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Figure 2 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 2 The structure of Lateolabrax maculatus mitochondrial genome. The total length of mitochondrial genome of L. maculatus was 16,601 bp comprising 13 protein-coding genes (PCGs), 2 rRNA genes and 22 tRNA genes. 249 high-confidence single nucleotide polymorphism (SNP) sites and 24 indels was identified in 85 individuals.
Figure 1 from: Gong J, Chen B, Li B, Zhou Z, Shi Y, Ke Q, Zhang D, Xu P (2020) Genetic analysis of whole mitochondrial genome of Lateolabrax maculatus (Perciformes: Moronidae) indicates the presence of two populations along the Chinese coast. Zoologia 37: 1-12. https://doi.org/10.3897/zoologia.37.e49046
Figure 1 Locations of 12 sampling sites of Lateolabrax maculatus. 85 individuals of L. maculatus were collected from 12 geographic locations including Tianjin (TJ), Yantai (YT), Wendeng (WD), Lianyungang (LY), Zhoushan (ZS), Wenzhou (WZ), Shantou (ST), Shenzhen (SZ), Zhanjiang (ZJ), Haikang (HK), Tieshan (TS), Fangcheng (FC) along Chinese coastal waters. The average sea surface temperature (SST) of 1981-2010 at 12 sampling sites were retrieved from NOAA Optimum Interpolation (OI) Sea Surface Temperature (SST) V2 (https://www.esrl.noaa.gov/psd/data/gridded/data.noaa.oisst.v2.html).
Datasets for: Genome wide analysis reveals genetic divergence between Goldsinny wrasse populations
<p><b>Background</b>: Marine fish populations are often characterized by high levels of gene flow and correspondingly low genetic divergence. This presents a challenge to define management units. Goldsinny wrasse (<i>Ctenolabrus rupestris</i>) is a heavily exploited species due to its importance as a cleaner-fish in commercial salmonid aquaculture. However, at the present, the population genetic structure of this species is still largely unresolved. Here, full-genome sequencing was used to produce the first genomic reference for this species, to study population-genomic divergence among four geographically distinct populations, and, to identify informative SNP markers for future studies.</p> <p><b>Results:</b> After construction of a <i>de novo </i>assembly, the genome was estimated to be highly polymorphic and of ~600Mbp in size. 33 235 genome wide SNPs were thereafter selected to assess genomic diversity and differentiation among four populations collected from Scandinavia, Scotland, and Spain. Global <i>F<sub>ST</sub></i> among these populations was 0.015–0.092. Approximately 4% of the investigated loci were identified as putative global outliers, and ~1% within Scandinavia. SNPs showing large divergence (<i>F<sub>ST</sub></i>>0.15) were picked as candidate diagnostic markers for population assignment. 173 of the most diagnostic SNPs between the two Scandinavian populations were validated by genotyping 47 individuals from each end of the species' Scandinavian distribution range. 69 of these SNPs were significantly (<i>p</i><0.05) differentiated (mean <i>F<sub>ST_173_loci</sub></i><i>=</i>0.065<i>, F<sub>ST_69_</sub></i><i><sub>loci</sub></i><i>=</i>0.140). Using these validated SNPs, individuals were assigned with high probability (≥ 94%) to their populations of origin.</p> <p><b>Conclusions:</b> Goldsinny wrasse displays a highly polymorphic genome, and substantial population genomic structure. Diversifying selection likely affects population structuring globally and within Scandinavia. The diagnostic loci identified now provide a promising and cost-efficient tool to investigate goldsinny wrasse populations further.</p>
Data from: Range-wide population genomics of the Mexican fruit fly: towards development of pathway analysis tools
Recurrently invading pests provide unique challenges for pest management, but also present opportunities to utilize genomics to understand invasion dynamics and inform regulatory management through pathway analysis. In the southern United States, the Mexican fruit fly Anastrepha ludens is such a pest, and its incursions into Texas and California represent major threats to the agricultural systems of those regions. We developed a draft genome assembly for A. ludens, conducted range-wide population genomics using restriction-site associated DNA sequencing, and then developed and demonstrated a panel of highly-differentiated diagnostic SNPs for source determination of intercepted flies in this system. Using 2,081 genome-wide SNPs, we identified four populations across the range of A. ludens, corresponding to western Mexico, eastern Mexico/Texas, Guatemala/Belize/Honduras, and Costa Rica/Panama, with some intergradation present between clusters, particularly in Central America. From this population genomics framework, we developed a diagnostic panel of 28 highly-differentiated SNPs that were able to recreate the genome-wide population structure in this species. We demonstrated this panel on a set of test specimens, including specimens intercepted as part of regular trapping surveillance in Texas and California, and we were able to predict populations of origin for these specimens. This methodology presents a highly applied use of genomic techniques and can be implemented in any group of recurrently invading pests.
