Genome-wide association study of body weight in chicken F2 resource population

New insights into the genetic loci related to egg weight and age at first egg traits in broiler breeder

Egg weight (EW) and age at first egg (AFE) are economically important traits in breeder chicken production. The genetic basis of these traits, however, is far from understood, especially for broiler breeders. In this study, genetic parameter estimation, genome-wide association analysis, meta-analysis, and selective sweep analysis were carried out to identify genetic loci associated with EW and AFE in 6,842 broiler breeders. The study found that the heritability of EW ranged from 0.42 to 0.44, while the heritability of AFE was estimated at 0.33 in the maternal line. Meta-analysis and selective sweep analysis identified two colocalized regions on GGA4 that significantly influenced EW at 32 wk (EW32W) and at 43 wk (EW43W) with both paternal and maternal lines. The genes AR, YIPF6, and STARD8 were located within the significant region (GGA4: 366.86-575.50 kb), potentially affecting EW through the regulation of follicle development, cell proliferation, and lipid transfer etc. The promising genes LCORL and NCAPG were positioned within the significant region (GGA4:75.35-75.42 Mb), potentially influencing EW through pleiotropic effects on growth and development. Additionally, 3 significant regions were associated with AFE on chromosomes GGA7, GGA19, and GGA27. All of these factors affected the AFE by influencing ovarian development. In our study, the genomic information from both paternal and maternal lines was used to identify genetic regions associated with EW and AFE. Two genomic regions and eight genes were identified as the most likely candidates affecting EW and AFE. These findings contribute to a better understanding of the genetic basis of egg production traits in broiler breeders and provide new insights into future technology development.

Elucidation of the genetic determination of body weight and size in Chinese local chicken breeds by large-scale genomic analyses

BACKGROUND

Body weight and size are important economic traits in chickens. While many growth-related quantitative trait loci (QTLs) and candidate genes have been identified, further research is needed to confirm and characterize these findings. In this study, we investigate genetic and genomic markers associated with chicken body weight and size. This study provides new insights into potential markers for genomic selection and breeding strategies to improve meat production in chickens.

METHODS

We performed whole-genome resequencing of and Wenshang Barred (WB) chickens (n = 596) and three additional breeds with varying body sizes (Recessive White (RW), WB, and Luxi Mini (LM) chickens; (n = 50)). We then used selective sweeps of mutations coupled with genome-wide association study (GWAS) to identify genomic markers associated with body weight and size.

RESULTS

We identified over 9.4 million high-quality single nucleotide polymorphisms (SNPs) among three chicken breeds/lines. Among these breeds, 287 protein-coding genes exhibited positive selection in the RW and WB populations, while 241 protein-coding genes showed positive selection in the LM and WB populations. Genomic heritability estimates were calculated for 26 body weight and size traits, including body weight, chest breadth, chest depth, thoracic horn, body oblique length, keel length, pelvic width, shank length, and shank circumference in the WB breed. The estimates ranged from 0.04 to 0.67. Our analysis also identified a total of 2,522 genome-wide significant SNPs, with 2,474 SNPs clustered around two genomic regions. The first region, located on chromosome 4 (7.41-7.64 Mb), was linked to body weight after ten weeks and body size traits. LCORL, LDB2, and PPARGC1A were identified as candidate genes in this region. The other region, located on chromosome 1 (170.46-171.53 Mb), was associated with body weight from four to eighteen weeks and body size traits. This region contained CAB39L and WDFY2 as candidate genes. Notably, LCORL, LDB2, and PPARGC1A showed highly selective signatures among the three breeds of chicken with varying body sizes.

CONCLUSION

Overall this study provides a comprehensive map of genomic variants associated with body weight and size in chickens. We propose two genomic regions, one on chromosome 1 and the other on chromosome 4, that could helpful for developing genome selection breeding strategies to enhance meat yield in chickens.

Identify Candidate Genes Associated with the Weight and Egg Quality Traits in Wenshui Green Shell-Laying Chickens by the Copy Number Variation-Based Genome-Wide Association Study

Copy number variation (CNV), as an essential source of genetic variation, can have an impact on gene expression, genetic diversity, disease susceptibility, and species evolution in animals. To better understand the weight and egg quality traits of chickens, this paper aimed to detect CNVs in Wenshui green shell-laying chickens and conduct a copy number variation regions (CNVRs)-based genome-wide association study (GWAS) to identify variants and candidate genes associated with their weight and egg quality traits to support related breeding efforts. In our paper, we identified 11,035 CNVRs in Wenshui green shell-laying chickens, which collectively spanned a length of 13.1 Mb, representing approximately 1.4% of its autosomal genome. Out of these CNVRs, there were 10,446 loss types, 491 gain types, and 98 mixed types. Notably, two CNVRs showed significant correlations with egg quality, while four CNVRs exhibited significant associations with body weight. These significant CNVRs are located on chromosome 4. Further analysis identified potential candidate genes that influence weight and egg quality traits, including FAM184B, MED28, LAP3, ATOH8, ST3GAL5, LDB2, and SORCS2. In this paper, the CNV map of the Wenshui green shell-laying chicken genome was constructed for the first time through population genotyping. Additionally, CNVRs can be employed as molecular markers to genetically improve chickens' weight and egg quality traits.

Weighted single-step GWAS identified candidate genes associated with carcass traits in a Chinese yellow-feathered chicken population

Carcass traits in broiler chickens are complex traits that are influenced by multiple genes. To gain deeper insights into the genetic mechanisms underlying carcass traits, here we conducted a weighted single-step genome-wide association study (wssGWAS) in a population of Chinese yellow-feathered chicken. The objective was to identify genomic regions and candidate genes associated with carcass weight (CW), eviscerated weight with giblets (EWG), eviscerated weight (EW), breast muscle weight (BMW), drumstick weight (DW), abdominal fat weight (AFW), abdominal fat percentage (AFP), gizzard weight (GW), and intestine length (IL). A total of 1,338 broiler chickens with phenotypic and pedigree information were included in this study. Of these, 435 chickens were genotyped using a 600K single nucleotide polymorphism chip for association analysis. The results indicate that the most significant regions for 9 traits explained 2.38% to 5.09% of the phenotypic variation, from which the region of 194.53 to 194.63Mb on chromosome 1 with the gene RELT and FAM168A identified on it was significantly associated with CW, EWG, EW, BMW, and DW. Meanwhile, the 5 traits have a strong genetic correlation, indicating that the region and the genes can be used for further research. In addition, some candidate genes associated with skeletal muscle development, fat deposition regulation, intestinal repair, and protection were identified. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses suggested that the genes are involved in processes such as vascular development (CD34, FGF7, FGFR3, ITGB1BP1, SEMA5A, LOXL2), bone formation (FGFR3, MATN1, MEF2D, DHRS3, SKI, STC1, HOXB1, HOXB3, TIPARP), and anatomical size regulation (ADD2, AKT1, CFTR, EDN3, FLII, HCLS1, ITGB1BP1, SEMA5A, SHC1, ULK1, DSTN, GSK3B, BORCS8, GRIP2). In conclusion, the integration of phenotype, genotype, and pedigree information without creating pseudo-phenotype will facilitate the genetic improvement of carcass traits in chickens, providing valuable insights into the genetic architecture and potential candidate genes underlying carcass traits, enriching our understanding and contributing to the breeding of high-quality broiler chickens.

