André Kahles

Multiple reference genomes and transcriptomes for Arabidopsis thaliana

Genetic differences between Arabidopsis thaliana accessions underlie the plant’s extensive phenotypic variation, and until now these have been interpreted largely in the context of the annotated reference accession Col-0. Here we report the sequencing, assembly and annotation of the genomes of 18 natural A. thaliana accessions, and their transcriptomes. When assessed on the basis of the reference annotation, one-third of protein-coding genes are predicted to be disrupted in at least one accession. However, re-annotation of each genome revealed that alternative gene models often restore coding potential. Gene expression in seedlings differed for nearly half of expressed genes and was frequently associated with cis variants within 5 kilobases, as were intron retention alternative splicing events. Sequence and expression variation is most pronounced in genes that respond to the biotic environment. Our data further promote evolutionary and functional studies in A. thaliana, especially the MAGIC genetic reference population descended from these accessions.

Systematic evaluation of spliced alignment programs for RNA-seq data

High-throughput RNA sequencing is an increasingly accessible method for studying gene structure and activity on a genome-wide scale. A critical step in RNA-seq data analysis is the alignment of partial transcript reads to a reference genome sequence. To assess the performance of current mapping software, we invited developers of RNA-seq aligners to process four large human and mouse RNA-seq data sets. In total, we compared 26 mapping protocols based on 11 programs and pipelines and found major performance differences between methods on numerous benchmarks, including alignment yield, basewise accuracy, mismatch and gap placement, exon junction discovery and suitability of alignments for transcript reconstruction. We observed concordant results on real and simulated RNA-seq data, confirming the relevance of the metrics employed. Future developments in RNA-seq alignment methods would benefit from improved placement of multimapped reads, balanced utilization of existing gene annotation and a reduced false discovery rate for splice junctions.

DNA methylation in Arabidopsis has a genetic basis and shows evidence of local adaptation

Epigenome modulation potentially provides a mechanism for organisms to adapt, within and between generations. However, neither the extent to which this occurs, nor the mechanisms involved are known. Here we investigate DNA methylation variation in Swedish Arabidopsis thaliana accessions grown at two different temperatures. Environmental effects were limited to transposons, where CHH methylation was found to increase with temperature. Genome-wide association studies (GWAS) revealed that the extensive CHH methylation variation was strongly associated with genetic variants in both cis and trans, including a major trans-association close to the DNA methyltransferase CMT2. Unlike CHH methylation, CpG gene body methylation (GBM) was not affected by growth temperature, but was instead correlated with the latitude of origin. Accessions from colder regions had higher levels of GBM for a significant fraction of the genome, and this was associated with increased transcription for the genes affected. GWAS revealed that this effect was largely due to trans-acting loci, many of which showed evidence of local adaptation. DOI: http://dx.doi.org/10.7554/eLife.05255.001

Nonsense-Mediated Decay of Alternative Precursor mRNA Splicing Variants Is a Major Determinant of the Arabidopsis Steady State Transcriptome

Alternative precursor mRNA splicing represents a major mechanism to increase transcriptome diversity in higher eukaryotes. This work demonstrates that a substantial fraction of the alternative splicing variants from Arabidopsis thaliana is subject to turn over via the RNA quality-control mechanism nonsense-mediated decay, having important implications for the regulation of gene expression. The nonsense-mediated decay (NMD) surveillance pathway can recognize erroneous transcripts and physiological mRNAs, such as precursor mRNA alternative splicing (AS) variants. Currently, information on the global extent of coupled AS and NMD remains scarce and even absent for any plant species. To address this, we conducted transcriptome-wide splicing studies using Arabidopsis thaliana mutants in the NMD factor homologs UP FRAMESHIFT1 (UPF1) and UPF3 as well as wild-type samples treated with the translation inhibitor cycloheximide. Our analyses revealed that at least 17.4% of all multi-exon, protein-coding genes produce splicing variants that are targeted by NMD. Moreover, we provide evidence that UPF1 and UPF3 act in a translation-independent mRNA decay pathway. Importantly, 92.3% of the NMD-responsive mRNAs exhibit classical NMD-eliciting features, supporting their authenticity as direct targets. Genes generating NMD-sensitive AS variants function in diverse biological processes, including signaling and protein modification, for which NaCl stress–modulated AS-NMD was found. Besides mRNAs, numerous noncoding RNAs and transcripts derived from intergenic regions were shown to be NMD responsive. In summary, we provide evidence for a major function of AS-coupled NMD in shaping the Arabidopsis transcriptome, having fundamental implications in gene regulation and quality control of transcript processing.

