阅读说明：本技术 基于lncRNA的SCA3/MJD的生物标志物的筛选和鉴定方法 (Method for screening and identifying biomarkers of SCA3/MJD based on lncRNA ) 是由 江泓 李天娇 陈召 彭慧蓉 唐北沙 于 2018-07-31 设计创作，主要内容包括：一种基于lncRNA的SCA3/MJD的生物标志物的筛选和鉴定方法,包括以下步骤：1)准备含脊髓小脑性共济失调3型的抗凝血和不含脊髓小脑性共济失调3型的抗凝血各5～10ml使用淋巴细胞分离液分离外周血单个核细胞；2)提取含lncRNA的总RNAs；3)对总RNAs样本进行高通量测序和生物信息学分析,挑选出组间差异表达的lncRNAs；4)对筛选得到的lncRNAs,进行qRT-PCR验证,并对其进行Wilcoxon秩和检验,筛选得到SCA3/MJD生物标志物lncRNAs。该筛选方法操作简单,筛选效率高,有效筛选出6个lncRNAs为SCA3/MJD生物标志物,且有助于扩充和完善lncRNA的表达谱。(A method for screening and identifying biomarkers of SCA3/MJD based on lncRNA, comprising the following steps: 1) preparing 5-10 ml of anticoagulant containing spinocerebellar ataxia 3 and 5-10 ml of anticoagulant without spinocerebellar ataxia 3 respectively, and separating peripheral blood mononuclear cells by using lymphocyte separation liquid; 2) extracting total RNAs containing lncRNA; 3) carrying out high-throughput sequencing and bioinformatics analysis on the total RNAs samples, and selecting lncRNAs which are differentially expressed among groups; 4) and carrying out qRT-PCR verification on the screened lncRNAs, carrying out Wilcoxon rank-sum test on the lncRNAs, and screening to obtain SCA3/MJD biomarker lncRNAs. The screening method is simple to operate and high in screening efficiency, effectively screens 6 lncRNAs serving as SCA3/MJD biomarkers, and is beneficial to expanding and perfecting the expression profile of lncRNA.)

1. A method for screening and identifying biomarkers of SCA3/MJD based on lncRNA, which is characterized by comprising the following steps:

1) preparing 5-10 ml of anticoagulation blood containing spinocerebellar ataxia 3 and anticoagulation blood without spinocerebellar ataxia 3, separating serum obtained by centrifugal separation again to obtain peripheral blood mononuclear cells, and freezing at low temperature for later use;

2) extracting total RNAs containing lncRNA in the peripheral blood mononuclear cells in the step 1);

3) carrying out high-throughput sequencing and bioinformatics analysis on the total RNAs samples obtained in the step 2), and selecting lncRNAs which are differentially expressed among groups;

4) and (3) carrying out qRT-PCR verification on the lncRNAs obtained by screening in the step 3), carrying out Wilcoxon rank sum test on the lncRNAs, and screening to obtain SCA3/MJD biomarker lncRNAs.

2. The method for screening and identifying lncRNA-based SCA3/MJD biomarkers according to claim 1, wherein the method for screening and identifying lncRNA-based SCA3/MJD biomarkers between steps 3) and 4) further comprises:

target gene prediction: by calculating a Spearman correlation coefficient and a Pearson correlation coefficient of lncRNA and mRNA, determining the mRNA as a target gene when the Spearman correlation coefficient is more than or equal to 0.6 and the Pearson correlation coefficient is more than or equal to 0.6;

and gene function annotation: the mRNA is annotated with GO and KEGG annotations and one or more of NT, NR, KOG, SwissProt, or InterPro annotations.

3. The method for screening and identifying biomarkers of SCA3/MJD based on lncRNA of claim 1 or 2, wherein the specific operations of high-throughput sequencing and bioinformatic analysis comprise:

a) performing high-throughput sequencing on the RNA sample by adopting Illumina Hiseq X-Ten;

b) three prediction software CPC, txcdredict and CNCI were used to score the coding capacity of transcripts, with different scoring ranges to distinguish mRNA from lncRNA;

c) comparing the transcript with a protein database Pfam, if the transcript is on the protein database Pfam, judging the transcript as mRNA, otherwise, judging the transcript as lncRNA;

d) and c), integrating the judgment results of the steps b) and c), and when the transcript is judged to be lncRNA in at least three modes of CPC, txCDPredict, CNCI and protein database Pfam comparison results, judging the transcript to be lncRNA.

