphism on body size traits in horse populations

The aim of this study was to determine polymorphism of LCORL gene in horse breeds and its association with body size. PCR-RFLP technique was performed using AluI for genotyping of 306 horses. Results showed that C is the rare allele in Iranian Breeds, because these horses have been used since ancient times as a courier and for war and archery, hence selection has done to benefit of spiky horses with medium body that need less food and are tireless. While, for foreign breeds; frequency of C allele was high that can be concluded these breeds used in fields, forests, and mines. A UPGMA dendrogram based on the Nei's standard genetic distance among studied breeds showed separate clusters for Iranian native and exotic breeds. Statistical association analysis of three observed genotypes with body size showed that there is an association between this polymorphism and body size criteria (p < 0.01). Overall, it can be concluded that studied mutation in LCORL gene can be used as candidate marker for improving body weight in horse.

Reducing the interval of a growth QTL on chromosome 4 in laying hens

In our previous research, we identified a QTL with an interval of 3.4 Mb for growth on chicken chromosome (GGA) 4 in an advanced intercross population of an initial cross between the New Hampshire inbred line (NHI) and the White Leghorn inbred line (WL77). In the current study, an association analysis was performed in a population of purebred white layers (WLA) with White Leghorn origin. Genotypic data of 130 SNPs within the previously identified 3.4-Mb region were obtained using a 60K SNP chip. In total, 24 significant SNPs (LOD ≥ 4.44) on GGA4 were detected for daily weigh gain from 8 to 14 weeks and two SNPs (LOD ≥ 4.80) for body weight at 14 weeks. The QTL interval was reduced by 1.9 Mb to an interval of 1.5 Mb (74.6-76.1 Mb) that harbors 15 genes. Furthermore, to identify additional loci for chicken growth, a genome-wide association study (GWAS) was carried out in a WLA population. The GWAS identified an additional QTL on GGA6 for body weight at six weeks (19.8-21.2 Mb). Our findings showed that by using a WLA population we were able to further reduce the QTL confidence interval previously detected using a NHI × WL77 advanced intercross population.

Genome-wide association study identifies loci and candidate genes for internal organ weights in Simmental beef cattle

Cattle internal organs as accessible raw materials have a long history of being widely used in beef processing, feed and pharmaceutical industry. These traits not only are of economic interest to breeders, but they are intrinsically linked to many valuable traits, such as growth, health, and productivity. Using the Illumina Bovine HD 770K SNP array, we performed a genome-wide association study for heart weight, liver weight, spleen weight, lung weight, and kidney weight in 1,217 Simmental cattle. In our research, 38 significant single nucleotide polymorphisms (SNPs) ( P < 1.49 × 10−6) were identified for five internal organ weight traits. These SNPs are within or near 13 genes, and some of them have been reported previously, including NDUFAF4, LCORL, BT.94996, SLIT2, FAM184B, LAP3, BBS12, MECOM, CD300LF, HSD17B3, TLR4, MXI1, and MB21D2. In addition, we detected four haplotype blocks on BTA6 containing 18 significant SNPs associated with spleen weight. Our results offer worthy insights into understanding the genetic mechanisms of internal organs' development, with potential application in breeding programs of Simmental beef cattle.

Searching for new loci and candidate genes for economically important traits through gene-based association analysis of Simmental cattle

Single-marker genome-wide association study (GWAS) is a convenient strategy of genetic analysis that has been successful in detecting the association of a number of single-nucleotide polymorphisms (SNPs) with quantitative traits. However, analysis of individual SNPs can only account for a small proportion of genetic variation and offers only limited knowledge of complex traits. This inadequacy may be overcome by employing a gene-based GWAS analytic approach, which can be considered complementary to the single-SNP association analysis. Here we performed an initial single-SNP GWAS for bone weight (BW) and meat pH value with a total of 770,000 SNPs in 1141 Simmental cattle. Additionally, 21836 cattle genes collected from the Ensembl Genes 83 database were analyzed to find supplementary evidence to support the importance of gene-based association study. Results of the single SNP-based association study showed that there were 11 SNPs significantly associated with bone weight (BW) and two SNPs associated with meat pH value. Interestingly, all of these SNPs were located in genes detected by the gene-based association study.