scholarly journals PlantRegMap: charting functional regulatory maps in plants

Author(s):  
Feng Tian ◽  
De-Chang Yang ◽  
Yu-Qi Meng ◽  
Jinpu Jin ◽  
Ge Gao

Abstract With the goal of charting plant transcriptional regulatory maps (i.e. transcription factors (TFs), cis-elements and interactions between them), we have upgraded the TF-centred database PlantTFDB (http://planttfdb.cbi.pku.edu.cn/) to a plant regulatory data and analysis platform PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) over the past three years. In this version, we updated the annotations for the previously collected TFs and set up a new section, ‘extended TF repertoires’ (TFext), to allow users prompt access to the TF repertoires of newly sequenced species. In addition to our regular TF updates, we are dedicated to updating the data on cis-elements and functional interactions between TFs and cis-elements. We established genome-wide conservation landscapes for 63 representative plants and then developed an algorithm, FunTFBS, to screen for functional regulatory elements and interactions by coupling the base-varied binding affinities of TFs with the evolutionary footprints on their binding sites. Using the FunTFBS algorithm and the conservation landscapes, we further identified over 20 million functional TF binding sites (TFBSs) and two million functional interactions for 21 346 TFs, charting the functional regulatory maps of these 63 plants. These resources are publicly available at PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) and a cloud-based mirror (http://plantregmap.gao-lab.org/), providing the plant research community with valuable resources for decoding plant transcriptional regulatory systems.

2018 ◽  
Author(s):  
Feng Tian ◽  
De-Chang Yang ◽  
Yu-Qi Meng ◽  
Jinpu Jin ◽  
Ge Gao

AbstractSystematic identification of functional transcriptional regulatory interactions is essential for understanding regulatory systems. Here, we firstly established genome-wide conservation landscapes for 63 green plants of seven lineages and then developed an algorithm FunTFBS to screen for functional regulatory elements and interactions by coupling base-varied binding affinities of transcription factors with the evolutionary footprints on their binding sites. Using the FunTFBS and the conservation landscapes, we further identified over two million functional interactions for 21,346 TFs, charting functional regulatory maps of these 63 plants. Our work provides plant community with valuable resources to decode plant transcriptional regulatory system and genome sequences.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sebastian Carrasco Pro ◽  
Katia Bulekova ◽  
Brian Gregor ◽  
Adam Labadorf ◽  
Juan Ignacio Fuxman Bass

Abstract Single nucleotide variants (SNVs) located in transcriptional regulatory regions can result in gene expression changes that lead to adaptive or detrimental phenotypic outcomes. Here, we predict gain or loss of binding sites for 741 transcription factors (TFs) across the human genome. We calculated ‘gainability’ and ‘disruptability’ scores for each TF that represent the likelihood of binding sites being created or disrupted, respectively. We found that functional cis-eQTL SNVs are more likely to alter TF binding sites than rare SNVs in the human population. In addition, we show that cancer somatic mutations have different effects on TF binding sites from different TF families on a cancer-type basis. Finally, we discuss the relationship between these results and cancer mutational signatures. Altogether, we provide a blueprint to study the impact of SNVs derived from genetic variation or disease association on TF binding to gene regulatory regions.


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Lin Zhang ◽  
Zhiqiang Song ◽  
Fangfang Li ◽  
Xixi Li ◽  
Haikun Ji ◽  
...  

Abstract Background Drought stress is one of the major abiotic stresses that affects plant growth and productivity. The GAPCp genes play important roles in drought stress tolerance in multiple species. The aim of this experiment was to identify the core cis-regulatory elements that may respond to drought stress in the GAPCp2 and GAPCp3 promoter sequences. Results In this study, the promoters of GAPCp2 and GAPCp3 were cloned. The promoter activities were significantly improved under abiotic stress via regulation of Rluc reporter gene expression, while promoter sequence analysis indicated that these fragments were not almost identical. In transgenic Arabidopsis with the expression of the GUS reporter gene under the control of one of these promoters, the activities of GUS were strong in almost all tissues except the seeds, and the activities were induced after abiotic stress. The yeast one-hybrid system and EMSA demonstrated that TaMYB bound TaGAPCp2P/3P. By analyzing different 5′ deletion mutants of these promoters, it was determined that TaGAPCp2P (− 1312~ − 528) and TaGAPCp3P (− 2049~ − 610), including the MYB binding site, contained enhancer elements that increased gene expression levels under drought stress. We used an effector and a reporter to co-transform tobacco and found that TaMYB interacted with the specific MYB binding sites of TaGAPCp2P (− 1197~ − 635) and TaGAPCp3P (− 1456~ − 1144 and − 718~ − 610) in plant cells. Then, the Y1H system and EMSA assay demonstrated that these MYB binding sites in TaGAPCp2P (− 1135 and − 985) and TaGAPCp3P (− 1414 and − 665) were the target cis-elements of TaMYB. The deletion of the specific MYB binding sites in the promoter fragments significantly restrained the drought response, and these results confirmed that these MYB binding sites (AACTAAA/C) play vital roles in improving the transcription levels under drought stress. The results of qRT-PCR in wheat protoplasts transiently overexpressing TaMYB indicated that the expression of TaGAPCp2/3 induced by abiotic stress was upregulated by TaMYB. Conclusion The MYB binding sites (AACTAAA/C) in TaGAPCp2P/3P were identified as the key cis-elements for responding to drought stress and were bound by the transcription factor TaMYB.


