Maize

Small interfering RNA (siRNA) technology has vast potential for functional genomics and development of therapeutics. However, it faces many obstacles predominantly instability of siRNAs due to nuclease digestion and subsequently biologically short half-life. Chemical modifications in siRNAs provide means to overcome these shortcomings and improve their stability and potency. Despite enormous utility bioinformatics resource of these chemically modified siRNAs (cm-siRNAs) is lacking.

MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require "read count" to be included with the input sequences, which restricts their use to deep-sequencing data.

Endogenous small non-coding RNAs (sRNAs), including microRNAs, PIWI-interacting RNAs and small interfering RNAs, play important gene regulatory roles in animals and plants by pairing to the protein-coding and non-coding transcripts. However, computationally assigning these various sRNAs to their regulatory target genes remains technically challenging. Recently, a high-throughput degradome sequencing method was applied to identify biologically relevant sRNA cleavage sites.

Splicing is one of the major contributors to observed spatiotemporal diversification of transcripts and proteins in metazoans. There are numerous factors that affect the process, but splice sites themselves along with the adjacent splicing signals are critical here. Unfortunately, there is still little known about splicing in plants and, consequently, further research in some fields of plant molecular biology will encounter difficulties.