Transcriptome analysis and characterisation of gill-expressed carbonic anhydrase and other key osmoregulatory genes in freshwater crayfish Cherax quadricarinatus

The pH and salinity balance mechanisms of crayfish are controlled by a set of transport-related genes. We identified a set of the genes from the gill transcriptome from a freshwater crayfish Cherax quadricarinatus using the Illumina NGS-sequencing technology. We identified and characterized carbonic anhydrase (CA) genes and some other key genes involved in systematic acid-base balance and osmotic/ionic regulation. We also examined expression patterns of some of these genes across different sublethal pH levels [1]. A total of 72,382,710 paired-end Illumina reads were assembled into 36,128 contigs with an average length of 800 bp. About 37% of the contigs received significant BLAST hits and 22% were assigned gene ontology terms. These data will assist in further physiological-genomic studies in crayfish.

Diagnóstico Molecular na era da sequenciação de 3ª geração e da PCR digital

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

La génomique évolutive mitochondriale révèle des échanges génétiques et la ségrégation chez les Gloméromycètes

Les champignons mycorhiziens à arbuscules (CMA) sont des organismes microscopiques du sol qui jouent un rôle crucial dans les écosystèmes naturels et que l’on retrouve dans tous les habitats de la planète. Ils vivent en relation symbiotique avec la vaste majorité des plantes terrestres. Ils sont des biotrophes obligatoires, c'est-à-dire qu'ils ne peuvent croître qu'en présence d'une plante hôte. Cette symbiose permet entre autres à la plante d'acquérir des nutriments supplémentaires, en particulier du phosphore et du nitrate. Malgré le fait que cette symbiose apporte des services importants aux écosystèmes, la richesse des espèces, la structure des communautés, ainsi que la diversité fonctionnelle des CMA sont mal connues et l'approfondissement des connaissances dans ces domaines dépend d’outils de diagnostic moléculaire. Cependant, la présence de polymorphisme nucléaire intra-isolat combiné à un manque de données génomiques dans différents groupes phylogénétique de ces champignons complique le développement de marqueurs moléculaires et la détermination de l'affiliation évolutive à hauts niveaux de résolution (c.a.d. entre espèces génétiquement similaires et/ou isolats de la même espèce). . Pour ces raisons, il semble une bonne alternative d’utiliser un système génétique différent en ciblant le génome mitochondrial, qui a été démontré homogène au sein d'un même isolat de CMA. Cependant, étant donné le mode de vie particulier de ces organismes, une meilleure compréhension des processus évolutifs mitochondriaux est nécessaire afin de valoriser l'utilisation de tels marqueurs dans des études de diversité et en génétique des populations. En ce sens, mon projet de doctorat consistait à investiguerétudier: i) les vecteurs de divergences inter-isolats et -espèces génétiquement rapprochéesphylogénétiquement apparentées, ii) la plasticité des génomes mitochondriaux, iii) l'héritabilité mitochondriale et les mécanismes potentiels de ségrégation, ainsi que iv) la diversité mitochondriale intra-isolat in situ. À l'aide de la génomique mitochondriale comparative, en utilisant le séquençage nouvelle génération, on a démontré la présence de variation génétique substantielle inter-isolats et -espèces, engendrées par l'invasion d'éléments mobiles dans les génomes mitochondriaux des CMA, donnant lieu à une évolution moléculaire rapide des régions intergéniques. Cette variation permettait de développer des marqueurs spécifiques à des isolats de la même espèce. Ensuite, à l'aide d'une approche analytique par réseaux de gènes sur des éléments mobiles, on a été en mesure de démontrer des évènements de recombinaisons homologues entre des haplotypes mitochondriaux distincts, menant à des réarrangements génomiques. Cela a permis d'ouvrir les perspectives sur la dynamique mitochondriale et l'hétéroplasmie dans un même isolatsuggère une coexistence de différents haplotypes mitochondriaux dans les populations naturelles et que les cultures monosporales pourraient induirent une sous-estimation de la diversité allélique mitochondriale. Cette apparente contradiction avec l'homogénéité mitochondriale intra-isolat généralement observée, a amené à investiguer étudier les échanges génétiques à l'aide de croisements d'isolats génétiquement distincts. Malgré l'observation de quelques spores filles hétéroplasmiques, l'homoplasmie était le statut par défaut dans toutes les cultures monosporales, avec un biais en faveur de l'un des haplotypes parentaux. Ces résultats suggèrent que la ségrégation opère durant la formation de la spore et/ou le développement de la coloniedu mycélium. De plus, ils supportent la présence d'une machinerie protéique de ségrégation mitochondriale chez les CMAAMF, où l'ensemble des gènes impliqués dans ce mécanisme ont été retrouvé et sont orthologues aux autres champignons. Finalement, on est revenue aux sources avecon a étudié le polymorphisme mitochondrial intra-isolat à l'aide d'une approche conventionnelle de PCR en utilisant une Taq polymérase de haute fidélité, suivie de clonage et de séquençage Sanger, sur deux isolats de R. irregularis. Cela a permis l'observation d'hétéroplasmie in situ, ainsi que la co-expression de variantes de variantes de protéines'ARNm dans une souche in vitro. Les résultats suggèrent que d'autres études basées sur le séquençage nouvelle génération aurait potentiellement ignorée cette variation, offrant ainsi plusieurs nouveaux arguments permettant de considérer les CMA comme des organismes possédant une population de génomes mitochondriaux et nucléaires distincts.

