Pop’s Pipes: poplar gene expression data analysis pipelines

We developed multiple gene expression pipelines and assembled them into a web-based tool called Pop’s Pipes to facilitate preprocessing and analysis of substantial poplar gene expression data. The input data can be spatiotemporal microarray and RNA-seq data from comparable tissues, time points, or treatment-vs-control conditions. Pop’s Pipes can be used to identify differentially expressed genes between one or multiple paired tissues, time points, or treatment-vs-control conditions in a single in silico analysis. The differentially expressed genes (DEGs) obtained for each comparison will be automatically analyzed by Pop’s Pipes for identifying significantly enriched gene ontologies and interpro protein domains. Also, significantly changed metabolic pathways across all input data sets will be identified. We also integrated a pipeline into Pop's Pipes for constructing any of three type gene ontology trees when a short list of gene ontologies from biological processes, molecular functions, or cellular components is used as an input. The resulting information from Pop’s Pipes enables scrutiny to create spatiotemporal models and hypotheses to understand how poplar develops and functions. Pop’s Pipes can analyze a microarray or RNA-seq data set with 10 time points in 4–10 h, with each time point containing three replicates of treatments and three controls. Such a data set usually takes a bioinformatician a few months to a year to analyze. Pop’s Pipes can thus save users tremendous amounts of research time when large numbers of comparative data need to be analyzed.     

Revealing allele-specific gene expression by single-cell transcriptomics

Single-cell sequencing has emerged as a revolutionary method that reveals biological processes with unprecedented resolution and scale, and has already greatly impacted biology and medicine. To investigate processes such as alternative splicing, novel exon detection and allele-specific expression (ASE), full-length based single-cell RNA-seq methods are required for broad sequence coverage and single nucleotide polymorphism (SNP) identification. In this review, we revisit recent achievements from studies that used single-cell RNA-seq to advance our understanding of ASE in the context of both autosomal and X-chromosome genes. We also recapitulate useful bioinformatic tools developed to identify haplotype phase.     

环境微生物宏基因组学研究中的生物信息学方法

高通量测序技术的发展促进了组学技术在环境微生物研究中的广泛应用,而宏基因组学是目前最为关键和成熟的组学方法。生物信息学在微生物宏基因组学研究中具有至关重要的作用。它贯穿于宏基因组学的数据收集和存储、数据处理和分析等各个阶段,既是宏基因组学推广的最大瓶颈,也是目前宏基因组学研究发展的关键所在。本文主要介绍和归纳了目前在高通量宏基因组测序中常用的生物信息学分析平台及其重要的信息分析工具。未来几年之内,测序成本的下降和测序深度的增加将进一步增大宏基因组学研究在数据存储、数据处理和数据挖掘层面的难度,因此相应生物信息学技术与方法的研究和发展也势在必行。近期内我们应该首先加强基础性分析和存储平台的建设以方便普通环境微生物研究者使用,同时针对目前生物信息分析的瓶颈步骤和关键任务重点突破,逐步发展。     

Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community

As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.     

Evaluation of automated pipelines for tree and plot metric estimation from TLS data in tropical forest areas

Background and AimsTerrestrial LiDAR scanning (TLS) data are of great interest in forest ecology and management because they provide detailed 3-D information on tree structure. Automated pipelines are increasingly used to process TLS data and extract various tree- and plot-level metrics. With these developments comes the risk of unknown reliability due to an absence of systematic output control. In the present study, we evaluated the estimation errors of various metrics, such as wood volume, at tree and plot levels for four automated pipelines.MethodsWe used TLS data collected from a 1-ha plot of tropical forest, from which 391 trees >10 cm in diameter were fully processed using human assistance to obtain control data for tree- and plot-level metrics.Key ResultsOur results showed that fully automated pipelines led to median relative errors in the quantitative structural model (QSM) volume ranging from 39 to 115 % at the tree level and 10 to 134 % at the 1-ha plot level. For tree-level metrics, the median error for the crown-projected area ranged from 46 to 59 % and that for the crown-hull volume varied from 72 to 88 %. This result suggests that the tree isolation step is the weak link in automated pipeline methods. We further analysed how human assistance with automated pipelines can help reduce the error in the final QSM volume. At the tree scale, we found that isolating trees using human assistance reduced the error in wood volume by a factor of 10. At the 1-ha plot scale, locating trees with human assistance reduced the error by a factor of 3.ConclusionsOur results suggest that in complex tropical forests, fully automated pipelines may provide relatively unreliable metrics at the tree and plot levels, but limited human assistance inputs can significantly reduce errors.     

