A Coverage Criterion for Spaced Seeds and its Applications to Support Vector Machine String Kernels and k-Mer Distances

Spaced seeds have been recently shown to not only detect more alignments, but also to give a more accurate measure of phylogenetic distances (Boden et al., 2013, Horwege et al., 2014, Leimeister et al., 2014), and to provide a lower misclassification rate when used with Support Vector Machines (SVMs) (On-odera and Shibuya, 2013), We confirm by independent experiments these two results, and propose in this article to use a coverage criterion (Benson and Mak, 2008, Martin, 2013, Martin and No{\'e}, 2014), to measure the seed efficiency in both cases in order to design better seed patterns. We show first how this coverage criterion can be directly measured by a full automaton-based approach. We then illustrate how this criterion performs when compared with two other criteria frequently used, namely the single-hit and multiple-hit criteria, through correlation coefficients with the correct classification/the true distance. At the end, for alignment-free distances, we propose an extension by adopting the coverage criterion, show how it performs, and indicate how it can be efficiently computed.Comment: http://online.liebertpub.com/doi/abs/10.1089/cmb.2014.017

A Coverage Criterion for Spaced Seeds and its Applications to Support Vector Machine String Kernels and k-Mer Distances

Spaced seeds have been recently shown to not only detect more alignments, but also to give a more accurate measure of phylogenetic distances (Boden et al., 2013, Horwege et al., 2014, Leimeister et al., 2014), and to provide a lower misclassification rate when used with Support Vector Machines (SVMs) (On-odera and Shibuya, 2013), We confirm by independent experiments these two results, and propose in this article to use a coverage criterion (Benson and Mak, 2008, Martin, 2013, Martin and No{\'e}, 2014), to measure the seed efficiency in both cases in order to design better seed patterns. We show first how this coverage criterion can be directly measured by a full automaton-based approach. We then illustrate how this criterion performs when compared with two other criteria frequently used, namely the single-hit and multiple-hit criteria, through correlation coefficients with the correct classification/the true distance. At the end, for alignment-free distances, we propose an extension by adopting the coverage criterion, show how it performs, and indicate how it can be efficiently computed.Comment: http://online.liebertpub.com/doi/abs/10.1089/cmb.2014.017

The properties and applications of single-molecule DNA sequencing

Single-molecule sequencing enables DNA or RNA to be sequenced directly from biological samples, making it well-suited for diagnostic and clinical applications. Here we review the properties and applications of this rapidly evolving and promising technology

Novel computational techniques for mapping and classifying Next-Generation Sequencing data

Since their emergence around 2006, Next-Generation Sequencing technologies have been revolutionizing biological and medical research. Quickly obtaining an extensive amount of short or long reads of DNA sequence from almost any biological sample enables detecting genomic variants, revealing the composition of species in a metagenome, deciphering cancer biology, decoding the evolution of living or extinct species, or understanding human migration patterns and human history in general. The pace at which the throughput of sequencing technologies is increasing surpasses the growth of storage and computer capacities, which creates new computational challenges in NGS data processing. In this thesis, we present novel computational techniques for read mapping and taxonomic classification. With more than a hundred of published mappers, read mapping might be considered fully solved. However, the vast majority of mappers follow the same paradigm and only little attention has been paid to non-standard mapping approaches. Here, we propound the so-called dynamic mapping that we show to significantly improve the resulting alignments compared to traditional mapping approaches. Dynamic mapping is based on exploiting the information from previously computed alignments, helping to improve the mapping of subsequent reads. We provide the first comprehensive overview of this method and demonstrate its qualities using Dynamic Mapping Simulator, a pipeline that compares various dynamic mapping scenarios to static mapping and iterative referencing. An important component of a dynamic mapper is an online consensus caller, i.e., a program collecting alignment statistics and guiding updates of the reference in the online fashion. We provide Ococo, the first online consensus caller that implements a smart statistics for individual genomic positions using compact bit counters. Beyond its application to dynamic mapping, Ococo can be employed as an online SNP caller in various analysis pipelines, enabling SNP calling from a stream without saving the alignments on disk. Metagenomic classification of NGS reads is another major topic studied in the thesis. Having a database with thousands of reference genomes placed on a taxonomic tree, the task is to rapidly assign a huge amount of NGS reads to tree nodes, and possibly estimate the relative abundance of involved species. In this thesis, we propose improved computational techniques for this task. In a series of experiments, we show that spaced seeds consistently improve the classification accuracy. We provide Seed-Kraken, a spaced seed extension of Kraken, the most popular classifier at present. Furthermore, we suggest ProPhyle, a new indexing strategy based on a BWT-index, obtaining a much smaller and more informative index compared to Kraken. We provide a modified version of BWA that improves the BWT-index for a quick k-mer look-up

