Genome-wide Analyses Identifies Known and New Markers Responsible of Chicken Plumage Color

Genome-Wide Scans for Selection Signatures in Haimen Goats Reveal Candidate Genes Associated with Growth Traits

Understanding the genetic characteristics of indigenous goat breeds is vital for their conservation and breeding. Haimen goats, native to China's Yangtze River Delta, possess distinctive traits such as white hair, moderate growth rate, high-quality meat, and small body size. However, knowledge regarding the genetic structure and germplasm characteristics of Haimen goats remains limited. In this study, we performed 20× whole-genome resequencing of 90 goats (60 Haimen goats and 30 Boer goats) to identify single-nucleotide polymorphisms (SNPs) and insertions/deletions (Indels) associated with growth traits. Here, we analyzed population genetic structure and genome-wide selection signatures between the Haimen and Boer goats based on whole-genome resequencing data. The principal component analysis (PCA) and neighbor-joining (N-J) tree results demonstrated significant genetic differentiation between the Haimen and Boer goats. The nucleotide diversity (Pi) and linkage disequilibrium (LD) decay results indicated higher genomic diversity in the Haimen goat population. Furthermore, selective sweep analysis identified candidate genes associated with growth traits. These genes exhibited strong selection signatures and were related to body size (DONSON, BMPR1B, and EPHA5), muscle development (GART, VGLL3, MYH15), and fat metabolism (ADAMTS5, LRP6, XDH, CPT1A, and GPD1). We also identified growth-related candidate genes (NCOR1, DPP6, NOTCH2, and FGGY) specific to Haimen goats. Among these genes, pancreatic lipase-related protein 1 (PNLIPRP1) emerged as the primary candidate gene influencing growth phenotypes. Further analysis revealed that a 26 bp Indel in PNLIPRP1 increased its gene expression, suggesting that this Indel could serve as a molecular marker for early marker-assisted selection, potentially enhancing early growth in goats. These findings provide valuable molecular markers and candidate genes for improving growth traits in Haimen goat breeding.

Genome-wide re-sequencing reveals selection signatures for important economic traits in Taihang chickens

Taihang chickens is precious genetic resource with excellent adaptability and disease resistance, as well as high-quality eggs and meat. However, the genetic mechanism underlying important economic traits remain largely unknown. To address this gap, we conducted whole-genome resequencing of 66 Taihang and 15 White Plymouth rock chicken (Baiyu). The population structure analysis revealed that Taihang chickens and Baiyu are 2 independent populations. The genomic regions with strong selection signals and some candidate genes related to economic and appearance traits were identified. Additionally, we found a continuously selected 1.2 Mb region on chromosome 2 that is closely related to disease resistance. Therefore, our findings were helpful in further understanding the genetic architecture of the Taihang chickens and provided a worthy theoretical basis and technological support to improve high-quality Taihang chickens.

A selection breeding pattern for sexually dimorphic breast plumage color in Guangxi Yao chickens

The breast plumage color of Guangxi Yao chickens shows obvious sexual dimorphism, with roosters showing black and black with red, and hens displaying partridge and red. Black plumage in roosters is considered a sign of quality, necessitating the purification of plumage color. Here, we developed an effective method based on genetic variations within MC1R and plumage characteristics. We clarified the distribution of 5 single nucleotide polymorphisms (SNP) and 3 haplotypes (H1, H2, and H3) of MC1R gene, and revealed potential associations between haplotype H1 and black breast plumage in the F2 resource population derived from a backcross between Guangxi Yao and Yellow chickens. Subsequently, using H1/H1 diplotype roosters and hens to construct families (n = 1,244) notably increased the proportion of offspring with black plumage. Further analysis suggested that red plumage in hens may be the putative phenotype of black plumage in roosters, driven by haplotype H1 of the MC1R gene, as verified by genotype and phenotype analysis. As expected, we found that almost all male offspring of hens with red breast plumage showed black plumage. In short, we established a selection pattern based on the combination of black-plumage roosters and red-plumage hens can significantly purify the sexually dimorphic plumage color and improve the efficiency of breeding programs in Guangxi Yao chickens. Our findings provide a novel technical framework to accelerate the breeding process for plumage trait in poultry.

