The Muscovy duck (Cairina moschata) is an excellent lean-type poultry species characterized by large body weight, rapid growth, high lean meat yield, good liver production performance, and high feed conversion efficiency. It plays an important role in modern poultry industry. However, the quality of the currently available Muscovy duck genome remains limited. Here, we report the de novo sequencing and assembly of the Muscovy duck genome using PacBio and Hi-C technologies. The total length of the genome assembly was 1270.04 Mb, the contig N50 was 6.56 Mb, and the scaffold N50 was 77.04 Mb and it was composed of 39 chromosomes. BUSCO evaluation showed that 95.2% of conserved genes were completely assembled in the Muscovy duck genome, indicating high completeness of the assembly results. The genome annotation results showed that the proportion of repetitive sequences was 22.14%, 16,901 coding genes were predicted, and 93.4% of the genes were functionally annotated. Comparative genomic analysis revealed that expanded gene families were associated with immune-related pathways in Cairina moschata. Cairina moschata was closely related to Anas platyrhynchos and Aythya fuligula, both of which belong to the family Anatidae. These results provide valuable resources for poultry genomic breeding programs.

The characterization of genetic architecture and the optimization of genomic prediction are pivotal for the genetic improvement of complex traits in poultry. In this study, we investigated the genetic basis of 15 growth and carcass traits in an F2 chicken population (n = 877) using high-depth whole-genome sequencing with an average coverage of 31.2 × . By implementing an ensemble strategy involving four independent callers, we identified 35,924 high-confidence structural variations (SVs), with deletions being the most prevalent type. Combining SNPs and SVs enhanced genomic heritability for 14 out of 15 traits compared to SNPs alone. SNP-based GWAS corroborated well-known genes, including the prominent QTL cluster on chromosome 1, the NCAPG-LCORL locus on chromosome 4, and IGF2BP1 on chromosome 27. Notably, SV-based analysis unveiled additional candidate genes, such as ZNF385D, MYH10, and MOB1B. To gain functional insights, eQTL-GWAS colocalization analysis integrating SNP-based GWAS signals with tissue-specific eQTL data identified significant colocalization signals for ITM2B in brain tissue, potentially implicating excitatory synaptic transmission, and TRIM13 in blood, potentially implicating inflammatory and immune regulation. To optimize genomic breeding value estimation through the effective utilization of multi-type markers, we developed GPDLBP, a hybrid deep learning framework that integrates locally connected networks to capture SV effects with the GBLUP model for SNP effects. Compared with the traditional SNP-only model, GPDLBP improved prediction accuracy for most traits, with gains exceeding 2% for BW21 (body weight at 21 days of age), BW49 (body weight at 49 days of age), EW (eviscerated weight), LMW (leg muscle weight), and AFW (abdominal fat weight); for example, prediction accuracy increased from 0.512 to 0.532 for BW49 and from 0.471 to 0.491 for EW. These findings show that SVs complement SNPs in both genetic dissection and genomic prediction of economically important traits in chickens. The integration of multiple variant types provides a practical strategy for accelerating precision breeding in high-depth sequencing-based poultry programs.

As the first sequenced non-mammalian amniote, the chicken (Gallus gallus) has served as a major source of cost-effective and protein-enriched foods since domestication. However, how structural variations (SVs) affect 3D genome reorganization to influence domestication and production traits remains unclear in chickens. Here, fifteen de novo chromosome-level genome assemblies are newly generated, along with high-throughput chromosome conformation capture (Hi-C), ATAC and RNA sequencing data. By integrating 13 published assemblies, the first pan-3D genome resource is constructed, spanning genes, SVs, and chromatin architectures, to investigate the dynamic characteristics of the 3D genome at different levels and the roles of SVs in the conservation and reorganization of chromatin architectures. Furthermore, candidate SVs and their linked genes are identified for domestication and production traits based on 1,735 resequencing accessions. Notably, the 240-bp and 81-bp SVs in the TSHR and DIO2 genes are considered the key targets in artificial selection for seasonal reproduction, and a 266-bp deletion upstream of the KLF3 gene affects carcass performance by rewriting the chromatin loop interaction network. Finally, SVs significantly improve the predictive accuracy in genomic selection models. Collectively, this study presents a comprehensive pan-3D resource to advance functional genomic research and breeding practice for the community.