Annotation and comparative analysis of fungal genomes: a hitchhiker's guide to genomics

This thesis describes several genome-sequencing projects such as those from the fungi Laccaria bicolor S238N-H82, Glomus intraradices DAOM 197198, Melampsora laricis-populina 98AG31, Puccinia graminis, Pichia pastoris GS115 and Candida bombicola, as well as the one of the haptophyte Emiliania huxleyi CCMP1516. These species are important organisms in many aspects, for instance: L. bicolor and G. intraradices are symbiotic fungi growing associate with trees and present an important ecological niches for promoting tree growth; M. laricis- populina and P. graminis are two devastating fungi threating plants; the tiny yeast P. pastoris is the major protein production platform in the pharmaceutical industry; the biosurfactant production yeast C. bombicola is likely to provide a low ecotoxicity detergent and E. huxleyi places in a unique phylogeny position of chromalveolate and contributes to the global carbon cycle system. The completion of the genome sequence and the subsequent functional studies broaden our understanding of these complex biological systems and promote the species as possible model organisms. However, it is commonly observed that the genome sequencing projects are launched with lots of enthusiasm but often frustratingly difficult to finish. Part of the reason are the ever-increasing expectations regarding quality delivery (both with respect to data and analyses). The Introductory Chapter aims to provide an overview of how best to conduct a genome sequencing project. It explains the importance of understanding the basic biology and genetics of the target organism. It also discusses the latest developments in new (next) generation high throughput sequencing (HTS) technologies, how to handle the data and their applications. The emergence of the new HTS technologies brings the whole biology research into a new frontier. For instance, with the help of the new sequencing technologies, we were able to sequence the genome of our interest, namely Pichia pastoris. This tiny yeast, the analysis of which forms the bulk of this thesis, is an important heterologous production platform because its methanol assimilation properties makes it ideally suitable for large scale industrial production. The unique protein assembly pathway of P. pastoris also attracts much basic research interests. We used the new HTS method to sequence and assemble the GS115 genome into four chromosomes and made it publicly available to the research community (Chapter 2 and Chapter 3). The public release of the GS115 brought broader interests on the comparison of GS115 and its parental strains. By sequencing the parental strain of GS115 with different new sequencing platforms, we identified several point mutations in the coding genes that likely contribute to the higher protein translocation efficiency in GS115. The sequence divergence and copy number variation of rDNA between strains also explains the difference of protein production efficiency (Chapter 4). Before 2008, the Sanger sequencing method was the only technology to obtain high quality complete genomes of eukaryotes. Because of the high cost of the Sanger method, regarding the other genome projects discussed in this thesis, it was necessary to team up with many other partners and to rely on the U.S. Department of Energy Joint Genome Institute (DOE-JGI) and the Broad Institute to generate the genome sequence. The M. larici-populina srain 98AG31 and the Puccinia graminis f. sp. tritici strain CRL 75-36-700-3 are two devastating basidiomycete ‘rusts’ that infect poplar and wheat. Lineage-specific gene family expansions in these two rusts highlight the possible role in their obligate biotrophic life-style. Two large sets of effector-like small-secreted proteins with different pri- mary sequence structures were identified in each organism. The in planta-induced transcriptomic data showed upregulation of these lineage-specific genes and they are likely involved in the establishing of the rust-host interaction. An additional immunolocalization study on M. larici-populina confirmed the accumulation of some candidate effectors in the haustoria and infection hyphae, which is described in Chapter 5

Genome assembly of next-generation sequencing data for the Oryx bacillus : species of the Mycobacterium tuberculosis complex

