Biology subjects

Liang, Z.

Publications and source records attributed to Liang, Z..

At least 145 records · Page 8Linked to original sources

bioRxiv2022

Coupling of perinuclear actin cap and nuclear mechanics regulates flow-induced YAP spatiotemporal nucleocytoplasmic transport

Mechanical forces, including flow shear stress, regulate fundamental cellular process by modulating the nucleocytoplasmic transport of transcription factors, such as Yes-associated Protein (YAP). However, the mechanical mechanism how flow induces the nucleocytoplasmic transport remains largely unclear. Here we found that unidirectional flow applied to endothelial cells induces biphasic YAP nucleocytoplasmic transport with initial nuclear import, followed by nuclear export as perinuclear actin cap forms and nuclear stiffening in a dose and timing-dependent manner. In contrast, pathological oscillatory flow induces slight actin cap formation and nuclear softening, sustaining YAP nuclear localization. To explain the disparately spatiotemporal distribution of YAP, we developed a three-dimensional mechanochemical model considering coupling processes of flow sensing, cytoskeleton organization, nucleus mechanotransduction, and YAP spatiotemporal transport. We discovered that actin cap formation and nuclear stiffness alteration under flow synergically regulate nuclear deformation, hence governing YAP transport. Furthermore, we expanded our single cell model to a collective vertex framework and found that actin cap irregularities in individual cells under flow shear stress potentially induce topological defects and spatially heterogeneous YAP distribution in cellular monolayers. Our work unveils the unified mechanism of flow-induced nucleocytoplasmic transport, offering a universal linkage between transcriptional regulation and mechanical stimulation.

bioengineering↗

bioRxiv2022

A systematically optimized awake mouse fMRI paradigm

Functional magnetic resonance imaging (fMRI) has been increasingly utilized in mice. Due to the non-negligible effects of anesthetics on mouse fMRI, it is becoming more common to perform fMRI in the awake mice. However, high stress level and head motion in awake mouse fMRI remain to be fully addressed, which limits its practical applications. Therefore, here we presented a systematically optimized awake mouse fMRI paradigm as a practical and open-source solution. First, we designed a soundproof habituation chamber in which multiple mice can be habituated simultaneously and independently. Then, combining corticosterone, body weight and behavioral measurements, we systematically evaluated the potential factors that may contribute to animals stress level for awake imaging. Among many factors, we found that the restraining setup allowing forelimbs freely moving and head tilted at 30-degree was optimal for minimizing stress level. Importantly, we implemented multiband simultaneous multi-slice imaging to enable ultrafast fMRI acquisition in awake mice. Compared to conventional single-band EPI, faster acquisition enabled by multiband imaging were more robust to head motion and yielded higher statistical power. Thus, more robust resting-state functional connectivity was detected using multiband acquisition in awake mouse fMRI, compared to conventional single-band acquisition. In conclusion, we presented an awake mouse fMRI paradigm that is highly optimized in both awake mice habituation and fMRI acquisition, and such paradigm minimized animals stress level and provided more resistance to head motion and higher statistical power.

neuroscience↗

bioRxiv2022

Whole-Brain fMRI Functional Connectivity Signatures Predict Sustained Emotional Experience in Naturalistic Contexts

Determining and decoding emotional brain processes under ecologically valid conditions remains a key challenge in affective neuroscience. The current functional magnetic resonance imaging (fMRI) based emotion decoding studies are mainly based on brief and isolated episodes of emotion induction, while sustained emotional experience in naturalistic environments that mirror daily life experiences are scarce. Here we use 10-minute movie clips as ecologically valid emotion-evoking procedures in n=52 individuals to explore emotion-specific fMRI functional connectivity (FC) profiles on the whole-brain level at high spatial resolution (400 atlas based parcels). Employing machine-learning based decoding and cross validation procedures allowed to develop predictive FC profiles that can accurately distinguish sustained happiness and sadness and that generalize across movies and subjects. Both functional brain network-based and subnetwork-based emotion prediction results suggest that emotion manifests as distributed representation of multiple networks, rather than a single functional network or subnetwork. Further, the results show that the Visual Network (VN) and Default Mode Network (DMN) associated functional networks, especially VN-DMN, exhibit a strong contribution to emotion prediction. To further estimate the cumulative effect of naturalistic long-term movie-based video-evoking emotions, we divide the 10-min episode into three stages: early stimulation (1 ~ 200 s), middle stimulation (201 ~ 400 s), and late stimulation (401 ~ 600 s) and examine the emotion prediction performance at different stimulation stages. We found that the late stimulation has a stronger predictive ability (accuracy=85.32%, F1-score=85.62%) compared to early and middle stimulation stages, implying that continuous exposure to emotional stimulation can lead to more intense emotions and further enhance emotion-specific distinguishable representations. The present work demonstrates that sustained sadness and happiness under naturalistic conditions are presented in emotion-specific network profiles and these expressions may play different roles in the generation and modulation of emotions. These findings elucidate the importance of network level adaptations for sustained emotional experiences during naturalistic contexts and open new venues for imaging network level contributions under naturalistic conditions.

