Applications In Population Genetics Research Articles

Microsatellite Markers for Characterization of Native and Introduced Populations of Plasmopara viticola, the Causal Agent of Grapevine Downy Mildew

We reported 31 microsatellite markers that have been developed from microsatellite-enriched and direct shotgun pyrosequencing libraries of Plasmopara viticola, the causal agent of grapevine downy mildew. These markers were optimized for population genetics applications and used to characterize 96 P. viticola isolates from three European and three North American populations.

A simple method for finding explicit analytic transition densities of diffusion processes with general diploid selection.

The transition density function of the Wright-Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright-Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation-selection balance.

Genetic diversity in wild and cultivated black raspberry (Rubus occidentalis L.) evaluated by simple sequence repeat markers

Breeding progress in black raspberry (Rubus occidentalis L.) has been limited by a lack of genetic diversity in elite germplasm. Black raspberry cultivars have been noted for showing very few phenotypic differences and seedlings from crosses between cultivars for a lack of segregation for important traits. Despite these challenges, little molecular work has been done to explore genetic diversity and relationships in wild and cultivated black raspberry germplasm. Microsatellite, or simple sequence repeat (SSR), markers are highly polymorphic codominant markers useful for studying genetic diversity, population genetics, genetic fingerprinting and other applications. We examined genetic diversity in 148 wild and cultivated black raspberry accessions using 21 polymorphic SSR markers. Black raspberry cultivars clustered tightly and showed higher than expected heterozygosity while that of wild accessions was low. Relationships between wild black raspberry accessions were poorly resolved and regional clusters were mostly absent from our analysis. Our results indicated that wild black raspberry germplasm is a relatively untapped resource available for future breeding.

PyElph - a software tool for gel images analysis and phylogenetics

BackgroundThis paper presents PyElph, a software tool which automatically extracts data from gel images, computes the molecular weights of the analyzed molecules or fragments, compares DNA patterns which result from experiments with molecular genetic markers and, also, generates phylogenetic trees computed by five clustering methods, using the information extracted from the analyzed gel image. The software can be successfully used for population genetics, phylogenetics, taxonomic studies and other applications which require gel image analysis. Researchers and students working in molecular biology and genetics would benefit greatly from the proposed software because it is free, open source, easy to use, has a friendly Graphical User Interface and does not depend on specific image acquisition devices like other commercial programs with similar functionalities do.ResultsPyElph software tool is entirely implemented in Python which is a very popular programming language among the bioinformatics community. It provides a very friendly Graphical User Interface which was designed in six steps that gradually lead to the results. The user is guided through the following steps: image loading and preparation, lane detection, band detection, molecular weights computation based on a molecular weight marker, band matching and finally, the computation and visualization of phylogenetic trees. A strong point of the software is the visualization component for the processed data. The Graphical User Interface provides operations for image manipulation and highlights lanes, bands and band matching in the analyzed gel image. All the data and images generated in each step can be saved. The software has been tested on several DNA patterns obtained from experiments with different genetic markers. Examples of genetic markers which can be analyzed using PyElph are RFLP (Restriction Fragment Length Polymorphism), AFLP (Amplified Fragment Length Polymorphism), RAPD (Random Amplification of Polymorphic DNA) and STR (Short Tandem Repeat). The similarity between the DNA sequences is computed and used to generate phylogenetic trees which are very useful for population genetics studies and taxonomic classification.ConclusionsPyElph decreases the effort and time spent processing data from gel images by providing an automatic step-by-step gel image analysis system with a friendly Graphical User Interface. The proposed free software tool is suitable for researchers and students which do not have access to expensive commercial software and image acquisition devices.

GDF: Dealing with High-throughput Genotyping Multiplatform Data for Medical and Population Genetic Applications

Background: A number of different high throughput genotyping platforms have arisen recently. These platforms generate large amounts of genotyping data which is subsequently processed and stored in public and/or private databases. Both, the variety of platforms employed by the different laboratories and the large amount of data they generate, entail serious problems for data managing in most laboratories. Some public or private software packages available today solve some important needs, but they deal with the data from a point of view that the researcher may probably not share, and no supervision of the results (e.g. genotyping inconsistencies or summaries of the genotyping data) may be performed. Results: The main goal of the Genotyping Data Filter (GDF) software is to allow the researcher to locally manage large numbers of genotypes generated by the most standard genotyping platforms, obtaining statistics and summaries of the genotyping experiments whilst maintaining their privacy. GDF also allows the user to supervise the data such that the researcher can easily evaluate important parameters, including the proportion of missing data in samples and single nucleotide polymorphisms (SNPs), Hardy-Weinberg equilibrium, etc. Additionally, GDF parses the raw data into different text formats needed as input files in popular software packages frequently used in medical and population genetic applications. Conclusions: GDF is a Perl program that efficiently process data from various genotyping platforms, allowing researchers to easily inspect their own genotyping data and to parse it for a wide spectrum of well-known specialized analysis software. It has been prepared to be run through a user friendly web interface on the most common cases, but it can also be run as a local script on personal computers, or even supercomputers for very large-scale projects.

