Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.

Hyperactive ribosome biogenesis (RiboSis) fuels unrestricted cell proliferation, whereas genomic hallmarks and therapeutic targets of RiboSis in cancers remain elusive, and efficient approaches to quantify RiboSis activity are still limited. Here, we have established an in silico approach to conveniently score RiboSis activity based on individual transcriptome data. By employing this novel approach and RNA-seq data of 14 645 samples from TCGA/GTEx dataset and 917 294 single-cell expression profiles across 13 cancer types, we observed the elevated activity of RiboSis in malignant cells of various human cancers, and high risk of severe outcomes in patients with high RiboSis activity. Our mining of pan-cancer multi-omics data characterized numerous molecular alterations of RiboSis, and unveiled the predominant somatic alteration in RiboSis genes was copy number variation. A total of 128 RiboSis genes, including EXOSC4, BOP1, RPLP0P6 and UTP23, were identified as potential therapeutic targets. Interestingly, we observed that the activity of RiboSis was associated with TP53 mutations, and hyperactive RiboSis was associated with poor outcomes in lung cancer patients without TP53 mutations, highlighting the importance of considering TP53 mutations during therapy by impairing RiboSis. Moreover, we predicted 23 compounds, including methotrexate and CX-5461, associated with the expression signature of RiboSis genes. The current study generates a comprehensive blueprint of molecular alterations in RiboSis genes across cancers, which provides a valuable resource for RiboSis-based anti-tumor therapy.

An updated overview of experimental and computational approaches to identify non-canonical DNA/RNA structures with emphasis on G-quadruplexes and R-loops.

Multiple types of non-canonical nucleic acid structures play essential roles in DNA recombination and replication, transcription, and genomic instability and have been associated with several human diseases. Thus, an increasing number of experimental and bioinformatics methods have been developed to identify these structures. To date, most reviews have focused on the features of non-canonical DNA/RNA structure formation, experimental approaches to mapping these structures, and the association of these structures with diseases. In addition, two reviews of computational algorithms for the prediction of non-canonical nucleic acid structures have been published. One of these reviews focused only on computational approaches for G4 detection until 2020. The other mainly summarized the computational tools for predicting cruciform, H-DNA and Z-DNA, in which the algorithms discussed were published before 2012. Since then, several experimental and computational methods have been developed. However, a systematic review including the conformation, sequencing mapping methods and computational prediction strategies for these structures has not yet been published. The purpose of this review is to provide an updated overview of conformation, current sequencing technologies and computational identification methods for non-canonical nucleic acid structures, as well as their strengths and weaknesses. We expect that this review will aid in understanding how these structures are characterised and how they contribute to related biological processes and diseases.

Comprehensive evaluation of computational methods for predicting cancer driver genes.

Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein-protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http://159.226.67.237/sun/cancer_driver/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.

A new approach to decode DNA methylome and genomic variants simultaneously from double strand bisulfite sequencing.

Genetic and epigenetic contributions to various diseases and biological processes have been well-recognized. However, simultaneous identification of single-nucleotide variants (SNVs) and DNA methylation levels from traditional bisulfite sequencing data is still challenging. Here, we develop double strand bisulfite sequencing (DSBS) for genome-wide accurate identification of SNVs and DNA methylation simultaneously at a single-base resolution by using one dataset. Locking Watson and Crick strand together by hairpin adapter followed by bisulfite treatment and massive parallel sequencing, DSBS simultaneously sequences the bisulfite-converted Watson and Crick strand in one paired-end read, eliminating the strand bias of bisulfite sequencing data. Mutual correction of read1 and read2 can estimate the amplification and sequencing errors, and enables our developed computational pipeline, DSBS Analyzer (https://github.com/tianguolangzi/DSBS), to accurately identify SNV and DNA methylation. Additionally, using DSBS, we provide a genome-wide hemimethylation landscape in the human cells, and reveal that the density of DNA hemimethylation sites in promoter region and CpG island is lower than that in other genomic regions. The cost-effective new approach, which decodes DNA methylome and genomic variants simultaneously, will facilitate more comprehensive studies on numerous diseases and biological processes driven by both genetic and epigenetic variations.