Environmental temperature significantly influences the evolutionary adaptation of poultry, while abdominal fat deposition represents a crucial economic trait affecting feed conversion efficiency and carcass quality. However, reports on the genetic mechanisms governing their co-evolutionary trade-offs remain scarce. This study employed whole-genome resequencing data from 469 chickens across 31 varieties. Through comparative analyses of heat- versus cold-adapted groups and high- versus low-fat groups, structural variations (SVs) were utilized as genetic markers. Selection signatures were identified via the population differentiation index (FST) and nucleotide diversity ratio (π ratio). We identified 103 overlapping genes located within significantly differentiated SVs at the intersection of temperature adaptation and fat deposition. Pathway analysis revealed significant enrichment in the thyroid hormone signaling pathway, pinpointing MED17 as a key selection target. Further validation via PCR genotyping in the heat-tolerant Wenchang chicken revealed that individuals harboring the MED17 mutation exhibited significantly higher abdominal fat deposition than those without. These results suggest that MED17 is associated with fat deposition in heat-tolerant Wenchang chickens, serving as a potential candidate gene for this trait, providing robust molecular markers for breeding novel strains with both thermotolerance and superior carcass traits.

Qingyuan partridge chickens are valued as a high-quality Indigenous broiler breed in China, characterized by their distinctive and superior meat flavor. To systematically investigate the flavor precursor basis and molecular signatures underlying this quality, we integrated volatile metabolomics, metabolomics, lipidomics, and RNA-seq analyses across five anatomical parts: breast muscle ( BM , Pectoralis major), abdominal muscle ( AM , External abdominal oblique), back muscle ( BAM , Latissimus dorsi), thigh muscle ( TM , Tensor fasciae latae), and drumstick muscle ( DM , Gastrocnemius). Metabolomics identified linoelaidic acid and malic acid, among others, as potential contributing substances of muscle parts. Lipidomics revealed distinct abundances of specific lipid species, including PE (20:4_18:0) and PS (18:0_21:0). RNA-seq revealed that differentially expressed genes were enriched in multiple flavor-associated pathways. Integrated multi-omics analysis further identified 83 metabolites, 97 lipids, and 1 volatile compound with strong interactive roles in defining the flavor precursor landscape, and notably, benzaldehyde emerged as a critical volatile marker for part discrimination. In summary, this multi-omics investigation uncovered potential factors of the flavor profile in Qingyuan partridge chickens, providing a reference for leveraging regional chicken specialties.

Accurate identification of indigenous chicken breeds is fundamental for the conservation and utilization of poultry genetic resources. To enable reliable identification of Wannan Yellow-feathered (WN) chickens, we developed a genomic framework based on whole-genome resequencing data. Comparative analyses of WN (n = 10) and 12 reference populations (n = 60) revealed clear population structure and identified 119 candidate selective regions containing 34,036 SNPs and 41 genes related to metabolism, reproduction, muscle development and behavior. Using these loci, a Random Forest model was constructed to prioritize informative markers, resulting in a compact panel of 41 SNPs. Validation on an independent cohort (n = 40) achieved 92.5% accuracy and an AUC of 0.995. Our results demonstrate that reliable breed identification requires integration of multiple frequency-variable loci rather than reliance on single markers. This study provides both biological insights into WN genetic architecture and a practical tool for breed authentication and conservation.

