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At least 379 records · Page 21

Developmental regulation of the gene for chimeric calcium/calmodulin-dependent protein kinase in anthers

Chimeric Ca(2+)/calmodulin-dependent protein kinase (CCaMK) was cloned from developing anthers of lily (Lilium longiflorum Thumb. cv. Nellie White) and tobacco (Nicotiana tabacum L. cv. Xanthi). Previous biochemical characterization and structure/function studies had revealed that CCaMK has dual modes of regulation by Ca(2+) and Ca(2+)/calmodulin. The unique structural features of CCaMK include a catalytic domain, a calmodulin-binding domain, and a neural visinin-like Ca(2+)-binding domain. The existence of these three features in a single polypeptide distinguishes it from other kinases. Western analysis revealed that CCaMK is expressed in a stage-specific manner in developing anthers. Expression of CCaMK was first detected in pollen mother cells and continued to increase, reaching a peak around the tetrad stage of meiosis. Following microsporogenesis, CCaMK expression rapidly decreased and at later stages of microspore development, no expression was detected. A tobacco genomic clone of CCaMK was isolated and transgenic tobacco plants were produced carrying the CCaMK promoter fused to the beta-glucuronidase reporter gene. Both CCaMK mRNA and protein were detected in the pollen sac and their localizations were restricted to the pollen mother cells and tapetal cells. Consistent results showing a stage-specific expression pattern were obtained by beta-glucuronidase analysis, in-situ hybridization and immunolocalization. The stage- and tissue-specific appearance of CCaMK in anthers suggests that it could play a role in sensing transient changes in free Ca(2+) concentration in target cells, thereby controlling developmental events in the anther.

NASA Discipline Plant Biology↗

Light-regulated root gravitropism: a role for, and characterization of, a calcium/calmodulin-dependent protein kinase homolog

Roots of many species grow downward (orthogravitropism) only when illuminated. Previous work suggests that this is a calcium-regulated response and that both calmodulin and calcium/calmodulin-dependent kinases participate in transducing gravity and light stimuli. A genomic sequence has been obtained for a calcium/calmodulin-dependent kinase homolog (MCK1) expressed in root caps, the site of perception for both light and gravity. This homolog consists of 7265 base pairs and contains 11 exons and 10 introns. Since MCK1 is expressed constitutively in both light and dark, it is unlikely that the light directly affects MCK1 expression, though the activity of the protein may be affected by light. In cultivars showing light-regulated gravitropism, we hypothesize that MCK1, or a homolog, functions in establishing the auxin asymmetry necessary for orthogravitropism.

NASA Discipline Plant Biology↗

Worms on the International Space Station

C. elegans was proposed as a model system for space biology studies in 1991 and has since flown on STS-42, STS-76, and STS-95. Data obtained from these flights have confirmed that C. elegans requires adequate in flight oxygenation and displays an increased rate of mutation, much like other organisms in space. Unlike vertebrates, C. elegans has been observed to successfully complete two continuous full life cycles in space without gross developmental abnormalities. These observations, could with the utility of C. elegans as a terrestrial, fully sequenced, model system make C. elegans a good candidate for long term research onboard the International Space Station (ISS). We are currently working on technology to support biological studies aboard the ISS. A component of this effort is in the development of the Space Station Biological Research Program (SSBRP) Incubator which will be able to house organisms at a constant temperature setpoint ranging from 4deg C to 45deg C. The SSBRP Incubator provides air exchange, power, data and video ports and, when placed in the collaborative NASA/NASDA 2.5M centrifuge rotor, will be capable of providing a lg gravity control. Current plans for validation of the Incubator include video monitoring and periodic sampling of C. elegans in the Incubator onboard the ISS. Once returned to earth, samples will be distributed for analysis via a specimen sharing plan and analyzed for gene expression and other parameters of growth and development in space flight. These data should provide the C. elegans research community with a baseline from which to propose studies for future flights. We have also been developing an appropriate method of culturing C. elegans in liquid media in order to remove the need for the crew to assure that strains are properly fed. Currently, we are growing strains in the chemically defined, axenic, media developed by Dr. Nancy Lu. Wild-type animals complete multiple generations and appear generally healthy after being grown in unchanged media for a minimum of three to four weeks. To assure proper oxygenation we have chosen to grow animals in ten milliliter OptiCells(TradeMark). The choice of the OptiCell(TradeMark) also allows for automation of culturing as demonstrated for cell cultures grown in the OptiCell(TradeMark). Arrangements have been made for the liquid media to be commercially produced by Mediatech, Inc. and OptiCells(TradeMark) are available from BioCrystal Ltd.