>Magister Scientiae - MScNext generation sequencing (NGS) technology platforms have accelerated ability to produce completed genome assemblies. Recently, collaborators at Tygerberg Medical School outsourced the sequencing of Oryx bacillus, a member of the Mycobacterium tuberculosis complex (MTC). A total of 31,271,059 short reads were generated and required filtering, assembly and annotation using bioinformatics algorithms. In this project, an NGS assembly pipeline was implemented, tailored specifically for SOLiD sequence data. The raw reads were aligned to seven fully sequenced and annotated MTC members, namely, Mycobacterium tuberculosis H37Rv, H37Ra, CDC1551, F11, KZN 1435, Mycobacterium bovis AF2122/97 and Mycobacterium bovis BCG str. Pasteur 1173P2 using NovoalignCS. Depth and breadth of sequence coverage across each base of the reference genome was calculated using BEDTools, and structural variation. Structural variation at the nucleotide level including deletions, insertions and single nucleotidepolymorphisms (SNPs) were called using three tools, GATK, SAMtools and Nesoni. These variations were further filtered using in-house PERL scripts. Putative functional roles for the alterations at the DNA level were extrapolated from the overlap with essential genes present in annotated MTC members. Approximately 20,730,631 short reads (59.78%) out of a total of 31,271,059 reads aligned to the seven reference genomes. The per base sequence coverage calculations revealed an average of 1,243 unaligned regions. These unaligned regions overlapped with mycobacterial regions of difference (RD) and genetic phage elements acquired by the MTC through horizontal gene transfer and are genes prevalent in the clinical isolates of M. tuberculosis. A total of 2,680 genetic variations were identified and categorised into 845 synonymous and 1,724 non-synonymous SNPs together with 44 insertions and 67 deletions. Some of the variant alleles overlapped known genes to be involved in TB drug resistance. While the biological significance of our findings remain to be elucidated, it nonetheless deserves further attention, because SNPs have the potential to impact on strain phenotype by gene disruption. Therefore, any hypotheses generated from these large-scale analyses will be tested by our collaborators at Tygerberg medical school

