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Applications and Progress in Single-Cell Genomics
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Applications and Progress in Single-Cell Genomics

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

Deadline for manuscript submissions: closed (10 March 2024) | Viewed by 2334

Special Issue Editor

Dr. Junil Kim

E-Mail Website
Guest Editor
School of Systems Biomedical Science, Soongsil University, Dongjak-Gu, Seoul 06978, Republic of Korea
Interests: systems biology; single-cell genomics; spatial transcriptomics; network biology

Special Issue Information

Dear Colleagues,

The rapid expansion of single-cell genomics technology has opened up avenues to unravel intricate biomolecular interactions with unprecedented precision and multimodal insights. Recently, the advent of spatial genomics has further enhanced the exploration of cell–cell interactions by incorporating neighboring cell context.

This Special Issue is dedicated to publishing information on state-of-the art single-cell genomics technologies and computational methodologies to elucidate the molecular mechanisms. Authors are encouraged to contribute their novel experimental technologies, analyses of newly acquired single-cell sequencing data, or innovative bioinformatics algorithms tailored for single-cell analysis.

Dr. Junil Kim
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

  • single-cell genomics
  • single-cell multiomics
  • spatial transcriptomics
  • single-cell analysis algorithms
  • deconvolution
  • cell–cell interactions

Published Papers (1 paper)

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Research

14 pages, 4256 KiB  
Article
Identification of Niche-Specific Gene Signatures between Malignant Tumor Microenvironments by Integrating Single Cell and Spatial Transcriptomics Data
by Jahanzeb Saqib, Beomsu Park, Yunjung Jin, Junseo Seo, Jaewoo Mo and Junil Kim
Genes 2023, 14(11), 2033; https://doi.org/10.3390/genes14112033 - 31 Oct 2023
Cited by 1 | Viewed by 2056
Abstract
The tumor microenvironment significantly affects the transcriptomic states of tumor cells. Single-cell RNA sequencing (scRNA-seq) helps elucidate the transcriptomes of individual cancer cells and their neighboring cells. However, cell dissociation results in the loss of information on neighboring cells. To address this challenge [...] Read more.
The tumor microenvironment significantly affects the transcriptomic states of tumor cells. Single-cell RNA sequencing (scRNA-seq) helps elucidate the transcriptomes of individual cancer cells and their neighboring cells. However, cell dissociation results in the loss of information on neighboring cells. To address this challenge and comprehensively assess the gene activity in tissue samples, it is imperative to integrate scRNA-seq with spatial transcriptomics. In our previous study on physically interacting cell sequencing (PIC-seq), we demonstrated that gene expression in single cells is affected by neighboring cell information. In the present study, we proposed a strategy to identify niche-specific gene signatures by harmonizing scRNA-seq and spatial transcriptomic data. This approach was applied to the paired or matched scRNA-seq and Visium platform data of five cancer types: breast cancer, gastrointestinal stromal tumor, liver hepatocellular carcinoma, uterine corpus endometrial carcinoma, and ovarian cancer. We observed distinct gene signatures specific to cellular niches and their neighboring counterparts. Intriguingly, these niche-specific genes display considerable dissimilarity to cell type markers and exhibit unique functional attributes independent of the cancer types. Collectively, these results demonstrate the potential of this integrative approach for identifying novel marker genes and their spatial relationships. Full article
(This article belongs to the Special Issue Applications and Progress in Single-Cell Genomics)
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