Asymmetric purine-pyrimidine distribution in cellular small RNA population of papaya

BACKGROUND: The small RNAs (sRNA) are a regulatory class of RNA mainly represented by the 21 and 24-nucleotide size classes. The cellular sRNAs are processed by RNase III family enzyme dicer (Dicer like in plant) from a self-complementary hairpin loop or other type of RNA duplexes. The papaya genome has been sequenced, but its microRNAs and other regulatory RNAs are yet to be analyzed. RESULTS: We analyzed the genomic features of the papaya sRNA population from three sRNA deep sequencing libraries made from leaves, flowers, and leaves infected with Papaya Ringspot Virus (PRSV). We also used the deep sequencing data to annotate the micro RNA (miRNA) in papaya. We identified 60 miRNAs, 24 of which were conserved in other species, and 36 of which were novel miRNAs specific to papaya. In contrast to the Chargaff’s purine-pyrimidine equilibrium, cellular sRNA was significantly biased towards a purine rich population. Of the two purine bases, higher frequency of adenine was present in 23nt or longer sRNAs, while 22nt or shorter sRNAs were over represented by guanine bases. However, this bias was not observed in the annotated miRNAs in plants. The 21nt species were expressed from fewer loci but expressed at higher levels relative to the 24nt species. The highly expressed 21nt species were clustered in a few isolated locations of the genome. The PRSV infected leaves showed higher accumulation of 21 and 22nt sRNA compared to uninfected leaves. We observed higher accumulation of miRNA* of seven annotated miRNAs in virus-infected tissue, indicating the potential function of miRNA* under stressed conditions. CONCLUSIONS: We have identified 60 miRNAs in papaya. Our study revealed the asymmetric purine-pyrimidine distribution in cellular sRNA population. The 21nt species of sRNAs have higher expression levels than 24nt sRNA. The miRNA* of some miRNAs shows higher accumulation in PRSV infected tissues, suggesting that these strands are not totally functionally redundant. The findings open a new avenue for further investigation of the sRNA silencing pathway in plants

Elucidation of the MicroRNA Transcriptome in Western Corn Rootworm Reveals Its Dynamic and Evolutionary Complexity

Diabrotica virgifera virgifera (western corn rootworm, WCR) is one of the most destructive agricultural insect pests in North America. It is highly adaptive to environmental stimuli and crop protection technologies. However, little is known about the underlying genetic basis of WCR behavior and adaptation. More specifically, the involvement of small RNAs (sRNAs), especially microRNAs (miRNAs), a class of endogenous small non-coding RNAs that regulate various biological processes, has not been examined, and the datasets of putative sRNA sequences have not previously been generated for WCR. To achieve a comprehensive collection of sRNA transcriptomes in WCR, we constructed, sequenced, and analyzed sRNA libraries from different life stages of WCR and northern corn rootworm (NCR), and identified 101 conserved precursor miRNAs (pre-miRNAs) in WCR and other Arthropoda. We also identified 277 corn rootworm specific pre-miRNAs. Systematic analyses of sRNA populations in WCR revealed that its sRNA transcriptome, which includes PIWI-interacting RNAs (piRNAs) and miRNAs, undergoes a dynamic change throughout insect development. Phylogenetic analysis of miRNA datasets from model species reveals that a large pool of species-specific miRNAs exists in corn rootworm; these are potentially evolutionarily transient. Comparisons of WCR miRNA clusters to other insect species highlight conserved miRNA-regulated processes that are common to insects. Parallel Analysis of RNA Ends (PARE) also uncovered potential miRNA-guided cleavage sites in WCR. Overall, this study provides a new resource for studying the sRNA transcriptome and miRNA-mediated gene regulation in WCR and other Coleopteran insects

Advances in alternative splicing identification: deep learning and pantranscriptome

In plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate identification of splicing events is a vital step in studying alternative splicing. This article presents the application of alternative splicing algorithms with or without reference genomes in plants, as well as the integration of advanced deep learning techniques for improved detection accuracy. In addition, we also discuss alternative splicing studies in the pan-genomic background and the usefulness of integrated strategies for fully profiling alternative splicing

