Document ...

Table of Contents

1 Data Collection & Processing Top

1.1 Gene Information Top

All the gene annotation information for the 70 plant species can be obtained from the URLs provided at the Data Sources tab of this page.

1.2 GO Annotaion Top

GO annotation information was download from the Gene Ontology database (; Release 2010-08-01) [24].

1.3 Small RNA Data Sets Top

♦ Small RNA(sRNA) high-throughput sequencing data sets of each species were obtained from the Gene Expression Omnibus (GEO) database ( [27]. All the sRNA data sets retrieved for this study were summarized in the Statistics page → Small RNA Datasets tab.

♦ SRNA sequences containing incomplete information (such as containing "N") and with length less than 18 or more than 28 were removed for further analysis. For each data set, the filtered sRNA sequences were mapped to all the gene models of the related plant species. All mapping steps were performed using the Bowtie algorithm [33] allowing no mismatches. Besides, for comparison, the normalized abundance of sRNAs from each data set was calculated as RPMs (reads per million), which divided the read number of each sRNA by the total reads from this data set, and multiplied by 106.

1.4 Other Information Top

The transcription factor (TF) information for each species (if available) was retrieved from two TF databases: PlantTFDB (Plant Transcription Factor Database; and PlnTFDB (The Plant Transcription Factor Database;

2 Browser Top

Browser is a quick approach to access your interested information. You can browse your interested species by either "Browse by Species" or "Browse by Classification".

2.1 Browse by Species Top

2.2 Browse by Classification Top

3 Searcher Top

Search can be performed by "Quick Searcher", "Simple Searcher", "Batched Searcher", "Advanced Searcher" or "BLAST Searcher".

3.1 Quick Searcher Top

3.2 Simple Searcher Top

3.4 Batched Searcher Top

3.4 Advanced Searcher Top

3.5 BLAST Searcher Top

4 Viewer Top

4.1 Gene Viewer Top

4.2 NAT Viewer Top

The NAT page largely comprises four main parts, i.e., "NAT Summarization", "Gene Information", "GO Annotation" and "Small RNA Expression".

4.3 Network Viewer Top

Network Viewer supports

5 Association Functions Top

5.1 My Network Top

In "My Network", genes or NAT pairs of interest may be stored temporarily on the server side during the session period and retrieved later. This feature will greatly facilitate users' digging of specific biological network formed by related NAT pairs involved in regulation of the same process. In many pages of the website, there is a button to add selected genes or NAT pairs to "My Network".

5.2 Gene Set Analysis Top

6 Appendix Top

6.1 Useful Hits Top

It's recommended that you use Chrome, Firefox, Safari or Opera to access PlantNATsDB, although IE (Internet Explorer) or Netscape still work well.

6.2 Useful Links Top

See the Useful Links tab of this page.

6.3 Methods Top

See the Methods tab of this page.

6.4 References Top

See the References tab of this page.


Table of Contents

1. Prediction of NAT Pairs Top

Prediction of NAT pairs was performed as previously described [17-18,22]. Specifically, the following criteria were used to identify cis-NATs and trans-NATs, respectively.
  For cis-NATs, they can be grouped into five categories, namely, (i) Divergent (head to head or 5' to 5' overlap); (ii) Convergent (tail to tail or 3' to 3' overlap); (iii) Containing (full overlap); (iv) Nearby head-to-head (5' close to 5') and (v) Nearby tail-to-tail (3' close to 3') according to their relative orientation and degree of overlap (Figure 1A) [28]. If a pair of transcripts was located on opposite strands at adjacent genomic loci, and had at least a 1 nucleotide (nt) overlapping region or their distance on the chromosome was on longer than 100 nts, then they were considered as a cis-NAT pair. In total, 26 plant species were subjected to cis-NAT prediction.
  For trans-NATs, BLASTN (, Release 2.2.20) [29] was used to search for transcript pairs with high sequence complementarity to each other and the following criteria should be satisfied for each transcript pair: (i) If the complementary region identified by BLAST covered more than half the length of either transcript, this transcript pair was designated to be a “high-coverage” (HC) trans-NAT pair; (ii) If the two transcripts had a continuous complementary region longer than 100 nts, they were classified as a “100 nt” pair. Functional trans-NATs should form RNA-RNA duplexes in vivo. We therefore used DINAMelt [30] to verify whether the transcript pairs could melt into RNA-RNA duplexes in the complementary regions in silico. All the trans-NAT pairs based on BLAST search were further used to DINAMelt hybridization validation. The trans-NAT pair was retained if it satisfied: (i) the paired region indentified by DINAMelt should be coincident with the BLAST-based search and (ii) any bubble in the paired region predicted by DINAMelt should be no longer than 10% of the region. For the BLAST-based trans-NAT pairs that contain transcripts longer than 10 Kb, they were not applied to DINAMelt validation due to the heavy computational work. Instead, it was considered as verified trans-NAT, if the paired region identified by BLAST was longer than 10% of its longer transcript.

