New Insights into Essential Genes and Functions

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Genetics".

Deadline for manuscript submissions: 20 September 2024 | Viewed by 3128

Special Issue Editors


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Guest Editor
Institute of Genetics and Biophysics “A. Buzzati Traverso”, CNR, Via Pietro Castellino, 111, 80131 Naples, Italy
Interests: molecular and cellular biology; epigenetics; neurology; Rett syndrome; X chromosome inactivation

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Guest Editor
High Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, 80131 Napoli, Italy
Interests: computational biology; NGS data analysis; integrative computational network biology; metabolic networks; microbiome
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Special Issue Information

Dear Colleagues,

The “high-throughput” era has led to interesting new opportunities for the functional study of genomes.

Computational and experimental genetics studies cause an incessantly increasing amount of data and information that need to be processed, integrated and organized to aid the goal of precision medicine.

While scientific disciplines have become increasingly sectorial, the link between them is often underestimated.

In this context, essential genes represent an interesting object of research shared by different areas of study, such as synthetic biology, systems biology, computational biology, molecular biology, cell biology, drug design and medicine.

Essential genes are commonly defined as genes that are necessary for the growth and survival of any organism or cell. They are identified experimentally through gene-deletion assays aimed at ablating the gene (and/or the function) of interest (e.g. antisense RNA, transposon mutagenesis, CRISPR-Cas9, Knock-out) and observing the effects on the phenotype.

At a genome-wide level, these procedures are complex, costly, and labour- and time-intensive, requiring support from computational approaches.

Many efforts have been devoted to identifying organism-wide essential genes, but essentiality is a dynamic property that strongly depends on environmental and genetic contexts and can be ascribed to functions other than genes.

This Special Issue, “New Insights into Essential Genes and Functions”, is dedicated to investigating essential genes and functions and their condition dependency.

With this in mind, we would like to invite original research papers and review articles dealing with the aforementioned issue from analytical, methodological, computational, biological and evolutionary perspectives, applied to eukaryotes or prokaryotes. We welcome all contributions advancing our understanding of essential biological processes and genes through innovative strategies and/or novel applications.

We look forward to receiving your contributions.

Dr. Marcella Vacca
Dr. Ilaria Granata
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • gene regulation
  • omics data
  • essentiality
  • epigenetics
  • machine learning

Published Papers (2 papers)

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Research

22 pages, 5725 KiB  
Article
Identification of Molecular Markers Associated with Prostate Cancer Subtypes: An Integrative Bioinformatics Approach
by Ilaria Granata and Paola Barboro
Biomolecules 2024, 14(1), 87; https://doi.org/10.3390/biom14010087 - 10 Jan 2024
Viewed by 1302
Abstract
Prostate cancer (PCa) is characterised by androgen dependency. Unfortunately, under anti-androgen treatment pressure, castration-resistant prostate cancer (CRPC) emerges, characterised by heterogeneous cell populations that, over time, lead to the development of different androgen-dependent or -independent phenotypes. Despite important advances in therapeutic strategies, CRPC [...] Read more.
Prostate cancer (PCa) is characterised by androgen dependency. Unfortunately, under anti-androgen treatment pressure, castration-resistant prostate cancer (CRPC) emerges, characterised by heterogeneous cell populations that, over time, lead to the development of different androgen-dependent or -independent phenotypes. Despite important advances in therapeutic strategies, CRPC remains incurable. Context-specific essential genes represent valuable candidates for targeted anti-cancer therapies. Through the investigation of gene and protein annotations and the integration of published transcriptomic data, we identified two consensus lists to stratify PCa patients’ risk and discriminate CRPC phenotypes based on androgen receptor activity. ROC and Kaplan–Meier survival analyses were used for gene set validation in independent datasets. We further evaluated these genes for their association with cancer dependency. The deregulated expression of the PCa-related genes was associated with overall and disease-specific survival, metastasis and/or high recurrence risk, while the CRPC-related genes clearly discriminated between adeno and neuroendocrine phenotypes. Some of the genes showed context-specific essentiality. We further identified candidate drugs through a computational repositioning approach for targeting these genes and treating lethal variants of PCa. This work provides a proof-of-concept for the use of an integrative approach to identify candidate biomarkers involved in PCa progression and CRPC pathogenesis within the goal of precision medicine. Full article
(This article belongs to the Special Issue New Insights into Essential Genes and Functions)
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0 pages, 1733 KiB  
Article
Untangling the Context-Specificity of Essential Genes by Means of Machine Learning: A Constructive Experience
by Maurizio Giordano, Emanuele Falbo, Lucia Maddalena, Marina Piccirillo and Ilaria Granata
Biomolecules 2024, 14(1), 18; https://doi.org/10.3390/biom14010018 - 22 Dec 2023
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Abstract
Gene essentiality is a genetic concept crucial for a comprehensive understanding of life and evolution. In the last decade, many essential genes (EGs) have been determined using different experimental and computational approaches, and this information has been used to reduce the genomes of [...] Read more.
Gene essentiality is a genetic concept crucial for a comprehensive understanding of life and evolution. In the last decade, many essential genes (EGs) have been determined using different experimental and computational approaches, and this information has been used to reduce the genomes of model organisms. A growing amount of evidence highlights that essentiality is a property that depends on the context. Because of their importance in vital biological processes, recognising context-specific EGs (csEGs) could help for identifying new potential pharmacological targets and to improve precision therapeutics. Since most of the computational procedures proposed to identify and predict EGs neglect their context-specificity, we focused on this aspect, providing a theoretical and experimental overview of the literature, data and computational methods dedicated to recognising csEGs. To this end, we adapted existing computational methods to exploit a specific context (the kidney tissue) and experimented with four different prediction methods using the labels provided by four different identification approaches. The considerations derived from the analysis of the obtained results, confirmed and validated also by further experiments for a different tissue context, provide the reader with guidance on exploiting existing tools for achieving csEGs identification and prediction. Full article
(This article belongs to the Special Issue New Insights into Essential Genes and Functions)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: To be determined
Authors: Chiara Lauritano; et al.
Affiliation: Ecosustainable Marine Biotechnology Department, Stazione Zoologica Anton Dohrn, Via Acton n. 55, 80133 Naples, Italy

Title: To be determined
Authors: Ilaria Granata; et al.
Affiliation: High Performance Computing and Networking Institute, National Research Council of Italy, Via P. Castellino, 111, 80131 Napoli, Italy

Title: To be determined
Authors: Vasco M Barreto; et al.
Affiliation: Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Costa da Caparica, Portugal

Title: To be determined
Authors: Francesco Filippini; et al.
Affiliation: Department of Biology, University of Padua, Via Ugo Bassi, 58/B, 35131 Padua, Italy

Title: To be determined
Authors: Samuel T. Waters; et al.
Affiliation: University of the District of Columbia, USA

Title: To be determined
Authors: Maurizio Giordano; et al.
Affiliation: Consiglio Nazionale delle Ricerche, Naples, Italy

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