11 research outputs found
Units of species and speciation.
<p>The Neo-Darwinian view of the Modern Synthesis is that "speciation genes" are the units driving speciation across the genome. Alternatively, if gene sets (including consortia of genes like plasmids or other mobile genetic elements) are sufficiently decoupled from their host genomes, this will lead to "gene ecology," in which gene sets, not species, determine reproductive isolation and/or adapt to ecological niches. Speciation could also be maintained (or potentially driven) by microbial symbionts or by host genes that select for particular symbionts, resulting in hologenome species. All of these speciation mechanisms can potentially be driven by selection or drift, and the list of units and mechanisms (arrows) is not exhaustive.</p
Schematic of the <i>symsim</i> model.
<p>(A) Additive fitness. The steps of the simulation are (i) growth/selection according to relative additive fitness within each niche, (ii) small probability of recombination (<i>r</i>) by gene conversion of homologous loci (diagonal lines) in a sympatric, mixed pool of genotypes from both niches, and (iii) individuals return to the niche to which their genotype is best adapted (<i>e.g.</i> in this 3-locus example, genotypes 000 and 010 go to niche 0, while 111 and 011 go to niche 1). Steps (i), (ii) and (iii) are iterated for a set number of generations or until any of the derived alleles go extinct. (B) Step fitness. The steps of the simulations are the same as for additive fitness, except that individuals can grow and be selected in both niches. Optimally adapted genotypes (111 and 000) compete in just one niche. Intermediates compete in both niches, but pay a fitness cost <i>s</i> for niche switching. In the example shown, an individual of genotype 010 obtains 2/3 of its resources in niche 0 (and adds a count of 2/3 of an individual to the population size of niche 0), and 1/3 from niche 1 (and adds a count of 1/3 of an individual to niche 1).</p
Models of speciation under different regimes of selection and recombination.
<p>In all models, a single population of chromosomes (circles) splits into two nascent species, distinguishable by sets of genetic differences. At each time point, the most frequent multilocus genotype is shown, but other chromosomes could be segregating in the population at lower frequencies. Different haplotypes (or clonal frames) are shown as black or white circles. The ancestral niche is shown in blue and a new niche in orange. Gene flow (recombination) between species is indicated by horizontal connections between branches. (<b>A</b>) In the simplest model of speciation with gene flow, a single mutation controlling sexual isolation (but not under selection) is the only divergent locus (yellow square), with other loci experiencing gene flow between incipient species. (<b>B</b>) Selection during speciation can produce a pattern of genetic diversity across the genome very similar to (A), but species are expected to be longer-lived. Mutations under selection at early and later stages of speciation are shown as orange stars. (<b>C</b>) Allopatric speciation with a population bottleneck and neutral divergence of species. As in (A), competitive exclusion should lead to the extinction of one species if they come back into contact. (<b>D</b>) Without gene flow, the mutation under selection between species (orange star) will purge diversity genome-wide as it sweeps through one population, resulting in genome-wide divergence from the other population.</p
Results of <i>symsim</i> model under additive fitness.
<p>(A, B, C) Weak selection. (D, E, F) Strong selection. (A, D) Probability of appearance (<i>p</i>) of the derived (niche 1) optimal genotype in 100 replicate simulations for each combination of the number of loci involved in niche adaptation, <i>L</i> and the recombination rate, <i>r</i>. High probabilities (<i>p</i> = 1) are shown in white, low probabilities in black, and intermediate probabilities in grey scale. The space under the red line indicates extinction of the niche-1 optimal genotype in all 100 replicates (<i>p</i><0.01). (B, E) Time to appearance of the niche 1 optimal genotype (mean over 100 replicate simulations). The red line is the same as in (A); <i>n.d.</i> refers to appearance time not determined, or effectively infinite, because extinction of niche-1 alleles occurred before the optimal genotype could appear. Shorter times are shown in white, effectively infinite times in black, and intermediate times in grey scale. (C, F) Completeness of speciation. The mean fraction of the pooled populations (niche 0 and 1) occupied by optimally-adapted genotypes is based on 10 replicate simulations for every combination of <i>L</i> and <i>r</i>. Complete speciation (optimal genotype fraction near 1) shown in white, incomplete in black, and intermediate completeness in grey scale. Magenta letters in C refer to the same simulations depicted in panels (A, B, C, D) of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053539#pone-0053539-g004" target="_blank">Figure 4</a>.</p
Bat skin microbiome: metadata