The Fleming-Viot limit of an interacting spatial population with fast density regulation

We consider population models in which the individuals reproduce, die and also migrate in space. The population size scales according to some parameter $N$, which can have different interpretations depending on the context. Each individual is assigned a mass of 1/N and the total mass in the system is called \emph{population density}. The dynamics has an intrinsic density regulation mechanism that drives the population density towards an equilibrium. We show that under a timescale separation between the \emph{slow} migration mechanism and the \emph{fast} density regulation mechanism, the population dynamics converges to a Fleming-Viot process as the scaling parameter $N$ approaches $\infty$. We first prove this result for a basic model in which the birth and death rates can only depend on the population density. In this case we obtain a \emph{neutral} Fleming-Viot process. We then extend this model by including position-dependence in the birth and death rates, as well as, offspring dispersal and immigration mechanisms. We show how these extensions add \emph{mutation} and \emph{selection} to the limiting Fleming-Viot process. All the results are proved in a multi-type setting, where there are $q$ types of individuals interacting with each other. We illustrate the usefulness of our convergence result by discussing applications in population genetics and cell biology.

A multiplex SNP assay for the dissection of human Y-chromosome haplogroup O representing the major paternal lineage in East and Southeast Asia

The majority of human Y chromosomes in men from East and Southeast Asia, and a considerable proportion of Oceanian men, especially those from Remote Oceania, belong to haplogroup O, characterized by a 5-bp deletion known as M175 (rs2032678). Recent advances in Y-SNP (single-nucleotide polymorphism) discovery have substantially improved the phylogenetic resolution of haplogroup O sublineages. By taking advantage of this recent knowledge, we hereby introduce a sensitive Y-SNP multiplex genotyping assay for the dissection of haplogroup O into its most significant sublineages. The multiplex assay thus provides an efficient way to infer patrilineal biogeographic ancestry in males of Asian/Oceanian patrilineal descent, and is suitable for applications in human population genetics, anthropological, genealogical, as well as forensic studies.

Accurate estimation of homologue-specific DNA concentration-ratios in cancer samples allows long-range haplotyping

AbstractInterpretation of allelic copy measurements at polymorphic markers in cancer samples presents distinctive challenges and opportunities. Due to frequent gross chromosomal alterations occurring in cancer (aneuploidy), many genomic regions are present at homologous-allele imbalance. Within such regions, the unequal contribution of alleles at heterozygous markers allows for direct phasing of the haplotype derived from each individual parent. In addition, genome-wide estimates of homologue specific copy- ratios (HSCRs) are important for interpretation of the cancer genome in terms of fixed integral copy-numbers. We describe HAPSEG, a probabilistic method to interpret bi- allelic marker data in cancer samples. HAPSEG operates by partitioning the genome into segments of distinct copy number and modeling the four distinct genotypes in each segment. We describe general methods for fitting these models to data which are suit- able for both SNP microarrays and massively parallel sequencing data. In addition, we demonstrate a specially tailored error-model for interpretation of systematic variations arising in microarray platforms. The ability to directly determine haplotypes from cancer samples represents an opportunity to expand reference panels of phased chromosomes, which may have general interest in various population genetic applications. In addition, this property may be exploited to interrogate the relationship between germline risk and cancer phenotype with greater sensitivity than is possible using unphased genotype. Finally, we exploit the statistical dependency of phased genotypes to enable the fitting of more elaborate sample-level error-model parameters, allowing more accurate estimation of HSCRs in cancer samples.

Characterization of 12 microsatellite loci in the waterfall damselfly (Paraphlebia zoe) for use in population genetic applications

The waterfall damselfly, Paraphelbia zoe, is distributed in cloud forest areas in the Mexican states of Veracruz, Hidalgo, and San Luis Potosi. We developed twelve microsatellite loci for P. zoe from representative samples from the state of Veracruz. Microsatellites were tested for polymorphism on a panel of 24 individuals. The number of alleles ranged from 3 to 11, observed heterozygosity from 0.083 to 0.875, and the fixation index from 0.021 to 0.563. These loci are the first to be described and characterized for P. zoe and should prove useful for population genetics in support of the conservation of this vulnerable species.