All the NAT pairs predicted in this study were summarized in the Statistics page → Statistics of NATs tab.

2. Small RNA Analysis Top

Small RNA (sRNA) sequences containing incomplete information (such as containing “N”) and with length less than 18 or more than 28 were removed for further analysis. For each data set, the filtered sRNA sequences were mapped to all the gene models of the related plant species. All mapping steps were performed using the Bowtie algorithm [33] allowing no mismatches. Besides, for comparison, the normalized abundance of sRNAs from each data set was calculated as RPMs (reads per million), which divided the read number of each sRNA by the total reads from this data set, and multiplied by 106.  
  For each NAT, an enrichment score was calculated to evaluate whether sRNAs were enriched in the overlapping region [17-18]. The enrichment score, E, was calculated using the following formula:

in which So = the total normalized abundance of the sRNAs generated from the overlapping region, Lo = the total length of the paired region of the two transcripts of the NATs, Sa = the total normalized abundance of the sRNAs generated from these two transcripts, and La = the total length of the two transcripts. Furthermore, a Pearson's chi-square test (χ2 test) was performed to test whether this enrichment was significant.

3. Gene Set Analysis Top

Statistical tests that have been used for "Gene Set Analysis" to identify enriched GO categories include the Fisher's exact test, the χ2 test, the T test, the binomial test and the hypergeometric test. Here we used the combination of the χ2 test and Fisher's exact test to evaluate the significance of enrichment for GO category.

Input Gene Set Others Total
Interested Term a b a+b
Other Terms c d c+d
Total a+c b+d a+b+c+d

[1]. Fisher's exact test directly calculates the P-value using the following formula:

p = \frac{ \displaystyle{{a+b}\choose{a}} \displaystyle{{c+d}\choose{c}} }{ \displaystyle{{n}\choose{a+c}} } = \frac{(a+b)!(c+d)!(a+c)!(b+d)!}{a!b!c!d!n!}

where  \tbinom nk  is the binomial coefficient and the symbol ! indicates the factorial operator.

[2]. For χ2 test, The value of the test-statistic is

\Chi^2 = \sum_{i=1}^{n} \frac{(O_i - E_i)^2}{E_i} ,


χ2 = Pearson's cumulative test statistic, which asymptotically approaches a χ2 distribution.
Oi = an observed frequency (i.e., a, b, c and d in the above table);
Ei = an expected frequency;
n = the number of cells in the table (i.e., n = 4).

The chi-square statistic can then be used to calculate a P-value by comparing the value of the statistic to a χ2 distribution. The number of degrees of freedom df = 1.

f(x;\,k) = \frac{1}{2^{k/2}\Gamma(k/2)}\,x^{k/2 - 1} e^{-x/2}\, I_{\{x\geq0\}},


k = degrees of freedom df = 1
Γ(k/2) denotes the Gamma function;.

f(x;\,k) = \frac{1}{2^{k/2}\Gamma(k/2)}\,x^{k/2 - 1} e^{-x/2}\, I_{\{x\geq0\}},

For small smaples (i.e., at least one of a, b, c and d is less than 5), PlantNATsDB uses the Fisher's exact test to calculate the P-value to evaluate the significance of enrichment for each category. With large samples, a χ2 test can be used in this situation.


