Analysis of Genetic Diversity in Romanian Carpatina Goats Using SNP Genotyping Data
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ABSTRACT:
SUBMITTER: Vlaic B
PROVIDER: S-EPMC10886219 | biostudies-literature | 2024 Feb
REPOSITORIES: biostudies-literature
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Project description:Mongolian goats are of great interest for studying ancient migration routes and domestication, and also represent a good model of adaptability to harsh environments. Recent climatic disasters and uncontrolled massive breeding endangered the valuable genetic resources of Mongolian goats and raised the question of their conservation status. Meanwhile, Mongolian goats have never been studied on genomic scale. We used Illumina Goat SNP50 to estimate genetic risks in five Mongolian goat breeds (Buural, Ulgii Red, Gobi GS, Erchim, Dorgon) and explored phylogenic relationships among these populations and in the context of other breeds. Various clustering methods showed that Mongolian goats grouped with other Asian breeds and were especially close to some neighboring Russian and Chinese breeds. The Buural breed showed the lowest estimates of inbreeding and exhibited the shortest genetic distances within the other Mongolian breeds, especially, to Ulgii Red and Gobi GS. These three breeds formed a single core group, being weakly differentiated from each other. Among them, Gobi GS displayed obvious signs of inbreeding probably resulted from artificial selection pressure. Dorgon and especially Erchim goats stand apart from the other Mongolian breeds according to various types of analyses, and bear unique features pointing to different breeding histories or distinct origins of these breeds. All populations showed strong decline in effective population size. However, none of them met formal criteria to be considered as endangered breeds. The SNP data obtained in this study improved the knowledge of Mongolian goat breeds and could be used in future management decisions in order to preserve their genetic diversity.
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Project description:The Angora goat populations in Argentina (AR), France (FR) and South Africa (SA) have been kept geographically and genetically distinct. Due to country-specific selection and breeding strategies, there is a need to characterize the populations on a genetic level. In this study we analysed genetic variability of Angora goats from three distinct geographical regions using the standardized 50k Goat SNP Chip. A total of 104 goats (AR: 30; FR: 26; SA: 48) were genotyped. Heterozygosity values as well as inbreeding coefficients across all autosomes per population were calculated. Diversity, as measured by expected heterozygosity (HE) ranged from 0.371 in the SA population to 0.397 in the AR population. The SA goats were the only population with a positive average inbreeding coefficient value of 0.009. After merging the three datasets, standard QC and LD-pruning, 15 105 SNPs remained for further analyses. Principal component and clustering analyses were used to visualize individual relationships within and between populations. All SA Angora goats were separated from the others and formed a well-defined, unique cluster, while outliers were identified in the FR and AR breeds. Apparent admixture between the AR and FR populations was observed, while both these populations showed signs of having some common ancestry with the SA goats. LD averaged over adjacent loci within the three populations per chromosome were calculated. The highest LD values estimated across populations were observed in the shorter intervals across populations. The Ne for the Angora breed was estimated to be 149 animals ten generations ago indicating a declining trend. Results confirmed that geographic isolation and different selection strategies caused genetic distinctiveness between the populations.
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Project description:The genetic relationship and population structure of two-rowed barley accessions from Kazakhstan were assessed using single-nucleotide polymorphism (SNP) markers. Two different approaches were employed in the analysis: (1) the accessions from Kazakhstan were compared with barley samples from six different regions around the world using 1955 polymorphic SNPs, and (2) 94 accessions collected from six breeding programs from Kazakhstan were studied using 5636 polymorphic SNPs using a 9K Illumina Infinium assay. In the first approach, the neighbor-joining tree showed that the majority of the accessions from Kazakhstan were grouped in a separate subcluster with a common ancestral node; there was a sister subcluster that comprised mainly barley samples that originated in Europe. The Pearson's correlation analysis suggested that Kazakh accessions were genetically close to samples from Africa and Europe. In the second approach, the application of the STRUCTURE package using 5636 polymorphic SNPs suggested that Kazakh barley samples consisted of five subclusters in three major clusters. The principal coordinate analysis plot showed that, among six breeding origins in Kazakhstan, the Krasnovodopad (KV) and Karaganda (KA) samples were the most distant groups. The assessment of the pedigrees in the KV and KA samples showed that the hybridization schemes in these breeding stations heavily used accessions from Ethiopia and Ukraine, respectively. The comparative analysis of the KV and KA samples allowed us to identify 214 SNPs with opposite allele frequencies that were tightly linked to 60 genes/gene blocks associated with plant adaptation traits, such as the heading date and plant height. The identified SNP markers can be efficiently used in studies of barley adaptation and deployed in breeding projects to develop new competitive cultivars.
