Overview
Novogene offers comprehensive Small RNA Sequencing service (sRNA-seq), to investigate the regulatory network of noncoding RNA of 18-40nt in length, especially for microRNA (miRNA) transcripts. Variations in miRNA can be correlated with gene silencing and post-transcriptional regulation of gene expression, which provides researchers an effective method of regulating target on mRNAs with unprecedented sensitivity and high resolution. Bioinformatic analysis of sRNA-seq illustrates differential expression of miRNAs, structural alterations and discovery of novel small RNAs via a high throughput research technique.
Applications
- Expression quantification of small RNA transcripts
- Function verification, such as gene knockout, over-expression of miRNA genes
- Advanced Analysis: miRNA target gene verification
- Advanced Analysis: piRNA identification and expression quantification
Advantages
- Extensive experience with thousands of samples being successfully sequenced.
- Unsurpassed data quality with a guaranteed Q30 score ≥ 85% that exceeds Illumina’s official benchmarks.
- Comprehensive analysis using mainstream software and mature in-house pipeline to meet multiple bioinformatic requests.
- Free correlation analysis for both small RNA and mRNA expression levels to investigate the regulatory networks.
Sample Requirements
| Library Type | Sample Type | Amount | RNA Integrity Number (Agilent 2100) |
Purity (NanoDrop) |
| Small RNA Library | Total RNA | ≥ 2 μg | Animal ≥ 7.5, Plant ≥ 7, with smooth baseline; |
OD260/280 = 1.8-2.2;
OD260/230 ≥ 1.8; |
|
Exosomal Small RNA Library
|
Exosomal RNA
|
≥ 20ng
|
Peak between 25-200nt, FU> 10, no peak > 2000nt
|
Note: For detailed information, please contact us.
Sequencing Parameters and Analysis Contents
| Platform Type | Illumina Novaseq 6000 |
| Read Length | Single-end 50 |
| Recommended Sequencing Depth | ≥ 10 million read pair per sample |
| Standard Analysis (miRNA) |
|
Note: Sequencing depths and bioinformatic analysis (or advanced analysis for mRNA association or piRNA) requests can be customized based on the project needs. Please contact us for more information.
Project Workflow
Spliceosome disassembly factors ILP1 and NTR1 promote miRNA biogenesis in Arabidopsis thaliana
Background:
MiRNAs are a class of endogenous small non-coding RNAs that predominantly mediate post-transcriptional gene silencing (PTGS). The intron-lariat spliceosome (ILS) complex is highly conserved among eukaryotes, and its disassembly marks the end of a canonical splicing cycle. But the regulation of miRNA biogenesis by spliceosome-associated proteins and the plant ILS complex remains limited and ambiguous.
Sampling:
Small RNA library: inflorescence tissues of three-week-old transgenic seedlings in Col-0 or the ilp1-1 mutant;
mRNA library: total RNA was isolated from 7-day-old seedlings grown under constant white light.
Sequencing Strategy:
1. TruSeq Small RNA Library Preparation Kit, SE50 using the Illumina Hiseq 2500
2. strand-specific mRNA library, 2 × 150-bp reads using the Illumina Hiseq X Ten platform
Conclusion:
This study shows that two conserved disassembly factors of the ILS complex, Increased Level of Polyploidy1-1D (ILP1) and NTC-Related protein 1(NTR1), positively regulate microRNA (miRNA) biogenesis by facilitating transcriptional elongation of MIRNA(MIR) genes in Arabidopsis thaliana(Figure1, 2). ILP1 and NTR1 forms a stable complex and co-regulates alternative splicing of more than a hundred genes across the Arabidopsis genome, including some primary transcripts of miRNAs (pri-miRNAs)(Figure3, 4). These results provide further insights into the regulatory role of spliceosomal machineries in the biogenesis of miRNAs.
Integrated miRNA-mRNA analysis reveals regulatory pathways underlying the curly fleece trait in Chinese tan sheep
Background:
Tan sheep is an indigenous Chinese breed well known for its beautiful curly fleece. One prominent breed characteristic of this sheep breed is that the degree of curliness differs markedly between lambs and adults, but the molecular mechanisms regulating the shift are still not well understood. In this study, we identified 49 differentially expressed (DE) microRNAs (miRNAs) between Tan sheep at the two stages through miRNA-seq, and combined the data with that in our earlier Suppression Subtractive Hybridization cDNA (SSH) library study to elucidate the mechanisms underlying curly fleece formation.