RNA‐Seq Read Alignments with PALMapper

Next‐generation sequencing technologies have revolutionized genome and transcriptome sequencing. RNA‐Seq experiments are able to generate huge amounts of transcriptome sequence reads at a fraction of the cost of Sanger sequencing. Reads produced by these technologies are relatively short and error prone. To utilize such reads for transcriptome reconstruction and gene‐structure identification, one needs to be able to accurately align the sequence reads over intron boundaries. In this unit, we describe PALMapper, a fast and easy‐to‐use tool that is designed to accurately compute both unspliced and spliced alignments for millions of RNA‐Seq reads. It combines the efficient read mapper GenomeMapper with the spliced aligner QPALMA, which exploits read‐quality information and predictions of splice sites to improve the alignment accuracy. The PALMapper package is available as a command‐line tool running on Unix or Mac OS X systems or through a Web interface based on Galaxy tools.Curr. Protoc. Bioinform. 32:11.6.1‐11.6.37.

Polypyrimidine Tract Binding Protein Homologs from Arabidopsis Are Key Regulators of Alternative Splicing with Implications in Fundamental Developmental Processes

Alternative precursor mRNA splicing massively expands the transcriptome diversity in higher eukaryotes. In this report, we describe Arabidopsis Polypyrimidine tract binding protein homologs as critical components of the plant splicing code and provide links between regulated alternative splicing events and seed germination as well as flowering time control. Alternative splicing (AS) generates transcript variants by variable exon/intron definition and massively expands transcriptome diversity. Changes in AS patterns have been found to be linked to manifold biological processes, yet fundamental aspects, such as the regulation of AS and its functional implications, largely remain to be addressed. In this work, widespread AS regulation by Arabidopsis thaliana Polypyrimidine tract binding protein homologs (PTBs) was revealed. In total, 452 AS events derived from 307 distinct genes were found to be responsive to the levels of the splicing factors PTB1 and PTB2, which predominantly triggered splicing of regulated introns, inclusion of cassette exons, and usage of upstream 5′ splice sites. By contrast, no major AS regulatory function of the distantly related PTB3 was found. Dependent on their position within the mRNA, PTB-regulated events can both modify the untranslated regions and give rise to alternative protein products. We find that PTB-mediated AS events are connected to diverse biological processes, and the functional implications of selected instances were further elucidated. Specifically, PTB misexpression changes AS of PHYTOCHROME INTERACTING FACTOR6, coinciding with altered rates of abscisic acid–dependent seed germination. Furthermore, AS patterns as well as the expression of key flowering regulators were massively changed in a PTB1/2 level-dependent manner.

MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples

Motivation: High-throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts. However, the extensive dynamic range of gene expression, technical limitations and biases, as well as the observed complexity of the transcriptional landscape, pose profound computational challenges for transcriptome reconstruction. Results: We present the novel framework MITIE (Mixed Integer Transcript IdEntification) for simultaneous transcript reconstruction and quantification. We define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data and show how to find the optimal solution using Mixed Integer Programming. MITIE can (i) take advantage of known transcripts, (ii) reconstruct and quantify transcripts simultaneously in multiple samples, and (iii) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data. When compared with state-of-the-art approaches, MITIE proves to be significantly more sensitive and overall more accurate. Moreover, MITIE yields substantial performance gains when used with multiple samples. We applied our system to 38 Drosophila melanogaster modENCODE RNA-Seq libraries and estimated the sensitivity of reconstructing omitted transcript annotations and the specificity with respect to annotated transcripts. Our results corroborate that a well-motivated objective paired with appropriate optimization techniques lead to significant improvements over the state-of-the-art in transcriptome reconstruction. Availability: MITIE is implemented in C++ and is available from http://bioweb.me/mitie under the GPL license. Contact: Jonas_Behr@web.de and raetsch@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online.

