Time-resolved, integrated analysis of clonally evolving genomes.

Clonal genome evolution is a key feature of asexually reproducing species and human cancer development. While many studies have described the landscapes of clonal genome evolution in cancer, few determine the underlying evolutionary parameters from molecular data, and even fewer integrate theory with data. We derived theoretical results linking mutation rate, time, expansion dynamics, and biological/clinical parameters. Subsequently, we inferred time-resolved estimates of evolutionary parameters from mutation accumulation, mutational signatures and selection. We then applied this framework to predict the time of speciation of the marbled crayfish, an enigmatic, globally invasive parthenogenetic freshwater crayfish. The results predict that speciation occurred between 1986 and 1990, which is consistent with biological records. We also used our framework to analyze whole-genome sequencing datasets from primary and relapsed glioblastoma, an aggressive brain tumor. The results identified evolutionary subgroups and showed that tumor cell survival could be inferred from genomic data that was generated during the resection of the primary tumor. 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.

Queuosine-tRNA promotes sex-dependent learning and memory formation by maintaining codon-biased translation elongation speed.

Queuosine (Q) is a modified nucleoside at the wobble position of specific tRNAs. In mammals, queuosinylation is facilitated by queuine uptake from the gut microbiota and is introduced into tRNA by the QTRT1-QTRT2 enzyme complex. By establishing a Qtrt1 knockout mouse model, we discovered that the loss of Q-tRNA leads to learning and memory deficits. Ribo-Seq analysis in the hippocampus of Qtrt1-deficient mice revealed not only stalling of ribosomes on Q-decoded codons, but also a global imbalance in translation elongation speed between codons that engage in weak and strong interactions with their cognate anticodons. While Q-dependent molecular and behavioral phenotypes were identified in both sexes, female mice were affected more severely than males. Proteomics analysis confirmed deregulation of synaptogenesis and neuronal morphology. Together, our findings provide a link between tRNA modification and brain functions and reveal an unexpected role of protein synthesis in sex-dependent cognitive performance.

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets.

Conventional dimensionality reduction methods like Multidimensional Scaling (MDS) are sensitive to the presence of orthogonal outliers, leading to significant defects in the embedding. We introduce a robust MDS method, called DeCOr-MDS (Detection and Correction of Orthogonal outliers using MDS), based on the geometry and statistics of simplices formed by data points, that allows to detect orthogonal outliers and subsequently reduce dimensionality. We validate our methods using synthetic datasets, and further show how it can be applied to a variety of large real biological datasets, including cancer image cell data, human microbiome project data and single cell RNA sequencing data, to address the task of data cleaning and visualization.

Analysis of Ribosome Profiling Data.

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.

Genome analysis of the monoclonal marbled crayfish reveals genetic separation over a short evolutionary timescale.

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.

Translational adaptation to heat stress is mediated by RNA 5-methylcytosine in Caenorhabditis elegans.

Methylation of carbon-5 of cytosines (m5 C) is a post-transcriptional nucleotide modification of RNA found in all kingdoms of life. While individual m5 C-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 m5 C in RNA, demonstrating that this modification is non-essential. Using this genetic tool, we determine the localisation and enzymatic specificity of m5 C 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 m5 C impacts the decoding of some triplets of these two amino acids, leading to reduced translation efficiency. Upon heat stress, m5 C loss leads to ribosome stalling at UUG triplets, the only codon translated by an m5 C34-modified tRNA. This leads to reduced translation efficiency of UUG-rich transcripts and impaired fertility, suggesting a role of m5 C tRNA wobble methylation in the adaptation to higher temperatures.

RiboVIEW: a computational framework for visualization, quality control and statistical analysis of ribosome profiling data.

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.

Queuine links translational control in eukaryotes to a micronutrient from bacteria.