1. Ponting, C.P., Oliver, P.L. and Reik, W. (2009) Evolution and functions of long noncoding RNAs. Cell, 136, 629-641.

2. Brosnan, C.A. and Voinnet, O. (2009) The long and the short of noncoding RNAs. Curr Opin Cell Biol, 21, 416-425.

3. Ghildiyal, M. and Zamore, P.D. (2009) Small silencing RNAs: an expanding universe. Nat Rev Genet, 10, 94-108.

4. Mercer, T.R., Dinger, M.E. and Mattick, J.S. (2009) Long non-coding RNAs: insights into functions. Nat Rev Genet, 10, 155-159.

5. Lapidot, M. and Pilpel, Y. (2006) Genome-wide natural antisense transcription: coupling its regulation to its different regulatory mechanisms. EMBO Rep, 7, 1216-1222.

6. Vanhee-Brossollet, C. and Vaquero, C. (1998) Do natural antisense transcripts make sense in eukaryotes? Gene, 211, 1-9.

7. Lavorgna, G., Dahary, D., Lehner, B., Sorek, R., Sanderson, C.M. and Casari, G. (2004) In search of antisense. Trends Biochem Sci, 29, 88-94.

8. Faghihi, M.A. and Wahlestedt, C. (2009) Regulatory roles of natural antisense transcripts. Nat Rev Mol Cell Biol, 10, 637-643.

9. Borsani, O., Zhu, J., Verslues, P.E., Sunkar, R. and Zhu, J.K. (2005) Endogenous siRNAs derived from a pair of natural cis-antisense transcripts regulate salt tolerance in Arabidopsis. Cell, 123, 1279-1291.

10. Watanabe, T., Totoki, Y., Toyoda, A., Kaneda, M., Kuramochi-Miyagawa, S., Obata, Y., Chiba, H., Kohara, Y., Kono, T., Nakano, T. et al. (2008) Endogenous siRNAs from naturally formed dsRNAs regulate transcripts in mouse oocytes. Nature, 453, 539-543.

11. Tam, O.H., Aravin, A.A., Stein, P., Girard, A., Murchison, E.P., Cheloufi, S., Hodges, E., Anger, M., Sachidanandam, R., Schultz, R.M. et al. (2008) Pseudogene-derived small interfering RNAs regulate gene expression in mouse oocytes. Nature, 453, 534-538.

12. Okamura, K., Balla, S., Martin, R., Liu, N. and Lai, E.C. (2008) Two distinct mechanisms generate endogenous siRNAs from bidirectional transcription in Drosophila melanogaster. Nat Struct Mol Biol, 15, 998.

13. Czech, B., Malone, C.D., Zhou, R., Stark, A., Schlingeheyde, C., Dus, M., Perrimon, N., Kellis, M., Wohlschlegel, J.A., Sachidanandam, R. et al. (2008) An endogenous small interfering RNA pathway in Drosophila. Nature, 453, 798-802.

14. Ghildiyal, M., Seitz, H., Horwich, M.D., Li, C., Du, T., Lee, S., Xu, J., Kittler, E.L., Zapp, M.L., Weng, Z. et al. (2008) Endogenous siRNAs derived from transposons and mRNAs in Drosophila somatic cells. Science, 320, 1077-1081.

15. Ron, M., Alandete Saez, M., Eshed Williams, L., Fletcher, J.C. and McCormick, S. (2010) Proper regulation of a sperm-specific cis-nat-siRNA is essential for double fertilization in Arabidopsis. Genes Dev, 24, 1010-1021.

16. Katiyar-Agarwal, S., Morgan, R., Dahlbeck, D., Borsani, O., Villegas, A., Jr., Zhu, J.K., Staskawicz, B.J. and Jin, H. (2006) A pathogen-inducible endogenous siRNA in plant immunity. Proc Natl Acad Sci U S A, 103, 18002-18007.

17. Zhou, X., Sunkar, R., Jin, H., Zhu, J.K. and Zhang, W. (2009) Genome-wide identification and analysis of small RNAs originated from natural antisense transcripts in Oryza sativa. Genome Res, 19, 70-78.

