Background The Chinese native Diqing Tibetan pig has a long history of domestication and is distributed in the southernmost region of China compared to other Tibetan breeds. In this study, we performed whole-genome sequencing of the Diqing Tibetan pigs. By integrating previously published data, we explored the genetic structure, population diversity, and genetic introgression from commercial European pigs and Southern Chinese domestic pigs into Diqing Tibetan pigs. We further examined the potential genetic influences of European pig introgression and inferred the historical events of admixture with Southern Chinese breeds.Results Our analysis revealed various instances of population admixture between Diqing Tibetan pigs and European pigs, as well as redundant introgression from South Chinese pigs when compared to other Tibetan pig populations. The introgression from European pigs significantly increased the population diversity in Diqing Tibetan pigs, which may influence fertility. Additionally, the introgression from European pigs affected the proportion of introgression from Southern Chinese pigs, with the most pronounced effect near the PSCK2 gene, which is associated with body size. Regarding ancestral genetic components from Southern Chinese pigs, we discovered a significant level of redundant proportion in Diqing Tibetan pigs compared to other Tibetan breeds. This admixture may have occurred at multiple time points from different breeds, with the Diannan small ear breed in Yunnan Province of China potentially serving as a recent primary contributor to the introgression into Diqing Tibetan breed.Conclusion Our study reveals that the Diqing Tibetan breed has been shaped by admixture from European and multiple Southern Chinese sources, where European introgression increased diversity and reshaped Southern ancestry, while Southern introgression itself derives from distinct Southern Chinese pig breeds.

Indigenous chickens in tropical regions routinely survive high environmental temperatures (40-45 °C) that cause significant mortality and production loss in commercial breeds, yet the genetic mechanisms of thermotolerance remain poorly understood. This study integrated genome-wide selective scans across 14 geographically and climatically diverse chicken breeds with multi-tissue expression data, gene expression quantitative trait locus (eQTL) analysis, transcriptome-wide association study (TWAS), and cross-species phenome-wide association study (PheWAS) to validate candidate genes. We identified 25 high-confidence genes under selection, with ATP1A1, PLCB4, RYR2 and AKT3 forming a regulatory hub coordinating cardiovascular, calcium and survival signaling. These genes converge on interconnected adrenergic, calcium, and GnRH signaling pathways, with coordinated expression across heart, hypothalamus, and liver forming an integrated thermoregulatory axis. The eQTL integration analysis using ChickenGTEx data identified 359 tissue-specific cis-eQTLs in selected regions. Additionally, TWAS analysis linked ATP1A1 to 145 gene-trait associations across 13 tissues and 14 trait categories (hepatic regulation, β = -2.13, p = 4.21 × 10⁻¹²), and cross-species PheWAS validated conserved roles in cardiovascular function (RYR2, resting heart rate p = 4.9 × 10⁻¹²), and ionic homeostasis (ATP1A1, chloride p = 1.18 × 10⁻³). In parallel, we also identified robust genomic signatures of domestication in classic candidate genes (TSHR, TBC1D1, BDNF), highlighting how initial separation from Red Jungle Fowl and subsequent adaptation to diverse climates have shaped the genetic and physiological diversity of the domesticated chicken. Collectively, our results reveal an integrated cardio-neuroendocrine calcium network driving heat adaptation, providing potential targets for breeding heat-tolerant chickens.

Understanding how biodiversity arises and how organisms adapt to different environments is fundamental to evolutionary biology. Hybridization may play an essential role in generating genetic diversity and promoting adaptation. In this work, we analyzed the population structure, demographic history, and selective landscapes of East Asian domestic pigs using a whole-genome resequencing dataset of 1,092 samples from 43 breeds. Our results indicate that North and South pigs form two deeply divergent lineages that split approximately 17,797 years ago, with no extant wild boar population identified as the direct ancestor of South pigs. In contrast, Central and Southwest pigs originated from a North ancestral background (∼9,012 years ago) with introgression from South pigs before their divergence (∼6,284 years ago), which was likely driven by bidirectional migrations between ancient northern and southern human populations in China. The North ancestry under selection contributed to increased body weight, while the South ancestry enhanced environmental adaptation through pathways involved in UV-B response, stress tolerance, and extracellular matrix remodeling. This South-derived ancestry facilitated the geographic expansion of North pigs into broader ecological zones, which led to the establishment of the Central and Southwest pigs. Specifically, we demonstrate that North-South hybridization increases genetic diversity and produces a mosaic inheritance pattern. Moreover, hybridization and adaptive introgression contribute to novel phenotypic variation in domesticated animals, offering valuable insights for genetic improvement and selective breeding.

