No abstract

MicroRNA (miRNA) is one class of newly identified, small, non-coding RNAs that play versatile and important roles in post-transcriptional gene regulation. All miRNAs have similar secondary hairpin structures; many of these are evolutionarily conserved. This suggests a powerful approach to predict the existence of new miRNA orthologs or homologs in other species. We developed a comprehensive strategy to identify new miRNA homologs by mining the repository of available ESTs. A total of 481 miRNAs, belonging to 37 miRNA families in 71 different plant species, were identified from more than 6 million EST sequences in plants. The potential targets of the EST-predicted miRNAs were also elucidated from the EST and protein databases, providing additional evidence for the real existence of these miRNAs in the given plant species. Some plant miRNAs were physically clustered together, suggesting that these miRNAs have similar gene expression patterns and are transcribed together as a polycistron, as observed among animal miRNAs. The uracil nucleotide is dominant in the first position of 5' mature miRNAs. Our results indicate that many miRNA families are evolutionarily conserved across all major lineages of plants, including mosses, gymnosperms, monocots and eudicots. Additionally, the number of miRNAs discovered was directly related to the number of available ESTs and not to evolutionary relatedness to Arabidopsis thaliana, indicating that miRNAs are conserved and little phylogenetic signal exists in the presence or absence of these miRNAs. Regulation of gene expression by miRNAs appears to have existed at the earliest stages of plant evolution and has been tightly constrained (functionally) for more than 425 million years.

Understanding the historical dynamics of forest communities is a critical element for accurate prediction of their response to future change. Here, we examine evergreen rainforest distribution in the Sunda Shelf region at the last glacial maximum (LGM), using a spatially explicit model incorporating geographic, paleoclimatic, and geologic evidence. Results indicate that at the LGM, Sundaland rainforests covered a substantially larger area than currently present. Extrapolation of the model over the past million years demonstrates that the current ''island archipelago'' setting in Sundaland is extremely unusual given the majority of its history and the dramatic biogeographic transitions caused by global deglaciation were rapid and brief. Compared with dominant glacial conditions, lowland forests were probably reduced from approximately 1.3 to 0.8 ؋ 10 6 km 2 while upland forests were probably reduced by half, from approximately 2.0 to 1.0 ؋ 10 5 km 2 . Coastal mangrove and swamp forests experienced the most dramatic change during deglaciations, going through a complete and major biogeographic relocation. The Sundaland forest dynamics of fragmentation and contraction and subsequent expansion, driven by glacial cycles, occur in the opposite phase as those in the northern hemisphere and equatorial Africa, indicating that Sundaland evergreen rainforest communities are currently in a refugial stage. Widespread human-mediated reduction and conversion of these forests in their refugial stage, when most species are passing through significant population bottlenecks, strongly emphasizes the urgency of conservation and management efforts. Further research into the natural process of fragmentation and contraction during deglaciation is necessary to understand the long-term effect of human activity on forest species. lowland evergreen rainforest ͉ paleoclimate simulation ͉ upland evergreen rainforest T he Southeast Asian continent has one of the most complex geological histories in the world (1-3). The product of an ongoing collision between 2 ancient continents separated by an island archipelago (4, 5), several distinct centers of biological diversity can be identified within a small geographic range (Indochina, Sundaland, Wallacea, and Papuasia), demarcated by the Isthmus of Kra (6) and Wallace's Line (7). During the Quaternary Period, cyclical climate changes have affected the region in 2 ways: sea level change (8) modified total land area (9) while climate change affected the geographic distribution and elevational zonation of forest types (10). These land area dynamics may have had an impact on global climate as well, potentially affecting the ENSO cycle (11). Understanding the historical spatial dynamics of forest distribution plays a crucial role in the ability to predict community response to future change (12, 13).Here, we have generated a distribution model of Sundaland rainforest at the Last Glacial Maximum (LGM) by combining paleontological constraints (5) with the results of a numerical simulation of paleoclimate...