18. Chen, D., Meng, Y., Ma, X., Mao, C., Bai, Y., Cao, J., Gu, H., Wu, P. and Chen, M. (2010) Small RNAs in angiosperms: sequence characteristics, distribution and generation. Bioinformatics, 26, 1391-1394.

19. Zhang, Y., Li, J., Kong, L., Gao, G., Liu, Q.R. and Wei, L. (2007) NATsDB: Natural Antisense Transcripts DataBase. Nucleic Acids Res, 35, D156-161.

20. Osato, N., Yamada, H., Satoh, K., Ooka, H., Yamamoto, M., Suzuki, K., Kawai, J., Carninci, P., Ohtomo, Y., Murakami, K. et al. (2003) Antisense transcripts with rice full-length cDNAs. Genome Biol, 5, R5.

21. Wang, X.J., Gaasterland, T. and Chua, N.H. (2005) Genome-wide prediction and identification of cis-natural antisense transcripts in Arabidopsis thaliana. Genome Biol, 6, R30.

22. Wang, H., Chua, N.H. and Wang, X.J. (2006) Prediction of trans-antisense transcripts in Arabidopsis thaliana. Genome Biol, 7, R92.

23. Jin, H., Vacic, V., Girke, T., Lonardi, S. and Zhu, J.K. (2008) Small RNAs and the regulation of cis-natural antisense transcripts in Arabidopsis. BMC Mol Biol, 9, 6.

24. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T. et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 25, 25-29.

25. Lee, Y., Tsai, J., Sunkara, S., Karamycheva, S., Pertea, G., Sultana, R., Antonescu, V., Chan, A., Cheung, F. and Quackenbush, J. (2005) The TIGR Gene Indices: clustering and assembling EST and known genes and integration with eukaryotic genomes. Nucleic Acids Res, 33, D71-74.

26. Griffiths-Jones, S., Saini, H.K., van Dongen, S. and Enright, A.J. (2008) miRBase: tools for microRNA genomics. Nucleic Acids Res, 36, D154-158.

27. Edgar, R., Domrachev, M. and Lash, A.E. (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res, 30, 207-210.

28. Osato, N., Suzuki, Y., Ikeo, K. and Gojobori, T. (2007) Transcriptional interferences in cis natural antisense transcripts of humans and mice. Genetics, 176, 1299-1306.

29. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. and Lipman, D.J. (1990) Basic local alignment search tool. J Mol Biol, 215, 403-410.

30. Markham, N.R. and Zuker, M. (2005) DINAMelt web server for nucleic acid melting prediction. Nucleic Acids Res, 33, W577-581.

31. Allen, E., Xie, Z., Gustafson, A.M. and Carrington, J.C. (2005) microRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell, 121, 207-221.

32. Pearson, W.R. and Lipman, D.J. (1988) Improved tools for biological sequence comparison. Proc Natl Acad Sci U S A, 85, 2444-2448.

33. Langmead, B., Trapnell, C., Pop, M. and Salzberg, S.L. (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol, 10, R25.

34. Lopes, C.T., Franz, M., Kazi, F., Donaldson, S.L., Morris, Q. and Bader, G.D. (2010) Cytoscape Web: an interactive web-based network browser. Bioinformatics, 26, 2347-2348.

35. German, M.A., Pillay, M., Jeong, D.H., Hetawal, A., Luo, S., Janardhanan, P., Kannan, V., Rymarquis, L.A., Nobuta, K., German, R. et al. (2008) Global identification of microRNA-target RNA pairs by parallel analysis of RNA ends. Nat Biotechnol, 26, 941-946.

36. Addo-Quaye, C., Eshoo, T.W., Bartel, D.P. and Axtell, M.J. (2008) Endogenous siRNA and miRNA targets identified by sequencing of the Arabidopsis degradome. Curr Biol, 18, 758-762.


