Models for transcript quantification from RNA-Seq

RNA-Seq is rapidly becoming the standard technology for transcriptome analysis. Fundamental to many of the applications of RNA-Seq is the quantification problem, which is the accurate measurement of relative transcript abundances from the sequenced reads. We focus on this problem, and review many recently published models that are used to estimate the relative abundances. In addition to describing the models and the different approaches to inference, we also explain how methods are related to each other. A key result is that we show how inference with many of the models results in identical estimates of relative abundances, even though model formulations can be very different. In fact, we are able to show how a single general model captures many of the elements of previously published methods. We also review the applications of RNA-Seq models to differential analysis, and explain why accurate relative transcript abundance estimates are crucial for downstream analyses

Large-scale methods in computational genomics

The explosive growth in biological sequence data coupled with the design and deployment of increasingly high throughput sequencing technologies has created a need for methods capable of processing large-scale sequence data in a time and cost effective manner. In this dissertation, we address this need through the development of faster algorithms, space-efficient methods, and high-performance parallel computing techniques for some key problems in computational genomics;The first problem addressed is the clustering of DNA sequences based on a measure of sequence similarity. Our clustering method: (i) guarantees linear space complexity, in contrast to the quadratic memory requirements of previously developed methods; (ii) identifies sequence pairs containing long maximal matches in the decreasing order of their maximal match lengths in run-time proportional to the sum of input and output sizes; (iii) provides heuristics to significantly reduce the number of pairs evaluated for checking sequence similarity without affecting quality; and (iv) has parallel strategies that provide linear speedup and a proportionate reduction in space per processor. Our approach has significantly enhanced the problem size reach while also drastically reducing the time to solution;The next problem we address is the de novo detection of genomic repeats called Long Terminal Repeat (LTR) retrotransposons. Our algorithm guarantees linear space complexity and produces high quality candidates for prediction in run-time proportional to the sum of input and output sizes. Validation of our approach on the yeast genome demonstrates both superior quality and performance results when compared to previously developed software;In a genome assembly project, fragments sequenced from a target genome are computationally assembled into numerous supersequences called contigs , which are then ordered and oriented into scaffolds . In this dissertation, we introduce a new problem called retroscaffolding for scaffolding contigs based on the knowledge of their LTR retrotransposon content. Through identification of sequencing gaps that span LTR retrotransposons, retroscaffolding provides a mechanism for prioritizing sequencing gaps for finishing purposes;While most of the problems addressed here have been studied previously, the main contribution in this dissertation is the development of methods that can scale to the largest available sequence collections

Gene annotation in Heliconius numata colouring the black box

Tese de mestrado, Biologia (Biologia Evolutiva e do Desenvolvimento, Universidade de Lisboa, Faculdade de Ciências, 2010O presente projecto teve por objectivo a identificação e anotação de genes que se sabe estarem ligados num arranjo de genes inquebrável por recombinação e que controla a padronização das asas da borboleta Heliconius numata. Este complexo é homologo posicional de complexos em outras espécies de Heliconius, nomeadamente o complexo Yb/Sb em H. melpomene e Cr em H. erato. Este “supergene” é visto como um hotspot de desenvolvimento (sensu Richardson & Brakefield 2003) que controla divergência fenotípica entre espécies próximas e convergência fenotípica entre espécies mais distantes. Em H. numata o supergene sofreu rearranjos genómicos que se pensa estarem correlacionados com a preservação das combinações alélicas necessárias para manter os fenótipos discretos característicos das relações miméticas locais (mimicry rings) que estes organismos estabelecem na natureza. Estes rearranjos podem estar a modificar ou perturbar expressão genica e é, portanto, de extrema importância identificar tais genes bem como compreender a sua estrutura, nomeadamente no que diz respeito a eventuais eventos de clivagem alternativa que possam estar correlacionados com as diferentes raças locais observáveis na natureza. Usando uma combinação de ferramentas bioinformáticas e sequências de transcriptoma de raças com fenótipos diferentes, modelos de genes serão estabelecidos para desenhar primers específicos de modo a amplificar os genes modelizados e testar hipóteses relativamente a diferenças na sua estrutura e distribuição na região de interesse.The present project aims at the identification and annotation of the specific genes known to be in a cluster of tighly linked genes known to control wing patterning in H. numata. This cluster is positionally homologous with cluster in other species of Heliconius, namely Yb/Sb in H. melpomene and Cr in H. erato. This “supergene” is seen as a developmental hotspot (sensu Richardson and Brakefield 2003) controlling both phenotypic divergence between closely related species and convergence between more distantly related species. In H. numata the supergene suffered genomic rearrangements that are thought to be preserving the necessary combination of loci to attain the concrete phenotypes typical in mimicry relations these butterflies establish in nature. These rearrangements may be disturbing or modifying gene expression. Therefore, it is extremely valuable to identify the genes in the genomic region of interest, and address eventual alternative splicing events that could be associated with the different locally adapted races. Using a combination of bioinformatics’ tools and transcriptome sequences from two phenotypically different races, I generated gene models in order to design primers and amplify these genes, testing hypothesis regarding splice variants and validating the models