neuroscience↗

bioRxiv2022

Anesthesia-related brain microstructure modulations detected by diffusion MRI

Brain clearance has been found to be greatly enhanced during sleep and anesthesia. Studies using optical microscopy have attributed this to an anesthesia-related expansion of the brains extra-cellular space. These results, however, have been based on invasive experiments with a limited field of view. Here, we employ diffusion kurtosis magnetic resonance imaging to assess brain microstructure in the awake and anesthetized mouse brain. We find both mean diffusivity and mean kurtosis to be significantly decreased in the anesthetized mouse brain compared to the awake state. This effect is observed in both gray matter and white matter. Our findings are consistent with the reports of brain ECS volume increase in sleep and anesthesia. Based on simple simulations, we discuss how an ECS volume increase (cell shrinkage) during sleep and anesthesia can coexist with other aspects of brain physiology. Our study demonstrates that diffusion kurtosis MRI can be used in the study of the glymphatic system. Importantly, our study shows an overlooked effect of anesthesia on brain microstructure which is relevant to preclinical MRI as a whole.

neuroscience↗

bioRxiv2022

Reconstruct a eukaryotic chromosome arm by de novo design and synthesis

The genome of an organism is inherited from its ancestor and keeps evolving over time, however, how much the current version could be altered remains unknown. Here, we use the left arm of chromosome XII (chrXIIL) as an example to probe the genome plasticity in Saccharomyces cerevisiae. A neochromosome was designed to harbor originally dispersed genes. The essentiality of sequences in chrXIIL was dissected by targeted DNA removal, chromosome truncation and random deletion. Notably, 12 genes were sufficient for survival, while 25 genes are required to retain robust fitness. Next, we demonstrated these genes could be reconstructed using synthetic regulatory sequences and recoded open-reading frames with "one-amino-acid-one-codon" strategy. Finally, we built a neochromsome, which could substitute for chrXIIL for cell viability, with these reconstructed genes. Our work not only highlights the high plasticity of yeast genome, but also illustrates the possibility of making functional chromosomes with completely artificial sequences. HIGHLIGHTSO_LIA neochromosome was designed to facilitate the assembly of exogenous DNA for stable expression in yeast C_LIO_LIThe left arm of chrXII could be minimized to just 12 genes to maintain viability, but additional genes were required to retain robust fitness C_LIO_LIComprehensive recoding and transcriptional refactoring using artificial regulatory sequences produced a functional chromosome arm C_LIO_LIA completely reconstructed neochromosome could replace the chrXIIL to maintain comparable fitness C_LI

synthetic biology↗

bioRxiv2022

Pyrfume: A Window to the World's Olfactory Data

Advances in theoretical understanding are frequently unlocked by access to large, diverse experimental datasets. Olfactory neuroscience and psychophysics remain years behind the other senses in part because rich datasets linking olfactory stimuli with their corresponding percepts, behaviors, and neural pathways underlying this transformation, remain scarce. Here we present a concerted effort to unlock and unify dozens of stimulus-linked olfactory datasets across species and modalities under a unified framework called Pyrfume. We present examples of how researchers might use Pyrfume to conduct novel analyses uncovering new principles, introduce trainees to the field, or construct benchmarks for machine olfaction.

neuroscience↗

bioRxiv2022

Generation of a new Adar1p150-/- mouse demonstrates isoform-specific roles in embryonic development and adult homeostasis.

