SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data.

RNA-protein binding is critical to gene regulation, controlling fundamental processes including splicing, translation, localization and stability, and aberrant RNA-protein interactions are known to play a role in a wide variety of diseases. However, molecular understanding of RNA-protein interactions remains limited; in particular, identification of RNA motifs that bind proteins has long been challenging, especially when such motifs depend on both sequence and structure. Moreover, although RNA binding proteins (RBPs) often contain more than one binding domain, algorithms capable of identifying more than one binding motif simultaneously have not been developed. In this paper we present a novel pipeline to determine binding peaks in crosslinking immunoprecipitation (CLIP) data, to discover multiple possible RNA sequence/structure motifs among them, and to experimentally validate such motifs. At the core is a new semi-automatic algorithm SARNAclust, the first unsupervised method to identify and deconvolve multiple sequence/structure motifs simultaneously. SARNAclust computes similarity between sequence/structure objects using a graph kernel, providing the ability to isolate the impact of specific features through the bulge graph formalism. Application of SARNAclust to synthetic data shows its capability of clustering 5 motifs at once with a V-measure value of over 0.95, while GraphClust achieves only a V-measure of 0.083 and RNAcontext cannot detect any of the motifs. When applied to existing eCLIP sets, SARNAclust finds known motifs for SLBP and HNRNPC and novel motifs for several other RBPs such as AGGF1, AKAP8L and ILF3. We demonstrate an experimental validation protocol, a targeted Bind-n-Seq-like high-throughput sequencing approach that relies on RNA inverse folding for oligo pool design, that can validate the components within the SLBP motif. Finally, we use this protocol to experimentally interrogate the SARNAclust motif predictions for protein ILF3. Our results support a newly identified partially double-stranded UUUUUGAGA motif similar to that known for the splicing factor HNRNPC.

Mirinho: An efficient and general plant and animal pre-miRNA predictor for genomic and deep sequencing data.

BACKGROUND: Several methods exist for the prediction of precursor miRNAs (pre-miRNAs) in genomic or sRNA-seq (small RNA sequences) data produced by NGS (Next Generation Sequencing). One key information used for this task is the characteristic hairpin structure adopted by pre-miRNAs, that in general are identified using RNA folders whose complexity is cubic in the size of the input. The vast majority of pre-miRNA predictors then rely on further information learned from previously validated miRNAs from the same or a closely related genome for the final prediction of new miRNAs. With this paper, we wished to address three main issues. The first was methodological and aimed at obtaining a more time-efficient predictor, however without losing in accuracy which represented a second issue. We indeed aimed at better predicting miRNAs at a genome scale, but also from sRNAseq data where in some cases, notably of plants, the current folding methods often infer the wrong structure. The third issue is related to the fact that it is important to rely as little as possible on previously recorded examples of miRNAs. We therefore also sought a method that is less dependent on previous miRNA records. RESULTS: As concerns the first and second issues, we present a novel alternative to a classical folder based on a thermodynamic Nearest-Neighbour (NN) model for computing the free energy and predicting the classical hairpin structure of a pre-miRNA. We show that the free energies thus computed correlate well with those of RNAFOLD. This novel method, called MIRINHO, has quadratic instead of cubic complexity and is much more efficient also in practice. When applied to sRNAseq data of plants, it gives in general better results than classical folders. On the third issue, we show that MIRINHO, which uses as only knowledge the length of the loops and stem-arms and the free energy of the pre-miRNA hairpin, compares well with algorithms that require more information. The results, obtained with different datasets, are indeed similar to those of other approaches with which such a comparison was possible. These needed to be publicly available softwares that could be used on a large input. In some cases, MIRINHO is even better in terms of sensitivity or precision. CONCLUSION: We provide a simpler and much faster method with very reasonable sensitivity and precision, which can be applied without special adaptation to the prediction of both animal and plant pre-miRNAs, using as input either genomic sequences or sRNA-seq data.

Protein arginine methyltransferase 2 controls inflammatory signaling in acute myeloid leukemia.

Arginine methylation is catalyzed by protein arginine methyltransferases (PRMTs) and is involved in various cellular processes, including cancer development. PRMT2 expression is increased in several cancer types although its role in acute myeloid leukemia (AML) remains unknown. Here, we investigate the role of PRMT2 in a cohort of patients with AML, PRMT2 knockout AML cell lines as well as a Prmt2 knockout mouse model. In patients, low PRMT2 expressors are enriched for inflammatory signatures, including the NF-κB pathway, and show inferior survival. In keeping with a role for PRMT2 in control of inflammatory signaling, bone marrow-derived macrophages from Prmt2 KO mice display increased pro-inflammatory cytokine signaling upon LPS treatment. In PRMT2-depleted AML cell lines, aberrant inflammatory signaling has been linked to overproduction of IL6, resulting from a deregulation of the NF-κB signaling pathway, therefore leading to hyperactivation of STAT3. Together, these findings identify PRMT2 as a key regulator of inflammation in AML.

