| Literature DB >> 29657289 |
Garima Bhatia1, Neetu Goyal2, Shailesh Sharma3, Santosh Kumar Upadhyay4, Kashmir Singh5.
Abstract
Small non-coding RNAs have been extensively studied in plants over the last decade. In contrast, genome-wide identification of plant long non-coding RNAs (lncRNAs) has recently gained momentum. LncRNAs are now being recognized as important players in gene regulation, and their potent regulatory roles are being studied comprehensively in eukaryotes. LncRNAs were first reported in humans in 1992. Since then, research in animals, particularly in humans, has rapidly progressed, and a vast amount of data has been generated, collected, and organized using computational approaches. Additionally, numerous studies have been conducted to understand the roles of these long RNA species in several diseases. However, the status of lncRNA investigation in plants lags behind that in animals (especially humans). Efforts are being made in this direction using computational tools and high-throughput sequencing technologies, such as the lncRNA microarray technique, RNA-sequencing (RNA-seq), RNA capture sequencing, (RNA CaptureSeq), etc. Given the current scenario, significant amounts of data have been produced regarding plant lncRNAs, and this amount is likely to increase in the subsequent years. In this review we have documented brief information about lncRNAs and their status of research in plants, along with the plant-specific resources/databases for information retrieval on lncRNAs.Entities:
Keywords: biological roles; genome-wide identification; lncRNA databases; lncRNAs; non-coding RNA
Year: 2017 PMID: 29657289 PMCID: PMC5831932 DOI: 10.3390/ncrna3020016
Source DB: PubMed Journal: Noncoding RNA ISSN: 2311-553X
Studies showing genome-wide identification of long non-coding RNAs (lncRNAs) in plants over the last decade.
| S.No. | Year | Publication Details and Reference No. | Approach of Identification | Plant Species | Biotypes and Number | Tissues/Developmental Stages | Stimuli/Biological Process | ||
|---|---|---|---|---|---|---|---|---|---|
| Abiotic Stress | Biotic Stress | Others | |||||||
| 1. | 2007 | Wen et al. | Expressed and genomic sequence data + Computational Pipeline | mRNA-like non-coding transcripts: 503 | - | ✕ | ✕ | ✕ | |
| 2. | 2009 | Amor et al. | Genome-wide bioinformatic analysis of full-length cDNA databases | Long non-protein coding RNAs: 76 | Inflorescences, stems, and leaves | ✓ | ✕ | ✕ | |
| 3. | 2011 | Xin et al. | Microarray Analysis + SBS Sequencing | Long non-protein coding RNAs: 125 | Leaf samples at 0 and 12 hours post inoculation | ✓ | ✓ | ✕ | |
| 4. | 2012 | Liu et al. | RNA sequencing + computational prediction | lincRNAs: 2708 | Root and leaf samples of 30-day-old plants and two-week-old seedlings | ✓ | ✕ | ✕ | |
| 5. | 2012 | Boerner and McGinnis | Full-length cDNA sequences + computational pipeline | lncRNAs | - | ✕ | ✕ | ✕ | |
| 6. | 2012 | Lu et al. | Strand-specific RNA-seq + computational pipeline | Cis-NATs: 3819 | Seedlings and epidermal cells | ✓ | ✕ | ✕ | |
| 7. | 2013 | Qi et al. | Deep transcriptomic sequencing | lncRNAs: 584 lincRNAs: 494 lncNATs: 90 | Shoots | ✓ | ✕ | ✕ | |
| 8. | 2013 | Wang et al. | Deep RNA-seq | ncRNAs: 1417 | Leaves, flowers, and fruits | ✕ | ✕ | ✕ | |
| 9. | 2013 | Yu et al. | RNA-seq + computational pipeline | Cis-NATs: 1031 | Seedling (three weeks old) and inflorescence apices (two months old) | ✕ | ✕ | ✕ | |
| 10. | 2014 | Wang et al. | Strand-specific RNA-seq + strand-specific tiling arrays | Sense–antisense transcript pairs: 37,238 | Cotyledons, hypocotyls, and roots of seedlings | ✕ | ✕ | ✓ | |
| 11. | 2014 | Zhu et al. | Strand-specific RNA-seq | lncRNAs | Two-week old seedlings | ✕ | ✓ | ✕ | |
