Computer programs for population genetics data analysis: a survival guide

A general and efficient representation of ancestral recombination graphs

As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. However, this approach is out of step with some modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalizes these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

A general and efficient representation of ancestral recombination graphs

As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. This approach is out of step with modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalises these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

First report on the molecular detection and genetic diversity of Anaplasma marginale in healthy dairy cattle in Khon Kaen province, Thailand

Background and Aim

Bovine anaplasmosis (BA) is one of the most important diseases of ruminants worldwide, causing significant economic losses in the livestock industry due to the high morbidity and mortality in susceptible cattle herds. Anaplasma marginale is the main causative agent of BA occurring worldwide in tropical and subtropical regions. This study aimed to investigate the first molecular detection and genetic diversity of A. marginale in dairy cattle in Khon Kaen Province, Thailand.

Materials and Methods

Blood samples were collected from 385 lactating cows from 40 dairy farms in five districts of Khon Kaen, regardless of age and health status. To detect A. marginale, all DNA preparations were used for molecular diagnosis using a single polymerase chain reaction with the msp4 gene target. A phylogenetic tree was constructed from the msp4 gene sequences using molecular genetic characterization. Genetic diversity was calculated as haplotype diversity, haplotype number, number of nucleotide differences, nucleotide diversity, and average number of nucleotide differences.

Results

The overall prevalence of A. marginale was 12.72% (49/385). The highest prevalence (17.19%) was found in Ubolratana district, followed by Muang, Kranuan, Khao Suan Kwang, and Nam Phong districts (14.94%, 14.74%, 13.79%, and 3.70%, respectively). Phylogenetic analysis showed that A. marginale was closely related to isolates from Australia (98.96%), China (99.68%), Spain (99.74%), and the USA (99.63%).

Conclusion

The molecular prevalence of BA in dairy cattle is the first to be observed in this area, and the genetic variability with separated clusters shown in the msp4 gene of A. marginale revealed species variation in dairy cattle. This significant genetic diversity contributes to the understanding of the diversity of A. marginale and will be important for the control and prevention of A. marginale in dairy cattle.

GenAPoPop 1.0: A user-friendly software to analyse genetic diversity and structure from partially clonal and selfed autopolyploid organisms

Autopolyploidy is quite common in most clades of eukaryotes. The emergence of sequence-based genotyping methods with individual and marker tags now enables confident allele dosage, overcoming the main obstacle to the democratization of the population genetic approaches when studying ecology and evolution of autopolyploid populations and species. Reproductive modes, including clonality, selfing and allogamy, have deep consequences on the ecology and evolution of population and species. Analysing genetic diversity and its dynamics over generations is one efficient way to infer the relative importance of clonality, selfing and allogamy in populations. GenAPoPop is a user-friendly solution to compute the specific corpus of population genetic indices, including indices about genotypic diversity, needed to analyse partially clonal, selfed and allogamous polysomic populations genotyped with confident allele dosage. It also easily provides the posterior probabilities of quantitative reproductive modes in autopolyploid populations genotyped at two-time steps and a graphical representation of the minimum spanning trees of the genetic distances between polyploid individuals, facilitating the interpretation of the genetic coancestry between individuals in hierarchically structured populations. GenAPoPop complements the previously existing solutions, including SPAGEDI and POLYGENE, to use genotypings to study the ecology and evolution of autopolyploid populations. It was specially developed with a simple graphical interface and workflow, and comes with a simulator to facilitate practical courses and teaching of population genetics for autopolyploid populations.

Roadmap to the study of gene and protein phylogeny and evolution-A practical guide

Developments in sequencing technologies and the sequencing of an ever-increasing number of genomes have revolutionised studies of biodiversity and organismal evolution. This accumulation of data has been paralleled by the creation of numerous public biological databases through which the scientific community can mine the sequences and annotations of genomes, transcriptomes, and proteomes of multiple species. However, to find the appropriate databases and bioinformatic tools for respective inquiries and aims can be challenging. Here, we present a compilation of DNA and protein databases, as well as bioinformatic tools for phylogenetic reconstruction and a wide range of studies on molecular evolution. We provide a protocol for information extraction from biological databases and simple phylogenetic reconstruction using probabilistic and distance methods, facilitating the study of biodiversity and evolution at the molecular level for the broad scientific community.

Survivors and colonizers: Contrasting biogeographic histories reconciled in the Antarctic freshwater copepod Boeckella poppei

Two main hypotheses have been proposed to explain the contemporary distribution of Antarctic terrestrial biota. We assess whether the current distribution of maritime Antarctic populations of the freshwater copepod Boeckella poppei is the result of (1) a post-Last Glacial Maximum (LGM) colonization, or whether (2) the species survived in regional glacial refugia throughout the LGM and earlier glaciations. Using 438 specimens from 34 different sampling sites across Southern South America, South Georgia, South Orkney Islands, South Shetland Islands, and the Antarctic Peninsula, we analyzed mitochondrial and nuclear sequences to uncover patterns of genetic diversity and population structure. We also performed median-joining haplotype network, phylogenetic reconstruction, and divergence time analyses. Finally, we evaluated past demographic changes and historical scenarios using the Approximate Bayesian Computation (ABC) method. Our data support the existence of two clades with different and contrasting biogeographic histories. The first clade has been present in maritime Antarctica since at least the mid-Pleistocene, with the South Orkney Islands the most likely refugial area. The second clade has a broader distribution including southern South America, South Georgia, South Shetland Islands, and the Antarctic Peninsula. The ABC method identified long-distance dispersal (LDD) colonization event(s) from southern South America to South Georgia and the maritime Antarctic after the LGM deglaciation, supporting more recent colonization of Antarctic locations. The current Antarctic and sub-Antarctic distribution of B. poppei is likely derived from two independent biogeographic events. The combination of both (1) post-LGM colonization from southern South America and (2) longer-term persistence in in situ regional refugia throughout glacial periods challenges current understanding of the biogeographic history of Antarctic freshwater biota. Re-colonization of ice-impacted Antarctic areas would have occurred following a LDD and Establishment model, pointing to the existence of possible post-dispersal barriers, despite widely assumed high passive dispersal capacity in freshwater invertebrates.

