Michael Morikone

Identification of Long Non-Coding RNA and Alternative Splicing Events During Tomato Fruit Development

Project Summary

Long non-coding RNAs (lncRNAs) are a class of regulatory RNA that are longer than 200 base pairs and do not code for protein. Alternative splicing (AS) is a process in gene transcription where a multi-exon gene is spliced into two or more different mature transcripts. Solanum lycopersicum, a model plant for fleshy fruit development, was studied through the use of RNA-Seq analysis for lncRNAs and AS events in order to better understand the molecular mechanisms of fleshy fruit development. Five distinct stages of tomato fruit with three biological replicates were used to monitor the changes in cell expanison, maturation and ripening. My project was based around generating a comprehensive list of isoforms from the RNA-Seq data in order to identify lncRNAs, AS events, and new protein-coding genes. It was determined from this dataset that there were 565 lncRNAs with 162 of these having significant changes in expression during fruit development. It was also shown that 289 paired isoforms had significant differential expression between stages. Additionally, there were 214 new protein coding genes that were identified from the dataset. A new lncRNA was identified that is an example of a cis-natural antisense transcript, which showed an inverted expression pattern to a zeta-carotene isomerase gene, a key component of lycopene biosynthesis, suggesting a possible regulatory role of this lncRNA in carotenogenesis. Identification of these lncRNAs and AS events will provide valuable resources for future research on the molecular mechanisms of gene regulation in fruit development, leading to the betterment of fruiting crops.

My Experience

I am an undergraduate student at California State University San Bernardino where I am close to graduating with degrees in both bioinformatics and biology. The bioinformatics program at my home institution is a combination of discrete biology, computer science, and mathematics courses, so having this bioinformatics experience at BTI has been very valuable. While I have had other bioinformatics related research experiences, my time at BTI has proved to be the most helpful as a budding scientist. The relationship with my mentor was very informative and allowed me to learn many things that I have not had the opportunity to otherwise. Outside of my project, there were also seminars and lab meetings that were commonly held that provided a scientific forum which further fed my interests in bioinformatics. After this internship experience, I am much more confident in my pursuit of a Ph.D. in bioinformatics or computational biology.

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