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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning

Abstract mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried out massively parallel kinetic decay measurements on over 50,000 bacterial mRNAs, using a learn-by-design approach to develop and validate a predictive sequence-to-function model of mRNA stability. mRNAs were designed to systematically vary translation rates, secondary structures, sequence compositions, G-quadruplexes, i-motifs, and RppH activity, resulting in mRNA half-lives from about 20 seconds to 20 minutes. We combined biophysical models and machine learning to develop steady-state and kinetic decay models of mRNA stability with high accuracy and generalizability, utilizing transcription rate models to identify mRNA isoforms and translation rate models to calculate ribosome protection. Overall, the developed model quantifies the key interactions that collectively control mRNA stability in bacterial operons and predicts how changing mRNA sequence alters mRNA stability, which is important when studying and engineering bacterial genetic systems.

Cetnar, Daniel P.↗
DOE OSTI2022

Identification of new marker genes from plant single‐cell RNA‐seq data using interpretable machine learning methods

Summary An essential step in the analysis of single‐cell RNA sequencing data is to classify cells into specific cell types using marker genes. In this study, we have developed a machine learning pipeline called single‐cell predictive marker (SPmarker) to identify novel cell‐type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning models to select marker genes. We have demonstrated that our method can: assign cell types based on cells that were labelled using published methods; project cell types identified by trajectory analysis from one data set to other data sets; and assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, the new marker genes have more orthologous genes identifiable in the corresponding rice single‐cell clusters. The new root hair marker genes also include 172 genes with orthologs expressed in root hair cells in five non‐ Arabidopsis species, which expands the number of marker genes for this cell type by 35–154%. Our results represent a new approach to identifying cell‐type marker genes from scRNA‐seq data and pave the way for cross‐species mapping of scRNA‐seq data in plants.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Ionizing radiation-induced mutagenesis: radiation studies in Neurospora predictive for results in mammalian cells

Ionizing radiation was the first mutagen discovered and was used to develop the first mutagenicity assay. In the ensuing 70+ years, ionizing radiation became a fundamental tool in understanding mutagenesis and is still a subject of intensive research. Frederick de Serres et al. developed and used the Neurospora crassa ad-3 system initially to explore the mutagenic effects of ionizing radiation. Using this system, de Serres et al. demonstrated the dependence of the frequency and spectra of mutations induced by ionizing radiation on the dose, dose rate, radiation quality, repair capabilities of the cells, and the target gene employed. This work in Neurospora predicted the subsequent observations of the mutagenic effects of ionizing radiation in mammalian cells. Modeled originally on the mouse specific-locus system developed by William L. Russell, the N. crassa ad-3 system developed by de Serres has itself served as a model for interpreting the results in subsequent systems in mammalian cells. This review describes the primary findings on the nature of ionizing radiation-induced mutagenesis in the N. crassa ad-3 system and the parallel observations made years later in mammalian cells.

NASA Discipline Radiation Health↗
DOE OSTI2022

Homologs of Phycobilisome Abundance Regulator PsoR Are Widespread across Cyanobacteria

During chromatic acclimation (CA), cyanobacteria undergo shifts in their physiology and metabolism in response to changes in their light environment. Various forms of CA, which involves the tuning of light-harvesting accessory complexes known as phycobilisomes (PBS) in response to distinct wavelengths of light, have been recognized. Recently, a negative regulator of PBS abundance, PsoR, about which little was known, was identified. We used sequence analyses and bioinformatics to predict the role of PsoR in cyanobacteria and PBS regulation and to examine its presence in a diverse range of cyanobacteria. PsoR has sequence similarities to the β-CASP family of proteins involved in DNA and RNA processing. PsoR is a putative nuclease widespread across Cyanobacteria, of which over 700 homologs have been observed. Promoter analysis suggested that psoR is co-transcribed with upstream gene tcpA. Multiple transcription factors involved in global gene regulation and stress responses were predicted to bind to the psoR-tcpA promoter. The predicted protein–protein interactions with PsoR homologs included proteins involved in DNA and RNA metabolism, as well as a phycocyanin-associated protein predicted to interact with PsoR from Fremyella diplosiphon (FdPsoR). The widespread presence of PsoR homologs in Cyanobacteria and their ties to DNA- and RNA-metabolizing proteins indicated a potentially unique role for PsoR in CA and PBS abundance regulation.