Enhancements to the ADMIXTURE algorithm for individual ancestry estimation

BackgroundThe estimation of individual ancestry from genetic data has become essential to applied population genetics and genetic epidemiology. Software programs for calculating ancestry estimates have become essential tools in the geneticist's analytic arsenal.ResultsHere we describe four enhancements to ADMIXTURE, a high-performance tool for estimating individual ancestries and population allele frequencies from SNP (single nucleotide polymorphism) data. First, ADMIXTURE can be used to estimate the number of underlying populations through cross-validation. Second, individuals of known ancestry can be exploited in supervised learning to yield more precise ancestry estimates. Third, by penalizing small admixture coefficients for each individual, one can encourage model parsimony, often yielding more interpretable results for small datasets or datasets with large numbers of ancestral populations. Finally, by exploiting multiple processors, large datasets can be analyzed even more rapidly.ConclusionsThe enhancements we have described make ADMIXTURE a more accurate, efficient, and versatile tool for ancestry estimation.

A reduced representation approach to population genetic analyses and applications to human evolution

Second-generation sequencing technologies allow surveys of sequence variation on an unprecedented scale. However, despite the rapid decrease in sequencing costs, collecting whole-genome sequence data on a population scale is still prohibitive for many laboratories. We have implemented an inexpensive, reduced representation protocol for preparing resequencing targets, and we have developed the analytical tools necessary for making population genetic inferences. This approach can be applied to any species for which a draft or complete reference genome sequence is available. The new tools we have developed include methods for aligning reads, calling genotypes, and incorporating sample-specific sequencing error rates in the estimate of evolutionary parameters. When applied to 19 individuals from a total of 18 human populations, our approach allowed sampling regions that are largely overlapping across individuals and that are representative of the entire genome. The resequencing data were used to test the serial founder model of human dispersal and to estimate the time of the Out of Africa migration. Our results also represent the first attempt to provide a time frame for the colonization of Australia based on large-scale resequencing data.

ENGINES: exploring single nucleotide variation in entire human genomes

BackgroundNext generation ultra-sequencing technologies are starting to produce extensive quantities of data from entire human genome or exome sequences, and therefore new software is needed to present and analyse this vast amount of information. The 1000 Genomes project has recently released raw data for 629 complete genomes representing several human populations through their Phase I interim analysis and, although there are certain public tools available that allow exploration of these genomes, to date there is no tool that permits comprehensive population analysis of the variation catalogued by such data.DescriptionWe have developed a genetic variant site explorer able to retrieve data for Single Nucleotide Variation (SNVs), population by population, from entire genomes without compromising future scalability and agility. ENGINES (ENtire Genome INterface for Exploring SNVs) uses data from the 1000 Genomes Phase I to demonstrate its capacity to handle large amounts of genetic variation (>7.3 billion genotypes and 28 million SNVs), as well as deriving summary statistics of interest for medical and population genetics applications. The whole dataset is pre-processed and summarized into a data mart accessible through a web interface. The query system allows the combination and comparison of each available population sample, while searching by rs-number list, chromosome region, or genes of interest. Frequency and FST filters are available to further refine queries, while results can be visually compared with other large-scale Single Nucleotide Polymorphism (SNP) repositories such as HapMap or Perlegen.ConclusionsENGINES is capable of accessing large-scale variation data repositories in a fast and comprehensive manner. It allows quick browsing of whole genome variation, while providing statistical information for each variant site such as allele frequency, heterozygosity or FST values for genetic differentiation. Access to the data mart generating scripts and to the web interface is granted from http://spsmart.cesga.es/engines.php

An accurate sequentially Markov conditional sampling distribution for the coalescent with recombination.

The sequentially Markov coalescent is a simplified genealogical process that aims to capture the essential features of the full coalescent model with recombination, while being scalable in the number of loci. In this article, the sequentially Markov framework is applied to the conditional sampling distribution (CSD), which is at the core of many statistical tools for population genetic analyses. Briefly, the CSD describes the probability that an additionally sampled DNA sequence is of a certain type, given that a collection of sequences has already been observed. A hidden Markov model (HMM) formulation of the sequentially Markov CSD is developed here, yielding an algorithm with time complexity linear in both the number of loci and the number of haplotypes. This work provides a highly accurate, practical approximation to a recently introduced CSD derived from the diffusion process associated with the coalescent with recombination. It is empirically demonstrated that the improvement in accuracy of the new CSD over previously proposed HMM-based CSDs increases substantially with the number of loci. The framework presented here can be adopted in a wide range of applications in population genetics, including imputing missing sequence data, estimating recombination rates, and inferring human colonization history.

