Implementación asistencial de estudios genómicos aplicados al diagnóstico molecular / Implementation of genomic studies applied to molecular diagnostics

El Hospital Garrahan ha sido pionero en el diagnóstico molecular de patologías pediátricas en Argentina. Los avances tecnológicos de las últimas décadas en el área de la biología molecular, sentaron las bases para la optimización y ampliación del diagnóstico molecular a partir de la secuenciación masiva en paralelo de múltiples genes. El presente trabajo describe el proceso de implementación de los estudios de secuenciación de nueva generación y el desarrollo de la Unidad de Genómica en un hospital público pediátrico de alta complejidad, así como su impacto en las capacidades diagnósticas de enfermedades poco frecuentes de origen genético. La creación del Grupo Interdisciplinario de Estudios Genómicos constituyó la vía institucional para la toma de decisiones que implican la implementación de nuevos estudios genómicos y el establecimiento de prioridades diagnósticas, extendiendo la disponibilidad del diagnóstico molecular a más disciplinas. La Unidad de Genómica trabaja en diseñar las estrategias que permitan la mayor optimización de los recursos con los que cuenta el hospital, teniendo en cuenta el equipamiento disponible, las prioridades establecidas y la frecuencia de las distintas patologías. Se demuestra el salto significativo operado en nuestras capacidades diagnósticas, tanto en la variedad de enfermedades como en el número de genes analizados, habiendo estudiado a la fecha alrededor de 2.000 pacientes, muchos de los cuales ven de este modo finalizada su odisea diagnóstica. Los estudios de NGS se han convertido en una herramienta de la práctica diaria para la atención de un número importante de pacientes de nuestro hospital. Continuaremos trabajando para ampliar su aplicación a la mayor cantidad de patologías, a través de los mecanismos institucionales ya existentes (AU)

The Garrahan Hospital has been a pioneer in the molecular diagnosis of pediatric diseases in Argentina. The technological advances of the last decades in the area of molecular biology have laid the foundations for the optimization and expansion of molecular diagnostics through massive parallel sequencing of multiple genes. This study describes the process of implementation of next-generation sequencing studies and the development of the Genomics Unit in a public pediatric tertiary hospital, and its impact on the capacity to diagnose rare diseases of genetic origin. The creation of the Interdisciplinary Group of Genomic Studies constituted the institutional pathway for decision-making involving the implementation of new genomic studies and the establishment of diagnostic priorities, extending the availability of molecular diagnostics to additional disciplines. The Genomics Unit is working to design strategies that allow for optimization of the resources available to the hospital, taking into account the equipment available, the priorities established, and the frequency of the different diseases. It demonstrates the significant leap in our diagnostic capabilities, both in the variety of diseases and in the number of genes analyzed. To date, around 2,000 patients have been studies, many of whom have thus completed their diagnostic odyssey. NGS studies have become a tool in daily practice for the care of a significant number of patients in our hospital. We will continue working to expand its application to as many diseases as possible, through the existing institutional mechanisms (AU)

ChroKit: a Shiny-based framework for interactive analysis, visualization and integration of genomic data.

We developed ChroKit (the Chromatin toolKit), an interactive web-based framework written in R that enables intuitive exploration, multidimensional analyses, and visualization of genomic data from ChIP-Seq, DNAse-Seq or any other NGS experiment that reports the enrichment of aligned reads over genomic regions. This program takes preprocessed NGS data and performs operations on genomic regions of interest, including resetting their boundaries, their annotation based on proximity to genomic features, the association to gene ontologies, and signal enrichment calculations. Genomic regions can be further refined or subsetted by user-defined logical operations and unsupervised classification algorithms. ChroKit generates a full range of plots that are easily manipulated by point and click operations, thus allowing 'on the fly' re-analysis and fast exploration of the data. Working sessions can be exported for reproducibility, accountability, and easy sharing within the bioinformatics community. ChroKit is multiplatform and can be deployed on a server to enhance computational speed and provide simultaneous access by multiple users. ChroKit is a fast and intuitive genomic analysis tool suited for a wide range of users due to its architecture and its user-friendly graphical interface. ChroKit source code is available at https://github.com/ocroci/ChroKit and the Docker image at https://hub.docker.com/r/ocroci/chrokit.

