A comprehensive, unbiased and systematic description of the biological processes involved in cervical ripening/dilatation using functional genomics

Functional genomics is the study of how the genome and its products, including RNA and proteins, function and interact to affect different biological processes. The field of functional genomics includes transcriptomics, proteomics, metabolomics and epigenomics, as these all relate to controlling the genome leading to expression of particular phenotypes. By studying whole genomes—clinical genomics, transcriptomes and epigenomes—functional genomics allows the exploration of the diverse relationship between genotype and phenotype, not only for humans as a species but also in individuals, allowing an understanding and evaluation of how the functional genome ‘contributes’ to different diseases. Functional variation in disease can help us better understand that disease, although it is currently limited in terms of ethnic diversity, and will ultimately give way to more personalized treatment plans.

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Computational functional genomics-based reduction of disease-related gene sets to their key components

Bioinformatics ◽

10.1093/bioinformatics/bty986 ◽

2018 ◽

Vol 35 (14) ◽

pp. 2362-2370 ◽

Cited By ~ 2

Author(s):

Catharina Lippmann ◽

Alfred Ultsch ◽

Jörn Lötsch

Keyword(s):

Functional Genomics ◽

Directed Acyclic Graph ◽

R Package ◽

Quantitative Information ◽

Knowledge Bases ◽

Supplementary Information ◽

Biological Processes ◽

Gene Set ◽

Gene Sets ◽

Disease Related Gene

Abstract Motivation The genetic architecture of diseases becomes increasingly known. This raises difficulties in picking suitable targets for further research among an increasing number of candidates. Although expression based methods of gene set reduction are applied to laboratory-derived genetic data, the analysis of topical sets of genes gathered from knowledge bases requires a modified approach as no quantitative information about gene expression is available. Results We propose a computational functional genomics-based approach at reducing sets of genes to the most relevant items based on the importance of the gene within the polyhierarchy of biological processes characterizing the disease. Knowledge bases about the biological roles of genes can provide a valid description of traits or diseases represented as a directed acyclic graph (DAG) picturing the polyhierarchy of disease relevant biological processes. The proposed method uses a gene importance score derived from the location of the gene-related biological processes in the DAG. It attempts to recreate the DAG and thereby, the roles of the original gene set, with the least number of genes in descending order of importance. This obtained precision and recall of over 70% to recreate the components of the DAG charactering the biological functions of n=540 genes relevant to pain with a subset of only the k=29 best-scoring genes. Conclusions A new method for reduction of gene sets is shown that is able to reproduce the biological processes in which the full gene set is involved by over 70%; however, by using only ∼5% of the original genes. Availability and implementation The necessary numerical parameters for the calculation of gene importance are implemented in the R package dbtORA at https://github.com/IME-TMP-FFM/dbtORA. Supplementary information Supplementary data are available at Bioinformatics online.

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MasterPATH: network analysis of functional genomics screening data

BMC Genomics ◽

10.1186/s12864-020-07047-2 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Natalia Rubanova ◽

Guillaume Pinna ◽

Jeremie Kropp ◽

Anna Campalans ◽

Juan Pablo Radicella ◽

...

Keyword(s):

Dna Damage ◽

Functional Genomics ◽

Oxidative Dna Damage ◽

Transcriptome Profiling ◽

Molecular Pathways ◽

Biological Processes ◽

Loss Of Function ◽

Damage Recognition ◽

Dna Damage Recognition

Abstract Background Functional genomics employs several experimental approaches to investigate gene functions. High-throughput techniques, such as loss-of-function screening and transcriptome profiling, allow to identify lists of genes potentially involved in biological processes of interest (so called hit list). Several computational methods exist to analyze and interpret such lists, the most widespread of which aim either at investigating of significantly enriched biological processes, or at extracting significantly represented subnetworks. Results Here we propose a novel network analysis method and corresponding computational software that employs the shortest path approach and centrality measure to discover members of molecular pathways leading to the studied phenotype, based on functional genomics screening data. The method works on integrated interactomes that consist of both directed and undirected networks – HIPPIE, SIGNOR, SignaLink, TFactS, KEGG, TransmiR, miRTarBase. The method finds nodes and short simple paths with significant high centrality in subnetworks induced by the hit genes and by so-called final implementers – the genes that are involved in molecular events responsible for final phenotypic realization of the biological processes of interest. We present the application of the method to the data from miRNA loss-of-function screen and transcriptome profiling of terminal human muscle differentiation process and to the gene loss-of-function screen exploring the genes that regulates human oxidative DNA damage recognition. The analysis highlighted the possible role of several known myogenesis regulatory miRNAs (miR-1, miR-125b, miR-216a) and their targets (AR, NR3C1, ARRB1, ITSN1, VAV3, TDGF1), as well as linked two major regulatory molecules of skeletal myogenesis, MYOD and SMAD3, to their previously known muscle-related targets (TGFB1, CDC42, CTCF) and also to a number of proteins such as C-KIT that have not been previously studied in the context of muscle differentiation. The analysis also showed the role of the interaction between H3 and SETDB1 proteins for oxidative DNA damage recognition. Conclusion The current work provides a systematic methodology to discover members of molecular pathways in integrated networks using functional genomics screening data. It also offers a valuable instrument to explain the appearance of a set of genes, previously not associated with the process of interest, in the hit list of each particular functional genomics screening.

