Soil fungal communities in tropical regions remain poorly understood. In order to increase the knowledge of diversity of soil-inhabiting fungi, we extracted total DNA from top-organic soil collected in seven localities dominated by four major ecosystems in the tropical island of Puerto Rico. In order to comprehensively characterize the fungal community, we PCR-amplified the ITS2 fungal barcode using newly designed degenerated primers and varying annealing temperatures to minimize primer bias. Sequencing results, obtained using Ion Torrent technology, comprised a total of 566,613 sequences after quality filtering. These sequences were clustered into 4,140 molecular operational taxonomic units (MOTUs) after removing low frequency sequences and rarefaction to account for differences in read depth between samples. Our results demonstrate that soil fungal communities in Puerto Rico are structured by ecosystem. Ascomycota, followed by Basidiomycota, dominates the diversity of fungi in soil. Amongst Ascomycota, the recently described soil-inhabiting class Archaeorhizomycetes was present in all the localities and taxa in this class were among the most commonly observed MOTUs. The Basidiomycota community was dominated by soil decomposers and ectomycorrhizal fungi with a distribution strongly affected by local variation to a greater degree than Ascomycota.

We give recursions for the expected site-frequency spectrum associated with Xi-coalescents, that is exchangeable coalescents which admit simultaneous multiple mergers of ancestral lineages. Xi-coalescents arise, for example, in association with population models of skewed offspring distributions with diploidy, recurrent advantageous mutations, or strong bottlenecks. In contrast, Lambda-coalescents admit multiple mergers of lineages, but at most one such merger each time. Xi-coalescents, as well as Lambda-coalescents, can predict an excess of singletons, compared to the Kingman coalescent. We compare estimates of coalescent parameters when Xi-coalescent models are applied to data obtained from Lambda-coalescents, and vice versa. In general, Xi-coalescents predict fewer singletons than corresponding Lambda-coalescents, but higher count of mutations of `size’ larger than singletons. We analyse unfolded site-frequency spectra obtained for nuclear loci of the diploid Atlantic cod, and obtain different coalescent parameter estimates than previously obtained with Lambda-coalescents. Our results provide new inference tools, and suggest that for nuclear population genetic data from diploid or polyploid highly fecund populations who may have skewed offspring distributions, one should not apply Lambda-coalescents, but Xi-coalescents.

Background: The length of a protein sequence is largely determined by its function, i.e. each functional group is associated with an optimal size. However, comparative genomics revealed that proteins’ length may be affected by additional factors. In 2002 it was shown that in bacterium Escherichia coli and the archaeon Archaeoglobus fulgidus, protein sequences with no homologs are, on average, shorter than those with homologs [1]. Most experts now agree that the length distributions are distinctly different between protein sequences with and without homologs in bacterial and archaeal genomes. In this study, we examine this postulate by a comprehensive analysis of all annotated prokaryotic genomes and focusing on certain exceptions. Results: We compared lengths’ distributions of “having homologs proteins” (HHPs) and “non-having homologs proteins” (orphans or ORFans) in all currently annotated completely sequenced prokaryotic genomes. As expected, the HHPs and ORFans have strikingly different length distributions in almost all genomes. As previously established, the HHPs, indeed, are, on average, longer than the ORFans, and the length distributions for the ORFans have a relatively narrow peak, in contrast to the HHPs, whose lengths spread over a wider range of values. However, about thirty genomes do not obey these rules. Practically all genomes of Mycoplasma and Ureaplasma have atypical ORFans distributions, with the mean lengths of ORFan larger than the mean lengths of HHPs. These genera constitute over 80% of atypical genomes. Conclusions: We confirmed on a ubiquitous set of genomes the previous observation that HHPs and ORFans have different gene length distributions. We also showed that Mycoplasmataceae genomes have very distinctive distributions of ORFans lengths. We offer several possible biological explanations of this phenomenon.

Competitive exclusion and habitat filtering are believed to have an important influence on the assembly of ecological communities, but ecologists and evolutionary biologists have not reached a consensus on how to quantify patterns that would reveal the action of these processes. No fewer than 22 phylogenetic community structure metrics and nine null models can be combined, providing 198 approaches to test for such patterns. Choosing statistically appropriate approaches is currently a daunting task. First, given random community assembly, we assessed similarities among metrics and among null models in their behavior across communities varying in species richness. Second, we developed spatially explicit, individual-based simulations where communities were assembled either at random, by competitive exclusion or by habitat filtering. Third, we quantified the performance (type I and II error rates) of all 198 approaches against each of the three assembly processes. Many metrics and null models are functionally equivalent, more than halving the number of unique approaches. Moreover, an even smaller subset of metric and null model combinations is suitable for testing community assembly patterns. Metrics like mean pairwise phylogenetic distance and phylogenetic diversity were better able to detect simulated community assembly patterns than metrics like phylogenetic abundance evenness. A null model that simulates regional dispersal pressure on the community of interest outperformed all others. We introduce a flexible new R package, metricTester, to facilitate robust analyses of method performance. The package is programmed in parallel to readily accommodate integration of new row-wise matrix calculations (metrics) and matrix-wise randomizations (null models) to generate expectations and quantify error rates of proposed methods.

