Single-locus Approaches Research Articles

Rapid detection, quantification and speciation of Leishmania using real-time PCR and DNA sequencing at the rRNA Internal Transcribed Spacer 2.

The ability to discriminate infection between closely related Leishmania species within the Viannia species complex, specifically L. braziliensis, L. guyanensis and L. panamensis is critical to inform the clinical diagnosis and determine the most efficacious treatment modality. We designed a nested primer set targeting the rRNA Internal Transcribed Spacer 2 (ITS2), located on Chromosome 27, to distinguish among all human infective Leishmania species. Separate nested and single primer pairs were developed for conventional and quantitative PCR approaches respectively. Species-specific single nucleotide polymorphisms and indels located within the PCR products were identified by Sanger sequencing. This single locus approach provides a sensitive and specific platform to identify the species of Leishmania causing infection.

A new long-read mitochondrial-genome protocol (PacBio HiFi) for haemosporidian parasites: a tool for population and biodiversity studies

BackgroundStudies on haemosporidian diversity, including origin of human malaria parasites, malaria's zoonotic dynamic, and regional biodiversity patterns, have used target gene approaches. However, current methods have a trade-off between scalability and data quality. Here, a long-read Next-Generation Sequencing protocol using PacBio HiFi is presented. The data processing is supported by a pipeline that uses machine-learning for analysing the reads.MethodsA set of primers was designed to target approximately 6 kb, almost the entire length of the haemosporidian mitochondrial genome. Amplicons from different samples were multiplexed in an SMRTbell® library preparation. A pipeline (HmtG-PacBio Pipeline) to process the reads is also provided; it integrates multiple sequence alignments, a machine-learning algorithm that uses modified variational autoencoders, and a clustering method to identify the mitochondrial haplotypes/species in a sample. Although 192 specimens could be studied simultaneously, a pilot experiment with 15 specimens is presented, including in silico experiments where multiple data combinations were tested.ResultsThe primers amplified various haemosporidian parasite genomes and yielded high-quality mt genome sequences. This new protocol allowed the detection and characterization of mixed infections and co-infections in the samples. The machine-learning approach converged into reproducible haplotypes with a low error rate, averaging 0.2% per read (minimum of 0.03% and maximum of 0.46%). The minimum recommended coverage per haplotype is 30X based on the detected error rates. The pipeline facilitates inspecting the data, including a local blast against a file of provided mitochondrial sequences that the researcher can customize.ConclusionsThis is not a diagnostic approach but a high-throughput method to study haemosporidian sequence assemblages and perform genotyping by targeting the mitochondrial genome. Accordingly, the methodology allowed for examining specimens with multiple infections and co-infections of different haemosporidian parasites. The pipeline enables data quality assessment and comparison of the haplotypes obtained to those from previous studies. Although a single locus approach, whole mitochondrial data provide high-quality information to characterize species pools of haemosporidian parasites.

DNA taxonomy reveals high species diversity among the stygobiont genus Metastenasellus (Crustacea, Isopoda) in African groundwater

This study aimed to explore the species diversity within the isopod genus Metastenasellus in Benin and Cameroon. Compared to other parts of the world, the described diversity of stygobiotic crustaceans in Africa is low due to a dearth of studies and taxonomic expertise. However, recent research activities in Benin and Cameroon suggest higher groundwater diversity than previously envisioned. Recent sampling campaigns in these countries have shown that Metastenasellus is a major group in the underground aquatic environment. The accumulation of biological material provided an opportunity to explore species diversity within the genus using a DNA taxonomy approach based on the cytochrome c oxidase subunit I (COI) gene fragment. Despite the limitations of using a single-locus approach for species delimitation, an overview of the diversity within the genus Metastenasellus was obtained, revealing the presence of 23 distinct lineages. Several elements suggest that most, if not all, of these lineages represent valid species. These include high genetic distances between lineages, morphologically distinct species separated by genetic distances of the same order of magnitude as between other described lineages, and the coexistence of different lineages at the same stations. Despite a limited sampling effort, these first results indicate a high level of species diversity and endemism within Metastenasellus in the studied regions. The narrow geographic distribution of the lineages suggests strong isolation and limited dispersal abilities. This study highlights the potential for discovering a significant number of new species within this genus and emphasizes the need for further research to uncover the extent of diversity in African stygobiotic isopods.

