The GTPase activating Rap/RanGAP domain-like 1 gene is associated with chicken reproductive traits

Analysis of the differentially expressed genes in the combs and testes of Qingyuan partridge roosters at different developmental stages

BACKGROUND

The sexual maturity of chickens is an important economic trait, and the breeding of precocious and delayed puberty roosters is an important selection strategy for broilers. The comb serves as an important secondary sexual characteristic of roosters and determines their sexual precocity. Moreover, comb development is closely associated with gonad development in roosters. However, the underlying molecular mechanism regulating the sexual maturity of roosters has not yet been fully explored.

RESULTS

In order to identify the genes related to precocious puberty in Qingyuan partridge roosters, and based on the synchrony of testis and combs development, combined with histological observation and RNA-seq method, the developmental status and gene expression profile of combs and testis were obtained. The results showed that during the early growth and development period (77 days of age), the development of combs and testis was significant in the high comb (H) group versus the low comb (L) group (p < 0.05); however, the morphological characteristic of the comb and testicular tissues converged during the late growth and development period (112 days of age) in the H and L groups. Based on these results, RNA-sequencing analysis was performed on the comb and testis tissues of the 77 and 112 days old Qingyuan Partridge roosters with different comb height traits. GO and KEGG analysis enrichment analysis showed that the differentially expressed genes were primarily enriched in MAPK signaling, VEGF signaling, and retinol metabolism pathways. Moreover, weighted correlation network analysis and module co-expression network analysis identified WNT6, AMH, IHH, STT3A, PEX16, KPNA7, CATHL2, ROR2, PAMR1, WISP2, IL17REL, NDRG4, CYP26B1, and CRHBP as the key genes associated with the regulation of precocity and delayed puberty in Qingyuan Partridge roosters.

CONCLUSIONS

In summary, we identified the key regulatory genes of sexual precocity in roosters, which provide a theoretical basis for understanding the developmental differences between precocious and delayed puberty in roosters.

Estimation of genetic parameters of eggshell translucency and production traits in different genotypes of laying hens

The translucency of eggshells is a ubiquitous appearance problem caused by moisture translocation and the accumulation of egg contents into the eggshell ultrastructure. Previous studies have mainly investigated the causes of eggshell translucency from nutritional and environmental perspectives. However, little is known of the effect of genetics the causes of eggshell translucency on hen production performance. To evaluate the genetic parameters of eggshell translucency and other production performance indicators, we performed an experiment on 3 pure hen lines: 624 Dwarf Layer-White, 1,612 Rhode Island Red, and 813 Rhode Island Red-White. We collected eggs from each hen over 5 d and measured eggshell translucent level (TL) using the grading method. Additionally we measured indicators of each hen during the laying period, including age at laying of the first egg (AFE), body weight at laying of the first egg (BWFE), weight of the first egg (FEW), body weight at 40 wk (BW40), egg weight at 40 wk (EW40), egg production up to 40 wk of age (EN), and calculated the genetic parameters among the indicators. The results showed that the estimated heritability of TL in the 3 genotypes were 0.30, 0.24, and 0.20, respectively, suggesting a low or moderate level of heritability. We found a positive correlation between TL and AFE, with genetic correlation coefficients 0.19 to 0.41, and negative genetic correlation between TL and EN, with correlation coefficient -0.36 to -0.19. Additionally, we observed positive correlation exists between AFE and FEW, BWFE and FEW, and BW40 and EW40; and negative correlation between AFE and EN in the 3 pure lines. These results enriched the research on heritability of eggshell translucency in different hen breeds and demonstrated moderate or low heritability of the indicator. Furthermore, eggshell translucency was negatively affected by AFE and EN. Our results provide a valuable reference for predicting selection response of eggshell translucency and production performance in brood hens, and locating the genes regulating eggshell translucency.

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.

Differential expression and functional analysis of circRNA in the ovaries of Yili geese at different egg-laying stages

BACKGROUND

Ovarian development is regulated by genes that are expressed dynamically and stage-specifically. Circular RNA (circRNA) has been proven to play a significant role in the regulation of animal reproduction.

OBJECTIVE

Studying the expression characteristics of circRNAs in goose ovaries at various egg-laying stages can provide a reference for the molecular regulation mechanism of ovary development in geese that is mediated by circRNAs.

METHODS

In this study, the expression profiles of circRNAs were compared in ovary tissues from Yili geese in three different breeding periods, namely the prelaying period (KL), laying period (CL), and ceased period (XL), and differentially expressed circRNAs related to ovarian development in Yili geese were screened. The potential biological functions of differential circRNAs were predicted by bioinformatics, and the differential circRNA-miRNA regulatory network was constructed.