The chicken is a valuable model for understanding fundamental biology and vertebrate evolution and is a major global source of nutrient-dense and lean protein. Despite being the first non-mammalian amniote to have its genome sequenced, a systematic characterization of functional variation on the chicken genome remains lacking. Here, we integrated bulk RNA sequencing (RNA-seq) data from 7,015 samples, single-cell RNA-seq data from 127,598 cells and 2,869 whole-genome sequences to present a pilot atlas of regulatory variants across 28 chicken tissues. This atlas reveals millions of regulatory effects on primary expression (protein-coding genes, long non-coding RNA and exons) and post-transcriptional modifications (alternative splicing and 3'-untranslated region alternative polyadenylation). We highlighted distinct molecular mechanisms underlying these regulatory variants, their context-dependent behavior and their utility in interpreting genome-wide associations for 39 chicken complex traits. Finally, our comparative analyses of gene regulation between chickens and mammals demonstrate how this resource can facilitate cross-species gene mapping of complex traits.

The poultry industry is one of the fastest-growing subsectors in agriculture, serving as a primary source of protein for the increasing global population. However, chickens carry many fatal diseases that compromise their welfare and negatively affect productivity. Among these, coccidiosis, an intestinal disease caused by Eimeria protozoan parasites, affects multiple animal species and represents a major threat to the poultry industry. Eimeria parasites invade the host cell through a distinctive process, depending on gliding motility, and require a transmembrane link between the host cell and parasite cytoskeleton. Each species invades intestinal epithelial cells in a specific gut region, leading to varying tissue damage and morbidity levels. Understanding the preliminary host-parasite interactions is crucial to revealing Eimeria species' conduct and cellular immune responses mediating the primary and secondary coccidian infection, which can inform the development of effective immunological strategies. The interaction between Eimeria invasion proteins and intestinal epithelial cells provokes a moderate immune response marked by elevated IFN-γ and IL-10 production in chickens. In this review, we highlight recent breakthroughs in understanding the Eimeria parasites that affect the host intestinal tract, emphasizing parasite invasion mechanisms, transmission dynamics, host immune responses, coccidian control mechanisms, and the interaction between host microbiota and coccidia. In conclusion, advancing our understanding of Eimeria invasion mechanisms and coccidia control requires a complex approach that combines cutting-edge molecular insights with innovative therapeutic strategies.

The intestinal microbiome is essential in regulating host muscle growth and development. Antibiotic treatment is commonly used to model dysbiosis of the intestinal microbiota, yet limited research addresses the relationship between gut microbes and muscle growth in yellow-feathered broilers. In this study, Xinghua chickens were administered broad-spectrum antibiotics for eight weeks to induce gut microbiome suppression. We investigated the relationships between the gut microbiome and muscle growth using 16S rRNA sequencing and transcriptomic analysis. Results indicated that antibiotic treatment significantly reduced body weight, dressed weight, eviscerated weight, and breast and leg muscle weight. Microbial diversity and richness in the duodenum, jejunum, ileum, and cecum were significantly decreased. The relative abundances of Firmicutes, Actinobacteria, and Bacteroidetes declined, while Proteobacteria increased. This microbial imbalance led to 298 differentially expressed genes (DEGs) in muscle tissue, of which 67 down-regulated genes were enriched in skeletal muscle development, including MYF6, MYBPC1 and METTL21C genes essential for muscle development. The DEGs were primarily involved in the MAPK signaling pathway, calcium signaling pathway, ECM-receptor interaction, actin cytoskeleton regulation, and nitrogen metabolism. Correlation analysis showed that dysregulation of the cecal microbiome had the most substantial effect on muscle growth and development. Furthermore, intestinal microbiome dysregulation reduced DNMT3b and METTL21C mRNA expression in muscle tissue, lowered overall DNA methylation and SAM levels, and induced methylation changes that impacted skeletal muscle development. This study demonstrates that gut microbiota influence DNA methylation in muscle tissue, thereby associated with muscle growth and development.

