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Genes
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Unraveling Genetic Complexity: Integrative Approaches in Variant Interpretation
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Unraveling Genetic Complexity: Integrative Approaches in Variant Interpretation

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: closed (15 September 2024) | Viewed by 1666

Special Issue Editor

Dr. Xiao Fan

E-Mail Website
Guest Editor
Herbert Wertheim College of Engineering, Gainesville, FL, USA
Interests: computational biology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advancements in next-generation sequencing have revolutionized our ability to comprehensively characterize molecular information at an unprecedented scale. While these technological breakthroughs offer remarkable opportunities, they also underscore the critical need for rapid and accurate interpretation of the vast array of genetic variations observed. This special issue aims to delve deeper into the intricate landscape of genetic variation and its implications for human health and disease, focusing on detailed characterization at multiple levels, including alleles, genes, macromolecular complexes, and signaling cascades. Furthermore, we seek to explore the comprehensive profiles of tissue- or cell-specific features, shedding light on the context-dependent nature of genetic variation. Leveraging innovative systems biology approaches that integrate multi-modality data across transcriptomes, epigenomes, and genome editing holds immense promise in elucidating the underlying genetic mechanisms driving human diseases and uncovering actionable insights with clinical relevance. We invite submissions that contribute to our understanding of genetic variations. Studies that integrate meaningful information from diverse data sources or address the challenges associated with variant interpretation through experimental advancements, statistical methodologies, or computational techniques are particularly relevant.

Dr. Xiao Fan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Genes 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 2600 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

  • genetic variation interpretation
  • multi-modality data integration
  • systems biology approach
  • genetic mechanism
  • human genetic diseases

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Published Papers (1 paper)

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Review

23 pages, 4617 KiB  
Review
Analyses of Human Genetic Data to Identify Clinically Relevant Domains of Neuroligins
by Alexander W. Lehr, Kathryn F. McDaniel and Katherine W. Roche
Genes 2024, 15(12), 1601; https://doi.org/10.3390/genes15121601 - 14 Dec 2024
Viewed by 1296
Abstract
Background/Objectives: Neuroligins (NLGNs) are postsynaptic adhesion molecules critical for neuronal development that are highly associated with autism spectrum disorder (ASD). Here, we provide an overview of the literature on NLGN rare variants. In addition, we introduce a new approach to analyze human variation [...] Read more.
Background/Objectives: Neuroligins (NLGNs) are postsynaptic adhesion molecules critical for neuronal development that are highly associated with autism spectrum disorder (ASD). Here, we provide an overview of the literature on NLGN rare variants. In addition, we introduce a new approach to analyze human variation within NLGN genes to identify sensitive regions that have an increased frequency of ASD-associated variants to better understand NLGN function. Methods: To identify critical protein subdomains within the NLGN gene family, we developed an algorithm that assesses tolerance to missense mutations in human genetic variation by comparing clinical variants from ClinVar to reference variants from gnomAD. This approach provides tolerance values to subdomains within the protein. Results: Our algorithm identified several critical regions that were conserved across multiple NLGN isoforms. Importantly, this approach also identified a previously reported cluster of pathogenic variants in NLGN4X (also conserved in NLGN1 and NLGN3) as well as a region around the highly characterized NLGN3 R451C ASD-associated mutation. Additionally, we highlighted other, as of yet, uncharacterized regions enriched with mutations. Conclusions: The systematic analysis of NLGN ASD-associated variants compared to variants identified in the unaffected population (gnomAD) reveals conserved domains in NLGN isoforms that are tolerant to variation or are enriched in clinically relevant variants. Examination of databases also allows for predictions of the presumed tolerance to loss of an allele. The use of the algorithm we developed effectively allowed the evaluation of subdomains of NLGNs and can be used to examine other ASD-associated genes. Full article
(This article belongs to the Special Issue Unraveling Genetic Complexity: Integrative Approaches in Variant Interpretation)
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