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MasterPATH: network analysis of functional genomics screening data

10.1101/264119 ◽

2018 ◽

Author(s):

Natalia Rubanova ◽

Anna Polesskaya ◽

Anna Campalans ◽

Guillaume Pinna ◽

Jeremie Kropp ◽

...

Keyword(s):

Network Analysis ◽

Functional Genomics ◽

Biological Process ◽

Transcriptome Profiling ◽

Repair Process ◽

Biological Processes ◽

Analysis Method ◽

Loss Of Function ◽

Gene Functions ◽

High Throughput Manner

AbstractFunctional genomics employs several experimental techniques to investigate gene functions. These techniques such as loss-of-function screening and transcriptome profiling performed in a high-throughput manner give as result a list of genes involved in the biological process of interest. There exist several computational methods for analysis and interpretation of the list. The most widespread methods aim at investigation of biological processes significantly represented in the list or at extracting significantly represented subnetworks. Here we present a new exploratory network analysis method that employs the shortest path approach and centrality measure to uncover members of active molecular pathways leading to the studied phenotype based on the results of functional genomics screening data. We present the method and we demonstrate what data can be retrieved by its application to the terminal muscle differentiation miRNA loss-of-function screening and transcriptomic profiling data and to the ‘druggable’ loss-of-function RNAi screening data of the DNA repair process.

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MicroCore: Mapping Genome Expression to Cell Pathways and Networks

Comparative and Functional Genomics ◽

10.1002/cfg.362 ◽

2004 ◽

Vol 5 (1) ◽

pp. 75-78 ◽

Cited By ~ 1

Author(s):

Manish Patel ◽

Sylvia Nagl

Keyword(s):

Functional Genomics ◽

Open Source ◽

Microarray Analysis ◽

Protein Interaction ◽

Biological Processes ◽

Expression Data ◽

Extended Version ◽

Proteomics Data ◽

Genome Expression ◽

Cellular Pathways

The MicroCore toolkit is a suite of analysis programs for microarray and proteomics data that is open source and programmed exclusively in Java. MicroCore provides a flexible and extensible environment for the interpretation of functional genomics data through visualization. The first version of the application (downloadable from the MicroCore website: http://www.ucl.ac.uk/oncology/MicroCore/microcore.htm), implements two programs—PIMs (protein interaction maps) and MicroExpress—and is soon to be followed by an extended version which will also feature a fuzzy k-means clustering application and a Java-based R plug-in for microarray analysis. PIMs and MicroExpress provide a simple yet powerful way of graphically relating large quantities of expression data from multiple experiments to cellular pathways and biological processes in a statistically meaningful way.

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Regulatory modules of human thermogenic adipocytes: functional genomics of large cohort and Meta-analysis derived marker-genes

BMC Genomics ◽

10.1186/s12864-021-08126-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Beáta B. Tóth ◽

Zoltán Barta ◽

Ákos Barnabás Barta ◽

László Fésüs

Keyword(s):

