NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulatory elements, the discovery of motifs and their combinatorial patterns from these CNN models has remained difficult. We show that the main difficulty is due to the problem of multifaceted neurons which respond to multiple types of sequence patterns. Since existing interpretation methods were mainly designed to visualize the class of sequences that can activate the neuron, the resulting visualization will correspond to a mixture of patterns. Such a mixture is usually difficult to interpret without resolving the mixed patterns. We propose the NeuronMotif algorithm to interpret such neurons. Given any convolutional neuron (CN) in the network, NeuronMotif first generates a large sample of sequences capable of activating the CN, which typically consists of a mixture of patterns. Then, the sequences are "demixed" in a layer-wise manner by backward clustering of the feature maps of the involved convolutional layers. NeuronMotif can output the sequence motifs, and the syntax rules governing their combinations are depicted by position weight matrices organized in tree structures. Compared to existing methods, the motifs found by NeuronMotif have more matches to known motifs in the JASPAR database. The higher-order patterns uncovered for deep CNs are supported by the literature and ATAC-seq footprinting. Overall, NeuronMotif enables the deciphering of cis-regulatory codes from deep CNs and enhances the utility of CNN in genome interpretation.

The loss of heterochromatin is associated with multiscale three-dimensional genome reorganization and aberrant transcription during cellular senescence.

Heterochromatin remodeling is critical for various cell processes. In particular, the "loss of heterochromatin" phenotype in cellular senescence is associated with the process of aging and age-related disorders. Although biological processes of senescent cells, including senescence-associated heterochromatin foci (SAHF) formation, chromosome compaction, and redistribution of key proteins, have been closely associated with high-order chromatin structure, the relationship between the high-order chromatin reorganization and the loss of heterochromatin phenotype during senescence has not been fully understood. By using senescent and deep senescent fibroblasts induced by DNA damage harboring the "loss of heterochromatin" phenotype, we observed progressive 3D reorganization of heterochromatin during senescence. Facultative and constitutive heterochromatin marked by H3K27me3 and H3K9me3, respectively, show different alterations. Facultative heterochromatin tends to switch from the repressive B-compartment to the active A-compartment, whereas constitutive heterochromatin shows no significant changes at the compartment level but enhanced interactions between themselves. Both types of heterochromatin show increased chromatin accessibility and gene expression leakage during senescence. Furthermore, increased chromatin accessibility in potential CTCF binding sites accompanies the establishment of novel loops in constitutive heterochromatin. Finally, we also observed aberrant expression of repetitive elements, including LTR (long terminal repeat) and satellite classes. Overall, facultative and constitutive heterochromatin show both similar and distinct multiscale alterations in the 3D map, chromatin accessibility, and gene expression leakage. This study provides an epigenomic map of heterochromatin reorganization during senescence.

Decoding multilevel relationships with the human tissue-cell-molecule network.

Understanding the biological functions of molecules in specific human tissues or cell types is crucial for gaining insights into human physiology and disease. To address this issue, it is essential to systematically uncover associations among multilevel elements consisting of disease phenotypes, tissues, cell types and molecules, which could pose a challenge because of their heterogeneity and incompleteness. To address this challenge, we describe a new methodological framework, called Graph Local InfoMax (GLIM), based on a human multilevel network (HMLN) that we established by introducing multiple tissues and cell types on top of molecular networks. GLIM can systematically mine the potential relationships between multilevel elements by embedding the features of the HMLN through contrastive learning. Our simulation results demonstrated that GLIM consistently outperforms other state-of-the-art algorithms in disease gene prediction. Moreover, GLIM was also successfully used to infer cell markers and rewire intercellular and molecular interactions in the context of specific tissues or diseases. As a typical case, the tissue-cell-molecule network underlying gastritis and gastric cancer was first uncovered by GLIM, providing systematic insights into the mechanism underlying the occurrence and development of gastric cancer. Overall, our constructed methodological framework has the potential to systematically uncover complex disease mechanisms and mine high-quality relationships among phenotypical, tissue, cellular and molecular elements.

