scholarly journals Development of Polymorphic Microsatellite Loci for Potato Wart from Next-Generation Sequence Data

2016 ◽  
Vol 106 (6) ◽  
pp. 636-644 ◽  
Author(s):  
Marie-Claude Gagnon ◽  
Theo A. J. van der Lee ◽  
Peter J. M. Bonants ◽  
Donna S. Smith ◽  
Xiang Li ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Sequence Data ◽  
Geographic Origin ◽  
Whole Genome Sequence ◽  
Specific Detection ◽  
Potato Wart ◽  
Intraspecific Genetic Diversity ◽  
Polymorphic Microsatellite ◽  
Genetic Clustering ◽  
Species Specific

Synchytrium endobioticum is the fungal agent causing potato wart disease. Because of its severity and persistence, quarantine measures are enforced worldwide to avoid the spread of this disease. Molecular markers exist for species-specific detection of this pathogen, yet markers to study the intraspecific genetic diversity of S. endobioticum were not available. Whole-genome sequence data from Dutch pathotype 1 isolate MB42 of S. endobioticum were mined for perfect microsatellite motifs. Of the 62 selected microsatellites, 21 could be amplified successfully and displayed moderate levels of polymorphism in 22 S. endobioticum isolates from different countries. Nineteen multilocus genotypes were observed, with only three isolates from Canada displaying identical profiles. The majority of isolates from Canada clustered genetically. In contrast, most isolates collected in Europe show no genetic clustering associated with their geographic origin. S. endobioticum isolates with the same pathotype displayed highly variable genotypes and none of the microsatellite markers correlated with a specific pathotype. The markers developed in this study can be used to assess intraspecific genetic diversity of S. endobioticum and allow track and trace of genotypes that will generate a better understanding of the migration and spread of this important fungal pathogen and support management of this disease.

scholarly journals Long-term molecular evolutionary rate determines intraspecific genetic diversity

2019 ◽  
Author(s):  
Jiaqi Wu ◽  
Takahiro Yonezawa ◽  
Hirohisa Kishino
Keyword(s):  
Genetic Diversity ◽  
De Novo ◽  
Early Stage ◽  
Morphological Evolution ◽  
Biological Traits ◽  
Gene Trees ◽  
Intraspecific Genetic Diversity ◽  
Molecular Evolutionary Rates ◽  
Species Specific

AbstractWhat determines genetic diversity and how it connects to the various biological traits is unknown. In this work, we offer answers to these questions. By comparing genetic variation of 14,671 mammalian gene trees with thousands of individual genomes of human, chimpanzee, gorilla, mouse and dog/wolf, we found that intraspecific genetic diversity is determined by long-term molecular evolutionary rates, rather than de novo mutation rates. This relationship was established during the early stage of mammalian evolution. Expanding this new finding, we developed a method to detect fluctuations of species-specific selection on genes as the deviations of intra-species genetic diversity predicted from long-term rates. We show that the evolution of epithelial cells, rather than of connective tissue, mainly contributes to morphological evolution of different species. For humans, evolution of the immune system and selective sweeps subjected by infectious diseases are most representative of adaptive evolution.

scholarly journals Predicting geographic location from genetic variation with deep neural networks

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
CJ Battey ◽  
Peter L Ralph ◽  
Andrew D Kern
Keyword(s):  
Deep Neural Networks ◽  
Sequence Data ◽  
Geographic Origin ◽  
Geographic Location ◽  
Genetic Data ◽  
Whole Genome Sequence ◽  
Human Populations ◽  
Anopheles Mosquitoes ◽  
Order Of Magnitude ◽  
Median Test

Most organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of known geographic origin. Here, we describe a deep learning method, which we call Locator, to accomplish this task faster and more accurately than existing approaches. In simulations, Locator infers sample location to within 4.1 generations of dispersal and runs at least an order of magnitude faster than a recent model-based approach. We leverage Locator’s computational efficiency to predict locations separately in windows across the genome, which allows us to both quantify uncertainty and describe the mosaic ancestry and patterns of geographic mixing that characterize many populations. Applied to whole-genome sequence data from Plasmodium parasites, Anopheles mosquitoes, and global human populations, this approach yields median test errors of 16.9km, 5.7km, and 85km, respectively.