Sequencing of hsp70 for discernment of species from the Leishmania (Viannia) guyanensis complex from endemic areas in Colombia

BackgroundColombia is ranked very high among countries with the highest numbers of endemic Leishmania species (n = 9) causing human disease. Although much effort has been devoted to generating simple and specific tools for Leishmania species identification, challenges remain in the discrimination of species belonging to the Leishmania (Viannia) guyanensis complex: L. (V.) guyanensis and L. (V.) panamensis.MethodsA set of seven reference strains of species belonging to the L. (Leishmania) and L. (Viannia) subgenera, clinical strains from human cases of cutaneous leishmaniasis (CL; n = 26) and samples collected from sylvatic mammals and sand flies (n = 7) from endemic areas in Colombia were analyzed in this study. The heat-shock protein 70 gene (hsp70) was amplified by PCR from DNA extracted from logarithmic-phase promastigotes or tissue samples, and the PCR products were sequenced. Sequence alignment was performed against a set of previously published and curated sequences, and phylogenetic analysis based on the maximum-likelihood and Bayesian inference approaches was conducted. Haplotype diversity among strains and species of the L. (V.) guyanensis complex was explored using a median-joining network.ResultsSequencing of the hsp70 gene for L. (Viannia) spp. typing was comparable to species identification using isoenzyme electrophoresis or monoclonal antibodies. Complete species matching was found, except for one sylvatic sample with an identity yet unsolved. Among the L. (V.) panamensis clinical strains, two distinctive phylogenetic clusters were found to correlate with two different zymodemes: L. (V.) panamensis Z2.2 and Z2.3. Analysis of samples from sylvatic environments identified novel records of naturally infected wild mammal and sand fly species.ConclusionsOur results support the adequacy of hsp70 gene sequencing as a single-locus approach for discrimination of L. (Viannia) spp., as well as for exploring the genetic diversity within the L. (V.) guyanensis complex.Graphical

Multi-locus evaluation of gastrointestinal bacterial communities from Zalophus californianus pups in the Gulf of California, México.

BackgroundThe gastrointestinal (GI) bacterial communities of sea lions described to date have occasionally revealed large intraspecific variability, which may originate from several factors including different methodological approaches. Indeed, GI bacterial community surveys commonly rely on the use of a single hypervariable region (HR) of 16S rRNA, which may result in misleading structural interpretations and limit comparisons among studies. Here, we considered a multi-locus analysis by targeting six HRs of 16S rRNA with the aims of (i) comprehensively assessing the GI bacterial consortium in rectal samples from Zalophus californianus pups and (ii) elucidating structural variations among the tested HRs. In addition, we evaluated which HRs may be most suitable for identifying intrinsic, structurally related microbiome characteristics, such as geographic variations or functional capabilities.MethodsWe employed a Short MUltiple Regions Framework (SMURF) approach using the Ion 16S™ Metagenomic Kit. This kit provides different proprietary primers designed to target six HRs of the 16S rRNA gene. To date, the only analytical pipeline available for this kit is the Ion Reporter™ Software of Thermo Fisher Scientific. Therefore, we propose an in-house pipeline to use with open-access tools, such as QIIME2 and PICRUSt 2, in downstream bioinformatic analyses.ResultsAs hypothesized, distinctive bacterial community profiles were observed for each analyzed HR. A higher number of bacterial taxa were detected with the V3 and V6–V7 regions. Conversely, the V8 and V9 regions were less informative, as we detected a lower number of taxa. The synergistic information of these HRs suggests that the GI microbiota of Zalophus californianus pups is predominated by five bacterial phyla: Proteobacteria (~50%), Bacteroidetes (~20%), Firmicutes (~18%), Fusobacteria (~7%), and Epsilonbacteraeota (~4%). Notably, our results differ at times from previously reported abundance profiles, which may promote re-evaluations of the GI bacterial compositions in sea lions and other pinniped species that have been reported to date. Moreover, consistent geographic differences were observed only with the V3, V4, and V6–V7 regions. In addition, these HRs also presented higher numbers of predicted molecular pathways, although no significant functional changes were apparent. Together, our results suggests that multi-locus analysis should be encouraged in GI microbial surveys, as single-locus approaches may result in misleading structural results that hamper the identification of structurally related microbiome features.