Association analysis of PMEL gene expression and single nucleotide polymorphism with plumage color in quail

To explore the relationship between PMEL gene and quail plumage color, to provide a reference for subsequent quail plumage color breeding. In this experiment, RT-qPCR technology was used to analyze the relative mRNA expression levels of Korean quail (maroon) and Beijing white quail embryos at different developmental stages. Two SNPs in PMEL gene were screened based on the RNA-Seq data of skin tissues of Korean quail and Beijing white quail during embryonic stage. The KASP technology was used for genotyping in the resource population and correlation analysis was carried out with the plumage color traits of quail. Finally, the bioinformatics technology was used to predict the effects of these two SNPs on the structure and function of the encoded protein. The results showed that the expression levels of PMEL gene during the embryonic development of Beijing white quail were extremely significantly higher than that of Korean quail (p < 0.01). The frequency distribution of the three genotypes (AA, AB, and BB) of the Beijing white quail at the c. 1030C > T and c. 1374A > G mutation sites were extremely significantly different from that of the Korean quail (p < 0.01). And there was a significant correlation between the c. 1374A > G mutation site with white plumage phenotype. Bioinformatics analysis showed that SNP1 (c. c1030t) located in exon 6 was a harmful mutation site, and SNP2 (c. a1374g) located in exon 7 was a neutral mutation site. Protein conservation prediction showed that the coding protein P344S site caused by SNP1 (c. c1030t) site and the coding protein I458M site caused by SNP2 (c. g2129a) site were non-conservative sites. The results of this experiment showed that the PMEL gene was associated with the plumage color traits of quail and could be used as a candidate gene for studying the plumage color of quail.

Genome-wide association study revealed the genomic regions associated with skin pigmentation in an Ogye x White Leghorn F2 chicken population

Skin color in chickens is an economically important trait that determines the first impression of a consumer toward a broiler and can ultimately affect consumer choice in the market. Therefore, identification of genomic regions associated with skin color is crucial for increasing the sales value of chickens. Although previous studies have attempted to reveal the genetic markers associated with the skin coloration in chickens, most were limited to investigations of candidate genes, such as melanin-related genes, and focused on case/control studies based on a single or small population. In this study, we performed a genome-wide association study (GWAS) on 770 F2 intercrosses produced by an experimental population of 2 chicken breeds, namely Ogye and White Leghorns, with different skin colors. The GWAS demonstrated that the L* value among the 3 skin color traits is highly heritable, and the genomic regions located on 2 chromosomes (20 and Z) were detected to harbor SNPs significantly associated with the skin color trait, accounting for most of the total genetic variance. Particular genomic regions spanning a ∼2.94 Mb region on GGA Z and a ∼3.58 Mb region on GGA 20 were significantly associated with skin color traits, and in these regions, certain candidate genes, including MTAP, FEM1C, GNAS, and EDN3, were found. Our findings could help elucidate the genetic mechanisms underlying chicken skin pigmentation. Furthermore, the candidate genes can be used to provide a valuable breeding strategy for the selection of specific chicken breeds with ideal skin coloration.

High-density single nucleotide polymorphism markers reveal the population structure of 2 local chicken genetic resources

Italy counts a large number of local chicken populations, some without a recognized genetic structure, such as Val Platani (VPL) and Cornuta (COS), which represent noteworthy local genetic resources. In this study, the genotype data of 34 COS and 42 VPL, obtained with the Affymetrix Axiom600KChicken Genotyping Array, were used with the aim to investigate the genetic diversity, the runs of homozygosity (ROH) pattern, as well as the population structure and relationship within the framework of other local Italian and commercial chickens. The genetic diversity indices, estimated using different approaches, displayed moderate levels of genetic diversity in both populations. The identified ROH hotspots harbored genes related to immune response and adaptation to local hot temperatures. The results on genetic relationship and population structure reported a clear clustering of the populations according to their geographic origin. The COS formed a nonoverlapping genomic cluster and clearly separated from the other populations, but showed evident proximity to the Siciliana breed (SIC). The VPL highlighted intermediate relationships between the COS-SIC group and the rest of the sample, but closer to the other Italian local chickens. Moreover, VPL showed a complex genomic structure, highlighting the presence of 2 subpopulations that match with the different source of the samples. The results obtained from the survey on genetic differentiation underline the hypothesis that Cornuta is a population with a defined genetic structure. The substructure that characterizes the Val Platani chicken is probably the consequence of the combined effects of genetic drift, small population size, reproductive isolation, and inbreeding. These findings contribute to the understanding of genetic diversity and population structure, and represent a starting point for designing programs to monitor and safeguard these local genetic resources, in order to define a possible official recognition program as breeds.