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Project description:New-generation sequencing technologies, among them SNP chips for massive genotyping, are useful for the effective management of genetic resources. To date, molecular studies in Peruvian cattle are still scarce. For the first time, the genetic diversity and population structure of a reproductive nucleus cattle herd of four commercial breeds from a Peruvian institution were determined. This nucleus comprises Brahman (N = 9), Braunvieh (N = 9), Gyr (N = 5), and Simmental (N = 15) breeds. Additionally, samples from a locally adapted creole cattle, the Arequipa Fighting Bull (AFB, N = 9), were incorporated. Female individuals were genotyped with the GGPBovine100K and males with the BovineHD. Quality control, and the proportion of polymorphic SNPs, minor allele frequency, expected heterozygosity, observed heterozygosity, and inbreeding coefficient were estimated for the five breeds. Admixture, principal component analysis (PCA), and discriminant analysis of principal components (DAPC) were performed. Also, a dendrogram was constructed using the Neighbor-Joining clustering algorithm. The genetic diversity indices in all breeds showed a high proportion of polymorphic SNPs, varying from 51.42% in Gyr to 97.58% in AFB. Also, AFB showed the highest expected heterozygosity estimate (0.41 ± 0.01), while Brahman the lowest (0.33 ± 0.01). Besides, Braunvieh possessed the highest observed heterozygosity (0.43 ± 0.01), while Brahman the lowest (0.37 ± 0.02), indicating that Brahman was less diverse. According to the molecular variance analysis, 75.71% of the variance occurs within individuals, whereas 24.29% occurs among populations. The pairwise genetic differentiation estimates (FST) between breeds showed values that ranged from 0.08 (Braunvieh vs. AFB) to 0.37 (Brahman vs. Braunvieh). Similarly, pairwise Reynold's distance ranged from 0.09 (Braunvieh vs. AFB) to 0.46 (Brahman vs. Braunvieh). The dendrogram, similar to the PCA, identified two groups, showing a clear separation between Bos indicus (Brahman and Gyr) and B. taurus breeds (Braunvieh, Simmental, and AFB). Simmental and Braunvieh grouped closely with the AFB cattle. Similar results were obtained for the population structure analysis with K = 2. The results from this study would contribute to the appropriate management, avoiding loss of genetic variability in these breeds and for future improvements in this nucleus. Additional work is needed to speed up the breeding process in the Peruvian cattle system.
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Project description:BackgroundSingle Nucleotide Polymorphisms (SNPs) can be used as genetic markers for applications such as genetic diversity studies or genetic mapping. New technologies now allow genotyping hundreds to thousands of SNPs in a single reaction.In order to evaluate the potential of these technologies in pea, we selected a custom 384-SNP set using SNPs discovered in Pisum through the resequencing of gene fragments in different genotypes and by compiling genomic sequence data present in databases. We then designed an Illumina GoldenGate assay to genotype both a Pisum germplasm collection and a genetic mapping population with the SNP set.ResultsWe obtained clear allelic data for more than 92% of the SNPs (356 out of 384). Interestingly, the technique was successful for all the genotypes present in the germplasm collection, including those from species or subspecies different from the P. sativum ssp sativum used to generate sequences. By genotyping the mapping population with the SNP set, we obtained a genetic map and map positions for 37 new gene markers.ConclusionOur results show that the Illumina GoldenGate assay can be used successfully for high-throughput SNP genotyping of diverse germplasm in pea. This genotyping approach will simplify genotyping procedures for association mapping or diversity studies purposes and open new perspectives in legume genomics.
