Integration of transcriptome sequencing and whole genome resequencing reveal candidate genes in egg production of upright and pendulous-comb chickens

Detection of polymorphisms in six genes and their association analysis with litter size in sheep

Litter size in sheep is a complex trait controlled by micro-effective polygenes. APAF1, CLSTN2, CTH, PLCB1, PLCB4, and CHST11 are all involved in mammalian reproduction. However, the effects of these genes on litter size in sheep are still unclear. Therefore, in this study, we used Sequenom MassARRAY® SNP assay technology to type the single nucleotide polymorphisms (SNPs) loci of six genes in five sheep breeds. The results showed that most sheep breeds contain three genotypes at each locus. Then, we conducted population genetic analysis on the SNPs of six genes and found that the polymorphic information content in all sheep breeds ranged from 0 to 0.37, and most sheep breeds were in Hardy-Weinberg equilibrium (p > 0.05). In addition, association analysis in Small Tail Han sheep indicated that the rs399534524 locus in CLSTN2 was highly associated with first parity litter size, and litter size in ewes with CT genotype was higher than that in ewes with CC genotype or TT genotype. Furthermore, the rs407142552 locus in CTH was highly associated with second parity litter size in Small Tail Han sheep, and litter size in ewes with CT genotype was higher than that in ewes with TT genotype. Finally, we predicted the CTH and CLSTN2 protein interaction network and found that HTR1E, NOM1, CCDC174 and ALPK3 interact with CLSTN2 and have been reported as candidate genes related to litter size in sheep. These results suggest that they may be useful genetic markers for increasing litter size in sheep.

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.

Integrating Genomics and Transcriptomics to Identify Candidate Genes for Egg Production in Taihe Black-Bone Silky Fowls (Gallus gallus domesticus Brisson)

The Taihe Black-Bone Silky Fowl (Gallus gallus domesticus Brisson) possesses significant value in terms of consumption, medicinal applications, and ornamental appeal, representing a precious genetic resource and traditional Chinese medicinal material. However, considerable variation exists within populations regarding egg-laying performance. This study integrates a whole-genome selection signal analysis (SSA) with a transcriptome analysis to identify genes associated with egg-laying traits in Taihe Black-Bone Silky Fowls. We identified 31 candidate genes under selection from the high-yield chicken (HC) and low-yield chicken (LC) groups. Additionally, through RNA-seq analysis, 257 common differentially expressed genes (DEGs) were identified from four comparative groups. Two overlapping genes-LPL and SETBP1-were found in both the selected gene and DEG lists. These selected genes and DEGs were enriched in pathways related to ovarian development, including the lysosome pathway, the ECM-receptor interaction pathway, the TGF-beta signaling pathway, the Wnt signaling pathway, the PPAR signaling pathway, and the glycerolipid metabolism pathway. These research findings contribute to the breeding of Taihe Black-Bone Silky Fowls with high egg production traits and provide a theoretical foundation for exploring the regulatory mechanisms of avian reproduction.

Metabolomics reveals the reasons for the occurrence of Pendulous-comb related to egg production performance

The chicken comb is an essential secondary sexual characteristic to measure sexual maturity and is closely related to reproductive performance. Pendulous comb (PC) and upright comb (UC) are 2 common comb phenotypes in hens, which have been highly associated with egg production performance. However, the reasons for the formation of PC remain undetermined. In this study, we first characterized the PC and UC chicken at start (at 175 d age), peak (at 217 d age), and postlaying (at 300 d age) and found that PC and UC could transform for each other. Furthermore, we suggested that PC chicken demonstrated better egg production performance than UC chicken, especially characterizing comb type in the start-laying period. Moreover, we performed histological evaluation of PC and UC tissue, which suggested that the low density of collagen fibers and acid mucopolysaccharides might lead to the formation of PC. To further explore the possible reasons for PC formation, we performed an untargeted metabolomic analysis of serum between PC and UC chicken in the start, peak, and postlaying periods. The enrichment analysis of period-unique differentially expressed metabolites (DEMs) between PC and UC showed that the different metabolic pathways and nutritional levels might contribute to the formation of PC in the different laying periods. Our research provided critical insights into the phenotypic diversity of chicken comb, establishing a foundation for early selection of chicken egg production performance.

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.

