Genome-Wide Association Study-Based Identification of SNPs and Haplotypes Associated With Goose Reproductive Performance and Egg Quality

Deciphering the Genetic Landscape: Insights Into the Genomic Signatures of Changle Goose

The Changle goose (CLG), a Chinese indigenous breed, is celebrated for its adaptability, rapid growth, and premium meat quality. Despite its agricultural value, the exploration of its genomic attributes has been scant. Our study entailed whole-genome resequencing of 303 geese across CLG and five other Chinese breeds, revealing distinct genetic diversity metrics. We discovered significant migration events from Xingguo gray goose to CLG and minor gene flow between them. We identified genomic regions through selective sweep analysis, correlating with CLG's unique traits. An elevated inbreeding coefficient in CLG, alongside reduced heterozygosity and rare single nucleotide polymorphisms (RSNPs), suggests a narrowed genetic diversity. Genomic regions related to reproduction, meat quality, and growth were identified, with the GATA3 gene showing strong selection signals for meat quality. A non-synonymous mutation in the Sloc2a1 gene, which is associated with reproductive traits in the CLG, exhibited significant differences in allelic frequency. The roles of CD82, CDH8, and PRKAB1 in growth and development, alongside FABP4, FAF1, ESR1, and AKAP12 in reproduction, were highlighted. Additionally, Cdkal1 and Mfsd14a may influence meat quality. This comprehensive genetic analysis underpins the unique genetic makeup of CLG, providing a basis for its conservation and informed breeding strategies.

The relationship between lysozyme gene polymorphism and quality changes during the storage of eggs derived from 2 commercial strains of Japanese quail

During the storage irreversible changes occur in eggs that result in a deterioration of their quality. The most significant changes affect the albumen. One of the major proteins of albumen present in egg white is lysozyme, which protects the embryo from microorganisms. This enzyme also contributes to the qualitative characteristics of albumen. It is possible that its polymorphism also affects the quality and stability of the obtained raw material that is, table eggs. Therefore, the aim of this study was to assess the potential effect of polymorphism in the lysozyme gene and protein on the quality changes during the storage of eggs derived from 2 genetic strains of Japanese quail belonging to various utility types. Eggs from selected females of laying and meat-type breeds were stored for 14 wk. During this period the egg quality traits were evaluated 10 times. DNA was isolated from each female and all exons of the lysozyme gene had been sequenced. In total, fourteen SNPs' and one 4-bp indel mutation were identified in exons and adjacent intronic sequences, among which SNP1 (1:32140723) resulted in a substitution of lysine with glutamine (Q21K). The results showed that SNP1 (strain S22), as well as the SNP2, SNP5, SNP7, SNP8, SNP10, SNP11, SNP12 and SNP13 were significantly associated with breaking strength during egg storage in both investigated Japanese quail strains. Furthermore, a 3 haplotype blocks containing nine SNPs (2, 5, 6, 7, 8, 10, 11, 12 and 13) were identified. These blocks displayed 8 distinct haplotypes that had significant association with breaking strength at all storage time points where egg quality analyses were performed. The study also revealed significant effects of breed and storage time on the egg quality traits. These results provide new insights into the genetic basis of egg quality during storage and could be incorporated into the breeding programs involving these strains.

Genome-Wide Association Analysis and Genetic Parameters for Egg Production Traits in Peking Ducks

Egg production traits are crucial in the poultry industry, including age at first egg (AFE), egg number (EN) at different stages, and laying rate (LR). Ducks exhibit higher egg production capacity than other poultry species, but the genetic mechanisms are still poorly understood. In this study, we collected egg-laying data of 618 Peking ducks from 22 to 66 weeks of age and genotyped them by whole-genome resequencing. Genetic parameters were calculated based on SNPs, and a genome-wide association study (GWAS) was performed for these traits. The SNP-based heritability of egg production traits ranged from 0.09 to 0.54. The GWAS identified nine significant SNP loci associated with AFE and egg number from 22 to 66 weeks. These loci showed that the corresponding alleles were positively correlated with a decrease in the traits. Moreover, three potential candidate genes (ENSAPLG00020011445, ENSAPLG00020012564, TMEM260) were identified. Functional enrichment analyses suggest that specific immune responses may have a critical impact on egg production capacity by influencing ovarian function and oocyte maturation processes. In conclusion, this study deepens the understanding of egg-laying genetics in Peking duck and provides a sound theoretical basis for future genetic improvement and genomic selection strategies in poultry.

