Genetics and Molecular Biology
Sociedade Brasileira de Genética
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Identification of LincRNA from Dermatophagoides farinae (Acari: Pyroglyphidae) for Potential Allergen-Related Targets
Volume: 43 , Issue: 1
Doi: 10.1590/1678-4685-GMB-2019-0243
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Abstract

Long noncoding RNAs (lncRNAs), especially their important subclass of long intergenic noncoding RNAs (lincRNAs), have been identified in some insects. They play important roles in the regulation of biological processes, such as immune response or cell differentiation and as possible evolutionary precursors for protein coding genes. House dust mites (HDMs) are recognized as allergenic mites because allergens are found in their feces and bodies. Dermatophagoides farinae is one of the most important pyroglyphid mites because of its abundance in the household. To determine if lincRNAs can regulate allergen presentation in HDMs, we analyzed RNA-seq data for HDMs. We identified 11 lincRNAs that are related to mRNAs coding for allergens in HDMs. Using qRT-PCR, we amplified 10 lincRNAs and their putative target allergen-encoding mRNAs, confirming expression of these lincRNAs and allergen genes. The results suggest that lincRNAs might be involved in the regulation of allergen production in HDMs and might represent potential acaricidal candidates to inhibit mite allergen production.

Keywords
Zhou, Wu, Zhu, Shao, Liu, and Cui: Identification of LincRNA from Dermatophagoides farinae (Acari: Pyroglyphidae) for Potential Allergen-Related Targets

Introduction

House dust mites (HDMs) are one of the most important worldwide causes of allergic diseases, including allergic asthma, allergic rhinitis, and atopic dermatitis. Common species of HDM, like Dermatophagoides pteronyssinus, Dermatophagoides farinae (D. farinae), and Blomia tropicalis (Calderon et al., 2015), produce allergenic proteins, i.e., that bind IgE from sera of >5% of patients with symptoms of HDM allergies (Caraballo 2017; Thomas, 2018). To date, 39 groups of mite allergens have been reported. The World Health Organization and International Union of Immunological Societies (WHO/IUIS) subcommittee on allergen nomenclature has assigned official names for isolated allergens, which are listed at www.allergen.org. HDM allergens are present in mite bodies, secreta, and excreta, with feces being the major source of allergens.

Production of allergenic proteins is likely regulated by both transcriptional and post-translational processes. One potential source of regulation is long noncoding RNA (lncRNA), a class of abundant noncoding RNA that overlaps traditional coding genes and includes not only antisense, intronic, and intergenic transcripts but also pseudogenes and retrotransposons. lncRNAs are involved in various processes, such as cis and/or trans regulation of transcription, dosage compensation, imprinting, and competition with other endogenous RNAs (Li et al., 2014; Wang et al., 2018).

A limited number of insect genes has been experimentally annotated as lncRNAs. A 2012 study identified long non-coding intergenic RNAs (lincRNAs, a subset of lncRNAs transcribed from intergenic DNA) in insects using RNA-seq data, reporting 1,119 candidate lincRNA loci in the Drosophila melanogaster genome (Young et al., 2012). Some lncRNAs in Plutella xylostella , a pest of cruciferous plants, have been investigated in the context of insecticide resistance and might be involved in detoxification processes (Etebari et al., 2015). In addition, a relatively high-depth screen of 35 publicly available RNA-seq datasets from Aedes aegypti discovered 3,482 putative lincRNAs (Etebari et al., 2016). Finally, comparison of 14,161 lncRNAs from seven different species, including 1,559 from Tribolium castaneum, 2,602 from Drosophila melanogaster, 2,066 from Anopheles gambiae, 1,529 from Apis mellifera, 2,459 from Apis cerana, 2,176 from Nasonia vitripennis, and 1,770 from Drosophila pseudoobscura , showed low sequence conservation among different species. Further, similarities within a species are due to lncRNA association with transposable elements (TEs) and simple repeats, and TEs are less frequent in lincRNA exons than in introns, indicating that TEs may have been removed by selection (Lopez-Ezquerra et al., 2017).

