Whole-genome resequencing reveals aberrant autosomal SNPs affect chicken feathering rate

SAG-YOLO: A Lightweight Real-Time One-Day-Old Chick Gender Detection Method

Feather sexing, based on wing feather growth rate, is a widely used method for chick sex identification. However, it still relies on manual sorting, necessitating automation. This study proposes an improved SAG-YOLO method for chick sex detection. Firstly, the model reduces both parameter size and computational complexity by replacing the original feature extraction with the StarNet lightweight Backbone. Next, the Additive Convolutional Gated Linear Unit (Additive CGLU) module, incorporated in the Neck section, enhances multi-scale feature interaction, improving detail capture while maintaining efficiency. Furthermore, the Group Normalization Head (GN Head) decreases parameters and computational overhead while boosting generalization and detection efficiency. Experimental results demonstrate that SAG-YOLO achieves a precision (P) of 90.5%, recall (R) of 90.7%, and mean average precision (mAP) of 97.0%, outperforming YOLO v10n by 1.3%, 2.6%, and 1.5%, respectively. Model parameters and floating-point operations are reduced by 0.8633 M and 2.0 GFLOPs, with a 0.2 ms faster GPU inference speed. In video stream detection, the model achieves 100% accuracy for female chicks and 96.25% accuracy for male chicks, demonstrating strong performance under motion blur and feature fuzziness. The improved model exhibits robust generalization, providing a practical solution for the intelligent sex sorting of day-old chicks.

Identification and validation of novel breed-specific biomarker for the purpose of village chicken authentication using genomics approaches

Local village chicken, or "Ayam kampung" as it's known in Malaysia, is considered a premium chicken breed with a higher price than other chicken breeds. As a result of their comparable appearances and sizes, colored broiler chickens are often sold as village chickens, which is a form of food fraud that can result in a 3- to 4-fold rise in profit. Therefore, developing a breed-specific authentication method is crucial for preventing food fraud in the poultry industry. This study aims to investigate the genetic diversity of village chickens from other commercial chicken breed populations available in the market (broiler [Cobb], colored broiler [Hubbard], and layer [DeKalb]) to identify breed-specific DNA fragments as biomarkers for village chicken authentication. The Whole-genome sequencing and mutation calling of 12 chickens (3 chickens/breed) led to the identification of a total of 73,454,654 single nucleotide polymorphisms (SNP) and 8,762,338 insertion and deletions (InDel) variants, with more variants detected in the village chicken population (6,346,704 SNPs; 752,408 InDels) compared to commercial breeds. Therefore, this study revealed that village chickens were more genetically variable compared to other breeds in Malaysia. Furthermore, the breed-specific genomic region located on chromosome 1 (1:84,405,652) harboring SNP (C-T) with high discrimination power was discovered and validated which can be considered as a novel breed-specific biomarker to develop a method for accurate authentication of village chickens in Malaysia. This authentication method offers potentialw applications in the chicken industry and food safety.

Identification of key modules and hub genes involved in regulating the feather follicle development of Wannan chickens using WGCNA

Carcass appearance is important economic trait, which affects customers in making purchase decisions. Both density and diameter of feather follicles are two important indicators of carcass appearance. However, the regulatory network and key genes be involved in feather follicle development remain poorly understood. To identify key genes and modules that involved in feather follicle development in chickens, 16 transcriptome datasets of Wannan chickens skin tissue (3 birds at the E9, E11, and E14, respectively, and 7 birds at the 12W) were used for weighted gene co-expression network analysis (WGCNA) analysis, and 12 skin tissue samples (3 birds for each stage) were selected for DEGs analysis. A total of 5,025, 2,337, and 10,623 DEGs were identified in 3 comparison groups, including the E9 vs. E11, the E11 vs. E14, and the E14 vs. 12W. Additionally, 31 co-expression gene modules were identified by WGCNA and the dark-orange, cyan, and blue module were found to be significantly associated with feather follicle development (p < 0.01). In total, 92,898 and 8,448 hub genes were obtained in the dark-orange, cyan, and blue modules, respectively. We focused on the cyan and blue modules, as 6 and 336 hub genes of these modules were identified to overlap with the DEGs of the three comparison groups, respectively. The 6 overlapped genes such as LAMC2, COL6A3, and COL6A2 etc., were over-represented in 12 categories such as focal adhesion and ECM-receptor interaction signaling pathway. Among the 336 genes that overlapped between the blue module and different DEGs comparison groups several genes including WNT7A and WNT9B were enriched in Wnt and ECM-receptor interaction signaling pathway. These results suggested that the LAMC2, COL6A3, COL6A2, WNT7A, and WNT9B genes may play a crucial role in the regulation of feather follicle development in Wannan chickens. Our results provided a reference for the molecular regulatory network and key genes in the development of feather follicles and contribute to molecular breeding for carcass appearance traits in chickens.