KRAS status predicted by pretreatment MRI radiomics was associated with lung metastasis in locally advanced rectal cancer patients.

BACKGROUND: Mutated KRAS may indicate an invasive nature and predict prognosis in locally advanced rectal cancer (LARC). We aimed to establish a radiomic model using pretreatment T2W MRIs to predict KRAS status and explore the association between the KRAS status or model predictions and lung metastasis. METHODS: In this retrospective multicentre study, LARC patients from two institutions between January 2012 and January 2019 were randomly divided into training and testing cohorts. Least absolute shrinkage and selection operator (LASSO) regression and the support vector machine (SVM) classifier were utilized to select significant radiomic features and establish a prediction model, which was validated by radiomic score distribution and decision curve analysis. The association between the model stratification and lung metastasis was investigated by Cox regression and Kaplan‒Meier survival analysis; the results were compared by the log-rank test. RESULTS: Overall, 103 patients were enrolled (73 and 30 in the training and testing cohorts, respectively). The median follow-up was 38.1 months (interquartile range: 26.9, 49.4). The radiomic model had an area under the curve (AUC) of 0.983 in the training cohort and 0.814 in the testing cohort. Using a cut-off of 0.679 defined by the receiver operating characteristic (ROC) curve, patients with a high radiomic score (RS) had a higher risk for lung metastasis (HR 3.565, 95% CI 1.337, 9.505, p = 0.011), showing similar predictive performances for the mutant and wild-type KRAS groups (HR 3.225, 95% CI 1.249, 8.323, p = 0.016, IDI: 1.08%, p = 0.687; NRI 2.23%, p = 0.766). CONCLUSIONS: We established and validated a radiomic model for predicting KRAS status in LARC. Patients with high RS experienced more lung metastases. The model could noninvasively detect KRAS status and may help individualize clinical decision-making.

OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.

The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, 'Mutation', 'Gene', 'Pathway' and 'Cancer', to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer.

BACKGROUND: To analyse the performance of multicentre pre-treatment MRI-based radiomics (MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment modalities to predict complete response to neoadjuvant (chemo)radiotherapy in locally advanced rectal cancer (LARC). METHODS: Baseline MRI and clinical characteristics with neoadjuvant treatment modalities at four centres were collected. Decision tree, support vector machine and five-fold cross-validation were applied for two non-imaging and three radiomics-based models' development and validation. RESULTS: We finally included 674 patients. Pre-treatment CEA, T stage, and histologic grade were selected to generate two non-imaging models: C model (clinical baseline characteristics alone) and CT model (clinical baseline characteristics combining neoadjuvant treatment modalities). The prediction performance of both non-imaging models were poor. The MBR signatures comprising 30 selected radiomics features, the MBR signatures combining clinical baseline characteristics (CMBR), and the CMBR incorporating neoadjuvant treatment modalities (CTMBR) all showed good discrimination with mean AUCs of 0.7835, 0.7871 and 0.7916 in validation sets, respectively. The three radiomics-based models had insignificant discrimination in performance. CONCLUSIONS: The performance of the radiomics-based models were superior to the non-imaging models. MBR signatures seemed to reflect LARC's true nature more accurately than clinical parameters and helped identify patients who can undergo organ preservation strategies.

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

Genomic analysis unveils mechanisms of northward invasion and signatures of plateau adaptation in the Asian house rat.

