Considerations for measuring genetic variation and population structure with multilocus fingerprinting

Multilocus DNA fingerprinting provides a cost-effective means to rapidly assay genetic variation at many loci. While this makes the technique particularly attractive for studies of evolution and conservation biology, fingerprint data can be difficult to interpret. Measurement errors inherent with the technique force investigators to group similar-sized alleles (bands) into discrete bins before estimating genetic parameters. If too little error is accounted for in this process homologous alleles will not be grouped in a common bin, whereas overestimated error can produce bins with homoplasic alleles. We used simulations and empirical data for two frog species ( Rana luteiventris and Hyla regilla ) to demonstrate that mean band-sharing ( S¯_xy ) and heterozygosity ( H ¯_E) are a function of both bin width and band profile complexity (i.e. number and distribution of bands). These estimators are also sensitive to the number of lanes included in the analysis when bin width is wide and a floating bin algorithm is employed. Multilocus estimates of H ¯_E were highly correlated with S¯_xy and thus provide no additional information about genetic variation. Estimates of population subdivision ( F ^ and Φ^_ST) appeared robust to changes in bin size. We also examined the issue of statistical independence for band-sharing data when comparisons are made among all samples. This analysis indicated that the covariance between band-sharing statistics was very small and not statistically different from zero. We recommend that sensitivity analyses for bin size be used to improve confidence in the biological interpretation of multilocus fingerprints, and that the covariance structure for band-sharing statistics be examined.     

Contrasting patterns of molecular diversity and Wolbachia infection in bisexual and parthenogenetic Strophosoma weevils (Coleoptera: Curculionidae)

It has been postulated that parthenogenesis in weevil species is of hybrid origin, but some have speculated that Wolbachia infection plays a role through the modification of host breeding systems. Here we focus on Strophosoma weevils, which are known to be pests in young forest stands. Using molecular data, we investigated the diversity of the two most common Strophosoma species in Europe: S. capitatum, which reproduces bisexually, and S. melanogrammum, which is parthenogenetic. Also researched were their associations with the endosymbiotic bacterium Wolbachia. These species of weevil were found to be clearly distinguishable based on their mitochondrial DNA, with the bisexual taxa being more diverse. However, the nuclear DNA divergence of the two species was very low, and the parthenogenetic taxon was found to be heterozygous. Wolbachia infection was detected in all individuals of the S. melanogrammum populations and less than half of the S. capitatum populations. Moreover, multiple Wolbachia strains were found in both taxa (two in the former and three in the latter). The results of this research suggest that parthenogenesis in this genus is of hybrid origin and that Wolbachia could have played a role in speciation of these weevils.     

Linkage disequilibrium clustering‐based approach for association mapping with tightly linked genomewide data

Genomewide association studies (GWAS) aim to identify genetic markers strongly associated with quantitative traits by utilizing linkage disequilibrium (LD) between candidate genes and markers. However, because of LD between nearby genetic markers, the standard GWAS approaches typically detect a number of correlated SNPs covering long genomic regions, making corrections for multiple testing overly conservative. Additionally, the high dimensionality of modern GWAS data poses considerable challenges for GWAS procedures such as permutation tests, which are computationally intensive. We propose a cluster‐based GWAS approach that first divides the genome into many large nonoverlapping windows and uses linkage disequilibrium network analysis in combination with principal component (PC) analysis as dimensional reduction tools to summarize the SNP data to independent PCs within clusters of loci connected by high LD. We then introduce single‐ and multilocus models that can efficiently conduct the association tests on such high‐dimensional data. The methods can be adapted to different model structures and used to analyse samples collected from the wild or from biparental F₂ populations, which are commonly used in ecological genetics mapping studies. We demonstrate the performance of our approaches with two publicly available data sets from a plant (Arabidopsis thaliana) and a fish (Pungitius pungitius), as well as with simulated data.     