To our knowledge, no lncRNAs have been explored in HDMs. Determining if HDMs contain lncRNAs will contribute to the understanding of allergen expression and regulation in HDMs. Previously, we used RNA-seq to identify HDM genes (Lin et al., 2018). Here, we identified D. farinae lncRNAs from RNA-seq data and confirmed their expression by qRT-PCR. Results of the current research will facilitate future studies to unravel the function of lncRNAs in HDMs and may help develop new methods to control HDMs or new immunotherapeutic strategies to treat allergies to mites.

Materials and Methods

Mite culture and transcriptomic analysis

D. farinae mites were isolated and cultured, and a cDNA library was constructed and sequenced according to previously reported methods (Lin et al., 2018). Briefly, total RNA extracted from ~2,000 homogenized mites was used to construct a transcriptome library with a SMART cDNA Library Construction Kit (American Clontech Corporation, #634901). Sequencing was performed using an Illumina HiSeq 2500 sequencer, followed by de novo assembly with the Trinity/Oases suite.

Total lincRNA and allergen-related lincRNA identification

LincRNAs and their targeted mRNAs were identified from RNA-seq data using a computational pipeline (Li et al., 2014). To identify lincRNAs and mRNAs related to potential allergens, the sequences of all genes encoding known allergens were downloaded from www.allergen.org, the official site for systematic allergen nomenclature. Sequences were then searched against mRNAs and lincRNAs using BLASTN with a cutoff e-value of 1e-5. Allergen sequences were selected and clustered.

Validation of lincRNA from D. farinae

Strand-specific real-time RT-PCR was used to quantify lincRNAs and target mRNAs coding for mite allergens. In brief, the miRNeasy Micro Kit (Qiagen, #217084) was used to isolate total RNA (TaKaRa Biotech, Dalian, China, #D312), and the PrimeScriptTM RT reagent kit (TaKaRa, #RR037A) was used for reverse transcription. The reverse transcription reaction system included 3 μL of total RNA (1,000 ng), 2 μL of 5X PrimeScript Buffer, 0.5 μL of RT primer (final concentration 100 nM), 0.5 μL of PrimeScript RT Enzyme Mix I, and DEPC-treated ddH2O to a final volume of 10 μL. Reverse transcription was carried out in an ABI 9700 PCR thermocycler at 42 ºC for 15 min, 85 ºC for 5 s, and then held at 4 ºC. A SYBR Green PCR kit (TaKaRa, #RR820A) was used for real-time PCR, performed in a total volume of 20 μL containing 10 μL of 2X Real-time PCR Master Mix, 2 μL F primer (final concentration 1 μM), 2 μL R Primer (final concentration 1 μM), 2 μL cDNA template, and 4 μL ddH2 O. Reactions were carried out on the LightCycler 480 real-time PCR instrument (Roche) at 95 °C for 30 s, followed by 40 cycles at 95 °C for 10 s and 60 °C for 50 s. cDNA was denatured at 95 ºC, followed by 40 cycles of 95 ºC for 10 s and 60 ºC for 50 s. Melting curve analysis was performed to validate generation of expected PCR products. The setting was 65 ºC to 95 ºC at a rate of 0.2 °C per 10 s. Product was detected by incubation at 95 ºC for 5 s, 65 ºC for 15 s, and then held at 95 ºC. Primer sequences for real-time RT-PCR are shown in Table 1. Data for real-time RT-PCR were expressed using the 2-DDCt method and analyzed in Excel.