Improving the quality of chicken meat while maintaining production efficiency is a challenging issue in poultry science. The current study was conducted to explore the effects of two feeding patterns (standard feed and omnivorous feed) on growth performance, slaughter performance, and meat quality traits of Xinghua (XH) chicken (indigenous chicken) and White Recessive Rock (WRR) chicken (commercial broiler). Feed consumption and body weight were determined weekly over 5 weeks, and meat quality traits with respect to breed and diet were evaluated. Mass spectrometry analyses facilitated the metabolomic profiling of breast muscle to reveal central metabolites associated with flavor formation. The metabolism of breast muscle was significantly altered by omnivorous feeding, which resulted in higher betaine concentrations and lower levels of creatine, acylcarnitines, and intermediates of amino acid biosynthesis. Breed-specific metabolic responses were noted: glycerophospholipid pathways were disrupted in WRR chickens, which had significantly lower levels of trimethylphosphate and triglycerides. Different flavor and texture profiles were correlated with these metabolic changes, with XH chickens exhibiting better flavor characteristics. Particularly for heritage breeds, this work offers practical advice for maximizing poultry diets while maintaining a balance between flavor enhancement and production efficiency.

Chicken meat is an essential source of high-quality animal protein, mainly derived from slow-growth chicken (SC) and fast-growth chicken (FC) breeds. Skeletal muscle is a highly adaptable tissue that is influenced by breed differences and the gut microbiome. Investigation whether remodeling the gut microbiota by fecal microbiota transplantation (FMT) improves chicken growth is an interesting question. We compared the gut microbial composition of eight breeds of SC (Xinghua chicken, Yangshan chicken, Zhongshan Salan chicken, Qingyuan Partridge chicken, Huiyang Bearded chicken and Huaixiang chicken) and FC (Xiaobai chicken and White rock chicken). Fecal microbiota from donor FC (Xiaobai chickens) with superior growth performance were transferred to SC (Xinghua chickens). The effects of FMT on growth performance, metabolic profile and gut microbiome of recipient chickens were evaluated. We found significant differences in gut microbial composition, with a higher abundance of Bacteroidetes in SC and a higher abundance of Firmicutes in FC. Xiaobai chickens with better growth performance and abundant Lactobacillus, and FMT significantly enhanced growth performance, the expression of mRNA (MYOG, MYF5, MYF6 and IGF1) related to breast and leg muscle development and improved the villus/crypt ratio in the jejunum. FMT altered the microbiota in the duodenum, jejunum, and ileum, increased Lactobacillus abundance, decreased the relative mRNA expression of the intestinal inflammatory factors (IL-1β, IL-6 and TNF-α), increased glutamine levels in the host, including in muscle tissues and intestinal contents, and Spearman correlation analysis indicated that the relative abundance of Lactobacillus was positively correlated with glutamine levels. Additionally, antibiotic treatment reduces glutamine levels in the intestines, blood, and muscle tissues of chickens. Glutamine can increase the expression of cyclinD1, cyclinD2, cyclinB2, MYOG, MYF5, MYF6 and IGF1 mRNA to promote chicken myoblasts proliferation and differentiation. This study found that the SC and FC gut microbes were significantly different, and the FC chicken gut microbes were able to reshape the FC gut microbiota through FMT, i.e., higher Lactobacillus, promoted chicken myoblasts proliferation and differentiation and growth performance by increasing glutamine levels.

In the fierce market competition, high-quality chicken products often stand out. There are significant differences in meat quality between yellow and white feathered chickens. However, the underlying mechanisms that lead to the differences in their meat quality remain unclear. Single nucleotide polymorphisms (SNP) are effective molecular markers that can be utilized in marker-assisted breeding programs targeting chicken meat quality traits. Our research findings indicated that the bloodline of yellow-feathered chickens can significantly alter the meat quality traits of chickens, especially in terms of the shear force and meat color of the breast muscle. Additionally, through metabolomic, lipidomic, and RNA-seq, we identified differentially expressed metabolites, lipids, and genes that influence meat quality. Furthermore, we discovered a key gene, the purinergic receptor P2 × 5 (P2RX5), which significantly contributes to meat quality traits. We identified five SNP sites within the P2RX5 gene and conducted genotyping. Three of these SNP sites were found to be significantly associated with meat quality traits in chickens, such as the a*value and cooking loss. These results indicated that our findings provide potential molecular markers for changing meat quality traits in chickens. However, due to our small sample size and the absence of testing on males, the generalizability of the results may be insufficient.

