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

Comparison of genomic prediction accuracy using different models for egg production traits in Taiwan country chicken

In local chickens targeted for niche markets, genotyping costs are relatively high due to the small population size and diverse breeding goals. The single-step genomic best linear unbiased prediction (ssGBLUP) model, which combines pedigree and genomic information, has been introduced to increase the accuracy of genomic estimated breeding value (GEBV). Therefore, this model may be more beneficial than the genomic BLUP (GBLUP) model for genomic selection in local chickens. Additionally, the single-step genome-wide association study (ssGWAS) can be used to extend the ssGBLUP model results to animals with available phenotypic information but without genotypic data. In this study, we compared the accuracy of (G)EBVs using the pedigree-based BLUP (PBLUP), GBLUP, and ssGBLUP models. Moreover, we conducted single-SNP GWAS (SNP-GWAS), GBLUP-GWAS, and ssGWAS methods to identify genes associated with egg production traits in the NCHU-G101 chicken to understand the feasibility of using genomic selection in a small population. The average prediction accuracy of (G)EBV for egg production traits using the PBLUP, GBLUP, and ssGBLUP models is 0.536, 0.531, and 0.555, respectively. In total, 22 suggestive- and 5% Bonferroni genome-wide significant-level SNPs for total egg number (EN), average laying rate (LR), average clutch length, and total clutch number are detected using 3 GWAS methods. These SNPs are mapped onto Gallus gallus chromosomes (GGA) 4, 6, 10, 18, and 25 in NCHU-G101 chicken. Furthermore, through SNP-GWAS and ssGWAS methods, we identify 2 genes on GGA4 associated with EN and LR: ENSGALG00000023172 and PPARGC1A. In conclusion, the ssGBLUP model demonstrates superior prediction accuracy, performing on average 3.41% than the PBLUP model. The implications of our gene results may guide future selection strategies for Taiwan Country chickens. Our results highlight the applicability of the ssGBLUP model for egg production traits selection in a small population, specifically NCHU-G101 chicken in Taiwan.

Genome-wide association study identified candidate genes for egg production traits in the Longyan Shan-ma duck

Egg production is an important economic trait in layer ducks and understanding the genetics basis is important for their breeding. In this study, a genome-wide association study (GWAS) for egg production traits in 303 female Longyan Shan-ma ducks was performed based on a genotyping-by-sequencing strategy. Sixty-two single nucleotide polymorphisms (SNPs) associated with egg weight traits were identified (P < 9.48 × 10-5), including 8 SNPs at 5% linkage disequilibrium (LD)-based Bonferroni-corrected genome-wide significance level (P < 4.74 × 10-6). One hundred and nineteen SNPs were associated with egg number traits (P < 9.48 × 10-5), including 13 SNPs with 5% LD-based Bonferroni-corrected genome-wide significance (P < 4.74 × 10-6). These SNPs annotated 146 target genes which contained known candidate genes for egg production traits, such as prolactin and prolactin releasing hormone receptor. This study identified that these associated genes were significantly enriched in egg production-related pathways (P < 0.05), such as the oxytocin signaling, MAPK signaling, and calcium signaling pathways. It was notable that 18 genes were differentially expressed in ovarian tissues between higher and lower egg production in Shan-ma ducks. The identified potential candidate genes and pathways provide insight into the genetic basis underlying the egg production trait of layer ducks.

The Omics Revolution in Understanding Chicken Reproduction: A Comprehensive Review

Omics approaches have significantly contributed to our understanding of several aspects of chicken reproduction. This review paper gives an overview of the use of omics technologies such as genomics, transcriptomics, proteomics, and metabolomics to elucidate the mechanisms of chicken reproduction. Genomics has transformed the study of chicken reproduction by allowing the examination of the full genetic makeup of chickens, resulting in the discovery of genes associated with reproductive features and disorders. Transcriptomics has provided insights into the gene expression patterns and regulatory mechanisms involved in reproductive processes, allowing for a better knowledge of developmental stages and hormone regulation. Furthermore, proteomics has made it easier to identify and quantify the proteins involved in reproductive physiology to better understand the molecular mechanisms driving fertility, embryonic development, and egg quality. Metabolomics has emerged as a useful technique for understanding the metabolic pathways and biomarkers linked to reproductive performance, providing vital insights for enhancing breeding tactics and reproductive health. The integration of omics data has resulted in the identification of critical molecular pathways and biomarkers linked with chicken reproductive features, providing the opportunity for targeted genetic selection and improved reproductive management approaches. Furthermore, omics technologies have helped to create biomarkers for fertility and embryonic viability, providing the poultry sector with tools for effective breeding and reproductive health management. Finally, omics technologies have greatly improved our understanding of chicken reproduction by revealing the molecular complexities that underpin reproductive processes.

