Preferential retention of genes from one parental genome after polyploidy illustrates the nature and scope of the genomic conflicts induced by hybridization.

Polyploidy is increasingly seen as a driver of both evolutionary innovation and ecological success. One source of polyploid organisms' successes may be their origins in the merging and mixing of genomes from two different species (e.g., allopolyploidy). Using POInT (the Polyploid Orthology Inference Tool), we model the resolution of three allopolyploidy events, one from the bakers' yeast (Saccharomyces cerevisiae), one from the thale cress (Arabidopsis thaliana) and one from grasses including Sorghum bicolor. Analyzing a total of 21 genomes, we assign to every gene a probability for having come from each parental subgenome (i.e., derived from the diploid progenitor species), yielding orthologous segments across all genomes. Our model detects statistically robust evidence for the existence of biased fractionation in all three lineages, whereby genes from one of the two subgenomes were more likely to be lost than those from the other subgenome. We further find that a driver of this pattern of biased losses is the co-retention of genes from the same parental genome that share functional interactions. The pattern of biased fractionation after the Arabidopsis and grass allopolyploid events was surprisingly constant in time, with the same parental genome favored throughout the lineages' history. In strong contrast, the yeast allopolyploid event shows evidence of biased fractionation only immediately after the event, with balanced gene losses more recently. The rapid loss of functionally associated genes from a single subgenome is difficult to reconcile with the action of genetic drift and suggests that selection may favor the removal of specific duplicates. Coupled to the evidence for continuing, functionally-associated biased fractionation after the A. thaliana At-α event, we suggest that, after allopolyploidy, there are functional conflicts between interacting genes encoded in different subgenomes that are ultimately resolved through preferential duplicate loss

POInT’s inferences regarding the loss of genes post-WGD.

<p>The At-α duplication produced two sets of homoeologous regions, one from the parental subgenome with more surviving genes (“Less fractionated subgenome,” upper track) and one with fewer (“More fractionated subgenome,” lower track). Genes in these tracks may have surviving duplicates in at least some taxa (orange/tan), or they may be single-copy in all species (blue if derived from the less fractionated subgenome and green if from the more fractionated one). Under each taxon name is the number of single-copy genes predicted to have been retained from that parental subgenome in that taxon. The branch length (numbers under the branches of the <u><i>upper</i></u> tree) gives the value of α×time in the model of <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#pgen.1007267.g002" target="_blank">Fig 2B</a>: larger values correspond to a relatively higher chance that a position with a ohnolog pair present at the start of a branch will be single-copy by its end. Numbers above the branches give POInT’s estimate of the number of genes returned to single copy deriving from the less fractionated (upper panel) and more fractioned (lower panel) subgenomes, respectively. Under the branches of the lower tree are the branch-specific ratio of genes retained from subgenome #2 relative to subgenome #1: these values can be compared to the overall estimate of this parameter, which is 0.64, shown in the upper left. POInT’s estimates of the other global parameters for this model are also given here. Above each pillar of genes is POInT’s estimate of the posterior probability of the set of subgenome assignments depicted, relative to the other <i>2</i>^<i>n</i><i>-1</i> possible assignments (where <i>n</i> is the number of genomes). The two root branches are shown in red: these correspond to branches where the biased fractionation parameter ε was allowed to differ from the rest of the tree in our analyses of temporal patterns of biased fractionation (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#sec002" target="_blank">Methods</a>). Similar trees depicting loss events for the grass and yeast WGDs are given as <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#pgen.1007267.s001" target="_blank">S1 Fig</a>.</p

Protein interactions between single-copy genes from alternative subgenomes are rarer than expected.