Improving CNV detection from short-read MPS data in neuromuscular disorders

Neuromuscular disorders (NMD) are highly heterogenic with around 1000 reported different subtypes. Most are genetic in origin, and some 500 genes are currently identified to cause NMDs. Massively parallel sequencing (MPS) approaches have been widely used to increase the cost-effectiveness and diagnostic yield in the work-up of the genetic molecular diagnosis and to speed up the process. Copy number variants (CNVs), deletions and duplications larger than 50 base pairs, explain approximately 10% of the Mendelian disorders. No best practices pipelines have been developed yet for CNV analysis from MPS data. Therefore, the detection and verification of CNV findings has often involved complementary methods, such as array comparative genomic hybridization (array CGH), multiplex ligation-dependent probe amplification (MLPA) and quantitative PCR approaches. Recently, various CNV detection programs have been developed, but for widely different types of designated research settings, which complicates choosing the correct approach for NMDs. These individual programs have generally exhibited less than ideal sensitivity and specificity for CNV detection. Our aim was to develop a comprehensive pipeline for the detection and annotation of CNVs with high accuracy from targeted gene panel sequencing and whole exome sequencing (WES) data of patients with NMDs. Four different CNV analysis programs were chosen for this study: CoNIFER, XHMM, ExomeDepth and CODEX. The targeted gene panel MYOcap includes 349 genes for myopathic disorders and MNDcap 302 genes for neurogenic disorders in their current panel versions. 2359 samples were sequenced with MYOcap, 942 samples with MNDcap and 262 samples with WES. This included for the targeted gene panels 24 positive control samples with previously characterized CNVs and 31 negative control samples with certain genes verified to not have CNVs. A detection sensitivity of 100% and specificity of 100% were reached for these control samples. Previously undetected CNVs from MYOcap or MNDcap sequenced samples were verified as true positive detections in 36 cases with MLPA, PCR or array CGH, and eight CNVs were verified as false positive detections. These and the positive control samples were utilized in validation of a predictive logistic regression model. In silico CNV generation into MYOcap sequenced samples provided 18,677 specific and 3892 unspecific CNV detections to initially train the model. The model was trained to differentiate true positive detections from false positive detections in order to increase the specificity of the CNV detection pipeline. The advantage of using four different CNV detection programs compared to using them individually, or with any other combination, was demonstrated by CNV detection sensitivity from the set of in silico CNVs. The predictive model with variables from all four programs provided the highest sensitivity (96.6%) and specificity (87.5%) for predicting CNV detections correctly, indicating an accuracy of 95.5% (95% CI 87.3–99.1%). The CNV detection pipeline together with the predictive model was validated for WES samples with control samples with 235 previously characterized CNVs. For CNVs spanning at least three exons, the detection sensitivity was 97.3% and the sensitivity of the predicative model was 99.3% after adjusting the model threshold for WES data. The CNV annotation platform cnvScan was expanded to contain the most recent CNV population databases as well as in-house CNV databases for all the sequenced sample sets. CNV detection results were filtered by < 1% frequency with reciprocal overlap of 90% in the common CNV population databases, with both it and < 5% frequency with 50% reciprocal overlap in the in-house CNV database, and by the true positive prediction with the model. These procedures significantly decreased the workload (with 3–13% of the original CNV detections preserved) in evaluating the CNVs further regarding clinical significance. The added value, i.e. the additional diagnostic yield from CNVs for both the targeted gene panel sequenced samples and WES samples was estimated to be 1.9%. Altogether 39 final genetic diagnoses were solved with these CNV findings. In addition, 18 patient cases had a likely pathogenic finding, and five had a heterozygous CNV likely pathogenic for a recessive disease without association to the patient’s phenotype. The clarified cases included six different DMD deletions or duplications causing dystrophinopathies. In three