Insights into regional patterns of Amazonian forest structure,diversity, and dominance from three large terra-firme forest dynamics plots

We analyze forest structure, diversity, and dominance in three large-scale Amazonian forest dynamics plots located in Northwestern (Yasuni and Amacayacu) and central (Manaus) Amazonia, to evaluate their consistency with prevailing wisdom regarding geographic variation and the shape of species abundance distributions, and to assess the robustness of among-site patterns to plot area, minimum tree size, and treatment of morphospecies. We utilized data for 441,088 trees (DBH ≥1 cm) in three 25-ha forest dynamics plots. Manaus had significantly higher biomass and mean wood density than Yasuni and Amacayacu. At the 1-ha scale, species richness averaged 649 for trees ≥1 cm DBH, and was lower in Amacayacu than in Manaus or Yasuni; however, at the 25-ha scale the rankings shifted, with Yasuni < Amacayacu < Manaus. Within each site, Fisher’s alpha initially increased with plot area to 1–10 ha, and then showed divergent patterns at larger areas depending on the site and minimum size. Abundance distributions were better fit by lognormal than by logseries distributions. Results were robust to the treatment of morphospecies. Overall, regional patterns in Amazonian tree species diversity vary with the spatial scale of analysis and the minimum tree size. The minimum area to capture local diversity is 2 ha for trees ≥1 cm DBH, or 10 ha for trees ≥10 cm DBH. The underlying species abundance distribution for Amazonian tree communities is lognormal, consistent with the idea that the rarest species have not yet been sampled. Enhanced sampling intensity is needed to fill the still large voids we have in plant diversity in Amazon forests.     

RNAnue: efficient data analysis for RNA–RNA interactomics

RNA–RNA inter- and intramolecular interactions are fundamental for numerous biological processes. While there are reasonable approaches to map RNA secondary structures genome-wide, understanding how different RNAs interact to carry out their regulatory functions requires mapping of intermolecular base pairs. Recently, different strategies to detect RNA–RNA duplexes in living cells, so called direct duplex detection (DDD) methods, have been developed. Common to all is the Psoralen-mediated in vivo RNA crosslinking followed by RNA Proximity Ligation to join the two interacting RNA strands. Sequencing of the RNA via classical RNA-seq and subsequent specialised bioinformatic analyses the result in the prediction of inter- and intramolecular RNA–RNA interactions. Existing approaches adapt standard RNA-seq analysis pipelines, but often neglect inherent features of RNA–RNA interactions that are useful for filtering and statistical assessment. Here we present RNAnue, a general pipeline for the inference of RNA–RNA interactions from DDD experiments that takes into account hybridisation potential and statistical significance to improve prediction accuracy. We applied RNAnue to data from different DDD studies and compared our results to those of the original methods. This showed that RNAnue performs better in terms of quantity and quality of predictions.     

Antipredation Sleeping Behavior of Skywalker Hoolock Gibbons (<Emphasis Type="Italic">Hoolock tianxing</Emphasis>) in Mt. Gaoligong,Yunnan, China

Studying sleeping behavior can provide key information for understanding the ecology of a species. Antipredation is an important factor that affects primate sleeping behavior. We studied antipredation sleeping behavior in skywalker hoolock gibbons (Hoolock tianxing). We studied one group (NA) and a solitary female (NB) at Nankang from July 2010 to September 2011, and another group (BB) at Banchang from May 2013 to December 2014 in Mt. Gaoligong, Yunnan, China. Over the study period, we recorded 67 sleeping trees for members of group NA over 92 days, 17 trees for the solitary female NB over 22 days, and 159 trees for members of group BB over 186 days. Skywalker hoolock gibbons at both sites rarely used the same tree on consecutive days (N = 3 at both sites). They traveled fast to enter sleeping tree a mean of 160 ± SD 43 min before sunset at Nankang, and a mean of 192 ± SD 40 min before sunset at Banchang. They seldom (Nankang: 14%, N = 183 observations; Banchang: 25%, N = 548 observations) defecated in sleeping trees. They slept at sites with more tall and large trees and preferred to sleep on tall trees in the site. They slept on branches of small diameter and closer to tree tops. Our study suggests that antipredation plays an important role in skywalker hoolock gibbons’ sleeping tree selection and sleeping behavior. In addition, our data suggest potential effects of habitat degradation on gibbons’ sleeping behavior. Tall trees are especially important for gibbons in degraded forest and should be protected.     

Old trees contribute bio-available nitrogen through canopy bryophytes

Symbiotic cyanobacteria??bryophyte associations on the forest floor are shown to contribute significantly to stand-level nitrogen budgets through the process of biological nitrogen fixation (BNF), but few studies have considered the role of canopy bryophytes. Given the high biomass of epiphytic bryophytes in many tree species of the North American temperate rain forest, we suggest that canopy bryophytes may contribute substantially to stand-level N dynamics. We confirm the presence of cyanobacteria and measure rates of BNF at three heights (0, 15 and 30 m) in Sitka spruce trees across three watershed estuaries of Clayoquot Sound, British Columbia, Canada. This study is the first to report BNF by cyanobacteria associated with epiphytic and forest floor bryophytes in the coastal temperate rain forest of North America. Cyanobacteria density was significantly greater in epiphytic bryophytes compared to mosses on the forest floor, and rates of BNF were highest at 30 m in the canopy. The majority of total stand-level BNF (0.76 kg N · ha^-1 · yr^-1) occurs in the canopy, rather than on the forest floor (0.26 kg N · ha^-1 · yr^-1). We suggest that BNF by cyanobacterial-bryophyte associations in the canopy of coastal temperate rain forests is a unique source of ecosystem N, which is dependent on large, old trees with high epiphytic bryophyte biomass.     