Evaluating methylation of human ribosomal DNA at each CpG site reveals its utility for cancer detection using cell-free DNA.

Ribosomal deoxyribonucleic acid (DNA) (rDNA) repeats are tandemly located on five acrocentric chromosomes with up to hundreds of copies in the human genome. DNA methylation, the most well-studied epigenetic mechanism, has been characterized for most genomic regions across various biological contexts. However, rDNA methylation patterns remain largely unexplored due to the repetitive structure. In this study, we designed a specific mapping strategy to investigate rDNA methylation patterns at each CpG site across various physiological and pathological processes. We found that CpG sites on rDNA could be categorized into two types. One is within or adjacent to transcribed regions; the other is distal to transcribed regions. The former shows highly variable methylation levels across samples, while the latter shows stable high methylation levels in normal tissues but severe hypomethylation in tumors. We further showed that rDNA methylation profiles in plasma cell-free DNA could be used as a biomarker for cancer detection. It shows good performances on public datasets, including colorectal cancer [area under the curve (AUC) = 0.85], lung cancer (AUC = 0.84), hepatocellular carcinoma (AUC = 0.91) and in-house generated hepatocellular carcinoma dataset (AUC = 0.96) even at low genome coverage (<1×). Taken together, these findings broaden our understanding of rDNA regulation and suggest the potential utility of rDNA methylation features as disease biomarkers.

Early evolution of Anamorphidae (Coleoptera: Coccinelloidea): the oldest known anamorphid beetles from Upper Cretaceous amber of northern Myanmar and the first report of potential glandular pores in the family.

In order to place newly discovered fossil taxa (Palaeosymbius gen. nov. with P. groehni and P. mesozoicus spp. nov.) from the mid-Cretaceous amber from northern Myanmar, we investigated the relations of extant and extinct lineages of the coccinellid group of Coccinelloidea with emphasis on the family Anamorphidae. We assembled a taxonomic sampling of 34 taxa, including 15 genera and 19 species of Anamorphidae, the most comprehensive sampling of Anamorphidae at the generic level in a phylogenetic analysis. A morphological dataset of 47 characters was built as well as a molecular alignment of 7140 bp including fragments of eight genes (12S, 16S, 18S, 28S, COI, COII, H3 and CAD). Five anamorphid and one endomychid species were sequenced for the first time and added to the dataset. We performed parsimony-based analysis of the morphological dataset and Bayesian inference analysis of the combined matrix (morphological plus molecular data). Our results confirm that Palaeosymbius belongs to Anamorphidae and represents the oldest known member of this family so far. Among Anamorphidae, Symbiotes (with extant and known Eocene species) was recovered as the most probable closest relative of Palaeosymbius. Our morphological studies additionally revealed the presence of probable glandular openings in the anterolateral corners of the pronotal margins in Asymbius sp. and Anamorphus sp., representing the first report of secretory openings in the family Anamorphidae. Similar openings are found in other cucujiform beetles such as Cryptophagidae and Boganiidae with possible defensive purposes.

Phylogenomics of weevils revisited: data curation and modelling compositional heterogeneity.

Weevils represent one of the most prolific radiations of beetles and the most diverse group of herbivores on land. The phylogeny of weevils (Curculionoidea) has received extensive attention, and a largely satisfactory framework for their interfamilial relationships has been established. However, a recent phylogenomic study of Curculionoidea based on anchored hybrid enrichment (AHE) data yielded an abnormal placement for the family Belidae (strongly supported as sister to Nemonychidae + Anthribidae). Here we reanalyse the genome-scale AHE data for Curculionoidea using various models of molecular evolution and data filtering methods to mitigate anticipated systematic errors and reduce compositional heterogeneity. When analysed with the infinite mixture model CAT-GTR or using appropriately filtered datasets, Belidae are always recovered as sister to the clade (Attelabidae, (Caridae, (Brentidae, Curculionidae))), which is congruent with studies based on morphology and other sources of molecular data. Although the relationships of the 'higher Curculionidae' remain challenging to resolve, we provide a consistent and robust backbone phylogeny of weevils. Our extensive analyses emphasize the significance of data curation and modelling across-site compositional heterogeneity in phylogenomic studies.

