China\'s local chicken breeds are rich in resources, and have formed different germplasm characteristics in the process of long-term selection and evolution. Scientific assessment of population genetic diversity and identification of inter-breed genetic structure are of great value to the protection and innovative utilization of local chicken breed resource. In order to evaluate the application effectiveness of 23K SNP chip \"Youxin-1\" in the analysis of genetic diversity and genetic structure of local chickens, we used RADseq to identify genomic genetic variation of 21 local chicken breeds and developed 23K chip \"Youxin-1\". The genetic statistics of each variety were calculated based on two sets of SNP data, and correlation, fitting and phylogenetic analysis were carried out to evaluate the application effectiveness of the chip. The results showed that the observed heterozygosity (Ho), polymorphism information content (PIC), inbred coefficient (FROH) and genetic differentiation coefficient (Fst) calculated based on the two SNP data sets were basically consistent in the 21 local chicken breeds. The genetic diversity of Langya chicken (LA), Piao chicken (PJ) and Wenchang chicken (WC) was relatively rich. The genetic diversity of Bian chickens (BJ), Langshan chickens (LS), Gushi chickens (GS), Dongxiang blue-eggshell chickens (DX) and Beijing fatty chickens (BY) was relatively poor, and the correlation coefficients of Ho, PIC, FROH and average Fst in the two groups were 0.794, 0.901, 0.926 and 0.984, respectively, all reaching extremely significant levels (P<0.01) with a high degree of fit (P<0.001) and R2 were 0.644, 0.827, 0.916 and 0.927. For the two sets of SNP data, the evolutionary tree constructed by neighbor-joining (NJ) method and maximum likelihood (ML) method was reasonable, and the 21 local chicken breeds were generally divided into six categories, which was consistent with the formation history and geographical distribution of the varieties. The 23K chip also realized reasonable clustering of the five new varieties without individual deviation. There are some differences in the estimation of genetic statistics using SNP with different densities, and data standardization is needed. 23K chip has good efficacy in the analysis of genetic diversity and structure of local chickens.
我国地方鸡品种资源丰富，且在长期的选择进化过程中形成了各异的种质特性。科学评估群体遗传多样性，明确品种间遗传结构，对地方鸡品种资源的保护与创新利用具有重要价值。为了评估23K SNP芯片“酉芯一号”在地方鸡遗传多样性和遗传结构分析中的应用效力，本文利用RADseq鉴定21个地方鸡种基因组遗传变异，并研发23K芯片“酉芯一号”。基于两组SNP数据集计算各品种的遗传统计量，开展相关性、拟合及系统发育分析，以评估芯片的应用效力。结果表明，基于两组SNP数据集计算的观察杂合度(Ho)、多态信息含量(PIC)、近交系数(FROH)和遗传分化系数(Fst)，在21个地方鸡种中趋势基本一致。琅琊鸡(LA)、瓢鸡(PJ)、文昌鸡(WC)的遗传多样性较为丰富；边鸡(BJ)、狼山鸡(LS)、固始鸡(GS)、东乡绿壳蛋鸡(DX)和北京油鸡(BY)的遗传多样性相对匮乏，两组Ho、PIC、FROH和平均Fst的相关系数分别为0.794、0.901、0.926和0.984，均达到极显著水平(P<0.01)，且拟合度较高(P<0.001)，R2分别为0.644、0.827、0.916和0.927。针对两组SNP数据集，采用邻接法(NJ)和极大似然法(ML)构建的进化树较为合理，将21个地方鸡种总体上分为6大类，与品种的形成历史和地理分布相吻合；23K芯片对5个新增品种亦实现有效聚类，没有出现个体偏离。利用不同密度的SNP估算遗传统计量会存在一定差异，需要进行数据和分析方法的标准化，23K芯片在地方鸡遗传多样性和结构分析中具有较好的效力。.

