How can alternative rna splicing generate

While each type of alternative splicing described above is distinct from one another, these events can simultaneously occur after pre-mRNA constructs are formed.

What is alternative splicing? Alternative splicing is a molecular mechanism that modifies pre-mRNA constructs prior to translation. The mRNA transcripts created from alternative splicing can translate into varying amino acid sequences that produce protein isoforms with different functions. But, as you probably know by now, biology is never that simple. Removal of these introns leaves only the protein-coding regions, called exons, which must be joined by RNA splicing to produce mature mRNA to allow for the translation of a functional protein.

These findings were later extended to other organisms including eukaryotes. As a quick summary—most genes in higher eukaryotes are transcribed as pre-mRNA, which contains non-coding and coding regions known as introns and exons, respectively. In a process mediated by the spliceosome, introns are removed while exons remain to give a final mature mRNA sequence. I would have expected introns to be kept in the sequence and exons to exit the scene. But that would be too obvious!

RNA splicing was discovered in the s, first in viruses and then in eukaryotes [2,3]. Soon after, scientists discovered alternative patterns of pre-mRNA splicing that produced different mature mRNAs containing various combinations of exons from a single precursor mRNA.

Therefore, alternative splicing, a type of post-transcriptional modification, is the process by which exons or portions of exons or non-coding regions within a pre-mRNA transcript are differentially joined or skipped, resulting in multiple protein isoforms being encoded by a single gene. As a result, alternative splicing increases the complexity of the proteome that can be generated from the available genome sequences. The first example of alternative splicing of a cellular gene in eukaryotes was identified in the IgM gene, a member of the immunoglobulin superfamily.

This splicing mechanism increases the informational diversity and functional capacity of a gene during post-transcriptional processing and provides an opportunity for gene regulation Figure 1. Figure 1. Alternative splicing generates transcriptome diversity and enables gene regulation. It can generate mRNAs that encode proteins with different or even opposite functions. Figure used with permission. Well, it plays a crucial role in generating biological complexity and proteomic diversity in humans and significantly affects various functions in cellular processes, tissue specificity, developmental states, and disease conditions.

As a result, alternative splicing is often involved in human disease e. Frequently, AS generates transcripts with premature termination codons PTCs that can be targeted to the nonsense-mediated mRNA decay NMD pathway, although an incomplete mRNA can also be translated for regulating the function of the corresponding full-length protein [ 14 , 15 , 16 ].

RNA splicing occurs mainly co-transcriptionally, inside the nucleus, and is mediated by the spliceosome machinery involving many regulatory proteins [ 17 ]. The regulation of AS modifies the ratio of different transcript isoforms that can be active in a specific tissue or at a particular developmental stage [ 13 ].

Light-induced regulation of AS plays a key role in plant morphogenesis, and the circadian clock, which orchestrates some major physiological processes, also regulates AS [ 19 , 20 ]. In addition, differential splicing is highly responsive to stress factors, such as low or high temperature, high salt concentrations and water or nutrient deficiency, probably allowing for rapid adaptation to changing environmental conditions [ 21 ].

In grapevine, like in other plant species, these different stress factors have previously been shown to regulate gene AS [ 22 , 23 , 24 , 25 ]. SR genes, which play a major role in gene splicing, are themselves subjected to AS modulation, especially under stress conditions, and may regulate the splicing of multiple downstream target pre-mRNAs, at the same time, to modify the transcriptome [ 26 , 27 ].

The analysis of pooled RNAseq data from leaves, roots and berries exposed to various stress conditions, together with the comparison of two rootstock varieties, suggested that tissue, environmental conditions and even genotype may contribute to the diversity of AS profiles [ 22 ]. The study of the transcriptome of mature berries collected from ten grapevine varieties with various metabolic profiles further showed that more than half of the expressed multiexon genes produced several splice isoforms, the majority of which were conserved between varieties [ 29 ].

The following study was aimed at acquiring new knowledge about the factors underlying grape berry ripening, whose control is highly desirable in view of the adaptation of grapevine varieties to climate warming. Considering that differential splicing could play an important role in that developmental process, we analysed the regulation of AS in berries of two contrasting white Vitis vinifera L. These two grapevine varieties present marked phenotypic differences, and their progenies show a strong variability that has previously been used for detecting QTLs linked to agronomic traits.

Among these traits, the berries of Gw and Ri differ in color, sugar and aroma precursor contents [ 30 , 31 , 32 ], as well as in the concentration of several biochemical compounds malic acid, tartaric acid, potassium ion influencing their pH level [ 33 , 34 ].