Genome-wide association studies for economically important traits in mink using copy number variation

Copy number variations (CNVs) are structural variants consisting of duplications and deletions of DNA segments, which are known to play important roles in the genetics of complex traits in livestock species. However, CNV-based genome-wide association studies (GWAS) have remained unexplored in American mink. Therefore, the purpose of the current study was to investigate the association between CNVs and complex traits in American mink. A CNV-based GWAS was performed with the ParseCNV2 software program using deregressed estimated breeding values of 27 traits as pseudophenotypes, categorized into traits of growth and feed efficiency, reproduction, pelt quality, and Aleutian disease tests. The study identified a total of 10,137 CNVs (6968 duplications and 3169 deletions) using the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array in 2986 American mink. The association analyses identified 250 CNV regions (CNVRs) associated with at least one of the studied traits. These CNVRs overlapped with a total of 320 potential candidate genes, and among them, several genes have been known to be related to the traits such as ARID1B, APPL1, TOX, and GPC5 (growth and feed efficiency traits); GRM1, RNASE10, WNT3, WNT3A, and WNT9B (reproduction traits); MYO10, and LIMS1 (pelt quality traits); and IFNGR2, APEX1, UBE3A, and STX11 (Aleutian disease tests). Overall, the results of the study provide potential candidate genes that may regulate economically important traits and therefore may be used as genetic markers in mink genomic breeding programs.

Association analysis of production traits of Japanese quail (Coturnix japonica) using restriction-site associated DNA sequencing

This study was designed to perform an association analysis and identify SNP markers associated with production traits of Japanese quail using restriction-site-associated DNA sequencing. Weekly body weight data from 805 quail were collected from hatching to 16 weeks of age. A total number of 3990 eggs obtained from 399 female quail were used to assess egg quality traits. Egg-related traits were measured at the beginning of egg production (first stage) and at 12 weeks of age (second stage). Five eggs were analyzed at each stage. Traits, such as egg weight, egg length and short axes, eggshell strength and weight, egg equator thickness, yolk weight, diameter, and colour, albumen weight, age of first egg, total number of laid eggs, and egg production rate, were assessed. A total of 383 SNPs and 1151 associations as well as 734 SNPs and 1442 associations were identified in relation to quail production traits using general linear model (GLM) and mixed linear model (MLM) approaches, respectively. The GLM-identified SNPs were located on chromosomes 1-13, 15, 17-20, 24, 26-28, and Z, underlying phenotypic traits, except for egg and albumen weight at the first stage and yolk yellowness at the second stage. The MLM-identified SNPs were positioned on defined chromosomes associated with phenotypic traits except for the egg long axis at the second stage of egg production. Finally, 35 speculated genes were identified as candidate genes for the targeted traits based on their nearest positions. Our findings provide a deeper understanding and allow a more precise genetic improvement of production traits of Galliformes, particularly in Japanese quail.

Genome-wide single nucleotide polymorphism (SNP) data reveal potential candidate genes for litter traits in a Yorkshire pig population

The litter trait is one of the most important economic traits, and increasing litter size is of great economic value in the pig industry. However, the molecular mechanisms underlying pig litter traits remain elusive. To identify molecular markers and candidate genes for pig litter traits, a genome-wide association study (GWAS) and selection signature analysis were conducted in a Yorkshire pig population. A total of 518 producing sows were genotyped with Illumina Porcine SNP 50 BeadChip, and 1969 farrowing records for the total number born (TNB), the number born alive (NBA), piglets born dead (PBD), and litter weight born alive (LWB) were collected. Then, a GWAS was performed for the four litter traits using a repeatability model. Based on the estimated breeding values (EBVs) of TNB, 15 high- and 15 low-prolificacy individuals were selected from the 518 sows to implement selection signature analysis. Subsequently, the selection signatures affecting the litter traits of sows were detected by using two methods including the fixation index (FST) and θ π . Combining the results of the GWAS and selection signature analysis, 20 promising candidate genes (NKAIN2, IGF1R, KISS1R, TYRO3, SPINT1, ADGRF5, APC2, PTBP1, CLCN3, CBR4, HPF1, FAM174A, SCP2, CLIC1, ZFYVE9, SPATA33, KIF5C, EPC2, GABRA2, and GABRA4) were identified. These findings provide novel insights into the genetic basis of pig litter traits and will be helpful for improving the reproductive performances of sows in pig breeding.

Genomic signatures of selection, local adaptation and production type characterisation of East Adriatic sheep breeds

BACKGROUND

The importance of sheep breeding in the Mediterranean part of the eastern Adriatic has a long tradition since its arrival during the Neolithic migrations. Sheep production system is extensive and generally carried out in traditional systems without intensive systematic breeding programmes for high uniform trait production (carcass, wool and milk yield). Therefore, eight indigenous Croatian sheep breeds from eastern Adriatic treated here as metapopulation (EAS), are generally considered as multipurpose breeds (milk, meat and wool), not specialised for a particular type of production, but known for their robustness and resistance to certain environmental conditions. Our objective was to identify genomic regions and genes that exhibit patterns of positive selection signatures, decipher their biological and productive functionality, and provide a "genomic" characterization of EAS adaptation and determine its production type.

RESULTS

We identified positive selection signatures in EAS using several methods based on reduced local variation, linkage disequilibrium and site frequency spectrum (eROHi, iHS, nSL and CLR). Our analyses identified numerous genomic regions and genes (e.g., desmosomal cadherin and desmoglein gene families) associated with environmental adaptation and economically important traits. Most candidate genes were related to meat/production and health/immune response traits, while some of the candidate genes discovered were important for domestication and evolutionary processes (e.g., HOXa gene family and FSIP2). These results were also confirmed by GO and QTL enrichment analysis.

CONCLUSIONS

Our results contribute to a better understanding of the unique adaptive genetic architecture of EAS and define its productive type, ultimately providing a new opportunity for future breeding programmes. At the same time, the numerous genes identified will improve our understanding of ruminant (sheep) robustness and resistance in the harsh and specific Mediterranean environment.

GWAS with principal component analysis identify QTLs associated with main peanut flavor-related traits

Peanut flavor is a complex and important trait affected by raw material and processing technology owing to its significant impact on consumer preference. In this research, principal component analysis (PCA) on 33 representative traits associated with flavor revealed that total sugars, sucrose, and total tocopherols provided more information related to peanut flavor. Genome-wide association studies (GWAS) using 102 U.S. peanut mini-core accessions were performed to study associations between 12,526 single nucleotide polymorphic (SNP) markers and the three traits. A total of 7 and 22 significant quantitative trait loci (QTLs) were identified to be significantly associated with total sugars and sucrose, respectively. Among these QTLs, four and eight candidate genes for the two traits were mined. In addition, two and five stable QTLs were identified for total sugars and sucrose in both years separately. No significant QTLs were detected for total tocopherols. The results from this research provide useful knowledge about the genetic control of peanut flavor, which will aid in clarifying the molecular mechanisms of flavor research in peanuts.

