Morphometric characteristics, genetic profile, and histology of Nile tilapia in Mwenga Territory, South Kivu

The minor carp, Aspidoparia morar is a benthopelagic fish belonging to the sub-family Danioninae under the family Cyprinidae. It has emerged as the single most dominant species in the river Brahmaputra in Assam. In the present study, 240 specimens were collected from Guwahati and Tezpur in the Brahmaputra River and Silchar in the Barak River to investigate the morphometric and meristic variation among the populations. For this a total of 20 morphometric traits and 11 meristic traits were studied. The mean lengths for most of the morphometric traits were higher for the Barak River except eye diameter, inter orbital length and anal fin length which were significantly higher on the Brahmaputra River, while the post orbital length and pelvic fin length were found to be almost equal. The regressions of standard length with all the morphometric traits except pelvic fin length, pelvic fin base, pectoral fin length, dorsal fin length, anal fin length, pre orbital length, post orbital length, inter orbital length and eye diameter showed significant variation between the rivers. Two meristic traits viz. branched rays in anal fin and gill rakers on the first gill arch also showed significant variation in the samples of the rivers.

Tenualosa ilisha (matured/adult) and jatka (immature/young), locally known as Ilish, is designated as the national fish of Bangladesh. Both the stages were collected from different fish markets from Savar, Bangladesh during the exploration. This study was carried out on comparative morphometric, meristic and osteology between the Tenualosa ilisha (matured) and jatka (immature/young). The morphometric characteristics were higher in matured Tenualosa ilisha than immature jatka and among them head length, pre-dorsal length, postorbital length, the height of anal fin, eye diameter length, and abdominal region length were found significantly different. The proportion of standard length and snout length, head length and snout length, abdominal region length and standard length were significantly different between the two stages. Among the meristic characteristics; number of dorsal fin rays, anal fin rays and scales on the lateral line were found with little differences between matured hilsa and jatka. There are very small differences in the number of scales, scutes and fin rays of different fins between the two stages of fishes. The osteological comparison reveals more or less identical structure. Most of the bones of the skull were similar in structure but differed in size, shape and thickness.

A research study on morphometrics of Kalophrynus palmatissimus (commonly known as Lowland Grainy Frog) at Ayer Hitam Forest Reserve (AHFR), Selangor and Pasoh Forest Reserve (PFR), Negeri Sembilan was carried out from 12 November 2016 to 13 September 2017. The study was to examine data on the morphometric traits of K. palmatissimus at the two forest reserves. 15 morphometric traits of K. palmatissimus that were taken by using vernier calipers. Frog surveys were done by using 15 and 18 nocturnal 400 m transect lines with an interval distance of 20 m at AHFR and PFR, respectively. The GPS coordinates for all frog samples were recorded to ensure the precise geographic location. In addition, five climatic data were recorded. The results showed that most morphometric traits in AHFR (n = 34) and PFR (n = 31) were positively correlated with each other. On the other hand, climatic factor, which was soil pH, had a significant positive influence on most of the morphometric traits (p < .01), except for tympanum diameter and upper eyelid width (p ≥ .05). Meanwhile, the temperature had a significantly negative influence on all morphometric traits (p < .01). General linear model (GLM) analysis showed that snout‐vent length (SVL) influenced most morphometric traits (F ≤ 80.86, p < .01), except for hand length (HAL: F = 0.299, p > .05). Later, it was found that the snout‐vent length of K. palmatissimus at AHFR was slightly larger than at PFR (AHFR: μ = 37.00 mm, SE = 1.16 c.f. PFR: μ = 30.29 mm, SE = 1.07). It showed that there were variations in morphometric traits of K. palmatissimus at AHFR and PFR. From PCA analysis, morphometric traits are grouped into two components for AHFR and PFR, respectively. In AHFR, head length, eye diameter, head width, internarial distance, interorbital distance, forearm length, tibia length, foot length, and thigh length were strongly correlated, while snout length and eye‐nostril distance were strongly correlated. In PFR, eye diameter, head width, internarial distance, interorbital distance, foot length, and thigh length were strongly correlated, though snout length and eye‐nostril distance were strongly correlated, hence, suggested that all morphometric traits grow simultaneously in K. palmatissimus with eye‐nostril distance (EN), and snout length (SL) growing almost simultaneously at AHFR (r = .91) and PFR (r = .97). There is still a lack of available information regarding the distribution and morphometric studies of K. palmatissimus in Malaysia, especially at AHFR and PFR. This study showed 15 different morphometric traits of K. palmatisssimus between AHFR and PFR, with K. palmatissimus at AHFR were found to be slightly larger than at PFR.

