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Ribosome profiling methods are based on high-throughput sequencing of ribosome-protected mRNA footprints and allow to study in detail translational changes. Bioinformatic and statistical tools are necessary to analyze sequencing data. Here, we describe our developed methods for a fast and reliable quality control of ribosome profiling data, to efficiently visualize ribosome positions and to estimate ribosome speed in an unbiased way. The methodology described here is applicable to several genetic and environmental conditions including stress and are based on the R package RiboVIEW and calculation of quantitative estimates of local and global translation speed, based on a biophysical model of translation dynamics.

Clonal genome evolution is a key aspect for parthenogenetic species and cancer. While many studies describe precise landscapes of clonal evolution in cancer, few studies determine the underlying evolutionary parameters from molecular data, and fewer integrate theory with data. We derived theoretical results linking mutation rate, time, expansion dynamics, transition to recurrence, and survival. With this, we inferred time-resolved estimates of evolutionary parameters from mutation accumulation, mutational signatures and selection. Using this framework we traced the speciation of the rapidly emerging and invasive marbled crayfish to a time window between 1947 and 1996, which is consistent with biological records. In glioblastoma samples, we determined tumor expansion patterns, and tumor cell survival ratio at resection. Interestingly, our results suggest that the expansion pattern in the primary tumor is predictive of the progress and time to recurrence. In addition, tumor cell survival was always higher after resection and was associated with the expansion pattern and time to recurrence. We further observed selection events in a subset of tumors, with longer and purifying-only selection phases in recurrent tumors. In conclusion, our framework allowed a time-resolved, integrated analysis of key parameters in clonally evolving genomes, and provided novel insights into the evolutionary age of marbled crayfish and the progression of glioblastoma.

Methylation of carbon‐5 of cytosines (m5C) is a post‐transcriptional nucleotide modification of RNA found in all kingdoms of life. While individual m5C‐methyltransferases have been studied, the impact of the global cytosine‐5 methylome on development, homeostasis and stress remains unknown. Here, using Caenorhabditis elegans, we generated the first organism devoid of m5C in RNA, demonstrating that this modification is non‐essential. Using this genetic tool, we determine the localisation and enzymatic specificity of m5C sites in the RNome in vivo. We find that NSUN‐4 acts as a dual rRNA and tRNA methyltransferase in C. elegans mitochondria. In agreement with leucine and proline being the most frequently methylated tRNA isoacceptors, loss of m5C impacts the decoding of some triplets of these two amino acids, leading to reduced translation efficiency. Upon heat stress, m5C loss leads to ribosome stalling at UUG triplets, the only codon translated by an m5C34‐modified tRNA. This leads to reduced translation efficiency of UUG‐rich transcripts and impaired fertility, suggesting a role of m5C tRNA wobble methylation in the adaptation to higher temperatures., Analysis of worm mutants devoid of m5C RNA modifications uncovers their contribution to efficient Leu/Pro codon translation, and requirement for fertility‐supporting Leu‐UUG decoding at higher temperatures.

Enzymes of the cytosine-5 RNA methyltransferase Trm4/NSun2 family methylate tRNAs at C48 and C49 in multiple tRNAs, as well as C34 and C40 in selected tRNAs. In contrast to most other organisms, fission yeast Schizosaccharomyces pombe carries two Trm4/NSun2 homologs, Trm4a (SPAC17D4.04) and Trm4b (SPAC23C4.17). Here, we have employed tRNA methylome analysis to determine the dependence of cytosine-5 methylation (m5C) tRNA methylation in vivo on the two enzymes. Remarkably, Trm4a is responsible for all C48 methylation, which lies in the tRNA variable loop, as well as for C34 in tRNALeuCAA and tRNAProCGG, which are at the anticodon wobble position. Conversely, Trm4b methylates C49 and C50, which both lie in the TΨC-stem. Thus, S. pombe show an unusual separation of activities of the NSun2/Trm4 enzymes that are united in a single enzyme in other eukaryotes like humans, mice and Saccharomyces cerevisiae. Furthermore, in vitro activity assays showed that Trm4a displays intron-dependent methylation of C34, whereas Trm4b activity is independent of the intron. The absence of Trm4a, but not Trm4b, causes a mild resistance of S. pombe to calcium chloride.