Chickens are a crucial source of protein for humans and a popular model animal for bird research. Despite the emergence of imputation as a reliable genotyping strategy for large populations, the lack of a high-quality chicken reference panel has hindered progress in chicken genome research. To address this, here we introduce the first phase of the 100K Global Chicken Reference Panel (100K GCRP). Currently, two panels are available: a comprehensive mix panel (CMP) for domestication diversity research and a commercial breed panel (CBP) for breeding broilers specifically. Evaluation of genotype imputation quality showed that CMP had the highest imputation accuracy compared to imputation using existing chicken panels in Animal-SNPAtlas and Animal Genotype Imputation Database (AGIDB), whereas CBP performed stably in the imputation of commercial populations. Additionally, we found that genome-wide association studies using GCRP-imputed data, whether on simulated or real phenotypes, exhibited greater statistical power. In conclusion, our study indicates that the GCRP effectively fills the gap in high-quality reference panels for chickens, providing an effective imputation platform for future genetic and breeding research. The project includes 11,951 samples and provides services for various applications on its website at http://farmrefpanel.com/GCRP/#/.

Small white-feather chickens (SWFC) have become popular as a hybrid strain recently. Shank color is a notable economic trait in this strain. Despite numerous studies on the green shank trait from both physiological and genetic perspectives, research focusing specifically on the green shank trait in hybrid chickens (HC) remains limited. In this study, to investigate the genetic mechanisms and molecular basis of the green shank trait in HC, we created a population by intercrossing white-feathered and yellow-feathered broilers, both with yellow shanks. Physiological analysis confirmed that melanin deposition in the shank dermis is the primary cause of the green shank trait in HC. By combining genome-wide association studies (GWAS) and population genomics analysis, the 83.20-85.68 Mb region on the Z chromosome was identified as a candidate region for the green shank trait in HC. Transcriptome sequencing revealed differentially expressed genes (DEGs) between green shank and yellow shank individuals, with MTAP and CDKN1A identified as candidate genes in the genomic region associated with the green shank trait. Notably, the green shank trait includes a light green phenotype. Our study is the first to identify genes associated with different color depths of the green shank. The candidate genes influence both the biosynthesis and deposition of pigments.

Circular RNAs (circRNAs) are generally considered a new class of non-coding RNA (ncRNA) that frequently appears in the eukaryotic transcriptome. In principle, circRNAs may encode proteins, as some of them are generated from exons and possess elements for internal ribosome entry. Circular RNAs have the potential to serve as an unexplored reservoir for the generation of novel proteins, yet the identification of coding-circRNAs is a daunting task. In this study, we developed a specialized strategy for the discovery of coding-circRNA by combining RNA sequencing, ribosome profiling, and mass spectrometry to find a multitude of circRNAs translated in vivo. A total of 40,084 circRNAs were found in chicken myoblasts and myotubes, and 15,332 circRNAs had a predicted open reading frame (ORF). Via ribosome footprints, we discovered that a group of circRNAs (4,069) was associated with translating ribosomes (ribo-circRNAs). Moreover, a total of 3,927 circRNAs with an infinite ORF were discovered, and 860 of them were associated with translating ribosome (ribo-no-stop-codon circRNAs). Mass spectrometry found 5 specific peptides spectra spanning a back-splice junction of circRNAs. circSIK2, one of the ribo-circRNAs, could be methylated by METTL3 and translated into SIK2-176aa, thus promoting the proliferation and differentiation of myoblasts and muscle hypertrophy. Our results suggest that many circRNAs were translating during chicken myogenesis, and METTL3 could enhance the translation of circSIK2. To the best of our knowledge, only two circRNAs translation events have been reported to be mediated by m6A. Our research would represent the third such event, and the first documented instance of a translatable circRNA in poultry.