The harsh environments of high-altitude habitats present formidable challenges for animal survival and reproduction. The adaptation of plateau endotherms to hypoxic and cold stresses has been studied for more than a century. However, the responses and contributions of the symbiotic microbiota to host adaptation remain unclear. Here, we conducted an integrated analysis of the gut and respiratory microbiomes of Tibetan chickens native to the high-altitudes of Lhasa and maintained for 20 years (approximately 20 generations) in low-altitude Beijing, as well as other high- and low-altitude breeds, to determine microbiota-host co-evolution in high-altitude adaptation. The results revealed that the respiratory microbial composition differed from that of the gut. The cecal microbiota was enriched in metabolic pathways, whereas the lung microbiota was more enriched in environmental information processing. Higher microbial diversity was observed in the ceca of chickens housed in Lhasa, whereas the lungs presented lower microbial diversity. Notably, consistent with the varying altitudes, the microbial communities in the ceca and lungs could be classified into distinct enterotypes and pulmotypes, respectively. The lung microbiome exhibited a more rapid environmental adaptation response to high-altitude environments, as 88 microbial genera were identified as signatures of high-altitude adaptation compared with only 7 in the ceca. Additionally, cecal Acetobacteroides was jointly regulated by the environmental conditions and host genetics, with higher abundance in the high-altitude chickens. FST analysis and mbQTL mapping identified NAT8L as a key gene under natural selection influencing Acetobacteroides colonization. Moreover, genotype-associated differences in metabolite levels indicate a potential link between NAT8L and Acetobacteroides, possibly through shared involvement in alanine, as-partate, and glutamate metabolism. These findings reveal a host gene-metabolism-microbiota axis that enhances energy efficiency, offering new perspectives for microbiota-host collaboration in high-altitude adaptation.

The study of domestication has been revolutionized with the advent of molecular genetics. Chickens, with their clear domestication history, emerge as an excellent model for study into the paths of evolution in domestication and improvement. Here we used genomic data from wild, indigenous, and commercial chickens to better understand how genetic drift and selection translate into their differentiations. Our investigation into the patterns of allelic change and divergence reveals a polygenic architecture governing genetic differentiation during domestication and improvement. We uncover distinctive population-specific differentiations in terms of genes and functions among wild, indigenous, and commercial chickens. Using Runs Of Homozygosity (ROH) based mixed model approach developed in this study, we identified only directional selection signatures occurring in wild and commercial chickens. Notably, our findings suggest that indigenous chickens serve as reservoirs of genetic diversity, necessary for rapid adaptation to new environments or subsequent modern breeding. This work provides unprecedented insights into the chicken domestication and improvement, and it illuminates our understanding of the domestication of other animal species.

Genetic resources are essential components of biodiversity. As national strategy, the conservation of genetic resources is crucial not only for biodiversity but also for sustainable agriculture and cultural heritage. However, the exact origin of most local breeds remains unclear at the genomic level. The conservation efforts are becoming more challenging as local breeds are currently experiencing genetic drift and admixture, which may be further complicated by historical hybridizations. A typical example is the Beijing-You chicken, a local breed renowned for its excellent meat flavor and unique appearance. With a relatively recent history ( 300 years), it displays mixed phenotypes which may have resulted from genomic admixture, with its exact origin yet to be determined. Through comprehensive genomic similarity analysis, we identified 12 genetic donor breeds for the Beijing-You chicken and quantified their genetic contributions, with the highest ancestry proportion coming from Henan chickens. The local ancestry components and genomic structure analyses of the Beijing-You chicken suggest recent hybridization in the formation of this breed. Furthermore, we innovatively used ancestry components as new material for genetic evaluation and selection signature detection, demonstrating that conservation efforts over the past decade have been effective. Analysis of selection signatures revealed genes and regions associated with polydactyly, egg production, intramuscular fat, and spermatogenesis. By integrating various analytical strategies, we developed a novel framework for genetic traceability and evaluation. Our results highlight the effectiveness of ancestry components in genetic assessment and offer valuable insights for the conservation, improvement, and sustainable utilization of local breeds.