Table 1
Oligonucleotide sets for strand-specific real-time RT-PCR using tagged primers to quantify lncRNA and targeted mRNA encoding mite allergens
Gene symbol or GenBank accession numberPrimer namePrimer sequence*
TRINITY_DN4665311-RTGGCCGTCATGGTGGCGAATCATCGGAAACTATATCGAATGATTC
11-RGGCCGTCATGGTGGCGAAT
11-FATCAGTGTTTTACCTTCCGTAT
KM010005.112-RTGCTAGCTTCAGCTAGGCATCCCATTACGTGTATTACATTTAACC
12-RGCTAGCTTCAGCTAGGCATC
12-FCGTCAATTACGGCATCATTA
TRINITY_DN1328621-FTCTGCCCTCGATATTCTGA
21-RTTGATTCCTTGGATATTGCAC
KM009996.122-FATGGCTGATTTAAGACCAC
22-RCTTTATCTTTCTTTACTTGGCTA
TRINITY_DN2063231-RTGGCCGTCATGGTGGCGAATTCATCAAGCGTAACACTACTGTCCC
31-F1GAAGGTAACTTCGATTTGTGG
31-RGGCCGTCATGGTGGCGAAT
KC305502.132-RTGCTAGCTTCAGCTAGGCATCGTTGGTCTTGCCAGTGCCCTTCTC
32-FTGAGCGTGCTCGCACCAA
32-RGCTAGCTTCAGCTAGGCATC
TRINITY_DN3941941-FTTATTGGCTGCAAACACTTG
41-RTCTGATCCTTGTGGTGGC
D63858.142-FTTATTGGCTGCAAACATTTT
42-RTCTGATCCTTGTGCTGGT
TRINITY_DN5189251-FGCTCTATATATCATCGGTTGC
51-RATAAATAATAAAATGAAATG
AY283280.152-FTCACAATCTAAAATGGCACT
52-RATAAAATTGGGTATGATACGAT
TRINITY_DN5596261-RTGGCCGTCATGGTGGCGAATGATCAACATTGACAAAGTGTTCG
61-FAGATCAACTCAAGACGAAA
61-RGGCCGTCATGGTGGCGAAT
KM009994.162-RTGCTAGCTTCAGCTGAGCCGATCCACATTACACAAAGTGTTA
62-RGCTAGCTTCAGCTGAGCC
62-FGGATGCATGTAAAGGTCGT
TRINITY_DN4350571-FCTATATGAATAAGCGATCCAAC
71-RTTTCCGACAATTAATTCGTTC
KC669700.172-FTATCGTTTAGTTCGTGCAT
72-RTATATTCAATAGTTCGCTCGT
TRINITY_DN5588281-RTGGCCGTCATGGTGGCGAATCAACGGGTTAATAAATTTGAT
81-FCGGCCACTTTTATCCTCTT
81-RGGCCGTCATGGTGGCGAAT
AF465625.182-RTGCTAGCTTCAGCTAGGCATCTATCCTCTTCCAAATCATCT
82-FGGAAGGTGATGAAAGTGTTG
82-RGCTAGCTTCAGCTAGGCATC
TRINITY_DN5476991-RTGGCCGTCATGGTGGCGAATTGTCGATGGACATCTTATCA
91-FCATCGTTCGGTCTTTCGTT
91-RGGCCGTCATGGTGGCGAAT
AF178772.192-RTGCTAGCTTCAGCTAGGCATCTTATTCGCCTATACAAGTCA
92-FAACACCAGCCCCTACAACAT
92-RGCTAGCTTCAGCTAGGCATC
TRINITY_DN8214101-FCACGTATGCAAAGATAGCAG
101-RAAAGAGGCAAAAGATACAGA
KM010014.1102-FTATTGAAGTTGAAACTACTGGC
102-RTTTATAAACACCGACAAGAGC
TRINITY_DN55999111-FAAAAAACTGTCAATCAAT
111-RTCATCATCATTGTAGG
KC305503.1112-FAAAAAACAGTCAATCAGG
112-RTTACGATGAATGCAAT
* RT primers contained six random bases.

Results

Computational identification of D. farinae lincRNA

We used a bioinformatics pipeline to identify lincRNAs from a set of strand-nonspecific RNA-seq data generated for D. farinae. From a total of 186,273 transcripts, 126,664 lincRNAs were predicted. We searched all known allergenic D. farinae proteins to find related lincRNAs. Identified lincRNAs and mRNAs were used to search against known allergenic D. farinae proteins. A total of 11 lincRNAs and 11 mRNAs related to mite allergens were expressed, some with levels indicating possible coordination (Table 2). These allergens were heat shock protein 70, ferritin, Der f 3, Der f 15, Der f 16, Der f 20, Der f 24, Der f 26, Der f 30, Der f 31, and Der f 33. Sequences for the 11 related lincRNAs are shown in Data S1.