Integrated Transcriptomics Profiling in Chahua and Digao Chickens' Breast for Assessment Molecular Mechanism of Meat Quality Traits

Meat quality traits are an important economic trait and remain a major argument, from the producer to the consumer. However, there are a few candidate genes and pathways of chicken meat quality traits that were reported for chicken molecular breeding. The purpose of the present study is to identify the candidate genes and pathways associated with meat quality underlying variations in meat quality. Hence, transcriptome profiles of breast tissue in commercial Digao (DG, 5 male) and Chahua (CH, 5 male) native chicken breeds were analyzed at the age of 100 days. The results found 3525 differentially expressed genes (DEGs) in CH compared to DG with adjusted p-values of ≤0.05 and log2FC ≥ 0.1 FDR ≤ 0.05. Functional analysis of GO showed that the DEGs are mainly involved in the two types of processes of meat quality, such as positive regulation of the metabolic process, extracellular structure organization, collagen trimer, cellular amino acid metabolic process, cellular amino acid catabolic process, and heme binding. Functional analysis of KEGG showed that the DEGs are mainly involved in the two types of processes of meat quality, such as oxidative phosphorylation, carbon metabolism, valine, leucine, and isoleucine degradation, and fatty acid degradation. Many of the DEGs are well known to be related to meat quality, such as COL28A1, COL1A2, MB, HBAD, HBA1, ACACA, ACADL, ACSL1, ATP8A1, CAV1, FADS2, FASN, DCN, CHCHD10, AGXT2, ALDH3A2, and MORN4. Therefore, the current study detected multiple pathways and genes that could be involved in the control of the meat quality traits of chickens. These findings should be used as an essential resource to improve the accuracy of selection for meat traits in chickens using marker-assisted selection based on differentially expressed genes.

Advanced Practical Strategies to Enhance Table Egg Production

The global demand for table eggs has increased exponentially due to the growing human population. To meet this demand, major advances in hen genetics, nutrition, and husbandry procedures are required. Developing cost-effective and practically applicable strategies to improve egg production and quality is necessary for the development of egg industry worldwide. Consumers have shown a strong desire regarding the improvement of hens' welfare and egg quality. They also become interested in functional and designer foods. Modifications in the nutritional composition of laying hen diets significantly impact egg nutritional composition and quality preservation. According to previous scientific research, enriched egg products can benefit human health. However, producers are facing a serious challenge in optimizing breeding, housing, and dietary strategies to ensure hen health and high product quality. This review discussed several practical strategies to increase egg production, quality, and hens' welfare. These practical strategies can potentially be used in layer farms for sustainable egg production. One of these strategies is the transition from conventional to enriched or cage-free production systems, thereby improving bird behavior and welfare. In addition, widely use of plant/herbal substances as dietary supplements in layers' diets positively impacts hens' physiological, productive, reproductive, and immunological performances.

Genomic signatures reveal selection in Lingxian white goose

Lingxian white goose (LXW) is a goose breed indigenous to China that is famous for its meat quality and fast growth. However, the genomic evidence underlying such excellent breeding characteristics remains poorly understood. Therefore, we performed whole-genome resequencing of 141 geese from 3 indigenous breeds to scan for selection signatures and detect genomic regions related to breed features of LXW. We identified 5 reproduction-related genes (SYNE1, ESR1, NRIP1, CCDC170, and ARMT1) in highly differentiated regions and 11 notable genes in 26 overlapping windows, some of which are responsible for meat quality (DHX15), growth traits (LDB2, SLIT2, and RBPJ), reproduction (KCNIP4), and unique immunity traits (DHX15 and SLIT2). These findings provide insights into the genetic characteristics of LXW and identify genes affecting important traits in LXW, which extends the genetic resources and basis for facilitating genetic improvement in domestic geese breeds.

Paternal transgenerational nutritional epigenetic effect: A new insight into nutritional manipulation to reduce the use of antibiotics in animal feeding

The use of antibiotics in animal feeding has been banned in many countries because of increasing concerns about the development of bacterial resistance to antibiotics and potential issues on food safety. Searching for antibiotic substitutes is essential. Applying transgenerational epigenetic technology to animal production could be an alternative. Some environmental changes can be transferred to memory-like responses in the offspring through epigenetic mechanisms without changing the DNA sequence. In this paper, we reviewed those nutrients and non-nutritional additives that have transgenerational epigenetic effects, including some amino acids, vitamins, and polysaccharides. The paternal transgenerational nutritional epigenetic regulation was particularly focused on mechanism of the substantial contribution of male stud animals to the animal industries. We illustrated the effects of paternal transgenerational epigenetics on the metabolism and immunity in farming animals and proposed strategies to modulate male breeding livestock or poultry.

Genome-wide association study of VHSV-resistance trait in Paralichthys olivaceus

In flounder aquaculture, selective breeding plays a vital role in the development of disease-resistant traits and animals with high growth rates. Moreover, superior animals are required to achieve high profits. Unlike growth-related traits, disease-resistant experiments need to be conducted in a controlled environment, as the improper measurement of traits often leads to low genetic correlation and incorrect estimation of breeding values. In this study, viral hemorrhagic septicemia virus (VHSV) resistance was studied using a genome-wide association study (GWAS), and the genetic parameters were estimated. Genotyping was performed using a high-quality 70 K single nucleotide polymorphism (SNP) Affymetrix® Axiom® myDesign™ Genotyping Array of olive flounder. A heritability of ∼0.18 for resistance to VHSV was estimated using genomic information of the fish. According to the GWAS, significant SNPs were detected in chromosomes 21, 24, and contig AGQT02032065.1. Three SNPs showed significance at the genome-wide level (p < 1 × 10^-6), while others showed significance above the suggestive cutoff (p < 1 × 10^-4). The 3% phenotypic variation was explained by the highest significant SNP, named AX-419319631. Of the important genes for disease resistance, SNPs were associated with plcg1, epha4, clstn2, pik3cb, hes6, meis3, prx6, cep164, siae, and kirrel3b. Most of the genes associated with these SNPs have been previously reported with respect to viral entry, propagation, and immune mechanisms. Therefore, our study provides helpful information regarding VHSV resistance in olive flounder, which can be used for breeding applications.

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.

An association of CEP78, MEF2C, VPS13A and ARRDC3 genes with survivability to heat stress in an F2 chicken population

Heat stress is a serious problem in the poultry industry. An effective tool for improving heat tolerance can be genomic selection based on single nucleotide polymorphisms. This study was performed to identify genomic regions controlling survivability to heat stress in a population of F₂ chickens that accidentally experienced acute heat stress, using Illumina 60K Chicken SNP Bead Chip. After quality control in markers, 47,730 SNPs remained for genome-wide association study (GWAS). The GWAS results indicated that markers Gga_rs16111480 (p = 8.503e-08), GGaluGA354375 (p = 5.99e-07) and Gga_rs14748694 (p = 7.085e-07) located on Z chromosome showed significant association with heat stress tolerance trait. The Gga_rs16111480 marker was located inside the CEP78 gene. The marker GGaluGA354375 was located inside the LOC101752071 gene and next to the MEF2C gene. The Gga_rs14748694 marker was adjacent to LOC101752071 and MEF2C genes. Moreover, the SNP maker of Gga_rs16111480 was located on 243 kb downstream of the VPS13A gene, and the GGaluGA354375 and Gga_rs14748694 SNPs were located on 947 kb and 888 kb downstream of the ARRDC3 gene, respectively. The results of this study suggest that apart from the gene LOC101752071, which its function was unknown, each of the two MEF2C and CEP78 genes were found to be closely related to heat stress resistance in bird.