Szewczyk, Nate↗

Isolation, structural analysis, and expression characteristics of the maize nuclear factor Y gene families

NUCLEAR FACTOR-Y (NF-Y) has been shown to play an important role in growth, development, and response to environmental stress. A NF-Y complex, which consists of three subunits, NF-YA, NF-YB, and, NF-YC, binds to CCAAT sequences in a promoter to control the expression of target genes. Although NF-Y proteins have been reported in Arabidopsis and rice, a comprehensive and systematic analysis of ZmNF-Y genes has not yet been performed. To examine the functions of ZmNF-Y genes in this family, we isolated and characterized 50 ZmNF-Y (14 ZmNF-YA, 18 ZmNF-YB, and 18 ZmNF-YC) genes in an analysis of the maize genome. The 50 ZmNF-Y genes were distributed on all 10 maize chromosomes, and 12 paralogs were identified. Multiple alignments showed that maize ZmNF-Y family proteins had conserved regions and relatively variable N-terminal or C-terminal domains. The comparative syntenic map illustrated 40 paralogous NF-Y gene pairs among the 10 maize chromosomes. Microarray data showed that the ZmNF-Y genes had tissue-specific expression patterns in various maize developmental stages and in response to biotic and abiotic stresses. The results suggested that ZmNF-YB2, 4, 8, 10, 13, and 16 and ZmNF-YC6, 8, and 15 were induced, while ZmNF-YA1, 3, 4, 6, 7, 10, 12, and 13, ZmNF-YB15, and ZmNF-YC3 and 9 were suppressed by drought stress. ZmNF-YA3, ZmNF-YA8 and ZmNF-YA12 were upregulated after infection by the three pathogens, while ZmNF-YA1 and ZmNF-YB2 were suppressed. These results indicate that the ZmNF-Ys may have significant roles in the response to abiotic and biotic stresses. - Highlights: • We indicated a total of 50 members of ZmNF-Y gene family in maize genome. • We analyzed gene structure, protein architecture of ZmNF-Y genes. • Evolution pattern and phylogenic relationships were analyzed among 50 ZmNF-Y genes. • Expression pattern of ZmNF-Ys were detected in various maize tissues. • Transcript levels of ZmNF-Ys were measured under various abiotic and biotic stresses.

60 APPLIED LIFE SCIENCES↗

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

ABSTRACT Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica , Debaryomyces hansenii , and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

Weintraub, Sarah J. [Department of Bioinformatics ↗

Transcriptomic data sets examining several stress responses in Zymomonas mobilis strains

We used RNA-seq to compare gene expression from Zymomonas mobilis ZM4 grown under various conditions: aerobic ± paraquat, anaerobic ± hydrogen peroxide, or an iron chelator. We analyzed two mutant strains lacking predicted transcription factors (ZMO_0442 and ZMO_1411) grown under aerobic or anaerobic conditions. We report the RNA-seq data from these experiments.