The RNA editing enzyme Adenosine deaminase acting on RNA 1 (ADAR1) is an essential regulator of innate immune activation by both cellular and viral dsRNA. Adenosine-to-Inosine (A-to-I) editing by ADAR1 modifies the sequence and structure of endogenous dsRNA and masks it from the cytoplasmic dsRNA sensor melanoma differentiation-associated protein 5 (MDA5), preventing innate immune activation. Loss of function mutations in ADAR are associated with rare autoinflammatory disorders including Aicardi-Goutieres Syndrome (AGS), defined by a constitutive systemic upregulation of type I interferon (IFN). The murine Adar gene encodes two protein isoforms with distinct functions: ADAR1p110 is constitutively expressed and localizes to the nucleus, whereas ADAR1p150 is primarily cytoplasmic and is inducible by IFN. Recent studies have demonstrated the critical requirement for ADAR1p150 to suppress innate immune activation by self dsRNAs, however, detailed in vivo characterization of the role of ADAR1p150 during development and in adult mice is lacking. We developed a new ADAR1p150-specific knockout mouse mutant based on a single nucleotide deletion that resulted in the loss of the ADARp150 protein without affecting ADAR1p110 expression. The Adar1p150-/- died embryonically at E11.5-E12.5 due to cell death in the fetal liver accompanied by an activated IFN response. Somatic loss of ADAR1p150 in adults was lethal and caused rapid hematopoietic failure, demonstrating an ongoing requirement for ADAR1p150 in vivo. The generation and characterization of this mouse model demonstrates the essential role of ADAR1p150 in vivo and provides a new tool for dissecting the functional differences between ADAR1 isoforms and their physiological contributions.

genetics↗

bioRxiv2022

Targeted genome editing in grape using multiple CRISPR-guided editing systems

The CRISPR/Cas9 system, together with newly developed CRISPR technologies such as CRISPR/LbCpf1 and base editors, have expanded the scope of targeted genome editing in plants. However, in grape, applications of these novel CRISPR-guided tools have not been reported. Here, we employed EGFP (enhanced green fluorescent protein) and RUBY to help to screen transformed grape cells based on fluorescence and red betalain and tested the activities of CRISPR/LbCpf1, CRISPR/xCas9 and cytidine base editor (CBE) in grape, respectively. The grape TMT1 (tonoplastic monosaccharide transporter1) and TMT2 genes were simultaneously edited by using LbCpf1, resulting in an efficiency of 16-48%. Furthermore, high temperature (34{degrees}C) could enhance editing efficiencies at most of the designed targets. The CRISPR/xCas9 could induce targeted mutagenesis at the target with NGG PAM, but the efficiencies were very low (< 1.9%). The targets with GAA and GAT PAMs that are reported in mammalian cells and rice were not recognized by xCas9 in our study. Moreover, successful C-to-T substitutions were achieved in GAI1 (gibberellin insensitive1) gene by using CBE. The editing efficiencies ranged from 2.4 to 15% at the two targets in GAI1 in grape cells. Analysis of independent embryos revealed a C-to-T efficiency of 12.5% at the first target of GAI1. Taken together, our results demonstrate the efficacy of these CRISPR-guided tools in grape and provide evidence for further application of these editing tools in this economically important species.

plant biology↗

bioRxiv2022

Structural principles of B-cell antigen receptor assembly

The B-cell antigen receptor (BCR) is composed of a membrane-bound immunoglobulin (mIg) of class M, D, G, A or E for antigen recognition and a disulfide-linked heterodimer between Ig and Ig{beta} (Ig/{beta}, also known as CD79A and CD79B) that functions as the signalling entity. The organizing principle of BCR assembly remains elusive. Here we report the cryo-electron microscopy structures of the intact IgM class BCR at 8.2 [A] resolution and its Fab-deleted form (IgM BCR{Delta}Fab) at 3.6 [A] resolution. At the ectodomain (ECD), Ig and Ig{beta} position their respective Ig folds roughly in parallel with an approximate 2-fold symmetry, which is distinct from structures of Ig{beta}/{beta} homodimers. Unlike previous predictions, the BCR structure displays an asymmetric arrangement, in which the Ig/{beta} ECD heterodimer mainly uses Ig to associate with C{micro}3-C{micro}4 domains of one heavy chain ({micro}HC) while leaving the other heavy chain ({micro}HC) empty. The transmembrane domain (TMD) helices of the two {micro}HCs also deviate from the 2-fold symmetry of the C{micro}3-C{micro}4 domain dimer and form together with the TMD helices of the Ig/{beta} heterodimer a tight 4-helix bundle. The asymmetry at the TMD helices prevents the recruitment of two Ig/{beta} heterodimers. Surprisingly, the connecting peptides (CPs) between the ECD and TMD are braided together through striking charge complementarity, resulting in intervening of the CP of {micro}HC in between those of Ig and Ig{beta} and crossover of the TMD relative to ECD for the Ig/{beta} heterodimer, to guide the TMD assembly. Interfacial analyses suggest that the IgM BCR structure we present here may represent a general organizational architecture of all BCR classes. Our studies thus provide a structural platform for understanding B-cell signalling and for designing rational therapies against BCR-mediated diseases.