The study of selection signature and its applications on identification of candidate genes using whole genome sequencing data in chicken - a review

Chicken is a major source of protein for the increasing human population and is useful for research purposes. There are almost 1,600 distinct regional breeds of chicken across the globe, among which a large body of genetic and phenotypic variations has been accumulated due to extensive natural and artificial selection. Moreover, natural selection is a crucial force for animal domestication. Several approaches have been adopted to detect selection signatures in different breeds of chicken using whole genome sequencing (WGS) data including integrated haplotype score (iHS), cross-populated extend haplotype homozygosity test (XP-EHH), fixation index (F_ST), cross-population composite likelihood ratio (XP-CLR), nucleotide diversity (Pi), and others. In addition, gene enrichment analyses are utilized to determine KEGG pathways and gene ontology (GO) terms related to traits of interest in chicken. Herein, we review different studies that have adopted diverse approaches to detect selection signatures in different breeds of chicken. This review systematically summarizes different findings on selection signatures and related candidate genes in chickens. Future studies could combine different selection signatures approaches to strengthen the quality of the results thereby providing more affirmative inference. This would further aid in deciphering the importance of selection in chicken conservation for the increasing human population.

Association analysis of melanophilin (MLPH) gene expression and polymorphism with plumage color in quail

We explore the relationship between the melanophilin (MLPH) gene and quail plumage color and provide a reference for subsequent quail plumage color breeding. In this experiment, real-time quantitative PCR (RT-qPCR) technology was used to analyze the relative mRNA expression levels of Korean quail (maroon) and Beijing white quail embryos at different developmental stages. Two single-nucleotide polymorphisms (SNPs) in the MLPH gene were screened based on the RNA-sequencing (RNA-Seq) data of skin tissues of Korean quail and Beijing white quail during the embryonic stage. Kompetitive allele-specific PCR (KASP) technology was used for genotyping in the resource population, and correlation analysis was carried out with the plumage color traits of quail. Finally, bioinformatics was used to predict the effects of these two SNPs on the structure and function of the encoded protein. The results showed that the expression level of the MLPH gene during embryonic development of Beijing white quail was significantly higher than that of Korean quail ( P < 0.01 ). The frequency distribution of the three genotypes (CC, CA and AA) of the Beijing white quail at the c.1807C  >  A mutation site was significantly different from that of the Korean quail ( P < 0.01 ). The frequency distribution of the three genotypes (GG, GA and AA) of the Beijing white quail at the c.2129G  >  A mutation site was significantly different from that of the Korean quail ( P < 0.01 ). And there was a significant correlation between the c.1807C  >  A mutation site and the white plumage phenotype. Bioinformatics showed that SNP1 (c.1807C  >  A) was a neutral mutation and that SNP2 (c.2129G  >  A) was a deleterious mutation. The prediction of protein conservation showed that the mutation sites of coding proteins R603S and G710D caused by SNP1 (c.1807C  >  A) and SNP2 (c.2129G  >  A) were highly conserved.

Candidate pigmentation genes related to feather color variation in an indigenous chicken breed revealed by whole genome data

Chicken plumage color is an inheritable phenotype that was naturally and artificially selected for during domestication. The Baicheng You chicken is an indigenous Chinese chicken breed presenting three main feather colors, lavender, black, and yellow plumages. To explore the genetic mechanisms underlying the pigmentation in Baicheng You chickens, we re-sequenced the whole genome of Baicheng You chicken with the three plumage colors. By analyzing the divergent regions of the genome among the chickens with different feather colors, we identified some candidate genomic regions associated with the feather colors in Baicheng You chickens. We found that EGR1, MLPH, RAB17, SOX5, and GRM5 genes were the potential genes for black, lavender, and yellow feathers. MLPH, GRM5, and SOX5 genes have been found to be related to plumage colors in birds. Our results showed that EGR1 is a most plausible candidate gene for black plumage, RAB17, MLPH, and SOX5 for lavender plumage, and GRM5 for yellow plumage in Baicheng You chicken.