Cretophengodidae, a new Cretaceous beetle family, sheds light on the evolution of bioluminescence.

Bioluminescent beetles of the superfamily Elateroidea (fireflies, fire beetles, glow-worms) are the most speciose group of terrestrial light-producing animals. The evolution of bioluminescence in elateroids is associated with unusual morphological modifications, such as soft-bodiedness and neoteny, but the fragmentary nature of the fossil record discloses little about the origin of these adaptations. We report the discovery of a new bioluminescent elateroid beetle family from the mid-Cretaceous of northern Myanmar (ca 99 Ma), Cretophengodidae fam. nov. Cretophengodes azari gen. et sp. nov. belongs to the bioluminescent lampyroid clade, and would appear to represent a transitional fossil linking the soft-bodied Phengodidae + Rhagophthalmidae clade and hard-bodied elateroids. The fossil male possesses a light organ on the abdomen which presumably served a defensive function, documenting a Cretaceous radiation of bioluminescent beetles coinciding with the diversification of major insectivore groups such as frogs and stem-group birds. The discovery adds a key branch to the elateroid tree of life and sheds light on the evolution of soft-bodiedness and the historical biogeography of elateroid beetles.

Dynamic transcriptome profiling in DNA damage-induced cellular senescence and transient cell-cycle arrest.

Cellular senescence is an irreversible cell cycle arrest process associated with aging and senescence-related diseases. DNA damage is an extensive feature of cellular senescence and aging. Different levels of DNA damage could lead to cellular senescence or transient cell-cycle arrest, but the genetic regulatory mechanisms determining cell fate are still not clear. In this work, high-resolution time course analysis of gene expression in DNA damage-induced cellular senescence and transient cell-cycle arrest was used to explore the transcriptomic differences between different cell fates after DNA damage response and to investigate the key regulatory factors affecting senescent cell fates. Pathways such as the cell cycle, DNA repair and cholesterol metabolism showed characteristic differential response. A number of key transcription factors were predicted to regulating cell cycle and DNA repair. Our study provides genome-wide insights into the molecular-level mechanisms of senescent cell fate decisions after DNA damage response.

Role of cardioprotective agents on chemotherapy-induced heart failure: A systematic review and network meta-analysis of randomized controlled trials.

BACKGROUND: Although previous clinical randomized controlled trials (RCTs) have tested the effect of a variety of cardioprotective agents on cancer therapy-induced cardiotoxicity, the number of included patients was limited, and the results remained controversial. In this study, we aimed to evaluate the preventive or therapeutic effects of cardioprotective agents on heart failure (HF) caused by cardiotoxicity induced by cancer therapy. METHODS: We included trials of the following cardioprotective drugs: Angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, beta-blockers, aldosterone antagonists and stains. We extracted the relevant information with predefined data extraction forms, and assessed the risk of bias in randomized controlled trials with the Cochrane risk of bias tool. The primary outcome was the left ventricular ejection fraction of patients after chemotherapy. We used the random-effects model to carry out pair-wise meta-analysis, and then carry out the random-effects network meta-analysis within the Bayesian framework. RESULTS: Twenty-two relevant RCTs, including 1 916 patients (79.6 % women) with a mean age of 48.4 years, were included. Based on the evaluation of all drug species from 20 studies (26 comparisons), the analysis found that 4 therapies, aldosterone antagonists (MD, 12.78 [95 % CI, 2.87-22.69] and MD, 13.75 [95 % CI, 2.21-25.30]), ACEIs (MD, 6.79 [95 % CI, 2.11-11.48] and MD, 7.76 [95 % CI, 2.64-12.88]), statin (MD, 8.35 [95 % CI, 1.11-15.59]), and beta-blockers (MD, 4.00 [95 % CI, 0.87-7.14]), had a higher efficacy than placebo and/or control, suggesting an LVEF protective effect of cardioprotective therapy. In the analysis classified by single drug or drug combination, based on 22 studies (31 comparisons), spironolactone (MD, 12.77 [95 % CI, 1.76-23.79] and MD, 14.62 [95 % CI, 1.70-27.55]), a combination of candesartan and carvedilol (MD, 12.40 [95 % CI, 0.99-23.81]), enalapril (MD, 7.35 [95 % CI, 1.16-13.54] and MD, 9.20 [95 % CI, 2.61-15.79]), and statin (MD, 8.36 [95 % CI, 0.36-16.36]) showed significant benefits in protecting left ventricular (LV) systolic function compared with the placebo and/or control. CONCLUSION: When classified according to drug type, aldosterone antagonists, ACEIs, statins, and beta-blockers could substantially improve the LV systolic function. In the analysis classified by single drug or drug combination, spironolactone, enalapril, and statin have a significant cardioprotective effect. However, ARBs have no cardioprotective effect and fail to improve the LVEF.

