Assessing conservation of alternative splicing with evolutionary splicing graphs.

Understanding how protein function has evolved and diversified is of great importance for human genetics and medicine. Here, we tackle the problem of describing the whole transcript variability observed in several species by generalizing the definition of splicing graph. We provide a practical solution to construct parsimonious evolutionary splicing graphs where each node is a minimal transcript building block defined across species. We show a clear link between the functional relevance, tissue regulation, and conservation of alternative transcripts on a set of 50 genes. By scaling up to the whole human protein-coding genome, we identify a few thousand genes where alternative splicing modulates the number and composition of pseudorepeats. We have implemented our approach in ThorAxe, an efficient, versatile, robust, and freely available computational tool.

Dicer-dependent heterochromatic small RNAs in the model diatom species Phaeodactylum tricornutum.

Diatoms are eukaryotic microalgae responsible for nearly half of the marine productivity. RNA interference (RNAi) is a mechanism of regulation of gene expression mediated by small RNAs (sRNAs) processed by the endoribonuclease Dicer (DCR). To date, the mechanism and physiological role of RNAi in diatoms are unknown. We mined diatom genomes and transcriptomes for key RNAi effectors and retraced their phylogenetic history. We generated DCR knockout lines in the model diatom species Phaeodactylum tricornutum and analyzed their mRNA and sRNA populations, repression-associated histone marks, and acclimatory response to nitrogen starvation. Diatoms presented a diversification of key RNAi effectors whose distribution across species suggests the presence of distinct RNAi pathways. P. tricornutum DCR was found to process 26-31-nt-long double-stranded sRNAs originating mostly from transposons covered by repression-associated epigenetic marks. In parallel, P. tricornutum DCR was necessary for the maintenance of the repression-associated histone marks H3K9me2/3 and H3K27me3. Finally, PtDCR-KO lines presented a compromised recovery post nitrogen starvation suggesting a role for P. tricornutum DCR in the acclimation to nutrient stress. Our study characterized the molecular function of the single DCR homolog of P. tricornutum suggesting an association between RNAi and heterochromatin maintenance in this model diatom species.

Building alternative splicing and evolution-aware sequence-structure maps for protein repeats.

Alternative splicing of repeats in proteins provides a mechanism for rewiring and fine-tuning protein interaction networks. In this work, we developed a robust and versatile method, ASPRING, to identify alternatively spliced protein repeats from gene annotations. ASPRING leverages evolutionary meaningful alternative splicing-aware hierarchical graphs to provide maps between protein repeats sequences and 3D structures. We re-think the definition of repeats by explicitly accounting for transcript diversity across several genes/species. Using a stringent sequence-based similarity criterion, we detected over 5,000 evolutionary conserved repeats by screening virtually all human protein-coding genes and their orthologs across a dozen species. Through a joint analysis of their sequences and structures, we extracted specificity-determining sequence signatures and assessed their implication in experimentally resolved and modelled protein interactions. Our findings demonstrate the widespread alternative usage of protein repeats in modulating protein interactions and open avenues for targeting repeat-mediated interactions.

ASES: visualizing evolutionary conservation of alternative splicing in proteins.

SUMMARY: ASES is a versatile tool for assessing the impact of alternative splicing (AS), initiation and termination of transcription on protein diversity in evolution. It identifies exon and transcript orthogroups from a set of input genes/species for comparative transcriptomics analyses. It computes an evolutionary splicing graph, where the nodes are exon orthogroups, allowing for a direct evaluation of AS conservation. It also reconstructs a transcripts' phylogenetic forest to date the appearance of specific transcripts and explore the events that have shaped them. ASES web server features a highly interactive interface enabling the synchronous selection of events, exons or transcripts in the different outputs, and the visualization and retrieval of the corresponding amino acid sequences, for subsequent 3D structure prediction. AVAILABILITY AND IMPLEMENTATION: http://www.lcqb.upmc.fr/Ases. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance.

SUMMARY: The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast. AVAILABILITY AND IMPLEMENTATION: CovRadar is freely accessible at https://covradar.net, its open-source code is available at https://gitlab.com/dacs-hpi/covradar. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Advancing Precision Vaccinology by Molecular and Genomic Surveillance of Severe Acute Respiratory Syndrome Coronavirus 2 in Germany, 2021.