A second look at exome sequencing data: detecting mobile elements insertion in a rare disease cohort.

About 0.3% of all variants are due to de novo mobile element insertions (MEIs). The massive development of next-generation sequencing has made it possible to identify MEIs on a large scale. We analyzed exome sequencing (ES) data from 3232 individuals (2410 probands) with developmental and/or neurological abnormalities, with MELT, a tool designed to identify MEIs. The results were filtered by frequency, impacted region and gene function. Following phenotype comparison, two candidates were identified in two unrelated probands. The first mobile element (ME) was found in a patient referred for poikilodermia. A homozygous insertion was identified in the FERMT1 gene involved in Kindler syndrome. RNA study confirmed its pathological impact on splicing. The second ME was a de novo Alu insertion in the GRIN2B gene involved in intellectual disability, and detected in a patient with a developmental disorder. The frequency of de novo exonic MEIs in our study is concordant with previous studies on ES data. This project, which aimed to identify pathological MEIs in the coding sequence of genes, confirms that including detection of MEs in the ES pipeline can increase the diagnostic rate. This work provides additional evidence that ES could be used alone as a diagnostic exam.

Integrative Clinical and DNA Methylation Analyses in a Population-Based Cohort Identifies CDH17 and LRP2 as Risk Recurrence Factors in Stage II Colon Cancer.

Stage II colon cancer (CC), although diagnosed early, accounts for 16% of CC deaths. Predictors of recurrence risk could mitigate this but are currently lacking. By using a DNA methylation-based clinical screening in real-world (n = 383) and in TCGA-derived cohorts of stage II CC (n = 134), we have devised a novel 40 CpG site-based classifier that can segregate stage II CC into four previously undescribed disease sub-classes that are characterised by distinct molecular features, including activation of MYC/E2F-dependant proliferation signatures. By multivariate analyses, hypermethylation of 2 CpG sites at genes CDH17 and LRP2, respectively, was found to independently confer either significantly increased (CDH17; p-value, 0.0203) or reduced (LRP2; p-value, 0.0047) risk of CC recurrence. Functional enrichment and immune cell infiltration analyses, on RNAseq data from the TCGA cohort, revealed cases with hypermethylation at CDH17 to be enriched for KRAS, epithelial-mesenchymal transition and inflammatory functions (via IL2/STAT5), associated with infiltration by 'exhausted' T cells. By contrast, LRP2 hypermethylated cases showed enrichment for mTORC1, DNA repair pathways and activated B cell signatures. These findings will be of value for improving personalised care paths and treatment in stage II CC patients.

Repeat Element Activation-Driven Inflammation: Role of NFκB and Implications in Normal Development and Cancer?

The human genome is composed of unique DNA sequences that encode proteins and unique sequence noncoding RNAs that are essential for normal development and cellular differentiation. The human genome also contains over 50% of genome sequences that are repeat in nature (tandem and interspersed repeats) that are now known to contribute dynamically to genetic diversity in populations, to be transcriptionally active under certain physiological conditions, and to be aberrantly active in disease states including cancer, where consequences are pleiotropic with impact on cancer cell phenotypes and on the tumor immune microenvironment. Repeat element-derived RNAs play unique roles in exogenous and endogenous cell signaling under normal and disease conditions. A key component of repeat element-derived transcript-dependent signaling occurs via triggering of innate immune receptor signaling that then feeds forward to inflammatory responses through interferon and NFκB signaling. It has recently been shown that cancer cells display abnormal transcriptional activity of repeat elements and that this is linked to either aggressive disease and treatment failure or to improved prognosis/treatment response, depending on cell context and the amplitude of the so-called 'viral mimicry' response that is engaged. 'Viral mimicry' refers to a cellular state of active antiviral response triggered by endogenous nucleic acids often derived from aberrantly transcribed endogenous retrotransposons and other repeat elements. In this paper, the literature regarding transcriptional activation of repeat elements and engagement of inflammatory signaling in normal (focusing on hematopoiesis) and cancer is reviewed with an emphasis on the role of innate immune receptor signaling, in particular by dsRNA receptors of the RIG-1 like receptor family and interferons/NFκB. How repeat element-derived RNA reprograms cell identity through RNA-guided chromatin state modulation is also discussed.

