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. 2022 Nov 9;51(D1):D192–D198. doi: 10.1093/nar/gkac981

lncRNASNP v3: an updated database for functional variants in long non-coding RNAs

Yanbo Yang 1,3, Dongyang Wang 2,3, Ya-Ru Miao 3, Xiaohong Wu 4, Haohui Luo 5, Wen Cao 6, Wenqian Yang 7, Jianye Yang 8, An-Yuan Guo 9,✉, Jing Gong 10,11,✉
PMCID: PMC9825536  PMID: 36350671

Abstract

Long non-coding RNAs (lncRNAs) act as versatile regulators of many biological processes and play vital roles in various diseases. lncRNASNP is dedicated to providing a comprehensive repository of single nucleotide polymorphisms (SNPs) and somatic mutations in lncRNAs and their impacts on lncRNA structure and function. Since the last release in 2018, there has been a huge increase in the number of variants and lncRNAs. Thus, we updated the lncRNASNP to version 3 by expanding the species to eight eukaryotic species (human, chimpanzee, pig, mouse, rat, chicken, zebrafish, and fruitfly), updating the data and adding several new features. SNPs in lncRNASNP have increased from 11 181 387 to 67 513 785. The human mutations have increased from 1 174 768 to 2 387 685, including 1 031 639 TCGA mutations and 1 356 046 CosmicNCVs. Compared with the last release, updated and new features in lncRNASNP v3 include (i) SNPs in lncRNAs and their impacts on lncRNAs for eight species, (ii) SNP effects on miRNA−lncRNA interactions for eight species, (iii) lncRNA expression profiles for six species, (iv) disease & GWAS-associated lncRNAs and variants, (v) experimental & predicted lncRNAs and drug target associations and (vi) SNP effects on lncRNA expression (eQTL) across tumor & normal tissues. The lncRNASNP v3 is freely available at http://gong_lab.hzau.edu.cn/lncRNASNP3/.

INTRODUCTION

Long non-coding RNAs (lncRNAs) are defined as transcripts longer than 200 nucleotides (nt) and lack protein-coding capacity (1). In recent decades, a large number of lncRNAs have been identified in animals and plants (2). Accumulating studies have revealed numerous functional lncRNAs, which exert their functions through multiple approaches, including interacting with DNA, RNA and protein (3), thereby regulating diverse cellular functions, such as RNA processing, mRNA stability, translation, and post-translational modifications (4). In addition, many lncRNAs have been reported to be involved in critical biological processes and diseases. For example, several lncRNAs were reported as suppressive or oncogenic factors in different cancers (5,6).

Single nucleotide polymorphisms (SNPs) and somatic mutations in lncRNAs can alter the lncRNA structure and affect lncRNA function and are thus further involved in various biological processes and human diseases (7–11). For example, rs12982687 could affect the binding capacity of lncRNA UCA1 with miR-873-5p and is involved in smoking-triggered colorectal cancer cell migration and invasion (9). Rs140618127 creates a binding site of miR-539-5p on lncRNA LOC146880, which causes the reduction of phosphorylation of ENO1 and is further linked to non-small cell lung cancer progression (8). However, among millions of SNPs and hundreds of thousands of lncRNAs, the functions of SNPs in lncRNAs remain largely unknown. Thus, we developed lncRNASNP that is dedicated to annotating SNPs in lncRNAs and predicting their effects on lncRNA structures and functions (12,13). Based on the lncRNASNP, several functional SNPs in lncRNAs have been identified and experimentally validated (8,14). However, more challenges than victories still exist for the functional validation of lncRNAs and related variants for several possible reasons. First, prioritizing functional variants in lncRNAs is more difficult than protein-coding genes because variants in lncRNAs do not directly affect the codon sequence. In addition, previous studies have shown that most lncRNAs are less conservation and lower expressed than protein-coding genes (15), and abundant lncRNAs show tissue specificity in expression (16). Therefore, systematic prediction of functional variants in lncRNAs and collection of comprehensive information, such as lncRNA expression in multiple tissues and variant conservation in multiple species, are essential for the prioritization of functional lncRNAs and related variants.