<p>We extracted single-copy genes for a range of values of POInT’s overall confidence in pillar assignments to subgenomes (<i>x</i>-axis) and computed the <i>P</i>-value for the test of the null hypothesis of no fewer protein-protein interactions between products of genes from alternative subgenomes than expected (<i>y</i>-axis; panel <b>A</b>: see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#sec002" target="_blank">Methods</a>). We also computed the frequency of such “crossing” interactions relative to interactions between products of the same subgenome (<i>y</i>-axis, panel <b>B</b>).</p

POInT estimates for different datasets and ancestral orders.

<p>POInT estimates for different datasets and ancestral orders.</p

Consistency across the ancestral genome of POInT’s estimates of the subparental genome of origin.

<p><b>A)</b> In the six panels, we illustrate how often POInT’s assignment of parental subgenome of origin for At-α changes between two successive pillars when considering the “high synteny” dataset. A red tick at position <i>i</i> corresponds to a situation where POInT assigned parents-of-origin to two chromosomal regions at position <i>i-1</i> with probability of ≥85% and either the <i>opposite</i> combination of parents at position <i>i</i> or with the same assignment but with confidence less than 85%. Gray ticks, in turn, correspond to those positions immediately after a red tick where the confidence in the parental assignments is less than 85%. The blue ticks in the lower half of each block indicate positions where there is a double synteny break after position <i>i-1</i> (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#sec002" target="_blank">Methods</a><i>)</i>. At these positions, the parental inferences at position <i>i</i> are independent of those at <i>i-1</i>. Locations where all 6 genomes have such breaks are shown with the pink dotted lines. <b>B)</b> Estimates of shared parental blocks across genomes. With very few exceptions, locations where POInT finds a change in subgenome assignments correspond to these six-fold synteny breaks from <b>A</b>. Each blue/green colored block corresponds to a situation where at least 5, 4, or 3 genomes (top, middle and bottom, respectively) agree between every neighbor as to the subgenome assignment at a confidence of 85% or more. Narrower black regions are regions where there is no position-to-position agreement in assignment for any number of genomes (e.g., these are regions where our confidence in subgenome assignments is low overall). Any shared loss of synteny can induce a new block: such synteny breaks might, for instance, reflect a shift to new ancestral chromosome. For reference, we also show the set of blocks inferred with the WGD-<i>f</i> model as the smaller set of red/purple blocks. This model does not include BF, making it degenerate, so that subgenome 1 and 2 can be swapped. We therefore define one region of one genome as being subgenome #1 and make the block assignments correspondingly. Almost all of the phasing of blocks can be done without the assumption of BF, as is seen with the similarity between the blue/green and red/purple blocks. The implication of this fact is that the blocks are defined by the pattern of shared gene losses and that including BF in the model serves only to allow us to assign unlinked blocks to the same subgenomes based on their BF patterns. <b>C)</b> For the 16 blocks with more than 100 pillars, we show the estimates of the strength of BF (maximum likelihood estimate of ε; <i>y</i>-axis) judged solely from that block (block mid-point on the <i>x</i>-axis). These values indicate strong BF in all but three cases: in most of the larger blocks the estimated strength of BF is nearly identical to that for the full dataset (blue line). For the three blocks with weak evidence for BF (ε≈1.0), we further interrogated the patterns of gene loss (tables at bottom). In two of three cases, the signal of BF is relatively strong along the shared root branch where most losses occurred, with conflicting patterns on other branches. We attribute these differences to sampling effects among the relatively small number of losses along each branch. For the final block, with coordinates from pillars 2113 to 2318, the inferred pattern of losses contradicts the subgenome assignment, with more inferred losses from subgenome 1. When we examined the pattern of synteny breaks in this region, we discovered an anomaly: all of the genomes except <i>Eutrema salsugineum</i> had a synteny break at the end of this block: <i>E</i>. <i>salsugineum</i> instead had a break six pillars later (the pink shaded region). Hence, this synteny pattern caused the block to be linked to the next, larger, block, giving rise to the incongruous gene loss inferences. Equivalent figures for the full At-α dataset, the yeasts and the grasses are given as <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#pgen.1007267.s002" target="_blank">S2 Fig</a>.</p

Statistically overrepresented GO terms from the cellular component hierarchy associated with At-α duplication status and parental subgenome of origin (see Methods).

