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At least 73 records · Page 4

Morpho-physiological and transcriptomic responses of field pennycress to waterlogging

Field pennycress (Thlaspi arvense) is a new biofuel winter annual crop with extreme cold hardiness and a short life cycle, enabling off-season integration into corn and soybean rotations across the U.S. Midwest. Pennycress fields are susceptible to winter snow melt and spring rainfall, leading to waterlogged soils. The objective of this research was to determine the extent to which waterlogging during the reproductive stage affected gene expression, morphology, physiology, recovery, and yield between two pennycress lines (SP32-10 and MN106). In a controlled environment, total pod number, shoot/root dry weight, and total seed count/weight were significantly reduced in SP32-10 in response to waterlogging, whereas primary branch number, shoot dry weight, and single seed weight were significantly reduced in MN106. This indicated waterlogging had a greater negative impact on seed yield in SP32-10 than MN106. We compared the transcriptomic response of SP32-10 and MN106 to determine the gene expression patterns underlying these different responses to seven days of waterlogging. The number of differentially expressed genes (DEGs) between waterlogged and control roots were doubled in MN106 (3,424) compared to SP32-10 (1,767). Functional enrichment analysis of upregulated DEGs revealed Gene Ontology (GO) terms associated with hypoxia and decreased oxygen, with genes in these categories encoding proteins involved in alcoholic fermentation and glycolysis. Additionally, downregulated DEGs revealed GO terms associated with cell wall biogenesis and suberin biosynthesis, indicating suppressed growth and energy conservation. Interestingly, MN106 waterlogged roots exhibited significant stronger regulation of these genes than SP32-10, displaying a more robust transcriptomic response overall. Together, these results reveal the reconfiguration of cellular and metabolic processes in response to the severe energy crisis invoked by waterlogging in pennycress.

ERF-VII↗

Phenotypically anchored transcriptomics across diverse agrichemicals reveals conserved pathways and unique gene expression signatures in zebrafish

Agrichemicals such as herbicides, fungicides, insecticides, and biocides are widely used in agriculture, yet some are associated with adverse effects in humans and the environment. While many of these chemicals have been extensively studied in vitro and are included in the EPA’s ToxCast program, comprehensive in vivo comparisons using RNA sequencing across structurally diverse agrichemicals, in a single screening platform, are lacking. In this study, we examined structurally diverse agrichemicals found in the U.S. Environmental Protection Agency’s (EPA) Toxcast Phase I and II library by statically exposing early life stage zebrafish at 6 h post fertilization (hpf) until 120 hpf at concentrations ranging from 0.25 to 100 µM. Morphological outcomes were assessed at 120 hpf across 10 endpoints, including yolk sac edema, craniofacial malformations, and axis abnormalities. Chemicals that produced robust concentration-response relationships were selected for transcriptomic profiling. For transcriptomic analysis, zebrafish were statically exposed to each chemical and sampled at 48 hpf, prior to the onset of morphological effects observed at 120 hpf. Differential expression analysis identified between 0 and 4,538 differentially expressed genes (DEGs) per chemical, with no clear correlation to morphological severity. Both DEG and co-expression network analyses revealed chemical-specific expression patterns that converged on shared biological pathways, including neurodevelopment and cytoskeletal organization. Key regulatory genes such as mylpfa and krt4 were identified within co-expression modules, suggesting their potential role in conserved toxicity mechanisms. Semantic similarity analysis of enriched gene ontology (GO) terms, when compared to existing datasets, highlighted gaps in the annotation of neurodevelopmental processes, indicating that some in vivo effects may not be fully captured by current curated resources. The results provide new insights into the modes of action of diverse agrichemicals and establish a framework for understanding how agrichemical structure relates to biological function in a vertebrate model.

agrichemical↗

Transcriptomics outputs and phylogenetic trees used for pathway discovery of diterpenoid alkaloids in Delphinium and Aconitum

Transcriptome assemblies, open reading frames in nucleotide and peptide sequences, clustered transcriptomes and corresponding amino acid files, and expression matrices in TPM and raw counts for RNA-seq datasets from Delphinium grandiflorum, Aconitum plicatum, Aconitum lycoctonum, Aconitum carmichaelii, Aconitum japonicum, Aconitum kusnezoffii, and Aconitum vilmorinianum. Also included are phylogenetic trees for terpene synthases and cytochromes P450 mined from these assemblies.