immunology↗

bioRxiv2022

An antibody-drug conjugate targeting GPR56 demonstrates efficacy in preclinical models of colorectal cancer

Antibody-drug conjugates (ADCs) have become an increasingly successful class of anticancer therapy, particularly within the past few years. Though ADCs are in clinical trials for colorectal cancer (CRC), a candidate has yet to be approved. CRC continues to be a leading cause of cancer-related death, emphasizing the need to identify novel target antigens for ADC development. GPR56, a member of the 7TM receptor family, is upregulated in colorectal tumors compared to normal tissues and located on the surface of CRC cells, making it a promising ADC target. Furthermore, high GPR56 expression occurs in tumors that are microsatellite stable, negative for the CpG methylator phenotype, and show chromosomal instability. We previously reported the generation of a high affinity GPR56-specific monoclonal antibody, 10C7, and we have now mapped the epitope to the C-terminal end of the extracellular domain, proximal to the GPCR proteolysis site. Here, we describe the development of a duocarmycin-conjugated 10C7 ADC. 10C7 co-internalized with GPR56 and trafficked to the lysosomes of CRC cells, which is critical for efficient ADC payload release. Evaluation of the ADC in a panel of CRC cell lines and tumor organoids with different levels of GPR56 expression showed the ADC selectively induced cytotoxicity at low nanomolar concentrations in a GPR56-dependent manner. A nontargeting control ADC showed minimal to no activity. Furthermore, GPR56 ADC exhibited significant antitumor efficacy against GPR56-expressing patient-derived xenograft models of CRC. This study provides rationale for the development of a GPR56-targeted ADC approach to potentially treat a large fraction of CRC patients.

cancer biology↗

bioRxiv2022

Multifactorial Methods Integrating Haplotype and Epistasis Effects for Genomic Estimation and Prediction of Quantitative Traits

The rapid growth in genomic selection data provides unprecedented opportunities to discover and utilize complex genetic effects for improving phenotypes but methodology is lacking. Epistasis effects are interaction effects and haplotype effects may contain local high-order epistasis effects. Multifactorial methods with SNP, haplotype and epistasis effects up to the third-order are developed to investigate the contributions of global low-order and local high-order epistasis effects to the phenotypic variance and the accuracy of gnomic prediction of quantitative traits. These methods include genomic best linear unbiased prediction (GBLUP) with associated reliability for individuals with and without phenotypic observations including a computationally efficient GBLUP method for large validation populations, and genomic restricted maximum estimation (GREML) of the variance and associated heritability using a combination of EM-REML and AI-REML iterative algorithms. These methods were developed for two models, Model-I with 10 effect types, and Model-II with 13 effect types including intra- and inter-chromosome pairwise epistasis effects that replace the pairwise epistasis effects of Model-I. GREML heritability estimate and GBLUP effect estimate for each effect of an effect type are derived except for third-order epistasis effects. The multifactorial models evaluate each effect type based on the phenotypic values adjusted for the remaining effect types and can use more effect types than separate models of SNP, haplotype and epistasis effects; and provide a methodology capability to evaluate the contributions of complex genetic effects to the phenotypic variance and prediction accuracy, and to discover and utilize complex genetic effects for improving the phenotypes of quantitative traits.