PDF HTML阅读 XML下载 导出引用 引用提醒 不同生长期圆斑星鲽形态性状对体重影响的通径分析 DOI: 作者: 作者单位: 1. 中国水产科学研究院 黄海水产研究所, 山东 青岛 266071;2. 上海海洋大学 水产与生命学院, 上海 201306;3. 天津渤海水产研究所, 天津 300457 作者简介: 边力(1988-),男,助理研究员,博士,研究方向为鱼类繁育与遗传育种.E-mail:bianli@ysfri.ac.cn 通讯作者: 中图分类号: S96 基金项目: 天津市农业科技成果转化与推广项目（201604100）；中国水产科学研究院黄海水产研究所基本科研业务费（20603022016005）. Path analysis of effects of morphometric traits on body weight in spotted halibut Verasper variegatus at different growth stages Author: Affiliation: 1. Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China;2. College of Fisheries and Life Science, Shanghai Ocean University, Shanghai 201306, China;3. Tianjin Bohai Sea Fisheries Research Institute, Tianjin 300457, China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:圆斑星鲽（）作为中国鲽形目（Pleuronectiformes）养殖鱼类的重要代表种类，具有生长速度快，可食用部分多，肉质细嫩等特点。为了探究圆斑星鲽形态性状与体重的关系，本研究分别测定11月龄、14月龄和17月龄3个不同生长期圆斑星鲽的体重及全长（FL）、体长（BL）、体高（BH）、头长（HL）、头高（HH）、尾柄长（CL）、尾柄高（CH）、吻长（SL）共计8个形态性状，分别进行相关分析和通径分析，剖析形态性状对于体重的直接作用和间接作用；利用回归分析的方法，建立各个时期以形态指标为自变量，体重为因变量的最优线性回归方程。结果显示，1）不同生长阶段，影响体重的重点形态指标存在差异，影响11月龄圆斑星鲽体重的主要形态性状为体高和体长，14月龄阶段为全长、体高和头长，17月龄阶段为全长和体高；2）11月龄、14月龄和17月龄形态性状对体重（BL，XHL，；3）除本研究所包括的形态指标外，体厚可能为另外一个影响圆斑星鲽体重的重要指标。本研究阐明了体重与形态指标间的相关关系，为圆斑星鲽的良种选育提供了生物学依据。 Abstract:is an important representative species of the Pleuronectiformes. It has a fast growth rate, most parts of its body are edible, and the meat is tender and delicious; all these features make a good aquaculture candidate. In order to explore the relationship between morphometric traits and body weight in , full length (FL), body length (BL), body height (BH), head length (HL), head height (HH), caudal peduncle length (CL), caudal peduncle height (CH), snout length (SL), and body weight (BW) of at 11, 14, and 17 months of age were measured. Correlation and path analysis were conducted, and the effects of each morphometric trait on body weight were separated into direct and indirect effects. Regression analyses were conducted with morphological traits as independent variables and body weight as the dependent variable at each growth stage. The results showed that (1) different morphometric traits had significant path coefficients at each growth stage; at the 11 month stage, the morphometric traits that significantly affected body weight were BH and BL, at the 14 month stage, the significant morphometric traits were FL, BH, and HL, at the 17 month stage, the significant traits were FL and BH. (2) The regression equations at 11, 14, and 17 months of age were =-362.484+13.145, and , respectively. (3) Besides the morphometric traits included in this study, body thickness is another potentially important trait that can affect body weight. This study demonstrated the relationship between morphometric traits and body weight. The results provide valuable information and theoretical guidance for breeding programs. 参考文献 相似文献 引证文献

The main objective of this study was to analyse the differences in morphometric characteristics among specimens of Atlantic juvenile bluefin tuna Thunnus thynnus [12.2–46.5 cm fork length (FL)] and juvenile little tuna Euthynnus alletteratus (14.1–26.4 cm FL). A total of 353 bluefin tuna (young of the year) and 288 little tuna (young of the year) were collected from the commercial hand line fisheries in the eastern Mediterranean Sea between July and October of 2011–2013 with three round-bent hook sizes (numbers 10, 12 and 14; Mustad 2315S). By using univariate and multivariate analysis, 11 morphometric characters were investigated. anova revealed highly significant differences (P < 0.001) for all morphometric parameters among the two species. The principal component analysis showed that the difference between the species resulted mainly from preanal length (LA), caudal fin hight (CC), snout length (SnL), eye diameter (ED) and postorbital length (PO). The stepwise discriminant analysis revealed that juveniles of the two tuna species were correctly classified, with a percentage of 99.2%. Length of pectoral fin (LP) was the strongest predictor in the discriminant functions.