Layer, Alicia↗
NASA NTRS2000

A strong loss-of-function mutation in RAN1 results in constitutive activation of the ethylene response pathway as well as a rosette-lethal phenotype

A recessive mutation was identified that constitutively activated the ethylene response pathway in Arabidopsis and resulted in a rosette-lethal phenotype. Positional cloning of the gene corresponding to this mutation revealed that it was allelic to responsive to antagonist1 (ran1), a mutation that causes seedlings to respond in a positive manner to what is normally a competitive inhibitor of ethylene binding. In contrast to the previously identified ran1-1 and ran1-2 alleles that are morphologically indistinguishable from wild-type plants, this ran1-3 allele results in a rosette-lethal phenotype. The predicted protein encoded by the RAN1 gene is similar to the Wilson and Menkes disease proteins and yeast Ccc2 protein, which are integral membrane cation-transporting P-type ATPases involved in copper trafficking. Genetic epistasis analysis indicated that RAN1 acts upstream of mutations in the ethylene receptor gene family. However, the rosette-lethal phenotype of ran1-3 was not suppressed by ethylene-insensitive mutants, suggesting that this mutation also affects a non-ethylene-dependent pathway regulating cell expansion. The phenotype of ran1-3 mutants is similar to loss-of-function ethylene receptor mutants, suggesting that RAN1 may be required to form functional ethylene receptors. Furthermore, these results suggest that copper is required not only for ethylene binding but also for the signaling function of the ethylene receptors.

NASA Discipline Plant Biology↗
DOE OSTI2022

Predicting stress response and improved protein overproduction in Bacillus subtilis

Abstract Bacillus subtilis is a well-characterized microorganism and a model for the study of Gram-positive bacteria. The bacterium can produce proteins at high densities and yields, which has made it valuable for industrial bioproduction. Like other cell factories, metabolic modeling of B. subtilis has discovered ways to optimize its metabolism toward various applications. The first genome-scale metabolic model (M-model) of B. subtilis was published more than a decade ago and has been applied extensively to understand metabolism, to predict growth phenotypes, and served as a template to reconstruct models for other Gram-positive bacteria. However, M-models are ill-suited to simulate the production and secretion of proteins as well as their proteomic response to stress. Thus, a new generation of metabolic models, known as metabolism and gene expression models (ME-models), has been initiated. Here, we describe the reconstruction and validation of a ME model of B. subtilis , i JT964-ME. This model achieved higher performance scores on the prediction of gene essentiality as compared to the M-model. We successfully validated the model by integrating physiological and omics data associated with gene expression responses to ethanol and salt stress. The model further identified the mechanism by which tryptophan synthesis is upregulated under ethanol stress. Further, we employed i JT964-ME to predict amylase production rates under two different growth conditions. We analyzed these flux distributions and identified key metabolic pathways that permitted the increase in amylase production. Models like i JT964-ME enable the study of proteomic response to stress and the illustrate the potential for optimizing protein production in bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics

Limited therapy options due to antibiotic resistance underscore the need for optimization of current diagnostics. In some bacterial species, antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug-resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and expression profiles, we generated predictive models and identified biomarkers of resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8–0.9) or very high (> 0.9) sensitivity and predictive values. For all drugs except for ciprofloxacin, gene expression information improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers. Finally, the implementation of a molecular susceptibility test system in routine microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantitative Proteomics and Quantitative PCR as Predictors of cis -1,2-Dichlorethene and Vinyl Chloride Reductive Dechlorination Rates in Bioaugmented Aquifer Microcosms

Quantitative measurement of process-specific biomarker genes of Dehalococcoides mccartyi (Dhc) supports monitoring at chlorinated ethene contaminated sites. In this study, we varied Dhc cell abundances from ~103 to 108 cells/mL in aquifer microcosms and correlated the corresponding reductive dehalogenase (RDase) gene and RDase protein abundances with measured reductive dechlorination (RD) rates of cis-1,2-dichloroethene (cDCE) and vinyl chloride (VC). An additional set of microcosms tested the RD rate-predictive power of the regression analyses. These efforts revealed (1) that targeted proteomics quantifies Dhc biomarker proteins (e.g., TceA and VcrA, OmeA) over a relevant range of Dhc cell densities, and (2) that protein and gene abundances can predict RD rates. Protein detection limits translated to a rate coefficient of 10 –4 day –1 (0.04 year –1 ) for both k cDCE and k vc , which is within the range observed at sites undergoing monitored natural attenuation (MNA) (i.e., without the implementation of enhanced bioremediation treatment). Rates predicted using a combination of quantitative biomarker gene and protein measurements generally resulted in the best match with experimentally determined rate constants. These new findings provide evidence that quantitative biomarker measurements may be useful predictors of in situ RD rates, which would constitute a major advance for the cost-effective management of contaminated sites.

