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Ziyani, C.

Publications and source records attributed to Ziyani, C..

2 recordsLinked to original sources

Widespread enhancer co-activity identified by multimodal single cell analysis

Non-coding regulatory elements such as enhancers are key in controlling the cell type-specificity and spatio-temporal expression of genes. To drive stable and precise gene transcription that is robust to genetic variation and environmental stress, genes are often targeted by multiple enhancers with redundant action. However, it is unknown whether enhancers targeting the same gene display simultaneous activity or whether some enhancer combinations are more often co-active than others. Here, we take advantage of the recent developments in single cell technology that permit assessing chromatin status (scATAC-seq) and gene expression (scRNA-seq) in the same single cells to link gene expression to the activity of multiple enhancers. Measuring activity patterns across 24,844 human lymphoblastoid single cells, we found that the majority of enhancers associated with the same gene display significant correlation in their chromatin profiles. For 6944 expressed genes associated with enhancers, we identified 89,885 significant enhancer-enhancer associations between nearby enhancers. We found that associated enhancers share similar transcription factor binding profiles and that gene essentiality is linked with higher enhancer co-activity. Our extensive enhancer co-activity maps can be used to pinpoint combinations of enhancers relevant in gene expression regulation and allow us to better predict the effect of genetic variation falling in non-coding regions.

genomics↗

Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis

Most human genes are co-expressed with a nearby gene. Yet, previous studies only reported this extensive local gene co-expression using bulk RNA-seq. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover thousands of co-expressed genes in two cell types and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes - but not the majority - are composed of functionally-related genes and (iii) provide evidence that these genes are transcribed synchronously and their co-expression is maintained up to the protein level. Finally, we identify gene-enhancer associations using multimodal single cell data, which reveal that >95% of co-expressed gene pairs share regulatory elements. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes.

genomics↗