Genome-wide association studies of egg production traits by whole genome sequencing of Laiwu Black chicken

Compared to high-yield commercial laying hens, Chinese indigenous chicken breeds have poor egg laying capacity due to the lack of intensive selection. However, as these breeds have not undergone systematic selection, it is possible that there is a greater abundance of genetic variations related to egg laying traits. In this study, we assessed 5 egg number (EN) traits at different stages of the egg-laying period: EN1 (from the first egg to 23 wk), EN2 (from 23 to 35 wk), EN3 (from 35 to 48 wk), EN4 (from the first egg to 35 wk), and EN5 (from the first egg to 48 wk). To investigate the molecular mechanisms underlying egg number traits in a Chinese local chicken breed, we conducted a genome-wide association study (GWAS) using data from whole-genome sequencing (WGS) of 399 Laiwu Black chickens. We obtained a total of 3.01 Tb of raw data with an average depth of 7.07 × per individual. A total of 86 genome-wide suggestive or significant single-nucleotide polymorphisms (SNP) contained within a set of 45 corresponding candidate genes were identified and found to be associated with stages EN1-EN5. The genes vitellogenin 2 (VTG2), lipase maturation factor 1 (LMF1), calcium voltage-gated channel auxiliary subunit alpha2delta 3 (CACNA2D3), poly(A) binding protein cytoplasmic 1 (PABPC1), programmed cell death 11 (PDCD11) and family with sequence similarity 213 member A (FAM213A) can be considered as the candidate genes associated with egg number traits, due to their reported association with animal reproduction traits. Noteworthy, results suggests that VTG2 and PDCD11 are not only involved in the regulation of EN3, but also in the regulation of EN5, implies that VTG2 and PDCD11 have a significant influence on egg production traits. Our study offers valuable genomic insights into the molecular genetic mechanisms that govern egg number traits in a Chinese indigenous egg-laying chicken breed. These findings have the potential to enhance the egg-laying performance of chickens.

Molecular genetic foundation of a sex-linked tailless trait in Hongshan chicken by whole genome data analysis

As a Chinese local chicken breed, Hongshan chickens have 2 kinds of tail feather phenotypes, normal and taillessness. Our previous studies showed that taillessness was a sex-linked dominant trait. Abnormal development of the tail vertebrae could be explained this phenomenon in some chicken breeds. However, the number of caudal vertebrae in rumpless Hongshan chickens was normal, so rumplessness in Hongshan chicken was not related to the development of the caudal vertebrae. Afterwards, we found that rumplessness in Hongshan was due to abnormal development of tail feather rather than abnormal development of caudal vertebrae. In order to understand the genetic foundation of the rumplessness of Hongshan chickens, we compared and reanalyzed 2 sets of data in normal and rumpless Hongshan chickens from our previous studies. By joint analysis of genome-wide selection signature analysis and genome-wide association approach, we found that 1 overlapping gene (EDIL3) and 16 peak genes (ENSGALG00000051843, ENSGALG00000053498, ENSGALG00000054800, KIF27, PTPRD, ENSGALG00000047579, ENSGALG00000041052, ARHGEF28, CAMK4, SERINC5, ENSGALG00000050776, ERCC8, MCC, ADAMTS19, ENSGALG00000053322, CHRNA8) located on the Z chromosome was associated with the rumpless trait. The results of this study furtherly revealed the molecular mechanism of the rumpless trait in Hongshan chickens, and identified the candidate genes associated with this trait. Our results will help to improve the shape of chicken tail feathers and to rise individual economic value in some specific market in China.

Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens

Genomic prediction plays an increasingly important role in modern animal breeding, with predictive accuracy being a crucial aspect. The classical linear mixed model is gradually unable to accommodate the growing number of target traits and the increasingly intricate genetic regulatory patterns. Hence, novel approaches are necessary for future genomic prediction. In this study, we used an illumina 50K SNP chip to genotype 4190 egg-type female Rhode Island Red chickens. Machine learning (ML) and classical bioinformatics methods were integrated to fit genotypes with 10 economic traits in chickens. We evaluated the effectiveness of ML methods using Pearson correlation coefficients and the RMSE between predicted and actual phenotypic values and compared them with rrBLUP and BayesA. Our results indicated that ML algorithms exhibit significantly superior performance to rrBLUP and BayesA in predicting body weight and eggshell strength traits. Conversely, rrBLUP and BayesA demonstrated 2-58% higher predictive accuracy in predicting egg numbers. Additionally, the incorporation of suggestively significant SNPs obtained through the GWAS into the ML models resulted in an increase in the predictive accuracy of 0.1-27% across nearly all traits. These findings suggest the potential of combining classical bioinformatics methods with ML techniques to improve genomic prediction in the future.