biosynthesis↗

Zymomonas mobilis oxidative stress transcriptomics

Zymomonas mobilis is an important bioenergy organism that has potential to produce biofuels, including ethanol, in high volumes. Here we examined the response of Zymomonas mobilis to various oxidative stresses using genome-scale transcriptomics data. We first examined the transcrpit abundance in WT aerobic growth compared to aerobic grown in paraquat, which forms superoxide. Under anaerobic growth conditions we compared WT Zymomonas mobilis with strains grown in media lacking iron as well as strains lacking iron that were treated with the iron chelator DIP before collection. Finally we examined transcript abundance in cells lacking ZMO_0422 (Rrf2 family transcription factor homolog) and ZMO_1411 (Fur homolog) grown under anaerobic conditions. Overall design: Transcriptomic analysis of WT, a deletion of ZMO_0422, and a deletion of ZMO_1411 in Zymomonas mobilis ZM4 under aerobic and anaerobic growth conditions along with various oxidative stresses: Paraquate addition, No Iron, and hydrogen peroxide addition.

aerobic↗

Transcriptomics and Proteomics Discussion

This presentation will cover the the basic pipelines for transcriptomics and proteomics that the GeneLab Analysis Working Groups (AWGs) have so far determined to be optimal. Basic transcriptomic pipelines will first be presented from primary analysis to higher-order systems analysis. Examples of how the data has been analyzed will be presented. Proteomics pipelines will also be presented compiled from various AWG members. Discussion will be generated from the AWG members to reach a consensus for each omic type.

Transcriptomics↗

Bionutrients-1: Utilizing Genomics and Transcriptomics to Assess the Reliability of Microorganisms for In Situ Nutrient Production on Long Duration Missions

The resupply of current long-duration crewed missions to the ISS relies on ground-launched supplies. As NASA looks toward Mars, ground-based resupply will no longer be an option. Critical nutrients, including vitamin C, vitamin K, folate, and thiamin, degrade during long-term storage, and regular consumption of these nutrients is essential for astronaut health. Another challenge of current food systems is the difficulty of consuming sufficient calories when subsisting on the limited flavors of freeze-dried food, which can lead to weight loss. The inclusion of microorganism-based food systems could alleviate both concerns. For example, the fermentation of rehydrated milk into yogurt with microorganisms genetically incorporating genes to produce critical vitamins would allow for both in situ production of nutrients and a fresh food product with additional flavor profiles. In comparison to plant food production, microorganisms require less flight infrastructure. The BioNutrients-1 mission is demonstrating viability of microbial fermentation food production in microgravity and testing the reliability of this approach for long-duration missions lacking resupply. While the BioNutrients-1 mission includes the collection of multiple phenotypic measurements, this status update will focus on the processing of samples for genomics and transcriptomics analyses as well as the planned analysis pipelines. First, the BioNutrients-1 mission seeks to identify microorganisms capable of surviving long-duration storage at ambient temperatures while maintaining genetic fidelity. To achieve this, nine commonly employed microbial species were stored at ambient temperatures in Stasis Packs on the ISS for five years. The viability and mutation rates will be measured at multiple time points for both flown and ground control samples. From an omics perspective, the changes in the bulk rates of point mutations and genetic rearrangements across the Stasis Pack species during the five years of storage will be determined, providing valuable insights into the potential of these microorganisms for long-duration space missions. Second, the BioNutrients-1 mission is characterizing the impact of microgravity on fermentation. Two strains of the yeast Saccharomyces cerevisiae, each encoding antioxidants (β-carotene or zeaxanthin) were flown to ISS for storage and fermentation within simplified bioreactors (Production Packs). The impact of microgravity on the expression of the antioxidant production genes and general metabolic genes will be determined using RNA sequencing. Ultimately, the transcriptome data will be compared to phenotypic measurements, such as the antioxidant yield, end-state biomass, and the production of EtOH, to determine the impacts of microgravity and long-term storage on microbial fermentation. The findings from this research will be instrumental in understanding the challenges and opportunities of microorganism-based food systems in space missions.