TransCRISPR-sgRNA design tool for CRISPR/Cas9 experiments targeting specific sequence motifs.

Eukaryotic genomes contain several types of recurrent sequence motifs, e.g. transcription factor motifs, miRNA binding sites, repetitive elements. CRISPR/Cas9 can facilitate identification and study of crucial motifs. We present transCRISPR, the first online tool dedicated to search for sequence motifs in the user-provided genomic regions and design optimal sgRNAs targeting them. Users can obtain sgRNAs for chosen motifs, for up to tens of thousands of target regions in 30 genomes, either for the Cas9 or dCas9 system. TransCRISPR provides user-friendly tables and visualizations, summarizing features of identified motifs and designed sgRNAs such as genomic localization, quality scores, closest transcription start sites and others. Experimental validation of sgRNAs for MYC binding sites designed with transCRISPR confirmed efficient disruption of the targeted motifs and effect on expression of MYC-regulated genes. TransCRISPR is available from https://transcrispr.igcz.poznan.pl/transcrispr/.

3D-GNOME 3.0: a three-dimensional genome modelling engine for analysing changes of promoter-enhancer contacts in the human genome.

In the current update, we added a feature for analysing changes in spatial distances between promoters and enhancers in chromatin 3D model ensembles. We updated our datasets by the novel in situ CTCF and RNAPII ChIA-PET chromatin loops obtained from the GM12878 cell line mapped to the GRCh38 genome assembly and extended the 1000 Genomes SVs dataset. To handle the new datasets, we applied GPU acceleration for the modelling engine, which gives a speed-up of 30× versus the previous versions. To improve visualisation and data analysis, we embedded the IGV tool for viewing ChIA-PET arcs with additional genes and SVs annotations. For 3D model visualisation, we added a new viewer: NGL, where we provided colouring by gene and enhancer location. The models are downloadable in mmcif and xyz format. The web server is hosted and performs calculations on DGX A100 GPU servers that provide optimal performance with multitasking. 3D-GNOME 3.0 web server provides unique insights into the topological mechanism of human variations at the population scale with high speed-up and is freely available at https://3dgnome.mini.pw.edu.pl/.

OpenXGR: a web-server update for genomic summary data interpretation.

How to effectively convert genomic summary data into downstream knowledge discovery represents a major challenge in human genomics research. To address this challenge, we have developed efficient and effective approaches and tools. Extending our previously established software tools, we here introduce OpenXGR (http://www.openxgr.com), a newly designed web server that offers almost real-time enrichment and subnetwork analyses for a user-input list of genes, SNPs or genomic regions. It achieves so through leveraging ontologies, networks, and functional genomic datasets (such as promoter capture Hi-C, e/pQTL and enhancer-gene maps for linking SNPs or genomic regions to candidate genes). Six analysers are provided, each doing specific interpretations tailored to genomic summary data at various levels. Three enrichment analysers are designed to identify ontology terms enriched for input genes, as well as genes linked from input SNPs or genomic regions. Three subnetwork analysers allow users to identify gene subnetworks from input gene-, SNP- or genomic region-level summary data. With a step-by-step user manual, OpenXGR provides a user-friendly and all-in-one platform for interpreting summary data on the human genome, enabling more integrated and effective knowledge discovery.

ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection.

The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. Here, we describe a workflow developed by our group to process and analyze large-scale SARS-CoV-2 Illumina amplicon sequencing data. This workflow automates all steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis.

Forecasting COVID-19 Infection Trends and New Hospital Admissions in Spain due to SARS-CoV-2 Variant of Concern Omicron / Estimación de las tendencias de infección por COVID-19 y de nuevos ingresos hospitalarios en España debido a la variante Ómicron del SARS-CoV-2

No disponible

pyRSD-CoEv: A python package for selective sweep detection and co-evolutionary gene cluster identification.

