xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs.

Genome-wide association studies (GWAS) have identified thousands of disease-associated non-coding variants, posing urgent needs for functional interpretation. Molecular Quantitative Trait Loci (xQTLs) such as eQTLs serve as an essential intermediate link between these non-coding variants and disease phenotypes and have been widely used to discover disease-risk genes from many population-scale studies. However, mining and analyzing the xQTLs data presents several significant bioinformatics challenges, particularly when it comes to integration with GWAS data. Here, we developed xQTLbiolinks as the first comprehensive and scalable tool for bulk and single-cell xQTLs data retrieval, quality control and pre-processing from public repositories and our integrated resource. In addition, xQTLbiolinks provided a robust colocalization module through integration with GWAS summary statistics. The result generated by xQTLbiolinks can be flexibly visualized or stored in standard R objects that can easily be integrated with other R packages and custom pipelines. We applied xQTLbiolinks to cancer GWAS summary statistics as case studies and demonstrated its robust utility and reproducibility. xQTLbiolinks will profoundly accelerate the interpretation of disease-associated variants, thus promoting a better understanding of disease etiologies. xQTLbiolinks is available at https://github.com/lilab-bioinfo/xQTLbiolinks.

Immune-response 3'UTR alternative polyadenylation quantitative trait loci contribute to variation in human complex traits and diseases.

Genome-wide association studies (GWASs) have identified thousands of non-coding variants that are associated with human complex traits and diseases. The analysis of such GWAS variants in different contexts and physiological states is essential for deciphering the regulatory mechanisms underlying human disease. Alternative polyadenylation (APA) is a key post-transcriptional modification for most human genes that substantially impacts upon cell behavior. Here, we mapped 9,493 3'-untranslated region APA quantitative trait loci in 18 human immune baseline cell types and 8 stimulation conditions (immune 3'aQTLs). Through the comparison between baseline and stimulation data, we observed the high responsiveness of 3'aQTLs to immune stimulation (response 3'aQTLs). Co-localization and mendelian randomization analyses of immune 3'aQTLs identified 678 genes where 3'aQTL are associated with variation in complex traits, 27.3% of which were derived from response 3'aQTLs. Overall, these analyses reveal the role of immune 3'aQTLs in the determination of complex traits, providing new insights into the regulatory mechanisms underlying disease etiologies.

TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes.

Genes have the ability to produce transcript variants that perform specific cellular functions. However, accurately detecting all transcript variants remains a long-standing challenge, especially when working with poorly annotated genomes or without a known genome. To address this issue, we have developed a new computational method, TransIntegrator, which enables transcriptome-wide detection of novel transcript variants. For this, we determined 10 Illumina sequencing transcriptomes and a PacBio full-length transcriptome for consecutive embryo development stages of amphioxus, a species of great evolutionary importance. Based on the transcriptomes, we employed TransIntegrator to create a comprehensive transcript variant library, namely iTranscriptome. The resulting iTrancriptome contained 91 915 distinct transcript variants, with an average of 2.4 variants per gene. This substantially improved current amphioxus genome annotation by expanding the number of genes from 21 954 to 38 777. Further analysis manifested that the gene expansion was largely ascribed to integration of multiple Illumina datasets instead of involving the PacBio data. Moreover, we demonstrated an example application of TransIntegrator, via generating iTrancriptome, in aiding accurate transcriptome assembly, which significantly outperformed other hybrid methods such as IDP-denovo and Trinity. For user convenience, we have deposited the source codes of TransIntegrator on GitHub as well as a conda package in Anaconda. In summary, this study proposes an affordable but efficient method for reliable transcriptomic research in most species.

Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug-gene-adverse drug reaction (ADR) interaction network. For the first time, the drug safety was assessed in a broad landscape of 1,156 distinct ADRs. We also designed a parameter ToxicityScore to quantify the overall drug safety. Moreover, we determined association strength for every 3,807,631 gene-ADR interactions, which clues mechanistic exploration of ADRs. For convenience, we deployed the model as a web service ADRAlert-gene at http://www.bio-add.org/ADRAlert/. In summary, this study offers insights into prioritizing safe drug therapy. It helps reduce the attrition rate of new drug discovery by providing a reliable ADR profile in the early preclinical stage.