RNA cytosine-5 methylation (m(5)C) has emerged as a key epitranscriptomic mark, which fulfills multiple roles in structural modulation, stress signaling and the regulation of protein translation. Bisulfite sequencing is currently the most accurate and reliable method to detect m(5)C marks at nucleotide resolution. Targeted bisulfite sequencing allows m(5)C detection at single base resolution, by combining the use of tailored primers with bisulfite treatment. A number of computational tools currently exist to analyse m(5)C marks in DNA bisulfite sequencing. However, these methods are not directly applicable to the analysis of RNA m(5)C marks, because DNA analysis focuses on CpG methylation, and because artifactual unconversion and misamplification in RNA can obscure actual methylation signals. We describe a pipeline designed specifically for RNA cytosine-5 methylation analysis in targeted bisulfite sequencing experiments. The pipeline is directly applicable to Illumina MiSeq (or equivalent) sequencing datasets using a web interface (hups://bisamp.dkfz.de), and is defined by optimized mapping parameters and the application of tailored filters for the removal of artifacts. We provide examples for the application of this pipeline in the unambiguous detection of m(5)C marks in tRNAs from mouse embryonic stem cells and neuron-differentiated stem cells as well as in 28S rRNA from human fibroblasts. Finally, we also discuss the adaptability of BisAMP to the analysis of DNA methylation. Our pipeline provides an accurate, fast and user-friendly framework for the analysis of cytosine-5 methylation in amplicons from bisulfite-treated RNA.

The relationship between genetic variability and individual phenotypes is usually investigated by testing for association relying on called genotypes. Allele counts obtained from next-generation sequence data could be used for this purpose too. Genetic association can be examined by treating alternative allele counts (AACs) as the response variable in negative binomial regression. AACs from sequence data often contain an excess of zeros, thus motivating the use of Hurdle and zero-inflated models. Here we examine rough type I error rates and the ability to pick out variants with small probability values for 7 different testing approaches that incorporate AACs as an explanatory or as a response variable. Model comparisons relied on chromosome 3 DNA sequence data from 407 Hispanic participants in the Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) project 1 with complete information on diastolic blood pressure and related medication. Our results suggest that in the investigation of the relationship between AAC as response variable and individual phenotypes as explanatory variable, Hurdle-negative binomial regression has some advantages. This model showed a good ability to discriminate strongly associated variants and controlled overall type I error rates. However, probability values from Hurdle-negative binomial regression were not obtained for approximately 25 % of the investigated variants because of convergence problems, and the mass of the probability value distribution was concentrated around 1.

Global protein translation as well as translation at the codon level can be regulated by tRNA modifications. In eukaryotes, levels of tRNA queuosinylation reflect the bioavailability of the precursor queuine, which is salvaged from the diet and gut microbiota. We show here that nutritionally determined Q‐tRNA levels promote Dnmt2‐mediated methylation of tRNA Asp and control translational speed of Q‐decoded codons as well as at near‐cognate codons. Deregulation of translation upon queuine depletion results in unfolded proteins that trigger endoplasmic reticulum stress and activation of the unfolded protein response, both in cultured human cell lines and in germ‐free mice fed with a queuosine‐deficient diet. Taken together, our findings comprehensively resolve the role of this anticodon tRNA modification in the context of native protein translation and describe a novel mechanism that links nutritionally determined modification levels to effective polypeptide synthesis and cellular homeostasis.