Introduction Domestic chickens primarily descended from the wild red junglefowl, play a crucial role in global egg and meat production. China hosts diverse indigenous chicken populations that have adapted to various environmental conditions, including high-altitude with hypoxic and ultraviolet radiation stress. Method We analyzed whole-genome sequences of 118 birds from five Indigenous Chinese chicken populations and 295 chicken genomes from publicly available databases to identify genomic diversity, admixture, and selection signatures of chickens adapted to high-altitude environments. Selection signatures were identified using nucleotide diversity (π), Tajima’s D, XPEHH, and XP-CLR, selection scan methods. Results We observed a reduction in genetic diversity and historical declines in effective population size in high-altitude chicken, suggesting ongoing selection pressures shaping these populations. Selection scans identified nine genomic regions under strong positive selection, enriched for genes associated with hypoxia and ultraviolet radiation. Notably, five genes (TPK1, BAZ2B, MARCHF7, LLGL2, and RCAN3) were repeatedly detected across multiple selection signature analyses. RNA-seq analysis further confirmed the differential expression of these genes in the lung and heart tissues of chickens adapted to high and low altitudes, reinforcing their role in physiological adaptation to hypoxic environments. Altitude adaptation is driven by the selection of genes involved in oxygen metabolism, cellular stress response, and energy regulation. Conclusion Our study provides compelling genetic evidence for differentiation between high and low and high-altitude Chinese chicken populations. These findings also ensure our understanding of local adaptation in poultry and establish a genomic framework for breeding strategies to improve environmental resilience to altitude-related stressors.

Excessive abdominal fat in broilers not only reduces feed efficiency and increases processing costs but also raises environmental concerns. This pathological overaccumulation results from complex metabolic dysregulation across multiple organs. While current research largely centers on adipogenesis within adipose tissue, a comprehensive understanding of the cross-organ regulatory factors influencing this process remains elusive. Here, we employed a high-fat diet (HFD) model and multi-omics approaches to investigate cross-organ regulatory mechanisms underlying abdominal fat deposition in broilers. Our results demonstrated that HFD not only promoted fat accumulation but also altered meat quality traits. Through 16S rRNA amplicon sequencing, we identified significant gut microbiota dysbiosis in HFD-fed chickens, manifested by an increased abundance of Lactobacillus and a decreased abundance of Enterococcus. However, jejunal microbiota transplantation from HFD donors did not induce abdominal fat deposition in recipient chickens. Metabolomic profiling revealed that HFD elevated the level of succinic acid, a metabolite positively correlated with Lactobacillus abundance and potentially generated by Lactobacillus. This increase in succinic acid (SA) further triggered metabolic inflammation response in both jejunal tissue and serum. In vivo validation established succinic acid as a key inflammatory mediator facilitating HFD-induced cross-organ communication between the jejunum and abdominal adipose tissue, enhancing intestinal lipid uptake and subsequent abdominal fat deposition. Bulk and single-nucleus RNA sequencing (snRNA-seq) revealed that HFD induced macrophage population expansion and intensified adipocyte-macrophage crosstalk. Adipocyte-macrophage co-culture systems further elucidated that macrophages are an indispensable factor in succinic acid-induced fat deposition. This study delineates a succinic acid-driven "gut-fat axis" governing abdominal fat deposition in broilers, integrating gut microbiota dysbiosis and macrophage-mediated inflammatory adipogenesis. By identifying succinic acid as a cross-organ signaling molecule that enhances lipid absorption and activates macrophage-dependent adipogenesis, we establish systemic metabolic-immune crosstalk as a pivotal regulatory mechanism. These findings redefine fat deposition as a process extending beyond adipose-centric models, advancing multi-omics-guided strategies for sustainable poultry production.

