Small RNAs in Plants

Assessing small RNA profiles in potato diploid hybrid and its resynthesized allopolyploid reveals conserved abundance with distinct genomic distribution

KEY MESSAGE

The shock produced by the allopolyploidization process on a potato interspecific diploid hybrid displays a non-random remobilization of the small RNAs profile on a variety of genomic features. Allopolyploidy, a complex process involving interspecific hybridization and whole genome duplication, significantly impacts plant evolution, leading to the emergence of novel phenotypes. Polyploids often present phenotypic nuances that enhance adaptability, enabling them to compete better and occasionally to colonize new habitats. Whole-genome duplication represents a genomic "shock" that can trigger genetic and epigenetic changes that yield novel expression patterns. In this work, we investigate the polyploidization effect on a diploid interspecific hybrid obtained through the cross between the cultivated potato Solanum tuberosum and the wild potato Solanum kurtzianum, by assessing the small RNAs (sRNAs) profile of the parental diploid hybrid and its derived allopolyploid. Small RNAs are key components of the epigenetic mechanisms involved in silencing by RNA-directed DNA Methylation (RdDM). A sRNA sequencing (sRNA-Seq) analysis was performed to individually profile the 21 to 22 nucleotide (21 to 22-nt) and 24-nt sRNA size classes due to their unique mechanism of biogenesis and mode of function. The composition and distribution of different genomic features and differentially accumulated (DA) sRNAs were evaluated throughout the potato genome. We selected a subset of genes associated with DA sRNAs for messenger RNA (mRNA) expression analysis to assess potential impacts on the transcriptome. Interestingly, we noted that 24-nt DA sRNAs that exclusively mapped to exons were correlated with differentially expressed mRNAs between genotypes, while this behavior was not observed when 24-nt DA sRNAs were mapped to intronic regions. These findings collectively emphasize the nonstochastic nature of sRNA remobilization in response to the genomic shock induced by allopolyploidization.

The evolutionary history of small RNAs in Solanaceae

The Solanaceae or "nightshade" family is an economically important group with remarkable diversity. To gain a better understanding of how the unique biology of the Solanaceae relates to the family's small RNA (sRNA) genomic landscape, we downloaded over 255 publicly available sRNA data sets that comprise over 2.6 billion reads of sequence data. We applied a suite of computational tools to predict and annotate two major sRNA classes: (1) microRNAs (miRNAs), typically 20- to 22-nucleotide (nt) RNAs generated from a hairpin precursor and functioning in gene silencing and (2) short interfering RNAs (siRNAs), including 24-nt heterochromatic siRNAs typically functioning to repress repetitive regions of the genome via RNA-directed DNA methylation, as well as secondary phased siRNAs and trans-acting siRNAs generated via miRNA-directed cleavage of a polymerase II-derived RNA precursor. Our analyses described thousands of sRNA loci, including poorly understood clusters of 22-nt siRNAs that accumulate during viral infection. The birth, death, expansion, and contraction of these sRNA loci are dynamic evolutionary processes that characterize the Solanaceae family. These analyses indicate that individuals within the same genus share similar sRNA landscapes, whereas comparisons between distinct genera within the Solanaceae reveal relatively few commonalities.

The Multiverse of Plant Small RNAs: How Can We Explore It?

Plant small RNAs (sRNAs) are a heterogeneous group of noncoding RNAs with a length of 20–24 nucleotides that are widely studied due to their importance as major regulators in various biological processes. sRNAs are divided into two main classes—microRNAs (miRNAs) and small interfering RNAs (siRNAs)—which differ in their biogenesis and functional pathways. Their identification and enrichment with new structural variants would not be possible without the use of various high-throughput sequencing (NGS) techniques, allowing for the detection of the total population of sRNAs in plants. Classifying sRNAs and predicting their functional role based on such high-performance datasets is a nontrivial bioinformatics task, as plants can generate millions of sRNAs from a variety of biosynthetic pathways. Over the years, many computing tools have been developed to meet this challenge. Here, we review more than 35 tools developed specifically for plant sRNAs over the past few years and explore some of their basic algorithms for performing tasks related to predicting, identifying, categorizing, and quantifying individual sRNAs in plant samples, as well as visualizing the results of these analyzes. We believe that this review will be practical for biologists who want to analyze their plant sRNA datasets but are overwhelmed by the number of tools available, thus answering the basic question of how to choose the right one for a particular study.