BACKGROUND: Comprehensive pathogen genomic surveillance represents a powerful tool to complement and advance precision vaccinology. The emergence of the Alpha variant in December 2020 and the resulting efforts to track the spread of this and other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern led to an expansion of genomic sequencing activities in Germany. METHODS: At Robert Koch Institute (RKI), the German National Institute of Public Health, we established the Integrated Molecular Surveillance for SARS-CoV-2 (IMS-SC2) network to perform SARS-CoV-2 genomic surveillance at the national scale, SARS-CoV-2-positive samples from laboratories distributed across Germany regularly undergo whole-genome sequencing at RKI. RESULTS: We report analyses of 3623 SARS-CoV-2 genomes collected between December 2020 and December 2021, of which 3282 were randomly sampled. All variants of concern were identified in the sequenced sample set, at ratios equivalent to those in the 100-fold larger German GISAID sequence dataset from the same time period. Phylogenetic analysis confirmed variant assignments. Multiple mutations of concern emerged during the observation period. To model vaccine effectiveness in vitro, we employed authentic-virus neutralization assays, confirming that both the Beta and Zeta variants are capable of immune evasion. The IMS-SC2 sequence dataset facilitated an estimate of the SARS-CoV-2 incidence based on genetic evolution rates. Together with modeled vaccine efficacies, Delta-specific incidence estimation indicated that the German vaccination campaign contributed substantially to a deceleration of the nascent German Delta wave. CONCLUSIONS: SARS-CoV-2 molecular and genomic surveillance may inform public health policies including vaccination strategies and enable a proactive approach to controlling coronavirus disease 2019 spread as the virus evolves.

Bacillus Calmette-Guerin vaccination and multiple sclerosis: A population-based birth cohort study in Quebec, Canada.

BACKGROUND AND PURPOSE: The bacillus Calmette-Guerin (BCG) vaccine could reduce the incidence of multiple sclerosis (MS) through immunomodulation. Previous studies, presenting some limitations, reported no association. We re-examined this association in a large cohort focusing on relapsing-remitting MS (RRMS). METHODS: The cohort included 400,563 individuals, and was linked with the Quebec provincial BCG vaccination registry and administrative health data. Individuals were followed up from 1983 to 2014 and then within Period 1 (1983-1996) and Period 2 (1997-2014), for the occurrence of MS. Incident MS cases were defined as those with ≥3 hospital or physician claims for MS. Subjects with ≥1 drug reimbursement for MS disease-modifying therapies were classified as RRMS. Cox proportional hazards regression was used to estimate hazard ratios (HRs) over the follow-ups, adjusting for potential confounders. Possible effect modification due to sex was assessed. RESULTS: A total of 178,335 (46%) individuals were BCG vaccinated. There were 274 (0.06%) incident MS cases identified in 1983-1996, and 1433 (0.4%) in 1997-2014. No association was found with RRMS, either in Period 1 (adjusted HR [HRadj ] = 0.96, 95% confidence interval [CI] = 0.63-1.45; 96 cases) or in Period 2 (HRadj  = 1.02, 95% CI = 0.85-1.23; 480 cases). The remaining MS cases, for whom the phenotype was unknown, were positively associated with BCG over the entire follow-up (HRadj  = 1.25, 95% CI = 1.10-1.41; 1131 cases) and in Period 2 (HRadj  = 1.33, 95% CI = 1.17-1.52; 953 cases). No interaction with sex was found. CONCLUSIONS: Findings suggest that BCG vaccination does not decrease the risk of RRMS, and that future studies should consider phenotypes of MS.

Association between Bacillus Calmette-Guerin vaccination and type 1 diabetes in adolescence: A population-based birth cohort study in Quebec, Canada.