Artificial selection footprints in indigenous and commercial chicken genomes

BACKGROUND

Although many studies have been done to reveal artificial selection signatures in commercial and indigenous chickens, a limited number of genes have been linked to specific traits. To identify more trait-related artificial selection signatures and genes, we re-sequenced a total of 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan Province, China.

RESULTS

We found 30 million non-redundant single nucleotide variants and small indels (< 50 bp) in the indigenous chickens, of which 10 million were not seen in 60 broilers, 56 layers and 35 red jungle fowls (RJFs) that we compared with. The variants in each breed are enriched in non-coding regions, while those in coding regions are largely tolerant, suggesting that most variants might affect cis-regulatory sequences. Based on 27 million bi-allelic single nucleotide polymorphisms identified in the chickens, we found numerous selective sweeps and affected genes in each indigenous chicken breed and substantially larger numbers of selective sweeps and affected genes in the broilers and layers than previously reported using a rigorous statistical model. Consistent with the locations of the variants, the vast majority (~ 98.3%) of the identified selective sweeps overlap known quantitative trait loci (QTLs). Meanwhile, 74.2% known QTLs overlap our identified selective sweeps. We confirmed most of previously identified trait-related genes and identified many novel ones, some of which might be related to body size and high egg production traits. Using RT-qPCR, we validated differential expression of eight genes (GHR, GHRHR, IGF2BP1, OVALX, ELF2, MGARP, NOCT, SLC25A15) that might be related to body size and high egg production traits in relevant tissues of relevant breeds.

CONCLUSION

We identify 30 million single nucleotide variants and small indels in the five indigenous chicken breeds, 10 million of which are novel. We predict substantially more selective sweeps and affected genes than previously reported in both indigenous and commercial breeds. These variants and affected genes are good candidates for further experimental investigations of genotype-phenotype relationships and practical applications in chicken breeding programs.

Whole transcriptome analysis reveals the key genes and noncoding RNAs related to follicular atresia in broilers

Broodiness, a maternal behavior, is accompanied by the atresia of follicles and the serious degradation of poultry reproductive performance. The comparison of follicles between brooding and laying hens is usually an ideal model for exploring the regulation mechanism of follicle atresia. In this study, we selected three brooding hens and three laying hens to collect their follicles for whole transcriptome sequencing. The results demonstrated different expression patterns between the follicles of brooding hens and laying hens. In the top 10 differentially expressed genes with the highest expression, MMP10 was relatively low expressed in the follicles of brooding hens, but other nine genes were relatively highly expressed, including LRR1, RACK1, SPECC1L, ABHD2, COL6A3, RPS17, ATRN, BIRC6, PGAM1 and SPECC1L. While miR-21-3p, miR-146a-5p, miR-142-5p and miR-1b-3p were highly expressed in the follicles of brooding hen, miR-106-5p, miR-451, miR-183, miR-7, miR-2188-5p and miR-182-5p were lowly expressed in brooding hen. In addition, we identified 124 lncRNAs specifically expressed in the follicles of brooding hens and 147 lncRNAs specifically expressed in the follicles of laying hens. Our results may provide a theoretical basis for further exploration of the molecular mechanism of broodiness in broilers.

Genome-Wide Association Study of Egg Production Traits in Shuanglian Chickens Using Whole Genome Sequencing

Egg production is the most important economic trait in laying hens. To identify molecular markers and candidate genes associated with egg production traits, such as age at first egg (AFE), weight at first egg (WFE), egg weight (EW), egg number (EN), and maximum consecutive egg laying days (MCD), a genome-wide analysis by whole genome sequencing was performed in Shuanglian chickens. Through whole genome sequencing and quality control, a total of 11,006,178 SNPs were obtained for further analysis. Heritability estimates ranged from moderate to high for EW (0.897) and MCD (0.632), and from low to moderate (0.193~0.379) for AFE, WFE, and EN. The GWAS results showed 11 genome-wide significant SNPs and 23 suggestive significant SNPs were identified to be associated with EN, MCD, WFE, and EW. Linkage disequilibrium analysis revealed twenty-seven SNPs associated with EN were located in a 0.57 Mb region on GGA10, and clustered into five blocks. Through functional annotation, three candidate genes NEO1, ADPGK, and CYP11A1, were identified to be associated with EN, while the S1PR4, LDB2, and GRM8 genes was linked to MCD, WFE, and EW, respectively. These findings may help us to better understand the molecular mechanisms underlying egg production traits in chickens and contribute to genetic improvement of these traits.