4. The method for screening and identifying biomarkers SCA3/MJD based on lncRNA as claimed in claim 1 or 2, wherein the quantitative real-time PCR (qRT-PCR) verification in step 4) is performed by:

a) reverse transcription was performed using the golden star RT6cDNA synthesis kit;

b) designing a Primer by Primer 5;

c) qRT-PCR is carried out by adopting a 2 XT 5Fast qPCR Mix (SYBR Green I) kit; GAPDH was used as a standardized internal control, and 2 was used ^-ΔΔCtThe method quantifies the expression of lncRNA.

5. The method for screening and identifying lncRNA-based SCA3/MJD biomarkers as claimed in claim 1 or 2, wherein the biomarkers lncRNAs comprise nosat 165686.1, LTCONS _00051791, LTCONS _00175021, LTCONS _00175040, nnsat 022144.2 and LTCONS _ 00176188.

6. The method for screening and identifying biomarkers of SCA3/MJD based on lncRNA as claimed in claim 1 or 2, wherein the LTCONS _00051791, LTCONS _00175021, LTCONS _00175040 and LTCONS _00176188 are located in chr13: 31723572-.

Technical Field

The invention relates to a method for screening biomarkers, in particular to a method for screening and identifying biomarkers SCA3/MJD based on lncRNA.

Background

Spinocerebellar ataxia (SCA) is one of the major neurodegenerative diseases in humans, with Spinocerebellar ataxia type 3/Machado-Joseph disease, SCA3/MJD being the most common. Spinocerebellar ataxia type 3/machado-josephsis (SCA3/MJD) and SCA7 are, like HD, one of (15) nine polyglutamine (polyQ) diseases, which are mainly caused by abnormal amplification of the trinucleotide CAG in the ATXN3 gene, and the onset age can be from 4 to over 70 years.

Non-coding RNA is of increasing interest as a class of transcripts that can be distinguished by length into long non-coding RNAs (incrnas) and short non-coding RNAs, where the long non-coding RNAs (incrnas) are over 200 nucleotides in length. Wapinski O, Chang HY and others reported in Long noncoding RNAs and human disease that lncRNA participates in transcriptional regulation, post-transcriptional regulation, and even in almost every step of the gene life cycle, and can interact with other biomolecules.

Salta E, De Strooper B et al show in Noncoding RNAs in neuro-synthesis that: part of lncRNA is associated with neurodegenerative diseases.

Tan JY, Vance KW et al, Cross-talking non-coding RNAs construct to cell-specific neuro-synthesis in SCA7, disclose that lnc-SCA7(ATXN7L3B) is highly conserved in the central nervous system of humans and adult mice and exerts a post-transcriptional regulatory effect on the causative gene ATXN7 of spinocerebellar ataxia type 7 (SCA 7). After knockout of lnc-sca7(ATXN7L3B) in N2a cells derived from mouse neuroblastoma, the transcript level of ATXN7 was significantly reduced, resulting in a significant reduction in the ATXN7 protein. When lnc-sca7(ATXN7L3B) was overexpressed, the transcript level of ATXN7 was significantly enhanced.

Sunwood JS, Lee St et al in "Altered Expression of the Long nonading RNANEAT1 in Huntington's Disease" showed that lncRNA is most expressed in thalamus and striatum, and confirmed that TUNA in caudate nucleus may be involved in the pathophysiology of Huntington's Disease by detecting gene Expression in brains of 44 HD patients and 36 healthy individuals. In addition, NEAT1, as a lncRNA, has also been shown to be involved in the impairment mechanism of Huntington's Disease (HD).

Despite the various hypotheses for the pathogenesis of SCA3/MJD, there is currently no accurate and effective treatment to monitor disease progression, delay or treat disease. Since long non-coding rnas (lncRNAs) have been confirmed to be involved in the pathogenesis of SCA7 and HD, we speculate that lncRNAs may also be involved in the pathogenesis of SCA3/MJD, it is desirable to provide a method suitable for screening the markers lncRNAs SCA 3/MJD.