Genes undergo distinct selective sweeps, and also interact and coevolve, forming the bases of complex phenotypic traits. Therefore, the identification of genes that coevolve or are under artificial selective sweeps is of great importance. However, previous computational methods have been designed for either populations of closely related breeds or individuals of distinct species. Approaches intended specifically for closely related individuals without replicate (i.e. each breed/strain is represented by only one individual) are long overdue. We present a free, powerful, open source package, pyRSD-CoEv, that allows the identification of genes undergoing coevolution and/or selection-based sweeps. pyRSD-CoEv includes two main analysis workflows for genomic variant data: (i) the identification of selective sweeps using relative homozygous single nucleotide variant density (RSD); and (ii) the identification of coevolutionary gene clusters based on correlated evolutionary rates. The python package pyRSD-CoEv is written using python 3.7 and is freely available from the github website at https://github.com/QianZiTang/pyRSD-CoEv. It runs on Linux.

SBSA: an online service for somatic binding sequence annotation.

Efficient annotation of alterations in binding sequences of molecular regulators can help identify novel candidates for mechanisms study and offer original therapeutic hypotheses. In this work, we developed Somatic Binding Sequence Annotator (SBSA) as a full-capacity online tool to annotate altered binding motifs/sequences, addressing diverse types of genomic variants and molecular regulators. The genomic variants can be somatic mutation, single nucleotide polymorphism, RNA editing, etc. The binding motifs/sequences involve transcription factors (TFs), RNA-binding proteins, miRNA seeds, miRNA-mRNA 3'-UTR binding target, or can be any custom motifs/sequences. Compared to similar tools, SBSA is the first to support miRNA seeds and miRNA-mRNA 3'-UTR binding target, and it unprecedentedly implements a personalized genome approach that accommodates joint adjacent variants. SBSA is empowered to support an indefinite species, including preloaded reference genomes for SARS-Cov-2 and 25 other common organisms. We demonstrated SBSA by annotating multi-omics data from over 30,890 human subjects. Of the millions of somatic binding sequences identified, many are with known severe biological repercussions, such as the somatic mutation in TERT promoter region which causes a gained binding sequence for E26 transformation-specific factor (ETS1). We further validated the function of this TERT mutation using experimental data in cancer cells. Availability:http://innovebioinfo.com/Annotation/SBSA/SBSA.php.

sideRETRO: uma ferramenta de bioinformática dedicada à identificação deinserções polimórficas, germinativas ou somáticas, de pseudogenes processados / sideRETRO: a bioinformatics tool for identifying somatic and polymorphic insertions of processed pseudogenes

Os avanços metodológicos e instrumentais decorrentes do Projeto Genoma Humano formaram o arcabouço necessário para o surgimento das tecnologias de sequenciamento de DNA de Nova Geração, as quais se caracterizam por um custo reduzido, uma baixa demanda operacional e a produção de um grande volume de dados por experimento. Concomitantemente a isso, o aumento no poder de processamento computacional permitiu o desenvolvimento de análises genéticas em larga escala, de modo que, atualmente, é possível estudar características genômicas individualizadas e, até então, pouco ou nunca exploradas. Dentre essas características, aquelas relacionadas às variações estruturais em genomas têm recebido bastante atenção. Os pseudogenes processados, ou retrocópias, são variações estruturais causadas pela duplicação de genes codificadores mediante à transposição de seu RNA mensageiro maduro pela maquinaria enzimática de LINE- 1. As retrocópias podem estar fixadas, ou seja, presentes em todos os genomas de uma dada espécie, os quais são representados pela montagem modelo do genoma de referência, ou podem não estar fixadas, sendo polimórficas, germinativas ou somáticas. No entanto, o conhecimento acerca das retrocópias não fixadas ainda é limitado devido à falta de ferramentas de bioinformática dedicadas a sua identificação e anotação em dados de sequenciamento de DNA. Posto isso, este trabalho apresenta o sideRETRO um programa computacional especializado na detecção de pseudogenes processados ausentes do genoma de referência, mas presentes em dados de sequenciamento de genoma completo e exoma de outros indivíduos. Além de apontar para a presença de retrocópias não fixadas, o sideRETRO é capaz de anotar várias outras características relacionadas a esses evento, tais como: a coordenada genômica de inserção do pseudogene processado, a qual constitui o cromossomo, o ponto de inserção e a fita de DNA (líder or retardada); o contexto genômico do evento (exônico, intrônico ou intergênico); a genotipagem (presente ou ausente) e a haplotipagem (em homozigose ou heterozigose). Para atestar a eficiência da ferramenta, o sideRETRO foi executado para dados simulados e para dados reais validados experimentalmente por um grupo independente. Portanto, em resumo, nesta tese são descritos o desenvolvimento e o uso do sideRETRO uma ferramenta computacional robusta e eficiente, designada para identificar e anotar pseudogenes processados não fixados. Por fim, vale destacar que o sideRETRO preenche uma lacuna metodológica e possibilita novas hipóteses e investigações sistemáticas no campo de chamada de variantes estruturais