The Asian house rat (AHR), Rattus tanezumi, has recently invaded the northern half of China. The AHR is a highly adaptive rat species that has also successfully conquered the Qinghai-Tibet Plateau (QTP) and replaced the brown rat (BR), R. norvegicus, at the edge of the QTP. Here, we assembled a draft genome of the AHR and explored the mechanisms of its northward invasion and the genetic basis underlying plateau adaptation in this species. Population genomic analyses revealed that the northwardly invasive AHRs consisted of two independent and genetically distinct populations which might result from multiple independent primary invasion events. One invasive population exhibited reduced genetic diversity and distinct population structure compared with its source population, while the other displayed preserved genetic polymorphisms and little genetic differentiation from its source population. Genes involved in G-protein coupled receptors and carbohydrate metabolism may contribute to the local adaptation of northern AHRs. In particular, RTN4 was identified as a key gene for AHRs in the QTP that favours adaptation to high-altitude hypoxia. Coincidently, the physiological performance and transcriptome profiles of hypoxia-exposed rats both showed better hypoxia adaptation in AHRs than in BRs that failed to colonize the heart of the QTP, which may have facilitated the replacement of the BR population by the invading AHRs at the edge of the QTP. This study provides profound insights into the multiple origins of the northwardly invasive AHR and the great tolerance to hypoxia in this species.

The clock-controlled chemokine contributes to neuroinflammation-induced depression.

The circadian rhythm plays a central role in immune function, and its disruption has been closely linked to the etiology of depression. However, the mechanisms underlying the association between depression and circadian rhythm remain unclear. We found that mice deficient of Per2, a central clock component of circadian output, were resilient to neuroinflammation-induced depressive behavior. After repeated central lipopolysaccharide (LPS) injections, MCP-1, MIP-1ß, and RANTES increased in wild type (WT) but not in Per2-deficient mice. In addition, intracerebroventricular injection of RANTES resulted in depression-like behavior, and Met-RANTES, a CCR5 antagonist, could reverse depression-like behavior induced by LPS treatments. These results indicated that the Per2 gene contributes to depression via chemokines, especially RANTES. Furthermore, BMAL1 expression decreased in LPS-treated Per2-deficient mice and BMAL1 could bind to the promoter of Rantes, indicating clock gene can act as a regulator for neuroinflammation. In conclusion, Rantes, a clock-controlled gene (CCG), is involved in clock-immunological mechanisms underlying the effects of Per2 on neuroinflammation-induced depression-like behavior.

Population genomics reveal rapid genetic differentiation in a recently invasive population of Rattus norvegicus.

BACKGROUND: Invasive species bring a serious effect on local biodiversity, ecosystems, and even human health and safety. Although the genetic signatures of historical range expansions have been explored in an array of species, the genetic consequences of contemporary range expansions have received little attention, especially in mammal species. In this study, we used whole-genome sequencing to explore the rapid genetic change and introduction history of a newly invasive brown rat (Rattus norvegicus) population which invaded Xinjiang Province, China in the late 1970s. RESULTS: Bayesian clustering analysis, principal components analysis, and phylogenetic analysis all showed clear genetic differentiation between newly introduced and native rat populations. Reduced genetic diversity and high linkage disequilibrium suggested a severe population bottleneck in this colonization event. Results of TreeMix analyses revealed that the introduced rats were derived from an adjacent population in geographic region (Northwest China). Demographic analysis indicated that a severe bottleneck occurred in XJ population after the split off from the source population, and the divergence of XJ population might have started before the invasion of XJ. Moreover, we detected 42 protein-coding genes with allele frequency shifts throughout the genome for XJ rats and they were mainly associated with lipid metabolism and immunity, which could be seen as a prelude to future selection analyses in the novel environment of XJ. CONCLUSIONS: This study presents the first genomic evidence on genetic differentiation which developed rapidly, and deepens the understanding of invasion history and evolutionary processes of this newly introduced rat population. This would add to our understanding of how invasive species become established and aid strategies aimed at the management of this notorious pest that have spread around the world with humans.

OncoBase: a platform for decoding regulatory somatic mutations in human cancers.

