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1. Alternative splicing preferentially increases transcript diversity associated with stress responses in the extremophyte Schrenkiella parvula

   Wijesinghege, Chathura; Tran, Kieu-Nga; Dassanayake, Maheshi (October 2022, bioRxiv)

   Alternative splicing extends the coding potential of genomes by creating multiple isoforms from one gene. Isoforms can render transcript specificity and diversity to initiate multiple responses required during transcriptome adjustments in stressed environments. Although the prevalence of alternative splicing is widely recognized, how diverse isoforms facilitate stress adaptation in plants that thrive in extreme environments are unexplored. Here we examine how an extremophyte model, Schrenkiella parvula, coordinates alternative splicing in response to high salinity compared to a salt-stress sensitive model, Arabidopsis thaliana. We use Iso-Seq to generate full length reference transcripts and RNA-seq to quantify differential isoform usage in response to salinity changes. We find that single-copy orthologs where S. parvula has a higher number of isoforms than A. thaliana as well as S. parvula genes observed and predicted using machine learning to have multiple isoforms are enriched in stress associated functions. Genes that showed differential isoform usage were largely mutually exclusive from genes that were differentially expressed in response to salt. S. parvula transcriptomes maintained specificity in isoform usage assessed via a measure of expression disorderdness during transcriptome reprogramming under salt. Our study adds a novel resource and insight to study plant stress tolerance evolved in extreme environments. 

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2. Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis

   https://doi.org/10.1093/genetics/iyac017  

   Healey, Hope_M; Bassham, Susan; Cresko, William_A; Sanchez_Alvarado, ed., A. (February 2022, Genetics)

   Abstract Single-cell RNA sequencing is a powerful technique that continues to expand across various biological applications. However, incomplete 3′-UTR annotations can impede single-cell analysis resulting in genes that are partially or completely uncounted. Performing single-cell RNA sequencing with incomplete 3′-UTR annotations can hinder the identification of cell identities and gene expression patterns and lead to erroneous biological inferences. We demonstrate that performing single-cell isoform sequencing in tandem with single-cell RNA sequencing can rapidly improve 3′-UTR annotations. Using threespine stickleback fish (Gasterosteus aculeatus), we show that gene models resulting from a minimal embryonic single-cell isoform sequencing dataset retained 26.1% greater single-cell RNA sequencing reads than gene models from Ensembl alone. Furthermore, pooling our single-cell sequencing isoforms with a previously published adult bulk Iso-Seq dataset from stickleback, and merging the annotation with the Ensembl gene models, resulted in a marginal improvement (+0.8%) over the single-cell isoform sequencing only dataset. In addition, isoforms identified by single-cell isoform sequencing included thousands of new splicing variants. The improved gene models obtained using single-cell isoform sequencing led to successful identification of cell types and increased the reads identified of many genes in our single-cell RNA sequencing stickleback dataset. Our work illuminates single-cell isoform sequencing as a cost-effective and efficient mechanism to rapidly annotate genomes for single-cell RNA sequencing. 

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3. High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing

   https://doi.org/10.1038/s41467-023-38324-9  

   Shi, Zhuo-Xing; Chen, Zhi-Chao; Zhong, Jia-Yong; Hu, Kun-Hua; Zheng, Ying-Feng; Chen, Ying; Xie, Shang-Qian; Bo, Xiao-Chen; Luo, Feng; Tang, Chong; et al (May 2023, Nature Communications)

   Abstract Although long-read single-cell RNA isoform sequencing (scISO-Seq) can reveal alternative RNA splicing in individual cells, it suffers from a low read throughput. Here, we introduce HIT-scISOseq, a method that removes most artifact cDNAs and concatenates multiple cDNAs for PacBio circular consensus sequencing (CCS) to achieve high-throughput and high-accuracy single-cell RNA isoform sequencing. HIT-scISOseq can yield >10 million high-accuracy long-reads in a single PacBio Sequel II SMRT Cell 8M. We also report the development of scISA-Tools that demultiplex HIT-scISOseq concatenated reads into single-cell cDNA reads with >99.99% accuracy and specificity. We apply HIT-scISOseq to characterize the transcriptomes of 3375 corneal limbus cells and reveal cell-type-specific isoform expression in them. HIT-scISOseq is a high-throughput, high-accuracy, technically accessible method and it can accelerate the burgeoning field of long-read single-cell transcriptomics. 

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4. Platform-integrated mRNA isoform quantification

   https://doi.org/10.1093/bioinformatics/btz932  

   Sun, Jiao; Chang, Jae-Woong; Zhang, Teng; Yong, Jeongsik; Kuang, Rui; Zhang, Wei; Gorodkin, ed., Jan (December 2019, Bioinformatics)

   Abstract MotivationAccurate estimation of transcript isoform abundance is critical for downstream transcriptome analyses and can lead to precise molecular mechanisms for understanding complex human diseases, like cancer. Simplex mRNA Sequencing (RNA-Seq) based isoform quantification approaches are facing the challenges of inherent sampling bias and unidentifiable read origins. A large-scale experiment shows that the consistency between RNA-Seq and other mRNA quantification platforms is relatively low at the isoform level compared to the gene level. In this project, we developed a platform-integrated model for transcript quantification (IntMTQ) to improve the performance of RNA-Seq on isoform expression estimation. IntMTQ, which benefits from the mRNA expressions reported by the other platforms, provides more precise RNA-Seq-based isoform quantification and leads to more accurate molecular signatures for disease phenotype prediction. ResultsIn the experiments to assess the quality of isoform expression estimated by IntMTQ, we designed three tasks for clustering and classification of 46 cancer cell lines with four different mRNA quantification platforms, including newly developed NanoString’s nCounter technology. The results demonstrate that the isoform expressions learned by IntMTQ consistently provide more and better molecular features for downstream analyses compared with five baseline algorithms which consider RNA-Seq data only. An independent RT-qPCR experiment on seven genes in twelve cancer cell lines showed that the IntMTQ improved overall transcript quantification. The platform-integrated algorithms could be applied to large-scale cancer studies, such as The Cancer Genome Atlas (TCGA), with both RNA-Seq and array-based platforms available. Availability and implementationSource code is available at: https://github.com/CompbioLabUcf/IntMTQ. Supplementary informationSupplementary data are available at Bioinformatics online. 

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5. Identification of cell-type specific alternative transcripts in the multicellular alga Volvox carteri

   Balasubramanian, Ravi Nicholas; Gao, Minglu; Umen, James (October 2023, BMC genomics)

   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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