Patients and healthy controls
Twenty-one pSS patients and twenty-one age-sex matched healthy controls were enrolled in this study. All the pSS patients were recruited from the Peking Union Medical College Hospital and met the American-European consensus criteria for diagnosis(17). Patients with other autoimmune diseases, active/ severe infection or malignant diseases were excluded from the study. All the pSS patients and matched healthy controls in this study have signed the informed consent. The RNA-seq analysis was carried out on 5 pSS patient samples and 5 corresponding healthy controls while the following validation study consisted of 16 pSS patients and 16 matched healthy controls. All the patients and healthy controls were females. Patient’s disease activity was determined by EULAR Sjögren’s syndrome disease activity index (ESSDAI)(18), and serological examinations, including Immunoglobulin G (IgG), immunoglobulin A (IgA), immunoglobulin M (IgM), anti-SSA and SSB antibody, erythrocyte sedimentation rate (ESR), rheumatoid factor (RF), and ect, were performed for the study subjects. The detailed demographic and clinical features of patients and healthy controls are listed in Table 1.
Peripheral blood (10 mL) was obtained from each subject and all the samples were collected in the ethylene diamine tetraacetic acid (EDTA) tubes. Peripheral blood mononuclear cells (PBMCs) were isolated using the Ficoll density gradient centrifugation and were counted using Cellometer Auto T4 (Nexcelom Bioscience, USA). Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) and the concentration of total RNA was measured by NanoDrop2000c spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). Then, the total RNA was reverse transcribed into complementary DNA (cDNA) using PrimeScript RT Master Mix (TaKaRa, Dalian, China) and was stored at -80℃ for the validation study.
Library preparation for LncRNA sequencing
A total amount of 20 ng RNA per sample was used as input material for the RNA sample preparations. Firstly, ribosomal RNA was removed by Epicentre Ribo-zero rRNA Removal Kit (Epicentre, USA), and rRNA free residues was cleaned up by ethanol precipitation. Subsequently, sequencing libraries were generated using the rRNA-depleted RNA by NEBNext Directional RNA Library Prep Kit for Illumina (NEB, USA) following manufacturer’s recommendations. Then, we used the Qubit RNA Assay Kit and Qubit 2.0 Flurometer (Life Technologies, CA, USA) to quantify RNAs. RNA integrity was assessed using the RNA Mano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA). The libraries were sequenced on an Illumina Hiseq 2500 platform and 125 bp paired-end reads were generated.
Real-time quantitative polymerase chain reaction (RT-qPCR)
The stored cDNAs were processed by TB Green Premix Taq II kit (TaKaRa, Dalian, China) and 7900 HT Fast Real-Time PCR System (ABI, Foster City, CA, USA). SYBR Green Buffer, other reagents in this kit, and the cDNAs were in a total volume of 10 ul and the RT-qPCR was performed in 384-well microplates. β-actin mRNA (5’-TGACGTGGACATCCGCAAAG-3’ (forward), 5’-CTGGAAGGTGGACAGCGAGG-3’(reverse)) was used as the internal reference in this study, and the LncRNA expression level was compared through the 2-ΔΔct method. Based on the results of the RNA-seq, we selected 11 differently expressed LncRNAs for validation study (P<0.05, fold change >1.5). The selected LncRNAs’ primer sequences are listed as follows: LINC00426 5′-CACACAATGTTCTCATCGCCC-3′(forward), 5′- GGACAGTGACATCTCACTTCCC A-3′(reverse), TPTEP1-202 5′- CCAGAAAGAAACTCAGCCCAC-3′(forward), 5′- TGTGAAGAGACCACCAAACAGG-3′(reverse), CYTOR-235 5′-CCAATGAGAATGAAGGCTGAG
ACA-3′ (forward), 5′- ACTGTGCTGTGAAGATCTGAAGAC-3′(reverse), RN7SL834P 5′- CCAGTTACTCAGAAGACAGAAGCA-3′(forward), 5′- GCATGGATATCTCATTGGCATAG-3′(reverse), NRIR 5′- CCATTCATAACCTCATAAACCACC-3′(forward), 5′- ACCATCTCACAATGT
GCCCA-3′(reverse), DTX2P1-UPK3BP1-PMS2P11 5′- TCACTGCCAGAGGGTTTCCC-3′(forward), 5′- ACGGGCAGCGTCATGTAGT-3′(reverse), BISPR 5′- GTACATGCCTGTAATCCCAACACTT-3′(forward), 5′- GGAAGGATTTTGTTGCTCACACTAG-3′(reverse), RN7SL141P 5′- TCGCACTAAGTTCAGCATTAATGG-3′(forward), 5′- TGATGGCTATTCATGGGCATGT-3′(reverse), LINC01550 5′- TACCGAGCTTTACAGCCATATTG
A-3′(forward), 5′- CAGTGTTATTTACCAGCAGGAAAAG-3′(reverse), SNHG8 5′- GCCTTTCTTCCAAATCATCAGC-3′(forward), 5′- GCAGTAGAGGATCAGGAATGGTG-3′(reverse), LOC105373098 5′- GTCATGTTCCTTACTAACAGCACGT-3′(forward), 5′- GCTCTTTCAGTCAGGTGTTCCC-3′(reverse), NEAT1 5′- CGGCACCTAGCATGTTTGAC-3′(forward), 5′- CGCCAAACCTAGAGAAAAGTCC-3′(reverse).
LncRNA-mRNA co-location and co-expression analysis
The co-localization and co-expression analysis were based on the LncRNAs which have been screened and verified for different expression in the study. LncRNAs involved in this analysis were differently expressed in the validation study as discussed above. Cis role was LncRNA acting on neighboring target genes. We searched coding genes 10k/100k upstream and downstream of lncRNA and then analyzed their function next. Trans role was LncRNA to identify each other by the expression level. We calculated the expressed correlation between LncRNAs and coding genes with r function.
The Ballgown was used to analyze the differentially expressed LncRNAs and mRNAs, transcripts with a P-adjust <0.05 or P-value<0.05 were assigned as differentially expressed. Hierarchical clustering was performed in Cluster 3.0 and the heat maps were drawn by Graphpad Prism 7.0. Gene Ontology (GO) enrichment analysis of differentially expressed genes or lncRNA target genes were implemented by GOseq (Release 2.12), KOBAS software (V2.0) was used to test the statistical enrichment of differential expression genes or lncRNA target genes in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The correlation between clinical features and validated LncRNAs were tested through Spearman’s correlation. A P-value (two-tailed) <0.05 was thought to be statistically significant.