Genetic drift, gene flow, and natural selection commonly influence population genetic diversity. In populations of self-compatible hermaphrodites, the mating system (e.g., self-fertilization) further reduces individual heterozygosity. Furthermore, selfing, as a form of inbreeding, significantly impacts genetic drift by reducing effective population size (N e). This can potentially accelerate genetic drift, particularly in small populations where self-fertilization is likely during founder events. To investigate the roles of genetic drift and contemporary mating system in populations of the freshwater snail Lymnaea stagnalis, we examined their effective population sizes (N e) and Tajima\'s D values, which reflect genetic drift over extended time periods, as well as estimates of within-population selfing rates and pairwise relatedness reflecting contemporary mating system. We used 4054 SNP markers obtained using restriction site associated DNA (RAD) sequencing from individuals in five snail populations originating from geographically closely located ponds. We found strong population genetic structure and differences in genetic diversity among populations. Covariation between genetic diversity and N e estimates and Tajima\'s D values suggested drift being an important determinant of genetic diversity and structure in these populations. However, this effect was independent of the contemporary mating system, as indicated by the similarity of selfing rates and relatedness estimates among populations. Thus, founder events (possibly including historical inbreeding) and/or drift due to small sizes of L. stagnalis populations are likely to explain their genetic structure and limit within-population genetic diversity.

Henckelia longisepala (H. W. Li) D. J. Middleton & Mich. Möller is a rare and endangered plant species found only in Southeastern Yunnan, China, and Northern Vietnam. It is listed as a threatened species in China and recognized as a plant species with extremely small populations (PSESP), while also having high ornamental value and utilization potential. This study used ddRAD-seq technology to quantify genetic diversity and structure for 32 samples from three extant populations of H. longisepala. The H. longisepala populations were found to have low levels of genetic diversity (Ho = 0.1216, He = 0.1302, Pi = 0.1731, FIS = 0.1456), with greater genetic differentiation observed among populations (FST = 0.3225). As indicated by genetic structure and phylogenetic analyses, samples clustered into three distinct genetic groups that corresponded to geographically separate populations. MaxEnt modeling was used to identify suitable areas for H. longisepala across three time periods and two climate scenarios (SSP1-2.6, SSP5-8.5). High-suitability areas were identified in Southeastern Yunnan Province, Northern Vietnam, and Eastern Laos. Future H. longisepala distribution was predicted to remain centered in these areas, but with a decrease in the total amount of suitable habitat. The present study provides key data on H. longisepala genetic diversity, as well as a theoretical basis for the conservation, development, and utilization of its germplasm resources.

Soybeans (Glycine max L.), originating in China, were introduced to South America in the late 19th century after passing through North America. South America is now a major soybean-producing region, accounting for approximately 40% of the global soybean production. Crops like soybeans gradually adapt to the local climate and human-selected conditions, resulting in beneficial variations during cultivation in different regions. Comparing the phenotypic and genetic variations in soybeans across different regions is crucial to determining the variations that may enhance soybean productivity. This study identified seed-related traits and conducted a genetic diversity analysis using 46 breeding soybean varieties from China and Uruguay. Compared to the Chinese soybean germplasm, the Uruguayan equivalent had a lower 100-grain weight, higher oil content, lower protein content, and higher soluble sugar content. Using ZDX1 gene chips, genetic typing was performed on the 46 breeding varieties. Cluster analysis based on SNP sites revealed significant differences in the genetic basis of Sino-Uruguayan soybean germplasm. Selection analysis, including nucleotide polymorphism (π) and fixation indexes (Fst), identified several genomic regions under selection between Sino-Uruguayan soybean germplasm. The selected intervals significantly enriched gene ontology (GO) terms related to protein metabolism. Additionally, differentiation occurred in genes associated with the oil content, seed weight, and cyst nematodes between Sino-Uruguayan soybean germplasm, such as GmbZIP123 and GmSSS1. These findings highlight the differences in seed-related phenotypes between Sino-Uruguay soybean germplasm and provide genomic-level insights into the mechanisms behind phenotypic differences, offering valuable references for understanding soybean evolution and molecular breeding.

