LncRNA Microarray Service

Partial results are shown below:

1. What challenges are associated with detecting lncRNAs compared to mRNAs?

The detection of long non-coding RNAs (lncRNAs) presents distinct challenges relative to messenger RNAs (mRNAs), primarily due to their inherently lower expression levels and pronounced tissue specificity. The unique attributes of lncRNAs, such as their low abundance and extensive isoform diversity, introduce additional complexity to their analysis. To effectively surmount these obstacles, our microarrays have been meticulously designed to ensure the precise detection and quantification of lncRNAs, despite their intricate nature.

2. How does the sensitivity of lncRNA microarrays compare to RNA sequencing?

In terms of sensitivity, lncRNA microarrays exhibit superior performance in detecting low-abundance lncRNAs when compared to RNA sequencing. RNA sequencing can encounter accuracy issues, particularly arising from high error rates and the inherently low expression levels of these transcripts. In contrast, our microarrays provide reliable measurements with minimal susceptibility to variations caused by low transcript abundance, thereby enhancing the overall sensitivity of detection.

3. Can lncRNA microarrays detect different transcript isoforms?

Absolutely, our lncRNA microarrays are adept at differentiating and detecting various isoforms. Unlike mRNAs, lncRNAs are known to generate multiple isoforms, each with uniquely distinct biological roles. Our advanced microarray design ensures the accurate identification and quantification of these diverse isoforms, thereby offering a comprehensive understanding of lncRNA functionality.

4. How does the accuracy of lncRNA quantification in microarrays compare to sequencing methods?

When it comes to the quantification of low-abundance lncRNAs, microarray technology offers greater accuracy compared to sequencing methods, which are often hampered by higher error rates and coverage limitations. Our microarrays are rigorously engineered to mitigate these issues, resulting in the provision of more reliable and extensive data that significantly enhances the precision of lncRNA quantification.

5. What custom solutions are available for lncRNA microarray analysis?

We offer tailored lncRNA microarray solutions that cater to specific research needs. Whether your requirements involve standard arrays or innovative designs, our customizable options ensure that our services are precisely aligned with your research objectives. This flexibility facilitates the acquisition of targeted and comprehensive genomic insights, thereby advancing your scientific endeavors.

Integrated Analysis of lncRNA and mRNA Expression Profiles Indicates Age-Related Changes in Meniscus

Journal: Frontiers in cell and developmental biology
Impact Factor: 5.206
Published: 10 March 2022

Background

The meniscus, crucial for knee function, deteriorates with age, heightening osteoarthritis risk due to changes like collagen thickening. Long non-coding RNAs (lncRNAs) are important in tissue aging and may contribute to meniscus degeneration. To explore this, the study analyzed lncRNA and mRNA expression profiles in young and aging menisci using microarray analysis, followed by bioinformatics to identify key molecules and pathways involved in age-related meniscus changes.

Materials & Methods

Results

The study used Arraystar Human lncRNA and mRNA Array to compare meniscus tissues from young and aging groups (n = 4/group). It identified 1608 differentially expressed lncRNAs and 1809 differentially expressed mRNAs. Expression patterns were visualized with volcano plots and hierarchical clustering.

FIGURE 1. Identifification of DE lncRNAs and mRNAs.

GO and pathway analyses of 1809 differentially expressed mRNAs highlighted key pathways involved in cartilage damage, including TGF-beta, Wnt, and PI3K-Akt. The study identified 18 mRNAs significantly altered, with notable downregulation of FGF6 and PPP2R5C.

FIGURE 2. Functional Enrichment Analysis of DE mRNAs.

A ceRNA network analysis using 19 DE mRNAs and 46 DE lncRNAs identified 98 nodes and 229 edges. The network, constructed with Cytoscape, highlighted lncRNA POC1B-AS1, which was further examined for its miRNA interactions and target genes in a detailed subnetwork.

FIGURE 3. CeRNA Analysis.

Conclusion

This study found significant changes in lncRNA and mRNA expression in the aging meniscus, including decreased MMP-2 and COL1A2 levels. Key pathways like Hippo and TGF-beta are involved in meniscal degeneration. Abnormal lncRNA expressions suggest new therapeutic targets for treating meniscal degeneration.

Reference

1. Ai LY, Du MZ, Chen YR, et al. Integrated analysis of lncRNA and mRNA expression profiles indicates age-related changes in meniscus. Frontiers in cell and developmental biology. 2022, 10:844555.