dbCNS: A New Database for Conserved Noncoding Sequences

An epigenetic toolbox for conservation biologists

Ongoing climatic shifts and increasing anthropogenic pressures demand an efficient delineation of conservation units and accurate predictions of populations' resilience and adaptive potential. Molecular tools involving DNA sequencing are nowadays routinely used for these purposes. Yet, most of the existing tools focusing on sequence-level information have shortcomings in detecting signals of short-term ecological relevance. Epigenetic modifications carry valuable information to better link individuals, populations, and species to their environment. Here, we discuss a series of epigenetic monitoring tools that can be directly applied to various conservation contexts, complementing already existing molecular monitoring frameworks. Focusing on DNA sequence-based methods (e.g. DNA methylation, for which the applications are readily available), we demonstrate how (a) the identification of epi-biomarkers associated with age or infection can facilitate the determination of an individual's health status in wild populations; (b) whole epigenome analyses can identify signatures of selection linked to environmental conditions and facilitate estimating the adaptive potential of populations; and (c) epi-eDNA (epigenetic environmental DNA), an epigenetic-based conservation tool, presents a non-invasive sampling method to monitor biological information beyond the mere presence of individuals. Overall, our framework refines conservation strategies, ensuring a comprehensive understanding of species' adaptive potential and persistence on ecologically relevant timescales.

PlantPAN 4.0: updated database for identifying conserved non-coding sequences and exploring dynamic transcriptional regulation in plant promoters

PlantPAN 4.0 (http://PlantPAN.itps.ncku.edu.tw/) is an integrative resource for constructing transcriptional regulatory networks for diverse plant species. In this release, the gene annotation and promoter sequences were expanded to cover 115 species. PlantPAN 4.0 can help users characterize the evolutionary differences and similarities among cis-regulatory elements; furthermore, this system can now help in identification of conserved non-coding sequences among homologous genes. The updated transcription factor binding site repository contains 3428 nonredundant matrices for 18305 transcription factors; this expansion helps in exploration of combinational and nucleotide variants of cis-regulatory elements in conserved non-coding sequences. Additionally, the genomic landscapes of regulatory factors were manually updated, and ChIP-seq data sets derived from a single-cell green alga (Chlamydomonas reinhardtii) were added. Furthermore, the statistical review and graphical analysis components were improved to offer intelligible information through ChIP-seq data analysis. These improvements included easy-to-read experimental condition clusters, searchable gene-centered interfaces for the identification of promoter regions' binding preferences by considering experimental condition clusters and peak visualization for all regulatory factors, and the 20 most significantly enriched gene ontology functions for regulatory factors. Thus, PlantPAN 4.0 can effectively reconstruct gene regulatory networks and help compare genomic cis-regulatory elements across plant species and experiments.

CNEReg Interprets Ruminant-specific Conserved Non-coding Elements by Developmental Gene Regulatory Network

The genetic information coded in DNA leads to trait innovation via a gene regulatory network (GRN) in development. Here, we developed a conserved non-coding element interpretation method to integrate multi-omics data into gene regulatory network (CNEReg) to investigate the ruminant multi-chambered stomach innovation. We generated paired expression and chromatin accessibility data during rumen and esophagus development in sheep, and revealed 1601 active ruminant-specific conserved non-coding elements (active-RSCNEs). To interpret the function of these active-RSCNEs, we defined toolkit transcription factors (TTFs) and modeled their regulation on rumen-specific genes via batteries of active-RSCNEs during development. Our developmental GRN revealed 18 TTFs and 313 active-RSCNEs regulating 7 rumen functional modules. Notably, 6 TTFs (OTX1, SOX21, HOXC8, SOX2, TP63, and PPARG), as well as 16 active-RSCNEs, functionally distinguished the rumen from the esophagus. Our study provides a systematic approach to understanding how gene regulation evolves and shapes complex traits by putting evo-devo concepts into practice with developmental multi-omics data.