The Omics Revolution in Understanding Chicken Reproduction: A Comprehensive Review

Omics approaches have significantly contributed to our understanding of several aspects of chicken reproduction. This review paper gives an overview of the use of omics technologies such as genomics, transcriptomics, proteomics, and metabolomics to elucidate the mechanisms of chicken reproduction. Genomics has transformed the study of chicken reproduction by allowing the examination of the full genetic makeup of chickens, resulting in the discovery of genes associated with reproductive features and disorders. Transcriptomics has provided insights into the gene expression patterns and regulatory mechanisms involved in reproductive processes, allowing for a better knowledge of developmental stages and hormone regulation. Furthermore, proteomics has made it easier to identify and quantify the proteins involved in reproductive physiology to better understand the molecular mechanisms driving fertility, embryonic development, and egg quality. Metabolomics has emerged as a useful technique for understanding the metabolic pathways and biomarkers linked to reproductive performance, providing vital insights for enhancing breeding tactics and reproductive health. The integration of omics data has resulted in the identification of critical molecular pathways and biomarkers linked with chicken reproductive features, providing the opportunity for targeted genetic selection and improved reproductive management approaches. Furthermore, omics technologies have helped to create biomarkers for fertility and embryonic viability, providing the poultry sector with tools for effective breeding and reproductive health management. Finally, omics technologies have greatly improved our understanding of chicken reproduction by revealing the molecular complexities that underpin reproductive processes.

Genetic Analysis of Egg Production Traits in Luhua Chickens: Insights from a Multi-Trait Animal Model and a Genome-Wide Association Study

Egg production plays a pivotal role in the economic viability of hens. To analyze the genetic rules of egg production, a total of 3151 Luhua chickens were selected, the egg production traits including egg weight at first laying (Start-EW), egg weight at 43 weeks (EW-43), egg number at 43 weeks (EN-43), and total egg number (EN-All) were recorded. Then, the effects of related factors on egg production traits were explored, using a multi-trait animal model for genetic parameter estimation and a genome-wide association study (GWAS). The results showed that body weight at first egg (BWFE), body weight at 43 weeks (BW-43), age at first egg (AFE), and seasons had significant effects on the egg production traits. Start-EW and EW-43 had moderate heritability of 0.30 and 0.21, while EN-43 and EN-All had low heritability of 0.13 and 0.16, respectively. Start-EW exhibited a robust positive correlation with EW-43, while Start-EW was negatively correlated with EN-43 and EN-All. Furthermore, gene ontology (GO) results indicated that Annexin A2 (ANXA2) and Frizzled family receptor 7 (FZD7) related to EW-43, Cyclin D1 (CCND1) and A2B adenosine receptor (ADORA2B) related to EN-All, and have been found to be mainly involved in metabolism and growth processes, and deserve more attention and further study. This study contributes to accelerating genetic progress in improving low heritability egg production traits in layers, especially in Luhua chickens.

Association analysis of production traits of Japanese quail (Coturnix japonica) using restriction-site associated DNA sequencing

This study was designed to perform an association analysis and identify SNP markers associated with production traits of Japanese quail using restriction-site-associated DNA sequencing. Weekly body weight data from 805 quail were collected from hatching to 16 weeks of age. A total number of 3990 eggs obtained from 399 female quail were used to assess egg quality traits. Egg-related traits were measured at the beginning of egg production (first stage) and at 12 weeks of age (second stage). Five eggs were analyzed at each stage. Traits, such as egg weight, egg length and short axes, eggshell strength and weight, egg equator thickness, yolk weight, diameter, and colour, albumen weight, age of first egg, total number of laid eggs, and egg production rate, were assessed. A total of 383 SNPs and 1151 associations as well as 734 SNPs and 1442 associations were identified in relation to quail production traits using general linear model (GLM) and mixed linear model (MLM) approaches, respectively. The GLM-identified SNPs were located on chromosomes 1-13, 15, 17-20, 24, 26-28, and Z, underlying phenotypic traits, except for egg and albumen weight at the first stage and yolk yellowness at the second stage. The MLM-identified SNPs were positioned on defined chromosomes associated with phenotypic traits except for the egg long axis at the second stage of egg production. Finally, 35 speculated genes were identified as candidate genes for the targeted traits based on their nearest positions. Our findings provide a deeper understanding and allow a more precise genetic improvement of production traits of Galliformes, particularly in Japanese quail.

Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis

BACKGROUND

Domestic goose breeds are descended from either the Swan goose (Anser cygnoides) or the Greylag goose (Anser anser), exhibiting variations in body size, reproductive performance, egg production, feather color, and other phenotypic traits. Constructing a pan-genome facilitates a thorough identification of genetic variations, thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.