Possible contamination related to mining activities might contribute with other risk factors in increasing the burden of birth defects (BDs) in many developing countries including the Democratic Republic of Congo. The subsequent prevalence is frequently underestimated. Implementation of focused public health interventions is hindered by the paucity of comprehensive data. We assessed the potential impact of mining on the prevalence and occurrence of visible BDs in neonates in South Kivu (SK). A hospital-based cross-sectional study was conducted among 65,474 newborns registered in 7 hospitals in SK from 2016-2021. Hospitals were categorized based on mining activities in their respective catchment areas. Living in a mining zone was the exposure, whereas the outcome was visible BDs. Prevalence was estimated per 100,000 live births, and risk of occurrence with odds ratio (OR) and their 95% confidence interval. 261 neonates with visible BDs were recorded accounting for a prevalence of 399 cases per 100,000 live births. The prevalence ranges between 217 and 1365 cases per 100,000 live births. An increased risk was found in mining zones(OR=2.07; 95%CI=1.59-2.68), Mubumbano(OR=1.72, 95%CI=1.22-2.43), and Mwenga(OR=3.89, 95%CI=2.73-5.54), whereas a reduced risk was reported in non-mining zones(OR=0.48, 95%CI=0.37-0.62) in Katana (OR=0.49, 95%CI=0.33-0.73). Musculoskeletal(28.74%) and central nervous systems(19.92%) were the most common BDs. A significant difference in prevalence for BDs involving the face, GI system and abdominal wall, musculoskeletal, central nervous and genitourinary systems between mining and non-mining zones was found(p<0.001). There is an excessive risk for visible BDs in areas with hazardous mining activities in SK region.​​ More complex studies are needed to define the possible causal relationship. Moreover, findings generated herein should be corroborated by other research design, periodically monitored by public health authorities, and used to inform initiatives promoting enhanced environmental health, access to pediatric surgical care, and public health campaigns aimed at decreasing risk of BDs.

Morphological differences, including growth-related changes, were examined in three morphologically similar East Asian sea bass species, Lateolabraxjaponicus, L.maculatus and L.latus. In many cases, body measurements indicated specific patterns of growth-related proportional changes. Lateolabraxlatus differed from the other two species in having greater body depth, caudal peduncle depth, caudal peduncle anterior depth, snout length, and upper and lower jaw length proportions. In particular, scatter plots for caudal peduncle anterior depth relative to standard length (SL) in that species indicated complete separation from those of the other two species, being a new key character for identification. Comparisons of L.japonicus and L.maculatus revealed considerable proportional differences in many length-measured characters, including fin lengths (first and second dorsal, caudal and pelvic), snout length, post-orbital preopercular width (POPW) and post-orbital length. In particular, snout length (SNL) and POPW proportions of the former were greater and smaller for specimens >200 and ≤ 200 mm SL, respectively. Because the scatter plots of these proportions for the two species did not overlap each other in either size range, identification of the species was possible using a combination of the two characters. In addition, scatter plots of the POPW / SNL proportion (%) of L.japonicus and L.maculatus were almost completely separated throughout the entire size range examined (border level 90%), a further aid to identification. The numbers of pored lateral line scales and scales above the lateral line tended to increase and decrease with growth, respectively, in L.japonicus, whereas scales below the lateral line and gill raker numbers tended to increase with growth in L.maculatus. Because the ranges of these meristic characters may therefore vary with specimen size, they are unsuitable for use as key characters. Accordingly, a new key is proposed for the genus Lateolabrax.

