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   RNA-Seq as said previously allows to quantify RNA into a cell at a particular time. With NGS development, a huge amount of data became available to scientists. They actually needed peoples to compute these data and this is when bioinformaticians came up. Computers are actually thought to treat a lot of data faster than humans. Thus, a lot of tools were developed to process NGS outputs. For the competition we used some of these tools to study splicing in C. elegans organism. Lets see how we proceeded !

   In bioinformatics, sequence alignment is a way of arranging RNA sequences in relation to each other, to determine their structure or function similarities. Sequences are stored in a matrix where rows from each sequence are compared. Gaps can be added into sequences so that identical or similar characters are aligned in successive columns. The organism studied here is <i> C.elegans</i>. The purpose here was to align RNAseq reads to its reference genome by using the Hisat algorithm.

  RNA is transcribed from DNA sequences that are composed of alternating coding exons and non-coding introns. A pre-RNA is produced that contains the transcribed Exons and Introns.

  Out of this pre-RNA, only coding Exons must be kept and the introns removed. This process of removing introns is called splicing. Different combinations of exons can be brought together to produce different variants of the protein to be, in a process called alternative splicing.

  It is those spliced RNA sequences that are then sequenced. To do, so they are retro-transcribed into their complementary DNA, the cDNA. This DNA is sequenced using NGS.

   Current sequencing technologies methods split the large DNA molecules to be sequenced into small chunks called reads. These reads sequences are mapped to the genome reference using algorithms like bowtie. Because reads are small, some sequences can be redundant, present at different locations in the genome, making them hard to map. To circumvent this, a technique of mapping called paired-end is used. It consists in sequencing a cDNA fragment at its extremities in both directions, 3’ to 5’ and 5’ to 3’ (reverse strand). Because these reads originate from the same fragment the distance between them is know and it is easier to map them. Indeed, if two reads can map at a same location only one will have its pair mapping further at the correct distance.

   These fastq files are the input for the HISAT software, based on bowtie, it performs the mapping of the reads on the genome. HISAT was used with the parameters previously described in the work of Denis Dupuy that produced the reference junctions file (ref). HISAT outputs bam files, they are a binary version of a sam file which contains the mapping informations like localisation of sequences reads sequences.

<p>If the biology team had produced a modified <i>C.elegans</i> worm, we would have been interested in checking if other gene splicing were impacted by the genetic construct. We therefore compared muscle and neuron alternative splicing patterns in order to identify specific genes which could be responsible for the differentiation in one of the tissue studied.

It could also have been possible to compare RNA-Seq samples from our worms to neuron or muscle specific WT patterns and detect modified junction usages.

<h3>3.1. Validating the efficiency of the pipeline results</h2>

<p>Since we knew a priori the behavior of unc60, it was an interesting positive control to investigate. We can see on the plot that muscular isoform B and non-muscular isoform A usages behave as expected. Indeed, in the muscle, the usage ratio for UNC-60B is 0.98 versus 0.02 for UNC-60A, a very dichotomic junction usage reflecting the muscle isoform specificity. In contrast, the usages ratios for both isoforms are neighbouring 0.5, which would indicate that both isoforms are used in neuron.</p>

<p>We had no a priori knowledge about ric-4 but it caught our attention since its behavior is very characteristic of an outlier. Actually its two isoforms are located on the opposite of the diagonal meaning an inversion of spliced forms in comparison with the genes located in the central area. We can see one form very used in the neuron whereas the other one is more used in the muscular tissue.We then investigate the role of ric-4. Thus we found that this gene is involved in the structuration of synapses and their functions.  

ric-4 is thought to be related to vesicles trafficking including SNARE vesicles. It is tagged as involved in synapses structuration and function. However SNARE vesicles processes are also found in muscle. Therefore muscle and neuron specific isoforms of these vesicular transport related proteins could exist.</p>

<p>rsr-1 was picked up because it presents a splicing pattern very similar to UNC-60. Indeed, rsr-1 isoforms in muscle have poles-apart usage ratios (0.98 vs 0.02) while in neuron this dichotomic usage is quite less pronounced (0.65 vs 0.35). rsr-1 is a homolog of SR160m, a splicing co-activator. It is important for development including normal pharyngeal morphology.

In Ensembl database this gene is featuring only one splice variant. We obtained 7 and 229 read counts for muscular isoforms, and 7 and 13 for the neuron. The few read counts could be due to mapping errors, revealing alternative junctions that are not actually real. This is possible in regions of lower complexity. rsr-1 actually present a low complexity region, long serine and arginine repeats.</p>

<p>We would like to underline something else which can also be used with our pipeline. Recently, a scientific team generated a reference file for spliced isoforms for the whole C.elegans genome. Combining our pipeline with this new information could allow us to spot specific splicing in a tissue specific manner. This could allow scientists to detect splicing variations in their sample in comparison with “reference” usage values. Thus we are currently working on the upgrade of our scripts to take into account this reference file.

We had the idea to apply the method used to generate the reference file for C.elegans to create tissues specific references. Using this could refine the analysis since the reference file currently generated is based on the whole body, and does not reflect the reality in a specific tissue.

<p style="font-size:1.5em; text-align:center; color:white">Feel free to email us to provide some feedback on our project, have some information on the team and our work, or to just say hello !</p>

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