Solving biclustering with a GRASP-like metaheuristic: two case-study on gene expression analysis

The explosion of "omics" data over the past few decades has generated an increasing need of efficiently analyzing high-dimensional gene expression data in several different and heterogenous contexts, such as for example in information retrieval, knowledge discovery, and data mining. For this reason, biclustering, or simultaneous clustering of both genes and conditions has generated considerable interest over the past few decades. Unfortunately, the problem of locating the most significant bicluster has been shown to be NP-complete. We have designed and implemented a GRASP-like heuristic algorithm to efficiently find good solutions in reasonable running times, and to overcome the inner intractability of the problem from a computational point of view. Experimental results on two datasets of expression data are promising indicating that this algorithm is able to find significant biclusters, especially from a biological point of view

Intraspecific diversity in the cold stress response of transposable elements in the diatom leptocylindrus aporus

Transposable elements (TEs), activated as a response to unfavorable conditions, have been proposed to contribute to the generation of genetic and phenotypic diversity in diatoms. Here we explore the transcriptome of three warm water strains of the diatom Leptocylindrus aporus, and the possible involvement of TEs in their response to changing temperature conditions. At low temperature (13 \ub0C) several stress response proteins were overexpressed, confirming low temperature to be unfavorable for L. aporus, while TE-related transcripts of the LTR retrotransposon superfamily were the most enriched transcripts. Their expression levels, as well as most of the stress-related proteins, were found to vary significantly among strains, and even within the same strains analysed at different times. The lack of overexpression after many months of culturing suggests a possible role of physiological plasticity in response to growth under controlled laboratory conditions. While further investigation on the possible central role of TEs in the diatom stress response is warranted, the strain-specific responses and possible role of in-culture evolution draw attention to the interplay between the high intraspecific variability and the physiological plasticity of diatoms, which can both contribute to the adaptation of a species to a wide range of conditions in the marine environment

Genomewide transcriptional reprogramming in the seagrass Cymodocea nodosa under experimental ocean acidification

Here, we report the first use of massive-scale RNA-sequencing to explore seagrass response to CO2-driven ocean acidification (OA). Large-scale gene expression changes in the seagrass Cymodocea nodosa occurred at CO2 levels projected by the end of the century. C. nodosa transcriptome was obtained using Illumina RNA-Seq technology and de novo assembly, and differential gene expression was explored in plants exposed to short-term high CO2/low pH conditions. At high pCO(2), there was a significant increased expression of transcripts associated with photosynthesis, including light reaction functions and CO2 fixation, and also to respiratory pathways, specifically for enzymes involved in glycolysis, in the tricarboxylic acid cycle and in the energy metabolism of the mitochondrial electron transport. The upregulation of respiratory metabolism is probably supported by the increased availability of photo-synthates and increased energy demand for biosynthesis and stress-related processes under elevated CO2 and low pH. The upregulation of several chaperones resembling heat stress-induced changes in gene expression highlighted the positive role these proteins play in tolerance to intracellular acid stress in seagrasses. OA further modifies C. nodosa secondary metabolism inducing the transcription of enzymes related to biosynthesis of carbon-based secondary compounds, in particular the synthesis of polyphenols and isoprenoid compounds that have a variety of biological functions including plant defence. By demonstrating which physiological processes are most sensitive to OA, this research provides a major advance in the understanding of seagrass metabolism in the context of altered seawater chemistry from global climate change.Portuguese FCT project HighGrass [PTDC/MAR-EST/3687/2012

Therapeutic homology-independent targeted integration in retina and liver

Challenges to the widespread application of gene therapy with adeno-associated viral (AAV) vectors include dominant conditions due to gain-of-function mutations which require allele-specific knockout, as well as long-term transgene expression from proliferating tissues, which is hampered by AAV DNA episomal status. To overcome these challenges, we used CRISPR/Cas9-mediated homology-independent targeted integration (HITI) in retina and liver as paradigmatic target tissues. We show that AAV-HITI targets photoreceptors of both mouse and pig retina, and this results in significant improvements to retinal morphology and function in mice with autosomal dominant retinitis pigmentosa. In addition, we show that neonatal systemic AAV-HITI delivery achieves stable liver transgene expression and phenotypic improvement in a mouse model of a severe lysosomal storage disease. We also show that HITI applications predominantly result in on-target editing. These results lay the groundwork for the application of AAV-HITI for the treatment of diseases affecting various organs

De novo assembly of a transcriptome from the eggs and early embryos of Astropecten aranciacus

Starfish have been instrumental in many fields of biological and ecological research. Oocytes of Astropecten aranciacus, a common species native to the Mediterranean Sea and the East Atlantic, have long been used as an experimental model to study meiotic maturation, fertilization, intracellular Ca2+ signaling, and cell cycle controls. However, investigation of the underlying molecular mechanisms has often been hampered by the overall lack of DNA or protein sequences for the species. In this study, we have assembled a transcriptome for this species from the oocytes, eggs, zygotes, and early embryos, which are known to have the highest RNA sequence complexity. Annotation of the transcriptome identified over 32,000 transcripts including the ones that encode 13 distinct cyclins and as many cyclin-dependent kinases (CDK), as well as the expected components of intracellular Ca2+ signaling toolkit. Although the mRNAs of cyclin and CDK families did not undergo significant abundance changes through the stages from oocyte to early embryo, as judged by real-time PCR, the transcript encoding Mos, a negative regulator of mitotic cell cycle, was drastically reduced during the period of rapid cleavages. Molecular phylogenetic analysis using the homologous amino acid sequences of cytochrome oxidase subunit I from A. aranciacus and 30 other starfish species indicated that Paxillosida, to which A. aranciacus belongs, is not likely to be the most basal order in Asteroidea. Taken together, the first transcriptome we assembled in this species is expected to enable us to perform comparative studies and to design gene-specific molecular tools with which to tackle long-standing biological questions

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock