Alternative splicing shapes transcriptome but not proteome diversity in Physcomitrella patens

Abstract

Alternative splicing (AS) can significantly impact the transcriptome and proteome of a eukaryotic cell. Here, using transcriptome and proteome profiling data, we analyzed AS in two life forms of the model moss Physcomitrella patens, namely protonemata and gametophores, as well as in protoplasts. We identified 12 043 genes subject to alternative splicing and analyzed the extent to which AS contributes to proteome diversity. We could distinguish a few examples that unambiguously indicated the presence of two or more splice isoforms from the same locus at the proteomic level. Our results indicate that alternative isoforms have a small effect on proteome diversity. We also revealed that mRNAs and pre-mRNAs have thousands of complementary binding sites for long non-coding RNAs (lncRNAs) that may lead to potential interactions in transcriptome. This finding points to an additional level of gene expression and AS regulation by non-coding transcripts in Physcomitrella patens. Among the differentially expressed and spliced genes we found serine/arginine-rich (SR) genes, which are known to regulate AS in cells. We found that treatment with abscisic (ABA) and methyl jasmonic acids (MeJA) led to an isoform-specific response and suggested that ABA in gametophores and MeJA in protoplasts regulate AS and the transcription of SR genes.

Distinct types of short open reading frames are translated in plant cells

“…3D). The level of transcription of some lncRNAs (according to the previous data (Fesenko et al 2017) and evidences of translation for the corresponding lncRNA-sORFs are shown in Fig. 3D.…”

“…We then classified the sORFs based on their location on the transcript: 63,109 “genic-sORFs” (located on annotated transcripts, but not on lncRNA), 1241 “intergenic-sORFs” (located on transcripts from our dataset and not annotated in the current version of the genome) and 5745 “lncRNA-sORFs” (located on lncRNAs from CantataDB (Szczesniak et al 2016), GreenC (Paytuvi Gallart et al 2016) or our data set (Fesenko et al 2017); Fig. 1B).…”

“…To select for sORFs that are transcribed, located in the exons of transcripts, and have introns, a bed file was generated using a python script (GffParser.py) and intersected with exon positions extracted from a gff3 file of P. patens genome annotations. To identify intergenic-sORFs, the bed file was also intersected with transcribed regions determined based on our RNAseq data (Fesenko et al 2017). Using an R script, sORFs fully overlapping with exons were selected; 75,685 sORFs remained after this step.…”

“…S14. In the first step, lncRNA-sORFs were identified by searching for identical sORFs in known lncRNA databases, including CantataDB (Szczesniak et al 2016), GreenC (Paytuvi Gallart et al 2016) and our previously published moss dataset (Fesenko et al 2017). After this sORF bed file was intersected with moss genome annotation, the locations of the sORFs on transcripts were determined, resulting in the further classification of genic-sORFs into uORFs, dORFs, CDS-sORFs and interlaced-sORFs.…”

Alternative splicing and translation play important roles in parallel with transcriptional regulation during rice hypoxic germination

“…In summary, although stress-induced genome-wide AS changes have been extensively documented in various plant species (Yang et al, 2015; Thatcher et al, 2016; Van et al, 2016; Fesenko et al, 2017), the quantification of corresponding AS isoforms at the protein level have seldom been reported. In this study, a parallel RNA seq and proteomic approach defined as proteogenomic has been applied to achieve integrative analysis using both transcriptome and proteome data.…”