Genome Wide Association Study Identifies Candidate Genes Related to the Earlywood Tracheid Properties in Picea crassifolia Kom

Picea crassifolia Kom. is one of the timber and ecological conifers in China and its wood tracheid traits directly affect wood formation and adaptability under harsh environment. Molecular studies on P. crassifolia remain inadequate because relatively few genes have been associated with these traits. To identify markers and candidate genes that can potentially be used for genetic improvement of wood tracheid traits, we examined 106 clones of P. crassifolia, and investigated phenotypic data for 14 wood tracheid traits before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome wide association study (GWAS). Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the studied traits. We developed 4,058,883 SLAF-tags and 12,275,765 SNP loci, and our analyses identified a total of 96 SNP loci that showed significant correlations with three earlywood tracheid traits using a mixed linear model (MLM). Next, candidate genes were screened in the 100 kb zone (50 kb upstream, 50 kb downstream) of each of the SNP loci, whereby 67 candidate genes were obtained in earlywood tracheid traits, including 34 genes of known function and 33 genes of unknown function. We provide the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in wood traits improvement and candidate genes for the development of earlywood tracheid in P. crassifolia.

Genome-Wide Association Study of Body Weight Traits in Inner Mongolia Cashmere Goats

Objective: Body weight is an important economic trait for a goat, which greatly affects animal growth and survival. The purpose of this study was to identify genes associated with birth weight (BW), weaning weight (WW), and yearling weight (YW).

Materials and Methods: In this study, a genome-wide association study (GWAS) of BW, WW, and YW was determined using the GGP_Goat_70K single-nucleotide polymorphism (SNP) chip in 1,920 Inner Mongolia cashmere goats.

Results: We discovered that 21 SNPs were significantly associated with BW on the genome-wide levels. These SNPs were located in 10 genes, e.g., Mitogen-Activated Protein Kinase 3 (MAPK3), LIM domain binding 2 (LDB2), and low-density lipoprotein receptor-related protein 1B (LRP1B), which may be related to muscle growth and development in Inner Mongolia Cashmere goats. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that these genes were significantly enriched in the regulation of actin cytoskeleton and phospholipase D signaling pathway etc.

Conclusion: In summary, this study will improve the marker-assisted breeding of Inner Mongolia cashmere goats and the molecular mechanisms of important economic traits.

Genome-Wide Association Study of Growth Performance and Immune Response to Newcastle Disease Virus of Indigenous Chicken in Rwanda

A chicken genome has several regions with quantitative trait loci (QTLs). However, replication and confirmation of QTL effects are required particularly in African chicken populations. This study identified single nucleotide polymorphisms (SNPs) and putative genes responsible for body weight (BW) and antibody response (AbR) to Newcastle disease (ND) in Rwanda indigenous chicken (IC) using genome-wide association studies (GWAS). Multiple testing was corrected using chromosomal false detection rates of 5 and 10% for significant and suggestive thresholds, respectively. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of four significant SNPs (rs74098018, rs13792572, rs314702374, and rs14123335) significantly (p ≤ 7.6E-5) associated with BW were identified on chromosomes (CHRs) 8, 11, and 19. In the vicinity of these SNPs, four genes such as pre-B-cell leukaemia homeobox 1 (PBX1), GPATCH1, MPHOSPH6, and MRM1 were identified. Four other significant SNPs (rs314787954, rs13623466, rs13910430, and rs737507850) all located on chromosome 1 were strongly (p ≤ 7.6E-5) associated with chicken antibody response to ND. The closest genes to these four SNPs were cell division cycle 16 (CDC16), zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2). Besides, other SNPs and genes suggestively (p ≤ 1.5E-5) associated with BW and antibody response to ND were reported. This work offers a useful entry point for the discovery of causative genes accountable for essential QTLs regulating BW and antibody response to ND traits. Results provide auspicious genes and SNP-based markers that can be used in the improvement of growth performance and ND resistance in IC populations based on gene-based and/or marker-assisted breeding selection.

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 Studies for Growth Curves in Meat Rabbits Through the Single-Step Nonlinear Mixed Model

Growth is a complex trait with moderate to high heritability in livestock and must be described by the longitudinal data measured over multiple time points. Therefore, the used phenotype in genome-wide association studies (GWAS) of growth traits could be either the measures at the preselected time point or the fitted parameters of whole growth trajectory. A promising alternative approach was recently proposed that combined the fitting of growth curves and estimation of single-nucleotide polymorphism (SNP) effects into single-step nonlinear mixed model (NMM). In this study, we collected the body weights at 35, 42, 49, 56, 63, 70, and 84 days of age for 401 animals in a crossbred population of meat rabbits and compared five fitting models of growth curves (Logistic, Gompertz, Brody, Von Bertalanffy, and Richards). The logistic model was preferably selected and subjected to GWAS using the approach of single-step NMM, which was based on 87,704 genome-wide SNPs. A total of 45 significant SNPs distributed on five chromosomes were found to simultaneously affect the two growth parameters of mature weight (A) and maturity rate (K). However, no SNP was found to be independently associated with either A or K. Seven positional genes, including KCNIP4, GBA3, PPARGC1A, LDB2, SHISA3, GNA13, and FGF10, were suggested to be candidates affecting growth performances in meat rabbits. To the best of our knowledge, this is the first report of GWAS based on single-step NMM for longitudinal traits in rabbits, which also revealed the genetic architecture of growth traits that are helpful in implementing genome selection.

A genome-wide association analysis for body weight at 35 days measured on 137,343 broiler chickens

BACKGROUND

Body weight (BW) is an economically important trait in the broiler (meat-type chickens) industry. Under the assumption of polygenicity, a "large" number of genes with "small" effects is expected to control BW. To detect such effects, a large sample size is required in genome-wide association studies (GWAS). Our objective was to conduct a GWAS for BW measured at 35 days of age with a large sample size.

METHODS

The GWAS included 137,343 broilers spanning 15 pedigree generations and 392,295 imputed single nucleotide polymorphisms (SNPs). A false discovery rate of 1% was adopted to account for multiple testing when declaring significant SNPs. A Bayesian ridge regression model was implemented, using AlphaBayes, to estimate the contribution to the total genetic variance of each region harbouring significant SNPs (1 Mb up/downstream) and the combined regions harbouring non-significant SNPs.

RESULTS

GWAS revealed 25 genomic regions harbouring 96 significant SNPs on 13 Gallus gallus autosomes (GGA1 to 4, 8, 10 to 15, 19 and 27), with the strongest associations on GGA4 at 65.67-66.31 Mb (Galgal4 assembly). The association of these regions points to several strong candidate genes including: (i) growth factors (GGA1, 4, 8, 13 and 14); (ii) leptin receptor overlapping transcript (LEPROT)/leptin receptor (LEPR) locus (GGA8), and the STAT3/STAT5B locus (GGA27), in connection with the JAK/STAT signalling pathway; (iii) T-box gene (TBX3/TBX5) on GGA15 and CHST11 (GGA1), which are both related to heart/skeleton development); and (iv) PLAG1 (GGA2). Combined together, these 25 genomic regions explained ~ 30% of the total genetic variance. The region harbouring significant SNPs that explained the largest portion of the total genetic variance (4.37%) was on GGA4 (~ 65.67-66.31 Mb).