The historical importation of Chinese pigs into Western countries has facilitated the introduction of Chinese haplotypes into European pig breeds, thereby shaping their genetic diversity and phenotypic traits. However, the genetic and biological implications of this introgression remain poorly understood. Based on SNP chip and resequencing data, we confirmed significant genetic introgression from Chinese pigs into commercial European lines. The genetic origins of the introgressed segments predominantly derive from Southern Chinese domestic pigs (CSDP), with additional contributions from other populations, such as Eastern Chinese domestic pigs (CEDP). Our study demonstrates that the selection pressure for Chinese pig introgression was stronger in Duroc pigs compared to the Large White and Landrace breeds. Based on ancestral haplotypes from CEDP and CSDP, we conducted a genome-wide association study (GWAS) and identified 10 quantitative trait loci (QTLs), five of which were not identified in previous studies or using SNPs. Expression genome-wide association studies (eGWAS) based on these introgressed haplotypes, using gene expression profiles from the duodenum, liver, and muscle tissues in the Duroc population, revealed eGWAS signals that were enriched near transcript start sites. By integrating GWAS signals for loin muscle depth with eGWAS signals in muscle tissue, we confirmed that a region 300 Kb from TAF11, which is enriched with open chromatin regions and encompasses a super-enhancer located within the same topologically associating domain as TAF11, was associated with both TAF11 expression and loin muscle depth, highlighting the profound influence of Chinese introgression. These findings offer valuable insights into the genetic influences of Chinese pig introgression on the Duroc breed, as well as the molecular basis for its effects on economically important traits in Duroc pigs.

Characterization of the genetic and molecular architecture underlying egg production traits in chickens is essential for improving the rate of genetic gain through intensive artificial selection. Here, to explore the dynamic landscape of regulatory effects across egg-laying stages in chickens, we generated 1272 RNA-seq samples of four tissues, i.e., the hypothalamic-pituitary-ovarian axis and liver, and paired whole-genome sequence data from 358 hens. We detected 1008 genes with stage-specific regulatory effects in at least one tissue excluding the pituitary. Out of them, 12.60, 52.78 and 32.84% were mediated by alterations in cell type composition, transcriptional factor activity, and gene co-expression networks among laying stages, respectively. Out of 80 significant loci associated with egg production traits that were detected in a large population (n = 12,952), 37 and 5 colocalized by shared and stage-specific regulatory effects, respectively. Furthermore, orthologues of these colocalized genes are enriched for the heritability of reproductive traits in pigs, cattle, and humans. In summary, we provide a resource for understanding reproduction-relevant gene regulation and highlight the importance of context-specific regulatory effects in deciphering complex traits.

Compared to many other vertebrates, chickens have a high reproductive efficiency in terms of egg production. The classic traits for evaluating egg-laying performance include age at first egg, egg number, clutch size, laying rate, etc. These egg-laying traits were not specifically designed to characterize egg production efficiency and stability. By considering the stage-specific variations in the egg production curve, this study aims to investigate the genetic mechanisms that directly influence the efficiency of egg production at each stage of the laying cycle. Using whole-genome sequencing data, we perform comprehensive genome-wide association study for 39 traits that focus on egg production efficiency and stability in the Gushi chicken. We showed that the haplotype-based approach is more effective for genetic mapping and capturing polygenic architecture. By combining the signals of Singleton Density Score (SDS), which is a population-genetic statistic designed to detect recent selection by leveraging the distribution of singletons, and association analyses, multiple egg-laying traits related to egg production efficiency were found to have experienced polygenic selection. Consistently, functional analysis of associated genes demonstrates that egg production efficiency benefits from multiple physiological functions. Furthermore, our results identified the CNNM2 gene, known for its role in magnesium homeostasis, plays a dual role in egg production variance, promoting variability during the up-stage while reducing it during the sustained-stage to optimize egg production efficiency. Collectively, our multiple genome analyses reveal a complex genetic mechanism underlying more efficient and stable egg production, and establish chicken genetics as a model for studying reproductive efficiency across species.