BioNutrients↗

RNAseq-based transcriptome assembly of Clostridium acetobutylicum for functional genome annotation and discovery

Accurate genome annotations are essential in modern biology and biotechnology, yet they are still largely based on genome sequencing and comparative analyses. We show that the Clostridium acetobutylicum genome annotation can be markedly improved by integrating bioinformatic predictions with RNA sequencing (RNAseq) data. Samples were acquired under butanol, butyrate, and unstressed treatments across various growth conditions. Analysis of an initial assembly revealed errors due to background signals and limitations of assembly algorithms. Hurdles for RNAseq transcriptome mapping include optimizing library complexity and sequencing depth, yet most studies report low sequencing depth and ignore the effect of ribosomal RNA abundance. An integrative analysis was developed to combine motif predictions, single-nucleotide resolution sequencing depth, and library complexity to resolve difficulties in assembly curation. This minimized false positive error and determined gene boundaries, in some cases, to the exact base-pair of prior studies. This will be the first strand-specific transcriptome assembly in a Clostridium organism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transcriptome and metabolome integration in sugarcane through culm development

Abstract Sugarcane (Saccharum sp.) is a tropical and subtropical C4 plant with a high photosynthetic and carbon assimilation efficiency that stores sucrose. Culm biomass is also composed of bagasse fibre, a by‐product of the sugarcane industry. This high‐yielding grass, high in sucrose and lignocellulosic biomass, is considered an optimal feedstock as an alternative to fossil fuels and to produce a broad range of high‐value biomaterials. The ideal sugarcane production system would optimise the relative production of sugar and these new products. Multi‐omics correlation analysis was used to generate a global view of the essential metabolic pathways identifying critical genes involved in carbon partitioning during different stages of development. This research employed an unprecedented metabolic and transcriptomic dataset of 360 samples from a selection of 1440 culms of 24 genotypes at five different development stages. Chemical composition and metabolome analysis showed an increase through the culm development of lignin, sucrose, carbon, and amino acids such as aspartic acid, serine, alanine, methionine, threonine 3‐cyano‐L‐alanine, and citric acid. Transcriptome analysis revealed functionalities such as transcription, nucleotide transport and metabolism, and the biosynthesis of amino acids that are highly activated during the immature stage and highly down‐regulated during the most mature age.

Perlo, Virginie↗

The single-cell transcriptome program of nodule development cellular lineages in Medicago truncatula

Legumes establish a symbiotic relationship with nitrogen-fixing rhizobia by developing nodules. Nodules are modified lateral roots that undergo changes in their cellular development in response to bacteria, but the transcriptional reprogramming that occurs in these root cells remains largely uncharacterized. Here, we describe the cell-type-specific transcriptome response of Medicago truncatula roots to rhizobia during early nodule development in the wild-type genotype Jemalong A17, complemented with a hypernodulating mutant (sunn-4) to expand the cell population responding to infection and subsequent biological inferences. The analysis identifies epidermal root hair and stele sub-cell types associated with a symbiotic response to infection and regulation of nodule proliferation. Trajectory inference shows cortex-derived cell lineages differentiating to form the nodule primordia and, posteriorly, its meristem, while modulating the regulation of phytohormone-related genes. Gene regulatory analysis of the cell transcriptomes identifies new regulators of nodulation, including STYLISH 4, for which the function is validated.

Cell Biology↗

Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome

The transcriptional regulatory network (TRN) of Bacillus subtilis coordinates cellular functions of fundamental interest, including metabolism, biofilm formation, and sporulation. Here, we use unsupervised machine learning to modularize the transcriptome and quantitatively describe regulatory activity under diverse conditions, creating an unbiased summary of gene expression. We obtain 83 independently modulated gene sets that explain most of the variance in expression and demonstrate that 76% of them represent the effects of known regulators. The TRN structure and its condition-dependent activity uncover putative or recently discovered roles for at least five regulons, such as a relationship between histidine utilization and quorum sensing. The TRN also facilitates quantification of population-level sporulation states. As this TRN covers the majority of the transcriptome and concisely characterizes the global expression state, it could inform research on nearly every aspect of transcriptional regulation in B. subtilis.

59 BASIC BIOLOGICAL SCIENCES↗

An integrated metagenomic, metabolomic and transcriptomic survey of Populus across genotypes and environments

Abstract Bridging molecular information to ecosystem-level processes would provide the capacity to understand system vulnerability and, potentially, a means for assessing ecosystem health. Here, we present an integrated dataset containing environmental and metagenomic information from plant-associated microbial communities, plant transcriptomics, plant and soil metabolomics, and soil chemistry and activity characterization measurements derived from the model tree species Populus trichocarpa . Soil, rhizosphere, root endosphere, and leaf samples were collected from 27 different P. trichocarpa genotypes grown in two different environments leading to an integrated dataset of 318 metagenomes, 98 plant transcriptomes, and 314 metabolomic profiles that are supported by diverse soil measurements. This expansive dataset will provide insights into causal linkages that relate genomic features and molecular level events to system-level properties and their environmental influences.