Bacterial Stress Response↗

METACLUSTER—an R package for context-specific expression analysis of metabolic gene clusters

Abstract Summary Plants and microbes produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have yet to be elucidated. Some biosynthetic pathways are encoded by enzymes collocated in the chromosome. To facilitate a more comprehensive condition and tissue-specific expression analysis of metabolic gene clusters, we developed METACLUSTER, a probabilistic framework for characterizing metabolic gene clusters using context-specific gene expression information. Availability and implementation METACLUSTER is freely available at https://github.com/mbanf/METACLUSTER. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗

Final Report for “The Genomic Basis of Heterosis in High-Yielding Triploid Hybrids of Willow ( Salix spp.) Bioenergy Crops”

Many studies have highlighted the complex, multigenic basis for heterosis (hybrid vigor) in inbred crops. Despite the lack a consensus model, it is vital that we turn our attention to understanding heterosis in undomesticated, outcrossing, heterozygous, and often polyploid species, such as willow ( Salix ). Shrub willow is a dedicated energy crop and is 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 triploid progeny produced from crosses between diploid and tetraploid species. Critical in understanding heterosis, the heritability of gene expression is dependent on allele-specific expression by local and remote factors in the genome. Here, we tested whether differentially expressed genes are responsible for heterosis in triploid crosses made between diploid S. purpurea , diploid S. viminalis , and tetraploid S. miyabeana parents. Three biological replicates of progeny and parent shoot tips were collected after 11 weeks in the greenhouse and individually sequenced via RNA-Seq (2×101). Our results highlight regulatory factors influencing differential expression and top modules of co-expressed genes correlated with heterosis for phenotypes collected in the greenhouse and in the field. We also show in diploid F 1 and F 2 S. purpurea that expression-level dominance and sex dimorphic expression is pervasive in shoot tips. Gene expression in triploids largely matches expected dosage values, but there are interesting categories of genes whose expression is divergent from expected dosage of alleles. Candidate genes have been identified whose differential expression be confirmed via allele-specific assays. Altogether, these data will be used to develop predictive models of heterosis and complement the growing genomic resources available for the improvement of shrub willow bioenergy crops.

09 BIOMASS FUELS↗

Does Simulated Spaceflight Modify Epigenetic Status During Bone Remodeling?

Little is known about the effects of spaceflight conditions on epigenetics. The term epigenetics describes changes to the genome that can affect expression of a gene without changes to the sequence of DNA. Epigenetic processes are thought to underlie cellular differentiation, where transcription of specific genes occurs in response to key stimuli, and may be heritable - passing from one cell to its daughter cell. We hypothesize that the mechanical environment during spaceflight, namely microgravity-induced weightlessness or exercise regulate gene expression in the osteoblast-lineage cells both to control bone formation by osteoblasts and bone resorption by osteoclasts, which continually shapes bone structure throughout life. Similarly we intend to evaluate how radiation regulates these same bone cell activity and differentiation related genes. We further hypothesize that the regulation in bone cell gene expression is at least partially controlled through epigenetic mechanisms of methylation or small non-coding RNA (microRNAs). We have acquired preliminary data suggesting that global genome methylation is modified in response to axial compression of the tibia - a model of exercise. We intend to pursue these hypotheses wherein we will evaluate changes in gene expression and, congruently, changes in epigenetic state in bones from mice subjected to the aforementioned conditions: hindlimb unloading to simulate weightlessness, axial compression of the tibia, or radiation exposure in order to gain insight into the role of epigenetics in spaceflight-induced bone loss.

radiation↗

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗

A Corrected Score Function Framework for Modelling Circadian Gene Expression

Many biological processes display oscillatory behaviour based on an approximately 24 h internal timing system specific to each individual. One process of particular interest is gene expression, for which several circadian transcriptomic studies have identified associations between gene expression during a 24 h period and an individual's health. A challenge with analysing data from these studies is that each individual's internal timing system is offset relative to the 24 h day-night cycle, where day–night cycle time is recorded for each collected sample. Laboratory procedures can accurately determine each individual's offset and determine the internal time of sample collection. However, these laboratory procedures are labour-intensive and expensive. Here, in this paper, we propose a corrected score function framework to obtain a regression model of gene expression given internal time when the offset of each individual is too burdensome to determine. A feature of this framework is that it does not require the probability distribution generating offsets to be symmetric with a mean of zero. Simulation studies validate the use of this corrected score function framework for cosinor regression, which is prevalent in circadian transcriptomic studies. Illustrations with data from three circadian transcriptomic studies further demonstrate that the proposed framework consistently mitigates bias relative to using a score function that does not account for this offset.