An Advanced Chicken Face Detection Network Based on GAN and MAE

Simple Summary

Chicken face detection is a fundamental task for accurate poultry management. Achieving satisfactory chicken face detection is necessary to implement downstream tasks, such as day-age detection, behavior recognition, and health monitoring. Nonetheless, the image dataset of the chicken face is small-scale, and there are few related studies. Moreover, chicken heads and features are smaller than other livestock, making recognition tricky. Inspired by these significances and obstacles, this paper proposes a chicken face detection network with an augmentation module. Based on the YOLOv4 backbone, our model achieved 0.91 F1, 0.84 mAP, and 37 FPS, far surpassing the two-stage RCNN and EfficientDet baselines. This model can be applied to an actual chicken coop, and its performance is adequate to conduct downstream tasks.

Abstract

Achieving high-accuracy chicken face detection is a significant breakthrough for smart poultry agriculture in large-scale farming and precision management. However, the current dataset of chicken faces based on accurate data is scarce, detection models possess low accuracy and slow speed, and the related detection algorithm is ineffective for small object detection. To tackle these problems, an object detection network based on GAN-MAE (generative adversarial network-masked autoencoders) data augmentation is proposed in this paper for detecting chickens of different ages. First, the images were generated using GAN and MAE to augment the dataset. Afterward, CSPDarknet53 was used as the backbone network to enhance the receptive field in the object detection network to detect different sizes of objects in the same image. The 128×128 feature map output was added to three feature map outputs of this paper, thus changing the feature map output of eightfold downsampling to fourfold downsampling, which provided smaller object features for subsequent feature fusion. Secondly, the feature fusion module was improved based on the idea of dense connection. Then the module achieved feature reuse so that the YOLO head classifier could combine features from different levels of feature layers to capture greater classification and detection results. Ultimately, the comparison experiments’ outcomes showed that the mAP (mean average Precision) of the suggested method was up to 0.84, which was 29.2% higher than other networks’, and the detection speed was the same, up to 37 frames per second. Better detection accuracy can be obtained while meeting the actual scenario detection requirements. Additionally, an end-to-end web system was designed to apply the algorithm to practical applications.

A High-Performance Day-Age Classification and Detection Model for Chick Based on Attention Encoder and Convolutional Neural Network

Thanks to the boom of computer vision techniques and artificial intelligence algorithms, it is more available to achieve artificial rearing for animals in real production scenarios. Improving the accuracy of chicken day-age detection is one of the instances, which is of great importance for chicken rearing. To solve this problem, we proposed an attention encoder structure to extract chicken image features, trying to improve the detection accuracy. To cope with the imbalance of the dataset, various data enhancement schemes such as Cutout, CutMix, and MixUp were proposed to verify the effectiveness of the proposed attention encoder. This paper put the structure into various mainstream CNN networks for comparison and multiple ablation experiments. The final experimental results show that by applying the attention encoder structure, ResNet-50 can improve the accuracy of chicken age detection to 95.2%. Finally, this paper also designed a complete image acquisition system for chicken houses and a detection application configured for mobile devices.

Draft genome assemblies of four manakins

Manakins are a family of small suboscine passerine birds characterized by their elaborate courtship displays, non-monogamous mating system, and sexual dimorphism. This family has served as a good model for the study of sexual selection. Here we present genome assemblies of four manakin species, including Cryptopipo holochlora, Dixiphia pipra (also known as Pseudopipra pipra), Machaeropterus deliciosus and Masius chrysopterus, generated by Single-tube Long Fragment Read (stLFR) technology. The assembled genome sizes ranged from 1.10 Gb to 1.19 Gb, with average scaffold N50 of 29 Mb and contig N50 of 169 Kb. On average, 12,055 protein-coding genes were annotated in the genomes, and 9.79% of the genomes were annotated as repetitive elements. We further identified 75 Mb of Z-linked sequences in manakins, containing 585 to 751 genes and an ~600 Kb pseudoautosomal region (PAR). One notable finding from these Z-linked sequences is that a possible Z-to-autosome/PAR reversal could have occurred in M. chrysopterus. These de novo genomes will contribute to a deeper understanding of evolutionary history and sexual selection in manakins.