| 12. | 2014 | Li et al. | EST databases, maize whole genome sequence annotation and RNA-seq datasets + computational pipeline | lncRNAs: 20,163 | Thirdteen distinct tissues (leaf, immature ear, immature tassel, seed, endosperm, embryo, embryo sac, anther, ovule, pollen, silk, and root and shoot apical meristem) | ✕ | ✕ | ✕ | |
| 13. | 2014 | Shuai et al. | RNA-seq + computational pipeline | lincRNAs: 2542 | Mature leaves | ✓ | ✕ | ✕ | |
| 14. | 2014 | Zhang et al. | Strand-specific RNA-seq + computational pipeline | lncRNAs: 2224 lincRNAs: 1624 lncNATs: 600 | Anthers, pistils, seeds five days after pollination, and shoots 14 days after germination | ✕ | ✕ | ✓ | |
| 15. | 2015 | Chen et al. | High-throughput RNA-seq + computational pipeline | lncRNAs: 1377 | Tension, opposite, and normal wood xylem from 30-year old trees | ✕ | ✕ | ✕ | |
| 16. | 2015 | Hao et al. | RNA-seq data + computational pipeline | lincRNAs: 3274 | Fruits at five ages, root, stem, leaf, male and female flowers, ovary, expanded fertilized and unfertilized ovary, base of the tendril, and tendril | ✕ | ✕ | ✕ | |
| 17. | 2015 | Zhu et al. | Paired-end strand-specific RNA-seq | lncRNAs: 3679 | Fruits: immature green, mature green, breaker, pink, and red-ripe stages | ✕ | ✕ | ✕ | |
| 18. | 2015 | Wang et al. | Strand-specific paired-end RNA-seq + computational pipeline | lncRNAs: 1565 | Leaves | ✕ | ✓ | ✕ | |
| 19. | 2015 | He et al. | RNA-seq + computational pipeline | lncRNAs | Roots | ✓ | ✕ | ✕ | |
| 20. | 2015 | Wang et al. | High-throughput sequencing + bioinformatic analysis | lncRNAs: 23,324 | Leaves and roots | ✓ | ✕ | ✕ | |
| 21. | 2015 | Kang and Liu | RNA-seq data + computational pipeline | lncRNAs: 5884 | Thirty-five distinct floral and fruit tissues and two vegetative tissues: seedlings and young leaves | ✕ | ✕ | ✕ | |
| 22. | 2016 | Zou et al., | Strand-specific RNA-seq + computational pipeline | lncRNAs: 5996 lincRNAs: 3510 lncNATs: 2486 | Ovules and fibers on 1, 10, and 15 days post anthesis; leaves from 2-week-old seedlings | ✕ | ✕ | ✕ | |
| 23. | 2016 | Tian et al., | RNA-seq + computational pipeline | lncRNAs: 7655 | Leaves | ✕ | ✕ | ✓ | |
| 24. | 2016 | Song et al. | RNA-seq data + computational pipeline | lncRNAs: 1133 | Winter bud, leaf, flower, root and bark | ✕ | ✕ | ✕ | |
| 25. | 2016 | Zhang et al. | RNA-seq + computational pipeline | lincRNAs: 58,218 | Leaves at 0, 1, 2, and 3 days post inoculation | ✕ | ✓ | ✕ | |
| 26. | 2016 | Khemka et al. | RNA-seq data + computational pipeline | lincRNAs: 2248 | Three vegetative tissues: germinating seedling, young leaves, and shoot apical meristem; and eight successive stages of flower tissues from closed flower bud to drooped flower | ✕ | ✕ | ✕ | |
| 27. | 2016 | Lv et al. BMC Genomics | Ribosomal RNA depletion and ultra-deep total RNA-seq | lncRNAs: 7245 lincRNAs: 6211 long intronic ncRNAs: 1034 | Leaf | ✓ | ✕ | ✕ | |
| 28. | 2016 | Chen et al. | Genome-wide strategy | lncRNAs: 388 | - | ✓ | ✕ | ✕ | |
| 29. | 2016 | Flórez-Zapata et al. | RNA-seq + computational pipeline | lncRNAs: 25,327 | Prophase I meiocytes from disc florets of the floral bud | ✕ | ✕ | ✕ | |
| 30. | 2016 | Joshi et al. | RNA-seq + computational pipeline | lncRNAs: 3181 | Leaves | ✕ | ✓ | ✕ | |
| 31. | 2016 | Yuan et al. BMC Genomics [ | Strand-specific RNA libraries + RNA-seq + computational pipeline | lncRNAs: 1212 | Shoot and root of 10-day-old seedlings | ✓ | ✕ | ✕ | |
| 32. | 2016 | Kwenda et al. | Strand-specific RNA-seq + computational pipeline | lincRNAs: 1113 | Stems | ✕ | ✓ | ✕ | |
Abbreviations used in Table 1: EST, expressed sequence tag; lncRNA, long non-coding RNA; lincRNA, long intergenic non-coding RNA; lncNAT, long non-coding natural antisense transcript; ncRNA, non-coding RNA; RNA-seq, RNA sequencing; SBS, sequencing by synthesis.