Table 2
lncRNA and targeted mRNA encoding mite allergens.
mRNA GenBank Accession NumbermRNAlncRNAIdentityLengthMismatchGapAllergen startAllergen endlncNAT startlncNAT endE-valueScore
KM010005.1Der f 33TRINITY_DN4665399.62105740110571060402022
KM009996.1Der f 30TRINITY_DN1328694.5555304294831554.00E-1685.7
KC305502.1Heat shock protein 70TRINITY_DN2063281.693446031207154735291.00E-37159
D63858.1Der f 3TRINITY_DN3941998.1263812016382966601128
AY283280.1Der f 26TRINITY_DN5189210048001471949567.00E-1995.6
KM009994.1Der f 20TRINITY_DN5596282.382273642444684046281.00E-20101
KC669700.1Ubiquinol-cytochrome c reductase binding protein-like proteinTRINITY_DN4350599.281381082796411384.00E-70266
AF465625.1Der f 16TRINITY_DN558821002650013711635287234.00E-148525
AF178772.1Der f 15TRINITY_DN5476998.6121630145816735373221.00E-111404
KM010014.1Der f 31TRINITY_DN821410054001544114649.00E-23107
KC305503.1FerritinTRINITY_DN5599987.0513918030844611392.00E-30133

Strand-specific real-time RT-PCR identification of lincRNAs and mRNAs related to potential D. farinae allergens

Strand-specific real-time RT-PCR was used to amplify the 11 lincRNAs and their associated mRNAs from D. farinae total RNA. Although one lincRNA (TRINITY_DN55999) failed to generate a curve, the other 10 lincRNAs and their putative target allergen-encoding mRNAs successfully amplified (Figure 1). Low levels of Der f 3 and Der f 20 mRNA were measured in the presence of higher levels of their corresponding lincRNAs, TRINITY_DN39419 and TRINITY_DN55962, indicating a possible negative interaction. However, mRNA expression levels of Der f 15, Der f 16, Der f 24, Der f 26, Der f 30, Der f 31, Der f 33, and heat shock protein 70 positively associated with expression of their corresponding lincRNAs.

qRT-PCR validation of expression of lincRNAs and mRNAs coding for allergens: (1) TRINITY_DN46653 and Der f 33; (2) TRINITY_DN13286 and Der f 30; (3) TRINITY_DN20632 and heat shock protein 70; (4) TRINITY_DN39419 and Der f 3; (5) TRINITY_DN51892 and Der f 26; (6) TRINITY_DN55962 and Der f 20; (7) TRINITY_DN43505 and Der f 24; (8) TRINITY_DN55882 and Der f 16; (9) TRINITY_DN54769 and Der f 15; and (10) TRINITY_DN8214 and Der f 31.
Figure 1
qRT-PCR validation of expression of lincRNAs and mRNAs coding for allergens: (1) TRINITY_DN46653 and Der f 33; (2) TRINITY_DN13286 and Der f 30; (3) TRINITY_DN20632 and heat shock protein 70; (4) TRINITY_DN39419 and Der f 3; (5) TRINITY_DN51892 and Der f 26; (6) TRINITY_DN55962 and Der f 20; (7) TRINITY_DN43505 and Der f 24; (8) TRINITY_DN55882 and Der f 16; (9) TRINITY_DN54769 and Der f 15; and (10) TRINITY_DN8214 and Der f 31.

Discussion

The present study is the first to identify lincRNAs from HDMs and to explore their potential functions. We used our previously reported RNA-seq data from D. farinae (Peng et al., 2018) to generate a computational pipeline (Li et al., 2014) that identified 126,664 lincRNAs from 186,273 predicted transcripts. To determine how many of these lincRNAs are related to HDM allergens, we searched mRNA sequences coding for 37 groups of mite allergens using lincRNAs as query sequences. A total of 11 lincRNAs corresponding to 11 mRNAs related to mite allergens were identified. Although the gene encoding ferritin and its lincRNA could not be amplified, strand-specific real-time RT-PCR identified the other 10 lincRNAs and their allergen-related potential target mRNAs in total mite RNA.

