Single-cell transcriptomic analysis of the immune microenvironment in pediatric acute leukemia.

Relapse and treatment resistance pose significant challenges in the management of pediatric B cell acute lymphoblastic leukemia (B-ALL) and acute myeloid leukemia (AML). The efficacy of immunotherapy in leukemia remains limited due to factors such as the immunosuppressive tumor microenvironment (TME) and lack of suitable immunotherapeutic targets. Thus, an in-depth characterization of the TME in pediatric leukemia is warranted to improve the efficacy of immunotherapy.

DIPAN: Detecting personalized intronic polyadenylation derived neoantigens from RNA sequencing data.

Intronic polyadenylation (IPA) refers to a particular type of alternative polyadenylation where a gene makes use of a polyadenylation site located within its introns. Aberrant IPA events have been observed in various types of cancer. IPA can produce noncoding transcripts or truncated protein-coding transcripts with altered coding sequences in the resulting protein product.

Comprehensive characterization of somatic mutations associated with chimeric RNAs in human cancers.

Chimeric RNAs, which can arise from gene recombination at the DNA level or non-canonical splicing events at the RNA level, have been identified as important roles in human tumors. Dysregulated gene expression caused by somatic mutations and altered splicing patterns of oncogenes or tumor suppressor genes can contribute to the development of tumors. Therefore, investigating the formation mechanism of chimeric RNAs via somatic mutations is critical for understanding tumor pathogenesis.

InPACT: a computational method for accurate characterization of intronic polyadenylation from RNA sequencing data.

Alternative polyadenylation can occur in introns, termed intronic polyadenylation (IPA), has been implicated in diverse biological processes and diseases, as it can produce noncoding transcripts or transcripts with truncated coding regions. However, a reliable method is required to accurately characterize IPA. Here, we propose a computational method called InPACT, which allows for the precise characterization of IPA from conventional RNA-seq data.

An atlas of cell-type-specific interactome networks across 44 human tumor types.

Background: Biological processes are controlled by groups of genes acting in concert. Investigating gene-gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors.

Methods: We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types.

ChIPr: accurate prediction of cohesin-mediated 3D genome organization from 2D chromatin features.

The three-dimensional genome organization influences diverse nuclear processes. Here we present Chromatin Interaction Predictor (ChIPr), a suite of regression models based on deep neural networks, random forest, and gradient boosting to predict cohesin-mediated chromatin interaction strength between any two loci in the genome. The predictions of ChIPr correlate well with ChIA-PET data in four cell lines.

The effects of coagulation factors on the risk of endometriosis: a Mendelian randomization study.

Background: Endometriosis is recognized as a complex gynecological disorder that can cause severe pain and infertility, affecting 6-10% of all reproductive-aged women. Endometriosis is a condition in which endometrial tissue, which normally lines the inside of the uterus, deposits in other tissues. The etiology and pathogenesis of endometriosis remain ambiguous.

eaQTLdb: An atlas of enhancer activity quantitative trait loci across cancer types.

Enhancers are key regulatory elements that exert crucial roles in diverse biological processes, including tumorigenesis and cancer development. Active enhancers could produce transcripts termed enhancer RNAs (eRNAs), which could be used as an index of enhancer activity. Here, we present a versatile data portal, enhancer activity quantitative trait loci database (eaQTLdb; http://www.

Prostate Cancer Transcriptomic Regulation by the Interplay of Germline Risk Alleles, Somatic Mutations, and 3D Genomic Architecture.

Unlabelled: Prostate cancer is one of the most heritable human cancers. Genome-wide association studies have identified at least 185 prostate cancer germline risk alleles, most noncoding. We used integrative three-dimensional (3D) spatial genomics to identify the chromatin interaction targets of 45 prostate cancer risk alleles, 31 of which were associated with the transcriptional regulation of target genes in 565 localized prostate tumors.

scAPAatlas: an atlas of alternative polyadenylation across cell types in human and mouse.

Alternative polyadenylation (APA) has been widely recognized as a crucial step during the post-transcriptional regulation of eukaryotic genes. Recent studies have demonstrated that APA exerts key regulatory roles in many biological processes and often occurs in a tissue- and cell-type-specific manner. However, to our knowledge, there is no database incorporating information about APA at the cell-type level.

Genome-wide germline correlates of the epigenetic landscape of prostate cancer.

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors.

Mitochondrial Trafficking and Processing of Telomerase RNA TERC.

Mitochondrial dysfunctions play major roles in many diseases. However, how mitochondrial stresses are relayed to downstream responses remains unclear. Here we show that the RNA component of mammalian telomerase TERC is imported into mitochondria, processed to a shorter form TERC-53, and then exported back to the cytosol.

Stress-responsive regulation of long non-coding RNA polyadenylation in Oryza sativa.

Recently, long non-coding RNAs (lncRNAs) have been demonstrated to be involved in many biological processes of plants; however, a systematic study on transcriptional and, in particular, post-transcriptional regulation of stress-responsive lncRNAs in Oryza sativa (rice) is lacking. We sequenced three types of RNA libraries (poly(A)+, poly(A)- and nuclear RNAs) under four abiotic stresses (cold, heat, drought and salt). Based on an integrative bioinformatics approach and ~200 high-throughput data sets, ~170 of which have been published, we revealed over 7000 lncRNAs, nearly half of which were identified for the first time.

Comprehensive analysis of long non-coding RNAs highlights their spatio-temporal expression patterns and evolutional conservation in Sus scrofa.

Despite modest sequence conservation and rapid evolution, long non-coding RNAs (lncRNAs) appear to be conserved in expression pattern and function. However, analysis of lncRNAs across tissues and developmental stages remains largely uncharacterized in mammals. Here, we systematically investigated the lncRNAs of the Guizhou miniature pig (Sus scrofa), which was widely used as biomedical model.

Recurrently deregulated lncRNAs in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) cells often invade the portal venous system and subsequently develop into portal vein tumour thrombosis (PVTT). Long noncoding RNAs (lncRNAs) have been associated with HCC, but a comprehensive analysis of their specific association with HCC metastasis has not been conducted. Here, by analysing 60 clinical samples' RNA-seq data from 20 HCC patients, we have identified and characterized 8,603 candidate lncRNAs.

Large-scale mapping of mammalian transcriptomes identifies conserved genes associated with different cell states.

Distinguishing cell states based only on gene expression data remains a challenging task. This is true even for analyses within a species. In cross-species comparisons, the results obtained by different groups have varied widely.

Systematic characterization of novel lncRNAs responding to phosphate starvation in Arabidopsis thaliana.

Background: Previously, several long non-coding RNAs (lncRNAs) were characterized as regulators in phosphate (Pi) starvation responses. However, systematic studies of novel lncRNAs involved in the Pi starvation signaling pathways have not been reported.

Results: Here, we used a genome-wide sequencing and bioinformatics approach to identify both poly(A) + and poly(A)- lncRNAs that responded to Pi starvation in Arabidopsis thaliana.

Characterization of stress-responsive lncRNAs in Arabidopsis thaliana by integrating expression, epigenetic and structural features.

Recently, in addition to poly(A)+ long non-coding RNAs (lncRNAs), many lncRNAs without poly(A) tails, have been characterized in mammals. However, the non-polyA lncRNAs and their conserved motifs, especially those associated with environmental stresses, have not been fully investigated in plant genomes. We performed poly(A)- RNA-seq for seedlings of Arabidopsis thaliana under four stress conditions, and predicted lncRNA transcripts.