The methodological and instrumental advances resulting from the Human Genome Project have created the necessary framework to the emergence of Next Generation DNA sequencing technologies, which are characterized by a reduced cost, low operational demand and the generation of a large volume of data per experiment. Concomitantly with this, the increase in computational processing power has driven the development of large-scale genetic analyses, which allowed us to study individualized genomic traits little or never explored before. Among these characteristics, those related to structural variations in genomes have received much attention. Processed pseudogenes, or retrocopies, are structural variations caused by the duplication of coding genes through the transposition of their mature messenger RNA by the LINE-1 enzymatic machinery. Retrocopies can be fixed (i.e., present in all genomes of a given species and included into the assembly of the reference genome) or unfixed, being polymorphic, germinal or somatic. However, knowledge about unfixed retrocopies is still limited due to the lack of bioinformatics tools dedicated to their identification and annotation in DNA sequencing data. Therefore, this work presents sideRETRO a computer program specialized in the detection of processed pseudogenes absent from the reference genome, but present in whole genome and exome sequencing data from other individuals. In addition to pointing out the presence of unfixed retrocopies, sideRETRO is able to annotate several other characteristics related to these events, such as: the genomic coordinate of the processed pseudogene insetion, which constitutes the chromosome, the insertion point and the DNA strand (leader or retard); the genomic context of the event (exonic, intronic or intergenic); genotyping (present or absent) and haplotyping (homozygous or heterozygous). To certify the sideRETRO efficiency, it was run on simulated data and on real data experimentally validated by an independent group. Therefore, in summary, this thesis describes the development and use of sideRETRO a robust and efficient computational tool, designed to identify and annotate unfixed processed pseudogenes. Finally, it is worth noting that sideRETRO fills a methodological gap and allows new hypotheses and systematic investigations in the field of structural variant calling

Author-sourced capture of pathway knowledge in computable form using Biofactoid.

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a web-based platform that allows scientists to specify networks of interactions between genes, their products, and chemical compounds, and then translates this information into a representation suitable for computational analysis, search and discovery. We also report the results of a pilot study to encourage the wide adoption of Biofactoid by the scientific community.

Integrative genomics analysis of nasal intestinal-type adenocarcinomas demonstrates the major role of CACNA1C and paves the way for a simple diagnostic tool in male woodworkers.

