Background: Cell type specialization is a hallmark of complex multicellular organisms and is usually established through implementation of cell-type-specific gene expression programs. The multicellular green alga Volvox carteri has just two cell types, germ and soma, that have previously been shown to have very different transcriptome com- positions which match their specialized roles. Here we interrogated another potential mechanism for differentiation in V. carteri, cell type specific alternative transcript isoforms (CTSAI).
Methods: We used pre-existing predictions of alternative transcripts and de novo transcript assembly with HISAT2 and Ballgown software to compile a list of loci with two or more transcript isoforms, identified a small subset
that were candidates for CTSAI, and manually curated this subset of genes to remove false positives. We experimentally verified three candidates using semi-quantitative RT-PCR to assess relative isoform abundance in each cell type.
Results: Of the 1978 loci with two or more predicted transcript isoforms 67 of these also showed cell type isoform expression biases. After curation 15 strong candidates for CTSAI were identified, three of which were experimen- tally verified, and their predicted gene product functions were evaluated in light of potential cell type specific roles. A comparison of genes with predicted alternative splicing from Chlamydomonas reinhardtii, a unicellular relative of V. carteri, identified little overlap between ortholog pairs with alternative splicing in both species. Finally, we inter- rogated cell type expression patterns of 126 V. carteri predicted RBP encoding genes and found 40 that showed either somatic or germ cell expression bias. These RBPs are potential mediators of CTSAI in V. carteri and suggest possible pre-adaptation for cell type specific RNA processing and a potential path for generating CTSAI in the early ancestors of metazoans and plants.
Conclusions: We predicted numerous instances of alternative transcript isoforms in Volvox, only a small subset of which showed cell type specific isoform expression bias. However, the validated examples of CTSAI supported existing hypotheses about cell type specialization in V. carteri, and also suggested new hypotheses about mecha- nisms of functional specialization for their gene products. Our data imply that CTSAI operates as a minor but impor- tant component of V. carteri cellular differentiation and could be used as a model for how alternative isoforms emerge and co-evolve with cell type specialization.
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Identification of cell-type specific alternative transcripts in the multicellular alga Volvox carteri
Cell type specialization is a hallmark of complex multicellular organisms and is usually established through implementation of cell-type-specific gene expression programs. The multicellular green alga
We used pre-existing predictions of alternative transcripts and de novo transcript assembly with HISAT2 and Ballgown software to compile a list of loci with two or more transcript isoforms, identified a small subset that were candidates for CTSAI, and manually curated this subset of genes to remove false positives. We experimentally verified three candidates using semi-quantitative RT-PCR to assess relative isoform abundance in each cell type.
Of the 1978 loci with two or more predicted transcript isoforms 67 of these also showed cell type isoform expression biases. After curation 15 strong candidates for CTSAI were identified, three of which were experimentally verified, and their predicted gene product functions were evaluated in light of potential cell type specific roles. A comparison of genes with predicted alternative splicing from
We predicted numerous instances of alternative transcript isoforms in Volvox, only a small subset of which showed cell type specific isoform expression bias. However, the validated examples of CTSAI supported existing hypotheses about cell type specialization in
- NSF-PAR ID:
- 10471752
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- BMC Genomics
- Volume:
- 24
- Issue:
- 1
- ISSN:
- 1471-2164
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Results In this study, we present a novel approach, DIFFUSE (Deep learning-based prediction of IsoForm FUnctions from Sequences and Expression), to predict isoform functions. To integrate various types of data, our approach adopts a hybrid framework by first using a deep neural network (DNN) to predict the functions of isoforms from their genomic sequences and then refining the prediction using a conditional random field (CRF) based on co-expression relationship. To overcome the lack of isoform-level ground truth labels, we further propose an iterative semi-supervised learning algorithm to train both the DNN and CRF together. Our extensive computational experiments demonstrate that DIFFUSE could effectively predict the functions of isoforms and genes. It achieves an average area under the receiver operating characteristics curve of 0.840 and area under the precision–recall curve of 0.581 over 4184 GO functional categories, which are significantly higher than the state-of-the-art methods. We further validate the prediction results by analyzing the correlation between functional similarity, sequence similarity, expression similarity and structural similarity, as well as the consistency between the predicted functions and some well-studied functional features of isoform sequences.
Availability and implementation https://github.com/haochenucr/DIFFUSE.
Supplementary information Supplementary data are available at Bioinformatics online.
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Abstract Background The
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