Sampling:
Skin tissue was collected from the shoulder of four female Chinese Tan sheep (two 1-month-old lambs and two 48-month-old adults)
Sequencing Strategy:
NEBNext® Multiplex Small RNA Library Prep Set for Illumina®, Illumina HiSeq 2500/2000 platform.
| miRNA | L_readcount | A_readcount | Log2 Fold Change | P-Value | P-Adj |
| oar-miR-148a | 67, 574.96753 | 231, 061.6487 | -1.7737 | 1.00E-09 | 0 |
| oar-miR-136 | 19.75893919 | 88.81995869 | -2.1684 | 6.98E-10 | 2.81E-09 |
| oar-miR-150 | 50.50740147 | 235.578046 | -2.2216 | 3.78E-11 | 4.18E-11 |
| oar-miR-29a | 867.6115945 | 5480.855957 | -2.6593 | 1.00E-09 | 0 |
| novel_459 | 0 | 20.61202625 | -5.3654 | 3.82E-06 | 1.82E-05 |
| KEGG Pathway | Count | P-Value | Corrected P-Value |
| Metabolic pathways | 180 | 0.894548594 | 0.984724863 |
| Pathways in cancer | 66 | 0.179111564 | 0. 939563595 |
| PI3-Akt signaling pathway | 64 | 0.39499336 | 0. 939563595 |
| HTLV-I-Infection | 50 | 0.192543289 | 0.895292925 |
| Phagosome | 45 | 0. 0017584833 | 0.480065813 |
| Protein processing in endoplasmic reticulum | 43 | 0.007929522 | 0.545550536 |
| Regulation of actin cytoskeleton | 43 | 0.245615216 | 0.939563595 |
| MAPK signaling pathway | 42 | 0.630365388 | 0.939563595 |
| Tuberculosis | 41 | 0.051840799 | 0.750257819 |
| Ras signaling pathway | 41 | 0.474634575 | 0.939563595 |
| Viral carcinogenesis | 39 | 0.270545221 | 0.947474735 |
| Transcriptional misregulation in cancer | 37 | 0.104993737 | 0.779793658 |
| Influenza A | 37 | 0.185182388 | 0.939563595 |
| Endocytosis | 36 | 0.500604613 | 0.957112583 |
| Epstein-Barr virus infection | 35 | 0.270987612 | 0.947474735 |
| Lysosome | 33 | 0.01255486 | 0.638411076 |
| MicroRNAs in cancer | 33 | 0.443228539 | 0.939563595 |
| Focal adhesion | 33 | 0.531854202 | 0.957112583 |
| cGMP-PKG signaling pathway | 31 | 0.425371479 | 0.939563595 |
| AMPK signaling pathway | 30 | 0.071269601 | 0.779793658 |
Conclusion:
This study explores the role of miRNAs in the curly fleece trait of Chinese Tan sheep. This study represents the comprehensive analysis of mRNA and miRNA in Tan sheep and offers detailed insight into the development of curly fleece as well as the potential mechanisms controlling curly hair formation in humans. The results provide important clues for elucidating the molecular mechanism underlying curly fleece and curly hair development.
Uncovering anthocyanin biosynthesis related microRNAs and their target genes by small RNA and degradome sequencing in tuberous roots of sweetpotato
Background:
Purple-fleshed sweetpotato (PFSP) is a desirable resource for functional food development because of the abundant anthocyanin accumulation in its tuberous roots. Some studies have shown that the expression regulation mediated by miRNA plays an important role in anthocyanin biosynthesis in plants. However, few miRNAs and their corresponding functions related to anthocyanin biosynthesis in tuberous roots of sweetpotato have been known.
Sampling:
Total RNA extracted from the tuberous roots of WFSP (Xushu-18) and PFSP (Xuzishu-3)
Sequencing Strategy:
NEBNext® Multiplex Small RNA library Prep Set for Illumina®, sequenced on an Illumina Hiseq 2000 platform
Conclusion:
The results represented a comprehensive expression profiling of miRNAs related to anthocyanin accumulation in sweetpotato and provided important clues for understanding the regulatory network of anthocyanin biosynthesis mediated by miRNA in tuberous crops. Our findings provided comprehensive information for anthocyanin-specific miRNAs and their targets, as well as a starting point for mechanism investigation of miRNAs in anthocyanin biosynthesis in sweetpotato.
sRNA Length Distribution
sRNA Classification-Repeat Sequence
miRNA-structure
miRNA-base bias
TPM Boxplot
TPM Density Distribution
Hierarchical Cluster