Isolation by distance and past climate resistance shaped the distribution of genealogical lineages of a neotropical lizard

Organisms adapted to open environments in South America have recently been used to understand the origins of the high Neotropical biodiversity. In the Caatinga, the largest continuous block of Seasonally Dry Tropical Forest in South America, phylogeographic studies have uncovered the role of historical climate changes and rivers (i.e., the São Francisco River, the largest perennial river in Caatinga), in promoting genetic differentiation and speciation of lizards and amphibians. We used mitochondrial data, demographic analyses, paleodistribution models, and landscape genetic methods to test the effects of spatial distances, historical climate fluctuations, and landscape heterogeneity on the genetic variation of the generalist lizard Tropidurus hispidus in the semi-arid Caatinga in northeastern Brazil. Four haplogroups with moderate geographical structure diverged in the Pleistocene, and exhibited high genetic diversity. Ecological niche models revealed large suitable climatic areas for T. hispidus in the past 790 thousand years, connecting the Caatinga and other regions via a narrow corridor. Part of the genetic differentiation in T. hispidus resulted from spatial distances among populations and isolation by resistance through climatic unsuitability areas in the Last Glacial Maximum (LGM), which probably reduced population connectivity and gene flow. Our findings highlight the role of the historical factors of the Caatinga, through LGM climate, and the generalist condition of species in shaping the genealogical histories of populations. Although the results are based on a single-locus approach, our study is a first step to shed light on the main drivers of the evolutionary history of T. hispidus, in a highly diverse and still poorly studied region.

Variants in clopidogrel-relevant genes and early neurological deterioration in ischemic stroke patients receiving clopidogrel

BackgroundEarly neurological deterioration (END) is common in acute ischemic stroke (IS). However, the underlying mechanisms for END are unclear. The aim of this study was to evaluate the associations of 16 variants in clopidogrel-relevant genes and interactions among these variants with END in acute IS patients receiving clopidogrel treatment.MethodsWe consecutively enrolled 375 acute IS patients between June 2014 and January 2015. Platelet aggregation was measured on admission and after the 7–10 days of clopidogrel treatment. The 16 variants in clopidogrel-relevant genes were examined using mass spectrometry. The primary outcome was END within the 10 days of admission. Gene-gene interactions were analyzed by generalized multifactor dimensionality reduction (GMDR) methods.ResultsAmong the 375 patients, 95 (25.3%) patients developed END within the first 10 days of admission. Among the 16 variants, only CYP2C19*2 (rs4244285) AA/AG was associated with END using single-locus analytical approach. GMDR analysis revealed that there was a synergistic effect of gene-gene interactions among CYP2C19*2 rs4244285, P2Y12 rs16863323, and GPIIIa rs2317676 on the risk for END. The high-risk interactions among the three variants were associated with the higher platelet aggregation and independent predictor for END after adjusting for the covariates (hazard ratio: 2.82; 95% confidence interval: 1.36–7.76; P = 0.003).ConclusionsEND is very common in patients with acute IS. The mechanisms leading to END are most likely multifactorial. Interactions among CYP2C19*2 rs4244285, P2Y12 rs16863323, and GPIIIa rs2317676 may confer a higher risk for END. It was very important to modify clopidogrel therapy for the patients carrying the high-risk interactive genotypes.Clinical trial registration informationThe study described here is registered at http://www.chictr.org/ (unique Identifier: ChiCTR-OCH-14004724). The date of trial registration was May 30, 2014.

Species delimitation reveals an underestimated diversity of Andean catfishes of the family Astroblepidae (Teleostei: Siluriformes)

ABSTRACT Catfishes of the family Astroblepidae form a group composed by 82 valid species of the genus Astroblepus inhabiting high-gradient streams and rivers throughout tropical portions of the Andean Cordillera. Little has been advanced in the systematics and biodiversity of astroblepids other than an unpublished thesis, a single regional multilocus study and isolated species descriptions. Here, we examined 208 specimens of Astroblepus that apparently belong to 16 valid species from several piedmont rivers from northern Colombia to southern Peru. Using three single-locus approaches for species delimitation in combination with a species tree analysis estimated from three mitochondrial genes, we identified a total of 25 well-delimited lineages including eight valid and 17 potential undescribed species distributed in two monophyletic groups: the Central Andes Clade, which contains 14 lineages from piedmont rivers of the Peruvian Amazon, and the Northern Andes Clade with 11 lineages from trans- and cis-Andean rivers of Colombia and Ecuador, including the Orinoco, Amazon, and Magdalena-Cauca basins and Pacific coastal drainages. Results of species delimitation methods highlight several taxonomical incongruences in recently described species denoting potential synonymies.