Navigating the labyrinth: a guide to sequence-based, community ecology of arbuscular mycorrhizal fungi

Data generated from next generation sequencing (NGS) will soon comprise the majority of information about arbuscular mycorrhizal fungal (AMF) communities. Although these approaches give deeper insight, analysing NGS data involves decisions that can significantly affect results and conclusions. This is particularly true for AMF community studies, because much remains to be known about their basic biology and genetics. During a workshop in 2013, representatives from seven research groups using NGS for AMF community ecology gathered to discuss common challenges and directions for future research. Our goal was to improve the quality and accessibility of NGS data for the AMF research community. Discussions spanned sampling design, sample preservation, sequencing, bioinformatics and data archiving. With concrete examples we demonstrated how different approaches can significantly alter analysis outcomes. Failure to consider the consequences of these decisions may compound bias introduced at each step along the workflow. The products of these discussions have been summarized in this paper in order to serve as a guide for any researcher undertaking NGS sequencing of AMF communities.

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

Supplementary Information : Hogan, Holland, Holloway, Petit and Read : Read Classification for Next Generation Sequencing, ESANN 2013, April 2013

This item provides supplementary materials for the paper mentioned in the title, specifically a range of organisms used in the study. The full abstract for the main paper is as follows: Next Generation Sequencing (NGS) technologies have revolutionised molecular biology, allowing clinical sequencing to become a matter of routine. NGS data sets consist of short sequence reads obtained from the machine, given context and meaning through downstream assembly and annotation. For these techniques to operate successfully, the collected reads must be consistent with the assumed species or species group, and not corrupted in some way. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans,with some strains exhibiting antibiotic resistance. In this paper, we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from alternative pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.

Read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molec- ular biology, allowing routine clinical sequencing. NGS data consists of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans, with some strains exhibiting antibiotic resistance. Here we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from other pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.

Supplementary material : large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

Large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

Four generations of sequencing: Is it ready for the clinic yet?

Next-generation sequencing techniques have revolutionized over the last decade providing researchers with low cost, high-throughput alternatives compared to the traditional Sanger sequencing methods. These sequencing techniques have rapidly evolved from first-generation to fourth-generation with very broad applications such as unravelling the complexity of the genome, in terms of genetic variations, and having a high impact on the biological field. In this review, we discuss the transition of sequencing from the second-generation to the third- and fourth-generations, and describe some of their novel biological applications. With the advancement in technology, the earlier challenges of minimal size of the instrument, flexibility of throughput, ease of data analysis and short run times are being addressed. However, the need for prospective analysis and effectiveness to test whether the knowledge of any given new variants identified has an effect on clinical outcome may need improvement.

Next generation sequencing identifies novel CACNA1A gene mutations in Episodic Ataxia type 2

Episodic Ataxia type 2 (EA2) is a rare autosomal dominantly inherited neurological disorder characterized by recurrent disabling imbalance, vertigo and episodes of ataxia lasting minutes to hours. EA2 is caused most often by loss of function mutations of the calcium channel gene CACNA1A. In addition to EA2, mutations in CACNA1A are responsible for two other allelic disorders: familial hemiplegic migraine type1 (FHM1) and spinocerebellar ataxia type 6 (SCA6). Herein, we have utilised Next Generation Sequencing (NGS) to screen the coding sequence, exon-intron boundaries and UTRs of five genes where mutation is known to produce symptoms related to EA2, including CACNA1A. We performed this screening in a group of 31 unrelated patients with EA2 symptoms. Both novel and known mutations were detected through NGS technology, and confirmed through Sanger sequencing. Genetic testing showed in total 15 mutation bearing patients (48%), of which 9 were novel mutations (6 missense and 3 small frameshift deletion mutations) and six known mutations (4 missense and 2 nonsense).These results demonstrate the efficiency of our NGS-panel for detecting known and novel mutations for EA2 in the CACNA1A gene, also identifying a novel missense mutation in ATP1A2 which is not a normal target for EA2 screening.