New strategies for characterizing genetic structure in wide-ranging, continuously distributed species: A Greater Sage-grouse case study

Characterizing genetic structure across a species’ range is relevant for management and conservation as it can be used to define population boundaries and quantify connectivity. Wide-ranging species residing in continuously distributed habitat pose substantial challenges for the characterization of genetic structure as many analytical methods used are less effective when isolation by distance is an underlying biological pattern. Here, we illustrate strategies for overcoming these challenges using a species of significant conservation concern, the Greater Sage-grouse (Centrocercus urophasianus), providing a new method to identify centers of genetic differentiation and combining multiple methods to help inform management and conservation strategies for this and other such species. Our objectives were to (1) describe large-scale patterns of population genetic structure and gene flow and (2) to characterize genetic subpopulation centers across the range of Greater Sage-grouse. Samples from 2,134 individuals were genotyped at 15 microsatellite loci. Using standard STRUCTURE and spatial principal components analyses, we found evidence for four or six areas of large-scale genetic differentiation and, following our novel method, 12 subpopulation centers of differentiation. Gene flow was greater, and differentiation reduced in areas of contiguous habitat (eastern Montana, most of Wyoming, much of Oregon, Nevada, and parts of Idaho). As expected, areas of fragmented habitat such as in Utah (with 6 subpopulation centers) exhibited the greatest genetic differentiation and lowest effective migration. The subpopulation centers defined here could be monitored to maintain genetic diversity and connectivity with other subpopulation centers. Many areas outside subpopulation centers are contact zones where different genetic groups converge and could be priorities for maintaining overall connectivity. Our novel method and process of leveraging multiple different analyses to find common genetic patterns provides a path forward to characterizing genetic structure in wide-ranging, continuously distributed species.

Extremely low mtDNA diversity and high genetic differentiation reveal the precarious genetic status of dugongs in New Caledonia, South Pacific

New Caledonia is home to one of the largest remaining populations of dugongs (Dugong dugon) and is located at the southeastern limit of the species' range. Local knowledge suggests that current levels of removal due to anthropogenic pressures are unsustainable, while trends suggest an ongoing decline in the population. Considering this unfavorable conservation context, this study aimed to assess the New Caledonian dugong population's resilience by determining its level of genetic diversity and degree of isolation relative to other populations. Mitochondrial DNA (mtDNA) control region sequences (n = 55) collected from live and dead dugongs in New Caledonia were compared to a global dataset of previously published sequences (n = 631) representing dugong populations throughout the species range. The New Caledonian dugong population displayed the lowest level of mtDNA diversity documented worldwide (3 haplotypes with 1 base pair difference), suggesting a recent origin of the current population through limited colonization events. Population structure analyses indicate a strong genetic differentiation with all the putative populations represented in the global dataset, including large neighbouring Australian populations. These results show that the dugong population in New Caledonia is particularly isolated, fragile, and vulnerable to anthropogenic threats and diseases with low potential for resilience through incoming gene flow. Our findings call for an instant conservation response and consideration for IUCN population assessment to support the long-term survival of the New Caledonian dugong population.

The relative fitness of the de novo variants in general Lithuanian population vs. in individuals with intellectual disability

The effect of a variant on an organism is always multifaceted and can be considered from multiple perspectives-biochemical, medical, or evolutionary. However, the relationship between the effects of amino acid substitution on protein activity, human health, and an individual's evolutionary fitness is not trivial. We uncover that the general Lithuanian population is characterized by a "mirror reflection" of the de novo variant fitness effect, confirming the theory of neutrality. Meanwhile, in the group of individuals with intellectual disability, compared with the reference exome de novo variants significantly changed the composition of the amino acid. Therefore, it predicts that, both in terms of the number of amino acids and changes in their relative fitness, the structure of the proteins encoded by the studied amino acids undergo significant changes following the de novo variant, leading to possible changes in protein function associated with phenotypic traits. These results suggest that the analysis of relative fitness of exome sequences with de novo variants can predict the future phenotype. Therefore even in those cases, then only a few of all functional prediction analysis tools predict a variant as damaging, the negative relative fitness or even adaptability of the genome variant should be carefully evaluated considering both its direct function and the global background of the possible disease-associated mechanism regardless of the phenotype being studied.

Phylogeography and population genetics of the cryptic bonnethead shark Sphyrna aff. tiburo in Brazil and the Caribbean inferred from mtDNA markers

Resolving the identity, phylogeny and distribution of cryptic species within species complexes is an essential precursor to management. The bonnethead shark, Sphyrna tiburo, is a small coastal shark distributed in the Western Atlantic from North Carolina (U.S.A.) to southern Brazil. Genetic analyses based on mitochondrial markers revealed that bonnethead sharks comprise a species complex with at least two lineages in the Northwestern Atlantic and the Caribbean (S. tiburo and Sphyrna aff. tiburo, respectively). The phylogeographic and phylogenetic analysis of two mitochondrial markers [control region (mtCR) and cytochrome oxidase I (COI)] showed that bonnethead sharks from southeastern Brazil correspond to S. aff. tiburo, extending the distribution of this cryptic species >5000 km. Bonnethead shark populations are only managed in the U.S.A. and in the 2000s were considered to be regionally extinct or collapsed in southeast Brazil. The results indicate that there is significant genetic differentiation between S. aff. tiburo from Brazil and other populations from the Caribbean (Φ_ST  = 0.9053, P < 0.000), which means that collapsed populations in the former are unlikely to be replenished from Caribbean immigration. The species identity of bonnethead sharks in the Southwest Atlantic and their relationship to North Atlantic and Caribbean populations still remains unresolved. Taxonomic revision and further sampling are required to reevaluate the status of the bonnethead shark complex through its distribution range.