Spliced alignment and its application in Arabidopsis thaliana

This thesis describes the development and biological applications of GeneSeqer, which is a homology-based gene prediction program by means of spliced alignment. Additionally, a program named MyGV was written in JAVA as a browser to visualize the output of GeneSeqer. In order to test and demonstrate the performance, GeneSeqer was utilized to map 176,915 Arabidopsis EST sequences on the whole genome of Arabidopsis thaliana, which consists of five chromosomes, with about 117 million base pairs in total. All results were parsed and imported into a MySQL database. Information that was inferred from the Arabidopsis spliced alignment results may serve as valuable resource for a number of projects of special scientific interest, such as alternative splicing, non-canonical splice sites, mini-exons, etc. We also built AtGDB (Arabidopsis thaliana Genome DataBase, http://www.plantgdb.org/AtGDB/) to interactively browse EST spliced alignments and GenBank annotations for the Arabidopsis genome. Moreover, as one application of the Arabidopsis EST mapping data, U12-type introns were identified from the transcript-confirmed introns in the Arabidopsis genome, and the characteristics of these minor class introns were further explored

ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences

BACKGROUND: Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems – hence the need to develop novel strategies. RESULTS: We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations. We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility. CONCLUSION: Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at

Pairagon+N-SCAN_EST: a model-based gene annotation pipeline

BACKGROUND: This paper describes Pairagon+N-SCAN_EST, a gene annotation pipeline that uses only native alignments. For each expressed sequence it chooses the best genomic alignment. Systems like ENSEMBL and ExoGean rely on trans alignments, in which expressed sequences are aligned to the genomic loci of putative homologs. Trans alignments contain a high proportion of mismatches, gaps, and/or apparently unspliceable introns, compared to alignments of cDNA sequences to their native loci. The Pairagon+N-SCAN_EST pipeline's first stage is Pairagon, a cDNA-to-genome alignment program based on a PairHMM probability model. This model relies on prior knowledge, such as the fact that introns must begin with GT, GC, or AT and end with AG or AC. It produces very precise alignments of high quality cDNA sequences. In the genomic regions between Pairagon's cDNA alignments, the pipeline combines EST alignments with de novo gene prediction by using N-SCAN_EST. N-SCAN_EST is based on a generalized HMM probability model augmented with a phylogenetic conservation model and EST alignments. It can predict complete transcripts by extending or merging EST alignments, but it can also predict genes in regions without EST alignments. Because they are based on probability models, both Pairagon and N-SCAN_EST can be trained automatically for new genomes and data sets. RESULTS: On the ENCODE regions of the human genome, Pairagon+N-SCAN_EST was as accurate as any other system tested in the EGASP assessment, including ENSEMBL and ExoGean. CONCLUSION: With sufficient mRNA/EST evidence, genome annotation without trans alignments can compete successfully with systems like ENSEMBL and ExoGean, which use trans alignments

metaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella

The metabolic SearcH And Reconstruction Kit (metaSHARK) is a new fully automated software package for the detection of enzyme-encoding genes within unannotated genome data and their visualization in the context of the surrounding metabolic network. The gene detection package (SHARKhunt) runs on a Linux systemand requires only a set of raw DNA sequences (genomic, expressed sequence tag and/ or genome survey sequence) as input. Its output may be uploaded to our web-based visualization tool (SHARKview) for exploring and comparing data from different organisms. We first demonstrate the utility of the software by comparing its results for the raw Plasmodium falciparum genome with the manual annotations available at the PlasmoDB and PlasmoCyc websites. We then apply SHARKhunt to the unannotated genome sequences of the coccidian parasite Eimeria tenella and observe that, at an E-value cut-off of 10(-20), our software makes 142 additional assertions of enzymatic function compared with a recent annotation package working with translated open reading frame sequences. The ability of the software to cope with low levels of sequence coverage is investigated by analyzing assemblies of the E.tenella genome at estimated coverages from 0.5x to 7.5x. Lastly, as an example of how metaSHARK can be used to evaluate the genomic evidence for specific metabolic pathways, we present a study of coenzyme A biosynthesis in P.falciparum and E.tenella

Sim4cc: a cross-species spliced alignment program

Advances in sequencing technologies have accelerated the sequencing of new genomes, far outpacing the generation of gene and protein resources needed to annotate them. Direct comparison and alignment of existing cDNA sequences from a related species is an effective and readily available means to determine genes in the new genomes. Current spliced alignment programs are inadequate for comparing sequences between different species, owing to their low sensitivity and splice junction accuracy. A new spliced alignment tool, sim4cc, overcomes problems in the earlier tools by incorporating three new features: universal spaced seeds, to increase sensitivity and allow comparisons between species at various evolutionary distances, and powerful splice signal models and evolutionarily-aware alignment techniques, to improve the accuracy of gene models. When tested on vertebrate comparisons at diverse evolutionary distances, sim4cc had significantly higher sensitivity compared to existing alignment programs, more than 10% higher than the closest competitor for some comparisons, while being comparable in speed to its predecessor, sim4. Sim4cc can be used in one-to-one or one-to-many comparisons of genomic and cDNA sequences, and can also be effectively incorporated into a high-throughput annotation engine, as demonstrated by the mapping of 64 000 Fagus grandifolia 454 ESTs and unigenes to the poplar genome