The Bacillus Calmette-Guerin (BCG) vaccine could reduce the incidence of type 1 diabetes through non-specific immunomodulation. Previous epidemiological studies, presenting some limitations, report no association. We examined this association of early life BCG vaccination and age at vaccination with type 1 diabetes incidence in adolescence in a large representative cohort in Quebec. The cohort included 387,704 individuals born in Quebec between 1970 and 1974 whose BCG vaccination status was determined from a provincial registry. Individuals were followed up from 1985 to their 19th birthday (maximum to 1993) for their use of physician services. Individuals were defined as type 1 diabetes cases if they had ≥4 related physician claims over a 2-year period, with at least 30 days between two claims. Cox proportional hazards regression was used to estimate the association of BCG vaccination and age at vaccination with type 1 diabetes. Covariates were selected based on a directed acyclic graph. Interaction according to sex was evaluated. A total of 178,133 (45.9%) individuals were vaccinated and 442 (0.11%) incident cases of type 1 diabetes were identified. The risk of type 1 diabetes was similar in vaccinated compared with unvaccinated individuals (adjusted hazard ratio = 1.06 [95% CI: 0.88-1.29]). There was no association with age at vaccination, and results did not differ by sex (Interaction, p = 0.60). Our results suggest that BCG vaccination does not prevent type 1 diabetes in adolescence.

General and abdominal obesity trajectories across adulthood, and risk of prostate cancer: results from the PROtEuS study, Montreal, Canada.

PURPOSE: Greater body fatness is a probable cause of advanced prostate cancer (PCa). Body fat distribution and timing of exposure may be relevant. We investigated associations between body size trajectories and PCa incidence in a population-based case-control study in Montreal, Canada. METHODS: Cases (n = 1,931), aged ≤ 75 years, were diagnosed with PCa in 2005-2009; 1,994 controls were selected from the electoral list. Interviews were conducted to assess body mass index (BMI) and Stunkard's silhouette at ages 20, 40, 50, 60 years, and before interview. Current waist and hip circumferences were measured, and a predictive model estimated waist circumference in the past. BMI and waist circumference trajectories were determined to identify subgroups. Logistic regression estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between anthropometric indicators and PCa. RESULTS: Subjects with a current BMI ≥ 30 kg/m2 had a lower risk of overall PCa (OR 0.71, 95% CI 0.59-0.85). Associations with adult BMI followed similar trends for less and more aggressive tumors, with stronger inverse relationships in early adulthood. Contrastingly, current waist circumference ≥ 102 cm was associated with elevated risk of high-grade PCa (OR 1.33, 95% CI 1.03-1.71). Men with increasing BMI or waist circumference adult trajectories had a lower risk of PCa, especially low-grade, than those in the normal-stable range. This was especially evident among men in the obese-increase group for BMI and waist circumference. CONCLUSION: Abdominal obesity increased the risk of aggressive PCa. The inverse relationship between body size trajectories and PCa may reflect PSA hemodilution, lower detection, and/or a true etiological effect.

Targeted domain assembly for fast functional profiling of metagenomic datasets with S3A.

MOTIVATION: The understanding of the ever-increasing number of metagenomic sequences accumulating in our databases demands for approaches that rapidly 'explore' the content of multiple and/or large metagenomic datasets with respect to specific domain targets, avoiding full domain annotation and full assembly. RESULTS: S3A is a fast and accurate domain-targeted assembler designed for a rapid functional profiling. It is based on a novel construction and a fast traversal of the Overlap-Layout-Consensus graph, designed to reconstruct coding regions from domain annotated metagenomic sequence reads. S3A relies on high-quality domain annotation to efficiently assemble metagenomic sequences and on the design of a new confidence measure for a fast evaluation of overlapping reads. Its implementation is highly generic and can be applied to any arbitrary type of annotation. On simulated data, S3A achieves a level of accuracy similar to that of classical metagenomics assembly tools while permitting to conduct a faster and sensitive profiling on domains of interest. When studying a few dozens of functional domains-a typical scenario-S3A is up to an order of magnitude faster than general purpose metagenomic assemblers, thus enabling the analysis of a larger number of datasets in the same amount of time. S3A opens new avenues to the fast exploration of the rapidly increasing number of metagenomic datasets displaying an ever-increasing size. AVAILABILITY AND IMPLEMENTATION: S3A is available at http://www.lcqb.upmc.fr/S3A_ASSEMBLER/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Jointly aligning a group of DNA reads improves accuracy of identifying large deletions.

