Identification of non-canonical ORFs and their potential biological function

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# Identification of non-canonical ORFs and their potential biological function

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				<a href="/training-material/hall-of-fame/gallardoalba/" class="contributor-badge contributor-gallardoalba"><img src="/training-material/assets/images/orcid.png" alt="orcid logo" width="36" height="36"/><img src="https://avatars.githubusercontent.com/gallardoalba?s=36" alt="Cristóbal Gallardo avatar" width="36" class="avatar" />
    Cristóbal Gallardo</a></li>
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## Requirements

Before diving into this slide deck, we recommend you to have a look at:

- [Introduction to Galaxy Analyses](/training-material/topics/introduction)

- [Sequence analysis](/training-material/topics/sequence-analysis)
    - Quality Control: [<i class="fab fa-slideshare" aria-hidden="true"></i><span class="visually-hidden">slides</span> slides](/training-material/topics/sequence-analysis/tutorials/quality-control/slides.html) - [<i class="fas fa-laptop" aria-hidden="true"></i><span class="visually-hidden">tutorial</span> hands-on](/training-material/topics/sequence-analysis/tutorials/quality-control/tutorial.html)
    - Mapping: [<i class="fab fa-slideshare" aria-hidden="true"></i><span class="visually-hidden">slides</span> slides](/training-material/topics/sequence-analysis/tutorials/mapping/slides.html) - [<i class="fas fa-laptop" aria-hidden="true"></i><span class="visually-hidden">tutorial</span> hands-on](/training-material/topics/sequence-analysis/tutorials/mapping/tutorial.html)

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## Index of contents

1. Introduction

2. Galaxy workflow

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## Introduction

- What do we mean by non-canonical ORFs?

- Why study non-canonical ORFs?

- Why have not been yet characterized?

- How identify non-canonical ORFs?

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## What do we mean by non-canonical ORFs?

![Definition of canonical](/training-material/topics/transcriptomics/images/differential_isoform/slides/cambridge_dictionary.png)

.footnote[Source: [Cambridge dictionary](https://dictionary.cambridge.org/dictionary/english/canonical)]

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## What do we mean by non-canonical ORFs?

![Mean Ribo-Seq expression and Ribo-Seq expression standard deviation (SD) have been plotted for human lymphoblastoid cells from RPFdbV2.](/training-material/topics/transcriptomics/images/differential_isoform/slides/expression_distribution.png)

.footnote[Source: <span class="citation"><a href="https://doi.org/10.1038/s41525-020-00167-4">Erady <i>et al.</i> 2021</a></span>]

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## What do we mean by non-canonical ORFs?

![The dark proteome: translation from noncanonical open reading frames.](/training-material/topics/transcriptomics/images/differential_isoform/slides/dark_proteome.png)

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## Why study non-canonical ORFs?

- Potentially novel <b>prognostic and diagnostic markers</b>

- The vast majority <b>have not been investigated</b>

- Particulary attractive as <b>allosteric celullar regulators</b>

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## Why study non-canonical ORFs?

![Noncanonical open reading frames enconde functional proteins essential for cancer cell survival.](/training-material/topics/transcriptomics/images/differential_isoform/slides/non-canonical_nature.png)

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## Why study non-canonical ORFs?

![Translation and natural selection of micropeptides from lon non-canonical RNAs.](/training-material/topics/transcriptomics/images/differential_isoform/slides/non-canonical_nature2.png)

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## Why have not been characterized?

- Arbitrary thresholds on ORF lengths
    - Peptides smaller than 100 aminoacids are usually discarted
- Frequently annotated as non-coding RNAs
- Propensity for structural disorder
    -  Discarted as intrinsically disordered proteins (IDPs)

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## Why study small peptides?

![The large unexplored biology of small proteins in pro and eukaryotes.](/training-material/topics/transcriptomics/images/differential_isoform/slides/small_peptides.png)

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## Why study small peptides?

![Short peptides regulate gene expression.](/training-material/topics/transcriptomics/images/differential_isoform/slides/short_peptides.png)

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## Why study small peptides?