The study aimed at describing objectively the interdependence among the morphological and heat tolerance traits of Nigerian indigenous pigs and to predict body weight from conformation traits. Data on body weight, eight linear body measurements (BL, CG, CD, WH, RH, EL, SL and TL) and three thermo-physiological parameters were measured on 150 randomly selected pigs of three growth stages (piglets, growers and finishers) from February to December, 2020. The animals were managed in an extensive system in Plateau State, north central Nigeria. General linear model was used to study growth stage and sex effects including their interaction. Multivariate principal component analysis was used for the size, shape and heat tolerance determination while the animals were classified using canonical discriminant analysis. The stepwise regression was used for body weight prediction. The results showed that finishers had significantly higher (P&lt;0.05) body weight, body length, chest girth, chest depth, withers height, rump height, ear length, snout length and tail length, followed by growers while the least values were recorded in piglets. Pulse rate was not significantly different (P&gt;0.05) between piglets and finishers, although the latter had higher respiratory rate (39.48±0.53 vs. 39.90±0.53 vs. 36.77±0.75). However, rectal temperature was similar (P&gt;0.05) among the three pig categories. With the exception of tail length, sexual dimorphism was observed in all the morphometric traits with higher values recorded for males. However, the three thermo-physiological traits were not affected by sex (P&gt;0.05). BW was highly and positively correlated with most biometric traits (r = 0.80-0.93, 0.66-0.80 and 0.83-0.93; P&lt;0.01 for piglets, growers and finishers, respectively). Three principal components (PC1, PC2 and PC3) were extracted for optimal balance of the animals. Withers height, ear length and body weight were found to be the most discriminating variables to separate the pig categories. Classification results showed that 100% of piglets, 96.7% of growers and 96.7% of finishers were correctly assigned to their distinct populations. The present Information could be exploited in devising appropriate management and breeding programs for tropically adapted pigs in Nigeria.

This study investigates the cpDNA sequences from six Hevea species, aiming to explore their genomic characteristics, gene content, and genetic relationships. The objectives include understanding the structure of these genomes, identifying potential gene rearrangements, and providing insights into genetic improvement and conservation strategies for the Hevea genus. cpDNA sequences from six Hevea species were sequenced and analyzed. Genome sizes, GC content, gene encoding potential, and structural integrity were assessed. Simple sequence repeats (SSRs) and codon usage were analyzed, with a focus on optimal codons and their frequency. Phylogenetic analysis was conducted to determine the genetic relationships within the Hevea genus. The cpDNAs from the six species exhibited genome sizes ranging from 161,093 bp to 161,254 bp, with GC content between 35.72% and 35.75%. Each genome contained 91 to 92 protein-coding genes, with the infA gene consistently present. No significant gene rearrangements were detected, and SSR analysis revealed mono-repeats primarily composed of A/T bases. Codon usage analysis indicated that leucine is predominantly encoded by the UUA codon, and 31 optimal codons were identified, mainly ending in A or U. Phylogenetic analysis clarified the genetic relationships among the species. The study provides detailed insights into the cpDNA characteristics of Hevea species, highlighting stable genome structures, conserved genes, and specific patterns of codon usage. These findings are valuable for conservation efforts, genetic improvement strategies, and the sustainable use of Hevea germplasm.

BackgroundWhole-genome sequence (WGS) data give access to more complete structural genetic information of individuals, including rare variants, not fully covered by single nucleotide polymorphism chips. We used WGS to investigate the amount of genetic diversity remaining after selection using optimal contribution (OC), considering different methods to estimate the relationships used in OC. OC was applied to minimise average relatedness of the selection candidates and thus miminise the loss of genetic diversity in a conservation strategy, e.g. for establishment of gene bank collections. Furthermore, OC was used to maximise average genetic merit of the selection candidates at a given level of relatedness, similar to a genetic improvement strategy. In this study, we used data from 277 bulls from the 1000 bull genomes project. We measured genetic diversity as the number of variants still segregating after selection using WGS data, and compared strategies that targeted conservation of rare (minor allele frequency <5 %) versus common variants.ResultsWhen OC without restriction on the number of selected individuals was applied, loss of variants was minimal and most individuals were selected, which is often unfeasible in practice. When 20 individuals were selected, the number of segregating rare variants was reduced by 29 % for the conservation strategy, and by 34 % for the genetic improvement strategy. The overall number of segregating variants was reduced by 30 % when OC was restricted to selecting five individuals, for both conservation and genetic improvement strategies. For common variants, this loss was about 15 %, while it was much higher, 72 %, for rare variants. Fewer rare variants were conserved with the genetic improvement strategy compared to the conservation strategy.ConclusionsThe use of WGS for genetic diversity quantification revealed that selection results in considerable losses of genetic diversity for rare variants. Using WGS instead of SNP chip data to estimate relationships slightly reduced the loss of rare variants, while using 50 K SNP chip data was sufficient to conserve common variants. The loss of rare variants could be mitigated by a few percent (up to 8 %) depending on which method is chosen to estimate relationships from WGS data.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0210-4) contains supplementary material, which is available to authorized users.