Disclosure of Invention

The technical problem to be solved by the invention is as follows: overcomes the defects of the prior art, and provides a method for screening and identifying the biomarkers of SCA3/MJD based on lncRNA, which has the advantages of simple operation, high screening efficiency and high accuracy.

The technical scheme adopted by the invention for solving the technical problems is as follows:

a method for screening and identifying biomarkers of SCA3/MJD based on lncRNA, comprising the following steps:

1) preparing 5-10 ml of anticoagulated blood containing spinocerebellar ataxia 3 type (SCA3/MJD) and anticoagulated blood without spinocerebellar ataxia 3 type (SCA3/MJD), separating serum obtained by centrifugal separation again to obtain peripheral blood mononuclear cells, and freezing at low temperature (-80 ℃) for later use;

2) extracting total RNAs containing lncRNA in the peripheral blood mononuclear cells in the step 1);

3) carrying out high-throughput sequencing and bioinformatics analysis on the total RNAs samples obtained in the step 2), and selecting lncRNAs which are differentially expressed among groups;

4) and (3) carrying out qRT-PCR (quantitative real-time PCR) verification on the lncRNAs obtained by screening in the step 3), carrying out Wilcoxon rank-sum test on the lncRNAs, and screening to obtain an SCA3/MJD biomarker lncRNSAN.

The method for screening and identifying the biomarkers of SCA3/MJD based on lncRNA further comprises the following steps between the steps 3) and 4):

target gene prediction: since the cis mechanism indicates that lncRNA functions in relation to the protein-encoding gene adjacent to its locus, we screened the adjacent mRNA as its target gene. Since the trans mechanism is independent of position, we predict by calculating the binding energy.

The mRNA is determined as the target gene when the Spearman correlation coefficient is more than or equal to 0.6 and the Pearson correlation coefficient is more than or equal to 0.6 by calculating the Spearman correlation coefficient and the Pearson correlation coefficient of the lncRNA and the mRNA.

Functional annotation of genes: GO, KEGG annotation and one or more of NT, NR, KOG, SwissProt, or InterPro annotation on mRNA, namely NT, NR, KOG, KEGG, and SwissProt annotation on mRNA by Blast and/or Diamond, GO annotation using Blast2GO and NR annotation results, InterPro annotation using InterPro scan 5.

Further, the specific operations of high-throughput sequencing and bioinformatics analysis include, among others:

a) performing high-throughput sequencing on the RNA sample by adopting Illumina Hiseq X-Ten;

b) three prediction software CPC, txcdredict and CNCI were used to score the coding capacity of transcripts, with different scoring ranges to distinguish mRNA from lncRNA;

c) comparing the transcript with a protein database Pfam, if the transcript is on the protein database Pfam, judging the transcript as mRNA, otherwise, judging the transcript as lncRNA;

d) and c), integrating the judgment results of the steps b) and c), and when the transcript is judged to be lncRNA in at least three modes of CPC, txCDPredict, CNCI and protein database Pfam comparison results, judging the transcript to be lncRNA.

Further, the specific operation of the quantitative real-time PCR (qRT-PCR) verification in step 4) is:

a) reverse transcription was performed using the golden star RT6cDNA synthesis kit;

b) designing a Primer by Primer 5;

c) qRT-PCR was performed using 2 XT 5Fast qPCR Mix (SYBR Green I) kit;

GAPDH was used as a normalization internal control and lncRNA was expressed quantitatively using the 2- Δ Δ Ct method.

Further, the method for screening and identifying the biomarkers of SCA3/MJD based on lncRNA, wherein the biomarkers lncRNAs comprise NONHSAT165686.1, LTCONS _00051791, LTCONS _00175021, LTCONS _00175040, NONHSAT022144.2 and LTCONS _ 00176188.

Furthermore, the LTCONS _00051791, LTCONS _00175021, LTCONS _00175040 and LTCONS _00176188 are respectively located in chr13: 31723572-.

The method for screening and identifying the biomarkers SCA3/MJD based on lncRNA has the beneficial effects that:

the anticoagulated PNMCs containing SCA3/MJD contained 124,394 total transcripts as detected by high throughput sequencing, which contained 15,926 new lncRNA, 13,651 new mRNA, 61,335 known lncRNA and 33,482 known mRNA.