Genetic structure and ecological niche segregation of Indian gray mongoose (Urva edwardsii) in Iran

Combining genetic data with ecological niche models is an effective approach for exploring climatic and nonclimatic environmental variables affecting spatial patterns of intraspecific genetic variation. Here, we adopted this combined approach to evaluate genetic structure and ecological niche of the Indian gray mongoose (Urva edwardsii) in Iran, as the most western part of the species range. Using mtDNA, we confirmed the presence of two highly differentiated clades. Then, we incorporated ensemble of small models (ESMs) using climatic and nonclimatic variables with genetic data to assess whether genetic differentiation among clades was coupled with their ecological niche. Climate niche divergence was also examined based on a principal component analysis on climatic factors only. The relative habitat suitability values predicted by the ESMs for both clades revealed their niche separation. Between-clade climate only niche comparison revealed that climate space occupied by clades is similar to some extent, but the niches that they utilize differ between the distribution ranges of clades. We found that in the absence of evidence for recent genetic exchanges, distribution models suggest the species occurs in different niches and that there are apparent areas of disconnection across the species range. The estimated divergence time between the two Iranian clades (4.9 Mya) coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The Zagros mountain-building event seems to have prevented the distribution of U. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events. Our findings indicated that the two U. edwardsii genetic clades in Iran can be considered as two conservation units and can be utilized to develop habitat-specific and climate change-integrated management strategies.

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Evaluation and comparison of population genetics software in Rabari Tribe of Gujarat population

Background

Today, when forensic experts talk about quantifiable hereditary traits, they do not just depend on the assessment and examination of DNA profiles but also relate them to the population structures. The use of high-throughput molecular marker technologies and advanced statistical and software tools have improved the accuracy of human genetic diversity analysis in many populations with limited time and resources. The present study aimed to investigate the genomic diversity in Gujarat’s Rabari population, using 20 autosomal genetic markers.

Numerous bio-statistical software programs are available for the interpretation of population data in forensics. These statistics deal with the measurement of uncertainty and also provides a probability of a random match. The present paper aims to provide a practical guide to the analysis of population genetics data. Three statistical software packages named Cervus, Genepop, and Fstat are compared and contrasted. The comparison is performed on the profiles obtained from fifty unrelated blood samples of healthy male individuals. DNA was extracted using the organic extraction method, 20 autosomal STR loci were amplified using PowerPlex 21 kit (Promega, Madison, WI, USA) and detected on 3100 Genetic Analyser (Life Technologies Corporation, Carlsbad, CA, USA).

Results

A total of 170 alleles were observed in the Rabari Tribe of Gujarat population, and allele frequencies ranged from 0.010 to 0.480. The highest allele frequency detected was 0.480 for allele 9 at locus TH01. Based on heterozygosity and the polymorphism information content, FGA may be considered as the most informative markers. Both the combined power of discrimination (CPD) and the combined power of exclusion (CPE) for the 20 analyzed loci were higher than 0.999999. The combined match probability (CPM) for all 20 loci was 2.5 × 10−22.

Conclusions

With respect to the results, the 20 STR loci are highly polymorphic and discriminating in the Gujarat population and could be used for forensic practice and population genetics studies. However, Fstat demonstrated better genetic software for analysis of the demographic structure of a specific or set of populations.

The Codon Usage Code for Cotranslational Folding of Viral Capsids

Codon bias is common to all organisms and is the result of mutation, drift, and selection. Selection for the efficiency and accuracy of translation is well recognized as a factor shaping the codon usage. In contrast, fewer studies report the control of the rate of translation as an additional selective pressure influencing the codon usage of an organism. Experimental molecular evolution using RNA virus populations is a powerful tool for the identification of mechanisms underlying the codon bias. Indeed, the role of deoptimized codons on the cotranslational folding has been proven in the capsids of two fecal-orally transmitted picornaviruses, poliovirus, and the hepatitis A virus, emphasizing the role of the frequency of codons in determining the phenotype. However, most studies on virus codon usage rely only on computational analyses, and experimental studies should be encouraged to clearly define the role of selection on codon evolution.

The evolutionary dynamics of biological invasions: A multi-approach perspective

Biological invasions, the establishment and spread of non-native species in new regions, can have extensive economic and environmental consequences. Increased global connectivity accelerates introduction rates, while climate and land-cover changes may decrease the barriers to invasive populations spread. A detailed knowledge of the invasion history, including assessing source populations, routes of spread, number of independent introductions, and the effects of genetic bottlenecks and admixture on the establishment success, adaptive potential, and further spread, is crucial from an applied perspective to mitigate socioeconomic impacts of invasive species, as well as for addressing fundamental questions on the evolutionary dynamics of the invasion process. Recent advances in genomics together with the development of geographic information systems provide unprecedented large genetic and environmental datasets at global and local scales to link population genomics, landscape ecology, and species distribution modeling into a common framework to study the invasion process. Although the factors underlying population invasiveness have been extensively reviewed, analytical methods currently available to optimally combine molecular and environmental data for inferring invasive population demographic parameters and predicting further spreading are still under development. In this review, we focus on the few recent insect invasion studies that combine different datasets and approaches to show how integrating genetic, observational, ecological, and environmental data pave the way to a more integrative biological invasion science. We provide guidelines to study the evolutionary dynamics of invasions at each step of the invasion process, and conclude on the benefits of including all types of information and up-to-date analytical tools from different research areas into a single framework.

An overview of current population genomics methods for the analysis of whole-genome resequencing data in eukaryotes

Characterizing the population history of a species and identifying loci underlying local adaptation is crucial in functional ecology, evolutionary biology, conservation and agronomy. The constant improvement of high-throughput sequencing techniques has facilitated the production of whole genome data in a wide range of species. Population genomics now provides tools to better integrate selection into a historical framework, and take into account selection when reconstructing demographic history. However, this improvement has come with a profusion of analytical tools that can confuse and discourage users. Such confusion limits the amount of information effectively retrieved from complex genomic data sets, and impairs the diffusion of the most recent analytical tools into fields such as conservation biology. It may also lead to redundancy among methods. To address these isssues, we propose an overview of more than 100 state-of-the-art methods that can deal with whole genome data. We summarize the strategies they use to infer demographic history and selection, and discuss some of their limitations. A website listing these methods is available at www.methodspopgen.com.