Resources and resourcefulness: Roles, opportunities and risks for women working at artisanal mines in South Kivu, Democratic Republic of the Congo

Context Chickens are the most important livestock in the Democratic Republic of Congo in particular and in Africa in general; they are kept for their meat and eggs for nutrition and economic status. The availability of chicken diversity information is very important in selection of breeds and in conservation of genetic resources. Aims This study aimed to determine allelic variability, genetic diversity, and genetic relationships of the indigenous chicken populations from the South Kivu region to support breeding programs and genetic resource conservations. Methods The LEI0258 microsatellite marker within the major histocompatibility complex gene region was used for genotyping. The LEI0258 locus amplicon sequences of 163 indigenous chickens were analysed. Key results The number of R13 and R12 repeats varied from 1 to 21 and from 3 to 21 respectively, whereas several combinations of indels and single-nucleotide polymorphisms were observed in the microsatellite flanking regions. In total, 45 different LEI0258 alleles ranging from 193 to 473 bp were determined, including 14 private alleles (Np). Expected heterozygosity (He) varied from 0.864 (Mwenga) to 0.938 (Bukavu), with a mean of 0.911, and observed heterozygosity (Ho) ranged from 0.417 (Uvira) to 0.667 (Mwenga), with a mean of 0.519. The analysis of molecular variance (AMOVA) showed higher genetic variation within individuals (56%) than among individuals (43%) and among chicken populations (1%). Clustering into three admixed gene pools (K = 3) showed the relationships among the chicken populations. Conclusion The present study showed the existence of high genetic diversity in chicken populations from South Kivu. Implications This study provides information useful for better conservation and breeding strategies of indigenous chicken populations in South Kivu.

King Coconut (KC) is an indigenous and highly valuable germplasm resource in Sri Lanka. Yet, KC populations' genetic diversity, relationships, and conservation strategies are not fully understood. Indigenous old KC populations have been dispersed across a few ancient villages in Sri Lanka. Five geographically dispersed locations were selected in Sri Lanka, and 20 KC individuals from each location were collected for the current study. Six randomly selected samples from every geographical location, together with the standard two Sri Lanka Red Dwarf and two Sri Lanka Tall varieties were initially genotyped using 21 SSR markers for polymorphism. Based on the results, ten polymorphic SSR markers were selected and used for genotyping. Power Marker, STRUCTURE, and GenAlex software were used for the SSR genetic analysis. Results revealed 0.62 mean Gene Diversity (Hs), 4.2 mean allele number, and 0.55 polymorphic information content (PIC). Clear differentiation of populations was observed with the STRUCTURE and UPGMA dendrogram. Single branching in the UPGMA dendrogram for Anuradhapura and Marandawila KC populations revealed high genetic uniformity over multi-branched Kadugannawa and Colambageara populations. According to AMOVA, 64% of the genetic variation has been partitioned among populations, indicating moderate population differentiation. Detail analysis, including a higher number of KC populations and systematic molecular analysis using more SSRs/SNPs needed in the future before implementing conservation and utilization strategies.