If you have any question/suggestion about PlantNATsDB, please feel free to contact us:

Data Sources:
ID Scientific name Common Name Type a Release Version Release Date Project Home Download
aly Arabidopsis lyrata Lyrate rockcress Chromosome JGI Araly1 Jul. 22, 2008 Link Link
ath Arabidopsis thaliana Arabidopsis Chromosome TAIR9 Jun. 19, 2009 Link Link
bdi Brachypodium distachyon Purple false brome Chromosome JGI v1.0 8x May 01 2009 Link Link
cpa Carica papaya Papaya Scaffold ASGPB v0.4 Dec 2 Nov. 19, 2008 Link Link
cre Chlamydomonas reinhardtii - Scaffold JGI Chlre4 Jan. 08, 2010 Link Link
csa Cucumis sativus Cucumber Scaffold JGI Cucsa_v1 Jan. 08, 2010 Link Link
fve Fragaria vesca Strawberry Scaffold Version 2 November 16, 2009 Link Link
gma Glycine max Soybean Chromosome JGI Glyma1 Feb. 24, 2010 Link Link
lja Lotus japonicus Lotus Chromosome Lj 1.0 May 18, 2009 Link Link
mac Musa acuminata dwarf banana Chromosome Version 1 Aug. 9,2012 Link Link
mes Manihot esculenta Cassava Scaffold  JGI Cassava1 Nov. 09, 2009 Link Link
mgu Mimulus guttatus Spotted monkey flower Scaffold  JGI Release v1.0 Jan. 20, 2010 Link Link
mpu Micromonas pusilla CCMP1545 - Scaffold JGI Release v2.0 Apr. 3, 2009 Link Link
msp Micromonas sp. RCC299 - Scaffold JGI Release v3.0 Apr. 4, 2009 Link Link
mtr Medicago truncatula Medicago Chromosome Mt 3.0 Oct. 12, 2009 Link Link
olu Ostreococcus lucimarinus CCE9901 - Chromosome JGI Release v2.0 Oct. 27, 2007 Link Link
osi Oryza sativa subsp. indica Rice (indica) Chromosome BGI Release Oct. 28, 2008 Link Link
osj Oryza sativa subsp. japonica Rice (japonica) Chromosome TIGR Rice Release 6.1 Jun. 3, 2009 Link Link
ota Ostreococcus tauri - Chromosome JGI Release v2.0 Apr. 11, 2008 Link Link
ppa Physcomitrella patens Moss Scaffold JGI Phypa1.1 Mar. 22, 2007 Link Link
ppe Prunus persica Peach Scaffold JGI v1.0 May 26, 2009 Link Link
ptr Populus trichocarpa Poplar Chromosome JGI Ptr v2.0 Mar. 16, 2010 Link Link
rco Ricinus communis Castor bean Scaffold TIGR/JCVI Release v0.1 May 22, 2008 Link Link
sbi Sorghum bicolor Sorghum Chromosome JGI Sbi1 Mar. 25, 2008 Link Link
smo Selaginella moellendorffii Spikemosses Scaffold JGI Selmo1 Oct. 19, 2007 Link Link
vca Volvox carteri Volvox Scaffold JGI Release v2.0 Sep. 13, 2007 Link Link
vvi Vitis vinifera Grape Chromosome Genoscope12x Mar. 19, 2010 Link Link
zma Zea mays Maize Chromosome Release 4a.53 Mar. 20, 2009 Link Link
ace Allium cepa Onion TC OnGI Release 2.0 Jul. 17, 2008 Link Link
aco Aquilegia coerulea Aquilegia TC AqGI Release 2.1 Jun. 6, 2008 Link Link
bna Brassica napus Rapeseed TC BnGI Release 4.0 Mar. 16, 2010 Link Link
bvu Beta vulgaris Beet TC BvGI Release 3.0 Jun. 16, 2010 Link Link
can Capsicum annuum Pepper TC PepGI Release 4.0 May 21, 2009 Link Link
cca Coffea canephora Coffee TC CocaGI Release 2.0 Apr. 14, 2010 Link Link
ccl Citrus clementina Clementine TC CiclGI Release 2.0 May 22, 2009 Link Link