Cytosine-5 RNA methylation plays an important role in several biologically and pathologically relevant processes. However, owing to methodological limitations, the transcriptome-wide distribution of this mark has remained largely unknown. We previously established RNA bisulfite sequencing as a method for the analysis of RNA cytosine-5 methylation patterns at single-base resolution. More recently, next-generation sequencing has provided opportunities to establish transcriptome-wide maps of this modification. Here we present a computational approach that integrates tailored filtering and data-driven statistical modeling to eliminate many of the artifacts that are known to be associated with bisulfite sequencing. Using RNAs from mouse embryonic stem cells we performed a comprehensive methylation analysis of mouse tRNAs, rRNAs and mRNAs. Our approach identified all known methylation marks in tRNA and two previously unknown but evolutionary conserved marks in 28S rRNA. In addition, mRNAs were found to be very sparsely methylated or not methylated at all. Finally, the tRNA-specific activity of the DNMT2 methyltransferase could be resolved at single-base resolution, which provided important further validation. Our approach can be used to profile cytosine-5 RNA methylation patterns in many experimental contexts and will be important for understanding the function of cytosine-5 RNA methylation in RNA biology and in human disease.

Recently, newly developed ribosome profiling methods based on high-throughput sequencing of ribosome-protected mRNA footprints allow to study genome-wide translational changes in detail. However, computational analysis of the sequencing data still represents a bottleneck for many laboratories. Further, specific pipelines for quality control and statistical analysis of ribosome profiling data, providing high levels of both accuracy and confidence, are currently lacking. In this study, we describe automated bioinformatic and statistical diagnoses to perform robust quality control of ribosome profiling data (RiboQC), to efficiently visualize ribosome positions and to estimate ribosome speed (RiboMine) in an unbiased way. We present an R pipeline to setup and undertake the analyses that offers the user an HTML page to scan own data regarding the following aspects: periodicity, ligation and digestion of footprints; reproducibility and batch effects of replicates; drug-related artifacts; unbiased codon enrichment including variability between mRNAs, for A, P and E sites; mining of some causal or confounding factors. We expect our pipeline to allow an optimal use of the wealth of information provided by ribosome profiling experiments.

Background Treatment with 5-fluorouracil (5-FU) is known to improve survival in many cancers including colorectal cancer. Response to the treatment, overall survival and recurrence show inter-individual variation. Methods In this study we employed a strategy to search eQTL variants influencing the expression of a large number of genes. We identified four single nucleotide polymorphisms, defined as master regulators of transcription, and genotyped them in a set of 218 colorectal cancer patients undergoing adjuvant 5-FU based therapy. Results Our results showed that the minor allele variant of the rs4846126 polymorphism was associated with poor overall and progression-free survival. Patients that were homozygous for the variant allele showed an over two fold increased risk of death (HR 2.20 95%CI 1.05–4.60) and progression (HR 2.88, 95% 1.47–5.63). The integration of external information from publicly available gene expression repositories suggested that the rs4846126 polymorphism deserves further investigation. This variant potentially regulates the gene expression of 273 genes with some of them possibly associated to the patient's response to 5-FU treatment or colorectal cancer. Conclusions Present results show that mining of public data repositories in combination with own data can be a fruitful approach to identify markers that affect therapy outcome. In particular, a genetic screen of master regulators may help in order to search for the polymorphisms involved in treatment response in cancer patients.

The marbled crayfish (Procambarus virginalis) represents a very recently evolved parthenogenetic freshwater crayfish species that has invaded diverse habitats in Europe and in Madagascar. However, population genetic analyses have been hindered by the homogeneous genetic structure of the population and the lack of suitable tools for data analysis. We have used whole-genome sequencing to characterize reference specimens from various known wild populations. In parallel, we established a whole-genome sequencing data analysis pipeline for the population genetic analysis of nearly monoclonal genomes. Our results provide evidence for systematic genetic differences between geographically separated populations and illustrate the emerging differentiation of the marbled crayfish genome. We also used mark-recapture population size estimation in combination with genetic data to model the growth pattern of marbled crayfish populations. Our findings uncover evolutionary dynamics in the marbled crayfish genome over a very short evolutionary timescale and identify the rapid growth of marbled crayfish populations as an important factor for ecological monitoring., Olena Maiakovska et al. provide whole-genome sequencing of the parthenogenetic and invasive marbled crayfish and develop a computational framework for data analysis of monoclonal genomes. These data and methodology allow the authors to demonstrate genetic separation between two populations and provide the first size estimate for a marbled crayfish colony, which they used to model population growth patterns.