Seminar: Deciphering the cis-regulatory logic of plant genomes at single-cell resolution
Date/Time: | Tuesday, 30 Jan 2024 - Tuesday, 30 Jan 2024 |
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Location: | 1414 Molecular Biology |
Cost: | Free |
Contact: | Danise Jones |
Phone: | 515-294-2687 |
Channel: | Research |
Categories: | Lectures |
Actions: | Download iCal/vCal | Email Reminder |
Significant progress has been made in recent years in plant genome assembly and gene annotation. However, the systematic identification of plant cis-regulatory DNA elements remains a challenge. A comprehensive and well-curated data set of plant cis-regulatory DNA elements is instrumental to understanding transcriptional regulation during development and/or in response to external stimuli. In addition, cis-regulatory DNA elements are also hotspots for genetic variations underlying key agronomical traits. We have discovered a plant-specific chromatin signature that is indicative of cis-regulatory DNA elements. We are using this newly identified signature in combination with high-throughput validation assays to systematically identify, analyze and functionally validate cis-regulatory elements in important crop species. In parallel, we are discovering cell-type-specific cis-regulatory elements using single-cell ATAC-seq (scATAC-seq) across a range of crop species. Data from maize revealed that cell-type-specific cis-regulatory elements are sequenced constrained, yet the sequence variation that does occur is important for expression and phenotypic variation. We discovered breeders have been unknowingly selecting genetic variants within cis-regulatory elements in modern maize breeding schemes. We also learned that scATAC-seq data is useful for predicting presence/absence expression of genes and used this to map transcription factors and their binding sites in a cell-type-specific manner. In this presentation I will discuss how we are using single-cell genomics to map the genetic basis for gene expression and chromatin accessible variation across the maize germplasm and present future goals to decode the cis-regulatory landscape of crop genomes using single-cell genomics through time, across environments and by genotype.