Functional Genomics ◽

Meta Analysis ◽

Interaction Network ◽

Regulatory Elements ◽

Integrative Approach ◽

Marker Genes ◽

Biological Processes ◽

White Adipocyte ◽

Regulatory Modules ◽

White Adipocytes

Abstract Background Recently, ProFAT and BATLAS studies identified brown and white adipocytes marker genes based on analysis of large databases. They offered scores to determine the thermogenic status of adipocytes using the gene-expression data of these markers. In this work, we investigated the functional context of these genes. Results Gene Set Enrichment Analyses (KEGG, Reactome) of the BATLAS and ProFAT marker-genes identified pathways deterministic in the formation of brown and white adipocytes. The collection of the annotated proteins of the defined pathways resulted in expanded white and brown characteristic protein-sets, which theoretically contain all functional proteins that could be involved in the formation of adipocytes. Based on our previously obtained RNA-seq data, we visualized the expression profile of these proteins coding genes and found patterns consistent with the two adipocyte phenotypes. The trajectory of the regulatory processes could be outlined by the transcriptional profile of progenitor and differentiated adipocytes, highlighting the importance of suppression processes in browning. Protein interaction network-based functional genomics by STRING, Cytoscape and R-Igraph platforms revealed that different biological processes shape the brown and white adipocytes and highlighted key regulatory elements and modules including GAPDH-CS, DECR1, SOD2, IL6, HRAS, MTOR, INS-AKT, ERBB2 and 4-NFKB, and SLIT-ROBO-MAPK. To assess the potential role of a particular protein in shaping adipocytes, we assigned interaction network location-based scores (betweenness centrality, number of bridges) to them and created a freely accessible platform, the AdipoNET (https//adiponet.com), to conveniently use these data. The Eukaryote Promoter Database predicted the response elements in the UCP1 promoter for the identified, potentially important transcription factors (HIF1A, MYC, REL, PPARG, TP53, AR, RUNX, and FoxO1). Conclusion Our integrative approach-based results allowed us to investigate potential regulatory elements of thermogenesis in adipose tissue. The analyses revealed that some unique biological processes form the brown and white adipocyte phenotypes, which presumes the existence of the transitional states. The data also suggests that the two phenotypes are not mutually exclusive, and differentiation of thermogenic adipocyte requires induction of browning as well as repressions of whitening. The recognition of these simultaneous actions and the identified regulatory modules can open new direction in obesity research.

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Fluorescent potentiometric dyes for membrane-potential imaging

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100168566 ◽

1994 ◽

Vol 52 ◽

pp. 166-167

Author(s):

Leslie M. Loew

Keyword(s):

Membrane Potential ◽

Single Cells ◽

Quantitative Imaging ◽

Optical Recording ◽

Biological Processes ◽

Major Focus ◽

The Past ◽

Excitable Systems ◽

Major Application ◽

The Impact

A major application of potentiometric dyes has been the multisite optical recording of electrical activity in excitable systems. After being championed by L.B. Cohen and his colleagues for the past 20 years, the impact of this technology is rapidly being felt and is spreading to an increasing number of neuroscience laboratories. A second class of experiments involves using dyes to image membrane potential distributions in single cells by digital imaging microscopy - a major focus of this lab. These studies usually do not require the temporal resolution of multisite optical recording, being primarily focussed on slow cell biological processes, and therefore can achieve much higher spatial resolution. We have developed 2 methods for quantitative imaging of membrane potential. One method uses dual wavelength imaging of membrane-staining dyes and the other uses quantitative 3D imaging of a fluorescent lipophilic cation; the dyes used in each case were synthesized for this purpose in this laboratory.

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Apoptosis and development

Essays in Biochemistry ◽

10.1042/bse0390011 ◽

2003 ◽

Vol 39 ◽

pp. 11-24 ◽

Cited By ~ 6

Author(s):

Justin V McCarthy

Keyword(s):

Drosophila Melanogaster ◽

Mammalian Cells ◽

Cell Number ◽

Model Organisms ◽

Biological Processes ◽

Nematode Caenorhabditis Elegans ◽

Apoptotic Pathway ◽

Genetic Pathways ◽

Evolutionarily Conserved ◽

Multicellular Organisms

Apoptosis is an evolutionarily conserved process used by multicellular organisms to developmentally regulate cell number or to eliminate cells that are potentially detrimental to the organism. The large diversity of regulators of apoptosis in mammalian cells and their numerous interactions complicate the analysis of their individual functions, particularly in development. The remarkable conservation of apoptotic mechanisms across species has allowed the genetic pathways of apoptosis determined in lower species, such as the nematode Caenorhabditis elegans and the fruitfly Drosophila melanogaster, to act as models for understanding the biology of apoptosis in mammalian cells. Though many components of the apoptotic pathway are conserved between species, the use of additional model organisms has revealed several important differences and supports the use of model organisms in deciphering complex biological processes such as apoptosis.

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