Whole-exome and whole-genome sequencing have revealed millions of somatic mutations associated with different human cancers, and the vast majority of them are located outside of coding sequences, making it challenging to directly interpret their functional effects. With the rapid advances in high-throughput sequencing technologies, genome-scale long-range chromatin interactions were detected, and distal target genes of regulatory elements were determined using three-dimensional (3D) chromatin looping. Herein, we present OncoBase (http://www.oncobase.biols.ac.cn/), an integrated database for annotating 81 385 242 somatic mutations in 68 cancer types from more than 120 cancer projects by exploring their roles in distal interactions between target genes and regulatory elements. OncoBase integrates local chromatin signatures, 3D chromatin interactions in different cell types and reconstruction of enhancer-target networks using state-of-the-art algorithms. It employs informative visualization tools to display the integrated local and 3D chromatin signatures and effects of somatic mutations on regulatory elements. Enhancer-promoter interactions estimated from chromatin interactions are integrated into a network diffusion system that quantitatively prioritizes somatic mutations and target genes from a large pool. Thus, OncoBase is a useful resource for the functional annotation of regulatory noncoding regions and systematically benchmarking the regulatory effects of embedded noncoding somatic mutations in human carcinogenesis.

EpiDenovo: a platform for linking regulatory de novo mutations to developmental epigenetics and diseases.

De novo mutations (DNMs) have been shown to be a major cause of severe early-onset genetic disorders such as autism spectrum disorder and intellectual disability. Over one million DNMs have been identified in developmental disorders by next generation sequencing, but linking these DNMs to the genes that they impact remains a challenge, as the majority of them are embedded in non-coding regions. As most developmental diseases occur in the early stages of development or during childhood, it is crucial to clarify the details of epigenetic regulation in early development in order to interpret the mechanisms underlying developmental disorders. Here, we develop EpiDenovo, a database that is freely available at http://www.epidenovo.biols.ac.cn/, and which provides the associations between embryonic epigenomes and DNMs in developmental disorders, including several neuropsychiatric disorders and congenital heart disease. EpiDenovo provides an easy-to-use web interface allowing users rapidly to find the epigenetic signatures of DNMs and the expression patterns of the genes that they regulate during embryonic development. In summary, EpiDenovo is a useful resource for selecting candidate genes for further functional studies in embryonic development, and for investigating regulatory DNMs as well as other genetic variants causing or underlying developmental disorders.

VarCards: an integrated genetic and clinical database for coding variants in the human genome.

A growing number of genomic tools and databases were developed to facilitate the interpretation of genomic variants, particularly in coding regions. However, these tools are separately available in different online websites or databases, making it challenging for general clinicians, geneticists and biologists to obtain the first-hand information regarding some particular variants and genes of interest. Starting with coding regions and splice sties, we artificially generated all possible single nucleotide variants (n = 110 154 363) and cataloged all reported insertion and deletions (n = 1 223 370). We then annotated these variants with respect to functional consequences from more than 60 genomic data sources to develop a database, named VarCards (http://varcards.biols.ac.cn/), by which users can conveniently search, browse and annotate the variant- and gene-level implications of given variants, including the following information: (i) functional effects; (ii) functional consequences through different in silico algorithms; (iii) allele frequencies in different populations; (iv) disease- and phenotype-related knowledge; (v) general meaningful gene-level information; and (vi) drug-gene interactions. As a case study, we successfully employed VarCards in interpretation of de novo mutations in autism spectrum disorders. In conclusion, VarCards provides an intuitive interface of necessary information for researchers to prioritize candidate variations and genes.

CirGRDB: a database for the genome-wide deciphering circadian genes and regulators.

Circadian rhythms govern various kinds of physiological and behavioral functions of the living organisms, and disruptions of the rhythms are highly detrimental to health. Although several databases have been built for circadian genes, a resource for comprehensive post-transcriptional regulatory information of circadian RNAs and expression patterns of disease-related circadian RNAs is still lacking. Here, we developed CirGRDB (http://cirgrdb.biols.ac.cn) by integrating more than 4936 genome-wide assays, with the aim of fulfilling the growing need to understand the rhythms of life. CirGRDB presents a friendly web interface that allows users to search and browse temporal expression patterns of interested genes in 37 human/mouse tissues or cell lines, and three clinical disorders including sleep disorder, aging and tumor. More importantly, eight kinds of potential transcriptional and post-transcriptional regulators involved in the rhythmic expression of the specific genes, including transcription factors, histone modifications, chromatin accessibility, enhancer RNAs, miRNAs, RNA-binding proteins, RNA editing and RNA methylation, can also be retrieved. Furthermore, a regulatory network could be generated based on the regulatory information. In summary, CirGRDB offers a useful repository for exploring disease-related circadian RNAs, and deciphering the transcriptional and post-transcriptional regulation of circadian rhythms.

