AStruct: detection of allele-specific RNA secondary structure in structuromic probing data.

BACKGROUND: Uncovering functional genetic variants from an allele-specific perspective is of paramount importance in advancing our understanding of gene regulation and genetic diseases. Recently, various allele-specific events, such as allele-specific gene expression, allele-specific methylation, and allele-specific binding, have been explored on a genome-wide scale due to the development of high-throughput sequencing methods. RNA secondary structure, which plays a crucial role in multiple RNA-associated processes like RNA modification, translation and splicing, has emerged as an essential focus of relevant research. However, tools to identify genetic variants associated with allele-specific RNA secondary structures are still lacking. RESULTS: Here, we develop a computational tool called 'AStruct' that enables us to detect allele-specific RNA secondary structure (ASRS) from RT-stop based structuromic probing data. AStruct shows robust performance in both simulated datasets and public icSHAPE datasets. We reveal that single nucleotide polymorphisms (SNPs) with higher AStruct scores are enriched in coding regions and tend to be functional. These SNPs are highly conservative, have the potential to disrupt sites involved in m6A modification or protein binding, and are frequently associated with disease. CONCLUSIONS: AStruct is a tool dedicated to invoke allele-specific RNA secondary structure events at heterozygous SNPs in RT-stop based structuromic probing data. It utilizes allelic variants, base pairing and RT-stop information under different cell conditions to detect dynamic and functional ASRS. Compared to sequence-based tools, AStruct considers dynamic cell conditions and outperforms in detecting functional variants. AStruct is implemented in JAVA and is freely accessible at: https://github.com/canceromics/AStruct .

A genetic basis for cancer sex differences revealed in Xp11 translocation renal cell carcinoma.

Xp11 translocation renal cell carcinoma (tRCC) is a female-predominant kidney cancer driven by translocations between the TFE3 gene on chromosome Xp11.2 and partner genes located on either chrX or on autosomes. The rearrangement processes that underlie TFE3 fusions, and whether they are linked to the female sex bias of this cancer, are largely unexplored. Moreover, whether oncogenic TFE3 fusions arise from both the active and inactive X chromosomes in females remains unknown. Here we address these questions by haplotype-specific analyses of whole-genome sequences of 29 tRCC samples from 15 patients and by re-analysis of 145 published tRCC whole-exome sequences. We show that TFE3 fusions universally arise as reciprocal translocations with minimal DNA loss or insertion at paired break ends. Strikingly, we observe a near exact 2:1 female:male ratio in TFE3 fusions arising via X:autosomal translocation (but not via X inversion), which accounts for the female predominance of tRCC. This 2:1 ratio is at least partially attributable to oncogenic fusions involving the inactive X chromosome and is accompanied by partial re-activation of silenced chrX genes on the rearranged chromosome. Our results highlight how somatic alterations involving the X chromosome place unique constraints on tumor initiation and exemplify how genetic rearrangements of the sex chromosomes can underlie cancer sex differences.

Genetic compensation response could exist in colorectal cancer: UPF3A upregulates the oncogenic homologue gene SRSF3 expression corresponding to SRSF6 to promote colorectal cancer metastasis.

BACKGROUND: Genetic compensation response (GCR) is a mechanism that maintains the robustness of functional genes, which has been recently identified. Whether GCR exists in tumors and its effects on tumor progression remains unknown. METHODS: Whole exome sequencing was performed to identify premature termination codon (PTC) gene mutations in colorectal cancer (CRC) tissues. RNA sequencing, Cancer Cell Line Encyclopedia database analysis, and high-throughput output of homologous genes using the Ensemble genome database were performed to further identify homologous genes of target PTC gene mutations. RESULTS: Serine and arginine-rich splicing factor 3 (SRSF3) increased the invasion ability in CRC cells and could be the target gene of up-frameshift 3A (UPF3A). The deletion of the 660th base A in the coding sequence region of SRSF6 caused a frameshift mutation of serine at position 220 (s220fs), which contributed to a PTC UAA termination of translation in HCT116 cells. We further found that SRSF3 was the only homologue of SRSF6 with a frameshift mutation. The transfection of s220fs of SRSF6 into HCT116 cells led to upregulation of its corresponding oncogenic homologue gene SRSF3 expression to promote CRC metastasis. SRSF3 was highly expressed in CRC liver metastases and was positively correlated with UPF3A expression and contributed to poor prognosis. CONCLUSION: GCR may exist in CRC and exert effects on the progression of CRC. Targeted inhibition of UPF3A could reduce the GCR effects and suppress the expression of oncogenic homologue genes corresponding to PTC mutations, indicating a novel therapeutic strategy for treatment of CRC metastasis.