42 ENGINEERING↗
NASA NTRS2007

High-LET Patterns of DSBs in DNA Loops, the HPRT Gene and Phosphorylation Foci

We present new results obtained with our model based on the track structure and chromatin geometry that predicts the DSB spatial and genomic distributions in a cell nucleus with the full genome represented. The model generates stochastic patterns of DSBs in the physical space of the nucleus filled with the realistic configuration of human chromosomes. The model was re-used to find the distribution of DSBs in a physical volume corresponding to a visible phosphorylation focus believed to be associated with a DSB. The data shows whether there must more than one DSB per foci due to finite size of the visible focus, even if a single DSB is radiochemically responsible for the phosphorylation of DNA in its vicinity. The same model can predict patterns of closely located DSBs in a given gene, or in a DNA loop, one of the large-scale chromatin structures. We demonstrated for the example of the HPRT gene, how different sorts of radiation lead to proximity effect in DSB locations, which is important for modeling gene deletions. The spectrum of intron deletions and total gene deletions was simulated for the HPRT gene. The same proximity effect of DSBs in a loop can hinder DSB restitutions, as parts of the loop between DSBs is deleted with a higher likelihood. The distributions of DSBs and deletions of DNA in a loop are presented.

Ponomarev, Artem L.↗
DOE OSTI2024

Predicting Anaerobic Membrane Bioreactor Performance Using Flow-Cytometry-Derived High and Low Nucleic Acid Content Cells

Having a tool to monitor the microbial abundances rapidly and to utilize the data to predict the reactor performance would facilitate the operation of an anaerobic membrane bioreactor (AnMBR). This study aims to achieve the aforementioned scenario by developing a linear regression model that incorporates a time-lagging mode. The model uses low nucleic acid (LNA) cell numbers and the ratio of high nucleic acid (HNA) to LNA cells as an input data set. First, the model was trained using data sets obtained from a 35 L pilot-scale AnMBR. The model was able to predict the chemical oxygen demand (COD) removal efficiency and methane production 3.5 days in advance. Subsequent validation of the model using flow cytometry (FCM)-derived data (at time t – 3.5 days) obtained from another biologically independent reactor did not exhibit any substantial difference between predicted and actual measurements of reactor performance at time t. Further cell sorting, 16S rRNA gene sequencing, and correlation analysis partly attributed this accurate prediction to HNA genera (e.g., Anaerovibrio and unclassified Bacteroidales) and LNA genera (e.g., Achromobacter, Ochrobactrum, and unclassified Anaerolineae). In summary, our findings suggest that HNA and LNA cell routine enumeration, along with the trained model, can derive a fast approach to predict the AnMBR performance.

42 ENGINEERING↗
DOE OSTI2021

Nonadditive gene expression is correlated with nonadditive phenotypic expression in interspecific triploid hybrids of willow ( Salix spp.)

Many studies have highlighted the complex and diverse basis for heterosis in inbred crops. Despite the lack of a consensus model, it is vital that we turn our attention to understanding heterosis in undomesticated, heterozygous, and polyploid species, such as willow (Salix spp.). Shrub willow is a dedicated energy crop bred to be fast-growing and high yielding on marginal land without competing with food crops. A trend in willow breeding is the consistent pattern of heterosis in triploids produced from crosses between diploid and tetraploid species. Here, we test whether differentially expressed genes are associated with heterosis in triploid families derived from diploid Salix purpurea, diploid Salix viminalis, and tetraploid Salix miyabeana parents. Three biological replicates of shoot tips from all family progeny and parents were collected after 12 weeks in the greenhouse and RNA extracted for RNA-Seq analysis. This study provides evidence that nonadditive patterns of gene expression are correlated with nonadditive phenotypic expression in interspecific triploid hybrids of willow. Expression-level dominance was most correlated with heterosis for biomass yield traits and was highly enriched for processes involved in starch and sucrose metabolism. In addition, there was a global dosage effect of parent alleles in triploid hybrids, with expression proportional to copy number variation. Importantly, differentially expressed genes between family parents were most predictive of heterosis for both field and greenhouse collected traits. Altogether, these data will be used to progress models of heterosis to complement the growing genomic resources available for the improvement of heterozygous perennial bioenergy crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