<p>On the <i>y</i> axis is the ln(fold-enrichment) of each GO terms among the single copy genes relative to the surviving duplicates from At-α. Dots represent cellular component terms that are significantly over (positive values) or underrepresented (negative values) among single copy genes relative to duplicates (Bonferroni corrected <i>P</i>-value ≤ 0.01 and a fold-enrichment of > ± 1.5). On the <i>x</i> axis is the ln(fold-enrichment) of GO terms of genes from subgenome 1 (the less fractionated genome) relative to those from subgenome 2 (the more fractionated one). GO terms that are overrepresented in genes from subgenome 1 with a <i>P</i>-value ≤ 0.05 after Bonferroni correction are shown as triangles. Points are colored based on the compartment in question, as indicated in the key at right. The patterns seen for the “Molecular Function” and “Biological Process” categories of terms are presented in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#pgen.1007267.s003" target="_blank">S3 Fig</a>.</p

Modeling WGD resolution with POInT.

<p>We employed a number of models of the fates of the duplicates produced by WGD. <b>A)</b> Statistical relationships between the various models for the yeast WGD (blue), At-α (green) and ρ (brown) events. The simplest model (WGD-<i>n</i>) considers only a balanced process of gene loss. From this model, we can either allow duplicate genes to become fixed (for instance by neo- or sub-functionalization, WGD-<i>f</i>) or for one of the two parental subgenomes to lose more genes than the other (WGD-<i>b</i>). Using a likelihood ratio test (LRT), we find that, for all three WGD events, allowing duplicate fixation significantly improves the fit of the data to the models (<i>P<</i>10⁻¹⁰, LRT, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#sec002" target="_blank">Methods</a>). However, for the yeast dataset, there is no significant evidence for biased fractionation (<i>P</i>>0.5, LRT), while for the two plant WGDs, adding it significantly improves the fit (<i>P<</i>10⁻¹⁰; LRT). From these two models, we can then allow the other process. Again, for yeast, there is significant evidence for fixation but not biased fractionation (<i>P<</i>10⁻¹⁰ and <i>P</i>>0.5, respectively, LRT) while for At-α and ρ, there is significant evidence for both (<i>P</i><10⁻¹⁰ in each case, LRT). We also tested a model where the biased fractionation parameter ε (see panel <b>B</b>) was allowed to differ on the shared root branch of the tree (WGD-<i>b</i>_<i>t</i><i>f</i>) compared to all of the other branches. For the two plant WGD events, there is no significant evidence that the level of biased fractionation differed early in history of the WGD relative to later in time (<i>P</i>≥0.19, <i>Results</i>). On the other hand, for the yeast WGD, biased fractionation was much more intense soon after the polyploidy event and weakened later (<i>P</i> = 0.001; <i>Results</i>). <b>B)</b> Model states and parameters. Our model has four states, two duplicated ones (<b>U</b> = undifferentiated duplicates and <b>F</b> = fixed duplicates) and two single copy states (<b>S</b>_<b>1</b> and <b>S</b>_<b>2</b>, corresponding to the two parental subgenomes). The base loss rate (α) is compounded with the estimated time to give the branch lengths of <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007267#pgen.1007267.g001" target="_blank">Fig 1</a>. The relative fixation rate γ (0≤γ<∞) gives the rate of duplicate fixation relative to the loss rate α. Likewise, the fractionation bias parameter ε (0≤ε≤1) gives the excess of preservations from subgenome 1 relative to subgenome 2 (assumed to be the more fractionated subgenome).</p

Transcriptome sequencing and analysis of Plasmodium gallinaceum reveals polymorphisms and selection on the apical membrane antigen-1

