Options and Considerations When Using a Yeast One-Hybrid System

A Rapid and Simplified Method to Isolate Specific Regulators Based on Biotin-Avidin Binding Affinities in Crops

Transcription factors (TFs) are indispensable components of transcriptional regulatory pathways involved in crop growth and development. Herein, we developed a new method for the identification of upstream TFs specific to genes in crops based on the binding affinities of biotin and avidin. First, we constructed and verified the new biotin and avidin system (BAS) by a coprecipitation assay. Subsequently, the feasibility of DNA-based BAS (DBAS) was further proved by in vivo and in vitro assays. Furthermore, we cloned the promoter of rice OsNRT1.1B and the possible regulators were screened and identified. Additionally, partial candidates were validated by the electrophoresis mobility shift assay (EMSA), yeast one-hybrid, and luciferase activity assays. Remarkably, the results showed that the candidates PIP3 and PIP19 both responded to nitrate immediately and overexpression of PIP3 caused retard growth, which indicates that the candidates are functional and the new DBAS method is useful to isolate regulators in crops.

Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.

Gene Ontology representation for transcription factor functions

Transcription plays a central role in defining the identity and functionalities of cells, as well as in their responses to changes in the cellular environment. The Gene Ontology (GO) provides a rigorously defined set of concepts that describe the functions of gene products. A GO annotation is a statement about the function of a particular gene product, represented as an association between a gene product and the biological concept a GO term defines. Critically, each GO annotation is based on traceable scientific evidence. Here, we describe the different GO terms that are associated with proteins involved in transcription and its regulation, focusing on the standard of evidence required to support these associations. This article is intended to help users of GO annotations understand how to interpret the annotations and can contribute to the consistency of GO annotations. We distinguish between three classes of activities involved in transcription or directly regulating it - general transcription factors, DNA-binding transcription factors, and transcription co-regulators.

Comprehensive mapping of the human cytokine gene regulatory network

Proper cytokine gene expression is essential in development, homeostasis and immune responses. Studies on the transcriptional control of cytokine genes have mostly focused on highly researched transcription factors (TFs) and cytokines, resulting in an incomplete portrait of cytokine gene regulation. Here, we used enhanced yeast one-hybrid (eY1H) assays to derive a comprehensive network comprising 1380 interactions between 265 TFs and 108 cytokine gene promoters. Our eY1H-derived network greatly expands the known repertoire of TF–cytokine gene interactions and the set of TFs known to regulate cytokine genes. We found an enrichment of nuclear receptors and confirmed their role in cytokine regulation in primary macrophages. Additionally, we used the eY1H-derived network as a framework to identify pairs of TFs that can be targeted with commercially-available drugs to synergistically modulate cytokine production. Finally, we integrated the eY1H data with single cell RNA-seq and phenotypic datasets to identify novel TF–cytokine regulatory axes in immune diseases and immune cell lineage development. Overall, the eY1H data provides a rich resource to study cytokine regulation in a variety of physiological and disease contexts.

Discovering human transcription factor physical interactions with genetic variants, novel DNA motifs, and repetitive elements using enhanced yeast one-hybrid assays

Identifying transcription factor (TF) binding to noncoding variants, uncharacterized DNA motifs, and repetitive genomic elements has been technically and computationally challenging. Current experimental methods, such as chromatin immunoprecipitation, generally test one TF at a time, and computational motif algorithms often lead to false-positive and -negative predictions. To address these limitations, we developed an experimental approach based on enhanced yeast one-hybrid assays. The first variation of this approach interrogates the binding of >1000 human TFs to repetitive DNA elements, while the second evaluates TF binding to single nucleotide variants, short insertions and deletions (indels), and novel DNA motifs. Using this approach, we detected the binding of 75 TFs, including several nuclear hormone receptors and ETS factors, to the highly repetitive Alu elements. Further, we identified cancer-associated changes in TF binding, including gain of interactions involving ETS TFs and loss of interactions involving KLF TFs to different mutations in the TERT promoter, and gain of a MYB interaction with an 18-bp indel in the TAL1 superenhancer. Additionally, we identified TFs that bind to three uncharacterized DNA motifs identified in DNase footprinting assays. We anticipate that these enhanced yeast one-hybrid approaches will expand our capabilities to study genetic variation and undercharacterized genomic regions.