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/#/.

Hu sheep are renowned for their adaptation to high-temperature, humid environments and their high fecundity. Despite serving as the founder species for sheep breeding in China, the genetic mechanisms underlying these desirable traits and the breed's origin have remained unresolved. To address the longstanding challenges in understanding their adaptations and origins, comprehensive analyses utilizing genetic data is conducted from over 300 Hu sheep and ≈200 other Chinese native sheep. The study unveils the migration history of sheep and the formation of the Hu sheep in eastern China. By employing multiple screening methods, this study identifies that the BMPR1B, UNC5C, and GRID2 synergistically contribute to the high fecundity trait in Hu sheep. The coexistence of beneficial genotypes in these genes increase the likelihood of multiple births. Notably, the results suggest a potential coevolution between environmental adaptation and reproductive traits in this breed. Overall, the study provides novel insights into the genetic origin and adaptation of Hu sheep, offering new perspectives for molecular breeding in sheep and other livestock species.

Understanding the genetic mechanisms underlying egg production is crucial for improving laying performance in chickens. However, traditional genome-wide association studies (GWAS) have not effectively utilized the information regarding the longitudinal trajectories and dynamics of egg-laying phenotype. In this study, based on individual egg production records over time, we first utilized the Yang-Ning model to characterize four egg production parameters. Our SNP-based GWAS on these parameters, along with three multidimensional GWAS models, captured different aspects of egg-laying dynamics. The novel significant associations and candidate genes identified, including C3, CADPS2, and TLN2, contribute significantly to egg-laying traits. By quantifying both direct and indirect effects of egg production parameters on egg number (EN) through the integration of Bayesian networks and structural equation modeling, we demonstrated that an earlier age at first egg directly promotes EN. The findings from this study enhance our understanding of the genetic mechanisms involved in egg production and provide valuable insights for optimizing chicken breeding strategies.

Organisms respond to environmental changes through two primary mechanisms: Fleeing or physiological adaptation. For many organisms, the possibilities and opportunities for escape are limited, so they often need to rely on altering physiological functions, behaviors, or phenotypes in response to environmental changes. This phenomenon of organisms developing different phenotypes in response to different environments is phenotypic plasticity. Phenotypic plasticity, the ability to develop different phenotypes in different environments, is a fundamental attribute of organisms and an important way to adapt to the environment. The robustness of biological systems to genetic variation and environmental disturbances is referred to as canalization. Canalization enables organisms to buffer various internal or external perturbations, helping to maintain the stability of crucial traits and reflecting different strategies for organisms to adapt to environmental changes. Bradshaw's 1965 proposition initiated the study of phenotypic plasticity's evolutionary genetic basis, leading to contemporary research focusing on methodologies and technologies for its assessment. Nowadays, phenotypic plasticity has become a popular research field, and with the development of new methods and technologies, researchers are increasingly focusing on research methodologies related to phenotypic plasticity. For quantitative assessment of phenotypic plasticity, researchers often utilize populations with identical genetic backgrounds and quantify plastic responses in two or more different environments, including a control environment. Classic methods for quantifying phenotypic plasticity compare differences in phenotype values at the population or individual level or examine the regression slope of phenotype values against the environment. Classic quantification methods have limitations, especially with nonlinear reactions. For instance, when reaction norm is nonlinear, simplifying it through responses to only two environments may make it challenging to accurately quantify plasticity, leading to potential serious underestimation or overestimation. Current research aims to refine methodologies, considering genetic backgrounds, gene-environment interactions (GxE), and other factors. Phenotypic plasticity is shaped by genetic and epigenetic factors. However, many details remain unclear, and future research needs to integrate genetic maps, transcriptomics, metabolomics, proteomics and epigenomics methods to reveal relevant mechanisms and principles. The relationship between phenotypic plasticity and adaptability varies across scenarios, requiring case-specific examination. Costs and constraints associated with plasticity must be considered when evaluating adaptability. Accurately assessing the costs of plastic responses can provide important insights into understanding the adaptability of plastic responses. Furthermore, the interpretation of plasticity responses may vary with researchers' perspectives and focuses, highlighting the necessity for more accurate definitions and descriptions of plasticity. With advancements in genomics, phenomics, single-cell biology and other fields, multidisciplinary research is becoming the norm. This systematic review provides a concise overview of phenotypic plasticity, including historical evolution, mechanisms, quantification methodologies, and its relationship with adaptability. Using examples from animals, plants, and microorganisms, it highlights challenges and proposes future research directions for a comprehensive understanding of this phenomenon across organisms.