With the wide application of next-generation sequencing in more species and tissues, the numbers of identified lncRNAs and SNPs have increased rapidly in the past few years. Since the last release of lncRNASNP in 2018 (13), the number of SNPs in human has increased seven-fold in the latest dbSNP (build 155) (17), and the lncRNAs provided by NONCODE (2) have also increased to 1.22-fold. In addition, the progress of high-throughput genomic technologies has also greatly benefitted animal researchers over the past decade. A series of animal SNP resources (14) and lncRNA databases (2) have been developed in recent years. Increasing studies have begun to focus on the impact of SNPs on lncRNAs in animals. For example, an analysis of pigs showed that several SNPs in lncRNA MEG3 were associated with meat production (18). Another study in chicken also demonstrated that rs1914215137 in the lncRNA pouBW1 was associated with chicken growth and carcass (19). However, large-scale genome-wide analyses of animal lncRNA-SNPs and their impacts have rarely been reported.

In recent years, some new databases have been developed to display the sequence, expression, and functions of lncRNAs (2,20–30). There are also databases describing SNPs in lncRNAs, e.g. lincSNP (31) provides disease-associated SNPs on lncRNAs, and LncVar (32) describes the SNPs and structural variants on lncRNAs and assesses the function of these variants. However, few databases predict the effects of SNPs on lncRNA−miRNA binding and focus on lncRNA-related variants in animals. Thus, we updated the lncRNASNP with the latest data and added six commonly studied animals as well as several new features. With the abundant data, the latest release of the lncRNASNP database will be a helpful resource for functional studies of SNPs and lncRNAs. The lncRNASNP v3 is freely available at http://gong_lab.hzau.edu.cn/lncRNASNP3/.

DATA SOURCE AND SUMMARY

In addition to human and mouse, six other species (chimpanzee, pig, mouse, rat, chicken, zebrafish and fruitfly) were included in lncRNASNP v3, bringing the total number of species to eight. The current release of lncRNASNP contains 438 104 lncRNA transcripts of 265 602 lncRNA genes across eight species obtained from NONCODE v6 (2) (Table 1). SNP data for human were obtained from dbSNP (build 155) (17), and SNP data for other species were obtained from the European Variation Archive (EVA) database (33) (Table 1). After intersecting the genomic positions of SNPs and lncRNA transcripts, we identified 67 513 785 SNPs in all lncRNAs (Table 1), hereafter termed lncRNA-SNPs. For human, we also identified 1 356 046 COSMIC mutations (34) and 1 031 639 TCGA cancer mutations (23) in lncRNAs. In addition, we systematically analyzed the impacts of all variants (SNPs and mutations) on lncRNA secondary structure and miRNA−lncRNA interactions. Furthermore, additional resources were integrated, including lncRNA expression profiles for six species (except chimpanzee and pig)(35), experimentally supported disease-related lncRNAs for three species (human, mouse, and rat), ClinVar variants (36) on human lncRNAs, associations between lncRNA expression and drug targets, and lncRNA-eQTLs from ncRNA-eQTL (37) and GTEx (38). Compared with the previous release, lncRNASNP v3 provides more information on SNPs and lncRNAs in more species, and adds several new features (Table 1).

Table 1.

Data summary in lncRNASNP v3

Data content Version 1.0 Version 2.0 Version 3.0
lncRNA genes/transcripts 42 948/68 579 170 002/258 758 265 602/438 104
All SNPs 1 272 824 11 181 387 67 513 785
lncRNASNP in GWASa 142/197 827 602/2 859 147 14 222/42 830 177
SNP affected MLPb 628 885/637 258 7 169 172/5 872 466 19 692 736/18 088 802
All Predicted MLPb 13 861 473 16 942 990 45 774 338
TCGA cancer mutations NA 315 234 1 031 639
TCGA mutations affected MLPb NA 83 633/80 114 340 422/283 635
CosmicNCVs NA 859 534 1 356 046
CosmicNCVs affected MLPb NA 362 940/350 827 453 202/354 231
lncRNA-associated diseasesc NA 697 129 513
ClinVar SNPs NA NA 135 937
lncRNA-associated drug & compoundsd NA NA 10 849/4688
lncRNA-associated eQTLse NA NA 28 019/615 376
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alncRNASNPs are GWAS TagSNPs/lncRNA SNPs in GWAS LD regions.

bMLP represents the miRNA−lncRNA target pair, and variants (SNPs, TCGA mutations, CosmicNCVs) in lncRNAs induce potential MLP loss/gain.

cThe number of experimentally supported lncRNA-associated disease pairs.

dThe number of lncRNA transcripts associated with drug & compounds (predicted)/the number of experimentally supported lncRNA-associated drug & compound pairs.

eThe numbers of eQTLs across normal/tumor tissues.