Complete genome sequencing of sixteen Francisella noatunensis subsp. orientalis isolates: A genomic approach for molecular characterization and spread dynamics of this clonal population

Francisella noatunensis subsp. orientalis (FNO) is an important emerging pathogen associated with disease outbreaks in farm-raised Nile tilapia. FNO genetic diversity using PCR-based typing, no intra-species discrimination was achieved among isolates/strains from different countries, thus demonstrating a clonal behaviour pattern. In this study, we aimed to evaluate the population structure of FNO isolates by comparing whole-genome sequencing data. The analysis of recombination showed that Brazilian isolates group formed a clonal population; whereas other lineages are also supported by this analysis for isolates from foreign countries. The whole-genome multilocus sequence typing (wgMLST) analysis showed varying numbers of dissimilar alleles, suggesting that the Brazilian clonal population are in expansion. Each Brazilian isolate could be identified as a single node by high-resolution gene-by-gene approach, presenting slight genetic differences associated to mutational events. The common ancestry node suggests a single entry into the country before 2012, and the rapid dissemination of this infectious agent may be linked to market sales of infected fingerlings.     

Phylogenetics of family Enterobacteriaceae and proposal to reclassify Escherichia hermannii and Salmonella subterranea as Atlantibacter hermannii and Atlantibacter subterranea gen. nov., comb. nov.

Multilocus sequence analysis based on hypervariable housekeeping proteins was utilized to differentiate closely related species in the family Enterobacteriaceae. Of 150 housekeeping proteins, the top 10 hypervariable proteins were selected and concatenated to obtain distance data. Distances between concatenated proteins within the family were 0.9–41.2%, whereas the 16S rRNA and atpD‐gyrB‐infB‐rpoB concatenated sequence (4MLSA) distances were 0.8–6.0% and 0.9–22.1%, respectively. These data indicate that phylogenetic analysis by concatenation of hypervariable proteins is a powerful tool for discriminating species in the family Enterobacteriaceae. To confirm the discriminatory power of the 10 chosen concatenated hypervariable proteins (C10HKP), phylogenetic trees based on C10HKP, 4MLSA, and the 16S rRNA gene were constructed. Comparison of average bootstrap values among C10HKP, 4MLSA and 16S rRNA genes indicated that the C10HKP tree was the most reliable. Location via the C10HKP tree was consistent with existing assignments for almost all species in the family Enterobacteriaceae. However, the C10HKP tree suggested that several species (including Enterobacter massiliensis, Escherichia vulneris, Escherichia hermannii, and Salmonella subterranea) should be reassigned to different clusters than those defined in previous analyses. Furthermore, E. hermannii and S. subterranea appeared to fall onto a branch independent from those occupied by the other Enterobacteriaceae. Therefore, we propose Atlantibacter gen. nov., such that E. hermannii and S. subterranea would be transferred to genus Atlantibacter as Atlantibacter hermannii, comb. nov. and Atlantibacter subterranea. comb. nov., respectively.     

Variation and association of fibronectin‐binding protein genes fnbA and fnbB in Staphylococcus aureus Japanese isolates

Fibronectin‐binding proteins A and B (FnBPA and FnBPB) mediate adhesion of Staphylococcus aureus to fibrinogen, elastin and fibronectin. FnBPA and FnBPB are encoded by two closely linked genes, fnbA and fnbB, respectively. With the exception of the N‐terminal regions, the amino acid sequences of FnBPA and FnBPB are highly conserved. To investigate the genetics and evolution of fnbA and fnbB, the most variable regions, which code for the 67th amino acids of the A through B regions (A67–B) of fnbA and fnbB, were focused upon. Eighty isolates of S. aureus in Japan were sequenced and 19 and 18 types in fnbA and fnbB, respectively, identified. Although the phylogeny of fnbA and fnbB were found to be quite different, each fnbA type connected with a specific fnbB type, indicating that fnbA and fnbB mutate independently, whereas the combination of both genes after recombination is stable. Hence those fnbA–fnbB combinations were defined as FnBP sequence types (FnSTs). Representative isolates of each FnST were assigned distinct STs by multilocus sequence typing, suggesting correspondence of FnST with genome lineage. Linkage disequilibrium (LD) analysis of the A67–B region revealed that subdomains N2, N3 and FnBR1 form a LD block in fnbA, whereas N2 and N3 form two independent LD blocks in fnbB. N2–N3 three‐dimensional structural models indicated that not only the variable amino acid residues, but also well‐conserved amino acid residues between FnBPA and FnBPB, are located on the surface of the protein. These results highlight a molecular process of the FnBP that has evolved by mingled mutation and recombination with retention of functions.     