Data from: Analysis of iris surface features in populations of diverse ancestry
There are many textural elements that can be found in the human eye, including Fuchs' crypts, Wolfflin nodules, pigment spots, contraction furrows and conjunctival melanosis. Although iris surface features have been well-studied in populations of European ancestry, the worldwide distribution of these traits is poorly understood. In this paper, we develop a new method of characterizing iris features from photographs of the iris. We then apply this method to a diverse sample of East Asian, European and South Asian ancestry. All five iris features showed significant differences in frequency between the three populations, indicating that iris features are largely population dependent. Although none of the features were correlated with each other in the East and South Asian groups, Fuchs' crypts were significantly correlated with contraction furrows and pigment spots and contraction furrows were significantly associated with pigment spots in the European group. The genetic marker SEMA3A rs10235789 was significantly associated with Fuchs' crypt grade in the European, East Asian and South Asian samples and a borderline association between TRAF3IP1 rs3739070 and contraction furrow grade was found in the European sample. The study of iris surface features in diverse populations may provide valuable information of forensic, biomedical and ophthalmological interest.
Cheirogaleus population density meta-analysis data
<p><b>Aim:</b> Global animal populations are in decline due to destruction and degradation of their natural habitat. Understanding the factors that determine the distribution and density of threatened animal populations is therefore now a crucial component of their study and conservation. The Cheirogaleidae are a diverse family of small-bodied, nocturnal lemurs that are widespread throughout the forests of Madagascar. However, many cheirogaleid lemurs are now highly threatened with extinction and the environmental factors that determine their distribution and population density are still little known. Here, I investigated the environmental drivers of Cheirogaleidae population density at genus level.</p> <p><b>Location: </b>Various forest sites across Madagascar.</p> <p><b>Methods:</b> I investigated how six environmental variables affect Cheirogaleidae population density at the genus level via random effect meta-analyses. I then used a Generalized Linear Mixed-effects Model to identify the primary predictors of Cheirogaleidae population density. Finally, I investigated how the population density of this family of lemurs varies between protected and unprotected areas of Madagascar via a GLM analysis.</p> <p><b>Results:</b> My results indicate that the relationships between the tested environmental factors and population density are genus-specific among the Cheirogaleidae. Rather remarkably, the density of <i>Microcebus </i>appears to have a profoundly positive relationship with anthropogenic disturbance and a negative relationship with forest cover, a finding that is also reflected by larger population densities within unprotected areas in comparison to localities within Madagascar's protected area network.</p> <p><b>Main Conclusions:</b> The results of this study are highly encouraging for the conservation of the Cheirogaleidae and highlight the remarkable resilience of these lemurs to habitat degradation and anthropogenic activity. However, this study also outlines the dearth of knowledge that we have for many species, and why these data are urgently needed to understand the biogeography and ecology of threatened animal populations and implement successful conservation.</p>
Data from: Genome-wide association analysis for blood lipid traits measured in three pig populations revealed a substantial level of genetic heterogeneity
Serum lipids are associated with myocardial infarction and cardiovascular disease in humans. Here we dissected the genetic architecture of blood lipid traits by applying genome-wide association studies (GWAS) in 1,256 pigs from Laiwu, Erhualian and Duroc × (Landrace × Yorkshire) populations, and a meta-analysis of GWAS in more than 2,400 pigs from five diverse populations. A total of 22 genomic loci surpassing the suggestive significance level were detected on 11 pig chromosomes (SSC) for six blood lipid traits. Meta-analysis of GWAS identified 5 novel loci associated with blood lipid traits. Comparison of GWAS loci across the tested populations revealed a substantial level of genetic heterogeneity for porcine blood lipid levels. We further evaluated the causality of nine polymorphisms nearby or within the APOB gene on SSC3 for serum LDL-C and TC levels. Of the 9 polymorphisms, an indel showed the most significant association with LDL-C and TC in Laiwu pigs. But the significant association was not identified in the White Duroc × Erhualian F2 resource population, in which the QTL for LDL-C and TC was also detected on SSC3. This indicates that population-specific signals may exist for the SSC3 QTL. Further investigations are warranted to validate this assumption.