RESULTS

To comprehensively facilitate population genomic and pan-genomic analyses in geese, we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples. By constructing the pan-genome for geese, we generated non-reference contigs totaling 612 Mb, unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes, 1,324 softcore genes, 2,734 shell genes, and 878 cloud genes in goose genomes. Furthermore, we detected an 81.97 Mb genomic region showing signs of genome selection, encompassing the TGFBR2 gene correlated with variations in body weight among geese. Genome-wide association studies utilizing single nucleotide polymorphisms (SNPs) and presence-absence variation revealed significant genomic associations with various goose meat quality, reproductive, and body composition traits. For instance, a gene encoding the SVEP1 protein was linked to carcass oblique length, and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length. Notably, the pan-genome analysis revealed enrichment of variable genes in the "hair follicle maturation" Gene Ontology term, potentially linked to the selection of feather-related traits in geese. A gene presence-absence variation analysis suggested a reduced frequency of genes associated with "regulation of heart contraction" in domesticated geese compared to their wild counterparts. Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.

CONCLUSION

This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits, thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese. Moreover, assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome, establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.

Whole Genome Resequencing Identifies Single-Nucleotide Polymorphism Markers of Growth and Reproduction Traits in Zhedong and Zi Crossbred Geese

The broodiness traits of domestic geese are a bottleneck that prevents the rapid development of the goose industry. To reduce the broodiness of the Zhedong goose and thus improve it, this study hybridized it with the Zi goose, which has almost no broody behavior. Genome resequencing was performed for the purebred Zhedong goose, as well as the F2 and F3 hybrids. The results showed that the F1 hybrids displayed significant heterosis in growth traits, and their body weight was significantly greater than those of the other groups. The F2 hybrids showed significant heterosis in egg-laying traits, and the number of eggs laid was significantly greater than those of the other groups. A total of 7,979,421 single-nucleotide polymorphisms (SNPs) were obtained, and three SNPs were screened. Molecular docking results showed that SNP11 located in the gene NUDT9 altered the structure and affinity of the binding pocket. The results suggested that SNP11 is an SNP related to goose broodiness. In the future, we will use the cage breeding method to sample the same half-sib families to accurately identify SNP markers of growth and reproductive traits.

Chromosome-level genome assembly of goose provides insight into the adaptation and growth of local goose breeds

BACKGROUND

Anatidae contains numerous waterfowl species with great economic value, but the genetic diversity basis remains insufficiently investigated. Here, we report a chromosome-level genome assembly of Lion-head goose (Anser cygnoides), a native breed in South China, through the combination of PacBio, Bionano, and Hi-C technologies.

FINDINGS

The assembly had a total genome size of 1.19 Gb, consisting of 1,859 contigs with an N50 length of 20.59 Mb, generating 40 pseudochromosomes, representing 97.27% of the assembled genome, and identifying 21,208 protein-coding genes. Comparative genomic analysis revealed that geese and ducks diverged approximately 28.42 million years ago, and geese have undergone massive gene family expansion and contraction. To identify genetic markers associated with body weight in different geese breeds, including Wuzong goose, Huangzong goose, Magang goose, and Lion-head goose, a genome-wide association study was performed, yielding an average of 1,520.6 Mb of raw data that detected 44,858 single-mucleotide polymorphisms (SNPs). Genome-wide association study showed that 6 SNPs were significantly associated with body weight and 25 were potentially associated. The significantly associated SNPs were annotated as LDLRAD4, GPR180, and OR, enriching in growth factor receptor regulation pathways.

CONCLUSIONS

We present the first chromosome-level assembly of the Lion-head goose genome, which will expand the genomic resources of the Anatidae family, providing a basis for adaptation and evolution. Candidate genes significantly associated with different goose breeds may serve to understand the underlying mechanisms of weight differences.

Genome-wide association study for reproduction-related traits in Chinese domestic goose

1. This study measured six reproduction traits in a Sichuan white goose population (209 individuals), including fertility, qualified egg rate, plasma concentrations of progesterone (P), follicle-stimulating hormone (FSH), prolactin (PRL) and oestrogen (E2).2. Whole-genome resequencing data from the same goose population (209 individuals) were used in a genome-wide association study (GWAS) utilising a mixed linear model to investigate the genes and genetic markers associated with reproduction traits. The frequency of the selected SNPs and haplotypes were determined using the Matrix-Assisted Laser Desorption Ionisation Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) method.3. In total, 42 SNPs significantly associated with these traits were identified. A haplotype block was constructed based on five SNPs that were significantly associated with qualified egg rate, with individuals having the haplotype CCTTAAGGAA having the lowest qualified egg rate.4. In conclusion, these results provided potential markers for marker-assisted selection to improve goose reproductive performance and a basis for elucidating the genetics of goose reproduction.