| S-EPMC3091664 | biostudies-literature
Project description:BackgroundThe tomato (Solanum lycopersium L.) is the most widely grown vegetable in the world. It was domesticated in Latin America and Italy and Spain are considered secondary centers of diversification. This food crop has experienced severe genetic bottlenecks and modern breeding activities have been characterized by trait introgression from wild species and divergence in different market classes.ResultsWith the aim to examine patterns of polymorphism, characterize population structure and identify putative loci under positive selection, we genotyped 214 tomato accessions (which include cultivated landraces, commercial varieties and wild relatives) using a custom-made Illumina SNP-panel. Most of the 175 successfully scored SNP loci were found to be polymorphic. Population structure analysis and estimates of genetic differentiation indicated that landraces constitute distinct sub-populations. Furthermore, contemporary varieties could be separated in groups (processing, fresh and cherry) that are consistent with the recent breeding aimed at market-class specialization. In addition, at the 95% confidence level, we identified 30, 34 and 37 loci under positive selection between landraces and each of the groups of commercial variety (cherry, processing and fresh market, respectively). Their number and genomic locations imply the presence of some extended regions with high genetic variation between landraces and contemporary varieties.ConclusionsOur work provides knowledge concerning the level and distribution of genetic variation within cultivated tomato landraces and increases our understanding of the genetic subdivision of contemporary varieties. The data indicate that adaptation and selection have led to a genomic signature in cultivated landraces and that the subpopulation structure of contemporary varieties is shaped by directed breeding and largely of recent origin. The genomic characterization presented here is an essential step towards a future exploitation of the available tomato genetic resources in research and breeding programs.
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Project description:Lvliang black goat (LBG) is an excellent local breed resource in China that is known for its black fur, excellent meat quality, and strong adaptability. Studying the genetic mechanism and germplasm characteristics of LBG can provide theoretical and practical basis for the protection of the genetic resources of this breed and help implement conservation and breeding. In this study, the genetic diversity of the LBG population was evaluated using whole-genome SNP data. It was found that the LBG population had a high genetic diversity and a low degree of inbreeding. According to the clustering results of male goats and the relationship between individuals, the LBG population was divided into 13 families. Then, through population structure analysis, it was found that LBG had a close genetic relationship with the Nanjiang goat and Qinggoda goat populations, and they may have the same ancestors. The LBG population has retained some ancient genetic characteristics and is a special population that integrates local genetic characteristics and foreign gene flow. Through four selection signal analyses, we detected multiple candidate genes related to economic traits (CFL2, SCD, NLRP14, etc.) and adaptability (C4BPA, FUT8, PRNP, etc.) in the LBG population. In addition, in a comparative analysis with three commercial breeds (Saanen goat, Boer goat and Angora goat) we also found multiple genes related to physical characteristics (ERG, NRG3, EDN3, etc.). Finally, we performed functional enrichment analysis on these genes and explored their genetic mechanisms. This study provides important data support for the protection and breeding of LBG and provides a new perspective for enriching the genetic diversity of goat populations.