RESULTS

The results showed that a total of 4483 circRNAs were identified in 12 ovarian tissue samples from Yili geese at different laying stages. In the KL vs. CL, XL vs. CL, and XL vs. KL groups, 159, 455, and 383 differentially expressed circRNAs were identified, respectively. The host genes of the differential circRNAs were mostly enriched in the signal transduction, metabolism, and other related pathways, such as those for phototransduction, glycerophospholipid metabolism, aminoacyl-tRNA biosynthesis, and retinol metabolism. Finally, we constructed circRNA-miRNA regulation networks. Nine differential circRNAs were randomly selected for qRT-PCR verification, and the expression trends were consistent with the sequencing results.

CONCLUSIONS

Our results indicated that significant differences in the expression profiles of circRNAs in the ovaries of Yili geese at different egg-laying stages. Meanwhile, through analyzing the differential circRNA-miRNA interaction network, core regulators such as circRNA NW_013186107.1:36835|52,574 and gga-miR-34b-5p were screened. This study provides a reference for the further analysis of the molecular regulatory mechanism of the circRNAs regulating goose ovary development and enriches the theory of genetic regulation during goose ovary development.

Transcriptomic analyses of the HPG axis-related tissues reveals potential candidate genes and regulatory pathways associated with egg production in ducks

Background

Egg production is one of the most important economic traits in the poultry industry. The hypothalamic-pituitary–gonadal (HPG) axis plays an essential role in regulating reproductive activities. However, the key genes and regulatory pathways within the HPG axis dominating egg production performance remain largely unknown in ducks.

Results

In this study, we compared the transcriptomic profiles of the HPG-related tissues between ducks with high egg production (HEP) and low egg production (LEP) to reveal candidate genes and regulatory pathways dominating egg production. We identified 543, 759, 670, and 181 differentially expressed genes (DEGs) in the hypothalamus, pituitary, ovary stroma, and F5 follicle membrane, respectively. Gene Ontology (GO) analysis revealed that DEGs from four HPG axis-related tissues were enriched in the "cellular component" category. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the neuroactive ligand-receptor interaction pathway was significantly enriched based on DEGs commonly identified in all four HPG axis-related tissues. Gene expression profiles and Protein–Protein Interaction (PPI) network were performed to show the regulatory relationships of the DEGs identified. Five DEGs encoding secreted proteins in the hypothalamus and pituitary have interaction with DEGs encoding targeted proteins in the ovary stroma and F5 follicle membrane, implying that they were these DEGs might play similar roles in the regulation of egg production.

Conclusions

Our results revealed that neuroactive ligand-receptor interaction pathway and five key genes(VEGFC, SPARC, BMP2, THBS1, and ADAMTS15) were identified as the key signaling pathways and candidate genes within the HPG axis responsible for different egg production performance between HEP and LEP. This is the first study comparing the transcriptomic profiles of all HPG axis-related tissues in HEP and LEP using RNA-seq in ducks to the best of our knowledge. These data are helpful to enrich our understanding of the classical HPG axis regulating the egg production performance and identify candidate genes that can be used for genetic selection in ducks.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08483-y.

Effects of Observed Incubation Behavior on Egg Production in Laying Hens of a Commercial Chicken Breed and Detection of Single-Nucleotide Polymorphisms Associated with the Incubation Behavior

Upon contact with laid eggs, avians initiate incubation behavior and stop laying additional eggs. This phenomenon suggests that the productivity of laying hens in free-range facilities may decrease because of frequent contact with laid eggs. Here, we examined whether hens of a commercial breed exhibit incubation behavior in a free-range facility and whether egg productivity subsequently decreases. One-hour observations were performed twice weekly for 3 weeks, during which 9 of 129 hens (7.0%) exhibited incubation behavior (i.e., sitting on eggs) in the free-range facility and were defined as incubating hens. During 4 d of continuous behavioral observation, incubating and non-incubating hens laid the same number of eggs statistically (4.6 and 3.6, on average, respectively); however, incubating hens spent significantly more time on average incubating the eggs (2071.9 min) than did the non-incubating hens (20.9 min; P<0.05), indicating a clear behavioral difference. Subsequently, the incubation behavior and egg productivity of incubating hens and a Silkie Fowl breed hen, which is known to exhibit typical incubation behavior and cessation of laying, were continuously compared for 27 d. The average minutes spent incubating eggs during the observation period increased in both the incubating hens and Silkie Fowl hen and the total time was almost the same (18,088.5 and 23,092 min, respectively). However, the Silkie Fowl hen stopped laying on day 17 after laying 17 eggs, whereas the incubating hens continued laying throughout the observation period. Incubating hens laid an average of 24.5 eggs, indicating that some hens (at least those of the commercial breed used in our study) can continue laying while exhibiting incubation behavior. A single-nucleotide polymorphism associated with incubation behavior was detected on chromosome 4 through genome-wide association analysis.

