Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
[Preprint]. 2025 May 11:2025.05.06.652526.
doi: 10.1101/2025.05.06.652526.

Transcription Factor (TF) validation using Dam-IT simultaneously captures genome-wide TF-DNA binding, direct gene regulation, and chromatin accessibility in plant cells

Affiliations

Transcription Factor (TF) validation using Dam-IT simultaneously captures genome-wide TF-DNA binding, direct gene regulation, and chromatin accessibility in plant cells

Will E Hinckley et al. bioRxiv. .

Abstract

Transcription Factors (TFs) govern vast networks of gene regulation. However, TF-DNA binding and TF-gene regulation datasets are typically measured separately due to experimental constraints, making it challenging to disentangle true biological relationships from batch effects. To fill this gap, we developed DamID-seq Incorporating Transcriptomics (Dam-IT), which simultaneously captures TF-DNA binding, direct TF-gene regulation, and chromatin accessibility in the same batch of cells. Dam-IT uses a transient cell-based TF-target validation system that is scalable and flexible to many experimental designs. As proof of concept, we used Dam-IT to reveal that bZIP1 directly regulates genes by binding to DNA regions of relatively low chromatin accessibility, supporting a "Hit-and-Run" mechanism of transcription.

Keywords: DNA binding; DamID; chromatin accessibility; gene regulation; transcription factor.

PubMed Disclaimer

Figures

Figure 1:
Figure 1:. Dam-IT simultaneously captures TF-DNA binding, direct TF-gene regulation, and chromatin accessibility from the same batch of cells.
1A - Dam-IT is a plant cell-based TF-perturbation method in which DAM:GR:TF fusion proteins are transiently expressed in plant protoplasts. DEX treatment triggers nuclear import of GR-TF fusion proteins, while simultaneous CHX treatment inhibits translation of secondary downstream TFs. Comparison to Empty Vector (DAM-GR-EV), allows the measurement of genome-wide direct gene regulatory activity of said TF., The Dam-IT protocol calls for FACS sorting of TF-transfected cells, and RNA and DNA are simultaneously extracted from the same sample of cells using the Qiagen AllPrep Micro kit. DNA and RNA fractions are then used for TARGET RNA-seq or DamID-seq as previously described (see Methods). 1B - Dam-IT uncovered bZIP1 and NLP7 target genes that are TF-bound and directly TF-regulated in the same sample of cells. Genes are bound in at least one DamIT DNA binding replicate. Volcano plots show Log2FC DAM-GR-TF/DAM-GR-EV. Genes within 1,000 bp of DNA-binding peaks were intersected with TF-regulated genes. 1C - The DAM-GR-EV (no TF) control from Dam-IT acts as a proxy for chromatin accessibility. Left: DAM-GR-EV DNA binding plotted over all expressed genes in the same cells, ordered by increasing gene expression. Right: DAM-GR-EV signal was plotted over Arabidopsis root ATAC-seq peaks from Farmer et al 2021, Molecular Plant.
Figure 2:
Figure 2:. Dam-IT uncovers bZIP1 binding sites in regions of low chromatin accessibility associated with bZIP1 directly regulated genes
2A - bZIP1 DNA-binding peaks (q<1e-08) are significantly enriched for the bZIP1 DNA-binding motif. The e-value was calculated using SEA from MEME Suite Tools on the union of all bZIP1 peaks. Gene Ontology enrichment was calculated for the bZIP1 induced or repressed DEGs. 2B - bZIP1 DEGs were ordered by DAM-GR-EV binding enrichment, where genes at the top of the heatmap have the highest DAM-GR-EV signal. This analysis found regions of DNA not accessible to DAM-GR-EV alone that were bound by DAM-GR-bZIP1 (gold box).

Similar articles

References

    1. O'Malley RC, Huang SC, Song L, Lewsey MG, Bartlett A, Nery JR, Galli M, Gallavotti A, Ecker JR. Cistrome and Epicistrome Features Shape the Regulatory DNA Landscape. Cell. 2016. May 19;165(5):1280–1292. doi: 10.1016/j.cell.2016.04.038. Erratum in: Cell. 2016 Sep 8;166(6):1598. doi: 10.1016/j.cell.2016.08.063. - DOI - DOI - PMC - PubMed
    1. Song L, Huang SC, Wise A, Castanon R, Nery JR, Chen H, Watanabe M, Thomas J, Bar-Joseph Z, Ecker JR. A transcription factor hierarchy defines an environmental stress response network. Science. 2016. Nov 4;354(6312):aag1550. doi: 10.1126/science.aag1550. - DOI - PMC - PubMed
    1. Tao XY, Guan XY, Hong GJ, He YQ, Li SJ, Feng SL, Wang J, Chen G, Xu F, Wang JW, Xu SC. Biotinylated Tn5 transposase-mediated CUT&Tag efficiently profiles transcription factor-DNA interactions in plants. Plant Biotechnol J. 2023. Jun;21(6):1191–1205. doi: 10.1111/pbi.14029. Epub 2023 Mar 2. - DOI - PMC - PubMed
    1. Van Steensel B, Henikoff S. Identification of in vivo DNA targets of chromatin proteins using tethered dam methyltransferase. Nat Biotechnol. 2000. Apr;18(4):424–8. doi: 10.1038/74487. - DOI - PubMed
    1. Gutierrez-Triana JA, Mateo JL, Ibberson D, Ryu S, Wittbrodt J. iDamIDseq and iDEAR: an improved method and computational pipeline to profile chromatin-binding proteins. Development. 2016. Nov 15;143(22):4272–4278. doi: 10.1242/dev.139261. Epub 2016 Oct 5. - DOI - PMC - PubMed

Publication types