Data from: Comparing G: multivariate analysis of genetic variation in multiple populations
The additive genetic variance–covariance matrix (G) summarizes the multivariate genetic relationships among a set of traits. The geometry of G describes the distribution of multivariate genetic variance, and generates genetic constraints that bias the direction of evolution. Determining if and how the multivariate genetic variance evolves has been limited by a number of analytical challenges in comparing G-matrices. Current methods for the comparison of G typically share several drawbacks: metrics that lack a direct relationship to evolutionary theory, the inability to be applied in conjunction with complex experimental designs, difficulties with determining statistical confidence in inferred differences and an inherently pair-wise focus. Here, we present a cohesive and general analytical framework for the comparative analysis of G that addresses these issues, and that incorporates and extends current methods with a strong geometrical basis. We describe the application of random skewers, common subspace analysis, the 4th-order genetic covariance tensor and the decomposition of the multivariate breeders equation, all within a Bayesian framework. We illustrate these methods using data from an artificial selection experiment on eight traits in Drosophila serrata, where a multi-generational pedigree was available to estimate G in each of six populations. One method, the tensor, elegantly captures all of the variation in genetic variance among populations, and allows the identification of the trait combinations that differ most in genetic variance. The tensor approach is likely to be the most generally applicable method to the comparison of G-matrices from any sampling or experimental design.
Data from: Facultative bacterial endosymbionts shape parasitoid food webs in natural host populations: a correlative analysis
1.Facultative bacterial endosymbionts can protect their aphid hosts from natural enemies such as hymenopteran parasitoids. As such, they have the capability to modulate interactions between aphids, parasitoids and hyperparasitoids. However, the magnitude of these effects in natural aphid populations and their associated parasitoid communities is currently unknown. Moreover, environmental factors such as plant fertilization and landscape complexity are known to affect aphid‐parasitoid interactions but it remains unclear how such environmental factors affect the interplay between aphids, parasitoids and endosymbionts. 2.Here, we tested whether facultative endosymbionts confer protection to parasitoids in natural populations of the English grain aphid, Sitobion avenae, and if this is affected by plant fertilization and landscape complexity. Furthermore, we examined whether the effects of facultative endosymbionts can cascade up to the hyperparasitoid level and increase primary‐hyperparasitoid food web specialization. 3.Living aphids and mummies were collected in fertilized and unfertilized plots within 13 wheat fields in Central Germany. We assessed the occurrence of primary parasitoid, hyperparasitoid and endosymbiont species in aphids and mummies using a newly established molecular approach. 4.Facultative endosymbiont infection rates were high across fields (~80 %), independent of whether aphids were parasitized or un‐parasitized. Aphid mummies exhibited a significantly lower share of facultative endosymbiont infection (~38 %). These findings suggest that facultative endosymbionts do not affect parasitoid oviposition behavior, but decrease parasitoid survival in the host. Facultative endosymbiont infection rates were lower in mummies collected from fertilized compared to unfertilized plants, indicating that plant fertilization boosts the facultative endosymbiont protective effect. Furthermore, we found strong evidence for species‐specific and negative cascading effects of facultative endosymbionts on primary and hyperparasitoids, respectively. Facultative endosymbionts impacted parasitoid assemblages and increased the specialization of primary‐hyperparasitoid food webs: these effects were independent from and much stronger than other environmental factors. 5.The current findings stongly suggest that facultative endosymbionts act as a driving force in aphid‐parasitoid‐hyperparastioid networks: they shape insect community composition at different trophic levels and modulate, directly and indirectly, the interactions between aphids, parasitoids and their environment.
Data from: Relative accuracy of three common methods of parentage analysis in natural populations
Parentage studies and family reconstructions have become increasingly popular for investigating a range of evolutionary, ecological and behavioral processes in natural populations. However, a number of different assignment methods have emerged in common use, and the accuracy of each may differ in relation to the number of loci examined, allelic diversity, incomplete sampling of all candidate parents, and the presence of genotyping errors. Here we examine how these factors affect the accuracy of three popular parentage inference methods (COLONY, FaMoz and an exclusion-Bayes' theorem approach by Christie et al. (2010a)) to resolve true parent-offspring pairs using simulated data. Our findings demonstrate that accuracy increases with the number and diversity of loci. These were clearly the most important factors in obtaining accurate assignments explaining 75-90% of variance in overall accuracy across 60 simulated scenarios. Furthermore, the proportion of candidate parents sampled had a small but significant impact on the susceptibility of each method to either false positive or false negative assignments. Within the range of values simulated, COLONY outperformed FaMoz, which outperformed the exclusion-Bayes' theorem method. However, with 20 or more highly polymorphic loci, all methods could be applied with confidence. Our results show that for parentage inference in natural populations, careful consideration of the number and quality of markers will increase the accuracy of assignments and mitigate the effects of incomplete sampling of parental populations.