![Example of small peptides biological function.](/training-material/topics/transcriptomics/images/differential_isoform/slides/small_peptides_examples.png)

.footnote[Source: <span class="citation"><a href="https://doi.org/10.1111/febs.15845">Steinberg and Koch 2021</a></span>]

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## Annotated as non-coding RNAs?

![Coding or non-coding? This is the question.](/training-material/topics/transcriptomics/images/differential_isoform/slides/question.jpg)

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## Annotated as non-coding RNAs?

![The small peptide world in long noncoding RNAs.](/training-material/topics/transcriptomics/images/differential_isoform/slides/small_non_coding.png)

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## Annotated as non-coding RNAs?

![SPENCER: a comprehensive database for small peptides encoded by noncanical RNAs in cancer patients.](/training-material/topics/transcriptomics/images/differential_isoform/slides/spencer_datase.png)

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## Why study intrinsically disordered proteins (IDP)?

![Why study intrinsically disordered proteins?](/training-material/topics/transcriptomics/images/differential_isoform/slides/disordered_regions.png)

.footnote[Source: <span class="citation"><a href="https://doi.org/10.1126/science.1228775">Babu <i>et al.</i> 2012</a></span>]

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## Disorder-Function Paradigm

![Disorder-Function paradigm.](/training-material/topics/transcriptomics/images/differential_isoform/slides/disorder_article.png)

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## Disorder-Function Paradigm

![Expanding the paradigm: intrinsically disordered proteins and allosteric regulation.](/training-material/topics/transcriptomics/images/differential_isoform/slides/intrinsically_disordered.png)

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## Disorder-Function Paradigm

![Intrinsically disordered proteins/regions and insight into their biomolecular interaction.](/training-material/topics/transcriptomics/images/differential_isoform/slides/disorder_protein.jpg)

.footnote[Source: <span class="citation"><a href="https://doi.org/10.1016/j.bpc.2022.106769">Chakrabarti and Chakravarty 2022</a></span>]

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## How identify non-canonical ORFs?

![How to identify non-canonical ORFs.](/training-material/topics/transcriptomics/images/differential_isoform/slides/scientist.jpg)

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## How identify non-canonical ORFs?

![IsoformSwitchAnalyzeR: analysis of changes in genome-wide patterns of alternative splicing and its functional consequences.](/training-material/topics/transcriptomics/images/differential_isoform/slides/isoform_switching.png)

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## How identify non-canonical ORFs?

![Illustration of isoform switch](/training-material/topics/transcriptomics/images/differential_isoform/slides/isoform_switching.jpg)

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## Galaxy Workflow

![Galaxy workflow.](/training-material/topics/transcriptomics/images/differential_isoform/slides/galaxy_training.png)

Full detailed explanation in the [Genome-wide alternative splicing analysis](/training-material/topics/transcriptomics/tutorials/differential-isoform-expression/tutorial.html) Galaxy training.

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## Galaxy Workflow

![Full workflow image.](/training-material/topics/transcriptomics/images/differential_isoform/full_workflow.png)

Full detailed explanation in the [Genome-wide alternative splicing analysis](/training-material/topics/transcriptomics/tutorials/differential-isoform-expression/tutorial.html) Galaxy training.

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## Galaxy Workflow

![Workflow summary.](/training-material/topics/transcriptomics/images/differential_isoform/galaxyworkflow.drawio.png)

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## Initial QC assessment

![QC step.Identify potential artifacts that may impact the interpretation of downstream analysis.](/training-material/topics/transcriptomics/images/differential_isoform/fastqc_per_base_sequence_quality.png)

Identify potential artifacts that may impact the interpretation of downstream analysis.

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## Mapping and identication of novel splicing sites with RNASTAR

![Mapping step with RNASTAR. Two-pass alignment enables sequence reads to span novel splice junctions by fewer nucleotides, conferring greater read depth and providing significantly more accurate quantification of novel splice junctions.](/training-material/topics/transcriptomics/images/differential_isoform/slides/STAR_pipeline.drawio.png)

Two-pass alignment enables sequence reads to span novel splice junctions by fewer nucleotides, conferring greater read depth and providing significantly more accurate quantification of novel splice junctions.