Endocrine and genetic factors affecting egg laying performance in chickens: a review

1. Egg-laying performance reflects the overall reproductive performance of breeding hens. The genetic traits for egg-laying performance have low or medium heritability, and, depending on the period involved, usually ranges from 0.16 to 0.64. Egg-laying in chickens is regulated by a combination of environmental, endocrine and genetic factors. 2. The main endocrine factors that regulate egg-laying are gonadotropin-releasing hormone (GnRH), prolactin (PRL), follicle-stimulating hormone (FSH) and luteinising hormone (LH). 3. In the last three decades, many studies have explored this aspect at a molecular genetic level. Recent studies identified 31 reproductive hormone-based candidate genes that were significantly associated with egg-laying performance. With the development of genome-sequencing technology, 64 new candidate genes and 108 single nucleotide polymorphisms (SNPs) related to egg-laying performance have been found using genome-wide association studies (GWAS), providing novel insights into the molecular genetic mechanisms governing egg production. At the same time, microRNAs that regulate genes responsible for egg-laying in chickens were reviewed. 4. Research on endocrinological and genetic factors affecting egg-laying performance will greatly improve the reproductive performance of chickens and promote the protection, development, and utilisation of poultry. This review summarises studies on the endocrine and genetic factors of egg-laying performance in chickens from 1972 to 2019.

Genome-Wide Association Analysis Reveals Key Genes Responsible for Egg Production of Lion Head Goose

The lion head goose is one of the most important agricultural resources in China; however, its breeding process is relatively slow. In the present study, a genome-wide association study was performed for the genetic selection of egg production characters in lion head geese. We detected 30 single-nucleotide polymorphisms located in or near 30 genes that might be associated with egg production character, and quantitative real-time polymerase chain reaction was used to verify their expression level in lion head geese. The results showed that the expression levels of CRTC1 (encoding CREB-regulated transcription coactivator 1), FAAH2 (encoding fatty acid amide hydrolase 2), GPC3 (encoding glypican 3), and SERPINC1 (encoding serpin family C member 1) in high egg production population were significantly lower than those in the low egg production populations (*P < 0.05). The expression levels of CLPB (encoding caseinolytic peptidase B protein homolog), GNA12 (encoding guanine nucleotide-binding protein subunit alpha-12), and ZMAT5 (encoding zinc finger, matrin type 5) in the high egg production population were significantly higher than those in the low egg production populations (*P < 0.05). The expression of BMP4 (encoding bone morphogenetic protein 4), FRMPD3 (encoding FERM and PDZ domain containing 3), LIF (encoding leukemia inhibitory factor), and NFYC (encoding nuclear transcription factor Y subunit gamma) in the high egg production population were very significantly lower than those in the low egg production population (**P < 0.01). Our findings provide an insight into the economic traits of lion head goose. These candidate genes might be valuable for future breeding improvement.

Gene co-expression network analysis reveals key potential gene modules in utero-vaginal junction associated with duration of fertility trait of breeder hens

The number of days (DN) when hens lay fertile eggs as well as the number of fertile eggs (FN) were produced after a single artificial insemination (AI), including the two duration of fertility (DF) traits. Indeed, they are the key production performance that associates with the production cost of hatching egg when its determination the interval between successive artificial inseminations. However, the relevant genes response for regulating the DF has not been uncovered yet. Therefore, we performed a weighted gene co-expression network analysis (WGCNA) to investigate the insight into co-expression gene modules on DF process in hens. The total mRNA was extracted from the utero-vaginal junction (UVJ, with the sperm storage function in hen’s oviduct which is the biological basis for DF) of 20 hens with several levels of DF traits, and performed transcriptome sequences of mRNA. As a result, three co-expression gene modules were identified to be highly correlated with DF traits. Moreover, the expression changes of top 5 hub genes in each module with DF traits were further confirmed in other 20 hens by RT-PCR. These findings highlighted the co-expression modules and their affiliated genes as playing important roles in the regulation of DF traits.