Hyperpigmentation of the visceral peritoneum (HVP) is a pigmentation abnormality in chickens that adversely affects carcass appearance, consumer acceptance, and poultry production. However, the genetic basis of HVP remains unclear. To investigate the causes and regulatory mechanisms of HVP, we employed high-performance liquid chromatography (HPLC), bulk RNA sequencing (RNA-seq), qRT-PCR, Western blotting, and siRNA interference. Additionally, single-cell RNA sequencing (scRNA-seq) was used to examine gene expression at the cellular level. Anatomical examination and hematoxylin and eosin (HE) staining revealed melanin deposition in the peritoneum of HVP-affected chickens. Spectrophotometric analysis at 500 nm showed significantly higher absorbance in the HVP group (p < 0.05), which correlated with the degree of pigmentation. HPLC confirmed the pigmentation as eumelanin, based on the pyrrole-2,3,5-tricarboxylic acid (PTCA) peak. RNA-seq identified 61 differentially expressed genes. Functional studies showed that dopachrome tautomerase (DCT) overexpression, combined with L-tyrosine (L-Tyr) supplementation, significantly increased melanin content (p < 0.05) and promoted melanocyte proliferation. In contrast, DCT silencing reduced melanin secretion and inhibited cell growth. ScRNA-seq analysis of over 9700 high-quality cells identified distinct melanocyte clusters, with DCT expression approximately 2.5-fold higher in melanocytes from the HVP group compared to the normal group. Furthermore, a DCT polymorphism (g.147917398 C > T) was identified as a potential marker for genetic selection (p-values = 0.033). These findings demonstrate that HVP is driven by DCT overexpression and excessive eumelanin deposition. DCT could serve as a molecular marker for genomic selection to improve poultry carcass quality and reduce economic losses in the poultry industry.

The earlobe color trait is a significant characteristic in chickens, exhibiting notable genetic diversity. Elucidating the mechanism of inheritance of the earlobe color trait would be beneficial in promoting genetic improvement with this phenotypic trait and would help in breed identification. Current research mainly hypothesizes that pigment deposition may underlie the phenotypic differences in earlobe color, with few studies exploring the molecular genetic mechanisms from the perspective of metabolomic differences. In this study, we selected Qingyuan Partridge chicken exhibiting both red and white earlobe traits as our subjects. By combining histological, metabolomic, and genomic approaches, we aim to identify the primary factors governing the formation of these two earlobe colorations. Histological analysis of frozen sections from two types of earlobe tissue revealed that red earlobe formation is correlated with capillary density. Untargeted metabolomic sequencing analysis identified 61 high-abundance differential metabolites, Whole-genome FST Study and Case-Control Genome-Wide Association Study, identified 93 significant overlapping SNPs and annotated to 70 relevant candidate genes. It is particularly noteworthy that the differentially expressed metabolites and candidate genes were both significantly enriched in the sphingolipid metabolism pathway. Among them, C16-ceramide in the sphingolipid metabolic pathway is a key metabolite affecting the formation of white earlobes, the genes SGMS1, SGPP2, and SMPD4 contribute to the formation of white earlobes by regulating the metabolism and deposition of relevant lipids in the sphingolipid metabolic pathway. Our research provides new insights into the molecular mechanisms behind poultry earlobe color traits and holds significant implications for the selective breeding of characteristic traits in Qingyuan Partridge chickens, and its application to production can accelerate the efficiency of earlobe color improvement.

G-quadruplexes (G4s) are distinct nucleic acid secondary structures formed by guanine-rich sequences in both DNA and RNA. These structures readily form and fulfill diverse biological functions. The structural diversity of G4s is influenced by several factors, including their strand orientation, glycosidic bond angles, and loop configurations. G4s are widely distributed in functionally significant genomic regions, including telomeres, promoter regions, exons, 5' untranslated region (5' UTR), intron region, and 3' untranslated region (3' UTR). G4s are implicated in critical biological processes, including telomere elongation, DNA replication, DNA damage repair, transcription, translation, and epigenetic regulation. This overview offers a comprehensive analysis of the determinants of G4 structure and their impact on associated biological processes. Briefly, it describes the effects of G4s on cancers, viruses, and other pathogenic substances. This overview aims to contribute new ideas for the regulation of related mechanisms and their potential impact on the treatment strategies of related diseases. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.