Singletrome enhances detection of long noncoding RNAs in single cell transcriptomes
Abstract Single cell RNA sequencing (scRNA-seq) has revolutionized the study of gene expression in individual cell types, but scRNA-seq studies have focused primarily on expression of protein-coding genes. Long noncoding RNAs (lncRNAs) are more diverse than protein-coding genes, yet remain underexpl...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-13528-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849333381671682048 |
|---|---|
| author | Raza Ur Rahman Iftikhar Ahmad Zixiu Li Robert P Sparks Amel Ben Saad Alan C Mullen |
| author_facet | Raza Ur Rahman Iftikhar Ahmad Zixiu Li Robert P Sparks Amel Ben Saad Alan C Mullen |
| author_sort | Raza Ur Rahman |
| collection | DOAJ |
| description | Abstract Single cell RNA sequencing (scRNA-seq) has revolutionized the study of gene expression in individual cell types, but scRNA-seq studies have focused primarily on expression of protein-coding genes. Long noncoding RNAs (lncRNAs) are more diverse than protein-coding genes, yet remain underexplored in part because they are underrepresented in reference annotations applied to scRNA-seq. Merging annotations containing protein-coding and lncRNA genes is not sufficient, because the addition of lncRNA genes that overlap in sense and antisense with protein-coding genes will affect how reads are counted for both protein-coding and lncRNA genes. Here, we introduce Singletrome, a Singularity image that integrates protein-coding and lncRNA gene transfer format (GTF) annotations to generate enhanced annotations that take into account the sense and antisense overlap of annotated genes, maps scRNA-seq data, and produces files for downstream analysis and visualization. With Singletrome, we detected thousands of lncRNAs not included in GENCODE, clustered cell types based solely on lncRNA expression, and demonstrated that machine learning can predict cell type and disease through lncRNAs alone. This comprehensive annotation will allow mapping of lncRNA expression across cell types of the human body, facilitating the development of an atlas of human lncRNAs in health and disease with the ability to integrate new lncRNA annotations as they become available. |
| format | Article |
| id | doaj-art-fe0b4bfd7e374fdea94232db1a90e50e |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-fe0b4bfd7e374fdea94232db1a90e50e2025-08-20T03:45:52ZengNature PortfolioScientific Reports2045-23222025-08-0115111610.1038/s41598-025-13528-9Singletrome enhances detection of long noncoding RNAs in single cell transcriptomesRaza Ur Rahman0Iftikhar Ahmad1Zixiu Li2Robert P Sparks3Amel Ben Saad4Alan C Mullen5Division of Gastroenterology, University of Massachusetts Chan Medical SchoolDepartment of Software Engineering, University of Europe for Applied SciencesPopulation and Quantitative Health Sciences, University of Massachusetts Chan Medical SchoolDivision of Gastroenterology, University of Massachusetts Chan Medical SchoolDivision of Gastroenterology, University of Massachusetts Chan Medical SchoolDivision of Gastroenterology, University of Massachusetts Chan Medical SchoolAbstract Single cell RNA sequencing (scRNA-seq) has revolutionized the study of gene expression in individual cell types, but scRNA-seq studies have focused primarily on expression of protein-coding genes. Long noncoding RNAs (lncRNAs) are more diverse than protein-coding genes, yet remain underexplored in part because they are underrepresented in reference annotations applied to scRNA-seq. Merging annotations containing protein-coding and lncRNA genes is not sufficient, because the addition of lncRNA genes that overlap in sense and antisense with protein-coding genes will affect how reads are counted for both protein-coding and lncRNA genes. Here, we introduce Singletrome, a Singularity image that integrates protein-coding and lncRNA gene transfer format (GTF) annotations to generate enhanced annotations that take into account the sense and antisense overlap of annotated genes, maps scRNA-seq data, and produces files for downstream analysis and visualization. With Singletrome, we detected thousands of lncRNAs not included in GENCODE, clustered cell types based solely on lncRNA expression, and demonstrated that machine learning can predict cell type and disease through lncRNAs alone. This comprehensive annotation will allow mapping of lncRNA expression across cell types of the human body, facilitating the development of an atlas of human lncRNAs in health and disease with the ability to integrate new lncRNA annotations as they become available.https://doi.org/10.1038/s41598-025-13528-9 |
| spellingShingle | Raza Ur Rahman Iftikhar Ahmad Zixiu Li Robert P Sparks Amel Ben Saad Alan C Mullen Singletrome enhances detection of long noncoding RNAs in single cell transcriptomes Scientific Reports |
| title | Singletrome enhances detection of long noncoding RNAs in single cell transcriptomes |
| title_full | Singletrome enhances detection of long noncoding RNAs in single cell transcriptomes |
| title_fullStr | Singletrome enhances detection of long noncoding RNAs in single cell transcriptomes |
| title_full_unstemmed | Singletrome enhances detection of long noncoding RNAs in single cell transcriptomes |
| title_short | Singletrome enhances detection of long noncoding RNAs in single cell transcriptomes |
| title_sort | singletrome enhances detection of long noncoding rnas in single cell transcriptomes |
| url | https://doi.org/10.1038/s41598-025-13528-9 |
| work_keys_str_mv | AT razaurrahman singletromeenhancesdetectionoflongnoncodingrnasinsinglecelltranscriptomes AT iftikharahmad singletromeenhancesdetectionoflongnoncodingrnasinsinglecelltranscriptomes AT zixiuli singletromeenhancesdetectionoflongnoncodingrnasinsinglecelltranscriptomes AT robertpsparks singletromeenhancesdetectionoflongnoncodingrnasinsinglecelltranscriptomes AT amelbensaad singletromeenhancesdetectionoflongnoncodingrnasinsinglecelltranscriptomes AT alancmullen singletromeenhancesdetectionoflongnoncodingrnasinsinglecelltranscriptomes |