An overview of the currently available databases for plant lncRNAs.
| S.No. | Name of the Database | Publication Details and Reference No. | Plant Species | Number of Plant lncRNAs | Description/Main Features | Data Sources | Link/URL |
|---|---|---|---|---|---|---|---|
| 1. | TAIR10 | Lamesch et al., (2012) | Information available about 33,602 genes of | Plant-specific | AFGC cDNA arrays, the literature, and sequencing and function genomics projects | ||
| 2. | PlantNATsDB | Chen et al. | Seventy plant species | NATs (including both protein coding and non-coding transcripts): 2,146,803 | A comprehensive database of NATs Plant-specific | Various data sources such as TAIR9, JGI Glyma1, JGI Cassava 1 | |
| 3. | PLncDB | Jin et al. | >13,000 lncRNAs | A comprehensive genomic database of Plant-specific | Data in the study by Liu et al., 2012 [ | ||
| 4. | NONCODE v4 | Xie et al. | 3853 lncRNA transcripts | An integrated knowledge database with comprehensive collection and annotation of lncRNAs plus other ncRNAs Not plant-specific | The literature, specialized databases, and GenBank | ||
| 5. | PNRD | Yi et al. | Four plant species: | 5573 lncRNAs | A comprehensive integrated web resource for lncRNAs and other ncRNAs Plant-specific | Integration of data from other databases and publications | |
| 6. | lncRNAdb v2.0 | Quek et al. | Seven lncRNA entries for | Reference database for functional lncRNAs, which have been experimentally validated. Not plant-specific | Manually curated from evidence supported by the literature | ||
| 7. | PLNlncRbase | Xuan et al. | Forty-three plant species | 1187 lncRNAs | A resource for experimentally validated lncRNAs Plant-specific | Manually curated from evidence supported by the literature (over 200 studies) | |
| 8. | GreeNC | Gallart et al. | Thirty-seven plant species and 6 algae | >120,000 (high-confidence) lncRNAs | A wiki-based information-rich database of lncRNAs Plant-specific | In silico identification based on data downloaded from Phytozome v10.3 | |
| 9. | CANTATAdb | Szczesśniak et al. | 10 plant species: | 45,117 lncRNAs | A database of lncRNAs with extended annotation like information about lncRNA-miRNA interactions Plant-specific | In silico identification based on publicly available RNA-Seq sample data | |
| 10. | DsTRD | Shao et al. (2016) | 27,687 lncRNAs | A transcriptional resource database specific for the medicinal plant danshen | In silico identification using an in-house Perl script | ||
| 11. | RNACentral | The RNAcentral Consortium. | ≈673 lncRNAs | A gateway for the users to access lncRNAs and other ncRNAs via single entry point Not plant-specific | 40 expert databases | ||
| 12. | PLncRNAdb | Ming Chen’s Lab | Four plant species: | 5000 lncRNAs | A database of lncRNAs with distinct annotation like information lncRNAs and various RBPs Plant-specific | In silico identification and the literature |
Abbreviations used in Table 2: AFGC, Arabidopsis Functional Genomics Consortium; JGI, Joint Genome Institue; lncRNA, long non-coding RNA; NAT, natural antisense transcript; ncRNA, non-coding RNA; RBP, RNA binding protein.