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Biomedicines
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Advances in Genomics and Bioinformatics of Human Disease
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Advances in Genomics and Bioinformatics of Human Disease

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 1669

Special Issue Editor

Dr. Sankarasubramanian Jagadesan

E-Mail Website
Guest Editor
Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center (UNMC), Omaha, NE 68198, USA
Interests: next generation sequencing and data analysis; data analysis; RNAseq and ScRNA analysis; metagenomics; comparative genome analysis and metabolic modeling; interaction studies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advances in genomics and bioinformatics have significantly deepened our understanding of human diseases, driving a shift toward precision medicine. High-throughput sequencing technologies, including long-read sequencing and single-cell RNA sequencing, now enable researchers to identify genetic variations, epigenetic modifications, and cellular heterogeneity with unprecedented precision. CRISPR-Cas9 and base-editing technologies facilitate targeted gene manipulation, empowering functional studies of disease-associated mutations. Simultaneously, bioinformatics has been dramatically enhanced by artificial intelligence (AI) and machine learning (ML), which improve genomic data analysis through accurate variant interpretation, pathogenicity prediction, and identification of novel therapeutic targets. The integration of multi-omics data—genomics, transcriptomics, proteomics, and metabolomics—offers comprehensive insights into disease mechanisms, fostering the discovery of biomarkers and personalized therapeutic strategies. These advancements are accelerating research into complex diseases such as cancer, cardiovascular disorders, and neurodegenerative conditions, refining diagnostic and prognostic capabilities, and paving the way for tailored treatments that significantly enhance patient outcomes and advance global healthcare.

Dr. Sankarasubramanian Jagadesan
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. Biomedicines 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

  • genomics
  • bioinformatics
  • precision medicine
  • single-cell RNA sequencing
  • genetic variations
  • cellular heterogeneity
  • AI/ML
  • pathogenicity prediction

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Published Papers (2 papers)

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16 pages, 1727 KB  
Article
A Hitchhiker Guide to Structural Variant Calling: A Comprehensive Benchmark Through Different Sequencing Technologies
by Giuseppe Giovanni Nardone, Valentina Andrioletti, Aurora Santin, Anna Morgan, Beatrice Spedicati, Maria Pina Concas, Paolo Gasparini, Giorgia Girotto and Ivan Limongelli
Biomedicines 2025, 13(8), 1949; https://doi.org/10.3390/biomedicines13081949 - 9 Aug 2025
Viewed by 612
Abstract
Background: Structural variants (SVs) play a significant role in gene function and are implicated in numerous human diseases. With advances in sequencing technologies, identifying SVs through whole-genome sequencing (WGS) has become a key area of research. However, variability in SV detection persists due [...] Read more.
Background: Structural variants (SVs) play a significant role in gene function and are implicated in numerous human diseases. With advances in sequencing technologies, identifying SVs through whole-genome sequencing (WGS) has become a key area of research. However, variability in SV detection persists due to the wide range of available tools and the absence of standardized methodologies. Methods: We assessed the accuracy of SV detection across various short-read (srWGS) and long-read (lrWGS) sequencing technologies—including Illumina short reads, PacBio long reads, and Oxford Nanopore Technologies (ONT) long reads—using deletion calls from the HG002 benchmark dataset. We examined how variables such as variant calling algorithms, reference genome choice, alignment strategies, and sequencing coverage influence SV detection performance. Results: DRAGEN v4.2 delivered the highest accuracy among ten srWGS callers tested. Notably, leveraging a graph-based multigenome reference improved SV calling in complex genomic regions. Moreover, we proved that combining minimap2 with Manta achieved performance comparable to DRAGEN for srWGS. For PacBio lrWGS data, Sniffles2 outperformed the other two tested tools. For ONT lrWGS, alignment with minimap2—among four aligners tested—consistently led to the best results. At up to 10× coverage, Duet achieved the highest accuracy, while at higher coverages, Dysgu yielded the best results. Conclusions: These results show for the first time that alignment software choice significantly impacts SV calling from srWGS, with results comparable to commercial solutions. For lrWGS, the performance depends on the technology and coverage. Full article
(This article belongs to the Special Issue Advances in Genomics and Bioinformatics of Human Disease)
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27 pages, 4299 KB  
Article
Causal Relationship Between Serum Uric Acid and Atherosclerotic Disease: A Mendelian Randomization and Transcriptomic Analysis
by Shitao Wang, Shuai Mei, Xiaozhu Ma, Qidamugai Wuyun, Li Zhou, Qiushi Luo, Ziyang Cai and Jiangtao Yan
Biomedicines 2025, 13(8), 1838; https://doi.org/10.3390/biomedicines13081838 - 28 Jul 2025
Viewed by 688
Abstract
Background/Objectives: Elevated serum uric acid levels are associated with the occurrence, development, and adverse events of coronary heart disease (CHD) and CHD risk factors. However, the extent of any pathogenic effect of the serum uric acid on CHD and whether CHD risk [...] Read more.
Background/Objectives: Elevated serum uric acid levels are associated with the occurrence, development, and adverse events of coronary heart disease (CHD) and CHD risk factors. However, the extent of any pathogenic effect of the serum uric acid on CHD and whether CHD risk factors play a confounding or mediating role are still unclear. Methods: The potential causal associations of serum uric acid with CHD were evaluated via cross-trait linkage disequilibrium score regression analysis and Mendelian randomization. The pleiotropy of genetic tools was analyzed via a Bayesian colocalization approach. Moreover, we utilized two-step MR to identify risk factors mediating the relationship between uric acid and CHD. Results: Mendelian randomization results derived from two genetic instrument selection strategies support that serum uric acid levels have a significant causal relationship with coronary artery disease, stable angina pectoris, and myocardial infarction. This causal relationship was partially mediated by diastolic blood pressure, mean arterial pressure, and serum triglycerides. Transcriptomic analysis revealed that serum uric acid may directly contribute to the development of atherosclerosis by inducing transcriptomic changes in macrophages. Conclusions: Our findings highlight that the control of serum urate concentration in the long-term management of CHD patients may be necessary. Well-designed clinical trials and foundational research are presently required to furnish conclusive proof regarding the specific clinical scenarios in which adequate reduction in urate concentrations can confer cardiovascular advantages. Full article
(This article belongs to the Special Issue Advances in Genomics and Bioinformatics of Human Disease)
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