Elucidation of the genetic determination of clutch traits in Chinese local chickens of the Laiwu Black breed

BACKGROUND

Egg laying rate (LR) is associated with a clutch, which is defined as consecutive days of oviposition. The clutch trait can be used as a selection indicator to improve egg production in poultry breeding. However, little is known about the genetic basis of clutch traits. In this study, our aim was to estimate genetic parameters and identify quantitative trait single nucleotide polymorphisms for clutch traits in 399 purebred Laiwu Black chickens (a native Chinese breed) using a genome-wide association study (GWAS).

METHODS

In this work, after estimating the genetic parameters of age at first egg, body weight at first egg, LR, longest clutch until 52 week of age, first week when the longest clutch starts, last week when the longest clutch ends, number of clutches, and longest number of days without egg-laying until 52 week of age, we identified single nucleotide polymorphisms (SNPs) and potential candidate genes associated with clutch traits in Laiwu Black chickens. The restricted maximum likelihood method was used to estimate genetic parameters of clutch pattern in 399 Laiwu Black hens, using the GCTA software.

RESULTS

The results showed that SNP-based heritability estimates of clutch traits ranged from 0.06 to 0.59. Genotyping data were obtained from whole genome re-sequencing data. After quality control, a total of 10,810,544 SNPs remained to be analyzed. The GWAS revealed that 421 significant SNPs responsible for clutch traits were scattered on chicken chromosomes 1-14, 17-19, 21-25, 28 and Z. Among the annotated genes, NELL2, SMYD9, SPTLC2, SMYD3 and PLCL1 were the most promising candidates for clutch traits in Laiwu Black chickens.

CONCLUSION

The findings of this research provide critical insight into the genetic basis of clutch traits. These results contribute to the identification of candidate genes and variants. Genes and SNPs potentially provide new avenues for further research and would help to establish a framework for new methods of genomic prediction, and increase the accuracy of estimated genetic merit for egg production and clutch traits.

Serum metabolic profile and metabolome genome-wide association study in chicken

BACKGROUND

Chickens provide globally important livestock products. Understanding the genetic and molecular mechanisms underpinning chicken economic traits is crucial for improving their selective breeding. Influenced by a combination of genetic and environmental factors, metabolites are the ultimate expression of physiological processes and can provide key insights into livestock economic traits. However, the serum metabolite profile and genetic architecture of the metabolome in chickens have not been well studied.

RESULTS

Here, comprehensive metabolome detection was performed using non-targeted LC-MS/MS on serum from a chicken advanced intercross line (AIL). In total, 7,191 metabolites were used to construct a chicken serum metabolomics dataset and to comprehensively characterize the serum metabolism of the chicken AIL population. Regulatory loci affecting metabolites were identified in a metabolome genome-wide association study (mGWAS). There were 10,061 significant SNPs associated with 253 metabolites that were widely distributed across the entire chicken genome. Many functional genes affect metabolite synthesis, metabolism, and regulation. We highlight the key roles of TDH and AASS in amino acids, and ABCB1 and CD36 in lipids.

CONCLUSIONS

We constructed a chicken serum metabolite dataset containing 7,191 metabolites to provide a reference for future chicken metabolome characterization work. Meanwhile, we used mGWAS to analyze the genetic basis of chicken metabolic traits and metabolites and to improve chicken breeding.

Genetics of rearing success in four pure laying hen lines during the first 17 weeks of age

This study aimed to investigate the genetics of rearing success (RS) in laying hens. Four rearing traits: clutch size (CS), first week mortality (FWM), rearing abnormalities (RA), and natural death (ND), were included as factors determining RS. Pedigree, genotypic, and phenotypic records of 4 purebred genetic lines of White Leghorn layers were available for 23,000 rearing batches obtained between 2010 and 2020. FWM and ND showed little or no variation amongst the 4 genetic lines over the years 2010-2020, whereas an increase was observed for CS and a decrease for RA. To determine whether these traits were heritable, genetic parameters for each trait were estimated, using a Linear Mixed Model. Heritabilities within lines were low (0.05-0.19 for CS, 0.01-0.04 for FWM, 0.02-0.06 for RA, 0.02-0.04 for ND, and 0.01-0.07 for RS). Additionally, genome wide association study was done to scan the genomes of the breeders to reveal single nucleotide polymorphisms (SNPs) associated with these traits. Manhattan plots indicated the existence of 12 different SNPs having a significant effect on RS. Thus, the identified SNPs will increase the understanding of the genetics of RS in laying hens.