After filtering and analyzing the DEGs by the software DEGseq data, we found 5,540 known lncrnas and 2,759 new lncrnas. In addition, there were 4701 known mRNAs and 2517 new mRNAs.

We found 3812 known lncRNAs upregulated and 2300 novel lncRNAs upregulated. In contrast, the rest down-regulated lncRNA.

Among the known lncrnas and the novel lncrnas, we confirmed that 6 lncrnas were statistically different in PBMCs by qRT-PCR, Wilcoxon rank-sum test, i.e., non-lncrnas 165686.1, LTCONS _00051791, LTCONS _00175021, LTCONS _00175040, non-lncrs 022144.2 and LTCONS _00176188 were significantly expressed in blood containing SCA3/MJD, wherein the lncrnas whose expression was upregulated were non-lncrnas 165686.1, LTCONS _00051791, LTCONS _00175021 and LTCONS _00175040, which were upregulated 5.6, 4.8, 2.0 and 2.4 times, respectively, compared to the control group; expression of down-regulated lncRNA: NONHSAT022144.2 and LTCONS _00176188, and expression of NONHSAT022144.2 in the SCA3/MJD patient group was approximately two thirds of that of the control group, and expression of LTCONS _00176188 in the SCA3/MJD patient group was approximately one quarter of that of the control group; and most significantly, NONHSAT022144.2 and NONHSAT165686.1 were expressed; NONHSAT165686.1, LTCONS _00051791, LTCONS _00175021, LTCONS _00175040, NONHSAT022144.2 and LTCONS _00176188 are SCA3/MJD biomarkers, and provide basis for developing SCA3/MJD disease-related diagnostic kits.

The newly discovered LTCONS _00051791, LTCONS _00175021, LTCONS _00175040 and LTCONS _001761884 lncRNAs help to expand and refine the expression profile of lncRNA.

Drawings

FIG. 1-is a graph of the enrichment results of the GO analysis of the differentially expressed genes DEGs (first 20);

FIG. 2-is a graph of the enrichment results of the GO analysis of the target genes (first 20) of the differentially expressed genes DEGs;

FIG. 3 is a graph showing the enrichment results of DEGs in different pathways by KEGG analysis;

FIG. 4 is a graph showing the results of KEGG analysis of the enrichment of target genes of the differentially expressed genes DEGs in different pathways;

FIG. 5-comparative analysis of the expression levels of differentially expressed gene lncRNAs in SCA3/MJD cases and healthy controls.

FIG. 6-comparative analysis of the expression levels of differentially expressed gene lncRNAs in the cerebellum tissue of SCA3/MJD cases and healthy controls.

Detailed Description

The invention is further explained with reference to the drawings and the embodiments.

Referring to fig. 1:

1) preparing 5-10 ml of anticoagulation blood (case sample) containing spinocerebellar ataxia 3 type (SCA3/MJD) and anticoagulation blood (control sample) without spinocerebellar ataxia 3 type (SCA3/MJD), separating serum obtained by centrifugal separation again to obtain Peripheral Blood Mononuclear Cells (PBMCs), and freezing at low temperature (-80 ℃) for later use;

a) sucking 10ml of anticoagulated blood into a 50ml centrifuge tube, centrifuging for 10 minutes by a centrifugal force of 500g, and layering serum and lower layer cells;

b) adding PBS with the volume of 1:1 for dilution;

c) carefully and slowly adding 15ml of lymphocyte separation solution, and mixing well;

d) centrifuging at 500g for 30 minutes, slowly lifting, and dividing the liquid into four layers;

e) sucking the transparent cloud layer (second layer) below the serum layer out to a 15ml centrifuge tube, and adding a proper amount of PBS for washing;

f) centrifuging at 500g for 5min, and removing supernatant;

g) adding PBS to dissolve cell sediment, and sucking to a new EP tube;

h) centrifuging at 500g for 5min, and removing supernatant;

i) repeating the step g.h;

j) adding 700ul Qrizol lysate to lyse the cells, and freezing to minus 80 ℃ for later use;

2) extracting lncRNA-containing total RNAs in the peripheral blood mononuclear cells of the step 1) by using an RNeasy kit (Qiagen, Hilden, Germany), and specifically operating according to the instruction of the RNeasy kit;