Comparative study for haplotype block partitioning methods - Evidence from chromosome 6 of the North American Rheumatoid Arthritis Consortium (NARAC) dataset.

Haplotype-based methods compete with “one-SNP-at-a-time” approaches on being preferred for association studies. Chromosome 6 contains most of the known genetic biomarkers for rheumatoid arthritis (RA) disease. Therefore, chromosome 6 serves as a benchmark for the haplotype methods testing. The aim of this study is to test the North American Rheumatoid Arthritis Consortium (NARAC) dataset to find out if haplotype block methods or single-locus approaches alone can sufficiently provide the significant single nucleotide polymorphisms (SNPs) associated with RA. In addition, could we be satisfied with only one method of the haplotype block methods for partitioning chromosome 6 of the NARAC dataset? In the NARAC dataset, chromosome 6 comprises 35,574 SNPs for 2,062 individuals (868 cases, 1,194 controls). Individual SNP approach and three haplotype block methods were applied to the NARAC dataset to identify the RA biomarkers. We employed three haplotype partitioning methods which are confidence interval test (CIT), four gamete test (FGT), and solid spine of linkage disequilibrium (SSLD). P-values after stringent Bonferroni correction for multiple testing were measured to assess the strength of association between the genetic variants and RA susceptibility. Moreover, the block size (in base pairs (bp) and number of SNPs included), number of blocks, percentage of uncovered SNPs by the block method, percentage of significant blocks from the total number of blocks, number of significant haplotypes and SNPs were used to compare among the three haplotype block methods. Individual SNP, CIT, FGT, and SSLD methods detected 432, 1,086, 1,099, and 1,322 associated SNPs, respectively. Each method identified significant SNPs that were not detected by any other method (Individual SNP: 12, FGT: 37, CIT: 55, and SSLD: 189 SNPs). 916 SNPs were discovered by all the three haplotype block methods. 367 SNPs were discovered by the haplotype block methods and the individual SNP approach. The P-values of these 367 SNPs were lower than those of the SNPs uniquely detected by only one method. The 367 SNPs detected by all the methods represent promising candidates for RA susceptibility. They should be further investigated for the European population. A hybrid technique including the four methods should be applied to detect the significant SNPs associated with RA for chromosome 6 of the NARAC dataset. Moreover, SSLD method may be preferred for its favored benefits in case of selecting only one method.

The genomics of local adaptation in trees: are we out of the woods yet?

There is substantial interest in uncovering the genetic basis of the traits underlying adaptive responses in tree species, as this information will ultimately aid conservation and industrial endeavors across populations, generations, and environments. Fundamentally, the characterization of such genetic bases is within the context of a genetic architecture, which describes the mutlidimensional relationship between genotype and phenotype through the identification of causative variants, their relative location within a genome, expression, pleiotropic effect, environmental influence, and degree of dominance, epistasis, and additivity. Here, we review theory related to polygenic local adaptation and contextualize these expectations with methods often used to uncover the genetic basis of traits important to tree conservation and industry. A broad literature survey suggests that most tree traits generally exhibit considerable heritability, that underlying quantitative genetic variation (QST) is structured more so across populations than neutral expectations (FST) in 69% of comparisons across the literature, and that single-locus associations often exhibit small estimated per-locus effects. Together, these results suggest differential selection across populations often acts on tree phenotypes underlain by polygenic architectures consisting of numerous small to moderate effect loci. Using this synthesis, we highlight the limits of using solely single-locus approaches to describe underlying genetic architectures and close by addressing hurdles and promising alternatives towards such goals, remark upon the current state of tree genomics, and identify future directions for this field. Importantly, we argue, the success of future endeavors should not be predicated on the shortcomings of past studies and will instead be dependent upon the application of theory to empiricism, standardized reporting, centralized open-access databases, and continual input and review of the community’s research.