IMPROVED CONTENT AND NEW FEATURES

Effects of variants on lncRNA secondary structures

Following the strategy of the last release, we used RNAsnp v1.2 (39) to assess variant effects on lncRNA secondary structure for human, mouse, and other species. We chose mode 1 of RNAsnp for lncRNAs <1000 nt and mode 2 for lncRNAs ≥1000 nt, as the software recommended. With an empirical P-value <0.2 (40), we obtained 9 782 203 SNPs with effects on lncRNA structure across species. Compared with lncRNASNP2, this number for human was updated from 1 425 449 to 8 959 447, and that of the mouse was updated from 395 443 to 677 302. The number of SNPs affecting lncRNA structure for other animals is 145 454 (Table 2).

Table 2.

Details of SNPs and lncRNAs for multiple species in lncRNASNP v3

Species lncRNA-SNP SNP affected lncRNA structure SNP affected MLPa lncRNA expression lncRNA diseases
Homo sapiens 62 374 572 8 959 447 18 571 275/17 053 141 102 970 127 528
Pan troglodytes 5579 927 649/630 NA NA
Mus musculus 4 353 914 677 302 1 069 549/988 382 130 051 1874
Rattus norvegicus 29 624 5 253 4 320/4 101 24 855 111
Sus scrofa 52 898 10 722 5 220/4 556 NA NA
Gallus gallus 439 68 86/88 11 942 NA
Danio rerio 26 655 4 382 835/753 4 827 NA
Drosophila melanogaster 670 104 124 102 40 802/37 151 42 537 NA
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aMLP represents the miRNA−lncRNA target pair, and variants (SNPs, TCGA mutations, CosmicNCVs) in lncRNAs induce potential MLP loss/gain.

Impacts of variants on miRNA–lncRNA interactions

Studies have proven that lncRNAs can interact with miRNAs, and variants in lncRNAs may affect the miRNA−lncRNA interactions (8). Hence, we systematically predicted the potential binding sites of miRNAs on lncRNAs and the impact of SNPs and mutations on miRNA–lncRNA interactions. We first predicted wild-type miRNA binding sites on lncRNAs using the mature miRNA sequences obtained from miRBase (release 22.1) (41). For better reliability, we intersected the prediction results of two popular software, miRmap (42) and TargetScan (43). Only the binding sites identified by both software were included as final miRNA binding sites. In addition, we provided the conservation information of miRNA binding sites. The UCSC LiftOver tool (44) was used to obtain the conservation information with the parameter of ‘minimum ratio of bases that must remap’ as 0.5. The miRNA binding sites in the conserved exons of at least two species were classified as conserved. Finally, we identified 45 774 338 lncRNA−miRNA pairs in eight species.

To assess the impact of SNPs and mutations on miRNA–lncRNA interactions, the sequences around each variant (±25 bp) were first extracted. Then, for the sequence of each variant, the wild-type allele was replaced with the alternative allele, and miRmap (42) and TargetScan (43) were used to predict the miRNA binding sites on them. Similar to the former criteria used in lncRNA−miRNA interaction identification, we only kept the miRNA–lncRNA pairs identified by both software. miRNA–lncRNA pairs existing in wild-type transcripts but not in variant alternative transcripts were defined as interaction losses, and on the contrary, they were defined as gains of miRNA target sites. Finally, we found 27 157 121 SNPs and 1 032 392 mutations that potentially caused the gain/loss of original miRNA target sites (Table 1).

lncRNA expression profiles for multiple species

lncRNASNP2 included lncRNA expression profiles obtained from TCGA (45). As TCGA v32.0 updated expression data based on a newer gene annotation file (GENCODE v36) (20), we updated TCGA lncRNA expression profiles from 11 857 to 14 996 human lncRNA genes across 33 human cancer types. In addition to the lncRNA expression profiles from TCGA, we also integrated lncRNA expression profiles from the LncExpDB database (21), which added the number of expressed human lncRNA transcripts to 102 970 (Table 2). In addition, we collected lncRNA expression profiles for pig, mouse, rat, chicken, zebrafish, and fruitfly from LncRBase v2 (35). The number of lncRNAs ranged from 4827 in zebrafish to 130 051 in mouse (Table 2). Detailed information on lncRNA expression can be queried by searching for specific lncRNAs in lncRNASNP v3.