The following supplementary material is available online for this article at http://onlinelibrary.wiley.com/doi/10.1111/jse.12938/suppinfo: Fig. S1. The geographical location of this individual and Records of Empress Wude. Fig. S2. Proportion of C > T and G > A substitutions in human DNA across DNA fragments in the Ashina individual. The red curve represented C > T substitutions that increased at the 5′-end and the blue curve represented G > T substitutions that increased at the 3′-end, as expected for authentic ancient DNA. Fig. S3. Detailed principal component analysis (PCA) of 1667 Eurasian exhibited the west–east Eurasian cline and north–south Eastern Eurasian cline. The Ashina individual fell within present-day and ancient Eastern Eurasians along PC2, and clustered with modern Tungusic and Mongolic speakers, ancient populations in Northeast Asia and eastern Mongolia Plateau, especially the populations previously referred to as "Ancient Northeast Asian" (ANA) that are genetically homogeneous hunter-gatherers from Northeast Asia ("Baikal_EN", 5200–4200 BCE, "Mongolia_N", 6000–4400 BCE, "AR_EN", 5500–5300 BCE, and "DevilsCave_N", 5700 BCE) and post-Iron Age East Steppe nomadic people including Xianbei, Rouran, Khitan and part of Mongols. Fig. S4. ADMIXTURE results for selected Eurasians for K = 2–6. A, Cross-validation (CV) errors for the ADMIXTURE analysis based on 1240 K data set. B, CV errors for the ADMIXTURE analysis based on HO data set. C, ADMIXTURE results for K = 2–6 based on 1240 K data set. After pruning for linkage disequilibrium, the number of SNPs included in this analysis was 871 858, the included modern populations were from HGDP. D, ADMIXTURE results included Turkic populations for K = 2–6 based on HO data set. The number of included SNPs was 279 737. The ADMIXTURE analyses base on 1240 K and HO data set both revealed two summarized ancestries in Ashina: one related to West Eurasian ancestry, the dominating one associated with East Eurasians including ANA and southern ancestry. The results of ADMIXTURE also presented the genetic discrepancy among Ashina, earlyMed_Turk and CentralSteppe_Turk and the genetic heterogeneity among Ashina and present-day Turkic-speaking populations. Fig. S5. Close genetic relationship between ancient and present-day Eurasian populations and geographically different individuals of the Türkic Khaganate. We presented top 60 outgroup-f3 signal for each different group of the Türkic Khaganate. Horizontal bars represent the point estimate ±3 standard error. The outgroup-f3 of Ashina showed the close genetic affinity with East Eurasians than West Eurasians, especially northern East Eurasian. earlyMed_Turk who sampled in Mongolia Plateau presented close genetic relationship with East Eurasians, especially Rouran.The CentralSteppe_Turk harbored similar genetic relationship with Eurasians. Fig. S6. f Statistics in forms of f4 (X, Mbuti; Ashina, pre-Iron Age Northeast Asian populations) and f4 (pre-Iron Age Northeast Asian populations, Mbuti; Ashina, X) test whether pre-Iron Age Northeast Asian populations make contribution to the formation of Ashina. Darker orange and blue squares showed sharing at |Z-score | > 6. Blue and orange squares show sharing at 3 < |Z-score | <6. Gray squares indicate significantly less sharing at the same threshold. A, f4 (X, Mbuti; Ashina, pre-Iron Age Northeast Asian populations) showed Ashina formed a genetic clade together with Neolithic hunter-gatherers in Northeast Asia including Amuer River, Mongolia Plateau and DevilsCave, Baikal Lake (Russia_Shamanka_Eneolithic). In addition, Ashina showed close genetic affinity with population related to Bronze Age SlabGrave and Ulaanzukh culture in Mongolia Plateauwho harbors dominating ANA ancestry. B, f4 (pre-Iron Age Northeast Asian populations, Mbuti; Ashina, X) further provided evidence that ancestry related to hunter-gathers in Northeast Asia dedicated to the gene pool of Ashina as reflected in significantly positive f4 with the exception of Sino-Tibetan populations. Fig. S7. The analysis of f4 (West Eurasian, Mbuti; Ashina, East Eurasian) detected whether gene influx from West Eurasian flowed into the gene pool of Ashina basing on 1240 K data set. A–L, West Eurasians included West Steppe nomadic populations from Bronze Age to Iron Age, Anatolian and Iranian farmers, East hunter-gatherers (EHG), ANE (MA1, Ancient North European) and Botai and the Bactria-Margiana Archaeological Complex (BMAC) of Central Asia. East Eurasian included reported population without gene flow from West Eurasian in previous studies. Different shapes represented different Z-scores of f4. The results showed the gene pool of Ashina was influenced by the eastward migration of West Steppe pastoralists and the population related to BMAC who was attested to migrated along Inner Asia Mountains Corridor into the Mongolia Plateau and influenced ancient Tianshan and Mongolian people (f4 > 0). The detected Anatolia farmers, EHG and Iranian farmers, Botai-related ancestry in Ashina might be mediated by the eastward migration of West Steppe pastoralists and BMAC, respectively. Fig. S8. The significantly genetic heterogeneity within the Türkic Khaganate. A, B, The genetic divergency in individuals of the Türkic Khaganate revealed by f4(X, Mbuti; Ashina, earlyMed_Turk/CentralSteppe_Turk) showing earlyMed_Turk/CentralSteppe_Turk harbored more allele with West Eurasian than Ashina. A, earlyMed_Turk. B, CentralSteppe_Turk. Fig. S9. The genetic relationship of Ashina with Iron-Age Tianshan nomadic populations. A–C, The results of f4 in form of f4 (X, Mbuti; Ashina, Kazakhstan_Kanju/Kazakhstan_Wusun/Kyrgzstan_TianshanHun) all showed Iron-Age Tianshan nomadic people harbored diverse genetic profile with Ashina with more genetic affinity with West Eurasian and West Siberian hunter-gatherers (WSHG). In contrast, Ashina shared more allele with East Eurasians than Iron-Age Tianshan nomadic populations. Different shapes represented different Z-score. Fig. S10. The genetic relationship of Ashina with Xiongnu populations in different periods. Jeong et al. ( 2020) split early Xiongnu into two subgroups, earlyXiongnu_west (SKT010, SKT001, SKT003, SKT009, SKT008, AST001) and earlyXiongnu_rest (JAG001, SKT002, SKT004, SKT005, SKT006, SKT012), based on their individual genetic modeling results. A, B, The results of f4 in form of f4 (X, Mbuti; Ashina, earlyXiongnu_rest/earlyXiongnu_west) showed Ashina shared more genetic affinity with East Eurasians than early Xiongnu. The genetic discrepancy with Ashina was different in earlyXiongnu_rest and earlyXiongnu_west, showing the genetic affinity with ancient populations in Northeast Asia and Mongolia Plateau was similar in earlyXiongnu_rest and Ashina (no significant Z-score). While