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1. PlantBind: an attention-based multi-label neural network for predicting plant transcription factor binding sites

   https://doi.org/10.1093/bib/bbac425  

   Yan, Wenkai ; Li, Zutan ; Pian, Cong ; Wu, Yufeng ( September 2022 , Briefings in Bioinformatics)

   Identification of transcription factor binding sites (TFBSs) is essential to understanding of gene regulation. Designing computational models for accurate prediction of TFBSs is crucial because it is not feasible to experimentally assay all transcription factors (TFs) in all sequenced eukaryotic genomes. Although many methods have been proposed for the identification of TFBSs in humans, methods designed for plants are comparatively underdeveloped. Here, we present PlantBind, a method for integrated prediction and interpretation of TFBSs based on DNA sequences and DNA shape profiles. Built on an attention-based multi-label deep learning framework, PlantBind not only simultaneously predicts the potential binding sites of 315 TFs, but also identifies the motifs bound by transcription factors. During the training process, this model revealed a strong similarity among TF family members with respect to target binding sequences. Trans-species prediction performance using four Zea mays TFs demonstrated the suitability of this model for transfer learning. Overall, this study provides an effective solution for identifying plant TFBSs, which will promote greater understanding of transcriptional regulatory mechanisms in plants.

    

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2. ProSampler: an ultrafast and accurate motif finder in large ChIP-seq datasets for combinatory motif discovery

   https://doi.org/10.1093/bioinformatics/btz290  

   Li, Yang ; Ni, Pengyu ; Zhang, Shaoqiang ; Li, Guojun ; Su, Zhengchang ; Berger, ed., Bonnie ( May 2019 , Bioinformatics)

   The availability of numerous ChIP-seq datasets for transcription factors (TF) has provided an unprecedented opportunity to identify all TF binding sites in genomes. However, the progress has been hindered by the lack of a highly efficient and accurate tool to find not only the target motifs, but also cooperative motifs in very big datasets.

   We herein present an ultrafast and accurate motif-finding algorithm, ProSampler, based on a novel numeration method and Gibbs sampler. ProSampler runs orders of magnitude faster than the fastest existing tools while often more accurately identifying motifs of both the target TFs and cooperators. Thus, ProSampler can greatly facilitate the efforts to identify the entire cis-regulatory code in genomes.

   Source code and binaries are freely available for download at https://github.com/zhengchangsulab/prosampler. It was implemented in C++ and supported on Linux, macOS and MS Windows platforms.

   Supplementary materials are available at Bioinformatics online.

    

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3. High-throughput data and modeling reveal insights into the mechanisms of cooperative DNA-binding by transcription factor proteins

   https://doi.org/10.1093/nar/gkad872  

   Martin, Vincentius ; Zhuang, Farica ; Zhang, Yuning ; Pinheiro, Kyle ; Gordân, Raluca ( October 2023 , Nucleic Acids Research)

   Cooperative DNA-binding by transcription factor (TF) proteins is critical for eukaryotic gene regulation. In the human genome, many regulatory regions contain TF-binding sites in close proximity to each other, which can facilitate cooperative interactions. However, binding site proximity does not necessarily imply cooperative binding, as TFs can also bind independently to each of their neighboring target sites. Currently, the rules that drive cooperative TF binding are not well understood. In addition, it is oftentimes difficult to infer direct TF–TF cooperativity from existing DNA-binding data. Here, we show that in vitro binding assays using DNA libraries of a few thousand genomic sequences with putative cooperative TF-binding events can be used to develop accurate models of cooperativity and to gain insights into cooperative binding mechanisms. Using factors ETS1 and RUNX1 as our case study, we show that the distance and orientation between ETS1 sites are critical determinants of cooperative ETS1–ETS1 binding, while cooperative ETS1–RUNX1 interactions show more flexibility in distance and orientation and can be accurately predicted based on the affinity and sequence/shape features of the binding sites. The approach described here, combining custom experimental design with machine-learning modeling, can be easily applied to study the cooperative DNA-binding patterns of any TFs.