Genetic parameter estimation and molecular foundation of chicken egg-laying trait

The age of first egg (AFE) in chicken can affect early and even life-time egg production performance to some extent, and therefore is an important economic trait that affects production efficiency. To better understand the genetic patterns of AFE and other production traits including body weight at first egg (BWA), first egg weight (FEW), and total egg number from AFE to 58 wk of age (total-EN), we recorded the production performance of 2 widely used layer breeds, white leghorn (WL) and Rhode Island Red (RIR) and estimated genetic parameters based on pedigree and production data. The results showed that the heritability of AFE in both breeds ranged from 0.4 to 0.6, and AFE showed strong positive genetic and phenotypic correlations to BWA as well as FEW, while showing strong negative genetic and phenotypic correlations with total-EN. Furtherly, by genome-wide association analysis study (GWAS), we identified 12 and 26 significant SNPs to be related to AFE in the 2-layer breeds, respectively. A total of 18 genes were identified that could affect AFE based on the significant SNP annotations obtained, but there were no gene overlapped in the 2 breeds indicating the genetic foundation of AFE could differ from breed to breed. Our results provided a deeper understanding of genetic patterns and molecular basement of AFE in different breeds and could help in the selection of egg production traits.

Genetic parameter estimation and molecular foundation of chicken beak shape

The bird beak is mainly functioned as feeding and attacking, and its shape has extremely important significance for survival and reproduction. In chickens, since beak shape could lead to some disadvantages including pecking and waste of feed, it is important to understand the inheritance of chicken beak shape. In the present study, we firstly established 4 indicators to describe the chicken beak shapes, including upper beak length (UL), lower beak length (LL), distance between upper and lower beak tips (DB) and upper beak curvature (BC). And then, we measured the 4 beak shape indicators as well as some production traits including body weight (BW), shank length (SL), egg weight (EW), eggshell strength (ES) of a layer breed, Rhode Island Red (RIR), in order to estimate genetic parameters of chicken beak shape. The heritabilities of UL and LL were 0.41 and 0.37, and the heritabilities of DB and BC were 0.22 and 0.21, indicating that beak shape was a highly or mediumly heritable. There were significant positive genetic and phenotypic correlations among UL, LL, and DB. And UL was positively correlated with body weight (BW18) and shank length (SL18) at 18 weeks of age in genetics, and DB was positively correlated with BC in terms of genetics and phenotype. We also found that layers of chicken cages played a role on beak shape, which could be attributed to the difference of lightness in different cage layers. By a genome-wide association study (GWAS) for the chicken UL, we identified 9 significant candidate genes associated with UL in RIR. For the variants with low minor allele frequencies (MAF <0.01) and outside of high linkage disequilibrium (LD) regions, we also conducted rare variant association studies (RVA) and GWAS to find the association between genotype and phenotype. We also analyzed transcriptomic data from multiple tissues of chicken embryos and revealed that all of the 9 genes were highly expressed in beak of chicken embryos, indicating their potential function for beak development. Our results provided the genetic foundation of chicken beak shape, which could help chicken breeding on beak related traits.

Transcriptome Profiling Unveils Key Genes Regulating the Growth and Development of Yangzhou Goose Knob

Goose is one of the most economically valuable poultry species and has a distinct appearance due to its possession of a knob. A knob is a hallmark of sexual maturity in goose (Anser cygnoides) and plays crucial roles in artificial selection, health status, social signaling, and body temperature regulation. However, the genetic mechanisms influencing the growth and development of goose knobs remain completely unclear. In this study, histomorphological and transcriptomic analyses of goose knobs in D70, D120, and D300 Yangzhou geese revealed differential changes in tissue morphology during the growth and development of goose knobs and the key core genes that regulate goose knob traits. Observation of tissue sections revealed that as age increased, the thickness of the knob epidermis, cuticle, and spinous cells gradually decreased. Additionally, fat cells in the dermis and subcutaneous connective tissue transitioned from loose to dense. Transcriptome sequencing results, analyzed through differential expression, Weighted Gene Co-expression Network Analysis (WGCNA), and pattern expression analysis methods, showed D70-vs.-D120 (up-regulated: 192; down-regulated: 423), D70-vs.-D300 (up-regulated: 1394; down-regulated: 1893), and D120-vs.-D300 (up-regulated: 1017; down-regulated: 1324). A total of 6243 differentially expressed genes (DEGs) were identified, indicating varied expression levels across the three groups in the knob tissues of D70, D120, and D300 Yangzhou geese. These DEGs are significantly enriched in biological processes (BP) such as skin morphogenesis, the regulation of keratinocyte proliferation, and epidermal cell differentiation. Furthermore, they demonstrate enrichment in pathways related to goose knob development, including ECM-receptor interaction, NF-kappa B, and PPAR signaling. Through pattern expression analysis, three gene expression clusters related to goose knob traits were identified. The joint analysis of candidate genes associated with goose knob development and WGCNA led to the identification of key core genes influencing goose knob development. These core genes comprise WNT4, WNT10A, TCF7L2, GATA3, ADRA2A, CASP3, SFN, KDF1, ERRFI1, SPRY1, and EVPL. In summary, this study provides a reference for understanding the molecular mechanisms of goose knob growth and development and provides effective ideas and methods for the genetic improvement of goose knob 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.