Impacts of El Niño related drought and forest fires on sun bear fruit resources in lowland dipterocarp forest of East Borneo

Droughts and forest fires, induced by the El Niño/Southern Oscillation (ENSO) event, have increased considerably over the last decades affecting millions of hectares of rainforest. We investigated the effects of the 1997–1998 forest fires and drought, associated with an exceptionally severe ENSO event, on fruit species important in the diet of Malayan sun bears (Helarctos malayanus) in lowland dipterocarp forest, East Kalimantan, Indonesian Borneo. Densities of sun bear fruit trees (≥10 cm DBH) were reduced by ～80%, from 167±41 (SD) fruit trees ha^?1 in unburned forest to 37±18 fruit trees ha^?1 in burned forest. Densities of hemi-epiphytic figs, one of the main fallback resources for sun bears during periods of food scarcity, declined by 95% in burned forest. Species diversity of sun bear food trees decreased by 44% in burned forest. Drought also affected sun bear fruit trees in unburned primary forest, with elevated mortality rates for the duration of 2 years, returning to levels reported as normal in region in the third year after the ENSO event. Mortality in unburned forest near the burn-edge was higher (25±5% of trees ≥10 cm DBH dead) than in the forest interior (14±5% of trees), indicating possible edge effects. Combined effects of fire and drought in burned primary forest resulted in an overall tree mortality of 78±11% (≥10 cm DBH) 33 months after the fire event. Disturbance due to fires has resulted in a serious decline of fruit resources for sun bears and, due to the scale of fire damage, in a serious decline of prime sun bear habitat. Recovery of sun bear populations in these burned-over forests will depend on regeneration of the forest, its future species composition, and efforts to prevent subsequent fire events.     

Characterising the effects of high ammonia emission on the growth of Norway spruce

This paper studies the effects of high ammonia emissions and nitrogen deposition on tree growth. Wood cores of 125 Norway spruces were analysed along a transect (800 m) from forest edge to forest interior. The forest edge was exposed to a strong ammonia emission source (poultry farm, less than 50 m). Atmospheric nitrogen bulk deposition, ammonia concentration, soil solution concentration, soil nutrient content, foliar N concentration and C/N ratio of the humus layer were measured at five plots along the transect. The tree growth increment of two clusters of trees close to the forest edge and forest interior was compared. The results indicate extremely high nitrogen load at the forest edge. All nitrogen variables show an `edge effect' with increasing values from forest interior to the forest edge. The growth of nitrogen-influenced spruce trees generally increases. Trees with excessive long-term nitrogen load appear to loose increment after a long-term nitrogen impact. The average gain of increment at the edge appears to be related to the amount of nitrogen emission.     

Disturbance dynamics and history of an old-growth subalpine fir (Abies fargesii) forest in central China

Disturbance history of an old-growth subalpine fir (Abies fargesii) forest in the Shennongjia Mountains of central China was reconstructed using dendroecological methods. Increment cores were extracted from 468 trees within six 100 m × 50 m permanent transects distributed across the old-growth subalpine fir forest of 300 ha. Growth patterns of 299 fir cores were examined for abrupt increases in radial growth to indicate formation of past canopy gaps and for rapid early radial growth to indicate establishment in past canopy gaps. The results showed that 70.8 % of the canopy fir trees experienced an average of 0.78 (ranging from 0 to 2) major release event for an average of 15.8 (ranging from 10 to 24) years, and an average of 1.94 (ranging from 0 to 3) moderate release events for an average of 25.6 (ranging from 10 to 36) years before they reached canopy. Recruitment pulse of trees coincided temporally with the peak of disturbance rate from the 1900s to the 1910s, suggesting occurrence of intense disturbance events during the time period. Radial growth analyses indicated that a history with small-scale disturbance events has resulted in the formation of the old-growth subalpine fir forest, and stand-replacing disturbances might not be necessary for the development of the forest. This study provides strong evidence that there are substantial variations in the disturbance severity and frequency over time. Most disturbance events might rather cause treefall gaps than clear large areas of forest at once. Thus, the old-growth subalpine fir forest experienced frequent gap-scale disturbances and few large-scale disturbances in its development history.     

GLiMMPS: robust statistical model for regulatory variation of alternative splicing using RNA-seq data

To characterize the genetic variation of alternative splicing, we develop GLiMMPS, a robust statistical method for detecting splicing quantitative trait loci (sQTLs) from RNA-seq data. GLiMMPS takes into account the individual variation in sequencing coverage and the noise prevalent in RNA-seq data. Analyses of simulated and real RNA-seq datasets demonstrate that GLiMMPS outperforms competing statistical models. Quantitative RT-PCR tests of 26 randomly selected GLiMMPS sQTLs yielded a validation rate of 100%. As population-scale RNA-seq studies become increasingly affordable and popular, GLiMMPS provides a useful tool for elucidating the genetic variation of alternative splicing in humans and model organisms.