scholarly journals Regulatory elements encoded in the first intron are necessary for proper expression of the MADS-box transcription factors AGL6 and AGL13 in Arabidopsis thaliana

2008 ◽  
Vol 319 (2) ◽  
pp. 587 ◽  
Author(s):  
Stephen E. Schauer ◽  
Ramarmurthy Baskar ◽  
Philipp Schlüter ◽  
Jacqueline Gheyselinck ◽  
Arturo Bolaños ◽  
...  
Open Medicine ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 640-650
Author(s):  
Maria Araceli Diaz Cruz ◽  
Dan Lund ◽  
Ferenc Szekeres ◽  
Sandra Karlsson ◽  
Maria Faresjö ◽  
...  

Abstract Nuclear receptors (NRs) are ligand-activated transcription factors that regulate gene expression when bound to specific DNA sequences. Crosstalk between steroid NR systems has been studied for understanding the development of hormone-driven cancers but not to an extent at a genetic level. This study aimed to investigate crosstalk between steroid NRs in conserved intron and exon sequences, with a focus on steroid NRs involved in prostate cancer etiology. For this purpose, we evaluated conserved intron and exon sequences among all 49 members of the NR Superfamily (NRS) and their relevance as regulatory sequences and NR-binding sequences. Sequence conservation was found to be higher in the first intron (35%), when compared with downstream introns. Seventy-nine percent of the conserved regions in the NRS contained putative transcription factor binding sites (TFBS) and a large fraction of these sequences contained splicing sites (SS). Analysis of transcription factors binding to putative intronic and exonic TFBS revealed that 5 and 16%, respectively, were NRs. The present study suggests crosstalk between steroid NRs, e.g., vitamin D, estrogen, progesterone, and retinoic acid endocrine systems, through cis-regulatory elements in conserved sequences of introns and exons. This investigation gives evidence for crosstalk between steroid hormones and contributes to novel targets for steroid NR regulation.


2020 ◽  
Author(s):  
Christina B. Azodi ◽  
John P. Lloyd ◽  
Shin-Han Shiu

ABSTRACTPlants respond to their environment by dynamically modulating gene expression. A powerful approach for understanding how these responses are regulated is to integrate information about cis-regulatory elements (CREs) into models called cis-regulatory codes. Transcriptional response to combined stress is typically not the sum of the responses to the individual stresses. However, cis-regulatory codes underlying combined stress response have not been established. Here we modeled transcriptional response to single and combined heat and drought stress in Arabidopsis thaliana. We grouped genes by their pattern of response (independent, antagonistic, synergistic) and trained machine learning models to predict their response using putative CREs (pCREs) as features (median F-measure = 0.64). We then developed a deep learning approach to integrate additional omics information (sequence conservation, chromatin accessibility, histone modification) into our models, improving performance by 6.2%. While pCREs important for predicting independent and antagonistic responses tended to resemble binding motifs of transcription factors associated with heat and/or drought stress, important synergistic pCREs resembled binding motifs of transcription factors not known to be associated with stress. These findings demonstrate how in silico approaches can improve our understanding of the complex codes regulating response to combined stress and help us identify prime targets for future characterization.


2020 ◽  
Vol 11 ◽  
Author(s):  
Maurizio Di Marzo ◽  
Irma Roig-Villanova ◽  
Eva Zanchetti ◽  
Francesca Caselli ◽  
Veronica Gregis ◽  
...  

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Christina B Azodi ◽  
John P Lloyd ◽  
Shin-Han Shiu

Abstract Plants respond to their environment by dynamically modulating gene expression. A powerful approach for understanding how these responses are regulated is to integrate information about cis-regulatory elements (CREs) into models called cis-regulatory codes. Transcriptional response to combined stress is typically not the sum of the responses to the individual stresses. However, cis-regulatory codes underlying combined stress response have not been established. Here we modeled transcriptional response to single and combined heat and drought stress in Arabidopsis thaliana. We grouped genes by their pattern of response (independent, antagonistic and synergistic) and trained machine learning models to predict their response using putative CREs (pCREs) as features (median F-measure = 0.64). We then developed a deep learning approach to integrate additional omics information (sequence conservation, chromatin accessibility and histone modification) into our models, improving performance by 6.2%. While pCREs important for predicting independent and antagonistic responses tended to resemble binding motifs of transcription factors associated with heat and/or drought stress, important synergistic pCREs resembled binding motifs of transcription factors not known to be associated with stress. These findings demonstrate how in silico approaches can improve our understanding of the complex codes regulating response to combined stress and help us identify prime targets for future characterization.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ching-Yu Shen ◽  
You-Yi Chen ◽  
Ke-Wei Liu ◽  
Hsiang-Chia Lu ◽  
Song-Bin Chang ◽  
...  

AbstractThe ovules and egg cells are well developed to be fertilized at anthesis in many flowering plants. However, ovule development is triggered by pollination in most orchids. In this study, we characterized the function of a Bsister gene, named PeMADS28, isolated from Phalaenopsis equestris, the genome-sequenced orchid. Spatial and temporal expression analysis showed PeMADS28 predominantly expressed in ovules between 32 and 48 days after pollination, which synchronizes with integument development. Subcellular localization and protein–protein interaction analyses revealed that PeMADS28 could form a homodimer as well as heterodimers with D-class and E-class MADS-box proteins. In addition, ectopic expression of PeMADS28 in Arabidopsis thaliana induced small curled rosette leaves, short silique length and few seeds, similar to that with overexpression of other species’ Bsister genes in Arabidopsis. Furthermore, complementation test revealed that PeMADS28 could rescue the phenotype of the ABS/TT16 mutant. Together, these results indicate the conserved function of BsisterPeMADS28 associated with ovule integument development in orchid.


BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Alexandre Z. Daly ◽  
Lindsey A. Dudley ◽  
Michael T. Peel ◽  
Stephen A. Liebhaber ◽  
Stephen C. J. Parker ◽  
...  

Abstract Background The pituitary gland is a neuroendocrine organ containing diverse cell types specialized in secreting hormones that regulate physiology. Pituitary thyrotropes produce thyroid-stimulating hormone (TSH), a critical factor for growth and maintenance of metabolism. The transcription factors POU1F1 and GATA2 have been implicated in thyrotrope fate, but the transcriptomic and epigenomic landscapes of these neuroendocrine cells have not been characterized. The goal of this work was to discover transcriptional regulatory elements that drive thyrotrope fate. Results We identified the transcription factors and epigenomic changes in chromatin that are associated with differentiation of POU1F1-expressing progenitors into thyrotropes using cell lines that represent an undifferentiated Pou1f1 lineage progenitor (GHF-T1) and a committed thyrotrope line that produces TSH (TαT1). We compared RNA-seq, ATAC-seq, histone modification (H3K27Ac, H3K4Me1, and H3K27Me3), and POU1F1 binding in these cell lines. POU1F1 binding sites are commonly associated with bZIP transcription factor consensus binding sites in GHF-T1 cells and Helix-Turn-Helix (HTH) or basic Helix-Loop-Helix (bHLH) factors in TαT1 cells, suggesting that these classes of transcription factors may recruit or cooperate with POU1F1 binding at unique sites. We validated enhancer function of novel elements we mapped near Cga, Pitx1, Gata2, and Tshb by transfection in TαT1 cells. Finally, we confirmed that an enhancer element near Tshb can drive expression in thyrotropes of transgenic mice, and we demonstrate that GATA2 enhances Tshb expression through this element. Conclusion These results extend the ENCODE multi-omic profiling approach to the pituitary gland, which should be valuable for understanding pituitary development and disease pathogenesis. Graphical abstract


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