CONCLUSIONS

To the best of our knowledge, this is the largest GWAS that has been conducted for BW in chicken to date. In spite of the identified regions, which showed a strong association with BW, the high proportion of genetic variance attributed to regions harbouring non-significant SNPs supports the hypothesis that the genetic architecture of BW35 is polygenic and complex. Our results also suggest that a large sample size will be required for future GWAS of BW35.

A Missense Mutation in the MYBPH Gene Is Associated With Abdominal Fat Traits in Meat-Type Chickens

Chicken is an important source of protein for human nutrition and a model system for growth and developmental biology. Although the genetic architecture of quantitative traits in meat-type chickens has been the subject of ongoing investigation, the identification of mutations associated with carcass traits of economic interest remains challenging. Therefore, our aim was to identify predicted deleterious mutation, which potentially affects protein function, and test if they were associated with carcass traits in chickens. For that, we performed a genome-wide association analysis (GWAS) for breast, thigh and drumstick traits in meat-type chickens and detected 19 unique quantitative trait loci (QTL). We then used: (1) the identified windows; (2) QTL for abdominal fat detected in a previous study with the same population and (3) previously obtained whole genome sequence data, to identify 18 predicted deleterious single nucleotide polymorphisms (SNPs) in those QTL for further association with breast, thigh, drumstick and abdominal fat traits. Using the additive model, a predicted deleterious SNP c.482C > T (SIFT score of 0.4) was associated (p-value < 0.05) with abdominal fat weight and percentage. This SNP is in the second exon of the MYBPH gene, and its allele frequency deviates from Hardy–Weinberg equilibrium. In conclusion, our study provides evidence that the c.482C > T SNP in the MYBPH gene is a putative causal mutation for fat deposition in meat-type chickens.

Identification and Validation of Marketing Weight-Related SNP Markers Using SLAF Sequencing in Male Yangzhou Geese

Growth performance is a complex economic trait for avian production. The swan goose (Anser cygnoides) has never been exploited genetically like chickens or other waterfowl species such as ducks. Traditional phenotypic selection is still the main method for genetic improvement of geese body weight. In this study, specific locus amplified fragment sequencing (SLAF-seq) with bulked segregant analysis (BSA) was conducted for discovering and genotyping single nucleotide polymorphisms (SNPs) associated with marketing weight trait in male geese. A total of 149,045 SNPs were obtained from 427,093 SLAF tags with an average sequencing depth of 44.97-fold and a Q30 value of 93.26%. After SNPs' filtering, a total of 12,917 SNPs were included in the study. The 31 highest significant SNPs-which had different allelic frequencies-were further validated by individual-based AS-PCR genotyping in two populations. The association between 10 novel SNPs and the marketing weight of male geese was confirmed. The 10 significant SNPs were involved in linear regression model analysis, which confirmed single-SNP associations and revealed three types of SNP networks for marketing weight. The 10 significant SNPs were located within or close to 10 novel genes, which were identified. The qPCR analysis showed significant difference between genotypes of each SNP in seven genes. Developed SLAF-seq and identified genes will enrich growth performance studies, promoting molecular breeding applications to boost the marketing weight of Chinese geese.

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.

High resolution mapping and candidate gene identification of downy mildew race 16 resistance in spinach

Background

Downy mildew, the most devastating disease of spinach (Spinacia oleracea L.), is caused by the oomycete Peronospora effusa [=P. farinosa f. sp. spinaciae]. The P. effusa shows race specificities to the resistant host and comprises 19 reported races and many novel isolates. Sixteen new P. effusa races were identified during the past three decades, and the new pathogen races are continually overcoming the genetic resistances used in commercial cultivars. A spinach breeding population derived from the cross between cultivars Whale and Lazio was inoculated with P. effusa race 16 in an environment-controlled facility; disease response was recorded and genotyped using genotyping by sequencing (GBS). The main objective of this study was to identify resistance-associated single nucleotide polymorphism (SNP) markers from the cultivar Whale against the P. effusa race 16.

Results

Association analysis conducted using GBS markers identified six significant SNPs (S3_658,306, S3_692697, S3_1050601, S3_1227787, S3_1227802, S3_1231197). The downy mildew resistance locus from cultivar Whale was mapped to a 0.57 Mb region on chromosome 3, including four disease resistance candidate genes (Spo12736, Spo12784, Spo12908, and Spo12821) within 2.69–11.28 Kb of the peak SNP.

Conclusions

Genomewide association analysis approach was used to map the P. effusa race 16 resistance loci and identify associated SNP markers and the candidate genes. The results from this study could be valuable in understanding the genetic basis of downy mildew resistance, and the SNP marker will be useful in spinach breeding to select resistant lines.

Genotyping and Whole-Genome Resequencing of Welsh Sheep Breeds Reveal Candidate Genes and Variants for Adaptation to Local Environment and Socioeconomic Traits

Background

Advances in genetic tools applied to livestock breeding has prompted research into the previously neglected breeds adapted to harsh local environments. One such group is the Welsh mountain sheep breeds, which can be farmed at altitudes of 300 m above sea level but are considered to have a low productive value because of their poor wool quality and small carcass size. This is contrary to the lowland breeds which are more suited to wool and meat production qualities, but do not fare well on upland pasture. Herein, medium-density genotyping data from 317 individuals representing 15 Welsh sheep breeds were used alongside the whole-genome resequencing data of 14 breeds from the same set to scan for the signatures of selection and candidate genetic variants using haplotype- and SNP-based approaches.

Results

Haplotype-based selection scan performed on the genotyping data pointed to a strong selection in the regions of GBA3, PPARGC1A, APOB, and PPP1R16B genes in the upland breeds, and RNF24, PANK2, and MUC15 in the lowland breeds. SNP-based selection scan performed on the resequencing data pointed to the missense mutations under putative selection relating to a local adaptation in the upland breeds with functions such as angiogenesis (VASH1), anti-oxidation (RWDD1), cell stress (HSPA5), membrane transport (ABCA13 and SLC22A7), and insulin signaling (PTPN1 and GIGFY1). By contrast, genes containing candidate missense mutations in the lowland breeds are related to cell cycle (CDK5RAP2), cell adhesion (CDHR3), and coat color (MC1R).

Conclusion

We found new variants in genes with potentially functional consequences to the adaptation of local sheep to their environments in Wales. Knowledge of these variations is important for improving the adaptative qualities of UK and world sheep breeds through a marker-assisted selection.

Identification of candidate genes associated with slaughter traits in F2 chicken population using genome-wide association study

Slaughter traits are crucial economic traits of chickens. We performed a GWAS to discover critical loci and candidate genes for 21 slaughter traits in an F2 chicken population resulting from crossing Luxi gamecocks and recessive white feather broilers. We found some SNPs and genes which were significantly associated with keel length, head length, body slope length, bilateral leg weight without shin, bilateral foot weight, subcutaneous fat thickness, heart weight, muscular stomach weight and glandular stomach weight. This study provides references for further investigation of slaughter traits and molecular breeding in chicken.