scholarly journals Population genomics of East Asian ethnic groups

Hereditas ◽  
2020 ◽  
Vol 157 (1) ◽  
Author(s):  
Ziqing Pan ◽  
Shuhua Xu
Keyword(s):  
Genetic Diversity ◽  
East Asia ◽  
Ethnic Groups ◽  
Population Genomics ◽  
Sequence Data ◽  
East Asian ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Evolutionary Forces ◽  
Asian Populations

AbstractEast Asia constitutes one-fifth of the global population and exhibits substantial genetic diversity. However, genetic investigations on populations in this region have been largely under-represented compared with European populations. Nonetheless, the last decade has seen considerable efforts and progress in genome-wide genotyping and whole-genome sequencing of the East-Asian ethnic groups. Here, we review the recent studies in terms of ancestral origin, population relationship, genetic differentiation, and admixture of major East- Asian groups, such as the Chinese, Korean, and Japanese populations. We mainly focus on insights from the whole-genome sequence data and also include the recent progress based on mitochondrial DNA (mtDNA) and Y chromosome data. We further discuss the evolutionary forces driving genetic diversity in East-Asian populations, and provide our perspectives for future directions on population genetics studies, particularly on underrepresented indigenous groups in East Asia.

scholarly journals Homogeneity of Arabian Peninsula dromedary camel populations with signals of geographic distinction based on whole genome sequence data

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Hussain Bahbahani ◽  
Faisal Almathen
Keyword(s):  
Genetic Diversity ◽  
Genome Sequence ◽  
Arabian Peninsula ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Dromedary Camels ◽  
Genome Sequence Data ◽  
Similarity Indices ◽  
Bactrian Camels

AbstractDromedary camels in the Arabian Peninsula distribute along different geographical and ecological locations, e.g. desert, mountains and coasts. Here, we are aiming to explore the whole genome sequence data of ten dromedary populations from the Arabian Peninsula to assess their genetic structure, admixture levels, diversity and similarity indices. Upon including reference dromedary and Bactrian camel populations from Iran and Kazakhstan, we characterise inter-species and geographic genetic distinction between the dromedary and the Bactrian camels. Individual-based alpha genetic diversity profiles are found to be generally higher in Bactrian camels than dromedary populations, with the exception of five autosomes (NC_044525.1, NC_044534.1, NC_044540.1, NC_044542.1, NC_044544.1) at diversity orders (q ≥ 2). The Arabian Peninsula camels are generally homogenous, with a small degree of genetic distinction correlating with three geographic groups: North, Central and West; Southwest; and Southeast of the Arabian Peninsula. No significant variation in diversity or similarity indices are observed among the different Arabian Peninsula dromedary populations. This study contributes to our understanding of the genetic diversity of Arabian Peninsula dromedary camels. It will help conserve the genetic stock of this species and support the design of breeding programmes for genetic improvement of favorable traits.

scholarly journals Genetic Diversity of Grapevine virus A in Washington and California Vineyards

2014 ◽  
Vol 104 (5) ◽  
pp. 548-560 ◽  
Author(s):  
Olufemi J. Alabi ◽  
Maher Al Rwahnih ◽  
Tefera A. Mekuria ◽  
Rayapati A. Naidu
Keyword(s):  
Genetic Diversity ◽  
Phylogenetic Analysis ◽  
Sequence Data ◽  
Management Strategies ◽  
Geographic Origin ◽  
Phylogenetic Network ◽  
Grapevine Virus ◽  
Grapevine Virus A ◽  
Strong Negative Selection ◽  
Epidemiological Characteristics