BACKGROUND: Nasal intestinal-type adenocarcinomas (ITAC) are strongly related to chronic wood dust exposure: The intestinal phenotype relies on CDX2 overexpression but underlying molecular mechanisms remain unknown. Our objectives were to investigate transcriptomic and methylation differences between healthy non-exposed and tumor olfactory cleft mucosae and to compare transcriptomic profiles between non-exposed, wood dust-exposed and ITAC mucosa cells. METHODS: We conducted a prospective monocentric study (NCT0281823) including 16 woodworkers with ITAC, 16 healthy exposed woodworkers and 13 healthy, non-exposed, controls. We compared tumor samples with healthy non-exposed samples, both in transcriptome and in methylome analyses. We also investigated wood dust-induced transcriptome modifications of exposed (without tumor) male woodworkers' samples and of contralateral sides of woodworkers with tumors. We conducted in parallel transcriptome and methylome analysis, and then, the transcriptome analysis was focused on the genes highlighted in methylome analysis. We replicated our results on dataset GSE17433. RESULTS: Several clusters of genes enabled the distinction between healthy and ITAC samples. Transcriptomic and IHC analysis confirmed a constant overexpression of CDX2 in ITAC samples, without any specific DNA methylation profile regarding the CDX2 locus. ITAC woodworkers also exhibited a specific transcriptomic profile in their contralateral (non-tumor) olfactory cleft, different from that of other exposed woodworkers, suggesting that they had a different exposure or a different susceptibility. Two top-loci (CACNA1C/CACNA1C-AS1 and SLC26A10) were identified with a hemimethylated profile, but only CACNA1C appeared to be overexpressed both in transcriptomic analysis and in immunohistochemistry. CONCLUSIONS: Several clusters of genes enable the distinction between healthy mucosa and ITAC samples even in contralateral nasal fossa thus paving the way for a simple diagnostic tool for ITAC in male woodworkers. CACNA1C might be considered as a master gene of ITAC and should be further investigated. TRIAL REGISTRATION: NIH ClinicalTrials, NCT0281823, registered May 23d 2016, https://www.clinicaltrials.gov/NCT0281823 .

Single-cell omics: Overview, analysis, and application in biomedical science.

Single-cell sequencing methods provide the highest resolution insight into cellular heterogeneity. Owing to their rapid growth and decreasing cost, they are now widely accessible to scientists worldwide. Single-cell technologies enable analysis of a large number of cells, making them powerful tools to characterise rare cell types and refine our understanding of diverse cell states. Moreover, single-cell application in biomedical sciences helps to unravel mechanisms related to disease pathogenesis and outcome. In this Viewpoint, we briefly describe existing single-cell methods (genomics, transcriptomics, epigenomics, proteomics, and mulitomics), comment on available analysis tools, and give examples of method applications in the biomedical field.

Application across species of a one health approach to liquid sample handling for respiratory based -omics analysis.

Airway inflammation is highly prevalent in horses, with the majority of non-infectious cases being defined as equine asthma. Currently, cytological analysis of airway derived samples is the principal method of assessing lower airway inflammation. Samples can be obtained by tracheal wash (TW) or by lavage of the lower respiratory tract (bronchoalveolar lavage (BAL) fluid; BALF). Although BALF cytology carries significant diagnostic advantages over TW cytology for the diagnosis of equine asthma, sample acquisition is invasive, making it prohibitive for routine and sequential screening of airway health. However, recent technological advances in sample collection and processing have made it possible to determine whether a wider range of analyses might be applied to TW samples. Considering that TW samples are relatively simple to collect, minimally invasive and readily available in the horse, it was considered appropriate to investigate whether, equine tracheal secretions represent a rich source of cells and both transcriptomic and proteomic data. Similar approaches have already been applied to a comparable sample set in humans; namely, induced sputum. Sputum represents a readily available source of airway biofluids enriched in proteins, changes in the expression of which may reveal novel mechanisms in the pathogenesis of respiratory diseases, such as asthma and chronic obstructive pulmonary disease. The aim of this study was to establish a robust protocol to isolate macrophages, protein and RNA for molecular characterization of TW samples and demonstrate the applicability of sample handling to rodent and human pediatric bronchoalveolar lavage fluid isolates. TW samples provided a good quality and yield of both RNA and protein for downstream transcriptomic/proteomic analyses. The sample handling methodologies were successfully applicable to BALF for rodent and human research. TW samples represent a rich source of airway cells, and molecular analysis to facilitate and study airway inflammation, based on both transcriptomic and proteomic analysis. This study provides a necessary methodological platform for future transcriptomic and/or proteomic studies on equine lower respiratory tract secretions and BALF samples from humans and mice.

Reproducible and accessible analysis of transposon insertion sequencing in Galaxy for qualitative essentiality analyses.

