Bioinformatics tools to classify and characterize plant small RNAs
| Author(s) | Hammond, Reza | |
| Date Accessioned | 2020-02-18T13:16:58Z | |
| Date Available | 2020-02-18T13:16:58Z | |
| Publication Date | 2019 | |
| SWORD Update | 2020-02-03T13:24:27Z | |
| Abstract | Small RNAs (sRNAs) in plants are a highly abundant class of noncoding RNAs that regulate silencing processes, mostly on the basis of sequence complementarity. There are several classes of small RNA that differ in both their biogenesis and mode of silencing. With the advent of next generation sequencing technologies, sRNA presence can be quantified at a relatively low cost and in a short amount of time. Due to the large amount of data however, there are many challenges associated with the classification of individual sRNAs in these datasets. It is for this reason that I have developed several tools to assist in the classification of sRNAs. The first of these tools is miRador, a novel micro RNA (miRNA) prediction tool that I designed to predict miRNAs from a set of sRNA libraries. This tool utilizes a newly established set of criteria for annotating plant miRNAs which enable it to predict miRNAs with a high level of accuracy. sPARTA is a miRNA target prediction and validation tool which utilizes Parallel Analysis of RNA Ends (PARE) sequencing libraries to validate target cleavage facilitated by a miRNA. Utilizing sPARTA in conjunction with miRador allows for the prediction and validation of novel miRNAs for a variety of plant species. In this dissertation, I utilize this pipeline on maize sRNA data to predict four novel miRNAs. I also present a clustering script that makes use of the Meyers Lab database systems to quickly cluster a variety of sequencing data. Using this approach, I attempted to characterize 24-nt phasiRNA producing loci for two separate projects, presented as case studies. In the first case study, we identify that 24-nt phasiRNAs in maize may be required for robust fertility at higher growth temperatures. In the second case study, we identify that asparagus generates inverted repeat-derived phasiRNAs from mRNAs lacking a miR2275 target site. Taken together, these tools improve scientists ability to characterize various classes of small RNAs, and their effects on their encoding genomes. | en_US |
| Advisor | Meyers, Blake C. | |
| Degree | Ph.D. | |
| Department | University of Delaware, Center for Bioinformatics and Computational Biology | |
| DOI | https://doi.org/10.58088/vxvq-br28 | |
| Unique Identifier | 1140968774 | |
| URL | http://udspace.udel.edu/handle/19716/25024 | |
| Language | en | |
| Publisher | University of Delaware | en_US |
| URI | https://search.proquest.com/docview/2307785089?accountid=10457 | |
| Title | Bioinformatics tools to classify and characterize plant small RNAs | en_US |
| Type | Thesis | en_US |