New insights into genetics underlying of plumage color

Plumage color can be considered as a social signal in chickens and a breeding identification tool among breeders. The relationship between plumage color and trait groups of immunity, growth and fertility is still a controversial issue. This research aimed to determine the genome-wide additive and epistatic variants affecting plumage color variation in chickens using the chicken Illumina 60k high-density SNP array. Two scenarios of genome-wide additive association studies using all SNPs and independent SNPs were carried out. To perform epistatic association analysis, the LD pruning approach was used to reduce the complexity of the analysis. We detected seven novel significant loci using all of the SNPs in the model and 14 SNPs using the LD pruning approach associated with plumage color. Moreover, 89 significantly associated SNP-SNP interactions (P-value <10^-6 ) distributed in 25 chromosomes were identified, indicating that all of the signals together putatively influence the quantitative variation of plumage color. By annotating genes relevant to top SNPs, we have distinguished 18 potential candidate genes comprising HNF4beta, CKMT1B, TBC1D22A, RPL8, CACNA2D1, FZD4, SGMS1, IRF8, OPTN, LOC420362, TRABD, OvoDA1, DAD1, USP6, RBM12B, MIR1772, MIR1709 and MIR6696 and also 89 putative gene-gene combinations responsible for plumage color variation in chickens. Furthermore, several KEGG pathways including metabolic pathway, cytokine-cytokine receptor interaction, focal adhesion, melanogenesis, glycosaminoglycan biosynthesis-keratan sulfate and sphingolipid metabolism were enriched in the gene-set analysis. The results indicated that plumage color is a highly polygenic trait which, in turn, can be affected by multiple coding genes, regulatory genes and gene-gene epistasis interactions. In addition to genes with additive effects, epistatic genes with tiny individual effect sizes but significant effects in a pair have the potential to control plumage coloration in chickens.

Massive genome inversion drives coexistence of divergent morphs in common quails

The presence of population-specific phenotypes often reflects local adaptation or barriers to gene flow. The co-occurrence of phenotypic polymorphisms that are restricted within the range of a highly mobile species is more difficult to explain. An example of such polymorphisms is in the common quail Coturnix coturnix, a small migratory bird that moves widely during the breeding season in search of new mating opportunities, following ephemeral habitats,^1,2 and whose females may lay successive clutches at different locations while migrating.³ In spite of this vagility, previous studies reported a higher frequency of heavier males with darker throat coloration in the southwest of the distribution (I. Jiménez-Blasco et al., 2015, Int. Union Game Biol., conference). We used population genomics and cytogenetics to explore the basis of this polymorphism and discovered a large inversion in the genome of the common quail. This inversion extends 115 Mbp in length and encompasses more than 7,000 genes (about 12% of the genome), producing two very different forms. Birds with the inversion are larger, have darker throat coloration and rounder wings, are inferred to have poorer flight efficiency, and are geographically restricted despite the high mobility of the species. Stable isotope analyses confirmed that birds carrying the inversion have shorter migratory distances or do not migrate. However, we found no evidence of pre- or post-zygotic isolation, indicating the two forms commonly interbreed and that the polymorphism remains locally restricted because of the effect on behavior. This illustrates a genomic mechanism underlying maintenance of geographically structured polymorphisms despite interbreeding with a lineage with high mobility.

Genome-Wide SNP Analysis Reveals the Population Structure and the Conservation Status of 23 Italian Chicken Breeds

The genomic variability of local Italian chicken breeds, which were monitored under a conservation plan, was studied using single nucleotide polymorphisms (SNPs) to understand their genetic diversity and population structure. A total of 582 samples from 23 local breeds and four commercial stocks were genotyped using the Affymetrix 600 K Chicken SNP Array. In general, the levels of genetic diversity, investigated through different approaches, were lowest in the local chicken breeds compared to those in the commercial stocks. The level of genomic inbreeding, based on runs of homozygosity (FROH), was markedly different among the breeds and ranged from 0.121 (Valdarnese) to 0.607 (Siciliana). In all breeds, short runs of homozygosity (ROH) (<4 Mb in length) were more frequent than long segments. The patterns of genetic differentiation, model-based clustering, and neighbor networks showed that most breeds formed non-overlapping clusters and were clearly separate populations, which indicated the presence of gene flow, especially among breeds that originated from the same geographical area. Four genomic regions were identified as hotspots of autozygosity (islands) among the breeds, where the candidate genes are involved in morphological traits, such as body weight and feed conversion ratio. We conclude that the investigated breeds have conserved authentic genetic patterns, and these results can improve conservation strategies; moreover, the conservation of local breeds may play an important role in the local economy as a source of high-quality products for consumers.