UNASSIGNED: Genome-wide association studies (GWASs) have identified 38 loci associated with ulcerative colitis (UC) susceptibility, but the risk genes and their biological mechanisms remained to be comprehensively elucidated.
UNASSIGNED: Multi-marker analysis of genomic annotation (MAGMA) software was used to annotate genes on GWAS summary statistics of UC from FinnGen database. Genetic analysis was performed to identify risk genes. Cross-tissue transcriptome-wide association study (TWAS) using the unified test for molecular signatures (UTMOST) was performed to compare GWAS summary statistics with gene expression matrix (from Genotype-Tissue Expression Project) for data integration. Subsequently, we used FUSION software to select key genes from the individual tissues. Additionally, conditional and joint analysis was conducted to improve our understanding on UC. Fine-mapping of causal gene sets (FOCUS) software was employed to accurately locate risk genes. The results of the four genetic analyses (MAGMA, UTMOST, FUSION and FOCUS) were combined to obtain a set of UC risk genes. Finally, Mendelian randomization (MR) analysis and Bayesian colocalization analysis were conducted to determine the causal relationship between the risk genes and UC. To test the robustness of our findings, the same approaches were taken to verify the GWAS data of UC on IEU.
UNASSIGNED: Multiple correction tests screened PIM3 as a risk gene for UC. The results of Bayesian colocalization analysis showed that the posterior probability of hypothesis 4 was 0.997 and 0.954 in the validation dataset. MR was conducted using the inverse variance weighting method and two single nucleotide polymorphisms (SNPs, rs28645887 and rs62231924) were included in the analysis (p < 0.001, 95%CI: 1.45-1.89). In the validation dataset, MR result was p < 0.001, 95%CI: 1.19-1.72, indicating a clear causal relationship between PIM3 and UC.
UNASSIGNED: Our study validated PIM3 as a key risk gene for UC and its expression level may be related to the risk of UC, providing a novel reference for further improving the current understanding on the genetic structure of UC.

Spatially isolated plant populations in agricultural landscapes exhibit genetic responses not only to habitat fragmentation per se but also to the composition of the landscape matrix between habitat patches. These responses can only be understood by examining how the landscape matrix influences among-habitat movements of pollinators and seed vectors, which act as genetic linkers among populations. We studied the forest herb Polygonatum multiflorum and its associated pollinator and genetic linker, the bumblebee Bombus pascuorum, in three European agricultural landscapes. We aimed to identify which landscape features affect the movement activity of B. pascuorum between forest patches and to assess the relative importance of these features in explaining the forest herb\'s population genetic structure. We applied microsatellite markers to estimate the movement activity of the bumblebee as well as the population genetic structure of the forest herb. We modelled the movement activity as a function of various landscape metrics. Those metrics found to explain the movement activity best were then used to explain the population genetic structure of the forest herb. The bumblebee movement activity was affected by the cover of maize fields and semi-natural grasslands on a larger spatial scale and by landscape heterogeneity on a smaller spatial scale. For some measures of the forest herb\'s population genetic structure, that is, allelic richness, observed heterozygosity and the F-value, the combinations of landscape metrics, which explained the linker movement activity best, yielded lower AICc values than 95% of the models including all possible combinations of landscape metrics. Synthesis: The genetic linker, B. pascuorum, mediates landscape effects on the population genetic structure of the forest herb P. multiflorum. Our study indicates, that the movement of the genetic linker among forest patches, and thus the pollen driven gene flow of the herb, depends on the relative value of floral resources in the specific landscape setting. Noteworthy, the population genetic structure of the long-lived, clonal forest herb species correlated with recent land-use types such as maize, which have been existing for not more than a few decades within these landscapes. This underscores the short time in which land-use changes can influence the evolutionary potential of long-lived wild plants.

Genetic diversity is an important biological trait for a successful invasion. During the expansion across a new territory, an invasive species may face unprecedented ecological conditions that will determine its demography and genetic diversity. The first record of the yellow-legged hornet (Vespa velutina) in Europe dates back to 2004 in France, from where it has successfully spread through a large territory in the continent, including Italy, Spain and Portugal. Integrative approaches offer a powerful strategy to detect and understand patterns of genetic variation in central and marginal populations. Here, we have analysed the relationship between genetic diversity parameters inferred from 15 V. velutina nuclear DNA microsatellite loci, and geographical and environmental drivers, such as the distance to the introduction focus, environmental suitability and distance to native and invasive niche centroids. Our results revealed a central-marginal dynamic, where allelic richness decreased towards the edge of the expansion range. The low environmental suitability of the territories invaded by marginal populations could prevent a diverse population from establishing and reducing the genetic diversity in populations at the expansion edge. Moreover, Markov chain Monte Carlo analysis showed both geographical and environmental distances were influencing population genetic differentiation. This study highlights the importance of combining genetic analysis with geographical and environmental drivers to understand genetic trends of invasive species to new environment.

