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Updated: Jun 15, 2025

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
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Improved functions for nonlinear sequence comparison using SEEKR.

Shuang Li1,2,3, Quinn E Eberhard1,2,3,4, Luke Ni5

  • 1Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina 27599, USA.

RNA (New York, N.Y.)
|August 26, 2024
PubMed
Summary
This summary is machine-generated.

SEquence Evaluation through k-mer Representation (SEEKR) now estimates statistical significance for nucleic acid sequence similarity. New SEEKR functions aid in identifying functional RNA elements and understanding RNA-seq data.

Keywords:
XISTeCLIPk-merlncRNAsequence comparison

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Sequence comparison is crucial for understanding nucleic acid function.
  • Nonlinear similarity quantification requires advanced methods beyond traditional alignment.
  • Long non-coding RNAs (lncRNAs) present unique challenges in sequence analysis.

Purpose of the Study:

  • To introduce enhanced functionalities for the SEEKR method, enabling statistical significance estimation and visualization of k-mer similarities.
  • To demonstrate the application of SEEKR in identifying specific lncRNA features and functional domains.
  • To provide guidelines for utilizing SEEKR in lncRNA research, including conservation studies and annotation validation.

Main Methods:

  • Development of new statistical functions within SEEKR for P-value estimation.
  • Implementation of visualization tools for k-mer similarity analysis.
  • Application of SEEKR to identify chromatin-enriched lncRNAs with XIST-like features.
  • Analysis of lncRNA fragments to predict RNA-protein interaction domains.
  • Utilizing RNA-seq read density visualization for lncRNA annotation support.

Main Results:

  • SEEKR can now provide statistically significant measures of sequence similarity.
  • Novel chromatin-enriched lncRNAs with XIST-like sequence features were identified.
  • Potential RNA-protein interaction domains within lncRNA fragments were predicted.
  • SEEKR's utility in assessing lncRNA conservation and validating annotations was demonstrated.

Conclusions:

  • The enhanced SEEKR method offers robust statistical assessment of nucleic acid sequence similarity.
  • SEEKR facilitates the discovery and functional characterization of lncRNAs.
  • Best practices for integrating SEEKR with RNA-seq data analysis improve lncRNA research reliability.