» Articles » PMID: 39263210

Unveiling Axolotl Transcriptome for Tissue Regeneration with High-resolution Annotation Via Long-read Sequencing

Overview
Specialty Biotechnology
Date 2024 Sep 12
PMID 39263210
Authors
Affiliations
Soon will be listed here.
Abstract

Axolotls are known for their remarkable regeneration ability. Exploring their transcriptome provides insight into regenerative mechanisms. However, the current annotation of the axolotl transcriptome is limited, leaving the role of unannotated transcripts in regeneration unknown. To discourse this challenge, we exploited long-read sequencing technology, which enables direct observation of full-length RNA transcripts, greatly enhancing the coverage and accuracy of axolotl transcriptome annotation. By utilizing this method, we identified 222 novel gene loci and 4775 novel transcripts, which were quantified using short-read sequencing data. Through the inclusive analysis, we discovered novel homologs, potential functional proteins, noncoding RNAs, and alternative splicing events in key regeneration pathways. In particular, we identified novel transcripts with high protein-coding potential implicated in cell cycle regulation and musculoskeletal development, and regeneration were identified. Interestingly, alternative splice variants were also detected across diverse pathways critical to regeneration. This specifies that these novel transcripts potentially play vital roles underpinning the robust regenerative capacities of axolotls. Single-cell transcriptomic analysis further revealed these isoforms to predominantly exist in axolotl limb chondrocytes and mature tissue cell populations. Overall, the findings significantly advanced consideration of the axolotl transcriptome and provided a new perspective for understanding the mechanisms of regenerative abilities of axolotls.

References
1.
Pan Q, Shai O, Lee L, Frey B, Blencowe B . Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet. 2008; 40(12):1413-5. DOI: 10.1038/ng.259. View

2.
Trapnell C, Williams B, Pertea G, Mortazavi A, Kwan G, van Baren M . Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010; 28(5):511-5. PMC: 3146043. DOI: 10.1038/nbt.1621. View

3.
Kim D, Paggi J, Park C, Bennett C, Salzberg S . Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019; 37(8):907-915. PMC: 7605509. DOI: 10.1038/s41587-019-0201-4. View

4.
Hao Y, Hao S, Andersen-Nissen E, Mauck 3rd W, Zheng S, Butler A . Integrated analysis of multimodal single-cell data. Cell. 2021; 184(13):3573-3587.e29. PMC: 8238499. DOI: 10.1016/j.cell.2021.04.048. View

5.
Watson D, Bayik D, Storevik S, Moreino S, Sprowls S, Han J . GAP43-dependent mitochondria transfer from astrocytes enhances glioblastoma tumorigenicity. Nat Cancer. 2023; 4(5):648-664. PMC: 10212766. DOI: 10.1038/s43018-023-00556-5. View