Data from: Microsatellite analysis of genetic diversity and population structure of Arabian horse populations
The Arabian horse ignites imagination throughout the world. Populations of this breed exist in many countries, and recent genetic work has examined the diversity and ancestry of a few of these populations in isolation. Here we explore seven different populations of Arabians represented by 682 horses. Three of these are Middle Eastern populations from near the historical origin of the breed, including Syrian, Persian, and Saudi Arabian. The remaining Western populations are found in Europe (the Shagya-Arabian and Polish-Arabian) and America (American-Arabian). Analysis of genetic structure was carried out using 15 microsatellite loci. Genetic distances, AMOVA, factorial correspondence analysis and a Bayesian method were applied. The results consistently show higher level of diversity within the Middle Eastern populations than the Western populations. The Western Arabian populations were the main source of among populations variation. Genetic differentiation was not strong among all Middle Eastern populations, but all American-Arabians showed differentiation from Middle Eastern populations and were somewhat uniform among themselves. Here, we explore the diversities of many different populations of Arabian horses, and find that populations not from the Middle East have noticeably lower levels of diversity, which may adversely affect the health of these populations.
Data from: The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis
The inference of population genetic structures is essential in many research areas in population genetics, conservation biology and evolutionary biology. Recently, unsupervised Bayesian clustering algorithms have been developed to detect a hidden population structure from genotypic data, assuming among others that individuals taken from the population are unrelated. Because of this hypothesis, markers in a sample taken from a subpopulation can be considered to be in Hardy-Weinberg and linkage equilibrium. However, close relatives might be sampled from the same subpopulation, and consequently, might cause Hardy-Weinberg and linkage disequilibrium and thus bias a population genetic structure analysis. In this study, we used simulated and real data to investigate the impact of close relatives in a sample on Bayesian population structure analysis. We also showed that, when close relatives were identified by a pedigree reconstruction approach and removed, the accuracy of a population genetic structure analysis can be greatly improved. The results indicate that unsupervised Bayesian clustering algorithms cannot be used blindly to detect genetic structure in a sample with closely related individuals. Rather, when closely related individuals are suspected to be frequent in a sample, these individuals should be first identified and removed before conducting a population structure analysis.
Data from: Population genomic analysis suggests strong influence of river network on spatial distribution of genetic variation in invasive saltcedar across the southwestern US
Understanding the complex influences of landscape and anthropogenic elements that shape the population genetic structure of invasive species provides insight into patterns of colonization and spread. The application of landscape genomics techniques to these questions may offer detailed, previously undocumented insights into factors influencing species invasions. We investigated the spatial pattern of genetic variation and the influences of landscape factors on population similarity in the invasive riparian shrub saltcedar (Tamarix L.) by analyzing 1,997 genome-wide SNP markers for 259 individuals from 25 populations collected throughout the southwestern US. Our results revealed a broad-scale spatial genetic differentiation of saltcedar populations between the Colorado and Rio Grande river basins and identified potential barriers to population similarity along both river systems. River pathways most strongly contributed to population similarity. In contrast, low temperature and dams likely served as barriers to population similarity. We hypothesize that large-scale geographic patterns in genetic diversity resulted from a combination of early introductions from distinct populations, the subsequent influence of natural selection, dispersal barriers, and founder effects during range expansion.
Data from: Using matrix and tensor factorizations for the single-trial analysis of population spike trains
Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.
Data from: Challenges in analysis and interpretation of microsatellite data for population genetic studies
Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (FST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.