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## Post-mapping QC assessment with RSeQC

![Post-mapping QC. RSeQC is a toolkit for generating RNA-seq-specific quality control metrics. The figure corresponds to RSeQC junction saturation of known (A) and novel (B) splicing sites.](/training-material/topics/transcriptomics/images/differential_isoform/rseqc_junction_saturation_plot.png)

RSeQC is a toolkit for generating RNA-seq-specific quality control metrics. The figure corresponds to RSeQC junction saturation of known (A) and novel (B) splicing sites.

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## Reference-based transcriptome assembly and quantification with StringTie

![Transcriptome assembly and quantification with StringTie. StringTie is a fast and highly efficient assembler of RNA-seq alignments into potential transcripts.](/training-material/topics/transcriptomics/images/differential_isoform/slides/stringtie_pipeline.png)

StringTie is a fast and highly efficient assembler of RNA-seq alignments into potential transcripts.

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## Post-assembly QC assessment with rnaQUAST

![Post-assembly QC. rnaQUAST, which will provide us diverse completeness/correctness statistics very useful in order to identify and address potential errors or gaps in the assembly process. The figure is a rnaQUAST cummulative isoform plot.](/training-material/topics/transcriptomics/images/differential_isoform/rnaQUAST_cumulative_isoform.png)

rnaQUAST, which will provide us diverse completeness/correctness statistics very useful in order to identify and address potential errors or gaps in the assembly process. The figure is a rnaQUAST cummulative isoform plot.

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## Isoform switching and functional analysis with IsoformSwitchAnalyzeR

![Isoform switching and functional analysis. IsoformSwitchAnalyzieR performs the differential isoform usage analysis by using DEXSeq.](/training-material/topics/transcriptomics/images/differential_isoform/slides/isoformswitch_pipeline.png)

IsoformSwitchAnalyzieR performs the differential isoform usage analysis by using DEXSeq.

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## Isoform switching and functional analysis with IsoformSwitchAnalyzeR

![IsoformSwitchAnalyzeR consequences plot.](/training-material/topics/transcriptomics/images/differential_isoform/isoformSwitchAnalyzer_consequences_isoform.png)

To analyze large-scale patterns in predicted IS consequences, IsoformSwitchAnalyzeR computes all isoform switching events resulting in a gain/loss of a specific consequence (e.g. protein domain gain/loss)

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## Thank You!

This material is the result of a collaborative work. Thanks to the [Galaxy Training Network](https://training.galaxyproject.org) and all the contributors!

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<table class="contributions">
	
	<tr>
		<td><abbr title="These people wrote the bulk of the tutorial, they may have done the analysis, built the workflow, and wrote the text themselves.">Author(s)</abbr></td>
		<td>
			<a href="/training-material/hall-of-fame/gallardoalba/" class="contributor-badge contributor-gallardoalba"><img src="/training-material/assets/images/orcid.png" alt="orcid logo" width="36" height="36"/><img src="https://avatars.githubusercontent.com/gallardoalba?s=36" alt="Cristóbal Gallardo avatar" width="36" class="avatar" />
    Cristóbal Gallardo</a>
		</td>
	</tr>

<tr>
		<td><abbr title="These people edited the text, either for spelling and grammar, flow, GTN-fit, or other similar editing categories">Editor(s)</abbr></td>
		<td>
			<a href="/training-material/hall-of-fame/lldelisle/" class="contributor-badge contributor-lldelisle"><img src="/training-material/assets/images/orcid.png" alt="orcid logo" width="36" height="36"/><img src="https://avatars.githubusercontent.com/lldelisle?s=36" alt="Lucille Delisle avatar" width="36" class="avatar" />
    Lucille Delisle</a></td>
	</tr>

</table>

</div>

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Tutorial Content is licensed under <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.<br/>