Reply to the comment by Morales et al. on “Population genetics reveal Myotis keenii (Keen’s myotis) and Myotis evotis (long-eared myotis) to be a single species”

A.E. Morales et al. (2021. Can. J. Zool. 99(5): 415–422) provided no new evidence to alter the conclusions of C.L. Lausen et al. (2019. Can. J. Zool. 97(3): 267–279). We present background information, relevant comparisons, and clarification of analyses to further strengthen our conclusions. The genesis of the original “evotis–keenii” study in British Columbia (Canada) was to differentiate Myotis keenii (Merriam, 1895) (Keen’s myotis), with one of the smallest North American bat distributions, from sympatric Myotis evotis (H. Allen, 1864) (long-eared myotis), using something other than the suggested post-mortem skull size comparison, but no differentiating trait could be found, leading to the molecular genetics examination of C.L. Lausen et al. (2019). We present cumulative data that rejects the 1979 hypothesis of M. keenii as a distinct species. A.E. Morales et al. (2021) inaccurately portray C.L. Lausen et al.’s (2019) question and results; present inaccurate morphological and outdated distribution data; overstate the impact of homoplasy without supporting evidence; and misinterpret evidence of population structure.

Primate landscape genetics: A review and practical guide

Landscape genetics is an emerging field that integrates population genetics, landscape ecology, and spatial statistics to investigate how geographical and environmental features and evolutionary processes such as gene flow, genetic drift, and selection structure genetic variation at both the population and individual levels, with implications for ecology, evolution, and conservation biology. Despite being particularly well suited for primatologists, this method is currently underutilized. Here, we synthesize the current state of research on landscape genetics in primates. We begin by outlining how landscape genetics has been used to disentangle the drivers of diversity, followed by a review of how landscape genetic methods have been applied to primates. This is followed by a section highlighting special considerations when applying the methods to primates, and a practical guide to facilitate further landscape genetics studies using both existing and de novo datasets. We conclude by exploring future avenues of inquiry that could be facilitated by recent developments as well as underdeveloped applications of landscape genetics to primates.

A workflow with R: Phylogenetic analyses and visualizations using mitochondrial cytochrome b gene sequences

Phylogenetic analyses can provide a wealth of information about the past demography of a population and the level of genetic diversity within and between species. By using special computer programs developed in recent years, large amounts of data have been produced in the molecular genetics area. To analyze these data, powerful new methods based on large computations have been applied in various software packages and programs. But these programs have their own specific input and output formats, and users need to create different input formats for almost every program. R is an open source software environment, and it supports open contribution and modification to its libraries. Furthermore, it is also possible to perform several analyses using a single input file format. In this article, by using the multiple sequences FASTA format file (.fas extension) we demonstrate and share a workflow of how to extract haplotypes and perform phylogenetic analyses and visualizations in R. As an example dataset, we used 120 Bombus terrestris dalmatinus mitochondrial cytochrome b gene (cyt b) sequences (373 bp) collected from eight different beehives in Antalya. This article presents a short guide on how to perform phylogenetic analyses using R and RStudio.

HW_TEST, a program for comprehensive HARDY-WEINBERG equilibrium testing

This article deals with a Windows (© Microsoft Inc.) executable, user-friendly program that tests the hypothesis of Hardy-Weinberg (HW) proportions from autosomal multiallelic data using different methods that include parametric, nonparametric and exact bootstrap tests, the latter obtained through computer simulations. The program can be obtained free of charge directly from the internet repository https://github.com/Lemes-RenanB/HardyWeinbergTesting.

GenPop-An Online Tool to Analyze Human Population Genetic Data

GenPop is a web based online cross platform tool developed to help Geneticist and Epidemiologist to deal with association studies in analyzing human population genetic data. The tool features include descriptive analysis such as Hardy-Weinberg equilibrium test, chi-square p-value and analysis of single nucleotide polymorphisms (SNPs) with multiple inheritance models such as dominant, recessive, allelic, genotype, odd's ratio and relative risk at 95% confidence interval and analysis of multiple SNPs including haplotype frequencies and linkage disequilibrium for a pair of biallelic markers. This is a user-driven human population genetic data analysis tool that is easily scalable and acceptable with multiple implementations of different algorithms. GenPop has been developed using PHP, JavaScript and with PHPExcel library to analyse the genetic data for case control studies.

Genetic Structure of Northern Fowl Mite (Mesostigmata: Macronyssidae) Populations Among Layer Chicken Flocks and Local House Sparrows (Passeriformes: Passeridae)

The northern fowl mite (NFM) Ornithonyssus sylviarum Canestrini and Fanzago is a blood-feeding ectoparasite found on many wild bird species and is a pest of poultry in the United States. It is unknown where NFM infestations of poultry originate, which has made it difficult to establish preventative biosecurity or effective control. We used microsatellite markers to evaluate genetic variation within and among NFM populations to determine routes of introduction onto farms and long-term persistence. We compared NFM from flocks of chickens (Gallus gallus) on different farms in California, Washington, and Georgia, and we compared NFM collected over a 5-yr interval. On three farms we collected NFM from chickens and house sparrows (Passer domesticus) nesting on each farm, which we used to assess movement between host species. There was strong genetic structure among mites from different poultry farms and low estimates of migration between farms. There were significant differences between mites on chickens and house sparrows on two farms where sparrows nested near flocks, indicating no exchange of mites. Only one farm showed evidence of NFM movement between chickens and sparrows. There was high genetic similarity between mites collected 5 yr apart on each of two farms, indicating that NFM infestations can persist for long periods. The genetic patterns did not reveal sources of NFM infestations on chicken farms. The data suggest that NFMs are strongly differentiated, which likely reflects periodic population declines with flock turnover and pesticide pressure.