In silico analyses of diversity and dissemination of antimicrobial resistance genes and mobile genetics elements, for plasmids of enteric pathogens

The antimicrobial resistance (AMR) mobilome plays a key role in the dissemination of resistance genes encoded by mobile genetics elements (MGEs) including plasmids, transposons (Tns), and insertion sequences (ISs). These MGEs contribute to the dissemination of multidrug resistance (MDR) in enteric bacterial pathogens which have been considered as a global public health risk. To further understand the diversity and distribution of AMR genes and MGEs across different plasmid types, we utilized multiple sequence-based computational approaches to evaluate AMR-associated plasmid genetics. A collection of 1,309 complete plasmid sequences from Gammaproteobacterial species, including 100 plasmids from each of the following 14 incompatibility (Inc) types: A/C, BO, FIA, FIB, FIC, FIIA, HI1, HI2, I1, K, M, N, P except W, where only 9 sequences were available, was extracted from the National Center for Biotechnology Information (NCBI) GenBank database using BLAST tools. The extracted FASTA files were analyzed using the AMRFinderPlus web-based tools to detect antimicrobial, disinfectant, biocide, and heavy metal resistance genes and ISFinder to identify IS/Tn MGEs within the plasmid sequences. In silico prediction based on plasmid replicon types showed that the resistance genes were diverse among plasmids, yet multiple genes were widely distributed across the plasmids from enteric bacterial species. These findings provide insights into the diversity of resistance genes and that MGEs mediate potential transmission of these genes across multiple plasmid replicon types. This notion was supported by the observation that many IS/Tn MGEs and resistance genes known to be associated with them were common across multiple different plasmid types. Our results provide critical insights about how the diverse population of resistance genes that are carried by the different plasmid types can allow for the dissemination of AMR across enteric bacteria. The results also highlight the value of computational-based approaches and in silico analyses for the assessment of AMR and MGEs, which are important elements of molecular epidemiology and public health outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

MAL33 drives natural variation in maltose metabolism in Saccharomyces eubayanus

Maltose is one of the most abundant sugars in brewer’s wort, and its efficient utilization is critical for successful fermentation. However, maltose consumption varies naturally among Saccharomyces eubayanus strains isolated from different host trees, such as Quercus and Nothofagus. To identify the genetic determinants underlying these phenotypic differences, we performed bulk segregant analysis (BSA) and quantitative trait loci (QTL) mapping using an F 2 offspring derived from QC18 (Quercus-associated) and CL467.1 (Nothofagus-associated) strains. QTL mapping identified two significant genomic regions on subtelomeric loci of chromosomes V-R and XVI-L, each containing complete MAL loci composed of MAL32 (encoding maltase), MAL31 (transporter), and MAL33 (transcriptional activator) genes. Comparative polymorphism analyses identified mutations in MAL32 and MAL33 of QC18, including frameshift mutations resulting in premature stop codons. Functional validation demonstrated that the heterologous expression of MAL33 ChrV from CL467.1 fully restored maltose utilization in QC18, indicating the functional presence of MAL33 cis-regulatory sequences and MAL32 and MAL31 genes in QC18. While structural protein predictions identified truncation and impaired functionality in the maltose-responsive activation domain of Mal33p from QC18, overexpression of QC18’s own MAL33 ChrV allele also improved maltose metabolism, suggesting dosage-dependent transcriptional limitations rather than complete functional loss. These results indicate that allelic variations in the maltose-responsive activation domain of Mal33p result in differences in maltose consumption between strains. Here, we hypothesized that reduced maltose metabolism in QC18 is an adaptive response to the distinct sugar composition in Quercus robur bark, contrasting with the starch-rich environment of Nothofagus pumilio. These findings highlight subtelomeric MAL gene diversity as a reservoir of genetic variation, representing a key evolutionary mechanism that influences maltose adaptation among natural Saccharomyces isolates.

evolutionary plasticity↗
DOE OSTI2022

The essential Rhodobacter sphaeroides CenKR two-component system regulates cell division and envelope biosynthesis