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Project description:Herein, the genetic diversity of the local Přeštice Black-Pied pig breed was assessed by the simultaneous analysis of the pedigree and single nucleotide polymorphism (SNP) data. The information about sire line, dam, date of birth, sex, breeding line, and herd for 1971 individuals was considered in the pedigree analysis. The SNP analysis (n = 181) was performed using the Illumina PorcineSNP60 BeadChip kit. The quality of pedigree and SNPs and the inbreeding coefficients (F) and effective population size (Ne) were evaluated. The correlations between inbreeding based on the runs of homozygosity (FROH) and pedigree (FPED) were also calculated. The average FPED for all animals was 3.44%, while the FROH varied from 10.81% for a minimum size of 1 Mbp to 3.98% for a minimum size of 16 Mbp. The average minor allele frequency was 0.28 ± 0.11. The observed and expected within breed heterozygosities were 0.38 ± 0.13 and 0.37 ± 0.12, respectively. The Ne, obtained using both the data sources, reached values around 50 animals. Moderate correlation coefficients (0.49-0.54) were observed between FPED and FROH. It is necessary to make decisions that stabilize the inbreeding rate in the long-term using optimal contribution selection based on the available SNP data.
| S-EPMC8702119 | biostudies-literature
Project description:Genotyping by sequencing (GBS) recently has emerged as a promising genomic approach for assessing genetic diversity on a genome-wide scale. However, concerns are not lacking about the uniquely large unbalance in GBS genotype data. Although some genotype imputation has been proposed to infer missing observations, little is known about the reliability of a genetic diversity analysis of GBS data, with up to 90% of observations missing. Here we performed an empirical assessment of accuracy in genetic diversity analysis of highly incomplete single nucleotide polymorphism genotypes with imputations. Three large single-nucleotide polymorphism genotype data sets for corn, wheat, and rice were acquired, and missing data with up to 90% of missing observations were randomly generated and then imputed for missing genotypes with three map-independent imputation methods. Estimating heterozygosity and inbreeding coefficient from original, missing, and imputed data revealed variable patterns of bias from assessed levels of missingness and genotype imputation, but the estimation biases were smaller for missing data without genotype imputation. The estimates of genetic differentiation were rather robust up to 90% of missing observations but became substantially biased when missing genotypes were imputed. The estimates of topology accuracy for four representative samples of interested groups generally were reduced with increased levels of missing genotypes. Probabilistic principal component analysis based imputation performed better in terms of topology accuracy than those analyses of missing data without genotype imputation. These findings are not only significant for understanding the reliability of the genetic diversity analysis with respect to large missing data and genotype imputation but also are instructive for performing a proper genetic diversity analysis of highly incomplete GBS or other genotype data.
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Project description:Melon is an important horticultural crop with a pleasant aromatic flavor and abundance of health-promoting substances. Numerous melon varieties have been cultivated worldwide in recent years, but the high number of varieties and the high similarity between them poses a major challenge for variety evaluation, discrimination, as well as innovation in breeding. Recently, simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs), two robust molecular markers, have been utilized as a rapid and reliable method for variety identification. To elucidate the genetic structure and diversity of melon varieties, we screened out 136 perfect SSRs and 164 perfect SNPs from the resequencing data of 149 accessions, including the most representative lines worldwide. This study established the DNA fingerprint of 259 widely-cultivated melon varieties in China using Target-seq technology. All melon varieties were classified into five subgruops, including ssp. agrestis, ssp. melo, muskmelon and two subgroups of foreign individuals. Compared with ssp. melo, the ssp. agrestis varieties might be exposed to a high risk of genetic erosion due to their extremely narrow genetic background. Increasing the gene exchange between ssp. melo and ssp. agrestis is therefore necessary in the breeding procedure. In addition, analysis of the DNA fingerprints of the 259 melon varieties showed a good linear correlation (R2 = 0.9722) between the SSR genotyping and SNP genotyping methods in variety identification. The pedigree analysis based on the DNA fingerprint of 'Jingyu' and 'Jingmi' series melon varieties was consistent with their breeding history. Based on the SNP index analysis, ssp. agrestis had low gene exchange with ssp. melo in chromosome 4, 7, 10, 11and 12, two specific SNP loci were verified to distinguish ssp. agrestis and ssp. melon varieties. Finally, 23 SSRs and 40 SNPs were selected as the core sets of markers for application in variety identification, which could be efficiently applied to variety authentication, variety monitoring, as well as the protection of intellectual property rights in melon.
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