Comparison of random and SSR‐enriched shotgun pyrosequencing for microsatellite discovery and single multiplex PCR optimization inAcacia harpophyllaF. Muell. Ex Benth

Streamlining the development and genotyping of microsatellites in species for which no genetic information is available represents an important technical challenge to overcome in order to enable mainstream application of state-of-the-art population genetic analysis techniques in nonmodel organisms. Using the example of Acacia harpophylla, an acacia tree endemic of north-eastern Australia, we show that high-throughput shotgun pyrosequencing technology, so-called second-generation sequencing, reduces time and cost of microsatellite marker discovery in nonmodel organisms and of their large-scale typing in natural populations. We found that 0.5% of short sequence reads generated on 454 Genome Sequencer FLX Titanium from random genome sampling and 2.2% of reads generated with prior microsatellite enrichment yielded microsatellite markers with designed polymerase chain reaction (PCR) primers, suggesting that enrichment increases efficiency of pyrosequencing when microsatellite discovery is the primary goal. Using stringent selection criteria to facilitate downstream PCR multiplex design, we identified 1435 microsatellite loci with designed primers from a total of 200,908 short sequence reads. From a subset of 96 loci tested for amplification, 38 were validated for population genetics applications, leading to the optimization of a cost-effective multiplex PCR protocol for the simultaneous typing of nine microsatellites in natural populations of A. harpophylla.

Development of 54 novel single‐nucleotide polymorphism (SNP) assays for sockeye and coho salmon and assessment of available SNPs to differentiate stocks within the Columbia River

Single-nucleotide polymorphisms (SNPs) have potential for broad application in population and conservation genetics, but availability of these markers is limited in many nonmodel species. In this study, genomic and expressed sequence tagged (EST) sequences from closely related salmonids (Chinook salmon and rainbow trout) were used to design primers for amplification and sequencing of sockeye (Oncorhynchus nerka) and coho (Oncorhynchus kisutch) salmon DNA for SNP discovery. One hundred and six primer sets were designed and tested for amplification in each species. An ascertainment panel of 32 diverse individuals from each species was used as template for PCR amplification and Sanger sequencing. In total, 21,647 bases of consensus sequence were screened in sockeye salmon and 20,784 bases in coho salmon with 93 and 149 SNP sites identified, respectively. Sixty-four SNP sites were chosen for assay development, and 54 of the assays were validated by comparison with genotype and sequence data (O. nerka = 23; O. kisutch = 31). These validated SNP assays along with 142 other available SNP assays [O. nerka = 103 (126 total); O. kisutch = 30 (61 total)] were used to genotype collections of O. nerka (N = 5) and O. kisutch (N = 4) from various sites in the Columbia River to evaluate the utility of these markers in this region. Results from factorial correspondence analysis indicate that these SNP markers are capable of distinguishing O. nerka populations, but O. kisutch collections were less distinct because of their common ancestry.

Y-STR profiling in two Afghanistan populations

Afghanistan’s unique geostrategic position in Eurasia has historically attracted commerce, conflict and conquest to the region. It was also an important stop along the Silk Road, connecting the far eastern civilizations with the western world. Nevertheless, limited genetic studies have been performed in Afghan populations. In this study, 17 Y-chromosomal short tandem repeat (Y-STR) loci were typed to evaluate their forensic and population genetic applications in 189 unrelated Afghan males geographically partitioned along the Hindu Kush Mountain range into north ( N = 44) and south ( N = 145) populations. North Afghanistan (0.9734, 0.9905) exhibits higher haplotype diversity than south Afghanistan (0.9408, 0.9813) at both the minimal 9-loci and 17-loci Yfiler haplotypes, respectively. The overall haplotype diversity for both Afghan populations at 17 Y-STR loci is 0.9850 and the corresponding value for the minimal 9-loci haplotypes is 0.9487. A query using of the most frequent Afghan Yfiler haplotype (7.98%) against the worldwide Y-STR haplotype reference database (YHRD) returned no profile match, indicating a high power of discrimination with 17 Y-STR loci. A median-joining network based on 15 Y-STR loci displays limited haplotype sharing between the two Afghan populations, possibly due to the Hindu Kush Mountain range serving as a natural barrier to gene flow between the two regions.