Aim Tropical forests have been recognized as important global carbon sinks and sources. However, many uncertainties about the spatial distribution of live tree above-ground biomass (AGB) remain, mostly due to limited availability of AGB field data. Recent studies in the Amazon have already shown the importance of large sample size for accurate AGB gradient analysis. Here we use a large stem density, basal area, community wood density and AGB dataset to study and explain their spatial patterns in an Asian tropical forest.Location Borneo, Southeast Asia. MethodsWe combined stem density, basal area, community wood density and AGB data from 83 locations in Borneo with an environmental database containing elevation, climate and soil variables. The Akaike information criterion was used to select models and environmental variables that best explained the observed values of stem density, basal area, community wood density and AGB. These models were used to extrapolate these parameters across Borneo. ResultsWe found that wood density, stem density, basal area and AGB respond significantly, but differentially, to the environment. AGB was only correlated with basal area, but not with stem density and community wood specific gravity. Main conclusionsUnlike results from Amazonian forests, soil fertility was an important positive correlate for AGB in Borneo while community wood density, which is a main driver of AGB in the Neotropics, did not correlate with AGB in Borneo. Also, Borneo's average AGB of 457.1 Mg ha -1 was c. 60% higher than the Amazonian average of 288.6 Mg ha -1 . We find evidence that this difference might be partly explained by the high density of large wind-dispersed Dipterocarpaceae in Borneo, which need to be tall and emergent to disperse their seeds. Our results emphasize the importance of Bornean forests as carbon sinks and sources due to their high carbon storage capacity.

Tropical Southeast (SE) Asia harbors extraordinary species richness and in its entirety comprises four of the Earth's 34 biodiversity hotspots. Here, we examine the assembly of the SE Asian biota through time and space. We conduct meta-analyses of geological, climatic, and biological (including 61 phylogenetic) data sets to test which areas have been the sources of long-term biological diversity in SE Asia, particularly in the pre-Miocene, Miocene, and Plio-Pleistocene, and whether the respective biota have been dominated by in situ diversification, immigration and/or emigration, or equilibrium dynamics. We identify Borneo and Indochina, in particular, as major "evolutionary hotspots" for a diverse range of fauna and flora. Although most of the region's biodiversity is a result of both the accumulation of immigrants and in situ diversification, within-area diversification and subsequent emigration have been the predominant signals characterizing Indochina and Borneo's biota since at least the early Miocene. In contrast, colonization events are comparatively rare from younger volcanically active emergent islands such as Java, which show increased levels of immigration events. Few dispersal events were observed across the major biogeographic barrier of Wallace's Line. Accelerated efforts to conserve Borneo's flora and fauna in particular, currently housing the highest levels of SE Asian plant and mammal species richness, are critically required.

Predicting community and species responses to disturbance is complicated by incomplete knowledge about species traits. A phylogenetic framework should partially solve this problem, as trait similarity is generally correlated with species relatedness, closely related species should have similar sensitivities to disturbance. Disturbance should thus result in community assemblages of closely related species. We tested this hypothesis with 18 disturbed and 16 reference whole-lake, long-term zooplankton data sets. Regardless of disturbance type, communities generally contained more closely related species when disturbed. This effect was independent of species richness, evenness, and abundance. Communities already under stress (i.e., those in acidic lakes) changed most when disturbed. Species sensitivities to specific disturbances were phylogenetically conserved, were independent of body size, and could be predicted by the sensitivities of close relatives within the same community. Phylogenetic relatedness can effectively act as a proxy for missing trait information when predicting community and species responses to disturbance.

BackgroundNext-generation sequencing technologies are rapidly generating whole-genome datasets for an increasing number of organisms. However, phylogenetic reconstruction of genomic data remains difficult because de novo assembly for non-model genomes and multi-genome alignment are challenging.ResultsTo greatly simplify the analysis, we present an Assembly and Alignment-Free (AAF) method (https://sourceforge.net/projects/aaf-phylogeny) that constructs phylogenies directly from unassembled genome sequence data, bypassing both genome assembly and alignment. Using mathematical calculations, models of sequence evolution, and simulated sequencing of published genomes, we address both evolutionary and sampling issues caused by direct reconstruction, including homoplasy, sequencing errors, and incomplete sequencing coverage. From these results, we calculate the statistical properties of the pairwise distances between genomes, allowing us to optimize parameter selection and perform bootstrapping. As a test case with real data, we successfully reconstructed the phylogeny of 12 mammals using raw sequencing reads. We also applied AAF to 21 tropical tree genome datasets with low coverage to demonstrate its effectiveness on non-model organisms.ConclusionOur AAF method opens up phylogenomics for species without an appropriate reference genome or high sequence coverage, and rapidly creates a phylogenetic framework for further analysis of genome structure and diversity among non-model organisms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1647-5) contains supplementary material, which is available to authorized users.

The effects of commercial logging on tree diversity in tropical rainforest are largely unknown. In this study, selectively logged tropical rainforest in Indonesian Borneo is shown to contain high tree species richness, despite severe structural damage. Plots logged 8 years before sampling contained fewer species of trees greater than 20 centimeters in diameter than did similar-sized unlogged plots. However, in samples of the same numbers of trees (requiring a 50 percent larger area), logged forest contained as many tree species as unlogged forest. These findings warrant reassessment of the conservation potential of large tracts of commercially logged tropical rainforest.