Machine learning for identifying resistance features of Klebsiella pneumoniae using whole-genome sequence single nucleotide polymorphisms

Introduction. Klebsiella pneumoniae, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of K. pneumoniae is increasing year by year, posing a severe threat to public health worldwide. K. pneumoniae has been listed as one of the pathogens causing the global crisis of antimicrobial resistance in nosocomial infections. We need to explore the drug resistance of K. pneumoniae for clinical diagnosis. Single nucleotide polymorphisms (SNPs) are of high density and have rich genetic information in whole-genome sequencing (WGS), which can affect the structure or expression of proteins. SNPs can be used to explore mutation sites associated with bacterial resistance.Hypothesis/Gap Statement. Machine learning methods can detect genetic features associated with the drug resistance of K. pneumoniae from whole-genome SNP data.Aims. This work used Fast Feature Selection (FFS) and Codon Mutation Detection (CMD) machine learning methods to detect genetic features related to drug resistance of K. pneumoniae from whole-genome SNP data.Methods. WGS data on resistance of K. pneumoniae strains to four antibiotics (tetracycline, gentamicin, imipenem, amikacin) were downloaded from the European Nucleotide Archive (ENA). Sequence alignments were performed with MUMmer 3 to complete SNP calling using K. pneumoniae HS11286 chromosome as the reference genome. The FFS algorithm was applied to feature selection of the SNP dataset. The training set was constructed based on mutation sites with mutation frequency >0.995. Based on the original SNP training set, 70% of SNPs were randomly selected from each dataset as the test set to verify the accuracy of the training results. Finally, the resistance genes were obtained by the CMD algorithm and Venny.Results. The number of strains resistant to tetracycline, gentamicin, imipenem and amikacin was 931, 1048, 789 and 203, respectively. Machine learning algorithms were applied to the SNP training set and test set, and 28 and 23 resistance genes were predicted, respectively. The 28 resistance genes in the training set included 22 genes in the test set, which verified the accuracy of gene prediction. Among them, some genes (KPHS_35310, KPHS_18220, KPHS_35880, etc.) corresponded to known resistance genes (Eef2, lpxK, MdtC, etc). Logistic regression classifiers were established based on the identified SNPs in the training set. The area under the curves (AUCs) of the four antibiotics was 0.939, 0.950, 0.912 and 0.935, showing a strong ability to predict bacterial resistance.Conclusion. Machine learning methods can effectively be used to predict resistance genes and associated SNPs. The FFS and CMD algorithms have wide applicability. They can be used for the drug-resistance analysis of any microorganism with genomic variation and phenotypic data. This work lays a foundation for resistance research in clinical applications.

Domestication Explains Two-Thirds of Differential-Gene-Expression Variance between Domestic and Wild Animals; The Remaining One-Third Reflects Intraspecific and Interspecific Variation

Belyaev's concept of destabilizing selection during domestication was a major achievement in the XX century. Its practical value has been realized in commercial colors of the domesticated fox that never occur in the wild and has been confirmed in a wide variety of pet breeds. Many human disease models involving animals allow to test drugs before human testing. Perhaps this is why investigators doing transcriptomic profiling of domestic versus wild animals have searched for breed-specific patterns. Here we sequenced hypothalamic transcriptomes of tame and aggressive rats, identified their differentially expressed genes (DEGs), and, for the first time, applied principal component analysis to compare them with all the known DEGs of domestic versus wild animals that we could find. Two principal components, PC1 and PC2, respectively explained 67% and 33% of differential-gene-expression variance (hereinafter: log2 value) between domestic and wild animals. PC1 corresponded to multiple orthologous DEGs supported by homologs; these DEGs kept the log2 value sign from species to species and from tissue to tissue (i.e., a common domestication pattern). PC2 represented stand-alone homologous DEG pairs reversing the log2 value sign from one species to another and from tissue to tissue (i.e., representing intraspecific and interspecific variation).

Identification and Validation of Marketing Weight-Related SNP Markers Using SLAF Sequencing in Male Yangzhou Geese

Growth performance is a complex economic trait for avian production. The swan goose (Anser cygnoides) has never been exploited genetically like chickens or other waterfowl species such as ducks. Traditional phenotypic selection is still the main method for genetic improvement of geese body weight. In this study, specific locus amplified fragment sequencing (SLAF-seq) with bulked segregant analysis (BSA) was conducted for discovering and genotyping single nucleotide polymorphisms (SNPs) associated with marketing weight trait in male geese. A total of 149,045 SNPs were obtained from 427,093 SLAF tags with an average sequencing depth of 44.97-fold and a Q30 value of 93.26%. After SNPs' filtering, a total of 12,917 SNPs were included in the study. The 31 highest significant SNPs-which had different allelic frequencies-were further validated by individual-based AS-PCR genotyping in two populations. The association between 10 novel SNPs and the marketing weight of male geese was confirmed. The 10 significant SNPs were involved in linear regression model analysis, which confirmed single-SNP associations and revealed three types of SNP networks for marketing weight. The 10 significant SNPs were located within or close to 10 novel genes, which were identified. The qPCR analysis showed significant difference between genotypes of each SNP in seven genes. Developed SLAF-seq and identified genes will enrich growth performance studies, promoting molecular breeding applications to boost the marketing weight of Chinese geese.