Interacting Networks of the Hypothalamic-Pituitary-Ovarian Axis Regulate Layer Hens Performance

Egg production is a vital biological and economic trait for poultry breeding. The 'hypothalamic-pituitary-ovarian (HPO) axis' determines the egg production, which affects the layer hens industry income. At the organism level, the HPO axis is influenced by the factors related to metabolic and nutritional status, environment, and genetics, whereas at the cellular and molecular levels, the HPO axis is influenced by the factors related to endocrine and metabolic regulation, cytokines, key genes, signaling pathways, post-transcriptional processing, and epigenetic modifications. MiRNAs and lncRNAs play a critical role in follicle selection and development, atresia, and ovulation in layer hens; in particular, miRNA is known to affect the development and atresia of follicles by regulating apoptosis and autophagy of granulosa cells. The current review elaborates on the regulation of the HPO axis and its role in the laying performance of hens at the organism, cellular, and molecular levels. In addition, this review provides an overview of the interactive network regulation mechanism of the HPO axis in layer hens, as well as comprehensive knowledge for successfully utilizing their genetic resources.

A significant quantitative trait locus on chromosome Z and its impact on egg production traits in seven maternal lines of meat-type chicken

BACKGROUND

Egg production is economically important in the meat-type chicken industry. To better understand the molecular genetic mechanism of egg production in meat-type chicken, genetic parameter estimation, genome-wide association analyses combined with meta-analyses, Bayesian analyses, and selective sweep analyses were performed to screen single nucleotide polymorphisms (SNPs) and other genetic loci that were significantly associated with egg number traits in 11,279 chickens from seven material lines.

RESULTS

Yellow-feathered meat-type chickens laid 115 eggs at 43 weeks of age and white-feathered chickens laid 143 eggs at 60 weeks of age, with heritability ranging from 0.034-0.258. Based on meta-analyses and selective sweep analyses, one region (10.81-13.05 Mb) on chromosome Z was associated with egg number in all lines. Further analyses using the W2 line was also associated with the same region, and 29 SNPs were identified that significantly affected estimation of breeding value of egg numbers. The 29 SNPs were identified as having a significant effect on the egg number EBV in 3194 birds in line W2. There are 36 genes in the region, with glial cell derived neurotrophic factor, DAB adaptor protein 2, protein kinase AMP-activated catalytic subunit alpha 1, NAD kinase 2, mitochondrial, WD repeat domain 70, leukemia inhibitory factor receptor alpha, complement C6, and complement C7 identified as being potentially affecting to egg number. In addition, three SNPs (rs318154184, rs13769886, and rs313325646) associated with egg number were located on or near the prolactin receptor gene.

CONCLUSION

Our study used genomic information from different chicken lines and populations to identify a genomic region (spanning 2.24 Mb) associated with egg number. Nine genes and 29 SNPs were identified as the most likely candidate genes and variations for egg production. These results contribute to the identification of candidate genes and variants for egg traits in poultry.

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

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

Transcriptome Sequencing-Based Mining of Genes Associated With Pubertal Initiation in Dolang Sheep

Improving the fertility of sheep is an important goal in sheep breeding as it greatly increases the productivity. Dolang sheep is a typical representative breed of lamb in Xinjiang and is the main local sheep breed and meat source in the region. To explore the genes associated with the initiation of puberty in Dolang sheep, the hypothalamic tissues of Dolang sheep prepubertal, pubertal, and postpubertal periods were collected for RNA-seq analysis on the Illumina platform, generating 64.08 Gb clean reads. A total of 575, 166, and 648 differentially expressed genes (DEGs) were detected in prepuberty_vs._puberty, postpuberty_vs._prepuberty, and postpuberty_vs._puberty analyses, respectively. Based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, the related genes involved in the initiation of puberty in Dolang sheep were mined. Ten genes that have direct or indirect functions in the initiation of puberty in Dolang sheep were screened using the GO and KEGG results. Additionally, quantitative real-time PCR was used to verify the reliability of the RNA-Seq data. This study provided a new approach for revealing the mechanism of puberty initiation in sheep and provided a theoretical basis and candidate genes for the breeding of early-pubertal sheep by molecular techniques, and at the same time, it is also beneficial for the protection, development, and utilization of the fine genetic resources of Xinjiang local sheep.