Data from: Are heritability and selection related to population size in nature? Meta-analysis and conservation implications
It is widely thought that small populations should have less additive genetic variance and respond less efficiently to natural selection than large populations. Across taxa, we meta-analytically quantified the relationship between adult census population size (N) and additive genetic variance (proxy: h2) and found no reduction in h2 with decreasing N; surveyed populations ranged from four to one million individuals (1735 h2estimates, 146 populations, 83 species). In terms of adaptation, ecological conditions may systematically differ between populations of varying N; the magnitude of selection these populations experience may therefore also differ. We thus also meta-analytically tested whether selection changes with N, and found little evidence for systematic differences in the strength, direction, or form of selection with N across different trait types and taxa (7344 selection estimates, 172 populations, 80 species). Collectively, our results (i) indirectly suggest that genetic drift neither overwhelms selection more in small than in large natural populations, nor weakens adaptive potential/h2 in small populations, and (ii) imply that natural populations of varying sizes experience a variety of environmental conditions, without consistently differing habitat quality at small N. However, we caution that the data are currently insufficient to determine whether some small populations may retain adaptive potential definitively. Further study is required into (i) selection and genetic variation in completely isolated populations of known N, underrepresented taxonomic groups, and non-generalist species, (ii) adaptive potential using multidimensional approaches, and (iii) the nature of selective pressures for specific traits.
Data from: Population genomic analysis uncovers African and European admixture in Drosophila melanogaster populations from the southeastern United States and Caribbean Islands
Drosophila melanogaster is postulated to have colonized North America in the past several 100 years in two waves. Flies from Europe colonized the east coast United States while flies from Africa inhabited the Caribbean, which if true, make the south-east US and Caribbean Islands a secondary contact zone for African and European D. melanogaster. This scenario has been proposed based on phenotypes and limited genetic data. In our study, we have sequenced individual whole genomes of flies from populations in the south-east US and Caribbean Islands and examined these populations in conjunction with population sequences from the west coast US, Africa, and Europe. We find that west coast US populations are closely related to the European population, likely reflecting a rapid westward expansion upon first settlements into North America. We also find genomic evidence of African and European admixture in south-east US and Caribbean populations, with a clinal pattern of decreasing proportions of African ancestry with higher latitude. Our genomic analysis of D. melanogaster populations from the south-east US and Caribbean Islands provides more evidence for the Caribbean Islands as the source of previously reported novel African alleles found in other east coast US populations. We also find the border between the south-east US and the Caribbean island to be the admixture hot zone where distinctly African-like Caribbean flies become genomically more similar to European-like south-east US flies. Our findings have important implications for previous studies examining the generation of east coast US clines via selection.
Data from: Population genomics of pearl millet (Pennisetum glaucum (L.) R. Br.): comparative analysis of global accessions and Senegalese landraces
Background: Pearl millet is a staple food for people in arid and semi-arid regions of Africa and South Asia due to its high drought tolerance and nutritional qualities. A better understanding of the genomic diversity and population structure of pearl millet germplasm is needed to support germplasm conservation and genetic improvement of this crop. Here we characterized two pearl millet diversity panels, (i) a set of global accessions from Africa, Asia, and the America, and (ii) a collection of landraces from multiple agro-ecological zones in Senegal. Results: We identified 83,875 single nucleotide polymorphisms (SNPs) in 500 pearl millet accessions, comprised of 252 global accessions and 248 Senegalese landraces, using genotyping by sequencing (GBS) of PstI-MspI reduced representation libraries. We used these SNPs to characterize genomic diversity and population structure among the accessions. The Senegalese landraces had the highest levels of genetic diversity (π), while accessions from southern Africa and Asia showed lower diversity levels. Principal component analyses and ancestry estimation indicated clear population structure between the Senegalese landraces and the global accessions, and among countries in the global accessions. In contrast, little population structure was observed across in the Senegalese landraces collections. We ordered SNPs on the pearl millet genetic map and observed much faster linkage disequilibrium (LD) decay in Senegalese landraces compared to global accessions. A comparison of pearl millet GBS linkage map with the foxtail millet (Setaria italica) and sorghum (Sorghum bicolor) genomes indicated extensive regions of synteny, as well as some large-scale rearrangements in the pearl millet lineage. Conclusions: We identified 83,875 SNPs as a genomic resource for pearl millet improvement. The high genetic diversity in Senegal relative to other regions of Africa and Asia supports a West African origin of this crop, followed by wide diffusion. The rapid LD decay and lack of confounding population structure along agro-ecological zones in Senegalese pearl millet will facilitate future association mapping studies. Comparative population genomics will provide insights into panicoid crop evolution and support improvement of these climate-resilient crops.
FIGURES 1-2. 1 in Taxonomic diagnosis of Dicyrtomina ornata and D. saundersi (Collembola: Dicyrtomidae) and analysis of their population genetic structure
FIGURES 1-2. 1, Dicyrtomina ornata, habitus; 2, Dicyrtomina saundersi, habitus.
THE ANALYSIS OF PRIMARY DISABILITY STRUCTUREOF POPULATION OF FERGANA REGION
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