Bacterial two-component systems (TCSs) often function through the detection of an extracytoplasmic stimulus and the transduction of a signal by a transmembrane sensory histidine kinase. This kinase then initiates a series of reversible phosphorylation modifications to regulate the activity of a cognate, cytoplasmic response regulator as a transcription factor. Several TCSs have been implicated in the regulation of cell cycle dynamics, cell envelope integrity, or cell wall development in Escherichia coli and other well-studied Gram-negative model organisms. However, many α-proteobacteria lack homologs to these regulators, so an understanding of how α-proteobacteria orchestrate extracytoplasmic events is lacking. In this work we identify an essential TCS, CenKR ( C ell en velope K inase and R egulator), in the α-proteobacterium Rhodobacter sphaeroides and show that modulation of its activity results in major morphological changes. Using genetic and biochemical approaches, we dissect the requirements for the phosphotransfer event between CenK and CenR, use this information to manipulate the activity of this TCS in vivo , and identify genes that are directly and indirectly controlled by CenKR in Rb . sphaeroides . Combining ChIP-seq and RNA-seq, we show that the CenKR TCS plays a direct role in maintenance of the cell envelope, regulates the expression of subunits of the Tol-Pal outer membrane division complex, and indirectly modulates the expression of peptidoglycan biosynthetic genes. CenKR represents the first TCS reported to directly control the expression of Tol-Pal machinery genes in Gram-negative bacteria, and we predict that homologs of this TCS serve a similar function in other closely related organisms. We propose that Rb . sphaeroides genes of unknown function that are directly regulated by CenKR play unknown roles in cell envelope biosynthesis, assembly, and/or remodeling in this and other α-proteobacteria.

Lakey, Bryan D. (ORCID:0000000332795242)↗
NASA NTRS2017

Ionizing Radiation Affects Gene Expression in Mouse Skin and Bone

Future long-duration space exploration beyond low earth orbit will increase human exposure to space radiation and microgravity conditions as well as associated risks to skeletal health. In animal studies, radiation exposure (greater than 1 Gy) is associated with pathological changes in bone structure, enhanced bone resorption, reduced bone formation and decreased bone mineral density, which can lead to skeletal fragility. Definitive measurements and detection of bone loss typically require large and specialized equipment which can make their application to long duration space missions logistically challenging. Towards the goal of developing non-invasive and less complicated monitoring methods to predict astronauts' health during spaceflight, we examined whether radiation induced gene expression changes in skin may be predictive of the responses of skeletal tissue to radiation exposure. We examined oxidative stress and growth arrest pathways in mouse skin and long bones by measuring gene expression levels via quantitative polymerase chain reaction (qPCR) after exposure to total body irradiation (IR). To investigate the effects of irradiation on gene expression, we used skin and femora (cortical shaft) from the following treatment groups: control (normally loaded, sham-irradiated), and IR (0.5 Gy 56Fe 600 MeV/n and 0.5 Gy 1H 150 MeV/n), euthanized at one and 11 days post-irradiation (IR). To determine the extent of bone loss, tibiae were harvested and cancellous microarchitecture in the proximal tibia quantified ex vivo using microcomputed tomography (microCT). Statistical analysis was performed using Student's t-test. At one day post-IR, expression of FGF18 in skin was significantly greater (3.8X) than sham-irradiated controls, but did not differ at 11 days post IR. Expression levels of other genes associated with antioxidant response (Nfe2l2, FoxO3 and Sod1) and the cell cycle (Trp53, Cdkn1a, Gadd45g) did not significantly differ between the control and IR groups at either time point. Radiation exposure resulted in a 27.0% increase in FGF18-positive hair follicles at one day post-IR and returned to basal levels at 11 days post-IR. A similar trend was observed from FGF18 gene expression analysis of skin. In bone (femora), there was an increase in the expression of the pro-osteoclastogenic cytokine, MCP-1, one day after IR compared to non-irradiated controls. FGF18 expression in skin and MCP- 1 expression in bone were found to be positively correlated (P less than 0.002, r=0.8779). Further, microcomputed tomography analysis of tibia from these animals showed reduced cancellous bone volume (-9.9%) at 11 days post- IR. These results suggest that measurements of early radiation induced changes in FGF18 gene expression in skin may have value for predicting subsequent loss of cancellous bone mass. Further research may lead to the development of a relatively simple diagnostic tool for bone loss, with the advantage that hair follicles and skin are relatively easy to acquire from human subjects.

space radiation↗
DOE OSTI2020

Predicting the chemical space of fungal polyketides by phylogeny-based bioinformatics analysis of polyketide synthase-nonribosomal peptide synthetase and its modification enzymes