In vivo single-cell lineage tracing in zebrafish using high-resolution infrared laser-mediated gene induction microscopy

Heterogeneity broadly exists in various cell types both during development and at homeostasis. Investigating heterogeneity is crucial for comprehensively understanding the complexity of ontogeny, dynamics, and function of specific cell types. Traditional bulk-labeling techniques are incompetent to dissect heterogeneity within cell population, while the new single-cell lineage tracing methodologies invented in the last decade can hardly achieve high-fidelity single-cell labeling and long-term in-vivo observation simultaneously. In this work, we developed a high-precision infrared laser-evoked gene operator heat-shock system, which uses laser-induced CreERT2 combined with loxP-DsRedx-loxP-GFP reporter to achieve precise single-cell labeling and tracing. In vivo study indicated that this system can precisely label single cell in brain, muscle and hematopoietic system in zebrafish embryo. Using this system, we traced the hematopoietic potential of hemogenic endothelium (HE) in the posterior blood island (PBI) of zebrafish embryo and found that HEs in the PBI are heterogeneous, which contains at least myeloid unipotent and myeloid-lymphoid bipotent subtypes.

Conservation genetics of the bonnethead shark Sphyrna tiburo in Bocas del Toro, Panama: Preliminary evidence of a unique stock

The bonnethead shark, Sphyrna tiburo, is a small elasmobranch distributed in the Eastern Pacific from southern California to Ecuador, and along the Western Atlantic, with preferences for continental margins of North, Central and South America, the Gulf of Mexico, and the Caribbean. Recent studies have suggested that it could be under a process of cryptic speciation, with the possibility to find different species in similar geographic locations. Here we assessed the population structure and genetic diversity of this highly philopatric and non-dispersive species in the Bocas del Toro Archipelago, Panama. Fragments of the mitochondrial genes cytochrome oxidase I and control region, were used to test the genetic structure of adult and juvenile S. tiburo in this area, and were compared with other locations of the Western Atlantic and Belize. We found significant genetic differentiation between Caribbean bonnethead sharks from Bocas del Toro and Belize, when compared to bonnetheads from other locations of the Western Atlantic. These results also suggest that Bocas del Toro could constitute a different genetic population unit for this species, whereby bonnethead sharks in this area could belong to a unique stock. The information obtained in this study could improve our understanding of the population dynamics of the bonnethead shark throughout its distribution range, and may be used as a baseline for future conservation initiatives for coastal sharks in Central America, a poorly studied an often overlooked region for shark conservation and research.

Comparison of Markov Chain Monte Carlo Software for the Evolutionary Analysis of Y-Chromosomal Microsatellite Data

The evolutionary analysis of genetic data is an important subject of modern bioscience, with practical applications in diverse fields. Parameters of interest in this context include effective population sizes, mutation rates, population growth rates and the times to most recent common ancestors. Studying Y-chromosomal microsatellite data, in particular, has proven useful to unravel the recent patrilineal history of Homo sapiens populations. We compared the individual analysis options and technical details of four software tools that are widely used for this purpose, namely BATWING, BEAST, IMa2 and LAMARC, all of which use Bayesian coalescent-based Markov chain Monte Carlo (MCMC) methods for parameter estimation. More specifically, we simulated datasets for either eight or 20 hypothetical Y-chromosomal microsatellites, assuming a mutation rate of 0.0030 per generation and a constant or exponentially increasing population size, and used these data to evaluate the parameter estimation capacity of each tool. The datasets comprised between 100 and 1000 samples. In addition to runtime, the practical utility of the tools of interest can also be expected to depend critically upon the convergence behavior of the actual MCMC implementation. In fact, we found that runtime increased, and convergence rate decreased, with increasing sample size as expected. BATWING performed best with respect to runtime and convergence behavior, but only supports simple evolutionary models. As regards the spectrum of evolutionary models covered, and also in terms of cross-platform usability, BEAST provided the greatest flexibility. Finally, IMa2 and LAMARC turned out best to incorporate elaborate migration models in the analysis process.

Genetic divergence, population differentiation and phylogeography of the cicada Subpsaltria yangi based on molecular and acoustic data: an example of the early stage of speciation?

Background

Geographical isolation combined with historical climatic fluctuations have been identified as two major factors that contribute to the formation of new species. On the other hand, biotic factors such as competition and predation are also able to drive the evolution and diversification of organisms. To determine whether geographical barriers contributed to population divergence or speciation in the rare endemic cicada Subpsaltria yangi the population differentiation, genetic structure and phylogeography of the species were investigated in the Loess Plateau and adjacent areas of northwestern China by analysing mitochondrial and nuclear DNA and comparing the calling song structure of 161 male individuals.

Results

The results reveal a low level of genetic differentiation and relatively simple phylogeographic structure for this species, but two independent clades corresponding to geographically isolated populations were recognised. Genetic and geographical distances were significantly correlated among lineages. Results of divergence-time estimation are consistent with a scenario of isolation due to glacial refugia and interglacial climate oscillation in northwestern China. Significant genetic divergence was found between the population occurring in the Helan Mountains and other populations, and recent population expansion has occurred in the Helan Mountains and/or adjacent areas. This population is also significantly different in calling song structure from other populations.

Conclusions

Geographical barriers (i.e., the deserts and semi-deserts surrounding the Helan Mountains), possibly coupled with related ecological differences, may have driven population divergence and allopatric speciation. This provides a possible example of incipient speciation in Cicadidae, improves understanding of population differentiation, acoustic signal diversification and phylogeographic relationships of this rare cicada species of conservation concern, and informs future studies on population differentiation, speciation and phylogeography of other insects with a high degree of endemism in the Helan Mountains and adjacent areas.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1317-8) contains supplementary material, which is available to authorized users.

Population Genetics and Molecular Epidemiology of Eukaryotes

Molecular epidemiology uses the distribution and organization of a pathogen's DNA to understand the distribution and determinants of disease. Since the biology of DNA for eukaryotic pathogens differs substantially from that of bacteria, the analytic approach to their molecular epidemiology can also differ. While many of the genotyping techniques presented earlier in this series, "Advances in Molecular Epidemiology of Infectious Diseases," can be applied to eukaryotes, the output must be interpreted in the light of how DNA is distributed from one generation to the next. In some cases, parasite populations can be evaluated in ways reminiscent of bacteria. They differ, however, when analyzed as sexually reproducing organisms, where all individuals are unique but the genetic composition of the population does not change unless a limited set of events occurs. It is these events (migration, mutation, nonrandom mating, selection, and genetic drift) that are of interest. At a given time, not all of them are likely to be equally important, so the list can easily be narrowed down to understand the driving forces behind the population as it is now and even what it will look like in the future. The main population characteristics measured to assess these events are differentiation and diversity, interpreted in the light of what is known about the population from observation. The population genetics of eukaryotes is important for planning and evaluation of control measures, surveillance, outbreak investigation, and monitoring of the development and spread of drug resistance. *This article is part of a curated collection.

iMEC: Online Marker Efficiency Calculator

PREMISE OF THE STUDY

To accurately design plant genetic studies, the information content of utilized markers and primers must be calculated. Plant genotyping studies should take into account the efficiency of each marker system by calculating different parameters to find the optimal combination of primers. This can be problematic because there are currently no easily accessible applications that can be used to calculate multiple indices together.