Grapevine virus A (GVA; genus Vitivirus, family Betaflexiviridae) has been implicated with the Kober stem grooving disorder of the rugose wood disease complex. In this study, 26 isolates of GVA recovered from wine grape (Vitis vinifera) cultivars from California and Washington were analyzed for their genetic diversity. An analysis of a portion of the RNA-dependent RNA polymerase (RdRp) and complete coat protein (CP) sequences revealed intra- and inter-isolate sequence diversity. Our results indicated that both RdRp and CP are under strong negative selection based on the normalized values for the ratio of nonsynonymous substitutions per nonsynonymous site to synonymous substitutions per synonymous site. A global phylogenetic analysis of CP sequences revealed segregation of virus isolates into four major clades with no geographic clustering. In contrast, the RdRp-based phylogenetic tree indicated segregation of GVA isolates from California and Washington into six clades, independent of geographic origin or cultivar. Phylogenetic network coupled with recombination analyses showed putative recombination events in both RdRp and CP sequence data sets, with more of these events located in the CP sequence. The preponderance of divergent variants of GVA co-replicating within individual grapevines could increase viral genotypic complexity with implications for phylogenetic analysis and evolutionary history of the virus. The knowledge of genetic diversity of GVA generated in this study will provide a foundation for elucidating the epidemiological characteristics of virus populations at different scales and implementing appropriate management strategies for minimizing the spread of genetic variants of the virus by vectors and via planting materials supplied to nurseries and grape growers.

scholarly journals Development and Validation of Polymorphic Microsatellite Loci for the NA2 Lineage of Phytophthora ramorum from Whole Genome Sequence Data

Plant Disease ◽  
2017 ◽  
Vol 101 (5) ◽  
pp. 666-673 ◽  
Author(s):  
Marie-Claude Gagnon ◽  
Nicolas Feau ◽  
Angela L. Dale ◽  
Braham Dhillon ◽  
Richard C. Hamelin ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Genome Sequence ◽  
Sequence Data ◽  
Ornamental Plants ◽  
Phytophthora Ramorum ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
And Migration

Phytophthora ramorum is the causal agent of sudden oak death and sudden larch death, and is also responsible for causing ramorum blight on woody ornamental plants. Many microsatellite markers are available to characterize the genetic diversity and population structure of P. ramorum. However, only two markers are polymorphic in the NA2 lineage, which is predominant in Canadian nurseries. Microsatellite motifs were mined from whole-genome sequence data of six P. ramorum NA2 isolates. Of the 43 microsatellite primer pairs selected, 13 loci displayed different allele sizes among the four P. ramorum lineages, 10 loci displayed intralineage variation in the EU1, EU2, and/or NA1 lineages, and 12 microsatellites displayed polymorphism in the NA2 lineage. Genotyping of 272 P. ramorum NA2 isolates collected in nurseries in British Columbia, Canada, from 2004 to 2013 revealed 12 multilocus genotypes (MLGs). One MLG was dominant when examined over time and across sampling locations, and only a few mutations separated the 12 MLGs. The NA2 population observed in Canadian nurseries also showed no signs of sexual recombination, similar to what has been observed in previous studies. The markers developed in this study can be used to assess P. ramorum inter- and intralineage genetic diversity and generate a better understanding of the population structure and migration patterns of this important plant pathogen, especially for the lesser-characterized NA2 lineage.

scholarly journals Simulation of African and non-African low and high coverage whole genome sequence data to assess variant calling approaches

2020 ◽  
Author(s):  
Shatha Alosaimi ◽  
Noëlle van Biljon ◽  
Denis Awany ◽  
Prisca K Thami ◽  
Joel Defo ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
False Positive ◽  
Sequence Data ◽  
False Negative ◽  
Variant Calling ◽  
High Rate ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Sequence Coverage ◽  
High Coverage

Abstract Current variant calling (VC) approaches have been designed to leverage populations of long-range haplotypes and were benchmarked using populations of European descent, whereas most genetic diversity is found in non-European such as Africa populations. Working with these genetically diverse populations, VC tools may produce false positive and false negative results, which may produce misleading conclusions in prioritization of mutations, clinical relevancy and actionability of genes. The most prominent question is which tool or pipeline has a high rate of sensitivity and precision when analysing African data with either low or high sequence coverage, given the high genetic diversity and heterogeneity of this data. Here, a total of 100 synthetic Whole Genome Sequencing (WGS) samples, mimicking the genetics profile of African and European subjects for different specific coverage levels (high/low), have been generated to assess the performance of nine different VC tools on these contrasting datasets. The performances of these tools were assessed in false positive and false negative call rates by comparing the simulated golden variants to the variants identified by each VC tool. Combining our results on sensitivity and positive predictive value (PPV), VarDict [PPV = 0.999 and Matthews correlation coefficient (MCC) = 0.832] and BCFtools (PPV = 0.999 and MCC = 0.813) perform best when using African population data on high and low coverage data. Overall, current VC tools produce high false positive and false negative rates when analysing African compared with European data. This highlights the need for development of VC approaches with high sensitivity and precision tailored for populations characterized by high genetic variations and low linkage disequilibrium.