Accurate detection of differential RNA processing

Deep transcriptome sequencing (RNA-Seq) has become a vital tool for studying the state of cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling data enable identification of novel isoforms, quantification of known isoforms and detection of changes in transcriptional or RNA-processing activity. Existing approaches to detect differential isoform abundance between samples either require a complete isoform annotation or fall short in providing statistically robust and calibrated significance estimates. Here, we propose a suite of statistical tests to address these open needs: a parametric test that uses known isoform annotations to detect changes in relative isoform abundance and a non-parametric test that detects differential read coverages and can be applied when isoform annotations are not available. Both methods account for the discrete nature of read counts and the inherent biological variability. We demonstrate that these tests compare favorably to previous methods, both in terms of accuracy and statistical calibrations. We use these techniques to analyze RNA-Seq libraries from Arabidopsis thaliana and Drosophila melanogaster. The identified differential RNA processing events were consistent with RT–qPCR measurements and previous studies. The proposed toolkit is available from http://bioweb.me/rdiff and enables in-depth analyses of transcriptomes, with or without available isoform annotation.

SplAdder: Identification, quantification and testing of alternative splicing events from RNA-Seq data

Motivation: Understanding the occurrence and regulation of alternative splicing (AS) is a key task towards explaining the regulatory processes that shape the complex transcriptomes of higher eukaryotes. With the advent of high-throughput sequencing of RNA (RNA-Seq), the diversity of AS transcripts could be measured at an unprecedented depth. Although the catalog of known AS events has grown ever since, novel transcripts are commonly observed when working with less well annotated organisms, in the context of disease, or within large populations. Whereas an identification of complete transcripts is technically challenging and computationally expensive, focusing on single splicing events as a proxy for transcriptome characteristics is fruitful and sufficient for a wide range of analyses. Results: We present SplAdder, an alternative splicing toolbox, that takes RNA-Seq alignments and an annotation file as input to (i) augment the annotation based on RNA-Seq evidence, (ii) identify alternative splicing events present in the augmented annotation graph, (iii) quantify and confirm these events based on the RNA-Seq data and (iv) test for significant quantitative differences between samples. Thereby, our main focus lies on performance, accuracy and usability. Availability: Source code and documentation are available for download at http://github.com/ratschlab/spladder. Example data, introductory information and a small tutorial are accessible via http://bioweb.me/spladder. Contacts: andre.kahles@ratschlab.org or gunnar.ratsch@ratschlab.org Supplementary information: Supplementary data are available at Bioinformatics online.

Oqtans: The RNA-seq Workbench in the Cloud for Complete and Reproducible Quantitative Transcriptome Analysis

We present Oqtans, an open-source workbench for quantitative transcriptome analysis, that is integrated in Galaxy. Its distinguishing features include customizable computational workflows and a modular pipeline architecture that facilitates comparative assessment of tool and data quality. Oqtans integrates an assortment of machine learning-powered tools into Galaxy, which show superior or equal performance to state-of-the-art tools. Implemented tools comprise a complete transcriptome analysis workflow: short-read alignment, transcript identification/quantification and differential expression analysis. Oqtans and Galaxy facilitate persistent storage, data exchange and documentation of intermediate results and analysis workflows. We illustrate how Oqtans aids the interpretation of data from different experiments in easy to understand use cases. Users can easily create their own workflows and extend Oqtans by integrating specific tools. Oqtans is available as (i) a cloud machine image with a demo instance at cloud.oqtans.org, (ii) a public Galaxy instance at galaxy.cbio.mskcc.org, (iii) a git repository containing all installed software (oqtans.org/git); most of which is also available from (iv) the Galaxy Toolshed and (v) a share string to use along with Galaxy CloudMan. Contact: vipin@cbio.mskcc.org, ratschg@mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online.