METHODS AND RESULTS

The program Online Marker Efficiency Calculator (iMEC) was developed using R for the simple computation of seven polymorphism indices (heterozygosity index, polymorphism information content, discriminating power, effective multiplex ratio, marker index, arithmetic mean heterozygosity, and resolving power). These indices are based on dominant and codominant DNA fingerprinting markers, thus allowing comparison and selection of optimal genetic markers for a given data set.

CONCLUSIONS

iMEC simplifies the calculation of diverse indices for the marker of choice to better enable researchers to measure polymorphism information for individual markers. The program is available at https://irscope.shinyapps.io/iMEC/.

Lessons learnt on the analysis of large sequence data in animal genomics

The 'omics revolution has made a large amount of sequence data available to researchers and the industry. This has had a profound impact in the field of bioinformatics, stimulating unprecedented advancements in this discipline. Mostly, this is usually looked at from the perspective of human 'omics, in particular human genomics. Plant and animal genomics, however, have also been deeply influenced by next-generation sequencing technologies, with several genomics applications now popular among researchers and the breeding industry. Genomics tends to generate huge amounts of data, and genomic sequence data account for an increasing proportion of big data in biological sciences, due largely to decreasing sequencing and genotyping costs and to large-scale sequencing and resequencing projects. The analysis of big data poses a challenge to scientists, as data gathering currently takes place at a faster pace than does data processing and analysis, and the associated computational burden is increasingly taxing, making even simple manipulation, visualization and transferring of data a cumbersome operation. The time consumed by the processing and analysing of huge data sets may be at the expense of data quality assessment and critical interpretation. Additionally, when analysing lots of data, something is likely to go awry-the software may crash or stop-and it can be very frustrating to track the error. We herein review the most relevant issues related to tackling these challenges and problems, from the perspective of animal genomics, and provide researchers that lack extensive computing experience with guidelines that will help when processing large genomic data sets.

A fast likelihood solution to the genetic clustering problem

The investigation of genetic clusters in natural populations is an ubiquitous problem in a range of fields relying on the analysis of genetic data, such as molecular ecology, conservation biology and microbiology. Typically, genetic clusters are defined as distinct panmictic populations, or parental groups in the context of hybridisation. Two types of methods have been developed for identifying such clusters: model-based methods, which are usually computer-intensive but yield results which can be interpreted in the light of an explicit population genetic model, and geometric approaches, which are less interpretable but remarkably faster.Here, we introduce snapclust, a fast maximum-likelihood solution to the genetic clustering problem, which allies the advantages of both model-based and geometric approaches. Our method relies on maximising the likelihood of a fixed number of panmictic populations, using a combination of geometric approach and fast likelihood optimisation, using the Expectation-Maximisation (EM) algorithm. It can be used for assigning genotypes to populations and optionally identify various types of hybrids between two parental populations. Several goodness-of-fit statistics can also be used to guide the choice of the retained number of clusters.Using extensive simulations, we show that snapclust performs comparably to current gold standards for genetic clustering as well as hybrid detection, with some advantages for identifying hybrids after several backcrosses, while being orders of magnitude faster than other model-based methods. We also illustrate how snapclust can be used for identifying the optimal number of clusters, and subsequently assign individuals to various hybrid classes simulated from an empirical microsatellite dataset. snapclust is implemented in the package adegenet for the free software R, and is therefore easily integrated into existing pipelines for genetic data analysis. It can be applied to any kind of co-dominant markers, and can easily be extended to more complex models including, for instance, varying ploidy levels. Given its flexibility and computer-efficiency, it provides a useful complement to the existing toolbox for the study of genetic diversity in natural populations.

Effects of Sample Size and Full Sibs on Genetic Diversity Characterization: A Case Study of Three Syntopic Iberian Pond-Breeding Amphibians

Accurate characterization of genetic diversity is essential for understanding population demography, predicting future trends and implementing efficient conservation policies. For that purpose, molecular markers are routinely developed for nonmodel species, but key questions regarding sampling design, such as calculation of minimum sample sizes or the effect of relatives in the sample, are often neglected. We used accumulation curves and sibship analyses to explore how these 2 factors affect marker performance in the characterization of genetic diversity. We illustrate this approach with the analysis of an empirical dataset including newly optimized microsatellite sets for 3 Iberian amphibian species: Hyla molleri, Epidalea calamita, and Pelophylax perezi. We studied 17-21 populations per species (total n = 547, 652, and 516 individuals, respectively), including a reference locality in which the effect of sample size was explored using larger samples (77-96 individuals). As expected, FIS and tests for Hardy-Weinberg equilibrium and linkage disequilibrium were affected by the presence of full sibs, and most initially inferred disequilibria were no longer statistically significant when full siblings were removed from the sample. We estimated that to obtain reliable estimates, the minimum sample size (potentially including full sibs) was close to 20 for expected heterozygosity, and between 50 and 80 for allelic richness. Our pilot study based on a reference population provided a rigorous assessment of marker properties and the effects of sample size and presence of full sibs in the sample. These examples illustrate the advantages of this approach to produce robust and reliable results for downstream analyses.

East of the Andes: The genetic profile of the Peruvian Amazon populations

OBJECTIVES

Assuming that the differences between the Andes and the Amazon rainforest at environmental and historical levels have influenced the distribution patterns of genes, languages, and cultures, the maternal and paternal genetic reconstruction of the Peruvian Amazon populations was used to test the relationships within and between these two extreme environments.