59 BASIC BIOLOGICAL SCIENCES↗

A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan–Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment.

60 APPLIED LIFE SCIENCES↗

Novel interaction interfaces mediate the interaction between the NEIL1 DNA glycosylase and mitochondrial transcription factor A

The maintenance of human mitochondrial DNA (mtDNA) is critical for proper cellular function as damage to mtDNA, if left unrepaired, can lead to a diverse array of pathologies. Of the pathways identified to participate in DNA repair within the mitochondria, base excision repair (BER) is the most extensively studied. Protein-protein interactions drive the step-by-step coordination required for the successful completion of this pathway and are important for crosstalk with other mitochondrial factors involved in genome maintenance. Human NEIL1 is one of seven DNA glycosylases that initiates BER in both the nuclear and mitochondrial compartments. In the current work, we scrutinized the interaction between NEIL1 and mitochondrial transcription factor A (TFAM), a protein that is essential for various aspects of mtDNA metabolism. We note, for the first time, that both the N- and C- terminal domains of NEIL1 interact with TFAM revealing a unique NEIL1 protein-binding interface. The interaction between the two proteins, as observed biochemically, appears to be transient and is most apparent at concentrations of low salt. The presence of DNA (or RNA) also positively influences the interaction between the two proteins, and molar mass estimates indicate that duplex DNA is required for complex formation at higher salt concentrations. Hydrogen deuterium exchange mass spectrometry data reveal that both proteins exchange less deuterium upon DNA binding, indicative of an interaction, and the addition of NEIL1 to the TFAM-DNA complex alters the interaction landscape. The transcriptional activity of TFAM appears to be independent of NEIL1 expression under normal cellular conditions, however, in the presence of DNA damage, we observe a significant reduction in the mRNA expression of TFAM-transcribed mitochondrial genes in the absence of NEIL1. Overall, our data indicate that the interaction between NEIL1 and TFAM can be modulated by local environment such as salt concentrations, protein availability, the presence of nucleic acids, as well as the presence of DNA damage.

59 BASIC BIOLOGICAL SCIENCES↗

Differential DNA methylation profile of key genes in malignant prostate epithelial cells transformed by inorganic arsenic or cadmium

Previous work shows altered methylation patterns in inorganic arsenic (iAs)- or cadmium (Cd)-transformed epithelial cells. Here, the methylation status near the transcriptional start site was assessed in the normal human prostate epithelial cell line (RWPE-1) that was malignantly transformed by 10 μM Cd for 11 weeks (CTPE) or 5 μM iAs for 29 weeks (CAsE-PE), at which time cells showed multiple markers of acquired cancer phenotype. Next generation sequencing of the transcriptome of CAsE-PE cells identified multiple dysregulated genes. Of the most highly dysregulated genes, five genes that can be relevant to the carcinogenic process (S100P, HYAL1, NTM, NES, ALDH1A1) were chosen for an in-depth analysis of the DNA methylation profile. DNA was isolated, bisulfite converted, and combined bisulfite restriction analysis was used to identify differentially methylated CpG sites, which was confirmed with bisulfite sequencing. Four of the five genes showed differential methylation in transformants relative to control cells that was inversely related to altered gene expression. Increased expression of HYAL1 (> 25-fold) and S100P (> 40-fold) in transformants was correlated with hypomethylation near the transcriptional start site. Decreased expression of NES (> 15-fold) and NTM (> 1000-fold) in transformants was correlated with hypermethylation near the transcriptional start site. ALDH1A1 expression was differentially expressed in transformed cells but was not differentially methylated relative to control. In conclusion, altered gene expression observed in Cd and iAs transformed cells may result from altered DNA methylation status. - Highlights: • Cd and iAs are known human carcinogens, yet neither appears directly mutagenic. • Prior data suggest epigenetic modification plays a role in Cd or iAs induced cancer. • Altered methylation of four misregulated genes was found in Cd or iAs transformants. • The resulting altered gene expression may be relevant to cellular transformation.