that genetic profile did not exist in earlyXiongnu_west who harbored more West Eurasian affinity than Ashina. C–E, The results of f4 in form of f4 (X, Mbuti; Ashina, lateXiongnu/lateXiongnu_han/lateXiongnu_sarmatian) presented the difference of harboring genetic relationships with Asina among late Xiongnu: late Xiongnu shared similar genetic affinity to ancient Northeast Asians with Ashina (non-significant Z-score when X included Northeast Asian populations), lateXiongnu_han possessed semblable genetic profile with Ashina (non-significant Z-score, except for AR_EN), that contrasted with lateXiongnu_sarmatian who shared more genetic affinity with West Eurasians than Ashina (significantly negative Z-score when X was West Eurasian populations). Fig. S11. The genetic relationship of Ashina with contemporary East Steppe nomadic populations including Xianbei and Rouran. A–C, The result of f4 in form of f4(X, Mbuti; Ashina, AR_Xianbei_IA/Mongolia_Xianbei/Rouran) revealed the genetic homogeneity of Ashina with Xianbei and Rouran (no significant Z score). Fig. S12. The genetic relationship of Ashina with Mongolic and Tungusic East Steppe pastoralists after the Türkic Khanate. (A–C) The result of f4 in form of f4(X, Mbuti; Ashina, lateMed_Khitan/lateMed_Mongol/Russia_Heishui_Mohe_early_Medieval) demonstrated the discrepancy of genetic relationship with Ashina in Khitan and Mongol empire; Mongolic Khitan and Tungusic Heshui_Mohe had genetic similarity with Ashina, while Mongols in Mongol empir period showed genetic differentiation with Ashina. Fig. S13. The genetic relationship of Ashina with historically Turkic-speaking pastoralists of Central Steppe after the collapse of the Türkic Khaganate. A–E, The result of f4 in form of f4 (X, Mbuti; Ashina, Kimak/KaraKhanid/Uigur/Karluk/Kipchak) indicated the high genetic differentiation between Ashina and later Turkic-speaking pastoralists of Central Steppe including Kimak, KaraKhanid, Uigur, Karluk and Kipchak Khaganate. The Central Steppe pastoralists had evident genetic affinity with West Eurasians (significantly negative Z-score when X included West Eurasians), indicating the prominent ancestry from West Eurasian in the Central Steppe pastoralists, that contrasted with Ashina who harbored dominating ancestry from Northeast Asian. Fig. S14. The genetic relationship of Ashina with Central Steppe pastoralists in Medieval period. A–C, The result of f4 in form of f4(X, Mbuti; Ashina, Kazakhstan_His/Kazakhstan_GoldenHordeAsian/CentralSteppe_Medieval_Nomad) showed diverse genetic relationship with Ashina among Central Steppe pastoralists in Medieval period. Kazakhstan_GoldenHordeAsian formed a genetic clade together with Ashina, which indicating the similar genetic profile between them. However, Kazakhstan_His and CentralSteppe_Medieval_Nomad showed closer genetic affinity with West Eurasians than Ashina. Fig. S15. Genetic heterogeneity of the Türkic Khaganate. Heatmap of P-value of pairwise qpWave among post-Iron Age Central/East Steppe pastoralists. "++" represented values greater than 0.05, and "+" represented values <0.05 and >0.01. Computations were based on the outgroup set (Mbuti.DG + Onge.DG + Russia_MA1_HG.SG + Russia_Kostenki14.SG + Iran_GanjDareh_N + Kazakhstan_Eneolithic_Botai.SG + Russia_Sintashta_MLBA.SG + AR19K + Mongolia_N_North+UpperMid_YR_LN). Fig. S16. The genetic relationship with Ashina of present-day Altaic-speaking populations. A, We conducted f4(X, Mbuti; Ashina, Tungusic/Mongolic/Turkic) to investigate the genetic relationship of present-day Altaic populations with Ashina, and found that Mongolic and Tungusic speakers formed genetic clade with Ashina, and influenced by additional gene flow from millet farmers in Yellow River or West Eurasian in some groups (negative Z-score). By contrast, Turkic populations showed extremely disparate genetic profile with Ashina with the exception of Yakut, Dolgan, Tuvinian and Salar who presented some extent of genetic affinity with Ashina. B, We further performed f4 (Mbuti, Ashina; Tungusic/Mongolic, Turkic) to provide robust evidence of supporting the close genetic affinity with Ashina in Tungusic and Mongolic populations rather than in Turkic populations. Tungusic and Mongolic speakers did have closer genetic relationship with Ashina than Turkic populations (Z < -3). "-"represented −6 < Z-score < −3; "--" represented Z-score < −6; "+" represented 3 < Z-score < 6; "++" represented Z-score >6. C, The result of f4 (Mbuti, Ashina; Tungusic, Mongolic) further revealed Tungusic population shared more alleles with Ashina than Mongolic populations as reflected in significantly negative f4 values with the exception of Eavek_FastEast. Fig. S17. The genetic affinity between Turkic-speaking populations and ancient populations related with the diffusion of Turkic language. Heatmap of P-value of pairwise qpWave among Turkic-speaking populations and ancient populations related with the diffusion of Turkic languages. The genetic relationships between Turkic-speaking population and ancient populations associated with the diffusion of Turkic language revealed the significantly genetic differentiation of Ashina/earlyMed_Turk/earlyXiongnu/lateXiongnu/earlyMed_Uigur and Turkic-speaking populations (P < 0.01), CentralSteppe_Turk formed pairwise clade with Uzbek and Dolgan, the formed pairwise clades existed in other pairwise combination, including pairwise combination of Kimak with Tatar_Siberian, Uyghur, Karakalpak, Nogai_Astrakhan, Nogai_Stavropol and Uzbek, pairwise combination between lateXiongnu to Karakalpak (P > 0.05). "++" represented values >0.05, and "+" represented values <0.05 and >0.01. Computations were based on the outgroup set (Mbuti.DG + Onge.DG + Russia_MA1_HG.SG + Russia_Kostenki14.SG + Iran_GanjDareh_N + Anatolia_N + CHG + AR19K + Mongolia_N_North+UpperMid_YR_LN). Fig. S18. The potential East Eurasian ancestral source of Turkic population. We performed f4(X, Mbuti; Pop, Turkic) to further determine whether other East Eurasians are more suited to explain the East Eurasian ancestry of Turkic than Ashina. X was chosen from representative populations including Chuanyun (the Southern East Asian), YR_LN (millet farmers in Yellow River), Russia_Sintashta_MLBA and Botai. Pop included other potential East Eurasian ancestral source of Turkic-speakers. We observed that Ashina was more suited to approximate East Eurasian ancestry of Turkic populations where Z-scores of f4 (X, Mbuti; Ashina, Turkic) tended to approach to zero. Supplementary Document. Section 1 Archaeological Site and Sample Description of the Xiaoling Mausoleum. Section 2 Material and Methods. Section 3 Ancient Data Analyses and Genetic Characterization of Ancient Individual. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