MATERIALS AND METHODS

We analyzed four Peruvian Amazon communities (Ashaninka, Huambisa, Cashibo, and Shipibo) for both Y chromosome (17 STRs and 8 SNPs) and mtDNA data (control region sequences, two diagnostic sites of the coding region, and one INDEL), and we studied their variability against the rest of South America.

RESULTS

We detected a high degree of genetic diversity in the Peruvian Amazon people, both for mtDNA than for Y chromosome, excepting for Cashibo people, who seem to have had no exchanges with their neighbors, in contrast with the others communities. The genetic structure follows the divide between the Andes and the Amazon, but we found a certain degree of gene flow between these two environments, as particularly emerged with the Y chromosome descent cluster's (DCs) analysis.

DISCUSSION

The Peruvian Amazon is home to an array of populations with differential rates of genetic exchanges with their neighbors and with the Andean people, depending on their peculiar demographic histories. We highlighted some successful Y chromosome lineages expansions originated in Peru during the pre-Columbian history which involved both Andeans and Amazon Arawak people, showing that at least a part of the Amazon rainforest did not remain isolated from those exchanges.

Extending GelJ for interoperability: Filling the gap in the bioinformatics resources for population genetics analysis with dominant markers

BACKGROUND AND OBJECTIVE

The manual transformation of DNA fingerprints of dominant markers into the input of tools for population genetics analysis is a time-consuming and error-prone task; especially when the researcher deals with a large number of samples. In addition, when the researcher needs to use several tools for population genetics analysis, the situation worsens due to the incompatibility of data-formats across tools. The goal of this work consists in automating, from banding patterns of gel images, the input-generation for the great diversity of tools devoted to population genetics analysis.

METHODS

After a thorough analysis of tools for population genetics analysis with dominant markers, and tools for working with phylogenetic trees; we have detected the input requirements of those systems. In the case of programs devoted to phylogenetic trees, the Newick and Nexus formats are widely employed; whereas, each population genetics analysis tool uses its own specific format. In order to handle such a diversity of formats in the latter case, we have developed a new XML format, called PopXML, that takes into account the variety of information required by each population genetics analysis tool. Moreover, the acquired knowledge has been incorporated into the pipeline of the GelJ system - a tool for analysing DNA fingerprint gel images - to reach our automatisation goal.

RESULTS

We have implemented, in the GelJ system, a pipeline that automatically generates, from gel banding patterns, the input of tools for population genetics analysis and phylogenetic trees. Such a pipeline has been employed to successfully generate, from thousands of banding patterns, the input of 29 population genetics analysis tools and 32 tools for managing phylogenetic trees.

CONCLUSIONS

GelJ has become the first tool that fills the gap between gel image processing software and population genetics analysis with dominant markers, phylogenetic reconstruction, and tree editing software. This has been achieved by automating the process of generating the input for the latter software from gel banding patterns processed by GelJ.

Different kinds of genetic markers permit inference of Paleolithic and Neolithic expansions in humans

Recent population genetic studies have provided valuable insights on the demographic history of our species. However, some issues such as the dating of the first demographic expansions in human populations remain puzzling. Indeed, although a few genetic studies argued that the first human expansions were concomitant with the Neolithic transition, many others found signals of expansion events starting during the Palaeolithic. Here we performed a simulation study to show that these contradictory findings may result from the differences in the genetic markers used, especially if two successive expansion events occurred. For a large majority of replicates for each scenario tested, microsatellite data allow only detecting the recent expansion event in that case, whereas sequence data allow only detecting the ancient expansion. Combined with previous real data analyses, our results bring support to the ideas that (i) a first human expansions started during the Palaeolithic period, (ii) a second expansion event occurred later, concomitantly with the Neolithic transition.

Genetic Analyses Suggest Separate Introductions of the Pine Pathogen Lecanosticta acicola Into Europe

Lecanosticta acicola is a heterothallic ascomycete that causes brown spot needle blight on native and nonnative Pinus spp. in many regions of the world. In this study we investigated the origin of European L. acicola populations and estimated the level of random mating of the pathogen in affected areas. Part of the elongation factor 1-α gene was sequenced, 11 microsatellite regions were screened, and the mating type idiomorphs were determined for 201 isolates of L. acicola collected from three continents and 17 host species. The isolates from Mexico and Guatemala were unique, highly diverse and could represent cryptic species of Lecanosticta. The isolates from East Asia formed a uniform and discrete group. Two distinct populations were identified in both North America and Europe. Approximate Bayesian computation analyses strongly suggest independent introductions of two populations from North America into Europe. Microsatellite data and mating type distributions indicated random recombination in the populations of North America and Europe. Its intercontinental introduction can most likely be explained as a consequence of the movement of infected plant material. In contrast, the spread of L. acicola within Europe appears to be primarily due to conidial dispersion and probably also ascospore dissemination.

PopSc: Computing Toolkit for Basic Statistics of Molecular Population Genetics Simultaneously Implemented in Web-Based Calculator, Python and R

Although various computer tools have been elaborately developed to calculate a series of statistics in molecular population genetics for both small- and large-scale DNA data, there is no efficient and easy-to-use toolkit available yet for exclusively focusing on the steps of mathematical calculation. Here, we present PopSc, a bioinformatic toolkit for calculating 45 basic statistics in molecular population genetics, which could be categorized into three classes, including (i) genetic diversity of DNA sequences, (ii) statistical tests for neutral evolution, and (iii) measures of genetic differentiation among populations. In contrast to the existing computer tools, PopSc was designed to directly accept the intermediate metadata, such as allele frequencies, rather than the raw DNA sequences or genotyping results. PopSc is first implemented as the web-based calculator with user-friendly interface, which greatly facilitates the teaching of population genetics in class and also promotes the convenient and straightforward calculation of statistics in research. Additionally, we also provide the Python library and R package of PopSc, which can be flexibly integrated into other advanced bioinformatic packages of population genetics analysis.