In eukaryotes, the wobble position of tRNA with a GUN anticodon is modified to the 7-deaza-guanosine derivative queuosine (Q34), but the original source of Q is bacterial, since Q is synthesized by eubacteria and salvaged by eukaryotes for incorporation into tRNA. Q34 modification stimulates Dnmt2/Pmt1-dependent C38 methylation (m5C38) in the tRNAAsp anticodon loop in Schizosaccharomyces pombe. Here, we show by ribosome profiling in S. pombe that Q modification enhances the translational speed of the C-ending codons for aspartate (GAC) and histidine (CAC) and reduces that of U-ending codons for asparagine (AAU) and tyrosine (UAU), thus equilibrating the genome-wide translation of synonymous Q codons. Furthermore, Q prevents translation errors by suppressing second-position misreading of the glycine codon GGC, but not of wobble misreading. The absence of Q causes reduced translation of mRNAs involved in mitochondrial functions, and accordingly, lack of Q modification causes a mitochondrial defect in S. pombe. We also show that Q-dependent stimulation of Dnmt2 is conserved in mice. Our findings reveal a direct mechanism for the regulation of translational speed and fidelity in eukaryotes by a nutrient originating from bacteria.

Division of labour: tRNA methylation by the NSun2 tRNA methyltransferases Trm4a and Trm4b in fission yeast.

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.

BisAMP: A web-based pipeline for targeted RNA cytosine-5 methylation analysis.

RNA cytosine-5 methylation (m5C) 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 m5C marks at nucleotide resolution. Targeted bisulfite sequencing allows m5C detection at single base resolution, by combining the use of tailored primers with bisulfite treatment. A number of computational tools currently exist to analyse m5C marks in DNA bisulfite sequencing. However, these methods are not directly applicable to the analysis of RNA m5C 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 (https://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 m5C 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.

Queuosine-modified tRNAs confer nutritional control of protein translation.

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.

Mutations in Cytosine-5 tRNA Methyltransferases Impact Mobile Element Expression and Genome Stability at Specific DNA Repeats.

The maintenance of eukaryotic genome stability is ensured by the interplay of transcriptional as well as post-transcriptional mechanisms that control recombination of repeat regions and the expression and mobility of transposable elements. We report here that mutations in two (cytosine-5) RNA methyltransferases, Dnmt2 and NSun2, impact the accumulation of mobile element-derived sequences and DNA repeat integrity in Drosophila. Loss of Dnmt2 function caused moderate effects under standard conditions, while heat shock exacerbated these effects. In contrast, NSun2 function affected mobile element expression and genome integrity in a heat shock-independent fashion. Reduced tRNA stability in both RCMT mutants indicated that tRNA-dependent processes affected mobile element expression and DNA repeat stability. Importantly, further experiments indicated that complex formation with RNA could also contribute to the impact of RCMT function on gene expression control. These results thus uncover a link between tRNA modification enzymes, the expression of repeat DNA, and genomic integrity.

Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs.

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. By 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.

Using next-generation DNA sequence data for genetic association tests based on allele counts with and without consideration of zero inflation.

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.

Practical investigation of the performance of robust logistic regression to predict the genetic risk of hypertension.

Logistic regression is usually applied to investigate the association between inherited genetic variants and a binary disease phenotype. A limitation of standard methods used to estimate the parameters of logistic regression models is their strong dependence on a few observations deviating from the majority of the data. We used data from the Genetic Analysis Workshop 18 to explore the possible benefit of robust logistic regression to estimate the genetic risk of hypertension. The comparison between standard and robust methods relied on the influence of departing hypertension profiles (outliers) on the estimated odds ratios, areas under the receiver operating characteristic curves, and clinical net benefit. Our results confirmed that single outliers may substantially affect the estimated genotype relative risks. The ranking of variants by probability values was different in standard and in robust logistic regression. For cutoff probabilities between 0.2 and 0.6, the clinical net benefit estimated by leave-one-out cross-validation in the investigated sample was slightly larger under robust regression, but the overall area under the receiver operating characteristic curve was larger for standard logistic regression. The potential advantage of robust statistics in the context of genetic association studies should be investigated in future analyses based on real and simulated data.

Inherited variability in a master regulator polymorphism (rs4846126) associates with survival in 5-FU treated colorectal cancer patients.

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.