3) performing high-throughput sequencing and bioinformatics analysis on the total RNAs samples obtained in the step 2), and selecting lncRNAs which are differentially expressed among groups:

a) performing high-throughput sequencing on the RNA sample by adopting Illumina Hiseq X-Ten;

b) three prediction software CPC, txcdredict and CNCI were used to score the coding capacity of transcripts, with different scoring ranges to distinguish mRNA from lncRNA;

c) comparing the transcript with a protein database Pfam, if the transcript is on the protein database Pfam, judging the transcript as mRNA, otherwise, judging the transcript as lncRNA;

d) synthesizing the judgment results of the steps b) and c), and when the transcript is judged to be lncRNA in at least three modes of CPC, txCDPredict, CNCI and protein database Pfam comparison results, considering the transcript to be lncRNA;

high throughput sequencing initially detected 124,394 total transcripts, which contained 15,926 new incrnas, 13,651 new mrnas, 61,335 known incrnas, and 33,482 known mrnas. After filtering and analyzing the DEGs by the software DEGseq data, we found 5,540 known lncrnas and 2,759 new lncrnas. In addition, there were 4701 known mRNAs and 2517 new mRNAs.

4) Target gene prediction:

since cis-mechanism (cis regulation, which refers to a transcriptional activation and expression regulation of adjacent mRNA by non-coding RNA) indicates that the function of lncRNA is related to the protein coding gene adjacent to its locus, we screened the adjacent mRNA as its target gene. Since the trans mechanism is independent of position, we predict by calculating the binding energy.

The mRNA is determined as the target gene by calculating the Spearman correlation coefficient and the Pearson correlation coefficient of the lncRNA and the mRNA, when the Spearman correlation coefficient is more than or equal to 0.6 and the Pearson correlation coefficient is more than or equal to 0.6, and 5,540 known lncRNA and 2,759 new lncRNA which are screened out are analyzed, so that 3443 target genes are found.

The overlapping relationship between mRNA and lncRNA was subdivided by analyzing the overlapping portion between lncRNA and the target gene, and the specific categories of the overlapping relationship between mRNA and lncRNA and the number of each category are shown in table 2.

TABLE 2 overlap Classification of mRNA and lncRNA

Lnc-Overlap-mRNA: denotes lncRNA on the same strand as mRNA, which overlaps with mRNA;

Lnc-AntiOverlap-mRNA: the lncRNA and mRNA are on different strands, and there is overlap between the lncRNA and mRNA;

Lnc-CompleteIn-mRNAxon: the lncRNA and the mRNA are on the same strand, and the lncRNA completely falls into the exon region of the mRNA;

Lnc-AntiCompleteIn-mRNAxon: lncRNA and mRNA are on different strands, and lncRNA falls completely within the exonic region of mRNA;

mRNA-CompleteIn-LncExon: meaning that lncRNA and mRNA are on the same strand and that the mRNA falls completely within the exon region of lncRNA;

mRNA-AntiCompleteIn-LncExon: meaning that lncRNA and mRNA are on different strands and that the mRNA falls completely within the exonic regions of lncRNA;

Lnc-CompleteIn-mRNAIntron: meaning that the lncRNA and mRNA are on the same strand and the lncRNA falls completely within the intron region of the mRNA;

Lnc-AntiCompletein-mRNAIntron: meaning that the lncRNA and mRNA are on different strands and the lncRNA falls completely within the intron region of the mRNA;

mRNA-CompleteIn-LncIntron: meaning that the incrna and mRNA are on the same strand and the mRNA falls completely within the intron region of the incrna;

mRNA-AntiCompleteIn-LncIntron: meaning that the incrna and mRNA are on different strands and that the mRNA falls completely within the intron region of the incrna.

5) Functional annotation of genes: NT, NR, KOG, KEGG and SwissProt annotations were performed on mRNA by Blast and/or Diamond, GO annotations were performed using Blast2GO and NR annotations, and InterPro annotations were performed using InterProScan 5.