Genomic Regions Related to White/Black Tail Feather Color in Dwarf Chickens Identified Using a Genome-Wide Association Study

Although the genetic foundation of chicken body feather color has been extensively explored, that of tail feather color remains poorly understood. In the present study, we used a synthetic chicken dwarf line (DW), derived from hybrids bred between a black tail chicken breed, Rhode Island Red (RIR), and a white tail breed, dwarf layer (DL), to investigate the genetic rules associated white/black tail color. Even though the body feathers are predominantly red, the DW line still comprises individuals with black or white tails after more than 10 generations of self-crossing and selection for the body feather color. We first performed four crosses using the DW chickens, including black-tailed males to females, reciprocal crosses between the black and white, and white males to females to elucidate the inheritance pattern of the white/black tail. We also performed a genome-wide association (GWA) analysis to determine the candidate genomic regions underlying the tail feather color using black tail chickens from the RIR and DW lines and white individuals from the DW line. In the crossing experiment, we found that (i) the white/black tail feather color is independent of body feather color; (ii) the phenotype is a simple autosomal trait; and (iii) the white is dominant to the black in the DW line. The GWA results showed that seven single-nucleotide polymorphisms (SNPs) on chromosome 24 were significantly correlated with tail feather color. The significant region (3.97-4.26 Mb) comprises nine known genes (NECTIN1, THY1, gga-mir-1466, USP2, C1QTNF5, RNF26, MCAM, CBL, and CCDC153) and five anonymous genes. This study revealed that the white/black tail feather trait is autosome-linked in DW chickens. Fourteen genes were found in the significant ~0.29 Mb genomic region, and some, especially MCAM, are suggested to play critical roles in the determination of white/black tail feather color. Our research is the first study on the genetics underlying tail feather color and could help further the understanding of feather pigmentation in chickens.

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.

Exploring the genetic architecture of feed efficiency traits in chickens

Chicken feed efficiency (FE) traits are the most important economic traits in broiler production. Several studies evaluating genetic factors affecting food consumption in chickens are available. However, most of these studies identified genomic regions containing putative quantitative trait loci for each trait separately. It is still a challenge to find common gene networks related to these traits. Therefore, here, a genome-wide association study (GWAS) was conducted to explore candidate genomic regions responsible for Feed Intake (FI), Body Weight Gain (BWG) and Feed Conversion Ratio (FCR) traits and their gene networks. A total of 1430 broilers from an experimental population was genotyped with the high density Affymetrix 600K SNP array. A total of 119 associated SNPs located in 20 chromosomes were identified, where some of them were common in more than one FE trait. In addition, novel genomic regions were prospected considering the SNPs dominance effects and sex interaction, identifying putative candidate genes only when these effects were fit in the model. Relevant candidate genes such as ATRNL1, PIK3C2A, PTPRN2, SORCS3 and gga-mir-1759 were highlighted in this study helping to elucidate the genomic architecture of feed efficiency traits. These results provide new insights on the mechanisms underlying the consumption and utilization of food in chickens.

QTL analysis for early growth in an intercross between native Japanese Nagoya and White Plymouth Rock chicken breeds using RAD sequencing-based SNP markers

An F₂ population of 239 chickens was obtained by an intercross between Nagoya (NAG), a native Japanese breed with low growth, and White Plymouth Rock (WPR), a Western breed with high growth. Using SNP markers obtained by restriction site-associated DNA sequencing, genome-wide QTL analysis was performed and it revealed three QTL for early postnatal growth in the F₂ population at genome-wide 5% significance levels. The most highly significant QTL affecting body weights at 2-4 weeks of age and weight gains at 2-3 and 0-4 weeks was located on GGA4 between 34.0 and 65.6 Mb with LOD scores of 3.9-5.9 and it explained 4.9-9.9% of the total variance of the traits. The analysis provided evidence for significant QTL on GGA2 between 105.6 and 125.2 Mb (LOD = 4.6) and on GGA1 between 51.1 and 61.6 Mb (LOD = 4.0) which had effects on body weight at 3 weeks and body weight gain at 0-1 week respectively. These two genomic regions explained 6.6 and 6.9% of the phenotypic F₂ variance of the corresponding traits respectively. The allele derived from WPR at all QTL increased the corresponding traits. Neither sex-specific nor epistatic QTL was detected. The results showed that the GGA4 QTL affecting multiple traits is a key locus responsible for early growth in our chicken cross, suggesting that this QTL may make a great contribution to genetic improvement of growth performance of the NAG breed with a low growth rate.

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 reveals the genetic determinism of growth traits in a Gushi-Anka F2 chicken population

Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F₂ resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1-6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.

Genetic Dissection of Growth Traits in a Unique Chicken Advanced Intercross Line

The advanced intercross line (AIL) that is created by successive generations of pseudo-random mating after the F₂ generation is a valuable resource, especially in agricultural livestock and poultry species, because it improves the precision of quantitative trait loci (QTL) mapping compared with traditional association populations by introducing more recombination events. The growth traits of broilers have significant economic value in the chicken industry, and many QTLs affecting growth traits have been identified, especially on chromosomes 1, 4, and 27, albeit with large confidence intervals that potentially contain dozens of genes. To promote a better understanding of the underlying genetic architecture of growth trait differences, specifically body weight and bone development, in this study, we report a nine-generation AIL derived from two divergent outbred lines: High Quality chicken Line A (HQLA) and Huiyang Bearded (HB) chicken. We evaluate the genetic architecture of the F₀, F₂, F₈, and F₉ generations of AIL and demonstrate that the population of the F₉ generation sufficiently randomized the founder genomes and has the characteristics of rapid linkage disequilibrium decay, limited allele frequency decline, and abundant nucleotide diversity. This AIL yielded a much narrower QTL than the F₂ generations, especially the QTL on chromosome 27, which was reduced to 120 Kb. An ancestral haplotype association analysis showed that most of the dominant haplotypes are inherited from HQLA but with fluctuation of the effects between them. We highlight the important role of four candidate genes (PHOSPHO1, IGF2BP1, ZNF652, and GIP) in bone growth. We also retrieved a missing QTL from AIL on chromosome 4 by identifying the founder selection signatures, which are explained by the loss of association power that results from rare alleles. Our study provides a reasonable resource for detecting quantitative trait genes and tracking ancestor history and will facilitate our understanding of the genetic mechanisms underlying chicken bone growth.

Goat Genomic Resources: The Search for Genes Associated with Its Economic Traits

Goat plays a crucial role in human livelihoods, being a major source of meat, milk, fiber, and hides, particularly under adverse climatic conditions. The goat genomics related to the candidate gene approach is now being used to recognize molecular mechanisms that have different expressions of growth, reproductive, milk, wool, and disease resistance. The appropriate literature on this topic has been reviewed in this article. Several genetic characterization attempts of different goats have reported the existence of genotypic and morphological variations between different goat populations. As a result, different whole-genome sequences along with annotated gene sequences, gene function, and other genomic information of different goats are available in different databases. The main objective of this review is to search the genes associated with economic traits in goats. More than 271 candidate genes have been discovered in goats. Candidate genes influence the physiological pathway, metabolism, and expression of phenotypes. These genes have different functions on economically important traits. Some genes have pleiotropic effect for expression of phenotypic traits. Hence, recognizing candidate genes and their mutations that cause variations in gene expression and phenotype of an economic trait can help breeders look for genetic markers for specific economic traits. The availability of reference whole-genome assembly of goats, annotated genes, and transcriptomics makes comparative genomics a useful tool for systemic genetic upgradation. Identification and characterization of trait-associated sequence variations and gene will provide powerful means to give positive influences for future goat breeding program.