Egg-laying performance is of great economic importance in poultry, but the underlying genetic mechanisms are still elusive. In this work, we conduct a multi-omics and multi-tissue integrative study in hens with distinct egg production, to detect the hub candidate genes and construct hub molecular networks contributing to egg-laying phenotypic differences. We identifiy three hub candidate genes as egg-laying facilitators: TFPI2, which promotes the GnRH secretion in hypothalamic neuron cells; CAMK2D, which promotes the FSHβ and LHβ secretion in pituitary cells; and OSTN, which promotes granulosa cell proliferation and the synthesis of sex steroid hormones. We reveal key endocrine factors involving egg production by inter-tissue crosstalk analysis, and demonstrate that both a hepatokine, APOA4, and an adipokine, ANGPTL2, could increase egg production by inter-tissue communication with hypothalamic-pituitary-ovarian axis. Together, These results reveal the molecular mechanisms of multi-tissue coordinative regulation of chicken egg-laying performance and provide key insights to avian reproductive regulation. Egg-laying performance is an important phenotype for breeding chicken. Here, the authors explore the regulatory networks driving phenotypic differences in egg-laying, and identify laying-related variants and endocrine factors.

BackgroundThe genome-wide association study (GWAS) is a powerful method for mapping quantitative trait loci (QTL). However, standard GWAS can detect only QTL that segregate in the mapping population. Crossing populations with different characteristics increases genetic variability but F2 or back-crosses lack mapping resolution due to the limited number of recombination events. This drawback can be overcome with advanced intercross line (AIL) populations, which increase the number recombination events and provide a more accurate mapping resolution. Recent studies in humans have revealed ancestry-dependent genetic architecture and shown the effectiveness of admixture mapping in admixed populations.ResultsThrough the incorporation of line-of-origin effects and GWAS on an F9 AIL population, we identified genes that affect body weight at eight weeks of age (BW8) in chickens. The proposed ancestral-haplotype-based GWAS (testing only the origin regardless of the alleles) revealed three new QTLs on GGA12, GGA15, and GGA20. By using the concepts of ancestral homozygotes (individuals that carry two haplotypes of the same origin) and ancestral heterozygotes (carrying one haplotype of each origin), we identified 632 loci that exhibited high-parent (the heterozygote is better than both parents) and mid-parent (the heterozygote is better than the median of the parents) dominance across 12 chromosomes. Out of the 199 genes associated with BW8, EYA1, PDE1C, and MYC were identified as the best candidate genes for further validation.ConclusionsIn addition to the candidate genes reported in this study, our research demonstrates the effectiveness of incorporating ancestral information in population genetic analyses, which can be broadly applicable for genetic mapping in populations generated by ancestors with distinct phenotypes and genetic backgrounds. Our methods can benefit both geneticists and biologists interested in the genetic determinism of complex traits.

BACKGROUND:Although the accumulation of whole-genome sequencing (WGS) data has accelerated the identification of mutations underlying complex traits, its impact on the accuracy of genomic predictions is limited. Reliable genotyping data and pre-selected beneficial loci can be used to improve prediction accuracy. Previously, we reported a low-coverage sequencing genotyping method that yielded 11.3 million highly accurate single-nucleotide polymorphisms (SNPs) in pigs. Here, we introduce a method termed selective linkage disequilibrium pruning (SLDP), which refines the set of SNPs that show a large gain during prediction of complex traits using whole-genome SNP data.RESULTS:We used the SLDP method to identify and select markers among millions of SNPs based on genome-wide association study (GWAS) prior information. We evaluated the performance of SLDP with respect to three real traits and six simulated traits with varying genetic architectures using two representative models (genomic best linear unbiased prediction and BayesR) on samples from 3579 Duroc boars. SLDP was determined by testing 180 combinations of two core parameters (GWAS P-value thresholds and linkage disequilibrium r2). The parameters for each trait were optimized in the training population by five fold cross-validation and then tested in the validation population. Similar to previous GWAS prior-based methods, the performance of SLDP was mainly affected by the genetic architecture of the traits analyzed. Specifically, SLDP performed better for traits controlled by major quantitative trait loci (QTL) or a small number of quantitative trait nucleotides (QTN). Compared with two commercial SNP chips, genotyping-by-sequencing data, and an unselected whole-genome SNP panel, the SLDP strategy led to significant improvements in prediction accuracy, which ranged from 0.84 to 3.22% for real traits controlled by major or moderate QTL and from 1.23 to 11.47% for simulated traits controlled by a small number of QTN.CONCLUSIONS:The SLDP marker selection method can be incorporated into mainstream prediction models to yield accuracy improvements for traits with a relatively simple genetic architecture, however, it has no significant advantage for traits not controlled by major QTL. The main factors that affect its performance are the genetic architecture of traits and the reliability of GWAS prior information. Our findings can facilitate the application of WGS-based genomic selection.