Cardiac injury associated with severe disease or ICU admission and death in hospitalized patients with COVID-19: a meta-analysis and systematic review.

BACKGROUND: Cardiac injury is now a common complication of coronavirus disease (COVID-19), but it remains unclear whether cardiac injury-related biomarkers can be independent predictors of mortality and severe disease development or intensive care unit (ICU) admission. METHODS: Two investigators searched the PubMed, EMBASE, Cochrane Library, MEDLINE, Chinese National Knowledge Infrastructure (CNKI), Wanfang, MedRxiv, and ChinaXiv databases for articles published through March 30, 2020. Retrospective studies assessing the relationship between the prognosis of COVID-19 patients and levels of troponin I (TnI) and other cardiac injury biomarkers (creatine kinase [CK], CK myocardial band [CK-MB], lactate dehydrogenase [LDH], and interleukin-6 [IL-6]) were included. The data were extracted independently by two investigators. RESULTS: The analysis included 23 studies with 4631 total individuals. The proportions of severe disease, ICU admission, or death among patients with non-elevated TnI (or troponin T [TnT]), and those with elevated TnI (or TnT) were 12.0% and 64.5%, 11.8% and 56.0%, and 8.2% and. 59.3%, respectively. Patients with elevated TnI levels had significantly higher risks of severe disease, ICU admission, and death (RR 5.57, 95% CI 3.04 to 10.22, P < 0.001; RR 6.20, 95% CI 2.52 to 15.29, P < 0.001; RR 5.64, 95% CI 2.69 to 11.83, P < 0.001). Patients with an elevated CK level were at significantly increased risk of severe disease or ICU admission (RR 1.98, 95% CI 1.50 to 2.61, P < 0.001). Patients with elevated CK-MB levels were at a higher risk of developing severe disease or requiring ICU admission (RR 3.24, 95% CI 1.66 to 6.34, P = 0.001). Patients with newly occurring arrhythmias were at higher risk of developing severe disease or requiring ICU admission (RR 13.09, 95% CI 7.00 to 24.47, P < 0.001). An elevated IL-6 level was associated with a higher risk of developing severe disease, requiring ICU admission, or death. CONCLUSIONS: COVID-19 patients with elevated TnI levels are at significantly higher risk of severe disease, ICU admission, and death. Elevated CK, CK-MB, LDH, and IL-6 levels and emerging arrhythmia are associated with the development of severe disease and need for ICU admission, and the mortality is significantly higher in patients with elevated LDH and IL-6 levels.

esATAC: an easy-to-use systematic pipeline for ATAC-seq data analysis.