Performing sequence alignment to identify structural variants, such as large deletions, from genome sequencing data is a fundamental task, but current methods are far from perfect. The current practice is to independently align each DNA read to a reference genome. We show that the propensity of genomic rearrangements to accumulate in repeat-rich regions imposes severe ambiguities in these alignments, and consequently on the variant calls-with current read lengths, this affects more than one third of known large deletions in the C. Venter genome. We present a method to jointly align reads to a genome, whereby alignment ambiguity of one read can be disambiguated by other reads. We show this leads to a significant improvement in the accuracy of identifying large deletions (≥20 bases), while imposing minimal computational overhead and maintaining an overall running time that is at par with current tools. A software implementation is available as an open-source Python program called JRA at https://bitbucket.org/jointreadalignment/jra-src.

Night-Shift Work and Risk of Prostate Cancer: Results From a Canadian Case-Control Study, the Prostate Cancer and Environment Study.

Night-shift work involving disruption of circadian rhythms has been associated with breast cancer risk. A role in prostate cancer is also suspected, but evidence is limited. We investigated the association between night-shift work and prostate cancer incidence in the Prostate Cancer and Environment Study (PROtEuS), a population-based case-control study conducted in 2005-2012 in Montreal, Quebec, Canada. Participants were 1,904 prostate cancer cases (432 high-grade cancers) and 1,965 population controls. Detailed work schedules for each job held for at least 2 years (n = 15,724) were elicited in face-to-face interviews. Night-shift work was defined as having ever worked ≥3 hours between midnight and 5:00 am ≥3 nights/month for ≥1 year. Unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals for the association between night-shift work and prostate cancer, adjusting for age, ancestry, and education. No association was found between overall prostate cancer and night-shift work metrics, including ever exposure, duration, intensity, cumulative exposure, rotating shifts, and early-morning shifts. For none of the exposure indices was there evidence of heterogeneity in odds ratios between low- and high-grade cancers. Sensitivity analyses restricting exposures to ≥7 nights/month or considering screening history yielded similar results. Our findings lend no support for a major role of night-shift work in prostate cancer development.

Meet-U: Educating through research immersion.

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master's students in bioinformatics and modeling, with protein-protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org.

A hybrid expert approach for retrospective assessment of occupational exposures in a population-based case-control study of cancer.

BACKGROUND: While the expert-based occupational exposure assessment approach has been considered the reference method for retrospective population-based studies, its implementation in large study samples has become prohibitive. To facilitate its application and improve upon it we developed, in the context of a Montreal population-based study of prostate cancer (PROtEuS), a hybrid approach combining job-exposure profiles (JEPs) summarizing expert evaluations from previous studies and expert review. We aim to describe the hybrid expert method and its impacts on the exposures assigned in PROtEuS compared to those from a previous study coded using the traditional expert method. METHODS: Applying the hybrid approach, experts evaluated semi-quantitative levels of confidence, concentration and frequency of exposure to 313 agents for 16,065 jobs held by 4005 subjects in PROtEuS. These assessments were compared to those from a different set of jobs coded in an earlier study of lung cancer, conducted on the same study base, for 90 blue-collar occupations and 203 agents. Endpoints evaluated included differences in the number of exposures and in the distribution of ratings across jobs, and the within-occupation variability in exposure. RESULTS: Compared to jobs from the lung cancer study, jobs in PROtEuS had on average 0.3 more exposures. PROtEuS exposures were more often assigned definite confidence ratings, but concentration and frequency levels tended to be lower. The within-occupation variability in ratings assigned to jobs were lower in PROtEuS jobs for all metrics. This was particularly evident for concentration, although considerable variability remained with over 40% of occupation/agent cells in PROtEuS exposed at different levels. The hybrid approach reduced coding time by half, compared to the traditional expert assessment. CONCLUSIONS: The new hybrid expert approach improved on efficiency and transparency, and resulted in greater confidence in assessments, compared to the traditional expert method applied in an earlier study involving a similar set of jobs. Assigned ratings were more homogeneous with the hybrid approach, possibly reflecting clearer guidelines for coding, greater coherence between experts and/or reliance on summaries of past assessments. Nevertheless, significant within-occupation variability remained with the hybrid approach, suggesting that experts took into account job-specific factors in their assessments.