BACKGROUND: Significant progress has been made in advancing and standardizing tools for human genomic and biomedical research. Yet, the field of next-generation sequencing (NGS) analysis for microorganisms (including multiple pathogens) remains fragmented, lacks accessible and reusable tools, is hindered by local computational resource limitations, and does not offer widely accepted standards. One such "problem areas" is the analysis of Transposon Insertion Sequencing (TIS) data. TIS allows probing of almost the entire genome of a microorganism by introducing random insertions of transposon-derived constructs. The impact of the insertions on the survival and growth under specific conditions provides precise information about genes affecting specific phenotypic characteristics. A wide array of tools has been developed to analyze TIS data. Among the variety of options available, it is often difficult to identify which one can provide a reliable and reproducible analysis. RESULTS: Here we sought to understand the challenges and propose reliable practices for the analysis of TIS experiments. Using data from two recent TIS studies, we have developed a series of workflows that include multiple tools for data de-multiplexing, promoter sequence identification, transposon flank alignment, and read count repartition across the genome. Particular attention was paid to quality control procedures, such as determining the optimal tool parameters for the analysis and removal of contamination. CONCLUSIONS: Our work provides an assessment of the currently available tools for TIS data analysis. It offers ready to use workflows that can be invoked by anyone in the world using our public Galaxy platform ( https://usegalaxy.org ). To lower the entry barriers, we have also developed interactive tutorials explaining details of TIS data analysis procedures at https://bit.ly/gxy-tis .

The Illumina Sequencing Protocol and the NovaSeq 6000 System.

The NovaSeq 6000 is a sequencing platform from Illumina that enables the sequencing of short reads with an output up to 6 Tb. The NovaSeq 6000 uses the typical Illumina sequencing workflow based on library preparation, cluster generation by in situ amplification, and sequencing by synthesis. Flexibility is one of the major features of the NovaSeq 6000. Several types of sequencing kits coupled with dual flow cell mode enable high scalability of sequencing outputs to match a wide range of applications from complete genome sequencing to metagenomics analysis. In this chapter, after explaining how to assemble a normalized pool of libraries for sequencing, we will describe the experimental steps required to run the pools on the NovaSeq 6000 platform.

Spatial multi-omics sequencing for fixed tissue via DBiT-seq.

This protocol describes the use of the deterministic barcoding in tissue for spatial omics sequencing platform to construct a multi-omics atlas on fixed frozen tissue samples. This approach uses a microfluidic-based method to introduce combinatorial DNA oligo barcodes directly to the cells in a tissue section fixed on a glass slide. This technique does not directly resolve single cells but can achieve a near-single-cell resolution for spatial transcriptomics and spatial analysis of a targeted panel of proteins. For complete details on the use and execution of this protocol, please refer to Liu et al. (2020).

Molluscan phylogenomics requires strategically selected genomes.

The extraordinary diversity in molluscan body plans, and the genomic mechanisms that enable it, remains one of the great questions of evolution. The eight distinct living taxonomic classes of molluscs are each unambiguously monophyletic; however, significant controversy remains about the phylogenetic relationships among those eight branches. Molluscs are the second-largest animal phylum, with over 100 000 living species with broad biological, economic and medical interest. To date, only around 53 genome assemblies have been accessioned to NCBI GenBank covering only four of the eight living molluscan classes. Furthermore, the molluscan taxa where partial or whole-genome assemblies are available are often aberrantly fast evolving or recently derived lineages. Characteristic adaptations provide interesting targets for whole-genome projects, in animals like the scaly-foot snail or octopus, but without basal-branching lineages for comparison, the context of recently derived features cannot be assessed. The currently available genomes also create a non-optimal set of taxa for resolving deeper phylogenetic branches: they are a small sample representing a large group, and those that are available come primarily from a rarefied pool. Thoughtful selection of taxa for future projects should focus on the blank areas of the molluscan tree, which are ripe with opportunities to delve into peculiarities of genome evolution, and reveal the biology and evolutionary history of molluscs. This article is part of the Theo Murphy meeting issue 'Molluscan genomics: broad insights and future directions for a neglected phylum'.