Summary: ATAC-seq is rapidly emerging as one of the major experimental approaches to probe chromatin accessibility genome-wide. Here, we present 'esATAC', a highly integrated easy-to-use R/Bioconductor package, for systematic ATAC-seq data analysis. It covers essential steps for full analyzing procedure, including raw data processing, quality control and downstream statistical analysis such as peak calling, enrichment analysis and transcription factor footprinting. esATAC supports one command line execution for preset pipelines and provides flexible interfaces for building customized pipelines. Availability and implementation: esATAC package is open source under the GPL-3.0 license. It is implemented in R and C++. Source code and binaries for Linux, MAC OS X and Windows are available through Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/esATAC.html). Supplementary information: Supplementary data are available at Bioinformatics online.

TPL-2 Regulates Macrophage Lipid Metabolism and M2 Differentiation to Control TH2-Mediated Immunopathology.

Persistent TH2 cytokine responses following chronic helminth infections can often lead to the development of tissue pathology and fibrotic scarring. Despite a good understanding of the cellular mechanisms involved in fibrogenesis, there are very few therapeutic options available, highlighting a significant medical need and gap in our understanding of the molecular mechanisms of TH2-mediated immunopathology. In this study, we found that the Map3 kinase, TPL-2 (Map3k8; Cot) regulated TH2-mediated intestinal, hepatic and pulmonary immunopathology following Schistosoma mansoni infection or S. mansoni egg injection. Elevated inflammation, TH2 cell responses and exacerbated fibrosis in Map3k8-/-mice was observed in mice with myeloid cell-specific (LysM) deletion of Map3k8, but not CD4 cell-specific deletion of Map3k8, indicating that TPL-2 regulated myeloid cell function to limit TH2-mediated immunopathology. Transcriptional and metabolic assays of Map3k8-/-M2 macrophages identified that TPL-2 was required for lipolysis, M2 macrophage activation and the expression of a variety of genes involved in immuno-regulatory and pro-fibrotic pathways. Taken together this study identified that TPL-2 regulated TH2-mediated inflammation by supporting lipolysis and M2 macrophage activation, preventing TH2 cell expansion and downstream immunopathology and fibrosis.

Model-guided quantitative analysis of microRNA-mediated regulation on competing endogenous RNAs using a synthetic gene circuit.

Competing endogenous RNAs (ceRNAs) cross-regulate each other at the posttranscriptional level by titrating shared microRNAs (miRNAs). Here, we established a computational model to quantitatively describe a minimum ceRNA network and experimentally validated our model predictions in cultured human cells by using synthetic gene circuits. We demonstrated that the range and strength of ceRNA regulation are largely determined by the relative abundance and the binding strength of miRNA and ceRNAs. We found that a nonreciprocal competing effect between partially and perfectly complementary targets is mainly due to different miRNA loss rates in these two types of regulations. Furthermore, we showed that miRNA-like off targets with high expression levels and strong binding sites significantly diminish the RNA interference efficiency, but the effect caused by high expression levels could be compensated by introducing more small interference RNAs (siRNAs). Thus, our results provided a quantitative understanding of ceRNA cross-regulation via shared miRNA and implied an siRNA design strategy to reduce the siRNA off-target effect in mammalian cells.

Tumor progression locus 2 reduces severe allergic airway inflammation by inhibiting Ccl24 production in dendritic cells.

