CNEwrap: a scalable toolkit with a novel algorithm for large-scale genome-wide accelerated conserved non-coding...

Area of Science:

• Genomics
• Bioinformatics
• Evolutionary Biology

Background:

• Conserved non-coding elements (CNEs) are crucial for gene regulation in eukaryotes.
• Identifying CNEs and their variations across genomes is challenging, limiting functional understanding.

Purpose of the Study:

• To develop a bioinformatics toolkit (CNEwrap) for efficient, large-scale CNE discovery and variation analysis.
• To introduce a novel algorithm (EvoAcc) for assessing accelerated evolution in CNEs.

Main Methods:

• CNEwrap integrates whole-genome alignment, CNE scanning, and accelerated evolution analysis.
• The EvoAcc algorithm uses nucleotide variation and phylogenetic data to detect accelerated evolution.
• Performance was validated using simulated datasets and functional genomic fragments in mammals.

Main Results:

• CNEwrap enables high-throughput, multi-species CNE discovery and comparative analysis.
• EvoAcc outperforms existing methods (PhyloAcc, PhyloP, ForwardGenomics) in simulated accelerated evolution scenarios.
• EvoAcc shows comparable or superior sensitivity to other algorithms in detecting accelerated segments and InDel mutations in mammals.

Conclusions:

• CNEwrap provides a scalable framework for uncovering CNEs and their evolutionary dynamics.
• EvoAcc enhances the analysis of conserved regulatory architectures by improving the detection of evolutionary changes.
• This toolkit deepens insights into eukaryotic gene regulation and evolution.