DiNAMO: highly sensitive DNA motif discovery in high-throughput sequencing data.

BACKGROUND: Discovering over-represented approximate motifs in DNA sequences is an essential part of bioinformatics. This topic has been studied extensively because of the increasing number of potential applications. However, it remains a difficult challenge, especially with the huge quantity of data generated by high throughput sequencing technologies. To overcome this problem, existing tools use greedy algorithms and probabilistic approaches to find motifs in reasonable time. Nevertheless these approaches lack sensitivity and have difficulties coping with rare and subtle motifs. RESULTS: We developed DiNAMO (for DNA MOtif), a new software based on an exhaustive and efficient algorithm for IUPAC motif discovery. We evaluated DiNAMO on synthetic and real datasets with two different applications, namely ChIP-seq peaks and Systematic Sequencing Error analysis. DiNAMO proves to compare favorably with other existing methods and is robust to noise. CONCLUSIONS: We shown that DiNAMO software can serve as a tool to search for degenerate motifs in an exact manner using IUPAC models. DiNAMO can be used in scanning mode with sliding windows or in fixed position mode, which makes it suitable for numerous potential applications. AVAILABILITY: https://github.com/bonsai-team/DiNAMO .

Lifetime occupational exposure to metals and welding fumes, and risk of glioma: a 7-country population-based case-control study.

BACKGROUND: Brain tumor etiology is poorly understood. Based on their ability to pass through the blood-brain barrier, it has been hypothesized that exposure to metals may increase the risk of brain cancer. Results from the few epidemiological studies on this issue are limited and inconsistent. METHODS: We investigated the relationship between glioma risk and occupational exposure to five metals - lead, cadmium, nickel, chromium and iron- as well as to welding fumes, using data from the seven-country INTEROCC study. A total of 1800 incident glioma cases and 5160 controls aged 30-69 years were included in the analysis. Lifetime occupational exposure to the agents was assessed using the INTEROCC JEM, a modified version of the Finnish job exposure matrix FINJEM. RESULTS: In general, cases had a slightly higher prevalence of exposure to the various metals and welding fumes than did controls, with the prevalence among ever exposed ranging between 1.7 and 2.2% for cadmium to 10.2 and 13.6% for iron among controls and cases, respectively. However, in multivariable logistic regression analyses, there was no association between ever exposure to any of the agents and risk of glioma with odds ratios (95% confidence intervals) ranging from 0.8 (0.7-1.0) for lead to 1.1 (0.7-1.6) for cadmium. Results were consistent across models considering cumulative exposure or duration, as well as in all sensitivity analyses conducted. CONCLUSIONS: Findings from this large-scale international study provide no evidence for an association between occupational exposure to any of the metals under scrutiny or welding fumes, and risk of glioma.

Ulysses: accurate detection of low-frequency structural variations in large insert-size sequencing libraries.

MOTIVATION: The detection of structural variations (SVs) in short-range Paired-End (PE) libraries remains challenging because SV breakpoints can involve large dispersed repeated sequences, or carry inherent complexity, hardly resolvable with classical PE sequencing data. In contrast, large insert-size sequencing libraries (Mate-Pair libraries) provide higher physical coverage of the genome and give access to repeat-containing regions. They can thus theoretically overcome previous limitations as they are becoming routinely accessible. Nevertheless, broad insert size distributions and high rates of chimerical sequences are usually associated to this type of libraries, which makes the accurate annotation of SV challenging. RESULTS: Here, we present Ulysses, a tool that achieves drastically higher detection accuracy than existing tools, both on simulated and real mate-pair sequencing datasets from the 1000 Human Genome project. Ulysses achieves high specificity over the complete spectrum of variants by assessing, in a principled manner, the statistical significance of each possible variant (duplications, deletions, translocations, insertions and inversions) against an explicit model for the generation of experimental noise. This statistical model proves particularly useful for the detection of low frequency variants. SV detection performed on a large insert Mate-Pair library from a breast cancer sample revealed a high level of somatic duplications in the tumor and, to a lesser extent, in the blood sample as well. Altogether, these results show that Ulysses is a valuable tool for the characterization of somatic mosaicism in human tissues and in cancer genomes.