Fungal polyketide synthase (PKS)–nonribosomal peptide synthetase (NRPS) hybrids are key enzymes for synthesizing structurally diverse hybrid natural products (NPs) with characteristic biological activities. Predicting their chemical space is of particular importance in the field of natural product chemistry. However, the unexplored programming rule of the PKS module has prevented prediction of its chemical structure based on amino acid sequences. Here, we conducted a phylogenetic analysis of 884 PKS–NRPS hybrids and a modification enzyme analysis of the corresponding biosynthetic gene cluster, revealing a hidden relationship between its genealogy and core structures. This unexpected result allowed us to predict 18 biosynthetic gene cluster (BGC) groups producing known carbon skeletons (number of BGCs; 489) and 11 uncharacterized BGC groups (171). The limited number of carbon skeletons suggests that fungi tend to select PK skeletons for survival during their evolution. The possible involvement of a horizontal gene transfer event leading to the diverse distribution of PKS–NRPS genes among fungal species is also proposed. This study provides insight into the chemical space of fungal PKs and the distribution of their biosynthetic gene clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A semidominant point mutation of Mediator tail subunit MED5b in Arabidopsis leads to altered enrichment of H3K27me3 and reduced expression of targets of MYC2

Abstract The Mediator complex coordinates regulatory input for transcription driven by RNA polymerase II in eukaryotes. reduced epidermal fluorescence4-3 (ref4-3) is a semidominant mutation that results in a single amino acid substitution in the Mediator tail subunit Med5b. Previous characterization of ref4-3 revealed altered expression of a variety of loci in Arabidopsis, including those contributing to phenylpropanoid biosynthesis. Examination of existing RNA-seq data indicated that loci enriched for the transcriptionally repressive chromatin modification H3K27me3 are overrepresented among genes that are misregulated in ref4-3. We used ChIP-seq and RNA-seq to examine the possibility that perturbation of H3K27me3 homeostasis in ref4-3 plants contributed to altered transcript levels. We observed that ref4-3 results in a modest global reduction of H3K27me3 at enriched loci and that this reduction is not dependent on gene expression; however, altered H3K27me3 was not strongly predictive of altered expression in ref4-3 plants. Instead, our analyses revealed a substantial enrichment of targets of the MYC2 transcriptional regulator among genes that exhibit decreased expression in ref4-3. Consistent with previous characterization of ref4-3, we observed that ref4-3-dependent decreased expression of MYC2 targets can be suppressed by loss of another Mediator tail subunit, MED25. This observation is consistent with previous biochemical characterization of MYC2. Our data highlight the diverse and distinct impacts that a single amino acid change in the tail subunit of Mediator can have on transcriptional circuits and raise the prospect that Mediator directly contributes to H3K27me3 homeostasis in plants.

Long, Jiaxin (ORCID:0000000335150706)↗
DOE OSTI2024

Integrated transcriptomic and metabolomic investigation of the genes and metabolites involved in swine follicular cyst formation

Follicular cysts are a common reproductive disorder in mammals that is usually caused by stress. However, the pathogenesis of follicular cysts in sows remains unclear. To provide new insights into the mechanisms of follicular cyst formation in pigs, we conducted a combined transcriptomic and metabolomic analysis on theca interna and mural granulosa cells of follicular cysts and mature follicles. We identified 2,533 up-regulated and 1,355 down-regulated genes in follicular cysts, compared with mature follicles. These differentially expressed genes were mainly found in signaling pathways related to tumor formation and cortisol synthesis and secretion as shown by Ingenuity Pathway Analysis, which predicted 4,362 upstream regulatory factors. The combined gene expression and pathway analysis identified the following genes as potential biomarkers for porcine follicular cysts: cytochrome P450 family 2 subfamily C polypeptide 18, L-lactate dehydrogenase, carbamoyl-phosphate synthase, fibroblast growth factor 7, integrin binding sialoprotein, interleukin 23 receptor, prolactin receptor, epiregulin, interleukin 1 receptor type II, arginine vasopressin receptor 1A, fibroblast growth factor 10, claudin 7, G Protein Subunit Gamma 3, cholecystokinin B receptor and cytosolic phospholipase A2 . Metabolomics analysis found significant differences in 87 metabolites, which were enriched in unsaturated fatty acid biosynthesis, and sphingolipid signaling pathways. These results provide valuable information on the molecular mechanisms of follicular cyst formation, which may facilitate the development of new therapeutics to prevent and treat follicular cysts.

Dai, Jiage↗