Genes ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 209 ◽  
Author(s):  
Elizaveta Radion ◽  
Olesya Sokolova ◽  
Sergei Ryazansky ◽  
Pavel Komarov ◽  
Yuri Abramov ◽  
...  

Piwi-interacting RNAs (piRNAs) control transposable element (TE) activity in the germline. piRNAs are produced from single-stranded precursors transcribed from distinct genomic loci, enriched by TE fragments and termed piRNA clusters. The specific chromatin organization and transcriptional regulation of Drosophila germline-specific piRNA clusters ensure transcription and processing of piRNA precursors. TEs harbour various regulatory elements that could affect piRNA cluster integrity. One of such elements is the suppressor-of-hairy-wing (Su(Hw))-mediated insulator, which is harboured in the retrotransposon gypsy. To understand how insulators contribute to piRNA cluster activity, we studied the effects of transgenes containing gypsy insulators on local organization of endogenous piRNA clusters. We show that transgene insertions interfere with piRNA precursor transcription, small RNA production and the formation of piRNA cluster-specific chromatin, a hallmark of which is Rhino, the germline homolog of the heterochromatin protein 1 (HP1). The mutations of Su(Hw) restored the integrity of piRNA clusters in transgenic strains. Surprisingly, Su(Hw) depletion enhanced the production of piRNAs by the domesticated telomeric retrotransposon TART, indicating that Su(Hw)-dependent elements protect TART transcripts from piRNA processing machinery in telomeres. A genome-wide analysis revealed that Su(Hw)-binding sites are depleted in endogenous germline piRNA clusters, suggesting that their functional integrity is under strict evolutionary constraints.


PLoS Genetics ◽  
2021 ◽  
Vol 17 (8) ◽  
pp. e1009689
Author(s):  
Savannah D. Savadel ◽  
Thomas Hartwig ◽  
Zachary M. Turpin ◽  
Daniel L. Vera ◽  
Pei-Yau Lung ◽  
...  

Elucidating the transcriptional regulatory networks that underlie growth and development requires robust ways to define the complete set of transcription factor (TF) binding sites. Although TF-binding sites are known to be generally located within accessible chromatin regions (ACRs), pinpointing these DNA regulatory elements globally remains challenging. Current approaches primarily identify binding sites for a single TF (e.g. ChIP-seq), or globally detect ACRs but lack the resolution to consistently define TF-binding sites (e.g. DNAse-seq, ATAC-seq). To address this challenge, we developed MNase-defined cistrome-Occupancy Analysis (MOA-seq), a high-resolution (< 30 bp), high-throughput, and genome-wide strategy to globally identify putative TF-binding sites within ACRs. We used MOA-seq on developing maize ears as a proof of concept, able to define a cistrome of 145,000 MOA footprints (MFs). While a substantial majority (76%) of the known ATAC-seq ACRs intersected with the MFs, only a minority of MFs overlapped with the ATAC peaks, indicating that the majority of MFs were novel and not detected by ATAC-seq. MFs were associated with promoters and significantly enriched for TF-binding and long-range chromatin interaction sites, including for the well-characterized FASCIATED EAR4, KNOTTED1, and TEOSINTE BRANCHED1. Importantly, the MOA-seq strategy improved the spatial resolution of TF-binding prediction and allowed us to identify 215 motif families collectively distributed over more than 100,000 non-overlapping, putatively-occupied binding sites across the genome. Our study presents a simple, efficient, and high-resolution approach to identify putative TF footprints and binding motifs genome-wide, to ultimately define a native cistrome atlas.


2018 ◽  
Author(s):  
Xinchen Wang ◽  
David B. Goldstein

AbstractNon-coding transcriptional regulatory elements are critical for controlling the spatiotemporal expression of genes. Here, we demonstrate that the number of bases in enhancers linked to a gene reflects its disease pathogenicity. Moreover, genes with redundant enhancer domains are depleted of cis-acting genetic variants that disrupt gene expression, and are buffered against the effects of disruptive non-coding mutations. Our results demonstrate that dosage-sensitive genes have evolved robustness to the disruptive effects of genetic variation by expanding their regulatory domains. This resolves a puzzle in the genetic literature about why disease genes are depleted of cis-eQTLs, suggesting that eQTL information may implicate the wrong genes at genome-wide association study loci, and establishes a framework for identifying non-coding regulatory variation with phenotypic consequences.