sequenced familial cases, the detected CNVs in CACNA1A, SGCD and TTN genes co-segregated with the disease. One case had two separate genetic diseases, tibial muscular dystrophy (TMD) and BMD, caused by the founder mutation FINmaj in the gene TTN and a deletion in DMD. Some of the solved cases had novel findings: the second ever reported large intragenic deletion in NEB causing dominant disease, and the first CNV, an intragenic deletion, in TIA1 in a patient diagnosed with Welander distal myopathy (WDM). Some of the genes associated with NMDs are challenging to analyze from short-read sequencing data due to homology or repetitive regions. An additional script was thus written to differentiate copy numbers of the highly homologous genes, SMN1 and SMN2. Two SMN1/SMN2 copy number 0/3 control cases were successfully recognized, and five cases were identified with a possible exon 7 conversion in SMN1 and a compatible spinal muscular atrophy phenotype. The latter findings were considered likely pathogenic and are awaiting further validation on the genomic level. Comparison of CNV detections within the in-house CNV database revealed divergences in the CNV detections within the triplicate repetitive region of NEB with potentially clinically significant changes. One array CGH validated change correlated well with the nemaline rod pathology observed in the patient. CNV analysis utilizing MPS data from targeted gene panels and WES samples provided increased diagnostic yield as reported also in other studies on NMDs. Our multi-algorithm and -platform approach decreased the workload in variant analysis and provided more insight into the many difficult to analyze genomic regions involved in NMDs. In the future, whole genome sequencing and long-read sequencing will likely provide higher resolution for CNV detections and reveal an even wider spectrum of structural genomic variants, together with other emerging comprehensive methods, such as optical mapping.Lihastaudit ovat hyvin heterogeenisiä, ja niistä on kuvattu noin tuhat alatyyppiä. Suurin osa on perinnöllisiä tauteja, ja tähän mennessä on tunnistettu noin 500 eri lihastauteja aiheuttavaa geeniä. Massiivista rinnakkaissekvensointia (MPS) on käytetty laajalti perinnöllisten tautien diagnostisen prosessin nopeuttamiseksi, kustannustehokkuuden parantamiseksi ja lopullisen geeniperäisen diagnoosin saavuttamiseksi. Kopiolukumuutokset, yli 50 emäsparin deleetiot tai duplikaatiot, aiheuttavat arviolta 10 % Mendelin mukaisesti periytyvistä taudeista. Kopiolukumuutosten havaitsemiseen sekvensointidatasta ei ole vielä kehitetty yleisesti hyväksyttyjä ja suositeltuja käytänteitä. Kopiolukumuutosten havaitsemiseksi ja varmistamiseksi käytetäänkin usein täydentäviä menetelmiä, kuten vertaileva genominen hybridisaatio sirulla (aCGH), rinnastettu ligaatio-riippuvainen alukemonistus (MLPA) ja kvantitatiivinen PCR. Kopiolukumuutosten havaitsemiseen sekvensointidatasta on kehitetty useita työkaluja vaihtelevissa tutkimusasetelmissa, mikä hankaloittaa oikean lähestymistavan valitsemista lihastaudeille. Yksittäisten ohjelmien on todettu tuottavan usein epätäsmällisiä ja herkkyydeltään vaihtelevia tai riittämättömiä havaintoja. Tämän tutkimuksen tavoitteena oli kehittää kattava menetelmä kopiolukumuutosten havaitsemiseen ja annotointiin suurella tarkkuudella kohdennetun geenipaneelin ja koko eksomin (WES) sekvensointidatasta lihastautipotilailta. Tutkimukseen valittiin neljä kopiolukumuutosanalyysin työkalua: CoNIFER, XHMM, ExomeDepth ja CODEX. Kohdennetuista geenipaneeleista MYOcap kattaa 349 geeniä lihaspainotteisille taudeille ja MNDcap 302 hermopainotteisille taudeille nykyisissä paneeliversioissa. MYOcap:lla sekvensointiin 2359 näytettä, MNDcap:lla 942 ja WES:llä 262. Kohdennetuilla geenipaneeleilla sekvensointiin 24 positiivista kontrollinäytettä, joissa on aiemmin tunnistettu kopiolukumuutos, ja 31 negatiivista kontrollinäytettä, joissa tietyt geenit oli varmistettu kopiolukumuutoksia sisältämättömiksi. Kontrollinäytteille saavutettiin kehittämällämme menetelmällä 100 % havaitsemisherkkyys ja 100 % tarkkuus. MYOcap:lla tai MNDcap:lla sekvensoiduista näytteistä havaituista kopiolukumuutoksista 36 varmistettiin todellisiksi havainnoiksi MLPA:lla, PCR:lla tai aCGH:llä ja kahdeksan varmistettiin vääriksi positiivisiksi. Nämä ja positiiviset kontrollinäytteet sisällytettiin logistiseen regressioon perustuvan tilastollisen mallin validointiin. Erottelumallin kehitysvaiheessa MYOcap-sekvensoituihin näytteisiin tehtiin in silico kopiolukumuutoksia, mikä tuotti 18677 spesifiä ja 3892 