BACKGROUND: Plasmodium erythrocyte invasion genes play a key role in malaria parasite transmission, host-specificity and immuno-evasion. However, the evolution of the genes responsible remains understudied. Investigating these genes in avian malaria parasites, where diversity is particularly high, offers new insights into the processes that confer malaria pathogenesis. These parasites can pose a significant threat to birds and since birds play crucial ecological roles they serve as important models for disease dynamics. Comprehensive knowledge of the genetic factors involved in avian malaria parasite invasion is lacking and has been hampered by difficulties in obtaining nuclear data from avian malaria parasites. Thus the first Illumina-based de novo transcriptome sequencing and analysis of the chicken parasite Plasmodium gallinaceum was performed to assess the evolution of essential Plasmodium genes. METHODS: White leghorn chickens were inoculated intravenously with erythrocytes containing P. gallinaceum. cDNA libraries were prepared from RNA extracts collected from infected chick blood and sequencing was run on the HiSeq2000 platform. Orthologues identified by transcriptome sequencing were characterized using phylogenetic, ab initio protein modelling and comparative and population-based methods. RESULTS: Analysis of the transcriptome identified several orthologues required for intra-erythrocytic survival and erythrocyte invasion, including the rhoptry neck protein 2 (RON2) and the apical membrane antigen-1 (AMA-1). Ama-1 of avian malaria parasites exhibits high levels of genetic diversity and evolves under positive diversifying selection, ostensibly due to protective host immune responses. CONCLUSION: Erythrocyte invasion by Plasmodium parasites require AMA-1 and RON2 interactions. AMA-1 and RON2 of P. gallinaceum are evolutionarily and structurally conserved, suggesting that these proteins may play essential roles for avian malaria parasites to invade host erythrocytes. In addition, host-driven selection presumably results in the high levels of genetic variation found in ama-1 of avian Plasmodium species. These findings have implications for investigating avian malaria epidemiology and population dynamics. Moreover, this work highlights the P. gallinaceum transcriptome as an important public resource for investigating the diversity and evolution of essential Plasmodium genes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1475-2875-13-382) contains supplementary material, which is available to authorized users

Preferential retention of genes from one parental genome after polyploidy illustrates the nature and scope of the genomic conflicts induced by hybridization

<div><p>Polyploidy is increasingly seen as a driver of both evolutionary innovation and ecological success. One source of polyploid organisms’ successes may be their origins in the merging and mixing of genomes from two different species (e.g., allopolyploidy). Using POInT (the <u>P</u>olyploid <u>O</u>rthology <u>In</u>ference <u>T</u>ool), we model the resolution of three allopolyploidy events, one from the bakers’ yeast (<i>Saccharomyces cerevisiae</i>), one from the thale cress (<i>Arabidopsis thaliana)</i> and one from grasses including <i>Sorghum bicolor</i>. Analyzing a total of 21 genomes, we assign to every gene a probability for having come from each parental subgenome (i.e., derived from the diploid progenitor species), yielding orthologous segments across all genomes. Our model detects statistically robust evidence for the existence of <i>biased fractionation</i> in all three lineages, whereby genes from one of the two subgenomes were more likely to be lost than those from the other subgenome. We further find that a driver of this pattern of biased losses is the co-retention of genes from the same parental genome that share functional interactions. The pattern of biased fractionation after the <i>Arabidopsis</i> and grass allopolyploid events was surprisingly constant in time, with the same parental genome favored throughout the lineages’ history. In strong contrast, the yeast allopolyploid event shows evidence of biased fractionation only immediately after the event, with balanced gene losses more recently. The rapid loss of functionally associated genes from a single subgenome is difficult to reconcile with the action of genetic drift and suggests that selection may favor the removal of specific duplicates. Coupled to the evidence for continuing, functionally-associated biased fractionation after the <i>A</i>. <i>thaliana</i> At-α event, we suggest that, after allopolyploidy, there are functional conflicts between interacting genes encoded in different subgenomes that are ultimately resolved through preferential duplicate loss.</p></div