Transcriptome analysis of hypothalamus and pituitary tissues reveals genetic mechanisms associated with high egg production rates in Changshun green-shell laying hens

BACKGROUND

Changshun green-shell laying hens are unique to the Guizhou Province, China, and have high egg quality but relatively low yield. Egg production traits are regulated by the hypothalamus-pituitary-ovary axis. However, the underlying mechanism remains unclear. Thus, we conducted RNA sequencing of hypothalamic and pituitary tissues from low- and high-yielding Changshun green-shell laying hens to identify critical pathways and candidate genes involved in controlling the egg production rate.

RESULTS

More than 39 million clean reads per sample were obtained, and more than 82% were mapped to the Gallus gallus genome. Further analysis identified 1,817 and 1,171 differentially expressed genes (DEGs) in the hypothalamus and pituitary, respectively. Nineteen DEGs were upregulated in both the hypothalamus and pituitary of high-yielding chickens. The functions of these DEGs were mainly associated with ion transport or signal transduction. Gene set enrichment analysis revealed that the pathways enriched in the hypothalamus were mainly associated with gonadotropin-releasing hormone (GnRH) secretion, neurotransmitter release, and circadian rhythms. The pathways enriched in the pituitary were mainly associated with GnRH secretion, energy metabolism, and signal transduction. Five and four DEGs in the hypothalamus and pituitary, respectively, were selected randomly for qRT-PCR analysis. The expression trends determined via qRT-PCR were consistent with the RNA-seq results.

CONCLUSIONS

The current study identified 19 DEGs upregulated in both the hypothalamus and pituitary gland, which could provide an important reference for further studies on the molecular mechanisms underlying egg production in Changshun green-shell laying hens. In addition, enrichment analysis showed that GnRH secretion and signal transduction, especially neurotransmitter release, play crucial roles in the regulation of egg production.

Whole Genome Resequencing Helps Study Important Traits in Chickens

The emergence of high-throughput sequencing technology promotes life science development, provides technical support to analyze many life mechanisms, and presents new solutions to previously unsolved problems in genomic research. Resequencing technology has been widely used for genome selection and research on chicken population structure, genetic diversity, evolutionary mechanisms, and important economic traits caused by genome sequence differences since the release of chicken genome sequence information. This article elaborates on the factors influencing whole genome resequencing and the differences between these factors and whole genome sequencing. It reviews the important research progress in chicken qualitative traits (e.g., frizzle feather and comb), quantitative traits (e.g., meat quality and growth traits), adaptability, and disease resistance, and provides a theoretical basis to study whole genome resequencing in chickens.

Whole-genome resequencing to unveil genetic characteristics and selection signatures of specific pathogen-free ducks

Specific pathogen-free ducks are important high-grade laboratory animals, with a key role in research related to poultry biosecurity, production, and breeding. However, the genetic characteristics of experimental duck varieties remain poorly explored. Herein we performed whole-genome resequencing to construct a single nucleotide polymorphism genetic map of the genomes of 3 experimental duck varieties [Jinding ducks (JD), Shaoxing ducks (SX), and Fujian Shanma ducks (SM)] to determine their genetic characteristics and identify selection signatures. Subsequent analyses of population structure and genetic diversity revealed that each duck variety formed a monophyletic group, with SM showing richer genetic diversity than JD and SX. Further, on exploring shared selection signatures, we found 2 overlapping genomic regions on chromosome Z of all experimental ducks, which comprised immune response-related genes (IL7R and IL6ST). Moreover, growth and skeletal development (IGF1R and GDF5), meat quality (FoxO1), and stress resistance (HSP90B1 and Gpx8-b) candidate gene loci were identified in strongly selected signatures specific to JD, SM, and SX, respectively. Our results identified the population genetic basis of experimental ducks at the whole-genome level, providing a framework for future molecular investigations of genetic variations and phenotypic changes. We believe that such studies will eventually contribute to the management of experimental animal resources.