genetics↗

bioRxiv2022

A benchmark study of protein folding algorithms on nanobodies

Nanobodies, also known as single domain or VHH antibodies, are the artificial recombinant variable domains of heavy-chain-only antibodies. Nanobodies have many unique properties, including small size, good solubility, superior stability, rapid clearance from blood, and deep tissue penetration. Therefore, nanobodies have emerged as promising tools for diagnosing and treating diseases. In recent years, many deep-learning-based protein structure prediction methods have emerged that require only protein sequences as input to obtain highly-credible 3D protein structures. Among them, AlphaFold2, RoseTTAFold, DeepAb, NanoNet, and tFold performed excellently in protein prediction or antibody/nanobody prediction. In this study, we selected 60 nanobody samples with known experimental 3D structures in the Protein Data Bank (PDB). Next, we predicted their 3D structures using these five prediction algorithms from only their 2D amino acid sequences. Then, we individually compared the predicted and experimental structures. Finally, the results are analyzed and discussed.

bioinformatics↗

bioRxiv2022

Segmented MS/MS acquisition of a1 ion-based strategy for in-depth proteome quantitation

In-depth proteome quantitation is of great significance for understanding protein functions, advancing biological, medical, environmental and metabolic engineering research. Herein, benefiting from the high formation efficiencies and intensities of dimethyl-labeled a1 ions for accurate quantitation, we developed an in-depth a1 ion-based proteome quantitation method, named deep-APQ, by a sequential MS/MS acquisition of the high mass range for identification and the low mass range for a1 ion intensity extraction to increase quantitative protein number and sequence coverage. By the analysis of HeLa protein digests, our developed method showed deeper quantitative coverage than our previously reported a1 ion-based quantitation method without mass range segmentation and lower missing values than widely-used label-free quantitation method. It also exhibited excellent accuracy and precision within a 20-fold dynamic range. We further integrated a workflow combining the deep-APQ method with highly efficient sample preparation, high-pH and low-pH reversed-phase separation and high-field asymmetric waveform ion mobility spectrometry (FAIMS) to study E. coli proteome responses under the nutritional conditions of glucose and acetate. A total of 3447 proteins were quantified, representing 82% of protein-coding genes, with the average sequence coverage up to 40%, demonstrating the high coverage of quantitation results. We found that most of the quantified proteins related to chemotaxis were differentially expressed, including the low-abundance proteins such as trg, fliL, and cheA, indicating that chemotaxis would play an important role for E. coli cell to survive from acetate toxicity. The above results demonstrated that the deep-APQ method is of great promising to achieve the deep-coverage proteome quantitation with high confidence. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/501662v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1457bdeorg.highwire.dtl.DTLVardef@c74e53org.highwire.dtl.DTLVardef@e72e9forg.highwire.dtl.DTLVardef@1a5cc43_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2022

A Multi-subject, Multi-session, and Multi-task database for EEG-based Biometrics Challenge

EEG signals exhibit commonality and variability across subjects, sessions, and tasks. But most existing EEG studies focus on mean group effects (commonality) by averaging signals over trials and subjects. The substantial intra- and inter-subject variability of EEG has often been overlooked. The recently significant technological advances in machine learning, especially deep learning, have brought technological innovations to EEG signal application in many aspects, but there are still great challenges in cross-session, cross-task, and cross-subject EEG decoding. In this work, an EEG-based biometric competition based on a large-scale M3CV (A Multi-subject, Multi-session, and Multi-task Database for investigation of EEG Commonality and Variability) database was launched to better characterize and harness the intra- and inter-subject variability and promote the development of machine learning algorithm in this field. In the M3CV database, EEG signals were recorded from 106 subjects, of which 95 subjects repeated two sessions of the experiments on different days. The whole experiment consisted of 6 paradigms, including resting-state, transient-state sensory, steady-state sensory, cognitive oddball, motor execution, and steady-state sensory with selective attention with 14 types of EEG signals, 120,000 epochs. With the learning tasks of the identification and verification, the performance metrics and baseline methods were introduced in the competition. In general, the proposed M3CV dataset and the EEG-based biometric competition aim to provide the opportunity to develop advanced machine learning algorithms for achieving an in-depth understanding of the commonality and variability of EEG signals across subjects, sessions, and tasks.

neuroscience↗

bioRxiv2022

The most common human ADAR1p150 Zα domain mutation P193A is well tolerated in mice.