59 BASIC BIOLOGICAL SCIENCES↗

Regulators of early maize leaf development inferred from transcriptomes of laser capture microdissection (LCM)-isolated embryonic leaf cells

The superior photosynthetic efficiency of C 4 leaves over C 3 leaves is owing to their unique Kranz anatomy, in which the vein is surrounded by one layer of bundle sheath (BS) cells and one layer of mesophyll (M) cells. Kranz anatomy development starts from three contiguous ground meristem (GM) cells, but its regulators and underlying molecular mechanism are largely unknown. To identify the regulators, we obtained the transcriptomes of 11 maize embryonic leaf cell types from five stages of pre-Kranz cells starting from median GM cells and six stages of pre-M cells starting from undifferentiated cells. Principal component and clustering analyses of transcriptomic data revealed rapid pre-Kranz cell differentiation in the first two stages but slow differentiation in the last three stages, suggesting early Kranz cell fate determination. In contrast, pre-M cells exhibit a more prolonged transcriptional differentiation process. Differential gene expression and coexpression analyses identified gene coexpression modules, one of which included 3 auxin transporter and 18 transcription factor (TF) genes, including known regulators of Kranz anatomy and/or vascular development. In situ hybridization of 11 TF genes validated their expression in early Kranz development. We determined the binding motifs of 15 TFs, predicted TF target gene relationships among the 18 TF and 3 auxin transporter genes, and validated 67 predictions by electrophoresis mobility shift assay. From these data, we constructed a gene regulatory network for Kranz development. Our study sheds light on the regulation of early maize leaf development and provides candidate leaf development regulators for future study.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of candidate host-specificity genes in Exserohilum turcicum using comparative genomics and transcriptomics

Abstract Exserohilum turcicum causes northern corn leaf blight and sorghum leaf blight. While the same species cause disease in both crops, the strains are host-specific. Here, we report the sequence and de novo annotated assemblies of one sorghum- and one maize-specific E. turcicum strain. The strains were sequenced using the PacBio Sequel II system. The total genome length for both assemblies was between 44 and 45 Mb with N50 of ∼2.5 Mb. Ninety-eight percent of the Benchmarking Universal Single-Copy Orthologs (BUSCO) for both assemblies had complete status. The estimated number of genes was 11,762 and 12,029 in the sorghum- and maize-specific isolates, respectively. Funannotate, EffectorP, SignalP, and transcriptome data were used to create functional annotation of each genome. The whole-genome comparison identified ten large-scale inversions and three translocations between the maize- and sorghum-specific strains, along with homologous genes and gene duplications. RNA was sequenced from the maize- and sorghum-specific isolate 10 days post-inoculation in maize and sorghum and from axenic cultures. Gene expression data from planta and axenic growth experiments were compared for each strain. Candidate host-specificity genes were identified by combining results from whole-genome comparison, synteny analysis, gene annotations, and transcriptome data. Overall, this study identified several candidate host-specificity genes that provide insights into E. turcicum interaction with its hosts.

Krone, Mara J. (ORCID:0000000159006624)↗

Genomic and transcriptomic characterization of carbohydrate-active enzymes in the anaerobic fungus Neocallimastix cameroonii var. constans

Anaerobic gut fungi effectively degrade lignocellulose in the guts of large herbivores, but there remain a limited number of isolated, publicly available, and sequenced strains that impede our understanding of the role of anaerobic fungi within microbial communities. We isolated and characterized a new fungal isolate, Neocallimastix cameroonii var. constans, providing a transcriptomic and genomic understanding of its ability to degrade diverse carbohydrates. This anaerobic fungal strain was stably cultivated for multiple years in vitro among members of an initial enrichment microbial community derived from goat feces, and it demonstrated the ability to pair with other microbial members, namely, archaeal methanogens to produce methane from lignocellulose. Genomic analysis revealed a higher number of predicted carbohydrate-active enzymes encoded in the N. cameroonii var. constans genome compared to most other sequenced anaerobic fungi. The carbohydrate-active enzyme profile for this isolate contained 660 glycoside hydrolases, 160 carbohydrate esterases, 194 glycosyltransferases, and 85 polysaccharide lyases. Differential gene expression analysis showed the upregulation of thousands of genes (including predicted carbohydrate-active enzymes) when N. cameroonii var. constans was grown on lignocellulose (reed canary grass) compared to less complex substrates, such as cellulose (filter paper), cellobiose, and glucose. AlphaFold was used to predict functions of transcriptionally active yet poorly annotated genes, revealing feruloyl esterases that likely play an important role in lignocellulose degradation by anaerobic fungi. The combination of this strain's genomic and transcriptomic characterization, omics-informed structural prediction, and robustness in microbial co-culture make it a well-suited platform to conduct future investigations into bioprocessing and enzyme discovery.