Conservation phylogenetics and computational species delimitation of Neotropical primates

Accurate definition of species boundaries plays a crucial role in the management and conservation of biological diversity. Although the science of genetics has been largely used to unveil cryptic biodiversity, phylogenetic theory has not been fully explored to address this issue. Recently, single-locus approaches to delimit evolutionary significant units (ESUs) have been widely used in several groups of organisms, presenting a valuable tool to test the uniqueness of biological clades. In this context, this study aimed to test the performance of coalescent-based delimitation methods using Neotropical primates, which is a lineage that includes several endangered species. This was achieved by evaluating the congruence between inferred ESUs and the nominal species recognized by taxonomists based on single-locus data. The results suggested that the molecular marker that best replicates standard taxonomy is the COI gene. GMYC presented the best overall performance at preventing lumping profiles, and the methodological combination that led to the lowest lumping frequency was the ST-GMYC using the timescale inferred on RelTime. The highest matching frequencies were produced by the ST-GMYC based on a BEAST timescale inferred with a Yule prior for the branching process. Overall, CSD approaches produced higher frequencies of mactches and splits than lumps. The implementation automated the delimitation of evolutionary units in a circularity-free system, which is valuable for decision-making policies, enabling the refinement of an entirely taxonomy-based procedure. The results also highlighted the importance of phylogeny-based analyses for the discipline of conservation. Importantly, our conclusions were based on a Neotropical primates dataset, with several endangered species that inhabit degraded areas, which has made this clade a focus of conservation policies in recent decades.

The Potential of DNA Barcode-Based Delineation Using Seven Putative Candidate Loci of the Plastid Region in Inferring Molecular Diversity of Cowpea at Sub-Species Level

The novelty and suitability of the mitochondrial gene CO1 in DNA barcoding as a reliable identification tool in animal species are undisputed. This is attributed to its standardized sequencing segment of the mitochondrial cytochrome c oxidase-1 gene (CO1) which has the necessary universality and variability making it a generally acceptable barcode region. CO1 is a haploid single locus that is uniparentally-inherited. Protein-coding regions are present in high-copy numbers making it an ideal barcode. The mitochondrial oxidase subunit I (COI) gene is a robust barcode with a suitable threshold for delineating animals and is not subject to drastic length variation, frequent mononucleotide repeats or microinversions. However, a low nucleotide substitution rate of plant mitochondrial genome [mtDNA] precludes the use of CO1 as a universal plant DNA barcode and makes the search for alternative barcode regions necessary. Currently, there exists no universal barcode for plants. The plastid region reveals leading candidate loci as appropriate DNA barcodes yet to be explored in biodiversity studies in Kenya. Four of these plastid regions are portions of coding genes (matK, rbcL, rpoB, and rpoC1), and three noncoding spacers (atpF-atpH, trnH-psbA, and psbK-psbL) which emerge as ideal candidate DNA loci. While different research groups propose various combinations of these loci, there exists no consensus; the lack thereof impedes progress in getting a suitable universal DNA barcode. Little research has attempted to investigate and document the applicability and extend of effectiveness of different DNA regions as barcodes to delineate cowpea at subspecies level. In this study we sought to test feasibility of the seven putative candidate DNA loci singly and in combination in order to establish a suitable single and multi-locus barcode regions that can have universal application in delineating diverse phylogeographic groups of closely related Kenyan cowpea variants. In this study, our focus was based on genetic parameters including analyses of intra- and infra-specific genetic divergence based on intra- and infra-specific K2P distances; calculation of Wilcoxon signed rank tests of intra-specific divergence among loci and coalescence analyses to delineate independent genetic clusters. Knowledge of DNA candidate loci that are informative will reveal the suitability of DNA barcoding as a tool in biodiversity studies. Results of this study indicate that: matK, trnH-psbA, psbK-psbL, and rbcL are good barcodes for delineating intra and infraspecific distances at single loci level. However, among the combinations, matK + trnH-psbA, rpoB + atpF-atpH + matK are the best barcodes in delineating cowpea subvariants. rbcL gene can be a suitable barcode marker at single locus level, but overall, multi locus approach appears more informative than single locus approach. The present study hopes to immensely contribute to the scanty body of knowledge on the novelty of DNA barcoding in cataloguing closely related cowpea variants at molecular level and hopes to open up future research on genomics and the possibility of use of conserved regions within DNA in inferring phylogenetic relationships among Kenyan cowpea variants.

Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method.

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

RAD-QTL Mapping Reveals Both Genome-Level Parallelism and Different Genetic Architecture Underlying the Evolution of Body Shape in Lake Whitefish (Coregonus clupeaformis) Species Pairs.