Biomedical Mutation Analysis (BMA): A software tool for analyzing mutations associated with antiviral resistance

INTRODUCTION

Hepatitis C virus (HCV) is considered a major public health problem, with 200 million people infected worldwide. The treatment for HCV chronic infection with pegylated interferon alpha plus ribavirin inhibitors is unspecific; consequently, the treatment is effective in only 50% of patients infected. This has prompted the development of direct-acting antivirals (DAA) that target virus proteins. These DAA have demonstrated a potent effect in vitro and in vivo; however, virus mutations associated with the development of resistance have been described.

OBJECTIVE

To design and develop an online information system for detecting mutations in amino acids known to be implicated in resistance to DAA.

MATERIALS AND METHODS

   We have used computer applications, technological tools, standard languages, infrastructure systems and algorithms, to analyze positions associated with resistance to DAA for the NS3, NS5A, and NS5B genes of HCV.

RESULTS

We have designed and developed an online information system named Biomedical Mutation Analysis (BMA), which allows users to calculate changes in nucleotide and amino acid sequences for each selected sequence from conventional Sanger and cloning sequencing using a graphical interface.

CONCLUSION

BMA quickly, easily and effectively analyzes mutations, including complete documentation and examples. Furthermore, the development of different visualization techniques allows proper interpretation and understanding of the results. The data obtained using BMA will be useful for the assessment and surveillance of HCV resistance to new antivirals, and for the treatment regimens by selecting those DAA to which the virus is not resistant, avoiding unnecessary treatment failures. The software is available at: http://bma.itiud.org.

Evidence for ecological speciation via a host shift in the holly leaf miner, Phytomyza glabricola (Diptera: Agromyzidae)

Evolutionary radiations have been well documented in plants and insects, and natural selection may often underly these radiations. If radiations are adaptive, the diversity of species could be due to ecological speciation in these lineages. Agromyzid flies exhibit patterns of repeated host-associated radiations. We investigated whether host-associated population divergence and evidence of divergent selection exist in the leaf miner Phytomyza glabricola on its sympatric host plants, the holly species, Ilex coriacea and I. glabra. Using AFLPs and nuclear sequence data, we found substantial genetic divergence between host-associated populations of these flies throughout their geographic range. Genome scans using the AFLP data identified 13 loci under divergent selection, consistent with processes of ecological speciation. EF-1α data suggest that I. glabra is the original host of P. glabricola and that I. coriacea is the novel host, but the AFLP data are ambiguous with regard to directionality of the host shift.

Developing educational resources for population genetics in R: an open and collaborative approach

The r computing and statistical language community has developed a myriad of resources for conducting population genetic analyses. However, resources for learning how to carry out population genetic analyses in r are scattered and often incomplete, which can make acquiring this skill unnecessarily difficult and time consuming. To address this gap, we developed an online community resource with guidance and working demonstrations for conducting population genetic analyses in r. The resource is freely available at http://popgen.nescent.org and includes material for both novices and advanced users of r for population genetics. To facilitate continued maintenance and growth of this resource, we developed a toolchain, process and conventions designed to (i) minimize financial and labour costs of upkeep; (ii) to provide a low barrier to contribution; and (iii) to ensure strong quality assurance. The toolchain includes automatic integration testing of every change and rebuilding of the website when new vignettes or edits are accepted. The process and conventions largely follow a common, distributed version control-based contribution workflow, which is used to provide and manage open peer review by designated website editors. The online resources include detailed documentation of this process, including video tutorials. We invite the community of population geneticists working in r to contribute to this resource, whether for a new use case of their own, or as one of the vignettes from the 'wish list' we maintain, or by improving existing vignettes.

Biomedical Mutation Analysis (BMA): A software tool for analyzing mutations associated with antiviral resistance

Introduction:Hepatitis C virus (HCV) is considered a major public health problem, with 200 million people infected worldwide. The treatment for HCV chronic infection with pegylated interferon alpha plus ribavirin inhibitors is unspecific; consequently, the treatment is effective in only 50% of patients infected. This has prompted the development of direct-acting antivirals (DAA) that target virus proteins. These DAA have demonstrated a potent effectin vitroandin vivo; however, virus mutations associated with the development of resistance have been described.Objective: To design and develop an online information system for detecting mutations in amino acids known to be implicated in resistance to DAA.Materials and methods:    We have used computer applications, technological tools, standard languages, infrastructure systems and algorithms, to analyze positions associated with resistance to DAA for the NS3, NS5A, and NS5B genes of HCV.Results: We have designed and developed an online information system named Biomedical Mutation Analysis (BMA), which allows users to calculate changes in nucleotide and amino acid sequences for each selected sequence from conventional Sanger and cloning sequencing using a graphical interface.Conclusion: BMA quickly, easily and effectively analyzes mutations, including complete documentation and examples. Furthermore, the development of different visualization techniques allows proper interpretation and understanding of the results.The data obtained using BMA will be useful for the assessment and surveillance of HCV resistance to new antivirals, and for the treatment regimens by selecting those DAA to which the virus is not resistant, avoiding unnecessary treatment failures. The software is available at: http://bma.itiud.org.

Microsatellites in Pursuit of Microbial Genome Evolution

Microsatellites or short sequence repeats are widespread genetic markers which are hypermutable 1-6 bp long short nucleotide motifs. Significantly, their applications in genetics are extensive due to their ceaseless mutational degree, widespread length variations and hypermutability skills. These features make them useful in determining the driving forces of evolution by using powerful molecular techniques. Consequently, revealing important questions, for example, what is the significance of these abundant sequences in DNA, what are their roles in genomic evolution? The answers of these important questions are hidden in the ways these short motifs contributed in altering the microbial genomes since the origin of life. Even though their size ranges from 1 -to- 6 bases, these repeats are becoming one of the most popular genetic probes in determining their associations and phylogenetic relationships in closely related genomes. Currently, they have been widely used in molecular genetics, biotechnology and evolutionary biology. However, due to limited knowledge; there is a significant gap in research and lack of information concerning hypermutational mechanisms. These mechanisms play a key role in microsatellite loci point mutations and phase variations. This review will extend the understandings of impacts and contributions of microsatellite in genomic evolution and their universal applications in microbiology.