    

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4. The Hypersaline Archaeal Histones HpyA and HstA Are DNA Binding Proteins That Defy Categorization According to Commonly Used Functional Criteria

   https://doi.org/10.1128/mbio.03449-22  

   Sakrikar, Saaz ; Hackley, Rylee K. ; Martinez-Pastor, Mar ; Darnell, Cynthia L. ; Vreugdenhil, Angie ; Schmid, Amy K. ( April 2023 , mBio)

   Komeili, Arash (Ed.)

   ABSTRACT Histone proteins are found across diverse lineages of Archaea , many of which package DNA and form chromatin. However, previous research has led to the hypothesis that the histone-like proteins of high-salt-adapted archaea, or halophiles, function differently. The sole histone protein encoded by the model halophilic species Halobacterium salinarum , HpyA, is nonessential and expressed at levels too low to enable genome-wide DNA packaging. Instead, HpyA mediates the transcriptional response to salt stress. Here we compare the features of genome-wide binding of HpyA to those of HstA, the sole histone of another model halophile, Haloferax volcanii . hstA , like hpyA , is a nonessential gene. To better understand HpyA and HstA functions, protein-DNA binding data (chromatin immunoprecipitation sequencing [ChIP-seq]) of these halophilic histones are compared to publicly available ChIP-seq data from DNA binding proteins across all domains of life, including transcription factors (TFs), nucleoid-associated proteins (NAPs), and histones. These analyses demonstrate that HpyA and HstA bind the genome infrequently in discrete regions, which is similar to TFs but unlike NAPs, which bind a much larger genomic fraction. However, unlike TFs that typically bind in intergenic regions, HpyA and HstA binding sites are located in both coding and intergenic regions. The genome-wide dinucleotide periodicity known to facilitate histone binding was undetectable in the genomes of both species. Instead, TF-like and histone-like binding sequence preferences were detected for HstA and HpyA, respectively. Taken together, these data suggest that halophilic archaeal histones are unlikely to facilitate genome-wide chromatin formation and that their function defies categorization as a TF, NAP, or histone. IMPORTANCE Most cells in eukaryotic species—from yeast to humans—possess histone proteins that pack and unpack DNA in response to environmental cues. These essential proteins regulate genes necessary for important cellular processes, including development and stress protection. Although the histone fold domain originated in the domain of life Archaea , the function of archaeal histone-like proteins is not well understood relative to those of eukaryotes. We recently discovered that, unlike histones of eukaryotes, histones in hypersaline-adapted archaeal species do not package DNA and can act as transcription factors (TFs) to regulate stress response gene expression. However, the function of histones across species of hypersaline-adapted archaea still remains unclear. Here, we compare hypersaline histone function to a variety of DNA binding proteins across the tree of life, revealing histone-like behavior in some respects and specific transcriptional regulatory function in others. 

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5. Regulatory Divergence in Wound-Responsive Gene Expression between Domesticated and Wild Tomato

   https://doi.org/10.1105/tpc.18.00194  

   Ming-Jung Liu, Koichi Sugimoto ( May 2018 , The Plant cell)

   The evolution of transcriptional regulatory mechanisms is central to how stress response and tolerance differ between species. However, it remains largely unknown how divergence in cis-regulatory sites and, subsequently, transcription factor (TF) binding specificity contribute to stress-responsive expression divergence, particularly between wild and domesticated spe-cies. By profiling wound-responsive gene transcriptomes in wild Solanum pennellii and do-mesticated S. lycopersicum, we found extensive wound-response divergence and identified 493 S. lycopersicum and 278 S. pennellii putative cis-regulatory elements (pCREs) that were predictive of wound-responsive gene expression. Only 24-52% of these wound-response pCREs (depending on wound-response patterns) were consistently enriched in the putative promoter regions of wound-responsive genes across species. In addition, between these two species, their differences in pCRE site sequences were significantly and positively correlated with differences in wound-responsive gene expression. Furthermore, ~11-39% of pCREs were specific to only one of the species and likely bound by TFs from different families. These findings indicate substantial regulatory divergence in these two plant species that di-verged ~3-7 million years ago. Our study provides insights into the mechanistic basis of how the transcriptional response to wounding is regulated and, importantly, the contribution of cis-regulatory components to variation in wound-responsive gene expression between a wild and a domesticated plant species. 

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