We identified and characterized a free PRE-1 element inserted into the promoter region of the porcine IGFBP7 gene whose integration mechanisms into the genome, including copy number, distribution preferences, capacity to exonize and phyloclustering pattern are similar to that of the primate Alu element. 98% of these PRE-1 elements also contain two conserved internal AluI restriction enzyme recognition sites, and the RNA structure of PRE1 can be folded into a two arms model like the Alu RNA structure. It is more surprising that the length of the PRE-1 fragments is nearly the same in 20 chromosomes and positively correlated to its fracture site frequency. All of these fracture sites are close to the mutation hot spots of PRE-1 families, and most of these hot spots are located in the non-complementary fragile regions of the PRE-1 RNA structure. Sequence homology analysis showed that the PRE-1 element seemed to share a common ancestor 7SL RNA with primates but was generated by different evolutionary model, which suggests that the suidae may be the closest relatives to primates in laurasiatheria.

Horizontal gene transfer (HGT) plays a central role in bacterial evolution, yet the molecular and cellular constraints on functional integration of the foreign genes are poorly understood. Here we performed inter-species replacement of the chromosomal folA gene, encoding an essential metabolic enzyme dihydrofolate reductase (DHFR), with orthologs from 35 other mesophilic bacteria. The orthologous inter-species replacements caused a marked drop (in the range 10-90%) in bacterial growth rate despite the fact that most orthologous DHFRs are as stable as E.coli DHFR at 370C and are more catalytically active than E. coli DHFR. Although phylogenetic distance between E. coli and orthologous DHFRs as well as their individual molecular properties correlate poorly with growth rates, the product of the intracellular DHFR abundance and catalytic activity (kcat/KM), correlates strongly with growth rates, indicating that the drop in DHFR abundance constitutes the major fitness barrier to HGT. Serial propagation of the orthologous strains for ~600 generations dramatically improved growth rates by largely alleviating the fitness barriers. Whole genome sequencing and global proteome quantification revealed that the evolved strains with the largest fitness improvements have accumulated mutations that inactivated the ATP-dependent Lon protease, causing an increase in the intracellular DHFR abundance. In one case DHFR abundance increased further due to mutations accumulated in folA promoter, but only after the lon inactivating mutations were fixed in the population. Thus, by apparently distinguishing between self and non-self proteins, protein homeostasis imposes an immediate and global barrier to the functional integration of foreign genes by decreasing the intracellular abundance of their products. Once this barrier is alleviated, more fine-tuned evolution occurs to adjust the function/expression of the transferred proteins to the constraints imposed by the intracellular environment of the host organism.

The impact of environment on human health is dramatic, with major risk factors including substance use, diet and exercise. However, identifying interactions between the environment and an individual’s genetic background (GxE) has been hampered by statistical and computational challenges. By combining RNA sequencing of whole blood and extensive environmental annotations collected from 922 individuals, we have evaluated GxE interactions at a cellular level. We have developed EAGLE, a hierarchical Bayesian model for identifying GxE interactions based on association between environment and allele-specific expression (ASE). EAGLE increases power by leveraging the controlled, within-sample comparison of environmental impact on different genetic backgrounds provided by ASE, while also taking into account technical covariates and over-dispersion of sequencing read counts. EAGLE identifies 35 GxE interactions, a substantial increase over standard GxE testing. Among EAGLE hits are variants that modulate response to smoking, exercise and blood pressure medication. Further, application of EAGLE identifies GxE interactions to infection response that replicate results reported in vitro, demonstrating the power of EAGLE to accurately identify GxE candidates from large RNA sequencing studies.

Mapping reads to a genome remains challenging, especially for non-model organisms with poorer quality assemblies, or for organisms with higher rates of mutations. While most research has focused on speeding up the mapping process, little attention has been paid to optimize the choice of mapper and parameters for a user’s dataset. Here we present Teaser, which assists in these choices through rapid automated benchmarking of different mappers and parameter settings for individualized data. Within minutes, Teaser completes a quantitative evaluation of an ensemble of mapping algorithms and parameters. Using Teaser, we demonstrate how Bowtie2 can be optimized for different data.