Gadopsis (Percichthyidae) is a freshwater genus distributed in south-eastern Australia, including Tasmania, and comprises two recognized species. Previous molecular phylogenetic investigations of the genus, mostly conducted in the pre-genomics era and reflecting a range of geographic and molecular sampling intensities, have supported the recognition of up to seven candidate species. Here we analyze a genome-wide SNP dataset that provides comprehensive geographic and genomic coverage of Gadopsis to produce a robust hypothesis of species boundaries and evolutionary relationships. We then leverage the SNP dataset to characterize relationships within candidate species that lack clear intraspecific phylogenetic relationships. We find further support for the seven previously identified candidate species of Gadopsis and evidence that the Bass Strait centered candidate species (SBA) originated from ancient hybridization. The SNP dataset permits a high degree of intraspecific resolution, providing improvements over previous studies, with numerous candidate species showing intraspecific divisions in phylogenetic analysis. Further population genetic analysis of the Murray-Darling candidate species (NMD) and SBA finds support for K = 6 and K = 7 genetic clusters, respectively. The SNP data generated for this study have diverse applications in natural resource management for these fishes of conservation concern.

Tephritis angustipennis (Diptera: Tephritidae) and Campiglossa loewiana (Diptera: Tephritidae) are phytophagous pests in China. Their damage has significantly impacted the collection and cultivation of germplasm resources of native Asteraceae plants. However, the genetic characteristics and structure of their population are unclear. This study focused on the highly damaging species of T. angustipennis and C. loewiana collected from the three-river source region (TRSR). We amplified the mitochondrial cytochrome C oxidase subunit I (mtCOI) gene sequences of these pests collected from this area and compared them with COI sequences from GenBank. We also analyzed their genetic diversity and structure. In T. angustipennis, 5 haplotypes were identified from 5 geographic locations; the genetic differentiation between France population FRPY (from Nylandia, Uusimaa) and China populations GLJZ (from Dehe Longwa Village, Maqin County), GLDR (from Zhique Village, Dari County), and GLMQ (from Rijin Village, Maqin County) was the strongest. GLJZ exhibited strong genetic differentiation from GLDR and GLMQ, with relatively low gene flow. For C. loewiana, 11 haplotypes were identified from 5 geographic locations; the genetic differentiation between the Chinese population GLMQ-YY (from Yangyu Forest Farm, Maqin County) and Finnish population FDNL (from Nylandia, Uusimaa) was the strongest, with relatively low gene flow, possibly due to geographical barriers in the Qinghai-Tibet plateau. Only 1 haplotype was identified across GLDR, GLMQ, and GLBM. High gene flow between distant locations indicates that human activities or wind dispersal may facilitate the dispersal of fruit flies and across different geographic. Geostatistical analysis suggested a recent population expansion of these 2 species in TRSR. Our findings provide technical references for identifying pests in the TRSR region and theoretical support for managing resistance, monitoring pest occurrences, analyzing environmental adaptability, and formulating biological control strategies for Tephritidae pests on Asteraceae plants.

The last glacial period is known to have greatly influenced the demographic history of temperate forest trees, with important range contractions and post-glacial expansions that led to the formation of multiple genetic lineages and secondary contact zones in the Northern Hemisphere. These dynamics have been extensively studied for European and North American species but are still poorly understood in other temperate regions of rich biodiversity such as the Caucasus. Our study helps filling that gap by deciphering the genomic landscapes of F. orientalis across the South Caucasus. The use of genome-wide data confirmed a past demographic history strongly influenced by the Last Glacial Maximum, revealing two disjunct glacial refugia in the Colchis and Hyrcanian regions. The resulting patterns of genetic diversity, load and differentiation are not always concordant across the region, with genetic load pinpointing the location of the glacial refugia more efficiently than genetic diversity alone. The Hyrcanian forests show depleted genetic diversity and substantial isolation, even if long-distance gene flow is still present with the main centre of diversity in the Greater Caucasus. Finally, we characterize a strong heterogeneity of genetic diversity and differentiation along the species chromosomes, with noticeably a first chromosome showing low diversity and weak differentiation.