Deep sequencing reveals microRNA signature is altered in the rat epididymis following bilateral castration.

BACKGROUND: In the epididymis of bilateral castrated male rat, gene expression profile changed significantly. However, up to date, no study has investigated how these genes were regulated by microRNAs (miRNAs). OBJECTIVE: We investigated the alterations in the miRNA signature of the epididymis from sham-operated and bilaterally castrated rats. METHODS: By employing deep sequencing technology and qPCR, the global alterations of epididymal miRNA signature between sham-operated (Con-EP library) and bilaterally castrated rats (Cas-EP library) were explored. MiRNA-target interaction networks were annotated by GO and KEGG enrichment. RESULTS: We identified 313 and 306 known miRNAs as well as 152 and 114 novel miRNAs in the Con-EP and Cas-EP libraries, respectively. 59 miRNAs were differentially expressed, including 24 up-regulated and 35 down-regulated miRNAs, among which two up-regulated and three down-regulated ones were validated using qPCR. The expression of these miRNAs in the epididymides of rats at different postnatal ages showed regular changes from birth to adult, suggesting they were androgen-regulated. GO analysis showed that many of the miRNA targets were enriched in metabolic processes. KEGG analysis demonstrated that the targets mainly participated in the mitogen-activated protein kinase (MAPK) pathway. Moreover, 3 and 6 functional modules were detected among the up- and down-regulated miRNA target interaction networks, respectively, and these modules were involved in various biological processes. CONCLUSION: This study represents the first systematic investigation of alterations in the miRNA signature of the epididymis from bilaterally castrated rats and will provide useful resources for functional studies of the miRNAs in the male reproductive system.

Karst rocky desertification progress: Soil calcium as a possible driving force.

Karst rocky desertification is a severe irreversible ecosystem failure. The karst ecosystem is so fragile that it is vulnerable to environmental changes, degrading into rocky desertification. Prior studies revealed the potential connections between the soil bacterial community, the edaphic properties and the aboveground vegetation cover in the karst ecosystem. However, how these three elements affect each other and work together in propelling in the karst rocky desertification progress largely remains unexplored. To answer this question, we monitored the bacterial community variations in soils sampled from multiple sites at a successional karst rocky desertification region by sequencing the 16S rRNA V3-V4 regions. Overall, we detected 34 bacterial phyla in the karst soils, of which Proteobacteria, Actinobacteria, and Acidobacteria are the most abundant. Network analysis of the bacterial community- vegetation-edaphic property-vegetation interactions identified 6 bacterial herds that had significant correlation with soil Ca2+ and available phosphorus change during vegetation degradation. Further functional simulation of these bacterial herds unveiled the change of Ca2+ and available phosphorus might disturb the soil carbon and nitrogen metabolism, and thus weakened soil quality. In summary, we hypothesized a calcium-driven bacterial response mechanism in the karst rocky desertification progress.

Pattern Genes Suggest Functional Connectivity of Organs.

Human organ, as the basic structural and functional unit in human body, is made of a large community of different cell types that organically bound together. Each organ usually exerts highly specified physiological function; while several related organs work smartly together to perform complicated body functions. In this study, we present a computational effort to understand the roles of genes in building functional connection between organs. More specifically, we mined multiple transcriptome datasets sampled from 36 human organs and tissues, and quantitatively identified 3,149 genes whose expressions showed consensus modularly patterns: specific to one organ/tissue, selectively expressed in several functionally related tissues and ubiquitously expressed. These pattern genes imply intrinsic connections between organs. According to the expression abundance of the 766 selective genes, we consistently cluster the 36 human organs/tissues into seven functional groups: adipose &gland, brain, muscle, immune, metabolism, mucoid and nerve conduction. The organs and tissues in each group either work together to form organ systems or coordinate to perform particular body functions. The particular roles of specific genes and selective genes suggest that they could not only be used to mechanistically explore organ functions, but also be designed for selective biomarkers and therapeutic targets.