This approach allowed us to compare samples from the two varieties, at each stage, regardless of the speed of ripening progression for each variety. To closely track the variation of AS during berry development, our strategy consisted in the comparison of consecutive stages, representing crucial steps in the physiological development of the grape berry: first, a step of intense cellular division and expansion from S1 to S2 , then the shift to ripening from S2 to S3 , and finally a step of strong accumulation of sugars and secondary metabolites from S3 to S4.

The logical sequencing of the comparisons enabled us to consistently link the splicing variations detected to the biological processes occurring during the different phases. In addition, we statistically analysed the difference in gene AS between the two varieties at the different stages. The comparisons were performed using the software rMATS replicate Multivariate-Analysis-of-Transcript-Splicing , primarily designed for AS analysis from replicate human samples [ 36 ], and that has recently been shown to be effective for accurate detection of differential AS DAS events in plant species [ 37 ].

The comparisons between consecutive stages in Gw and Ri, and between the two varieties at each stage, were performed using replicates of RNAseq data obtained from berries harvested at four developmental stages, i. For each AS event, the rMATS software distinguished two alternative isoforms and estimated the inclusion level IL as the proportion of the longest isoform among the total, which indicated the degree of AS.

A total of unique differential events affected different genes, aggregating AS events which varied between consecutive stages and between the two varieties, as well as 49 AS events varying at both stage and variety level Fig. Among these, 67 AS events were newly identified with reference to the VCost. The list, genomic coordinates and general description of these DAS events are exhaustively reported in the Additional file 2.

The results of gene ontology GO analysis performed on gene sets compiled either from stage or variety comparisons followed the same trends Additional file 3. Three other categories showed a weaker overrepresentation, i. These results suggest that the two varieties substantially differed in gene expression regulation by AS, in the studied conditions.

Additionally, the variation of AS was more pronounced, on average, when the two varieties were compared at any stage than when consecutive stages were compared for a single variety. Overall, The following presentation focuses on 80 genes affected by at least one DAS event with an absolute value of ILD exceeding 0.

DAS events detected during berry development in Gw and Ri. A number of genes underwent similar splicing regulation in Gw and Ri during the developmental phase investigated. They affected genes with defined or hypothetical roles in development, transport, stress response or regulation of gene expression.

The arrows indicate the position of the skipped exons. The transcript variants included in the VCost. The arrows respectively indicate the position of the skipped exon and of the retained intron. In contrast with the above-described cases, a number of splicing changes occurred in only one variety during the developmental period studied, suggesting a genotype-specific response to some internal or environmental stimuli.

Surprisingly, this AS event was not detected at all in the second variety, Ri. The other DAS events were of two types, depending on whether the ratios of isoforms were similar or not in the two varieties before mid-ripening Table 4. Eleven events corresponded to the former case, for which differences in isoform ratios between Gw and Ri were only detected at mid-ripening S4.

Finally, for a good number of additional AS events which were not significantly regulated between stages, we observed differential isoform ratios between Gw and Ri during the whole period of development studied Table 5.

Seven other AS events were also remarkable due to the predominance of a different isoform in each variety isoform shift. On the whole, the genes exhibiting variety-dependent splicing profiles were primarily related to the regulation of gene expression, to RNA processing and splicing, and secondarily to stress response and DNA damage repair.

Variety-specific AS events associated with the gain or loss of a splice site. The Sashimi plots showing RNAseq reads aligned to gene annotations are respectively color-coded in red for Gw and blue for Ri.

Subsequently, we examined the transcription rate of the genes that underwent AS regulation in the course of berry development in Gw and Ri. Among the genes above noticed for undergoing remarkable splicing regulation Tables 1 , 2 , 3 and 4 , MIEL1 Vitvi04g was subjected to similar transcriptional up-regulation in the two varieties 3-fold and 2. In addition, the transcription rates of BOR3 Vitvi05g and of another gene of unknown function Vitvi14g were respectively decreased 2.

By searching for regulation events of lower-intensity 0. In summary, very few of the genes affected by splicing variation during the studied period were concomitantly regulated at the transcriptional level, highlighting a lack of correlation between these two biological processes.

Our study was aimed at identifying AS variation during berry ripening, in two white grapevine varieties, Gw and Ri, that typically show differences related to phenology, as well as berry morphology and metabolism [ 30 , 31 , 32 , 33 , 34 , 35 ]. However, a total of unique AS events presented differential isoform ratios in the ten pairwise comparisons performed, one half in stage comparisons and the other half in variety comparisons.

Remarkably, almost one-quarter of these AS events had not been previously mentioned in the reference VCost. Despite the great interest in deciphering fruit development mechanisms in crop species, few similar studies have been reported until now. Moreover, some discrepancies appear, especially in the total number of differential AS events detected. These inconsistencies seem to be mostly attributable to the various levels of performance of the methods used for AS event detection and validation.

