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Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
Published on: October 31, 2025
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Comparative analysis of the transcriptome across distant species.
Mark B Gerstein1, Joel Rozowsky2, Koon-Kiu Yan2
11] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [3] Department of Computer Science, Yale University, 51 Prospect Street, New Haven, Connecticut 06511, USA [4] [5].
Nature
|August 29, 2014
Summary
Comparing transcriptomes across species reveals fundamental biological principles. This study identified shared gene expression patterns and a universal model for predicting gene activity from chromatin data in humans, worms, and flies.
Area of Science:
- Comparative genomics
- Transcriptomics
- Developmental biology
Background:
- The transcriptome provides a snapshot of genome activity.
- Cross-species transcriptome comparisons can uncover fundamental biological principles.
- Previous comparisons were limited within species or phyla.
Purpose of the Study:
- To identify conserved features in transcriptomes across distant animal species (human, worm, fly).
- To develop a universal model for predicting gene expression from chromatin data.
- To compare non-coding transcription levels across species.
Main Methods:
- RNA-sequencing data generation and uniform processing by ENCODE and modENCODE consortia.
- Comparative analysis of transcriptomes across human, worm, and fly.
- Development and application of a predictive model using chromatin features.
Main Results:
- Discovery of shared co-expression modules, many enriched in developmental genes, across metazoan phyla.
- Identification of a novel developmental stage alignment between worm pupae and fly embryos.
- Quantification of similar non-canonical transcription levels per base pair across species.
- Demonstration that gene expression levels can be predicted from promoter chromatin features using an organism-independent model.
Conclusions:
- Transcriptome comparisons across diverse species reveal ancient, conserved features.
- Developmental processes show conserved regulatory principles across animals.
- A universal model can predict gene expression from chromatin data across species, highlighting conserved regulatory mechanisms.
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