FIG. 1 shows the first 20 Differentially Expressed Genes (DEG) derived from GO enrichment analysis, including Intracellular (GO:0005622), Intracellular part (GO:0044424), Regulation of response constraints (GO:0048583), Regulation of Intracellular signal transduction (GO:1902531), Intracellular organ part (GO:0044446), Organicellular part (GO:0044422), Nuclear part (GO:0044428), Nuclear (GO:0005654), Binding (GO:0005488), Cell (GO:0005623), cellular-expressed Cell (GO:0031974), Organicellular organ part (GO:0043233), cellular (0005737), cellular organ (GO:0044464), cellular-expressed Cell (GO:0044464), cellular organ of molecular gene (GO:0043067), regulatory Cell of molecular gene (GO:0043067), Cell of molecular gene (GO: 638), Cell of biological gene of Cell of molecular gene (GO: 638), Cell of molecular gene (GO: 638), Cell of molecular gene of interest (GO: 638), Cell of molecular gene of interest (GO).

Meanwhile, we performed GO analysis on the target genes of differentially expressed genes, and enriched the first 20 genes of the differentially expressed genes, including CCR chemokinetic receptor binding (GO:0048020), chemokinetic receptor binding (GO:0042379), stress to external biological concentrations (GO:0043207), stress other organization (GO:0051707), chemokinetic activity (GO:0008009), stress to biological concentrations (GO:0009607), protein recovery (GO:0042026), stress regulation of stress interaction (GO:0032103), stress to biological concentrations (GO:0031730), stress to strain (CCR 0006950), CCR1 binding (GO: 37), stress to biological concentrations (GO: 3611), stress to strain (GO: 369), stress to strain (GO: 3626), regulation of natural killer cell chemoreception (GO:2000501), cytokine receiver binding (GO:0005126), as shown in FIG. 2. KEGG analysis showed that the differentially expressed genes DEGs and their target genes were enriched in different pathways, as shown in fig. 3 and 4.

4) Carrying out qRT-PCR (quantitative real-time PCR) verification on the lnncRNAs obtained by screening in the step 3), carrying out Wilcoxon rank sum test on the lnncRNAs, and screening to obtain an SCA3/MJD biomarker LNCRNAS:

from the lncRNAs obtained by screening in the step 3), lncRNAs with the differential expression fold of the differential expression genes of >5 of the case sample and the control sample are further selected to be subjected to a qRT-PCR verification test, and the lncRNAs with the differential expression fold of >5 of the differential expression genes comprise 20 lncRNAs related to SCA/MJD 3. See table 2 for specific names and locations.

a) Use of Goldenstar ^TMRT6cDNA Synthesis kit to the screening of lnrRNAs reverse transcription:

the RNA template and various components of the kit are thawed on ice until ready for use.

Preparing a reverse transcription reaction system (20 mu l) in a micro-centrifuge tube without nuclease according to the table, gently mixing the reaction system and the reverse transcription reaction system by using a gun head, and centrifuging the reaction system for a short time;

using 2pmol if gene specific primers are used;

RNA template suggested use of f is: total RNA,10 ng-5 mug; mRNA,0.5 ng-0.5. mu.g.

If used, the golden star ^TMOligo (dT)17 or gene-specific primer is incubated for 30-50 min at 50 DEG C

If the Goldenstar' Randomer is used, the incubation is carried out for 10min at 25 ℃ and the incubation is carried out for 30-50 min at 50 DEG C

Or 15min (the product was used for Real-time Quantification PCR).

Incubating at 85 deg.C for 5min, and placing on ice or refrigerating;

b) primers were designed by Primer 5, and the Primer information is shown in table 2;

TABLE 2 location, type of disorder and primer design of lncRNAs

Novel lncRNAs:using the‘LTCONS’；known lncRNAs:using the‘NONHSAT’

F:represents forward primer；R:represents reverse primer；

Location information based on database hg19(raw data from high-throughput sequencing)

c) Quantitative Real-time PCR was performed using 2 XT 5Fast qPCR Mix (SYBR Green I) kit, using GAPDH as a standardized internal reference, and 2 ^-ΔΔCtThe method quantifies the expression of lncRNA.

