An emerging model organism <i>Caenorhabditis elegans</i> for alternative pre‐<scp>mRNA</scp> processing <i>in vivo</i>

Wani, Shotaro; Kuroyanagi, Hidehito

doi:10.1002/wrna.1428

Cited by 10 publications

(8 citation statements)

References 87 publications

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“…Furthermore, subcellular specificity has also been observed in the C. elegans ventral nerve cord, where synaptic tiling of motor neurons DA8 and DA9 depends on the transmembrane Semaphorins and PLX-1/Plexin (Mizumoto & Shen, 2013). Given the low frequency of C. elegans genes that exhibit alternative splicing (Wani & Kuroyanagi, 2017), it is perhaps surprising that the IE model can capture 85% of synaptic specificity in the nerve ring. This could be a consequence of the reduced complexity of the C. elegans nervous system relative to other organisms.…”

Section: Discussionmentioning

confidence: 99%

“…Alternative splicing allows for a gene to code for multiple isoform proteins and could increase the number of unique CAM expression labels. C. elegans exhibits little isoform diversity compared to other organisms (25% of protein-coding genes in C. elegans exhibit alternative splicing (Wani & Kuroyanagi, 2017) compared to 95% in humans (Pan et al, 2008)). Moreover, there are rarely more than 10 isoforms expressed by an alternatively spliced CAM gene, compared to the thousands to tens-of-thousands expressed in other organisms (Zipursky & Sanes, 2010).…”

Section: Relative Process Placement Is Specifiedmentioning

confidence: 99%

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Volumetric reconstruction of main Caenorhabditis elegans neuropil at two different time points

Brittin

Cook

Hall³

et al. 2018

Preprint

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Detailed knowledge of both synaptic connectivity and the spatial proximity of neurons is crucial for understanding wiring specificity in the nervous system. Here, we volumetrically reconstructed the C. elegans nerve ring from legacy serial-sectioned electron micrographs at two distinct time points: the L4 and young adult. The new volumetric reconstructions provide detailed spatial and morphological information of neural processes in the nerve ring. Our analysis suggests that the nerve ring exhibits three levels of wiring specificity: spatial, synaptic and subcellular. Neuron classes innervate well defined neighborhoods and aggregate functionally similar synapses to support distinct computational pathways. Connectivity fractions vary based on neuron class and synapse type. We find that the variability in process placement accounts for less than 20% of the variability in synaptic connectivity and models based only on spatial information cannot account for the reproducibility of synaptic connections among homologous neurons. This suggests that additional, non-spatial factors also contribute to synaptic and subcellular specificity. With this in mind, we conjecture that a spatially constrained, genetic model could provide sufficient synaptic specificity. Using a model of cell-specific combinatorial genetic expression, we show that additional specificity, such as sub-cellular domains or alternative splicing, would be required to reproduce the wiring specificity in the nerve ring.

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Section: Discussionmentioning

confidence: 99%

Section: Relative Process Placement Is Specifiedmentioning

confidence: 99%

Volumetric reconstruction of main Caenorhabditis elegans neuropil at two different time points

Brittin

Cook

Hall³

et al. 2018

Preprint

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“…To begin to understand how AS regulation is coordinated across animal development, we use C . elegans as a simple animal model (its use as a model for studying AS regulation is reviewed in [ 3 , 40 ]). C .…”

Section: Introductionmentioning

confidence: 99%

The combinatorial control of alternative splicing in C. elegans

Fraser

2017

PLoS Genet

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Normal development requires the right splice variants to be made in the right tissues at the right time. The core splicing machinery is engaged in all splicing events, but which precise splice variant is made requires the choice between alternative splice sites—for this to occur, a set of splicing factors (SFs) must recognize and bind to short RNA motifs in the pre-mRNA. In C. elegans, there is known to be extensive variation in splicing patterns across development, but little is known about the targets of each SF or how multiple SFs combine to regulate splicing. Here we combine RNA-seq with in vitro binding assays to study how 4 different C. elegans SFs, ASD-1, FOX-1, MEC-8, and EXC-7, regulate splicing. The 4 SFs chosen all have well-characterised biology and well-studied loss-of-function genetic alleles, and all contain RRM domains. Intriguingly, while the SFs we examined have varied roles in C. elegans development, they show an unexpectedly high overlap in their targets. We also find that binding sites for these SFs occur on the same pre-mRNAs more frequently than expected suggesting extensive combinatorial control of splicing. We confirm that regulation of splicing by multiple SFs is often combinatorial and show that this is functionally significant. We also find that SFs appear to combine to affect splicing in two modes—they either bind in close proximity within the same intron or they appear to bind to separate regions of the intron in a conserved order. Finally, we find that the genes whose splicing are regulated by multiple SFs are highly enriched for genes involved in the cytoskeleton and in ion channels that are key for neurotransmission. Together, this shows that specific classes of genes have complex combinatorial regulation of splicing and that this combinatorial regulation is critical for normal development to occur.

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“…Using the advantages of transparent model organisms and colourful reporter genes, in vivo minigene assays have been developed using C. elegans (Wani and Kuroyanagi, 2017). This fluorescent in vivo minigene reporter allows the visualisation of tissue-specific alternative splicing patterns in a model organism.…”

Section: Animal Models For Splicing Analysismentioning

confidence: 99%

RNA splicing analysis in genomic medicine

Wai

Douglas

Baralle

2019

The International Journal of Biochemistry & Cell Biology

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High-throughput next-generation sequencing technologies have led to a rapid increase in the number of sequence variants identified in clinical practice via diagnostic genetic tests. Current bioinformatic analysis pipelines fail to take adequate account of the possible splicing effects of such variants, particularly where variants fall outwith canonical splice site sequences, and consequently the pathogenicity of such variants may often be missed. The regulation of splicing is highly complex and as a result, in silico prediction tools lack sufficient sensitivity and specificity for reliable use. Variants of all kinds can be linked to aberrant splicing in disease and the need for correct identification and diagnosis grows ever more crucial as novel splice-switching antisense oligonucleotide therapies start to enter clinical usage. RT-PCR provides a useful targeted assay of the splicing effects of identified variants, while minigene assays, massive parallel reporter assays and animal models can also be used for more detailed study of a particular splicing system, given enough time and resources. However, RNA-sequencing (RNA-seq) has the potential to be used as a rapid diagnostic tool in genomic medicine. By utilising data science approaches and machine learning, it may prove possible to finally understand and interpret the 'splicing code' and apply this knowledge in human disease diagnostics.

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An emerging model organism Caenorhabditis elegans for alternative pre‐mRNA processing in vivo

Cited by 10 publications

References 87 publications

Volumetric reconstruction of main Caenorhabditis elegans neuropil at two different time points

Volumetric reconstruction of main Caenorhabditis elegans neuropil at two different time points

The combinatorial control of alternative splicing in C. elegans

RNA splicing analysis in genomic medicine

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