Genetic landscape of papillary thyroid carcinoma in the Chinese population.

Improvement in the clinical outcome of human cancers requires characterization of the genetic alterations underlying their pathogenesis. Large-scale genomic and transcriptomic characterization of papillary thyroid carcinomas (PTCs) in Western populations has revealed multiple oncogenic drivers which are essential for understanding pathogenic mechanisms of this disease, while, so far, the genetic landscape in Chinese patients with PTC remains uncharacterized. Here, we conducted a large-scale genetic analysis of PTCs from patients in China to determine the mutational landscape of this cancer. By performing targeted DNA amplicon and targeted RNA deep-sequencing, we elucidated the landscape of somatic genetic alterations in 355 Chinese patients with PTC. A total of 88.7% of PTCs were found to harbor at least one candidate oncogenic driver genetic alteration. Among them, around 72.4% of the cases carried BRAF mutations; 2.8% of cases harbored RAS mutations; and 13.8% of cases were characterized with in-frame gene fusions, including seven newly identified kinase gene fusions. TERT promoter mutations were likely to occur in a sub-clonal manner in our PTC cohort. The prevalence of somatic genetic alterations in PTC was significantly different between our Chinese cohort and TCGA datasets for American patients. Additionally, combined analyses of genetic alterations and clinicopathologic features demonstrated that kinase gene fusion was associated with younger age at diagnosis, larger tumor size, and lymph node metastasis in PTC. With the analyses of DNA rearrangement sites of RET gene fusions in PTC, signatures of chromosome translocations related to RET fusion events were also depicted. Collectively, our results provide fundamental insight into the pathogenesis of PTC in the Chinese population. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Population Genomics Reveals Speciation and Introgression between Brown Norway Rats and Their Sibling Species.

Murine rodents are excellent models for study of adaptive radiations and speciation. Brown Norway rats (Rattus norvegicus) are successful global colonizers and the contributions of their domesticated laboratory strains to biomedical research are well established. To identify nucleotide-based speciation timing of the rat and genomic information contributing to its colonization capabilities, we analyzed 51 whole-genome sequences of wild-derived Brown Norway rats and their sibling species, R. nitidus, and identified over 20 million genetic variants in the wild Brown Norway rats that were absent in the laboratory strains, which substantially expand the reservoir of rat genetic diversity. We showed that divergence of the rat and its siblings coincided with drastic climatic changes that occurred during the Middle Pleistocene. Further, we revealed that there was a geographically widespread influx of genes between Brown Norway rats and the sibling species following the divergence, resulting in numerous introgressed regions in the genomes of admixed Brown Norway rats. Intriguing, genes related to chemical communications among these introgressed regions appeared to contribute to the population-specific adaptations of the admixed Brown Norway rats. Our data reveals evolutionary history of the Brown Norway rat, and offers new insights into the role of climatic changes in speciation of animals and the effect of interspecies introgression on animal adaptation.

Transcriptome Sequencing Reveals Candidate NF-κB Target Genes Involved in Repeated Cocaine Administration.

Background: Drug-induced alterations in gene expression play an important role in the development of addictive behavior. Numerous transcription factors have been implicated in mediating the gene expression changes that occur in drug addiction. Nuclear factor kappa B is an inducible transcription factor complex that is rapidly activated by diverse stimuli. Methods: We performed next-generation high-throughput sequencing of the prefrontal cortex in a mouse model of repeated cocaine administration combined with pharmacological nuclear factor kappa B inhibition to identify nuclear factor kappa B target genes that participate in the cocaine addiction process. Results: We found that the nuclear factor kappa B antagonist sodium diethyldithiocarbamate trihydrate significantly reversed the cocaine-induced expression changes of the amphetamine addiction pathway. Genes that demonstrated differential expression in response to cocaine treatment that was also reversed by sodium diethyldithiocarbamate trihydrate were enriched for the axon guidance pathway. Furthermore, the nuclear factor kappa B homo-dimer motif could be mapped to 86 of these sodium diethyldithiocarbamate trihydrate-reversed genes, which were also enriched for axon guidance. Conclusions: We suggest that nuclear factor kappa B directly modifies the expression of axon guidance pathway members, leading to cocaine sensitization. Our findings reveal the role of prefrontal cortex nuclear factor kappa B activity in addiction and uncover the molecular mechanisms by which nuclear factor kappa B drives changes in the addicted brain.