Molecular characterization and a duplicated 31-bp indel within the LDB2 gene and its associations with production performance in chickens

Many studies have shown that the LDB2 gene plays a regulatory role in retinal development and the cell cycle, but its biological role remains unclear. In this study, a 31-bp indel in the LDB2 gene was found for the first time on the basis of 2797 individuals from 10 different breeds, which led to different genotypes among individuals (II, ID and DD). Among these genotypes, DD was the most dominant. Association analysis of an F₂ resource population crossed with the Gushi (GS) chicken and Anka chicken showed that the DD genotype conferred a significantly greater semi-evisceration weight (SEW, 1108.665 g ± 6.263), evisceration weight (EW, 927.455 g ± 5.424), carcass weight (CW, 1197.306 g ± 6.443), breast muscle weight (BMW, 71.05 g ± 0.574), and leg muscle weight (LMW, 100.303 g ± 0.677) than the ID genotype (SEW, 1059.079 g ± 16.86; EW, 879.459 g ± 14.446; CW, 1141.821 g ± 17.176; BMW, 67.164 g ± 1.523; and LMW, 96.163 g ± 1.823). In addition, LDB2 gene expression in different breeds was significantly higher in the breast muscles and leg muscles than in other tissues. The expression level in the breast muscle differed significantly among stages of GS chicken development, with the highest expression observed at 6 weeks. The expression levels in the pectoral muscles differed significantly among Ross 308 genotypes. In summary, we studied the relationships between a 31-bp indel in the LDB2 gene and economic traits in chickens. The indel was significantly correlated with multiple growth and carcass traits in the F₂ resource population and affected the expression of the LDB2 gene in muscle tissue. In short, our study revealed that the LDB2 gene 31-bp indel can be used as a potential genetic marker for molecular breeding.

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.

Identification of QTLs for resistance to leaf spots in cultivated peanut (Arachis hypogaea L.) through GWAS analysis

Two QTLs on ChrB09 significantly associated with both early and late leaf spots were identified by genome-wide association study in the US peanut mini-core collection. Early leaf spot (ELS) and late leaf spot (LLS) are two serious peanut diseases in the USA, causing tens of millions of dollars of annual economic losses. However, the genetic factors underlying resistance to those diseases in peanuts have not been well-studied. We conducted a genome-wide association study for the two peanut diseases using Affymetrix version 2.0 SNP array with 120 genotypes mainly coming from the US peanut mini-core collection. A total of 46 quantitative trait loci (QTLs) were identified with phenotypic variation explained (PVE) from 10.19 to 24.11%, in which eighteen QTLs are for resistance to ELS and 28 QTLs for LLS. Among the 46 QTLs, there were four and two major QTLs with PVE higher than 16.99% for resistance ELS and LLS, respectively. Of the six major QTLs, five were located on the B sub-genome and only one was on the A sub-genome, which suggested that the B sub-genome has more potential resistance genomic regions than the A sub-genome. In addition, two genomic regions on chromosome B09 were found to provide significant resistance to both ELS and LLS. A total of 74 non-redundant genes were identified as resistance genes, among which, twelve candidate genes were in significant genomic regions including two candidate genes for both ELS and LLS, and other ten candidate genes for ELS. The QTLs and candidate genes obtained from this study will be useful to breed peanuts for resistances to the diseases.

Signatures of selection analysis using whole-genome sequence data reveals novel candidate genes for pony and light horse types

Natural selection and domestication have shaped modern horse populations, resulting in a vast range of phenotypically diverse breeds. Horse breeds are classified into three types (pony, light, and draft) generally based on their body type. Understanding the genetic basis of horse type variation and selective pressures related to the evolutionary trend can be particularly important for current selection strategies. Whole-genome sequences were generated for 14 pony and 32 light horses to investigate the genetic signatures of selection of the horse type in pony and light horses. In the overlapping extremes of the fixation index and nucleotide diversity results, we found novel genomic signatures of selective sweeps near key genes previously implicated in body measurements including C4ORF33, CRB1, CPN1, FAM13A, and FGF12 that may influence variation in pony and light horse types. This study contributes to a better understanding of the genetic background of differences between pony and light horse types.

Genotype frequency distributions of 28 SNP markers in two commercial lines and five Chinese native chicken populations

Background

Modern breeding in the poultry industry mainly aims to produce high-performance poultry lines and breeds in two main directions of productivity, meat and eggs. To understand more about the productive potential of lowly selected Chinese native chicken populations, we selected 14 representative SNP markers strongly associated with growth traits or carcass traits and 14 SNP markers strongly associated with egg laying traits through previous reports. By using the MassArray technology, we detected the genotype frequency distributions of these 28 SNP markers in seven populations including four lowly selected as well as one moderately selected Sichuan native chicken populations, one commercial broiler line and one commercial layer line.

Results

Based on the genotype frequency distributions of these 28 SNP markers in 5 native chicken populations and 2 commercial lines, the results suggested that these Chinese indigenous chicken populations have a relatively close relationship with the commercial broiler line but a marked distinction from the commercial layer line. Two native chicken breeds, Shimian Caoke Chicken and Daheng Broilers, share similar genetic structure with the broiler line.

Conclusions

Our observations may help us to better select and breed superior domestic chickens and provide new clues for further study of breeding programs in local chicken populations.

Genome-wide association study provides insights into the genetic architecture of bone size and mass in chickens

Bone size is an important trait for chickens because of its association with osteoporosis in layers and meat production in broilers. Here, we employed high density genotyping platforms to detect candidate genes for bone traits. Estimates of the narrow heritabilities ranged from 0.37 ± 0.04 for shank length to 0.59 ± 0.04 for tibia length. The dominance heritability was 0.12 ± 0.04 for shank length. Using a linear mixed model approach, we identified a promising locus within NCAPG on chromosome 4, which was associated with tibia length and mass, femur length and area, and shank length. In addition, three other loci were associated with bone size or mass at a Bonferroni-corrected genome-wide significance threshold of 1%. One region on chicken chromosome 1 between 168.38 and 171.82 Mb harbored HTR2A, LPAR6, CAB39L, and TRPC4. A second region that accounted for 2.2% of the phenotypic variance was located around WNT9A on chromosome 2, where allele substitution was predicted to be associated with tibia length. Four candidate genes identified on chromosome 27 comprising SPOP, NGFR, GIP, and HOXB3 were associated with tibia length and mass, femur length and area, and shank length. Genome partitioning analysis indicated that the variance explained by each chromosome was proportional to its length.