Author(s):  
Hidenori Nishihara

Abstract Acquisition of cis-elements is a major driving force for rewiring a gene regulatory network. Several kinds of transposable elements (TEs), mostly retrotransposons that propagate via a copy-and-paste mechanism, are known to possess transcription factor binding motifs and have provided source sequences for enhancers/promoters. However, it remains largely unknown whether retrotransposons have spread the binding sites of master regulators of morphogenesis and accelerated cis-regulatory expansion involved in common mammalian morphological features during evolution. Here, I demonstrate that thousands of binding sites for estrogen receptor α (ERα) and three related pioneer factors (FoxA1, GATA3 and AP2γ) that are essential regulators of mammary gland development arose from a spreading of the binding motifs by retrotransposons. The TE-derived functional elements serve primarily as distal enhancers and are enriched around genes associated with mammary gland morphogenesis. The source TEs occurred via a two-phased expansion consisting of mainly L2/MIR in a eutherian ancestor and endogenous retrovirus 1 (ERV1) in simian primates and murines. Thus the build-up of potential sources for cis-elements by retrotransposons followed by their frequent utilization by the host (co-option/exaptation) may have a general accelerating effect on both establishing and diversifying a gene regulatory network, leading to morphological innovation.


2013 ◽  
Vol 42 (5) ◽  
pp. 2833-2847 ◽  
Author(s):  
Peng Jiang ◽  
Mona Singh

Abstract Combinatorial interplay among transcription factors (TFs) is an important mechanism by which transcriptional regulatory specificity is achieved. However, despite the increasing number of TFs for which either binding specificities or genome-wide occupancy data are known, knowledge about cooperativity between TFs remains limited. To address this, we developed a computational framework for predicting genome-wide co-binding between TFs (CCAT, Combinatorial Code Analysis Tool), and applied it to Drosophila melanogaster to uncover cooperativity among TFs during embryo development. Using publicly available TF binding specificity data and DNaseI chromatin accessibility data, we first predicted genome-wide binding sites for 324 TFs across five stages of D. melanogaster embryo development. We then applied CCAT in each of these developmental stages, and identified from 19 to 58 pairs of TFs in each stage whose predicted binding sites are significantly co-localized. We found that nearby binding sites for pairs of TFs predicted to cooperate were enriched in regions bound in relevant ChIP experiments, and were more evolutionarily conserved than other pairs. Further, we found that TFs tend to be co-localized with other TFs in a dynamic manner across developmental stages. All generated data as well as source code for our front-to-end pipeline are available at http://cat.princeton.edu.


Genetics ◽  
2002 ◽  
Vol 161 (2) ◽  
pp. 793-801
Author(s):  
Wilailak Pooma ◽  
Christos Gersos ◽  
Erich Grotewold

Abstract The understanding of control of gene regulation in higher eukaryotes relies heavily on results derived from non-in vivo studies, but rarely can the significance of these approximations be established in vivo. Here, we investigated the effect of Mutator and Spm insertions on the expression of the flavonoid biosynthetic gene a1, independently regulated by the transcription factors C1 and P. The a1-mum2 and a1-m2 alleles carry Mu1 and Spm insertions, respectively, in a cis-element (ARE) of unknown function located between the P- and C1-binding sites. We show that the insertions of Mu1 and Spm similarly influence the expression of a1 controlled by C1 or P. The P-controlled a1 expression in a1-m2 is Spm dependent, and the mutant phenotype of a1-mum2 is suppressed in the pericarp in the absence of the autonomous MuDR element. Footprints within the ARE affect the regulation of a1 by C1 and P differently, providing evidence that these factors control a1 expression using distinct cis-acting regulatory elements. Together, our findings contribute significantly to one of the best-described plant regulatory systems, while stressing the need to complement with in vivo experiments current approaches used for the study of control of gene expression.


2020 ◽  
Vol 118 (2) ◽  
pp. e2021171118
Author(s):  
Gi Bae Kim ◽  
Ye Gao ◽  
Bernhard O. Palsson ◽  
Sang Yup Lee

A transcription factor (TF) is a sequence-specific DNA-binding protein that modulates the transcription of a set of particular genes, and thus regulates gene expression in the cell. TFs have commonly been predicted by analyzing sequence homology with the DNA-binding domains of TFs already characterized. Thus, TFs that do not show homologies with the reported ones are difficult to predict. Here we report the development of a deep learning-based tool, DeepTFactor, that predicts whether a protein in question is a TF. DeepTFactor uses a convolutional neural network to extract features of a protein. It showed high performance in predicting TFs of both eukaryotic and prokaryotic origins, resulting in F1 scores of 0.8154 and 0.8000, respectively. Analysis of the gradients of prediction score with respect to input suggested that DeepTFactor detects DNA-binding domains and other latent features for TF prediction. DeepTFactor predicted 332 candidate TFs in Escherichia coli K-12 MG1655. Among them, 84 candidate TFs belong to the y-ome, which is a collection of genes that lack experimental evidence of function. We experimentally validated the results of DeepTFactor prediction by further characterizing genome-wide binding sites of three predicted TFs, YqhC, YiaU, and YahB. Furthermore, we made available the list of 4,674,808 TFs predicted from 73,873,012 protein sequences in 48,346 genomes. DeepTFactor will serve as a useful tool for predicting TFs, which is necessary for understanding the regulatory systems of organisms of interest. We provide DeepTFactor as a stand-alone program, available at https://bitbucket.org/kaistsystemsbiology/deeptfactor.


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