Mutations in lncRNAs

Mutations within lncRNAs have also been proven to play important roles in cancer (46). Using the latest somatic mutation data from TCGA v32.0 and COSMIC v95, we obtained 1 031 639 TCGA mutations and 1 356 046 CosmicNCVs on human lncRNA transcripts, which increased by 3.3-fold and 1.6-fold compared with the lncRNASNP2. We used RNAsnp v1.2 (39) to estimate the effects of TCGA and COSMIC mutations on lncRNA secondary structure. With the threshold of Empirical P value <0.2, we obtained 199 450 TCGA lncRNA-mutations and 250 733 COSMIC lncRNA-mutations that potentially affected the lncRNA secondary structure. We next utilized FATHMM (47) to assess whether TCGA mutations in lncRNAs are deleterious. With the threshold of score >0.7, we identified 419 523 (42.11%) pathogenic variants on lncRNA transcripts.

In addition, for each lncRNA gene, we compared the expression of TCGA samples with and without mutations using the Wilcoxon signed-rank test. Under the threshold of nominal P value <0.05, expressions of 895 lncRNA genes across 28 cancer types were identified as significantly affected by TCGA mutations.

Disease & GWAS-associated lncRNAs and variants

In recent years, massive research has focused on the roles of lncRNAs in diseases (3,48). Due to the growing need for disease-related lncRNAs, we collected the latest disease-associated lncRNA information from continuously updated databases (Lnc2Cancer 3.0 (49), LncRNADisease 2.0 (50), LncRNAWiki 2.0 (51) and MNDR v3.1 (52)). After data integration and deduplication, we obtained a total of 127 528 disease-lncRNA pairs in human. Since MNDR v3.1 (52) is a comprehensive database providing lncRNA information on multiple species, we also collected 1874 disease-lncRNA pairs in mouse and 111 disease-lncRNA pairs in rat. In addition to lncRNA transcripts, we also matched 135 937 disease-associated variants obtained from ClinVar v4.1 (36) on lncRNAs. Furthermore, to identify the lncRNA-SNPs related to human diseases or complex traits, we first collected 182 272 GWAS tagSNPs (14 222 tagSNPs were located in lncRNA regions) from the NHGRI GWAS Catalog (53) and obtained the LD regions of each GWAS SNP for different populations using plink v1.90 with the ‘–block’ parameter. The phased human SNV files (1000 Genomes 30x) and population information were downloaded from IGSR (54). Finally, 19 populations with more than 100 individuals were included in the above analysis. Our results show that 42 830 177 lncRNA-SNPs are in the GWAS LD regions of all populations (Table 1).

Experimental & predicted lncRNA and drug target associations

Increasing evidence indicates that lncRNAs could be potential therapeutic targets for cancer and disease, and linked to drug resistance (55). The NoncoRNA database (56) is a comprehensive database providing experimentally supported ncRNAs and drug target associations. We therefore integrated NoncoRNA datasets with lncRNAs in lncRNASNP v3 and obtained 4688 drug-associated lncRNA transcripts (Table 1). As associations between lncRNAs and drugs remain largely unknown, we further calculated correlations between lncRNA expression profiles and drug sensitivity data. To do so, we first downloaded the NCI-60 dataset containing half-cell growth inhibition concentrations (GI50) of 24 360 drugs/compounds from the CellMiner Cross Database (57) and then collected the corresponding lncRNA expression profiles of NCI-60 from GSE80332 (58). The correlations were calculated using the Spearman correlation, and the P value of the correlation coefficient was corrected by FDR. We finally kept 10 849 lncRNA-drug pairs with FDR < 0.05 and |r| > 0.5 (Table 1).