ADAR1 mediated A-to-I RNA editing is a self/non-self discrimination mechanism for cellular double stranded RNAs. ADAR mutations are one cause of Aicardi-Goutieres Syndrome, an inherited paediatric encephalopathy, broadly classed as a "Type I interferonopathy". The most common ADAR1 mutation is a proline 193 alanine (p.P193A) mutation, mapping to the ADAR1p150 isoform specific Z domain. We report the development of an independent murine P195A knock-in mouse, homologous to the human P193A mutation. The Adar1P195A/P195A mice are largely normal and the mutation is well tolerated. Contrasting with previous reports when the P195A mutation was compounded with an ADAR1 null allele, the majority of mice have only a modest reduction in weaning weight and survived long-term. Severe runting and shortened survival of Adar1P195A/-animals are dependent on the parental genotype. The P195A mutation is well tolerated in vivo and the loss of MDA5 is sufficient to completely rescue the Adar1P195A/- mice.

genetics↗

bioRxiv2022

Mapping Responsive Genomic Elements to Heat Stress in a Maize Diversity Panel

Many plant species exhibit genetic variation for tolerating environmental stress. A transcriptome investigation of over 100 maize inbreds revealed many cis- and trans-acting eQTLs that influence the expression response to heat stress. The cis-acting eQTL in response to heat stress are identified in genes with differential responses to heat stress between genotypes as well as genes that are only expressed under heat stress. The cis-acting variants for heat stress responsive expression likely result from distinct promoter activities and the differential heat responses of the alleles were confirmed for selected genes using transient expression assays. Global foot-printing of transcription factor binding was performed in control and heat stress conditions to document regions with heat-enriched transcription factor binding occupancies. Footprints enriched near proximal regions of characterized heat-responsive genes in a large association panel can be utilized for prioritizing functional genomic regions that regulate genotype-specific responses under heat stress.

plant biology↗

bioRxiv2022

Deep Learning Guided Diffusion MRI Tractography in the Mouse Brain

Diffusion MRI (dMRI) tractography is the only tool for non-invasive mapping of macroscopic structural connectivity over the entire brain. Although it has been successfully used to reconstruct large white matter tracts in the human and animal brains, the sensitivity and specificity of dMRI tractography remained limited. Especially, the fiber orientation distributions (FODs) estimated from dMRI signals, key to tractography, may deviate from histologically measured fiber orientation in crossing fibers and gray matter regions. In this study, we demonstrated that a deep learning network, trained using mesoscopic tract-tracing data from the Allen Mouse Brain Connectivity Atlas, was able to improve the estimation of FODs from mouse brain dMRI data. Tractography results based on the network generated FODs showed improved specificity while maintaining sensitivity comparable to results based on FOD estimated using a conventional spherical deconvolution method. Our result is a proof-of-concept of how mesoscale tract-tracing data can guide dMRI tractography and enhance our ability to characterize brain connectivity.

bioengineering↗

bioRxiv2022

Conserved and variable responses of the HEAT SHOCK FACTOR transcription factor family in maize and Setaria viridis

Responding to the environment is a core aspect of plant growth and development. Mounting an effective response is important for plants to balance growth and survival. The HEAT SHOCK FACTOR (HSF) transcription factor family is a central and required component of plant heat stress responses and acquired thermotolerance. The HSF family has dramatically expanded in plant lineages, often including a repertoire of 20 or more genes. Here we assess the composition and heat responsiveness of the HSF family in Setaria viridis (Setaria), a model C4 panicoid grass, and make targeted comparisons between the HSF families of Setaria and maize. Examples of both conserved and variable expression responses to a heat stress event were observed when comparing the two species. Novel and existing data on chromatin accessibility, histone modifications, and genome-wide DNA binding profiles were utilized to assess the chromatin of HSF family members with distinct responses to heat stress. We observed significant variability for both expression and chromatin state within syntenic and orthologous sets of HSFs between Setaria and maize, as well as between syntenic pairs of maize HSFs retained following its most recent genome duplication event. These observations collectively support a complex scenario of expansion and sub-functionalization within this transcription factor family that has significant untapped potential for better understanding the evolution of large gene families. Significance StatementA comparison of the Heat Shock Factor transcription factors in maize and Setaria reveals examples of consistent and variable expression responses to heat stress and provides insights into the role of chromatin in predicting expression responses.

plant biology↗