Genome-Wide Association Study of Meat Quality Traits in Hanwoo Beef Cattle Using Imputed Whole-Genome Sequence Data

The discovery of single nucleotide polymorphisms (SNP) and the subsequent genotyping of large numbers of animals have enabled large-scale analyses to begin to understand the biological processes that underpin variation in animal populations. In beef cattle, genome-wide association studies using genotype arrays have revealed many quantitative trait loci (QTL) for various production traits such as growth, efficiency and meat quality. Most studies regarding meat quality have focused on marbling, which is a key trait associated with meat eating quality. However, other important traits like meat color, texture and fat color have not commonly been studied. Developments in genome sequencing technologies provide new opportunities to identify regions associated with these traits more precisely. The objective of this study was to estimate variance components and identify significant variants underpinning variation in meat quality traits using imputed whole genome sequence data. Phenotypic and genomic data from 2,110 Hanwoo cattle were used. The estimated heritabilities for the studied traits were 0.01, 0.16, 0.31, and 0.49 for fat color, meat color, meat texture and marbling score, respectively. Marbling score and meat texture were highly correlated. The genome-wide association study revealed 107 significant SNPs located on 14 selected chromosomes (one QTL region per selected chromosome). Four QTL regions were identified on BTA2, 12, 16, and 24 for marbling score and two QTL regions were found for meat texture trait on BTA12 and 29. Similarly, three QTL regions were identified for meat color on BTA2, 14 and 24 and five QTL regions for fat color on BTA7, 10, 12, 16, and 21. Candidate genes were identified for all traits, and their potential influence on the given trait was discussed. The significant SNP will be an important inclusion into commercial genotyping arrays to select new breeding animals more accurately.

Discovery and characterization of functional modules associated with body weight in broilers

Aim of the present study was to investigate whether body weight (BW) in broilers is associated with functional modular genes. To this end, first a GWAS for BW was conducted using 6,598 broilers and the high density SNP array. The next step was to search for positional candidate genes and QTLs within strong LD genomic regions around the significant SNPs. Using all positional candidate genes, a network was then constructed and community structure analysis was performed. Finally, functional enrichment analysis was applied to infer the functional relevance of modular genes. A total number of 645 positional candidate genes were identified in strong LD genomic regions around 11 genome-wide significant markers. 428 of the positional candidate genes were located within growth related QTLs. Community structure analysis detected 5 modules while functional enrichment analysis showed that 52 modular genes participated in developmental processes such as skeletal system development. An additional number of 14 modular genes (GABRG1, NGF, APOBEC2, STAT5B, STAT3, SMAD4, MED1, CACNB1, SLAIN2, LEMD2, ZC3H18, TMEM132D, FRYL and SGCB) were also identified as related to body weight. Taken together, current results suggested a total number of 66 genes as most plausible functional candidates for the trait examined.

Genomics, environment and balancing selection in behaviourally bimodal populations: The caribou case

Selection forces that favour different phenotypes in different environments can change frequencies of genes between populations along environmental clines. Clines are also compatible with balancing forces, such as negative frequency-dependent selection (NFDS), which maintains phenotypic polymorphisms within populations. For example, NFDS is hypothesized to maintain partial migration, a dimorphic behavioural trait prominent in species where only a fraction of the population seasonally migrates. Overall, NFDS is believed to be a common phenomenon in nature, yet a scarcity of studies were published linking naturally occurring allelic variation with bimodal or multimodal phenotypes and balancing selection. We applied a Pool-seq approach and detected selection on alleles associated with environmental variables along a North-South gradient in western North American caribou, a species displaying partially migratory behaviour. On 51 loci, we found a signature of balancing selection, which could be related to NFDS and ultimately the maintenance of the phenotypic polymorphisms known within these populations. Yet, remarkably, we detected directional selection on a locus when our sample was divided into two behaviourally distinctive groups regardless of geographic provenance (a subset of GPS-collared migratory or sedentary individuals), indicating that, within populations, phenotypically homogeneous groups were genetically distinctive. Loci under selection were linked to functional genes involved in oxidative stress response, body development and taste perception. Overall, results indicated genetic differentiation along an environmental gradient of caribou populations, which we found characterized by genes potentially undergoing balancing selection. We suggest that the underlining balancing force, NFDS, plays a strong role within populations harbouring multiple haplotypes and phenotypes, as it is the norm in animals, plants and humans too.

Genome-wide association studies targeting the yield of extraembryonic fluid and production traits in Russian White chickens

Background

The Russian White is a gene pool breed, registered in 1953 after crossing White Leghorns with local populations and, for 50 years, selected for cold tolerance and high egg production (EL). The breed has great potential in meeting demands of local food producers, commercial farmers and biotechnology sector of specific pathogen-free (SPF) eggs, the former valuing the breed for its egg weight (EW), EL, age at first egg (AFE), body weight (BW), and the latter for its yield of extraembryonic fluid (YEF) in 12.5-day embryos, ratio of extraembryonic fluid to egg weight, and embryo mass. Moreover, its cold tolerance has been presumably associated with day-old chick down colour (DOCDC) – white rather than yellow, the genetic basis of these traits being however poorly understood.

Results

We undertook genome-wide association studies (GWASs) for eight performance traits using single nucleotide polymorphism (SNP) genotyping of 146 birds and an Illumina 60KBeadChip. Several suggestive associations (p < 5.16*10^− 5) were found for YEF, AFE, BW and EW. Moreover, on chromosome 2, an association with the white DOCDC was found where there is an linkage disequilibrium block of SNPs including genes that are responsible not for colour, but for immune resistance.

Conclusions

The obtained GWAS data can be used to explore the genetics of immunity and carry out selection for increasing YEF for SPF eggs production.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5605-5) contains supplementary material, which is available to authorized users.

Genome-wide association study reveals novel loci associated with body size and carcass yields in Pekin ducks

Background

Pekin duck products have become popular in Asia over recent decades and account for an increasing market share. However, the genetic mechanisms affecting carcass growth in Pekin ducks remain unknown. This study aimed to identify quantitative trait loci affecting body size and carcass yields in Pekin ducks.

Results

We measured 18 carcass traits in 639 Pekin ducks and performed genotyping using genotyping-by-sequencing (GBS). Loci-based association analysis detected 37 significant loci for the 17 traits. Thirty-seven identified candidate genes were involved in many biological processes. One single nucleotide polymorphism (SNP) (Chr1_140105435 A > T) located in the intron of the ATPase phospholipid transporting 11A gene (ATP11A) attained genome-wide significance associated with five weight traits. Eight SNPs were significantly associated with three body size traits, including the candidate gene plexin domain containing 2 (PLXDC2) associated with breast width and tensin 3 (TNS3) associated with fossil bone length. Only two SNPs were significantly associated with foot weight and four SNPs were significantly associated with heart weight. In the gene-based analysis, three genes (LOC101791418, TUBGCP3 (encoding tubulin gamma complex-associated protein 3), and ATP11A) were associated with four traits (42-day body weight, eviscerated weight, half-eviscerated weight, and leg muscle weight percentage). However, no loci were significantly associated with leg muscle weight in this study.

Conclusions

The novel results of this study improve our understanding of the genetic mechanisms regulating body growth in ducks and thus provide a genetic basis for breeding programs aimed at maximizing the economic potential of Pekin ducks.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5379-1) contains supplementary material, which is available to authorized users.