Nature PlantsPlant BiologyPeer-reviewed journal article
Transcription factor binding site divergence across maize inbred lines drives transcriptional and phenotypic variation
Mary GalliiD, Zongliang CheniD, Tara GhandouriD, Amina ChaudhryiD, Jason GregoryiD, Fan Feng, Miaomiao LiiD, Nathaniel SchleifiD, Xuan ZhangiD, Yinxin DongiD, Gaoyuan SongiD, Justin W. WalleyiD, George S. ChuckiD, Clinton WhippleiD, Heidi F. KaeppleriD, Shao‐shan Carol HuangiD, Andrea GallavottiiD
Abstract
Regulatory elements are important constituents of plant genomes that have shaped ancient and modern crops. Their identification, function, and diversity in crop genomes however are poorly characterized, thus limiting our ability to harness their power for further agricultural advances using induced or natural variation. Here, we use DNA affinity purification-sequencing (DAP-seq) to map transcription factor (TF) binding events for 200 maize TFs belonging to 30 distinct families and heterodimer pairs in two distinct inbred lines historically used for maize hybrid plant production, providing empirical binding site annotation for 5.3% of the maize genome. TF binding site comparison in B73 and Mo17 inbreds reveals widespread differences, driven largely by structural variation, that correlate with gene expression changes. TF binding site presence-absence variation helps clarify complex QTL such as vgt1, an important determinant of maize flowering time, and DICE, a distal enhancer involved in herbivore resistance. Modification of TF binding regions via CRISPR-Cas9 mediated editing alters target gene expression and phenotype. Our functional catalog of maize TF binding events enables collective and comparative TF binding analysis, and highlights its value for agricultural improvement.
- organism: zebrafish
- assay: ChIP-seq
- research focus: gene regulatory network inference
- research focus: variant calling
- research focus: variant effect prediction
- approach: experimental assay
- approach: wet-lab / biochemical assay
- Citations
- 31
- FWCI
- 13.80
- Field percentile
- top 1%
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