Differential color development and response to light deprivation of fig (Ficus carica L.) syconia peel and female flower tissues: transcriptome elucidation

BACKGROUND

Color directly affects fruit quality and consumer preference. In fig syconia, the female flower tissue is contained in a receptacle. Anthocyanin pigmentation of this tissue and the peel differs temporally and spatially. A transcriptome study was carried out to elucidate key genes and transcription factors regulating differences in fig coloring.

RESULTS

Anthocyanins in the female flower tissue were identified mainly as pelargonidin-3-glucoside and cyanidin-3-rutinoside; in the peel, the major anthocyanins were cyanidin 3-O-glucoside and cyanidin-3-rutinoside. Anthocyanin content was significantly higher in the female flower tissue vs. peel before fig ripening, whereas at ripening, the anthocyanin content in the peel was 5.39 times higher than that in the female flower tissue. Light-deprivation treatment strongly inhibited peel, but not female flower tissue, anthocyanin pigmentation. RNA-Seq revealed 522 differentially expressed genes (recruited with criteria log₂ ≥ 2 and P < 0.05) at fig ripening, with 50 upregulated and 472 downregulated genes in the female flower tissue. Light deprivation upregulated 1180 and downregulated 856 genes in the peel, and upregulated 909 and downregulated 817 genes in the female flower tissue. KEGG enrichment revealed significantly changed expression in the phenylpropanoid-biosynthesis and flavonoid-biosynthesis pathways in the peel, but not in the female flower tissue, with significant repression of FcCHS, FcCHI, FcF3H, FcF3'H, FcDFR and FcUFGT transcripts. Light deprivation led to differential expression of 71 and 80 transcription factor genes in the peel and female flower tissue, respectively. Yeast one-hybrid screen revealed that FcHY5 and FcMYB114 bind the promoter regions of FcCHS and FcDFR, respectively in the flavonoid-biosynthesis pathway.

CONCLUSIONS

Phenylpropanoid- and flavonoid-biosynthesis pathways were differentially expressed spatially and temporally in the peel and female flower tissue of fig syconia; pathway expression in the peel was strongly regulated by light signal. Differentially expressed transcription factors were recruited as candidates to screen important expression regulators in the light-dependent and light-independent anthocyanin-synthesis pathway. Our study lays the groundwork for further elucidation of crucial players in fig pigmentation.

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Identifying the sets of transcription factors (TFs) that regulate each human gene is a daunting task that requires integrating numerous experimental and computational approaches. One such method is the yeast one-hybrid (Y1H) assay, in which interactions between TFs and DNA regions are tested in the milieu of the yeast nucleus using reporter genes. Y1H assays involve two components: a 'DNA-bait' (e.g., promoters, enhancers, silencers, etc.) and a 'TF-prey,' which can be screened for reporter gene activation. Most published protocols for performing Y1H screens are based on transforming TF-prey libraries or arrays into DNA-bait yeast strains. Here, we describe a pipeline, called enhanced Y1H (eY1H) assays, where TF-DNA interactions are interrogated by mating DNA-bait strains with an arrayed collection of TF-prey strains using a high density array (HDA) robotic platform that allows screening in a 1,536 colony format. This allows for a dramatic increase in throughput (60 DNA-bait sequences against >1,000 TFs takes two weeks per researcher) and reproducibility. We illustrate the different types of expected results by testing human promoter sequences against an array of 1,086 human TFs, as well as examples of issues that can arise during screens and how to troubleshoot them.