RBP-Var: a database of functional variants involved in regulation mediated by RNA-binding proteins.

Transcription factors bind to the genome by forming specific contacts with the primary DNA sequence; however, RNA-binding proteins (RBPs) have greater scope to achieve binding specificity through the RNA secondary structure. It has been revealed that single nucleotide variants (SNVs) that alter RNA structure, also known as RiboSNitches, exhibit 3-fold greater local structure changes than replicates of the same DNA sequence, demonstrated by the fact that depletion of RiboSNitches could result in the alteration of specific RNA shapes at thousands of sites, including 3' UTRs, binding sites of microRNAs and RBPs. However, the network between SNVs and post-transcriptional regulation remains unclear. Here, we developed RBP-Var, a database freely available at http://www.rbp-var.biols.ac.cn/, which provides annotation of functional variants involved in post-transcriptional interaction and regulation. RBP-Var provides an easy-to-use web interface that allows users to rapidly find whether SNVs of interest can transform the secondary structure of RNA and identify RBPs whose binding may be subsequently disrupted. RBP-Var integrates DNA and RNA biology to understand how various genetic variants and post-transcriptional mechanisms cooperate to orchestrate gene expression. In summary, RBP-Var is useful in selecting candidate SNVs for further functional studies and exploring causal SNVs underlying human diseases.

Asian house rats may facilitate their invasive success through suppressing brown rats in chronic interaction.

BACKGROUND: The Asian house rat (Rattus tanezumi) and the brown rat (Rattus norvegicus) are closely related species and are partially sympatric in southern China. Over the past 20 years, R. tanezumi has significantly expanded northward in China and partially replaced the native brown rat subspecies, R. n. humiliatus. Although invasive species are often more aggressive than native species, we did not observe interspecific physical aggression between R. tanezumi and R. n. humiliatus. Here, we focused on whether or not R. tanezumi was superior to R. n. humiliatus in terms of nonphysical competition, which is primarily mediated by chemical signals. RESULTS: We performed two laboratory experiments to test different paradigms in domesticated R. tanezumi and R. n. humiliatus. In Experiment 1, we caged adult male rats of each species for 2 months in heterospecific or conspecific pairs, partitioned by perforated galvanized iron sheets, allowing exchange of chemical stimuli and ultrasonic vocalization. The sexual attractiveness of male urine odor showed a tendency (marginal significance) to increase in R. tanezumi caged with R. n. humiliatus, compared with those in conspecific pairs. Hippocampal glucocorticoid receptor (GR) and brain-derived nutrition factor (BDNF) mRNA were upregulated in R. n. humiliatus and R. tanezumi, respectively, when the rats were caged in heterospecific pairs. In Experiment 2, we kept juvenile male rats in individual cages in rooms with either the same or the different species for 2 months, allowing chemical interaction. The sexual attractiveness of male urine was significantly enhanced in R. tanezumi, but reduced in R. n. humiliatus by heterospecific cues and mRNA expression of hippocampal GR and BDNF were upregulated by heterospecific cues in R. n. humiliatus and R. tanezumi, respectively. Although not identical, the results from Experiments 1 and 2 were generally consistent. CONCLUSIONS: The results of both experiments indicate that nonphysical/chronic interspecific stimuli, particularly scent signals, between R. n. humiliatus and R. tanezumi may negatively affect R. n. humiliatus and positively affect R. tanezumi. We infer that chronic interspecific interactions may have contributed to the invasion of R. tanezumi into the range of R. n. humiliatus in natural habitats.