WHISTLE: A Functionally Annotated High-Accuracy Map of Human m6A Epitranscriptome.

N6-Methyladenosine (m6A) is the most prevalent posttranscriptional modification in eukaryotes and plays a pivotal role in various biological processes, such as splicing, RNA degradation, and RNA-protein interaction. Accurately identification of the location of m6A is essential for related downstream studies. In this chapter, we introduce a prediction framework WHISTLE, which enables us to acquire so far the most accurate map of the transcriptome-wide human m6A RNA-methylation sites (with an average AUC: 0.948 and 0.880 under the full transcript or mature messenger RNA models, respectively, when tested on independent datasets). Besides, each individual m6A site was also functionally annotated according to the "guilt-by-association" principle by integrating RNA methylation data, gene expression data and protein-protein interaction data. A web server was constructed for conveniently querying the predicted RNA methylation sites and their putative biological functions. The website supports the query by genes, by GO function, table view, and the download of all the functionally annotated map of predicted map of human m6A epitranscriptome. The WHISTLE web server is freely available at: www.xjtlu.edu.cn/biologicalsciences/whistle and http://whistle-epitranscriptome.com .

m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome.

N 6-Methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. It plays a pivotal role during various biological processes and disease pathogenesis. We present here a comprehensive knowledgebase, m6A-Atlas, for unraveling the m6A epitranscriptome. Compared to existing databases, m6A-Atlas features a high-confidence collection of 442 162 reliable m6A sites identified from seven base-resolution technologies and the quantitative (rather than binary) epitranscriptome profiles estimated from 1363 high-throughput sequencing samples. It also offers novel features, such as; the conservation of m6A sites among seven vertebrate species (including human, mouse and chimp), the m6A epitranscriptomes of 10 virus species (including HIV, KSHV and DENV), the putative biological functions of individual m6A sites predicted from epitranscriptome data, and the potential pathogenesis of m6A sites inferred from disease-associated genetic mutations that can directly destroy m6A directing sequence motifs. A user-friendly graphical user interface was constructed to support the query, visualization and sharing of the m6A epitranscriptomes annotated with sites specifying their interaction with post-transcriptional machinery (RBP-binding, microRNA interaction and splicing sites) and interactively display the landscape of multiple RNA modifications. These resources provide fresh opportunities for unraveling the m6A epitranscriptomes. m6A-Atlas is freely accessible at: www.xjtlu.edu.cn/biologicalsciences/atlas.

RMDisease: a database of genetic variants that affect RNA modifications, with implications for epitranscriptome pathogenesis.

Deciphering the biological impacts of millions of single nucleotide variants remains a major challenge. Recent studies suggest that RNA modifications play versatile roles in essential biological mechanisms, and are closely related to the progression of various diseases including multiple cancers. To comprehensively unveil the association between disease-associated variants and their epitranscriptome disturbance, we built RMDisease, a database of genetic variants that can affect RNA modifications. By integrating the prediction results of 18 different RNA modification prediction tools and also 303,426 experimentally-validated RNA modification sites, RMDisease identified a total of 202,307 human SNPs that may affect (add or remove) sites of eight types of RNA modifications (m6A, m5C, m1A, m5U, Ψ, m6Am, m7G and Nm). These include 4,289 disease-associated variants that may imply disease pathogenesis functioning at the epitranscriptome layer. These SNPs were further annotated with essential information such as post-transcriptional regulations (sites for miRNA binding, interaction with RNA-binding proteins and alternative splicing) revealing putative regulatory circuits. A convenient graphical user interface was constructed to support the query, exploration and download of the relevant information. RMDisease should make a useful resource for studying the epitranscriptome impact of genetic variants via multiple RNA modifications with emphasis on their potential disease relevance. RMDisease is freely accessible at: www.xjtlu.edu.cn/biologicalsciences/rmd.