SNP effects on lncRNA expression (eQTL) across tumor and normal tissues

Expression quantitative trait locus (eQTL) analysis, which links variants in gene expression to genotypes, has been widely used in genetic studies to decipher target genes of functional SNPs (59). Recent studies have shown that SNPs could also exert their roles by regulating the expression of lncRNAs, thereby increasing the risk of cancer (60). In previous years, we have systematically identified eQTLs on ncRNAs across tumor samples and developed the ncRNA-eQTL database (37). To maximize the use of this resource, we matched lncRNA genes in lncRNASNP v3 with the eQTL genes in ncRNA-eQTL (lncRNA genes with the same position were considered to be the same lncRNAs) and extracted all the eQTL SNPs regulating these lncRNAs. We linked 564 157 cis-eQTLs, 51 219 trans-eQTLs, 7009 GWAS-eQTLs and 2831 survival-eQTLs into lncRNASNP v3 (Table 1). In addition, the GTEx project has also systematically analyzed the associations between SNPs and gene expressions for ‘normal’ and ‘non-disease’ tissues (38). Hence, we downloaded GTEx-eQTLs across 49 human tissues and extracted eQTLs with q-values ≤0.05. After matching lncRNA genes by position, we obtained 28,019 cis-eQTLs regulating lncRNA genes across normal tissues (Table 1).

DATABASE ORGANIZATION AND WEB INTERFACE

The lncRNASNP v3 database was built with the Flask framework (http://flask.pocoo.org/) as the backend server, and all data mentioned above were organized into MongoDB. The database is freely available at http://gong_lab.hzau.edu.cn/lncRNASNP3. lncRNASNP v3 comprises eight sections: lncRNA, SNP, Mutation, miRNA, eQTL, Disease, Drug and Tool (Figure 1A). On the homepage, users can browse the resources by species or modules (Figure 1B). In lncRNASNP v3, most pages developed in the last release were redesigned for the convenience of searching and browsing information for multiple species (Figure 1C). Users can obtain more information on SNP, miRNA, and lncRNA pages by clicking the ‘Detail’ button at each retrieved record (Figure 1D). On the ‘eQTL’ and ‘Drug’ pages, we displayed results according to different types or different sources. Users can browse distinct information by switching the button above the module (Figure 1E). On the ‘Help’ page, we provided more detailed information about the data sources, analysis methods, and usage instructions.

Figure 1.

Figure 1.

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The interface of lncRNASNP v3. (A) Navigation in lncRNASNP v3. (B) Browse by species or by modules on the homepage. (C) The search box on the ‘miRNA’ page. (D) The details of the miRNA:lncRNA interaction after clicking the ‘Detail’ button on the ‘miRNA’ page. (E) The module for lncRNA expression-drugs correlation results (NCI-60). Users can browse the experimental lncRNAs and drug target associations by clicking the ‘NoncoRNA’ button.

SUMMARY AND FUTURE PERSPECTIVES

Since the last release of lncRNASNP in 2018, the numbers of the lncRNAs and SNPs/mutations, especially the number of lncRNAs and SNPs in animals, have increased significantly, attracting increasing attention from animal researchers. Therefore, we updated the lncRNASNP using the latest data, expanded the species to eight commonly studied animals and added several new features. To meet the demand for more comprehensive data, in the current release of lncRNASNP, we expanded the lncRNA expression and disease information for more species. We also developed new features, such as disease-associated lncRNAs and variants, experimental & predicted lncRNA-drug target associations, and TCGA & GTEx eQTLs on lncRNAs, to provide comprehensive insights for SNP and lncRNA-related research. In addition, we redesigned the web interface to make it more convenient for users to obtain the information. In the future, with the cost of sequencing technologies continually decreasing, lncRNAs and SNPs in more species are expected to be identified. We will update the lncRNASNP database regularly and maintain lncRNASNP as a useful repository for the functional study of lncRNAs and lncRNAs-variants.

DATA AVAILABILITY

lncRNASNP is freely available to the public without registration or login requirements (http://gong_lab.hzau.edu.cn/lncRNASNP3).

Contributor Information

Yanbo Yang, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.

Dongyang Wang, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.

Ya-Ru Miao, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.

Xiaohong Wu, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.

Haohui Luo, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.

Wen Cao, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.

Wenqian Yang, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.

Jianye Yang, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.

An-Yuan Guo, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.

Jing Gong, Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China.

FUNDING

National Key R&D Program of China [2021YFF0703700 to J.G. and A.Y.G.]; National Natural Science Foundation of China [31970644 to J.G.]; Huazhong Agricultural University Scientific & Technological Self-innovation Foundation [11041810351 to J.G.]. Funding for open access charge: National Key R&D Program of China [2021YFF0703700].

Conflict of interest statement. None declared.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

lncRNASNP is freely available to the public without registration or login requirements (http://gong_lab.hzau.edu.cn/lncRNASNP3).

Articles from Nucleic Acids Research are provided here courtesy of Oxford University Press

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