All cDNA samples were configured into a Realtime PCR reaction system: 2 XT 5Fast qPCR Mix 10. mu.l, 10uM PCR specific primer F0.8. mu.l, 10uM PCR specific primer R0.8. mu.l, template DNA (<100ng), double distilled water was added to a total volume of 20. mu.l;

add 18ul of the mixture to each well corresponding to 384-PCR plate, and add the corresponding 2. mu.l cDNA; the PCR reaction was carried out on a quant sutdio 5384 qPCR instrument using GAPDH as an internal reference, and GAPDH and all the indices were carried out according to the following procedures: at 95 ℃ for 3 min; 40 PCR cycles (95 ℃, 60 seconds; 60 ℃, 10-15 seconds; 95 ℃,10 seconds; and (60 ℃ fluorescence signal acquisition)); by using 2 ^-ΔΔCtThe method performs data analysis.

Statistical significance was considered when P value <0.05 by Wilcoxon rank-sum testing of the statistically different expressed genes between groups, where 6 lncRNAs had statistical significance, including 6 lncRNAs in total known as noshsat 165686.1, noshsat 022144.2 and newly discovered LTCONS _00051791, LTCONS _00175021, LTCONS _00175040, and LTCONS _ 00176188.

Results of comparison of expression levels of differentially expressed genes lncRNAs in peripheral blood mononuclear cells of the case sample and the control sample are shown in fig. 5, in which 4 lncRNAs in total of nonosat 165686.1, LTCONS _00051791, LTCONS _00175021, and LTCONS _00175040 were up-regulated in expression level, lncRNA nnsat 022144.2, and lncraltcons _00176188 were down-regulated in expression level, and NONHSAT165686.1 was about 5.6 times (p ═ 0.036), LTCONS _00051791 was about 4.8 times (p ═ 0.018), and both LTCONS _00175021 and LTCONS _00175040 were more than two times (p ═ 0.027 of LTCONS _00175021 and p ═ 0.032 of LTCONS _ 00175040); in contrast, the expression levels of known lncrnanronhsat 022144.2 and new lncRNA ltcos _00176188 were 0.259-fold (p 0.000) and 0.640-fold (p 0.043) in the case samples, respectively, compared to the control group.

The results of comparison of the expression levels of the above differentially expressed genes in the cerebellum of the case sample and the control sample are shown in FIG. 6, in which the expression levels of LTCLONS _00176188 and NONHSAT022144.2, which are down-regulated, are reduced by about one fourth in the cerebellum tissue of the SCA3/MJD patient, relative to the control group (healthy individuals); in the cerebellum tissue of the SCA3/MJD patient, the expression level of the up-regulated differentially expressed gene LTCLONS _00051791 is 1.5 times higher than that of the control group (healthy individuals), the expression level of NONHSAT165686.1 is only 5% higher than that of the control group, and the expression of LTCLONS _00175040 in the cerebellum tissue of the SCA3/MJD patient is only 5% of that of the control group; the expression level of LTCONS _00175021 was reduced by about one third in the cerebellum.

NONHSAT022144.2, which was shown to be located in chr11 in the NONCODE database (https:// www.bioinfo.org/NONCODE2016 /): 65499058 and 65506444, with the highest expression in heart (FPKM ═ 202.808), followed by brain (FPKM ═ 152.041), may indicate that noshsat 022144.2 is involved in the regulation of the nervous system.

Nonahsat 022144.2 by search of UCSC genome browser (http:// genome. UCSC. edu/cgi-bin/hgTracks. The MALAT1 gene, also known as NEAT2, a nuclear parapherckleassembly transcript 2 gene, NEAT1, a family of genes that has been shown to be resistant to neuronal damage, contribute to neuroprotection in huntington's cases, and can be used as a potential therapeutic approach. Since the pathogenesis of Huntington's disease and SCA3/MJD are very similar and are among the PolyQ diseases, it is suggested that NONHSAT022144.2 may be a potential therapeutic molecule for SCA 3/MJD.

In the NONCODE database, the position of NONHSAT165686.1 was shown to be in Chr13: 48233221-. FBD is characterized by progressive dementia, cerebellar ataxia and spasticity, with partial clinical features similar to SCA 3/MJD. Incidentally, FDD also has symptoms such as progressive ataxia.

In combination with the comparison of the expression levels of the above differentially expressed genes in the cerebellum of the case sample and the control sample shown in FIG. 6, 6 lncRNAs in total of NONHSAT165686.1, LTCONS _00051791, LTCONS _00175021, LTCONS _00175040, NONHSAT022144.2 and LTCONS _00176188 were found to be biomarkers of SCA 3/MJD.