ees Euphorbia esula Leafy spurge TC EuesGI Release 1.0 Jun. 30, 2008 Link Link
esi Ectocarpus siliculosus Brown algae TC BaGI Release 1.0 May 27, 2010 Link Link
far Festuca arundinacea Tall fescue TC FaGI Release 3.0 Apr. 7, 2010 Link Link
fpr Festuca pratensis Meadow ryegrass TC MrGI Release 1.0 May 28, 2010 Link Link
ghi Gossypium hirsutum Upland cotton TC CGI Release 10.1 Mar. 4, 2010 Link Link
gra Gossypium raimondii Cotton TC GoraGI Release 1.0 Jul. 2, 2008 Link Link
han Helianthus annuus Sunflower TC HaGI Release 6.0 May 24, 2009 Link Link
hvu Hordeum vulgare Barley TC HvGI Release 11.0 Apr. 14, 2010 Link Link
ini Ipomoea nil Morning glory TC IpniG Release 1.0 Jun. 30, 2008 Link Link
lsa Lactuca sativa Garden lettuce TC LsGI Release 3.0 Jul. 2, 2008 Link Link
lse Lactuca serriola Prickly lettuce TC LaseGI Release 1.0 Jun. 28, 2008  Link Link
mcr Mesembryanthemum crystallinum Ice plant TC McGI Release 5.0 Jun. 19, 2008 Link Link
mdo Malus x domestica Apple TC MdGI Release 3.0 Apr. 8, 2010 Link Link
nbe Nicotiana benthamiana - TC NbGI Release 4.0 Apr. 9, 2010 Link Link
nta Nicotiana tabacum Tobacco TC NtGI Release 6.0 Apr. 10, 2010 Link Link
pco Phaseolus coccineus Scarlet bean TC PcGI Release 1.0 May 27, 2009 Link Link
phy Petunia hybrida Petunia TC PhGI Release 1.0 Apr. 14, 2010 Link Link
pta Pinus taeda Loblolly pine TC PGI Release 8.0 Apr. 15, 2010 Link Link
pvi Panicum virgatum Switchgrass TC PaviGI Release 1.0 May 28, 2009 Link Link
pvu Phaseolus vulgaris Kidney bean TC PhvGI Release 1.0 Apr. 15, 2010 Link Link
qro Quercus robur Oak TC OGI Release 1.0 Jul. 1, 2010 Link Link
rsa Raphanus sativus Radish TC RsGI Release 1.0 May 27, 2010 Link Link
sce Secale cereale Rye TC RyeGI Release 4.0 Jul. 3, 2008 Link Link
she Striga hermonthica Purple witch weed TC ShGI Release 1.0 May 27, 2010 Link Link
sly Solanum lycopersicum Tomato TC LeGI Release 13.0 Apr. 13, 2010 Link Link
sme Solanum melongena Eggplant TC SomeGI Release 1.0 May 28, 2010 Link Link
sof Saccharum officinarum Sugarcane TC SoGI Release 1.0 Apr. 9, 2010 Link Link
stu Solanum tuberosum Potato TC StGI Release 13.0 Apr. 16, 2010 Link Link
tae Triticum aestivum Wheat TC TaGI Release 12.0 Apr. 18, 2010 Link Link
tca Theobroma cacao Cocoa TC TcaGI Release 3.0 May 21, 2009 Link Link
ter Triphysaria eriantha Triphysaria TC TriphGI Release 1.0 Aug. 15, 2008  Link Link
tve Triphysaria versicolor - TC TverGI Release 2.0 Jun. 28, 2008 Link Link
vun Vigna unguiculata Cowpea TC VuGI Release 1.0 May 27, 2010 Link Link
pab Picea abies Spruce TC Sgi Release 4.0  Mar. 5, 2010 Link Link
csi Citrus sinensis Orange TC CsGI Release 1.0 Jun. 25, 2008 Link Link

aTCs: "Tentative Consensus" sequences, are assemblies of ESTs.

Browsers with 1024 x 768 resolution recommended. JavaScript & Adobe Flash Player are required in order to use full functionality.
Author: Dijun Chen    © 2010-2012 Ming Chen's Lab, Zhejiang University