scholarly journals Development of genomic simple sequence repeat markers for Glycyrrhiza lepidota and cross-amplification of other Glycyrrhiza species

2019 ◽  
Author(s):  
Jun Hyoung Bang ◽  
Chi Eun Hong ◽  
Sebastin Raveendar ◽  
Kyong Hwan Bang ◽  
Kyung Ho Ma ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Ssr Markers ◽  
Simple Sequence Repeat ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Sequence Repeat ◽  
Molecular Studies ◽  
Simple Sequence ◽  
Genomic Simple Sequence Repeat

Background. Licorice (Glycyrrhiza spp. L.) is used as a natural sweetener and medicinal herb. Molecular studies have been conducted to find differences between wild and cultivated species because most wild species are highly resistant to abiotic and biotic stresses compared with their cultivated counterparts. However, few molecular markers have been developed for studying the genetic diversity and population structure of licorice species and to identify differences between cultivars. Thus, the present study aimed to develop a set of genomic simple sequence repeat (SSR) markers for molecular studies of these species. Methods. We designed 100 SSR markers based on the whole-genome sequence data of wild Glycyrrhiza lepidota and selected 62 SSR markers. Results. The genetic diversity analysis using these markers identified 2–23 alleles, and the major allele frequency, observed heterozygosity, genetic diversity, and polymorphism information content were 0.11–0.91, 0–0.90, 0.17–0.94, and 0.15–0.93, respectively. Interspecies transferability values were 93.5%, 91.6%, and 91.1% for G. echinata, G. glabra, and G. uralensis, respectively. Phylogenetic analysis clustered cultivated (group 1) and wild (group 2) species into three and two subgroups, respectively. The SSR markers developed here can be applied to genetic diversity, population structure, and cultivar differentiation studies, as well as to breeding of licorice varieties.

scholarly journals Genetic Analyses of Saprolegnia Strains Isolated from Salmonid Fish of Different Geographic Origin Document the Connection Between Pathogenicity and Molecular Diversity

2021 ◽  
Vol 7 (9) ◽  
pp. 713
Author(s):  
Abdelhameed Elameen ◽  
Svein Stueland ◽  
Ralf Kristensen ◽  
Rosa F. Fristad ◽  
Trude Vrålstad ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Sequence Data ◽  
Genetic Relationships ◽  
Geographic Origin ◽  
Mantel Test ◽  
Group Method ◽  
Aflp Analysis ◽  
Its Sequencing ◽  
Sequencing Data ◽  
Pair Group

Saprolegnia parasitica is recognized as one of the most important oomycetes pests of salmon and trout species. The amplified fragment length polymorphism (AFLP) and method sequence data of the internal transcribed spacer (ITS) were used to study the genetic diversity and relationships of Saprolegnia spp. collected from Canada, Chile, Japan, Norway and Scotland. AFLP analysis of 37 Saprolegnia spp. isolates using six primer combinations gave a total of 163 clear polymorphic bands. Bayesian cluster analysis using genetic similarity divided the isolates into three main groups, suggesting that there are genetic relationships among the isolates. The unweighted pair group method with arithmetic mean (UPGMA) and principal coordinate analysis (PCO) confirmed the pattern of the cluster analyses. ITS analyses of 48 Saprolegnia sequences resulted in five well-defined clades. Analysis of molecular variance (AMOVA) revealed greater variation within countries (91.01%) than among countries (8.99%). We were able to distinguish the Saprolegnia isolates according to their species, ability to produce oogonia with and without long spines on the cysts and their ability to or not to cause mortality in salmonids. AFLP markers and ITS sequencing data obtained in the study, were found to be an efficient tool to characterize the genetic diversity and relationships of Saprolegnia spp. The comparison of AFLP analysis and ITS sequence data using the Mantel test showed a very high and significant correlation (r2 = 0.8317).

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