Parseq: reconstruction of microbial transcription landscape from RNA-Seq read counts using state-space models.

MOTIVATION: The most common RNA-Seq strategy consists of random shearing, amplification and high-throughput sequencing of the RNA fraction. Methods to analyze transcription level variations along the genome from the read count profiles generated by the RNA-Seq protocol are needed. RESULTS: We developed a statistical approach to estimate the local transcription levels and to identify transcript borders. This transcriptional landscape reconstruction relies on a state-space model to describe transcription level variations in terms of abrupt shifts and more progressive drifts. A new emission model is introduced to capture not only the read count variance inside a transcript but also its short-range autocorrelation and the fraction of positions with zero counts. The estimation relies on a particle Gibbs algorithm whose running time makes it more suited to microbial genomes. The approach outperformed read-overlapping strategies on synthetic and real microbial datasets. AVAILABILITY: A program named Parseq is available at: http://www.lgm.upmc.fr/parseq/. CONTACT: bodgan.mirauta@upmc.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fiona: a parallel and automatic strategy for read error correction.

MOTIVATION: Automatic error correction of high-throughput sequencing data can have a dramatic impact on the amount of usable base pairs and their quality. It has been shown that the performance of tasks such as de novo genome assembly and SNP calling can be dramatically improved after read error correction. While a large number of methods specialized for correcting substitution errors as found in Illumina data exist, few methods for the correction of indel errors, common to technologies like 454 or Ion Torrent, have been proposed. RESULTS: We present Fiona, a new stand-alone read error-correction method. Fiona provides a new statistical approach for sequencing error detection and optimal error correction and estimates its parameters automatically. Fiona is able to correct substitution, insertion and deletion errors and can be applied to any sequencing technology. It uses an efficient implementation of the partial suffix array to detect read overlaps with different seed lengths in parallel. We tested Fiona on several real datasets from a variety of organisms with different read lengths and compared its performance with state-of-the-art methods. Fiona shows a constantly higher correction accuracy over a broad range of datasets from 454 and Ion Torrent sequencers, without compromise in speed. CONCLUSION: Fiona is an accurate parameter-free read error-correction method that can be run on inexpensive hardware and can make use of multicore parallelization whenever available. Fiona was implemented using the SeqAn library for sequence analysis and is publicly available for download at http://www.seqan.de/projects/fiona. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The diversity of small non-coding RNAs in the diatom Phaeodactylum tricornutum.

BACKGROUND: Marine diatoms constitute a major component of eukaryotic phytoplankton and stand at the crossroads of several evolutionary lineages. These microalgae possess peculiar genomic features and novel combinations of genes acquired from bacterial, animal and plant ancestors. Furthermore, they display both DNA methylation and gene silencing activities. Yet, the biogenesis and regulatory function of small RNAs (sRNAs) remain ill defined in diatoms. RESULTS: Here we report the first comprehensive characterization of the sRNA landscape and its correlation with genomic and epigenomic information in Phaeodactylum tricornutum. The majority of sRNAs is 25 to 30 nt-long and maps to repetitive and silenced Transposable Elements marked by DNA methylation. A subset of this population also targets DNA methylated protein-coding genes, suggesting that gene body methylation might be sRNA-driven in diatoms. Remarkably, 25-30 nt sRNAs display a well-defined and unprecedented 180 nt-long periodic distribution at several highly methylated regions that awaits characterization. While canonical miRNAs are not detectable, other 21-25 nt sRNAs of unknown origin are highly expressed. Besides, non-coding RNAs with well-described function, namely tRNAs and U2 snRNA, constitute a major source of 21-25 nt sRNAs and likely play important roles under stressful environmental conditions. CONCLUSIONS: P. tricornutum has evolved diversified sRNA pathways, likely implicated in the regulation of largely still uncharacterized genetic and epigenetic processes. These results uncover an unexpected complexity of diatom sRNA population and previously unappreciated features, providing new insights into the diversification of sRNA-based processes in eukaryotes.