ei-spesifiä kopiolukumuutoshavaintoa mallinnukseen. Malli kehitettiin erottelemaan todelliset kopiolukumuutoshavainnot vääristä positiivista havainnoista havaintomenetelmän tarkkuuden lisäämiseksi. Neljän ohjelman havaintojen käyttämisen paremmuus verrattuna ohjelmien käyttämiseen yksittäin tai muilla yhdistelmillä todennettiin in silico kopiolukumuutosten havaitsemisen herkkyyden tuloksilla. Erottelumalli, jossa oli muuttujia kaikilta neljältä ohjelmalta, saavutti korkeimman herkkyyden (96,6 %), täsmällisyyden (87,5 %) ja tarkkuuden 95,5 % (95 % CI 87,3–99,1 %) kopiolukumuutosten erottelulle. Kopiolukumuutoshavaitsemismenetelmä ja erottelumalli validoitiin WES-kontrollinäytteillä, joissa oli 235 aiemmin tunnistettua kopiolukumuutosta. Havaitsemisherkkyys kopiolukumuutoksille, jotka sisältävät vähintään kolme eksonia oli 97,3 %, ja erottelumallin herkkyys oli 99,3 % kunhan mallin arviointiraja oli uudelleensäädetty WES-datalle. Kopiolukumuutosten annotaatiotyökalu cnvScan laajennettiin sisältämään uusimmat kopiolukumuutospopulaatiotietokannat ja talonsisäinen kopiolukumuutostietokanta kaikista sekvensointinäytejoukoista. Alkuperäiset kopiolukumuutoshavainnot neljältä ohjelmalta suodatettiin 1 % enimmäisyleisyyden ja vastavuoroisen 90 % muutoksen kattamisen vaatimuksella yleisissä kopiolukumuutospopulaatiotietokannoissa, tällä sekä 5 % enimmäisyleisyyden ja vastavuoroisen 50 % muutoksen kattamisen vaatimuksella talonsisäisessä tietokannassa, ja lisäksi erottelumallilla todellisiin havaintoihin. Nämä toimenpiteet vähensivät merkittävästi työmäärää kliinisen merkityksen arvioinnille kopiolukumuutoksille säästäen 3–13 % alkuperäisistä havainnoista. Lisääntyneiden diagnoosien määrä kopiolukumuutoshavaintojen myötä sekä kohdennetuilla geenipaneeleilla että WES-sekvensoiduilla näytteillä oli noin 1,9 %. Kopiolukumuutoshavainnoilla saavutettiin 39 lopullista geneettistä diagnoosia potilaille. Lisäksi 18:lla tutkitulla oli todennäköisesti patogeeninen löydös, ja viidellä tutkitulla havaittiin heterotsygoottinen kopiolukumuutos, jonka arvioitiin olevan patogeeninen peittyvästi periytyvän taudin variantti ilman yhteyttä potilaan taudinkuvaan. Selvitettyihin tapauksiin sisältyi kuusi eri DMD-geenissä olevaa deleetiota tai duplikaatiota, jotka aiheuttivat dystrofinopatioita. Kolme potilasta, joilla oli oireisia perheenjäseniä, sekvensointiin perhetapauksina, ja havaitut kopiolukumuutokset geeneissä CACNA1A, SGCD ja TTN segregoituivat yhdessä taudin kanssa. Yhdellä tutkitulla havaittiin kaksi perinnöllistä tautia, tibiaalinen lihasdystrofia (TMD) ja BMD, joiden aiheuttajina olivat perustajamutaatio FINmaj TTN-geenissä ja deleetio DMD-geenissä. Osalla selvitetyistä tapauksista oli ennen havaitsemattomia löydöksiä: NEB-geenissä toinen koskaan raportoitu iso geeninsisäinen deleetio, joka aiheuttaa vallitsevasti periytyvän taudin, sekä TIA1-geenin geeninsisäinen deleetio, joka on ensimmäinen havaittu kopiolukumuutos TIA1:ssä Welanderin distaalimyopatiaa (WDM) sairastavalla potilaalla. Jotkin geeneistä, jotka on liitetty lihastauteihin, ovat haastavia analysoitavia lyhytlukuisesta sekvensointidatasta homologian ja toistojaksojen takia. Hyvin homologisille geeneille SMN1 ja SMN2 kehitettiin erillinen ohjelma erottelemaan geenien kopiolukumäärät. Kaksi kontrollitapausta tunnistettiin onnistuneesti SMN1 ja SMN2 kopiolukumäärillä 0 ja 3, ja lisäksi tunnistettiin viisi tapausta, joilla on mahdollisesti eksonin 7 konversio SMN1:ssä ja yhteensopiva spinaalinen lihasatrofia. Jälkimmäiset löydökset luokiteltiin todennäköisesti patogeeniseksi, ja ne odottavat genomista lisävarmistusta. Kopiolukumuutoshavaintojen vertailu NEB-geenin triplikaattitoistoalueella talonsisäisessä tietokannassa paljasti eroavaisuuksia, joilla on potentiaalisesti kliinisesti merkitystä. Yksi aCGH:llä varmistettu muutos korreloi selkeästi nemaliinisauvakappalepatologian kanssa, joka potilaalla oli havaittu. Kopiolukumuutoshavainnointi käyttäen sekvensointidataa kohdennetusta geenipaneelista tai WES-näytteistä lisäsi diagnoosien määrää kuten aiemmissa vastaavissa tutkimuksissa lihastaudeille. Käyttämämme usean algoritmin ja alustan lähestymistapa vähensi varianttianalyysin työmäärää ja tarjosi lisää tietoa useista hankalasti analysoitavista genomisista alueista, jotka on liitetty lihastauteihin. Tulevaisuudessa koko genomin sekvensointi ja pitkälukuinen sekvensointi tarjonnevat paremman resoluution kopiolukumuutoksille ja paljastavat enemmän rakenteellisia genomin muutoksia yhdessä muiden kehitteillä olevien kattavien menetelmien kanssa, kuten optinen kartoitus