TALC: Transcript-level Aware Long-read Correction.

MOTIVATION: Long-read sequencing technologies are invaluable for determining complex RNA transcript architectures but are error-prone. Numerous 'hybrid correction' algorithms have been developed for genomic data that correct long reads by exploiting the accuracy and depth of short reads sequenced from the same sample. These algorithms are not suited for correcting more complex transcriptome sequencing data. RESULTS: We have created a novel reference-free algorithm called Transcript-level Aware Long-Read Correction (TALC) which models changes in RNA expression and isoform representation in a weighted De Bruijn graph to correct long reads from transcriptome studies. We show that transcript-level aware correction by TALC improves the accuracy of the whole spectrum of downstream RNA-seq applications and is thus necessary for transcriptome analyses that use long read technology. AVAILABILITY AND IMPLEMENTATION: TALC is implemented in C++ and available at https://github.com/lbroseus/TALC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

GECKO is a genetic algorithm to classify and explore high throughput sequencing data.

Comparative analysis of high throughput sequencing data between multiple conditions often involves mapping of sequencing reads to a reference and downstream bioinformatics analyses. Both of these steps may introduce heavy bias and potential data loss. This is especially true in studies where patient transcriptomes or genomes may vary from their references, such as in cancer. Here we describe a novel approach and associated software that makes use of advances in genetic algorithms and feature selection to comprehensively explore massive volumes of sequencing data to classify and discover new sequences of interest without a mapping step and without intensive use of specialized bioinformatics pipelines. We demonstrate that our approach called GECKO for GEnetic Classification using k-mer Optimization is effective at classifying and extracting meaningful sequences from multiple types of sequencing approaches including mRNA, microRNA, and DNA methylome data.

IRFinder: assessing the impact of intron retention on mammalian gene expression.

Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. We have developed a program and database called IRFinder to accurately detect IR from mRNA sequencing data. Analysis of 2573 samples showed that IR occurs in all tissues analyzed, affects over 80% of all coding genes and is associated with cell differentiation and the cell cycle. Frequently retained introns are enriched for specific RNA binding protein sites and are often retained in clusters in the same gene. IR is associated with lower protein levels and intron-retaining transcripts that escape nonsense-mediated decay are not actively translated.

Coordinate redeployment of PRC1 proteins suppresses tumor formation during Drosophila development.

Polycomb group proteins form two main complexes, PRC2 and PRC1, which generally coregulate their target genes. Here we show that PRC1 components act as neoplastic tumor suppressors independently of PRC2 function. By mapping the distribution of PRC1 components and trimethylation of histone H3 at Lys27 (H3K27me3) across the genome, we identify a large set of genes that acquire PRC1 in the absence of H3K27me3 in Drosophila larval tissues. These genes massively outnumber canonical targets and are mainly involved in the regulation of cell proliferation, signaling and polarity. Alterations in PRC1 components specifically deregulate this set of genes, whereas canonical targets are derepressed in both PRC1 and PRC2 mutants. In human embryonic stem cells, PRC1 components colocalize with H3K27me3 as in Drosophila embryos, whereas in differentiated cell types they are selectively recruited to a large set of proliferation and signaling-associated genes that lack H3K27me3, suggesting that the redeployment of PRC1 components during development is evolutionarily conserved.

Cooperativity, specificity, and evolutionary stability of Polycomb targeting in Drosophila.

Metazoan genomes are partitioned into modular chromosomal domains containing active or repressive chromatin. In flies, Polycomb group (PcG) response elements (PREs) recruit PHO and other DNA-binding factors and act as nucleation sites for the formation of Polycomb repressive domains. The sequence specificity of PREs is not well understood. Here, we use comparative epigenomics and transgenic assays to show that Drosophila domain organization and PRE specification are evolutionarily conserved despite significant cis-element divergence within Polycomb domains, whereas cis-element evolution is strongly correlated with transcription factor binding divergence outside of Polycomb domains. Cooperative interactions of PcG complexes and their recruiting factor PHO stabilize PHO recruitment to low-specificity sequences. Consistently, PHO recruitment to sites within Polycomb domains is stabilized by PRC1. These data suggest that cooperative rather than hierarchical interactions among low-affinity sequences, DNA-binding factors, and the Polycomb machinery are giving rise to specific and strongly conserved 3D structures in Drosophila.

Identification of regulators of the three-dimensional polycomb organization by a microscopy-based genome-wide RNAi screen.

Polycomb group (PcG) proteins dynamically define cellular identities through epigenetic repression of key developmental genes. PcG target gene repression can be stabilized through the interaction in the nucleus at PcG foci. Here, we report the results of a high-resolution microscopy genome-wide RNAi screen that identifies 129 genes that regulate the nuclear organization of Pc foci. Candidate genes include PcG components and chromatin factors, as well as many protein-modifying enzymes, including components of the SUMOylation pathway. In the absence of SUMO, Pc foci coagulate into larger aggregates. Conversely, loss of function of the SUMO peptidase Velo disperses Pc foci. Moreover, SUMO and Velo colocalize with PcG proteins at PREs, and Pc SUMOylation affects its chromatin targeting, suggesting that the dynamic regulation of Pc SUMOylation regulates PcG-mediated silencing by modulating the kinetics of Pc binding to chromatin as well as its ability to form Polycomb foci.

Analysis of replication profiles reveals key role of RFC-Ctf18 in yeast replication stress response.

Maintenance of genome integrity relies on surveillance mechanisms that detect and signal arrested replication forks. Although evidence from budding yeast indicates that the DNA replication checkpoint (DRC) is primarily activated by single-stranded DNA (ssDNA), studies in higher eukaryotes have implicated primer ends in this process. To identify factors that signal primed ssDNA in Saccharomyces cerevisiae, we have screened a collection of checkpoint mutants for their ability to activate the DRC, using the repression of late origins as readout for checkpoint activity. This quantitative analysis reveals that neither RFC(Rad24) and the 9-1-1 clamp nor the alternative clamp loader RFC(Elg1) is required to signal paused forks. In contrast, we found that RFC(Ctf18) is essential for the Mrc1-dependent activation of Rad53 and for the maintenance of paused forks. These data identify RFC(Ctf18) as a key DRC mediator, potentially bridging Mrc1 and primed ssDNA to signal paused forks.

Topoisomerase I suppresses genomic instability by preventing interference between replication and transcription.

Topoisomerase I (Top1) is a key enzyme in functioning at the interface between DNA replication, transcription and mRNA maturation. Here, we show that Top1 suppresses genomic instability in mammalian cells by preventing a conflict between transcription and DNA replication. Using DNA combing and ChIP (chromatin immunoprecipitation)-on-chip, we found that Top1-deficient cells accumulate stalled replication forks and chromosome breaks in S phase, and that breaks occur preferentially at gene-rich regions of the genome. Notably, these phenotypes were suppressed by preventing the formation of RNA-DNA hybrids (R-loops) during transcription. Moreover, these defects could be mimicked by depletion of the splicing factor ASF/SF2 (alternative splicing factor/splicing factor 2), which interacts functionally with Top1. Taken together, these data indicate that Top1 prevents replication fork collapse by suppressing the formation of R-loops in an ASF/SF2-dependent manner. We propose that interference between replication and transcription represents a major source of spontaneous replication stress, which could drive genomic instability during the early stages of tumorigenesis.