CAZymes↗

De novo transcriptome sequencing of Capsicum frutescens . L and comprehensive analysis of salt stress alleviating mechanism by Bacillus atrophaeus WU ‐9

Abstract Salt stress, as one of the most severe environmental stresses, can cause a series of changes in plants. However, the explanation of plant salt stress alleviating mechanism of plant growth–promoting rhizobacteria (PGPR) was hindered by the limited availability of transcriptomic information for salt stress‐treated plants grown in a microorganism‐controlled environment. Our previous reports have selected Bacillus atrophaeus WU‐9 as PGPR significantly alleviating pepper ( Capsicum frutescens . L) salt stress. In this work, the RNA‐seq analysis of salt stress‐treated and untreated plants, grown with and without WU‐9 in a microorganism‐controlled environment, was used to reveal the plant salt stress alleviating mechanisms of WU‐9. Twelve sequencing libraries, prepared by treating with WU‐9 and salt (150 mM NaCl for 36 h), were constructed by RNA‐Seq technique. Non‐inoculated seedlings mainly respond to salt stress through regulation of signal transduction, such as ethylene‐activated signaling pathway, signaling and cell communication, etc. And ethylene signal participated in salt stress response in pepper through regulating defense responses, fruit ripening and senescence. WU‐9 inoculation under salt stress mainly improves salt tolerance and plant growth by regulating salt stress‐responding ethylene and auxin signal transduction, utilization of proline, photosynthesis, antioxidant enzyme activities and cell enlargement. Furthermore, 86 differentially expressed genes and 20 transcription factors were identified as associated with salt stress response and tolerance. Thus, this innovative transcriptomic study identified the salt stress response and alleviation in C. frutescens . L with PGPR inoculation. This result provided novel insights into the salinity alleviation in pepper regulated by PGPR.

Wang, Wenfei↗

Hidden diversity: Transcriptomic and photosynthetic variation among common ‘wild type’ Chlamydomonas strains

The unicellular green alga Chlamydomonas reinhardtii is a widely studied reference organism, particularly in photosynthesis research. It employs photoprotective mechanisms, such as state transitions (ST) and non-photochemical quenching (NPQ), to cope with rapid light changes. Most widely used strains share a recent common ancestor yet differ by up to ~50 000 nuclear variants—genetic diversity that is often overlooked. Even among ‘wild type’ strains, we document significant phenotypic differences, such as pigment accumulation, and nutrient utilization. To elucidate the basis for this variation, we compared transcriptomes and physiological traits of seven commonly used laboratory strains, including the reference strain and the CLiP mutant library parental strain. Despite identical growth conditions, ~40% of genes were differentially expressed between strains. Most of these differences are attributable to changes that have accrued during laboratory propagation, and adverse conditions may have driven transcriptomic drift. At the physiological level, we catalog the range of strain-dependent responses related to photosynthesis and high light (HL) acclimation. Specifically, (i) all strains develop NPQ upon HL exposure, but to various degrees, (ii) they show a substantial variation in ST capacity, and (iii) they regulate the composition of the photosynthetic apparatus differently. We find that NPQ levels do not correlate with LHCSR3 expression, suggesting an additional layer of NPQ regulation. STs are constantly activated and independent of growth light intensities. Overall, our findings highlight significant strain-to-strain differences in virtually all photosynthetic parameters, emphasizing the importance of careful strain selection in future research endeavors.

59 BASIC BIOLOGICAL SCIENCES↗

Transcriptomic Data Sets for Zymomonas mobilis 2032 during Fermentation of Ammonia Fiber Expansion (AFEX)-Pretreated Corn Stover and Switchgrass Hydrolysates

The transcriptomes of Zymomonas mobilis 2032 were captured during the fermentation of ammonia fiber expansion (AFEX)-pretreated corn stover and switchgrass hydrolysates containing different concentrations of glucose and xylose. RNA samples were collected when Z. mobilis was fermenting glucose or xylose. Here, we present transcriptome sequencing (RNA-Seq) data obtained during separate phases of glucose or xylose consumption.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available.

59 BASIC BIOLOGICAL SCIENCES↗