This study assessed the phenotypic and genetic relationships among three Nigerian indigenous goat breeds, Sahel (SAH), Sokoto Red (SOR), and West African Dwarf (WAD), using morphometric traits and growth hormone (GH) gene markers. Body weight (BWT) and body linear measurements, including height at withers (HW), body length (BL), heart girth (HG), paunch girth (PG), and ear length (EL), were recorded to evaluate phenotypic diversity. Significant differences (P&lt;0.05) were observed across all traits, with SAH goats exhibiting the largest body dimensions and WAD goats the smallest. Blood samples, about 3 mL, were aseptically collected and preserved in EDTA tubes at -4°C for genomic DNA extraction and analysis. The GH gene was amplified using PCR, followed by electrophoresis and allele analysis. WAD goats showed the highest genetic variability, with a mean effective allele count of 1.79±0.06 and observed heterozygosity of 0.30±0.10, while SAH goats exhibited the lowest (1.49±0.02 and 0.10±0.10, respectively). Genetic similarity was highest between SOR and SAH (0.9930) and lowest between WAD and SAH (0.9877), with corresponding genetic distances of 0.0070 and 0.0124. A phylogenetic dendrogram grouped SOR and SAH together, with WAD forming a distinct branch, reflecting ecological and geographical divergence. These findings underscore the moderate genetic diversity and phenotypic variation among Nigerian indigenous goat breeds and highlight the importance of conservation and selective breeding strategies to improve productivity and adaptability. Keywords: breeds, diversity, goats, genetic distance, genetic similarity, phylogeny