<b>mapping_bats.txt</b> is the sampled bats mapping file<br><br><b>Bat_OTUs_table_TAX.biom</b> is the taxonomy assigned OTU by library matrix with of only non-chimeric sequences<br><br><b>unique.dbOTU.nonchimera.fasta</b> is a fasta file of only non-chimeric OTU representatives<br><br><b>BatTree</b> is the phylogenetic tree built with FastTree 2.1.8<strong><br><br>Summarize_OTUs_Table_bat_only </strong>is a summary file of the information in the biom table<strong>Â <br><br><br></strong><br><br>
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Bat skin microbiome: metadata
<b>mapping_bats.txt</b> is the sampled bats mapping file<br><br><b>Bat_OTUs_table_TAX.biom</b> is the taxonomy assigned OTU by library matrix with of only non-chimeric sequences<br><br><b>unique.dbOTU.nonchimera.fasta</b> is a fasta file of only non-chimeric OTU representatives<br><br><b>BatTree</b> is the phylogenetic tree built with FastTree 2.1.8<strong><br><br>Summarize_OTUs_Table_bat_only </strong>is a summary file of the information in the biom table<strong>Â <br><br><br></strong><br><br>
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Bat skin microbiome: raw sequencing data
Raw sequencing data. This experiment was carried out in two sequencing runs (Run1 and Run2). <br
La Charente
18 mars 18811881/03/18 (A10,N4303)-1881/03/18.Appartient à l’ensemble documentaire : PoitouCh
Data_Sheet_2.FASTA
<p>Bacterial communities are composed of distinct groups of potentially interacting lineages, each thought to occupy a distinct ecological niche. It remains unclear, however, how quickly niche preference evolves and whether more closely related lineages are more likely to share ecological niches. We addressed these questions by following the dynamics of two bloom-forming cyanobacterial genera over an 8-year time-course in Lake Champlain, Canada, using 16S amplicon sequencing and measurements of several environmental parameters. The two genera, Microcystis (M) and Dolichospermum (D), are frequently observed simultaneously during bloom events and thus have partially overlapping niches. However, the extent of their niche overlap is debated, and it is also unclear to what extent niche partitioning occurs among strains within each genus. To identify strains within each genus, we applied minimum entropy decomposition (MED) to 16S rRNA gene sequences. We confirmed that at a genus level, M and D have different preferences for nitrogen and phosphorus concentrations. Within each genus, we also identified strains differentially associated with temperature, precipitation, and concentrations of nutrients and toxins. In general, niche similarity between strains (as measured by co-occurrence over time) declined with genetic distance. This pattern is consistent with habitat filtering – in which closely related taxa are ecologically similar, and therefore tend to co-occur under similar environmental conditions. In contrast with this general pattern, similarity in certain niche dimensions (notably particulate nitrogen and phosphorus) did not decline linearly with genetic distance, and instead showed a complex polynomial relationship. This observation suggests the importance of processes other than habitat filtering – such as competition between closely related taxa, or convergent trait evolution in distantly related taxa – in shaping particular traits in microbial communities.</p
Data_Sheet_3.ZIP
<p>Bacterial communities are composed of distinct groups of potentially interacting lineages, each thought to occupy a distinct ecological niche. It remains unclear, however, how quickly niche preference evolves and whether more closely related lineages are more likely to share ecological niches. We addressed these questions by following the dynamics of two bloom-forming cyanobacterial genera over an 8-year time-course in Lake Champlain, Canada, using 16S amplicon sequencing and measurements of several environmental parameters. The two genera, Microcystis (M) and Dolichospermum (D), are frequently observed simultaneously during bloom events and thus have partially overlapping niches. However, the extent of their niche overlap is debated, and it is also unclear to what extent niche partitioning occurs among strains within each genus. To identify strains within each genus, we applied minimum entropy decomposition (MED) to 16S rRNA gene sequences. We confirmed that at a genus level, M and D have different preferences for nitrogen and phosphorus concentrations. Within each genus, we also identified strains differentially associated with temperature, precipitation, and concentrations of nutrients and toxins. In general, niche similarity between strains (as measured by co-occurrence over time) declined with genetic distance. This pattern is consistent with habitat filtering – in which closely related taxa are ecologically similar, and therefore tend to co-occur under similar environmental conditions. In contrast with this general pattern, similarity in certain niche dimensions (notably particulate nitrogen and phosphorus) did not decline linearly with genetic distance, and instead showed a complex polynomial relationship. This observation suggests the importance of processes other than habitat filtering – such as competition between closely related taxa, or convergent trait evolution in distantly related taxa – in shaping particular traits in microbial communities.</p