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 for performance traits in chickens using genotype by sequencing approach

Performance traits are economically important and are targets for selection in breeding programs, especially in the poultry industry. To identify regions on the chicken genome associated with performance traits, different genomic approaches have been applied in the last years. The aim of this study was the application of CornellGBS approach (134,528 SNPs generated from a PstI restriction enzyme) on Genome-Wide Association Studies (GWAS) in an outbred F₂ chicken population. We have validated 91.7% of these 134,528 SNPs after imputation of missed genotypes. Out of those, 20 SNPs were associated with feed conversion, one was associated with body weight at 35 days of age (P < 7.86E-07) and 93 were suggestively associated with a variety of performance traits (P < 1.57E-05). The majority of these SNPs (86.2%) overlapped with previously mapped QTL for the same performance traits and some of the SNPs also showed novel potential QTL regions. The results obtained in this study suggests future searches for candidate genes and QTL refinements as well as potential use of the SNPs described here in breeding programs.

Genome-wide association study of 8 carcass traits in Jinghai Yellow chickens using specific-locus amplified fragment sequencing technology

Carcass traits are important to the commercial chicken industry, and understanding the genetics of these traits will be useful in the development of commercially viable varieties of chickens. We conducted a genome-wide association study based on 8 carcass trait phenotypes in a population of 400 43-week-old Jinghai Yellow chickens. Specific-locus amplified fragment sequencing technology was used to identify 90,961 single nucleotide polymorphisms (SNP) distributed among 29 chromosomes and the mitochondrial genome. SNP that were significantly associated with phenotypic traits were identified by a simple general linear model. Fifteen SNP attained genome-wide significance (P < 1.87E−6) and were associated with 5 of the 8 carcass traits; only one SNP was significantly associated with 2 traits (foot weight and wing weight). Twelve genes were associated with these 15 SNP. A region of chromosome 4 between 75.5 and 76.1 Mb was associated with carcass weight, foot weight, and wing weight. An 84-kb region on chromosome 3 (51.2 Mb) was associated with eviscerated weight and semi-eviscerated weight.

Population genomic analyses based on 1 million SNPs in commercial egg layers

Identifying signatures of selection can provide valuable insight about the genes or genomic regions that are or have been under selective pressure, which can lead to a better understanding of genotype-phenotype relationships. A common strategy for selection signature detection is to compare samples from several populations and search for genomic regions with outstanding genetic differentiation. Wright's fixation index, F_ST, is a useful index for evaluation of genetic differentiation between populations. The aim of this study was to detect selective signatures between different chicken groups based on SNP-wise F_ST calculation. A total of 96 individuals of three commercial layer breeds and 14 non-commercial fancy breeds were genotyped with three different 600K SNP-chips. After filtering a total of 1 million SNPs were available for F_ST calculation. Averages of F_ST values were calculated for overlapping windows. Comparisons of these were then conducted between commercial egg layers and non-commercial fancy breeds, as well as between white egg layers and brown egg layers. Comparing non-commercial and commercial breeds resulted in the detection of 630 selective signatures, while 656 selective signatures were detected in the comparison between the commercial egg-layer breeds. Annotation of selection signature regions revealed various genes corresponding to productions traits, for which layer breeds were selected. Among them were NCOA1, SREBF2 and RALGAPA1 associated with reproductive traits, broodiness and egg production. Furthermore, several of the detected genes were associated with growth and carcass traits, including POMC, PRKAB2, SPP1, IGF2, CAPN1, TGFb2 and IGFBP2. Our approach demonstrates that including different populations with a specific breeding history can provide a unique opportunity for a better understanding of farm animal selection.

Genomics of complex traits

The analysis of complex genetic traits, including mapping and identification of causative genes, has long been an enigma of genetic biology, whether in the animal sciences or in medical sciences. Traits of agricultural interest and traits of medical interest are often under the influence of both environmental factors and multiple genes, each with modest contributions to the total variance in the trait. Although the number of known mutations underlying complex traits is still relatively small, advances in genomics have greatly enhanced traditional pathways to their analysis and gene mining. The candidate gene approach, linkage analysis, and association studies are all significantly more powerful with recent advances in genome mapping, sequencing, and analysis of individual variation. Avenues to gene discovery are discussed with emphasis on genome wide association studies (GWAS) and the use of single nucleotide polymorphisms (SNPs) as revealed by increasingly powerful commercially available microarrays.