Studying gene flow between different livestock breeds will benefit the discovery of genes related to production traits and provide insight into human historical breeding. Chinese pigs have played an indispensable role in the breeding of Western commercial pigs. However, the differences in the timing and volume of the contribution of pigs from different Chinese regions to Western pigs are not yet apparent. In this paper, we combine the whole-genome sequencing data of 592 pigs from different studies and illustrate patterns of gene flow from Chinese pigs into Western commercial pigs. We describe introgression patterns from four distinct Chinese indigenous groups into five Western commercial groups. There were considerable differences in the number and length of the putative introgressed segments from Chinese pig groups that contributed to Western commercial pig breeds. The contribution of pigs from different Chinese geographical locations to a given western commercial breed varied more than that from a specific Chinese pig group to different Western commercial breeds, implying admixture within Europe after introgression. Within different Western commercial lines from the same breed, the introgression patterns from a given Chinese pig group seemed highly conserved, suggesting that introgression of Chinese pigs into Western commercial pig breeds mainly occurred at an early stage of breed formation. Finally, based on analyses of introgression signals, allele frequencies, and selection footprints, we identified a ∼2.65 Mb Chinese-derived haplotype under selection in Duroc pigs (CHR14: 95.68–98.33 Mb). Functional and phenotypic studies demonstrate that this PRKG1 haplotype is related to backfat and loin depth in Duroc pigs. Overall, we demonstrate that the introgression history of domestic pigs is complex and that Western commercial pigs contain distinct traces of mixed ancestry, likely derived from various Chinese pig breeds.

Genome-wide association study（GWAS） is an effective method to locate genomic loci that are significantly associated with traits. With the accumulated phenotypic data, the continuous development of high-throughput genotyping technology, and the improved statistical methods, it promotes the wide application of GWAS in area of human disease and animal and plant genetics.False positives are one of the important concerns that impair the reliability of genome-wide association results. To control the false positives, in addition to correcting the P-values, GWAS models have been continuously improved from the naive methods like ANOVA（for quantitative trait） or Chi-square test（for quality trait）, to general linear model（GLM）, which incorporates fixed-effect covariates, to the mixed linear model（MLM）, which incorporates random effects. Fitting individual genetic effects into random effects defined by the genomic relationships matrix（GRM） is commonly adapted currently. Since the parameter estimation of MLM consumes a lot of computational resources, researchers have tried to optimize solving models and constructing GRM（which also improves computing efficiency）, and the time complexity gradually decreased from O（MN3） to O（MN） for MLM-based methods,achieving a great leap in computational speed and statistical efficacy. For inflations caused by unbalanced case-control data,researchers further correct the generalized mixed linear model（GLMM）. This paper comprehensively introduces the basic principles and development of GWAS, with specific emphasis on the model improvement and optimization details. We also list the applications of MLM in GWAS in agriculture, including progress on animals, plants and microbes, as well as the application of haplotype in GWAS. Finally, we give prospects on the future developments of GWAS from the viewpoints of further model optimization and experimental design.

Recently,Worobey et al.(2022)pub-lished a report entitled 'The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19pan-demic'that succinctly summarizes their study[1].A pre-print version of this study had earlier elicited a series of high-profile media coverages[2,3].All these reports deliver a social-political message that the Huanan market is the epicenter of COVID-19.