c-MYC and p53 expression highlight starry-sky pattern as a favourable prognostic feature in R-CHOP-treated diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a clinically heterogeneous entity, in which the first-line treatment currently consists of an immuno-chemotherapy regimen (R-CHOP). However, around 30% of patients will not respond or will relapse. Overexpression of c-MYC or p53 is frequently found in DLBCL, but an association with prognosis remains controversial, as for other biomarkers previously linked with DLBCL aggressivity (CD5, CD23, or BCL2). The aim of this study was to explore the expression of these biomarkers and their correlation with outcome, clinical, or pathological features in a DLBCL cohort. Immunohistochemical (c-MYC, p53, BCL2, CD5, and CD23), morphological ('starry-sky' pattern [SSP]), targeted gene panel sequencing by next-generation sequencing (NGS), and fluorescence in situ hybridisation analyses were performed on tissue microarray blocks for a retrospective cohort of 94 R-CHOP-treated de novo DLBCL. In univariate analyses, p53 overexpression (p53high ) was associated with unfavourable outcome (p = 0.04) and with c-MYC overexpression (p = 0.01), whereas c-MYC overexpression was linked with an SSP (p = 0.004), but only tended towards an inferior prognosis (p = 0.06). Presence of a starry-sky morphology was found to be correlated with better survival in p53high DLBCL (p = 0.03) and/or c-MYC-positive DLBCL (p = 0.002). Furthermore, NGS data revealed that these three variables were associated with somatic mutations (PIM1, TNFRSF14, FOXO1, and B2M) involved in B-cell proliferation, survival, metabolism, and immune signalling. Taken together, these results show that the SSP pattern seems to be a protective factor in high-risk DLBCL subgroups and highlight cell death as a built-in failsafe mechanism to control tumour growth.

Identification of novel, clonally stable, somatic mutations targeting transcription factors PAX5 and NKX2-3, the epigenetic regulator LRIF1, and BRAF in a case of atypical B-cell chronic lymphocytic leukemia harboring a t(14;18)(q32;q21).

Diagnosis of B-cell chronic lymphocytic leukemia (B-CLL) is usually straightforward, involving clinical, immunophenotypic (Matutes score), and (immuno)genetic analyses (to refine patient prognosis for treatment). CLL cases with atypical presentation (e.g., Matutes ≤ 3) are also encountered, and for these diseases, biology and prognostic impact are less clear. Here we report the genomic characterization of a case of atypical B-CLL in a 70-yr-old male patient; B-CLL cells showed a Matutes score of 3, chromosomal translocation t(14;18)(q32;q21) (BCL2/IGH), mutated IGHV, deletion 17p, and mutations in BCL2, NOTCH1 (subclonal), and TP53 (subclonal). Quite strikingly, a novel PAX5 mutation that was predicted to be loss of function was also seen. Exome sequencing identified, in addition, a potentially actionable BRAF mutation, together with novel somatic mutations affecting the homeobox transcription factor NKX2-3, known to control B-lymphocyte development and homing, and the epigenetic regulator LRIF1, which is implicated in chromatin compaction and gene silencing. Neither NKX2-3 nor LRIF1 mutations, predicted to be loss of function, have previously been reported in B-CLL. Sequencing confirmed the presence of these mutations together with BCL2, NOTCH1, and BRAF mutations, with the t(14;18)(q32;q21) translocation, in the initial diagnostic sample obtained 12 yr prior. This is suggestive of a role for these novel mutations in B-CLL initiation and stable clonal evolution, including upon treatment withdrawal. This case extends the spectrum of atypical B-CLL with t(14;18)(q32;q21) and highlights the value of more global precision genomics for patient follow-up and treatment in these patients.

CYCLON and NPM1 Cooperate within an Oncogenic Network Predictive of R-CHOP Response in DLBCL.

R-CHOP immuno-chemotherapy significantly improved clinical management of diffuse large B-cell lymphoma (DLBCL). However, 30-40% of DLBCL patients still present a refractory disease or relapse. Most of the prognostic markers identified to date fail to accurately stratify high-risk DLBCL patients. We have previously shown that the nuclear protein CYCLON is associated with DLBCL disease progression and resistance to anti-CD20 immunotherapy in preclinical models. We also recently reported that it also represents a potent predictor of refractory disease and relapse in a retrospective DLBCL cohort. However, only sparse data are available to predict the potential biological role of CYCLON and how it might exert its adverse effects on lymphoma cells. Here, we characterized the protein interaction network of CYCLON, connecting this protein to the nucleolus, RNA processing, MYC signaling and cell cycle progression. Among this network, NPM1, a nucleolar multi-functional protein frequently deregulated in cancer, emerged as another potential target related to treatment resistance in DLBCL. Immunohistochemistry evaluation of CYCLON and NPM1 revealed that their co-expression is strongly related to inferior prognosis in DLBCL. More specifically, alternative sub-cellular localizations of the proteins (extra-nucleolar CYCLON and pan-cellular NPM1) represent independent predictive factors specifically associated to R-CHOP refractory DLBCL patients, which could allow them to be orientated towards risk-adapted or novel targeted therapies.

A reference genome for pea provides insight into legume genome evolution.

We report the first annotated chromosome-level reference genome assembly for pea, Gregor Mendel's original genetic model. Phylogenetics and paleogenomics show genomic rearrangements across legumes and suggest a major role for repetitive elements in pea genome evolution. Compared to other sequenced Leguminosae genomes, the pea genome shows intense gene dynamics, most likely associated with genome size expansion when the Fabeae diverged from its sister tribes. During Pisum evolution, translocation and transposition differentially occurred across lineages. This reference sequence will accelerate our understanding of the molecular basis of agronomically important traits and support crop improvement.