Parallel changes in body shape may evolve in response to similar environmental conditions, but whether such parallel phenotypic changes share a common genetic basis is still debated. The goal of this study was to assess whether parallel phenotypic changes could be explained by genetic parallelism, multiple genetic routes, or both. We first provide evidence for parallelism in fish shape by using geometric morphometrics among 300 fish representing five species pairs of Lake Whitefish. Using a genetic map comprising 3438 restriction site−associated DNA sequencing single-nucleotide polymorphisms, we then identified quantitative trait loci underlying body shape traits in a backcross family reared in the laboratory. A total of 138 body shape quantitative trait loci were identified in this cross, thus revealing a highly polygenic architecture of body shape in Lake Whitefish. Third, we tested for evidence of genetic parallelism among independent wild populations using both a single-locus method (outlier analysis) and a polygenic approach (analysis of covariation among markers). The single-locus approach provided limited evidence for genetic parallelism. However, the polygenic analysis revealed genetic parallelism for three of the five lakes, which differed from the two other lakes. These results provide evidence for both genetic parallelism and multiple genetic routes underlying parallel phenotypic evolution in fish shape among populations occupying similar ecological niches.

Delimiting Species-Poor Data Sets using Single Molecular Markers: A Study of Barcode Gaps, Haplowebs and GMYC.

Most single-locus molecular approaches to species delimitation available to date have been designed and tested on data sets comprising at least tens of species, whereas the opposite case (species-poor data sets for which the hypothesis that all individuals are conspecific cannot by rejected beforehand) has rarely been the focus of such attempts. Here we compare the performance of barcode gap detection, haplowebs and generalized mixed Yule-coalescent (GMYC) models to delineate chimpanzees and bonobos using nuclear sequence markers, then apply these single-locus species delimitation methods to data sets of one, three, or six species simulated under a wide range of population sizes, speciation rates, mutation rates and sampling efforts. Our results show that barcode gap detection and GMYC models are unable to delineate species properly in data sets composed of one or two species, two situations in which haplowebs outperform them. For data sets composed of three or six species, bGMYC and haplowebs outperform the single-threshold and multiple-threshold versions of GMYC, whereas a clear barcode gap is only observed when population sizes and speciation rates are both small. The latter conditions represent a "sweet spot" for molecular taxonomy where all the single-locus approaches tested work well; however, the performance of these methods decreases strongly when population sizes and speciation rates are high, suggesting that multilocus approaches may be necessary to tackle such cases.

Genome scans for the contemporary response to selection in quantitative traits.

Genome scans have been an important approach for discovering historical signatures of selection in both model and nonmodel species. An exciting new experimental design for genome scans is to measure the change in allele frequency before and after contemporary selection within a generation, from a single population. The most widely-used methods, however, have two major limitations: they are based on testing one locus at a time, and they only have power to uncover loci that have evolved under relatively strong selection. On the other hand, complex quantitative traits are common in nature and are caused by several loci of small effect. Selection on a quantitative trait at the phenotypic level is predicted to be accompanied by subtle allele frequency changes in many loci that covary (a polygenic soft sweep), rather than a large, single-effect allele (a selective sweep). In this issue of Molecular Ecology, Bourret et al. (2014) measure the contemporary response to natural selection across the genome in multiple cohorts of Atlantic salmon during their first year at sea. They introduce a multilocus framework based on groups of markers that covary in their genotypic distribution. While the traditional, single-locus approach did not find evidence for repeated patterns of selection, the multivariate approach found that a group of covarying SNPs was selected for in different cohorts at one site. Their multilocus framework has potential to be a more fruitful approach for uncovering the genomic basis of adaptation in quantitative traits, although caution should be applied as the framework has yet to be validated with simulated data.

Optimized multilocus sequence typing (MLST) scheme for Trypanosoma cruzi.

