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Background <p>Cis-regulatory elements constitute a fundamental layer of gene regulation, yet their computational identification has largely relied on transcription factor (TF)-centric frameworks that assume genome-wide background normalization and explicit TF binding models. While effective at the genome scale, such assumptions are less suitable for gene-centered analyses, where local sequence composition defines the relevant regulatory context.</p> Results <p>Here, we introduce a TF-independent observational framework for the gene-centered identification of cis-regulatory islands (GCIC), designed to characterize regulatory sequence organization based on local enrichment and diversity of short cis-regulatory sequence words derived from curated plant regulatory elements. Cis-regulatory islands identified by the GCIC framework (GCIC islands) are defined through the spatial overlap of independently enriched motif families, without relying on TF identity or genome-wide normalization. Application of the GCIC framework to the <i>DROOPING LEAF</i> (<i>DL</i>) locus in rice reveals discrete cis-regulatory islands, including one coinciding with a known intronic regulatory region, and highlights spatial patterns distinct from PWM-based motif scanning and clustering approaches. Genome-wide analysis shows that GCIC islands are broadly distributed but exhibit heterogeneous motif-family usage, with gene-level diversity and island-level reuse of motif-family combinations.</p> Conclusions <p>We demonstrate that cis-regulatory organization can be interpreted as a gene-centered property of sequence vocabulary usage within an observational framework. The GCIC framework provides a complementary representation of regulatory landscapes for gene-centered analyses, enabling locus-level interpretation of regulatory sequence organization beyond predictive inference.</p>

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Gene-centered identification of cis-regulatory islands highlights regulatory landscapes complementary to motif-centric approaches

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  • 发表日期：

    2026年4月23日

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  • Yoshihiro Ohmori

摘要

Background

Cis-regulatory elements constitute a fundamental layer of gene regulation, yet their computational identification has largely relied on transcription factor (TF)-centric frameworks that assume genome-wide background normalization and explicit TF binding models. While effective at the genome scale, such assumptions are less suitable for gene-centered analyses, where local sequence composition defines the relevant regulatory context.

Results

Here, we introduce a TF-independent observational framework for the gene-centered identification of cis-regulatory islands (GCIC), designed to characterize regulatory sequence organization based on local enrichment and diversity of short cis-regulatory sequence words derived from curated plant regulatory elements. Cis-regulatory islands identified by the GCIC framework (GCIC islands) are defined through the spatial overlap of independently enriched motif families, without relying on TF identity or genome-wide normalization. Application of the GCIC framework to the DROOPING LEAF (DL) locus in rice reveals discrete cis-regulatory islands, including one coinciding with a known intronic regulatory region, and highlights spatial patterns distinct from PWM-based motif scanning and clustering approaches. Genome-wide analysis shows that GCIC islands are broadly distributed but exhibit heterogeneous motif-family usage, with gene-level diversity and island-level reuse of motif-family combinations.

Conclusions

We demonstrate that cis-regulatory organization can be interpreted as a gene-centered property of sequence vocabulary usage within an observational framework. The GCIC framework provides a complementary representation of regulatory landscapes for gene-centered analyses, enabling locus-level interpretation of regulatory sequence organization beyond predictive inference.