Characterization of Microsatellite Loci and Reliable Genotyping in a Polyploid Plant, Mercurialis perennis (Euphorbiaceae)

For many applications in population genetics, codominant simple sequence repeats (SSRs) may have substantial advantages over dominant anonymous markers such as amplified fragment length polymorphisms (AFLPs). In high polyploids, however, allele dosage of SSRs cannot easily be determined and alleles are not easily attributable to potentially diploidized loci. Here, we argue that SSRs may nonetheless be better than AFLPs for polyploid taxa if they are analyzed as effectively dominant markers because they are more reliable and more precise. We describe the transfer of SSRs developed for diploid Mercurialis huetii to the clonal dioecious M. perennis. Primers were tested on a set of 54 male and female plants from natural decaploid populations. Eight of 65 tested loci produced polymorphic fragments. Binary profiles from 4 different scoring routines were used to define multilocus lineages (MLLs). Allowing for fragment differences within 1 MLL, all analyses revealed the same 14 MLLs without conflicting with merigenet, sex, or plot assignment. For semiautomatic scoring, a combination of as few as 2 of the 4 most polymorphic loci resulted in unambiguous discrimination of clones. Our study demonstrates that microsatellite fingerprinting of polyploid plants is a cost efficient and reliable alternative to AFLPs, not least because fewer loci are required than for diploids.

Ecological genetics of freshwater fish: a short review of the genotype–phenotype connection

Molecular ecology or ecological genetics is an expanding application of population genetics which has flourished in the last two decades but it is dominated by systematic and phylogeographic studies, with relatively little emphasis on the study of the genetic basis of the process of adaptation to different ecological conditions. The relationship between genotype and adaptive phenotypes is weak because populations are often difficult to quantify and experiments are logistically challenging or unfeasible. Interestingly, in freshwater fish, studies to characterize the genetic architecture of adaptive traits are not as rare as in other vertebrate groups. In this review, we summarize the few cases where the relationship between the ecology and genetics of freshwater fish is more developed, namely the relationship between genetic markers and ecological phenotypes.

De Novo Discovery and Multiplexed Amplification of Microsatellite Markers for Black Alder (Alnus glutinosa) and Related Species Using SSR-Enriched Shotgun Pyrosequencing

Recent developments in sequencing technologies and bioinformatics analyses provide an unprecedented opportunity for cost and time effective high quality microsatellite marker discovery in nonmodel organisms for which no genomic information is available. Here, we use shotgun pyrosequencing of a microsatellite-enriched library to develop, for the first time, microsatellite markers for Alnus glutinosa, a keystone tree species of European riparian woodland communities. From a total of 17 855 short sequences, we identified 590 perfect microsatellites from which 392 had designed primers. A subset of 48 loci were tested for amplification, 12 of which were polymorphic in A. glutinosa. These 12 loci were successfully coamplified in a single multiplex polymerase chain reaction experiment and validated for population genetics applications. In addition, 10 and 8 of these microsatellites were found to be transferable to the related A. incana and A. cordata species. The developed multiplex of 12 microsatellite markers therefore provides new opportunities for experimental evolutionary and forest genetics research in Alnus.

Survey and analysis of simple sequence repeats in the Laccaria bicolor genome, with development of microsatellite markers

It is becoming clear that simple sequence repeats (SSRs) play a significant role in fungal genome organization, and they are a large source of genetic markers for population genetics and meiotic maps. We identified SSRs in the Laccaria bicolor genome by in silico survey and analyzed their distribution in the different genomic regions. We also compared the abundance and distribution of SSRs in L. bicolor with those of the following fungal genomes: Phanerochaete chrysosporium, Coprinopsis cinerea, Ustilago maydis, Cryptococcus neoformans, Aspergillus nidulans, Magnaporthe grisea, Neurospora crassa and Saccharomyces cerevisiae. Using the MISA computer program, we detected 277,062 SSRs in the L. bicolor genome representing 8% of the assembled genomic sequence. Among the analyzed basidiomycetes, L. bicolor exhibited the highest SSR density although no correlation between relative abundance and the genome sizes was observed. In most genomes the short motifs (mono- to trinucleotides) were more abundant than the longer repeated SSRs. Generally, in each organism, the occurrence, relative abundance, and relative density of SSRs decreased as the repeat unit increased. Furthermore, each organism had its own common and longest SSRs. In the L. bicolor genome, most of the SSRs were located in intergenic regions (73.3%) and the highest SSR density was observed in transposable elements (TEs; 6,706 SSRs/Mb). However, 81% of the protein-coding genes contained SSRs in their exons, suggesting that SSR polymorphism may alter gene phenotypes. Within a L. bicolor offspring, sequence polymorphism of 78 SSRs was mainly detected in non-TE intergenic regions. Unlike previously developed microsatellite markers, these new ones are spread throughout the genome; these markers could have immediate applications in population genetics.