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-genome sequencing identifies potential candidate genes for egg production traits in laying ducks (Anas platyrhynchos)

Egg production traits are economically important in laying ducks. Genetic molecular mechanisms and candidate genes underlying these traits remain unclear. In this study, whole genome variants were identified through whole-genome resequencing using three high-egg producing (HEN) and three low-egg producing (LEN) laying ducks. The gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways for the genes of common differential variants between HEN and LEN ducks were determined. Frizzled class receptor 6 (FZD6) was further genotyped using the Sequenom MassARRAY iPLEX platform. The association of FZD6 gene polymorphisms with 73 egg production and weight traits in 329 female ducks were estimated. A total of 65,535 single nucleotide polymorphisms (SNPs) and 4,702 indels were identified across the genome. Fourteen GO terms and 14 KEGG pathways were determined for the genes of common differential variants, including MAPK signaling, Wnt signaling, melanogenesis and calcium signaling pathways, which are key functional pathways for poultry egg production reported in previous reports. Further analysis showed that 27 SNPs of FZD6 were associated with three early egg production of duck and egg weight traits, including egg production at 17 weeks (EP17), 18 weeks (EP18) and 19 weeks (EP19) and egg weight at 59 weeks (EW59). The FZD6 should be considered a novel candidate gene for egg production traits in laying ducks.

RNA sequencing reveals lncRNA-mediated non-mendelian inheritance of feather growth change in chickens

Background

Long non-coding RNAs (lncRNAs) play an essential role in biological processes. However, the expression patterns of lncRNAs that regulate the non-Mendelian inheritance feather phenotypes remain unknown.

Objective

This study aimed to compare the expression profiles of lncRNAs in the follicles of the late-feathering cocks (LC) and late-feathering hens (LH) that followed genetic rules and the early-feathering hen (EH) and early-feathering cock (EC) that did not conform to the genetic laws.

Methods

We performed RNA sequencing and investigated the differentially expressed lncRNAs (DElncRNAs) between the early- and late-feathering chickens, which function by cis-acting or participate in the competing endogenous RNA (ceRNA) network.

Results

A total of 53 upregulated and 43 downregulated lncRNAs were identified in EC vs. LC, and 58 upregulated and 109 downregulated lncRNAs were identified in EH vs. LH. The target mRNAs regulated by lncRNAs in cis were enriched in the pentose phosphate pathway, TGF-β signaling pathway and Jak-STAT signaling pathway in EC vs. LC and were associated with the TGF-β signaling pathway, Wnt signaling pathway, p53 signaling pathway and Jak-STAT signaling pathway in EH vs. LH. In addition, the lncRNA-mediated ceRNA regulatory pathways of hair follicle formation were mainly enriched in the TGF-β signaling pathway, Wnt signaling pathway, melanogenesis, and calcium signaling pathways. The levels of ENSGALG00000047626 were significantly higher in the late-feathering chickens than in the early-feathering chickens, which regulated the expression of SSTR2 by gga-miR-1649-5p.

Conclusion

This study provides a novel molecular mechanism of lncRNA’s response to the feather rate that does not conform to the genetic laws in chickens.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13258-022-01304-2.

Transcriptional Characteristics Showed That miR-144-y/FOXO3 Participates in Embryonic Skin and Feather Follicle Development in Zhedong White Goose

Simple Summary

Feather is one of the most valuable and economical products in goose farming and plays a crucial physiological role in birds. For avian biology and the poultry industry, it is essential to comprehend and regulate how skin and feather follicles develop during embryogenesis. This study showed that several key regulatory genes (FOXO3, CTGF, and PTCH1, among others) and miRNAs (miR-144-y) participated in the developmental process of the skin and feather follicles in Zhedong white goose. Our findings are particularly important because they will serve as a valuable resource for upcoming studies on down feathers in agricultural economic growth regarding complex molecular mechanisms and breeding techniques.

Abstract

Skin and feather follicle development are essential processes for goose embryonic growth. Transcriptome and next-generation sequencing (NGS) network analyses were performed to improve the genome of Zhedong White goose and discover the critical genes, miRNAs, and pathways involved in goose skin and feather follicle morphogenesis. Sequencing output generated 6,002,591,668 to 8,675,720,319 clean reads from fifteen libraries. There were 1234, 3024, 4416, and 5326 different genes showing differential expression in four stages, E10 vs. E13, E10 vs. E18, E10 vs. E23, and E10 vs. E28, respectively. The differentially expressed genes (DEGs) were found to be implicated in multiple biological processes and pathways associated with feather growth and development, such as the Wnt signaling pathway, cell adhesion molecules, ECM–receptor interaction signaling pathways, and cell cycle and DNA replication pathways, according to functional analysis. In total, 8276 DEGs were assembled into twenty gene profiles with diverse expression patterns. The reliability of transcriptome results was verified by real-time quantitative PCR by selecting seven DEGs and five miRNAs. The localization of forkhead box O3 (FOXO3), connective tissue growth factor (CTGF), protein parched homolog1 (PTCH1), and miR-144-y by in situ hybridization showed spatial-temporal expression patterns and that FOXO3 and miR-144-y have an antagonistic targeting relationship. The correlation coefficient of FOXO3 and miR-144-y was -0.948, showing a strong negative correlation. Dual-luciferase reporter assay results demonstrated that miR-144-y could bind to the expected location to suppress the expression of FOXO3, which supports that there is a targeting relationship between them. The detections in this report will provide critical insight into the complex molecular mechanisms and breeding practices underlying the developmental characteristics of skin and feather follicles in Zhedong white geese.