BACKGROUND: The molecular and cellular pathways driving the pathogenesis of severe asthma are poorly defined. Tumor progression locus 2 (TPL-2) (COT, MAP3K8) kinase activates the MEK1/2-extracellular-signal regulated kinase 1/2 MAP kinase signaling pathway following Toll-like receptor, TNFR1, and IL-1R stimulation. OBJECTIVE: TPL-2 has been widely described as a critical regulator of inflammation, and we sought to investigate the role of TPL-2 in house dust mite (HDM)-mediated allergic airway inflammation. METHODS: A comparative analysis of wild-type and Map3k8-/- mice was conducted. Mixed bone marrow chimeras, conditional knockout mice, and adoptive transfer models were also used. Differential cell counts were performed on the bronchoalveolar lavage fluid, followed by histological analysis of lung sections. Flow cytometry and quantitative PCR was used to measure type 2 cytokines. ELISA was used to assess the production of IgE, type 2 cytokines, and Ccl24. RNA sequencing was used to characterize dendritic cell (DC) transcripts. RESULTS: TPL-2 deficiency led to exacerbated HDM-induced airway allergy, with increased airway and tissue eosinophilia, lung inflammation, and IL-4, IL-5, IL-13, and IgE production. Increased airway allergic responses in Map3k8-/- mice were not due to a cell-intrinsic role for TPL-2 in T cells, B cells, or LysM+ cells but due to a regulatory role for TPL-2 in DCs. TPL-2 inhibited Ccl24 expression in lung DCs, and blockade of Ccl24 prevented the exaggerated airway eosinophilia and lung inflammation in mice given HDM-pulsed Map3k8-/- DCs. CONCLUSIONS: TPL-2 regulates DC-derived Ccl24 production to prevent severe type 2 airway allergy in mice.

Integrating multiple genomic data to predict disease-causing nonsynonymous single nucleotide variants in exome sequencing studies.

Exome sequencing has been widely used in detecting pathogenic nonsynonymous single nucleotide variants (SNVs) for human inherited diseases. However, traditional statistical genetics methods are ineffective in analyzing exome sequencing data, due to such facts as the large number of sequenced variants, the presence of non-negligible fraction of pathogenic rare variants or de novo mutations, and the limited size of affected and normal populations. Indeed, prevalent applications of exome sequencing have been appealing for an effective computational method for identifying causative nonsynonymous SNVs from a large number of sequenced variants. Here, we propose a bioinformatics approach called SPRING (Snv PRioritization via the INtegration of Genomic data) for identifying pathogenic nonsynonymous SNVs for a given query disease. Based on six functional effect scores calculated by existing methods (SIFT, PolyPhen2, LRT, MutationTaster, GERP and PhyloP) and five association scores derived from a variety of genomic data sources (gene ontology, protein-protein interactions, protein sequences, protein domain annotations and gene pathway annotations), SPRING calculates the statistical significance that an SNV is causative for a query disease and hence provides a means of prioritizing candidate SNVs. With a series of comprehensive validation experiments, we demonstrate that SPRING is valid for diseases whose genetic bases are either partly known or completely unknown and effective for diseases with a variety of inheritance styles. In applications of our method to real exome sequencing data sets, we show the capability of SPRING in detecting causative de novo mutations for autism, epileptic encephalopathies and intellectual disability. We further provide an online service, the standalone software and genome-wide predictions of causative SNVs for 5,080 diseases at http://bioinfo.au.tsinghua.edu.cn/spring.

CRISPR-ERA: a comprehensive design tool for CRISPR-mediated gene editing, repression and activation.

UNLABELLED: The CRISPR/Cas9 system was recently developed as a powerful and flexible technology for targeted genome engineering, including genome editing (altering the genetic sequence) and gene regulation (without altering the genetic sequence). These applications require the design of single guide RNAs (sgRNAs) that are efficient and specific. However, this remains challenging, as it requires the consideration of many criteria. Several sgRNA design tools have been developed for gene editing, but currently there is no tool for the design of sgRNAs for gene regulation. With accumulating experimental data on the use of CRISPR/Cas9 for gene editing and regulation, we implement a comprehensive computational tool based on a set of sgRNA design rules summarized from these published reports. We report a genome-wide sgRNA design tool and provide an online website for predicting sgRNAs that are efficient and specific. We name the tool CRISPR-ERA, for clustered regularly interspaced short palindromic repeat-mediated editing, repression, and activation (ERA). AVAILABILITY AND IMPLEMENTATION: http://CRISPR-ERA.stanford.edu. CONTACT: stanley.qi@stanford.edu or xwwang@tsinghua.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrated omics study delineates the dynamics of lipid droplets in Rhodococcus opacus PD630.