High-quality RNA extraction from copepods for Next Generation Sequencing: A comparative study

Despite the ecological importance of copepods, few Next Generation Sequencing studies (NGS) have been performed on small crustaceans, and a standard method for RNA extraction is lacking. In this study, we compared three commonly-used methods: TRIzol®, Aurum Total RNA Mini Kit and Qiagen RNeasy Micro Kit, in combination with preservation reagents TRIzol® or RNAlater®, to obtain high-quality and quantity of RNA from copepods for NGS. Total RNA was extracted from the copepods Calanus helgolandicus, Centropages typicus and Temora stylifera and its quantity and quality were evaluated using NanoDrop, agarose gel electrophoresis and Agilent Bioanalyzer. Our results demonstrate that preservation of copepods in RNAlater® and extraction with Qiagen RNeasy Micro Kit were the optimal isolation method for high-quality and quantity of RNA for NGS studies of C. helgolandicus. Intriguingly, C. helgolandicus 28S rRNA is formed by two subunits that separate after heat-denaturation and migrate along with 18S rRNA. This unique property of protostome RNA has never been reported in copepods. Overall, our comparative study on RNA extraction protocols will help increase gene expression studies on copepods using high-throughput applications, such as RNA-Seq and microarrays.

The Interlaboratory Robustness Of Next-Generation Sequencing (IRON) Study Phase II: Deep-Sequencing Analyses Of Hematological Malignancies Performed In 8,867 Cases By An International Network Involving 27 Laboratories

Introduction: Amplicon deep-sequencing using second-generation sequencing technology is an innovative molecular diagnostic technique and enables a highly-sensitive detection of mutations. As an international consortium we had investigated previously the robustness, precision, and reproducibility of 454 amplicon next-generation sequencing (NGS) across 10 laboratories from 8 countries (Leukemia, 2011;25:1840-8).

Aims: In Phase II of the study, we established distinct working groups for various hematological malignancies, i.e. acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), and multiple myeloma. Currently, 27 laboratories from 13 countries are part of this research consortium. In total, 74 gene targets were selected by the working groups and amplicons were developed for a NGS deep-sequencing assay (454 Life Sciences, Branford, CT). A data analysis pipeline was developed to standardize mutation interpretation both for accessing raw data (Roche Amplicon Variant Analyzer, 454 Life Sciences) and variant interpretation (Sequence Pilot, JSI Medical Systems, Kippenheim, Germany).

Results: We will report on the design, standardization, quality control aspects, landscape of mutations, as well as the prognostic and predictive utility of this assay in a cohort of 8,867 cases. Overall, 1,146 primer sequences were designed and tested. In detail, for example in AML, 924 cases had been screened for CEBPA mutations. RUNX1 mutations were analyzed in 1,888 cases applying the deep-sequencing read counts to study the stability of such mutations at relapse and their utility as a biomarker to detect residual disease. Analyses of DNMT3A (n=1,041) were focused to perform landscape investigations and to address the prognostic relevance. Additionally, this working group is focusing on TET2, ASXL1, and TP53 analyses. A novel prognostic model is being developed allowing stratification of AML into prognostic subgroups based on molecular markers only. In ALL, 1,124 pediatric and adult cases have been screened, including 763 assays for TP53 mutations both at diagnosis and relapse of ALL. Pediatric and adult leukemia expert labs developed additional content to study the mutation incidence of other B and T lineage markers such as IKZF1, JAK2, IL7R, PAX5, EP300, LEF1, CRLF2, PHF6, WT1, JAK1, PTEN, AKT1, IL7R, NOTCH1, CREBBP, or FBXW7. Further, the molecular landscape of CLL is changing rapidly. As such, a separate working group focused on analyses including NOTCH1, SF3B1, MYD88, XPO1, FBXW7 and BIRC3. Currently, 922 cases were screened to investigate the range of mutational burden of NOTCH1 mutations for their prognostic relevance. In MDS, RUNX1 mutation analyses were performed in 977 cases. The prognostic relevance of TP53 mutations in MDS was assessed in additional 327 cases, including isolated deletions of chromosome 5q. Next, content was developed targeting genes of the cellular splicing component, e.g. SF3B1, SRSF2, U2AF1, and ZRSR2. In BCR-ABL1-negative MPN, nine genes of interest (JAK2, MPL, TET2, CBL, KRAS, EZH2, IDH1, IDH2, ASXL1) have been analyzed in a cohort of 155 primary myelofibrosis cases searching for novel somatic mutations and addressing their relevance for disease progression and leukemia transformation. Moreover, an assay was developed and applied to CMML cases allowing the simultaneous analysis of 25 leukemia-associated target genes in a single sequencing run using just 20 ng of starting DNA. Finally, nine laboratories are studying CML, applying ultra-deep sequencing of the BCR-ABL1 tyrosine kinase domain. Analyses were performed on 615 cases investigating the dynamics of expansion of mutated clones under various tyrosine kinase inhibitor therapies.

Conclusion: Molecular characterization of hematological malignancies today requires high diagnostic sensitivity and specificity. As part of the IRON-II study, a network of laboratories analyzed a variety of disease entities applying amplicon-based NGS assays. Importantly, the consortium not only standardized assay design for disease-specific panels, but also achieved consensus on a common data analysis pipeline for mutation interpretation. Distinct working groups have been forged to address scientific tasks and in total 8,867 cases had been analyzed thus far.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.