For instance, splicing analysis during the course of blueberry fruit development highlighted more than genes affected by AS regulation when using the Cuffdiff program, while the use of the ArabiTag algorithm enabled the identification of only ca. It is now accepted that increased sequencing depth, together with the consideration of multiple reads from replicate samples covering a splice junction, allow for improving the accuracy of AS event detection.

We used the rMATS software, shown effective in plants for accurate AS analysis from replicate data [ 37 ], to analyze and statistically validate the differential events occurring between two conditions, either consecutive stages, or the two varieties at each stage. Thereafter, we applied stringent threshold values for the number of reads covering the splice junction and for the ratio of splice isoforms ILs , in order to select only the most reliable results.

Indeed, the number of AS events can be overestimated when taking into account the many low abundant and incompletely spliced IR transcripts constituting a noise in the splicing process [ 40 ]. The investigation of AS in other plant species suggest that this type of event occurs much more frequently than generally reported.

For instance, ES events were found to be only 1. These findings argue in favor of a sofar underestimated importance of ES events in plants. It is worth mentioning that almost half of the differential ES events detected by rMATS were newly identified AS events, suggesting that this software was particularly well-suited to this task. While no particular GO term enrichment was found in the set of genes affected by AS events regulated between developmental stages, a special look to the most significant events showed that they mainly impacted some genes putatively involved in gene expression regulation, stress response and development cf.

Fruit formation is associated with numerous changes at the morphological and physiological levels and involves an intense metabolic activity. The stage-regulated AS events that were shared by the two varieties held our attention due to a possible role in berry development. Given the fact that ripening of the grape berry, a non-climacteric fruit, is highly dependent on ABA, the increasing predominance of XBAT Several other genes affected by similar splicing regulation in the two varieties, during berry ripening, deserve attention.

For instance, MAN2 Vitvi12g , involved in the hydrolysis of mannan polysaccharides which are structural components of the plant cell wall, was subjected to AS regulation before the start of berry softening and maturation, and secondarily, at the mid-ripening stage which is characterized by changes in osmotic pressure accompagnying cell wall disassembling.

In parallel, we measured a slight down-regulation of its transcription between S1 and S2 in Gw and Ri. This gene has previously been shown to be transcriptionally regulated during grape berry development, and its expression could be linked to the maintenance of cell wall relaxation and pericarp elasticity in the course of ripening [ 47 , 48 ]. This gene most probably regulates the trafficking of intracellular vesicles, a process tied to cell wall remodelling and textural changes during fruit maturation [ 51 ].

Likewise, the splicing regulation of MIEL1 Vitvi04g coding an E3-ubiquitin ligase involved in cuticular wax biosynthesis [ 52 ] could be significant in this context, particularly given that we observed its transcriptional up-regulation at the same time.

Waxy polymers confer hydrophobicity to the outer layer of the fruit skin, and their amount and composition have recently been shown to be modulated during berry development [ 53 ]. Their synthesis requires fatty acids whose metabolism has been shown to be transcriptionally regulated during the biogenesis of the grape berry exocarp [ 54 ].

We also detected the AS regulation of LPCAT1 Vitvi18g and ABCA1 Vitvi17g , respectively encoding a lysophosphatidylcholine acyltransferase catalysing the biosynthesis of lipids and a membrane lipid transporter, as well as of ITPK3 Vitvi18g belonging to a small gene family involved in the synthesis of phytic acid, which is an essential phosphore-storage component of plant seeds.

In addition, the AS regulation of CID5 Vitvi11g coding for a polyadenylate-binding-protein-interacting protein probably involved in endoploidy regulation could be linked to berry growth, as suggested by endoreduplication studies in tomato [ 55 ]. The genes belonging to the stress response pathways seem to be particularly prone to AS regulation, which is thought to be a way to promptly change the transcriptome in response to challenging environmental conditions [ 61 ].

Although grapevine plants generally tolerate moderate drought conditions, extreme light and temperature combined with water scarcity may negatively impact the development of varieties adapted to temperate climates [ 62 ]. The most unexpected finding of this study was the differential AS profiles exhibited by the two grapevine varieties. When gene AS was compared between Gw and Ri at each developmental stage, a total of differential events affecting different genes were detected.

The most distinctive AS events were events occurring specifically or very preferentially in a single variety cf. Tables 4 and 5 , Supplemental file 4. GO enrichment analysis suggested that the two varieties particularly differed in the splicing of genes related to transcription and translation regulation as well as to RNA splicing, itself.

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