Real-time RT-PCR results showed that mRNA expression levels of Der f 3 and Der f 20 negatively correlated with expression of their corresponding lincRNAs, but mRNA expression levels of Der f 15, Der f 16, Der f 24, Der f 26, Der f 30, Der f 31, Der f 33, and heat shock protein 70 positively associated with expression of their lincRNAs. According to a previous report, recombinant Der f 33 reacts to the serum of patients with mite allergies, with a 23.5% positive rate for the skin prick test. In an asthma mouse model, Der f 33 induces airway allergy-like responses (Wang et al., 2016). Further, immunoblotting showed that 63.4% of dust mite allergic patients react to Der f 26 (An et al., 2013). Enzyme immunoassays indicated that recombinant Der f 16, prepared using an Escherichia coli expression system, binds IgE from 47% (8/17) of mite-allergic patients (Kawamoto et al., 2002). In addition, 43 HDM-allergic patients have shown 32.5% positive responses to skin prick tests for recombinant Der f 31 (Lin et al., 2018).

Aberrant expression of lncRNAs has been reported in immune-related diseases, including allergic diseases. For example, patients with eosinophilic esophagitis, an allergic inflammatory disorder, have altered lncRNA profiles (Sherrill et al., 2014), and altered lincRNA expression has been identified in CD8+ T cells of severe asthma patients (Tsitsiou et al., 2012). lincRNAs are involved in the innate immune response, including activation of monocytes and macrophages as well as regulating expression of inflammatory genes (Hadjicharalambous and Lindsay, 2019), highlighting potential pathways through which lincRNAs may mediate allergenic responses. However, few studies have examined lncRNAs with regards to HDM allergens. Our previous results show that exposing cells to HDM extracts results in differential expression of 270 lncRNAs, 119 of which were co-expressed with mRNAs. Bioinformatic analysis suggested these lncRNAs may target gene pathways related to glycolysis, axon guidance, ErbB signaling, and MAPK signaling (Wang et al., 2018).

In this study, we identified lncRNAs related to allergens produced by the important HDM D. farinae. One potential application of lincRNAs is the development of acaricidal candidates to inhibit mite allergen production in homes. However, to test that possibility, we must first validate the functions of these lincRNAs by developing an asthmatic animal model sensitized by mRNA coding for allergens and then treat animals with corresponding lncRNAs. This is a logical next step in future research.

Acknowledgments

This study was supported by the National Natural Sciences Foundation of China (Grant No. NSFC31272369), the 333 project of Jiangsu Province in 2017 (BRA2017216), the Major Program of Wuxi health and Family Planning Commission (Z201701), and the Primary Research & Development Plan of Jiangsu Province (Grant No.BE2018627).

Notes

Associate Editor: Marcela Ullano-Silva

Conflicts of Interest

The authors declare that there is no conflict of interest.

Author contributions

CL and YC conceived and designed the study, YZ, MW, and HZ conducted the qRT-PCR. JS conducted the RNA-seq data analysis, YC and YZ contributed to writing the manuscript. All authors read and approved the final version of the manuscript.

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Appendices

Supplementary material

The following online material is available for this article:

Sequences of lincRNAs identified from this study.
https://www.researchpad.co/tools/openurl?pubtype=article&doi=10.1590/1678-4685-GMB-2019-0243&title=Identification of LincRNA from <i>Dermatophagoides farinae</i> (Acari: Pyroglyphidae) for Potential Allergen-Related Targets&author=Ying Zhou,Meili Wu,Hanting Zhu,Junjie Shao,Chang Liu,Yubao Cui,&keyword=House dust mites (HDMs),Dermatophagoides farinae,long noncoding RNAs (lncRNAs),allergen,RNA-seq,&subject=Genomics and Bioinformatics,