Two ultraviolet radiation datasets that cover China

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes

Analyzing the microRNA Transcriptome in Plants Using Deep Sequencing Data

MicroRNAs (miRNAs) are 20- to 24-nucleotide endogenous small RNA molecules emerging as an important class of sequence-specific, trans-acting regulators for modulating gene expression at the post-transcription level. There has been a surge of interest in the past decade in identifying miRNAs and profiling their expression pattern using various experimental approaches. In particular, ultra-deep sampling of specifically prepared low-molecular-weight RNA libraries based on next-generation sequencing technologies has been used successfully in diverse species. The challenge now is to effectively deconvolute the complex sequencing data to provide comprehensive and reliable information on the miRNAs, miRNA precursors, and expression profile of miRNA genes. Here we review the recently developed computational tools and their applications in profiling the miRNA transcriptomes, with an emphasis on the model plant Arabidopsis thaliana. Highlighted is also progress and insight into miRNA biology derived from analyzing available deep sequencing data

Analyzing the microRNA Transcriptome in Plants Using Deep Sequencing Data

biolog

Identification of Species-Specific MicroRNAs Provides Insights into Dynamic Evolution of MicroRNAs in Plants

MicroRNAs (miRNAs) are an important class of regulatory small RNAs that program gene expression, mainly at the post-transcriptional level. Although sporadic examples of species-specific miRNAs (termed SS-miRNAs) have been reported, a genome-scale study across a variety of distant species has not been assessed. Here, by comprehensively analyzing miRNAs in 81 plant species phylogenetically ranging from chlorophytes to angiosperms, we identified 8048 species-specific miRNAs from 5499 families, representing over 61.2% of the miRNA families in the examined species. An analysis of the conservation from different taxonomic levels supported the high turnover rate of SS-miRNAs, even over short evolutionary distances. A comparison of the intrinsic features between SS-miRNAs and NSS-miRNAs (non-species-specific miRNAs) indicated that the AU content of mature miRNAs was the most striking difference. Our data further illustrated a significant bias of the genomic coordinates towards SS-miRNAs lying close to or within genes. By analyzing the 125,267 putative target genes for the 7966 miRNAs, we found the preferentially regulated functions of SS-miRNAs related to diverse metabolic processes. Collectively, these findings underscore the dynamic evolution of miRNAs in the species-specific lineages

Asymmetric purine-pyrimidine distribution in cellular small RNA population of papaya

Abstract Background The small RNAs (sRNA) are a regulatory class of RNA mainly represented by the 21 and 24-nucleotide size classes. The cellular sRNAs are processed by RNase III family enzyme dicer (Dicer like in plant) from a self-complementary hairpin loop or other type of RNA duplexes. The papaya genome has been sequenced, but its microRNAs and other regulatory RNAs are yet to be analyzed. Results We analyzed the genomic features of the papaya sRNA population from three sRNA deep sequencing libraries made from leaves, flowers, and leaves infected with Papaya Ringspot Virus (PRSV). We also used the deep sequencing data to annotate the micro RNA (miRNA) in papaya. We identified 60 miRNAs, 24 of which were conserved in other species, and 36 of which were novel miRNAs specific to papaya. In contrast to the Chargaff’s purine-pyrimidine equilibrium, cellular sRNA was significantly biased towards a purine rich population. Of the two purine bases, higher frequency of adenine was present in 23nt or longer sRNAs, while 22nt or shorter sRNAs were over represented by guanine bases. However, this bias was not observed in the annotated miRNAs in plants. The 21nt species were expressed from fewer loci but expressed at higher levels relative to the 24nt species. The highly expressed 21nt species were clustered in a few isolated locations of the genome. The PRSV infected leaves showed higher accumulation of 21 and 22nt sRNA compared to uninfected leaves. We observed higher accumulation of miRNA* of seven annotated miRNAs in virus-infected tissue, indicating the potential function of miRNA* under stressed conditions. Conclusions We have identified 60 miRNAs in papaya. Our study revealed the asymmetric purine-pyrimidine distribution in cellular sRNA population. The 21nt species of sRNAs have higher expression levels than 24nt sRNA. The miRNA* of some miRNAs shows higher accumulation in PRSV infected tissues, suggesting that these strands are not totally functionally redundant. The findings open a new avenue for further investigation of the sRNA silencing pathway in plants.</p