Rhodococcus opacus strain PD630 (R. opacus PD630), is an oleaginous bacterium, and also is one of few prokaryotic organisms that contain lipid droplets (LDs). LD is an important organelle for lipid storage but also intercellular communication regarding energy metabolism, and yet is a poorly understood cellular organelle. To understand the dynamics of LD using a simple model organism, we conducted a series of comprehensive omics studies of R. opacus PD630 including complete genome, transcriptome and proteome analysis. The genome of R. opacus PD630 encodes 8947 genes that are significantly enriched in the lipid transport, synthesis and metabolic, indicating a super ability of carbon source biosynthesis and catabolism. The comparative transcriptome analysis from three culture conditions revealed the landscape of gene-altered expressions responsible for lipid accumulation. The LD proteomes further identified the proteins that mediate lipid synthesis, storage and other biological functions. Integrating these three omics uncovered 177 proteins that may be involved in lipid metabolism and LD dynamics. A LD structure-like protein LPD06283 was further verified to affect the LD morphology. Our omics studies provide not only a first integrated omics study of prokaryotic LD organelle, but also a systematic platform for facilitating further prokaryotic LD research and biofuel development.

Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method.

BACKGROUND: MicroRNAs (miRNAs) are a class of endogenous small regulatory RNAs. Identifications of the dys-regulated or perturbed miRNAs and their key target genes are important for understanding the regulatory networks associated with the studied cellular processes. Several computational methods have been developed to infer the perturbed miRNA regulatory networks by integrating genome-wide gene expression data and sequence-based miRNA-target predictions. However, most of them only use the expression information of the miRNA direct targets, rarely considering the secondary effects of miRNA perturbation on the global gene regulatory networks. RESULTS: We proposed a network propagation based method to infer the perturbed miRNAs and their key target genes by integrating gene expressions and global gene regulatory network information. The method used random walk with restart in gene regulatory networks to model the network effects of the miRNA perturbation. Then, it evaluated the significance of the correlation between the network effects of the miRNA perturbation and the gene differential expression levels with a forward searching strategy. Results show that our method outperformed several compared methods in rediscovering the experimentally perturbed miRNAs in cancer cell lines. Then, we applied it on a gene expression dataset of colorectal cancer clinical patient samples and inferred the perturbed miRNA regulatory networks of colorectal cancer, including several known oncogenic or tumor-suppressive miRNAs, such as miR-17, miR-26 and miR-145. CONCLUSIONS: Our network propagation based method takes advantage of the network effect of the miRNA perturbation on its target genes. It is a useful approach to infer the perturbed miRNAs and their key target genes associated with the studied biological processes using gene expression data.

A new fossil species of the extant genus Vicelva from mid-Cretaceous Kachin amber (Coleoptera: Staphylinidae).

A new species of the extant staphylinid genus Vicelva Moore & Legner, V. rasilis sp. nov., is reported from mid-Cretaceous Kachin amber of northern Myanmar. Vicelva rasilis is distinguishable from extant members of Vicelva by the smoother dorsal surface of head, pronotum and elytra, less prominent median projection of clypeus, unnotched mesal edge of mandibles, semiglabrous antennomere 6, and longer tarsomere 1. The pollen-containing coprolite attached to the beetle and the crystals within the beetle body provide valuable information about the biology and taphonomy of the fossil.

An enigmatic Cretaceous beetle with possible affinity to Erotylidae (Coleoptera: Cucujiformia).

The morphology of beetles of the recently defined superfamilies Erotyloidea, Nitiduloidea and Cucujoidea is varied. Determining the systematic positions of Mesozoic fossils within these groups can often be challenging. Here we describe and illustrate a puzzling cucujiform beetle, Isocryptophilus exilipunctus Li & Cai gen. & sp. nov., based on an individual from mid-Cretaceous Burmese amber. While we cannot definitively pinpoint the exact phylogenetic position of Isocryptophilus, its possible affinity to Erotylidae is discussed in light of our phylogenetic analyses. A broader-sampled morphological matrix, coupled with a robust molecular phylogeny of these groups, will be promising for clarifying the systematic placement of the fossil.