Trypanosoma cruzi, the aetiological agent of Chagas disease possess extensive genetic diversity. This has led to the development of a plethora of molecular typing methods for the identification of both the known major genetic lineages and for more fine scale characterization of different multilocus genotypes within these major lineages. Whole genome sequencing applied to large sample sizes is not currently viable and multilocus enzyme electrophoresis, the previous gold standard for T. cruzi typing, is laborious and time consuming. In the present work, we present an optimized Multilocus Sequence Typing (MLST) scheme, based on the combined analysis of two recently proposed MLST approaches. Here, thirteen concatenated gene fragments were applied to a panel of T. cruzi reference strains encompassing all known genetic lineages. Concatenation of 13 fragments allowed assignment of all strains to the predicted Discrete Typing Units (DTUs), or near-clades, with the exception of one strain that was an outlier for TcV, due to apparent loss of heterozygosity in one fragment. Monophyly for all DTUs, along with robust bootstrap support, was restored when this fragment was subsequently excluded from the analysis. All possible combinations of loci were assessed against predefined criteria with the objective of selecting the most appropriate combination of between two and twelve fragments, for an optimized MLST scheme. The optimum combination consisted of 7 loci and discriminated between all reference strains in the panel, with the majority supported by robust bootstrap values. Additionally, a reduced panel of just 4 gene fragments displayed high bootstrap values for DTU assignment and discriminated 21 out of 25 genotypes. We propose that the seven-fragment MLST scheme could be used as a gold standard for T. cruzi typing, against which other typing approaches, particularly single locus approaches or systematic PCR assays based on amplicon size, could be compared.

Exploring the effects of immunity and life history on the dynamics of an endogenous retrovirus

Mammalian DNA is littered with the signatures of past retroviral infections. For example, at least 8% of the human genome can be attributed to endogenous retroviruses (ERVs). We take a single-locus approach to develop a simple susceptible-infected-recovered model to investigate the circumstances under which a disease-causing retrovirus can become incorporated into the host genome and spread through the host population if it were to confer an immunological advantage. In the absence of any fitness benefit provided by the long terminal repeat (LTR), we conclude that signatures of ERVs are likely to go to fixation within a population when the probability of evolving cellular/humoral immunity to a related exogenous version of the virus is extremely small. We extend this model to examine whether changing the speed of the host life history influences the likelihood that an exogenous retrovirus will incorporate and spread to fixation. Our results reveal the parameter space under which incorporation of exogenous retroviruses into a host genome may be beneficial to the host. In our final model, we find that the likelihood of an LTR reaching fixation in a host population is not strongly affected by host life history.

Kernel canonical correlation analysis for assessing gene–gene interactions and application to ovarian cancer

Although single-locus approaches have been widely applied to identify disease-associated single-nucleotide polymorphisms (SNPs), complex diseases are thought to be the product of multiple interactions between loci. This has led to the recent development of statistical methods for detecting statistical interactions between two loci. Canonical correlation analysis (CCA) has previously been proposed to detect gene–gene coassociation. However, this approach is limited to detecting linear relations and can only be applied when the number of observations exceeds the number of SNPs in a gene. This limitation is particularly important for next-generation sequencing, which could yield a large number of novel variants on a limited number of subjects. To overcome these limitations, we propose an approach to detect gene–gene interactions on the basis of a kernelized version of CCA (KCCA). Our simulation studies showed that KCCA controls the Type-I error, and is more powerful than leading gene-based approaches under a disease model with negligible marginal effects. To demonstrate the utility of our approach, we also applied KCCA to assess interactions between 200 genes in the NF-κB pathway in relation to ovarian cancer risk in 3869 cases and 3276 controls. We identified 13 significant gene pairs relevant to ovarian cancer risk (local false discovery rate <0.05). Finally, we discuss the advantages of KCCA in gene–gene interaction analysis and its future role in genetic association studies.

DNA barcoding and species delimitation: the Stylodrilus heringianus case (Annelida : Clitellata : Lumbriculidae)

Individuals of the aquatic oligochaete species Stylodrilus heringianus Claparède, 1862 were collected across a part of this species’ distribution range in Sweden, Estonia, Great Britain and Spain to test whether they represent a single metapopulation or several separately evolving lineages. Using sequences of the barcoding gene cytochrome c oxidase subunit I (COI) and two nuclear genes (internal transcribed spacer region and histone 3), three different approaches were conducted: pairwise distance-method, Bayesian inference and network analysis. Both the COI phylogeny and network analyses were concordant in recovering six haplotype clusters, which showed a maximum genetic distance of 7.7% (K2P) among each other. Nevertheless, nuclear genes failed to confirm any lineage separation, and we conclude that the sampled specimens all belong to the same species. A phylogeographic history with allopatric divergence and secondary contact is suggested to explain this intraspecific pattern of mitochondrial divergence and nuclear non-divergence. The study shows that a mitochondrial single-locus approach can be problematic for the accurate delimitation of species, and we emphasise the need for nuclear genes as supplementary markers, when taxonomic resolution is assessed with COI barcodes.