Sea surface temperature,rather than land mass or geographic distance,may drive genetic differentiation in a species complex of highly dispersive seabirds

Seabirds, particularly Procellariiformes, are highly mobile organisms with a great capacity for long dispersal, though simultaneously showing high philopatry, two conflicting life‐history traits that may lead to contrasted patterns of genetic population structure. Landmasses were suggested to explain differentiation patterns observed in seabirds, but philopatry, isolation by distance, segregation between breeding and nonbreeding zones, and oceanographic conditions (sea surface temperatures) may also contribute to differentiation patterns. To our knowledge, no study has simultaneously contrasted the multiple factors contributing to the diversification of seabird species, especially in the gray zone of speciation. We conducted a multilocus phylogeographic study on a widespread seabird species complex, the little shearwater complex, showing highly homogeneous morphology, which led to considerable taxonomic debate. We sequenced three mitochondrial and six nuclear markers on all extant populations from the Atlantic (lherminieri) and Indian Oceans (bailloni), that is, five nominal lineages from 13 populations, along with one population from the eastern Pacific Ocean (representing the dichrous lineage). We found sharp differentiation among populations separated by the African continent with both mitochondrial and nuclear markers, while only mitochondrial markers allowed characterizing the five nominal lineages. No differentiation could be detected within these five lineages, questioning the strong level of philopatry showed by these shearwaters. Finally, we propose that Atlantic populations likely originated from the Indian Ocean. Within the Atlantic, a stepping‐stone process accounts for the current distribution. Based on our divergence time estimates, we suggest that the observed pattern of differentiation mostly resulted from historical and current variation in sea surface temperatures.     

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene‐mapping approach

Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small‐effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine‐spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL‐mapping approaches based on a de‐biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL‐mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single‐locus analyses of an F₂ interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1–6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small‐effect loci. Apart from suggesting moderately heritable (h² ≈ 0.15–0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL‐mapping approach developed here has distinctive advantages over the traditional QTL‐mapping methods in analyses of dense marker panels.     

Revisiting the phylogeny of Wolbachia in Collembola

The endosymbiont Wolbachia has been detected in a few parthenogenetic collembolans sampled in Europe and America, including three species of Poduromorpha, two species of Entomobryomorpha, and two species of Neelipleona. Based on 16S rRNA and ftsZ gene sequences, most of the Wolbachia infecting parthenogenetic collembolans were characterized as members of supergroup E and showed concordant phylogeny with their hosts. However, the two neelipleonan symbionts form another unique group, indicating that Wolbachia has infected parthenogenetic collembolans multiple times. In this study, five parthenogenetic collembolan species were identified as hosts of Wolbachia, and four new Wolbachia strains were reported for four collembolan species sampled in China, respectively, including a neelipleonan strain from Megalothorax incertus (wMinc). Our results demonstrated that the Wolbachia multilocus sequence typing (MLST) system is superior to the 16S rRNA + ftsZ approach for phylogenetic analyses of collembolan Wolbachia. The MLST system assigned these Wolbachia of parthenogenetic collembolans to supergroup E as a unique clade, which included wMinc, supporting the monophyletic origin of Wolbachia in parthenogenetic collembolan species. Moreover, our data suggested supergroup E as one of the most divergent lineages in Wolbachia and revealed the discrepancy between the phylogenies of Wolbachia from parthenogenetic collembolans and their hosts, which may result from the high level of genetic divergence between collembolan Wolbachia, in association with the geographic differentiation of their hosts, or the possible horizontal transmission of Wolbachia between different collembolan species.