60 APPLIED LIFE SCIENCES↗

Inferring protein expression changes from mRNA in Alzheimer’s dementia using deep neural networks

Identifying the molecular systems and proteins that modify the progression of Alzheimer’s disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic data, has limited our ability to advance candidate targets that are mainly based on gene expression. Therefore, by using a deep neural network that predicts protein abundance from mRNA expression, here we attempt to track the early protein drivers of ADRD. Specifically, by applying the clei2block deep learning model to 1192 brain RNA-seq samples, we identify protein modules and disease-associated expression changes that were not directly observed at the mRNA level. Moreover, pseudo-temporal trajectory inference based on the predicted proteome became more closely correlated with cognitive decline and hippocampal atrophy compared to RNA-based trajectories. This suggests that the predicted changes in protein expression could provide a better molecular representation of ADRD progression. Furthermore, overlaying clinical traits on protein pseudotime trajectory identifies protein modules altered before cognitive impairment. These results demonstrate how our method can be used to identify potential early protein drivers and possible drug targets for treating and/or preventing ADRD.

60 APPLIED LIFE SCIENCES↗

Natural variation and improved genome annotation of the emerging biofuel crop field pennycress ( Thlaspi arvense )

The Brassicaceae family comprises more than 3,700 species with a diversity of phenotypic characteristics, including seed oil content and composition. Recently, the global interest in Thlaspi arvense L. (pennycress) has grown as the seed oil composition makes it a suitable source for biodiesel and aviation fuel production. However, many wild traits of this species need to be domesticated to make pennycress ideal for cultivation. Molecular breeding and engineering efforts require the availability of an accurate genome sequence of the species. Here, we describe pennycress genome annotation improvements, using a combination of long- and short-read transcriptome data obtained from RNA derived from embryos of 22 accessions, in addition to public genome and gene expression information. Our analysis identified 27,213 protein-coding genes, as well as on average 6,188 biallelic SNPs. In addition, we used the identified SNPs to evaluate the population structure of our accessions. The data from this analysis support that the accession Ames 32872, originally from Armenia, is highly divergent from the other accessions, while the accessions originating from Canada and the United States cluster together. When we evaluated the likely signatures of natural selection from alternative SNPs, we found 7 candidate genes under likely recent positive selection. These genes are enriched with functions related to amino acid metabolism and lipid biosynthesis and highlight possible future targets for crop improvement efforts in pennycress.

59 BASIC BIOLOGICAL SCIENCES↗

TransPlatformer

We propose TransPlatformer for translating toxicogenomics from one platform to another. Transcriptomic profiling has evolved through multiple generations of technology, from microarrays (e.g., Affymetrix, CodeLink) to more recent high-throughput sequencing and targeted panels such as S1500+. Microarrays, which dominated gene expression studies in the early 2000s, provided affordable and high-throughput transcript quantification but suffered from cross-hybridization issues and limited dynamic range . RNA-Seq, introduced in the late 2000s, revolutionized transcriptomics by enabling unbiased and comprehensive gene expression analysis, albeit at higher costs and computational demands . Despite advances, many studies rely on historical microarray data, necessitating the translation of legacy data into modern platforms to ensure continuity and comparability. This translation is complicated by factors such as platform-specific probe design, differences in transcript coverage, and batch effects . Existing methods for cross-platform mapping include statistical normalization, machine learning models, and biological anchoring approaches. The ability to translate transcriptomic data between platforms has broad implications, including enhanced meta-analyses, improved toxicological modeling, and better integration of historical datasets with contemporary research. TransPlatformer seeks to contribute to this effort by evaluating translation methodologies and proposing novel strategies to improve cross-platform gene expression harmonization. In this repository there are code examples for TransPlatformer implementation

Cong, Guojing↗

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux, metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.

09 BIOMASS FUELS↗