RNA Transcript Abundance Research Articles

Luteolin Mitigates Dopaminergic Neuron Degeneration and Restrains Microglial M1 Polarization by Inhibiting Toll Like Receptor 4.

Luteolin is a natural flavonoid and its neuroprotective and anti-inflammatory effects have been confirmed to mitigate neurodegeneration. Despite these findings, the underlying mechanisms responsible for these effects remain unclear. Toll-like receptor 4 (TLR4) is widely distributed in microglia and plays a pivotal role in neuroinflammation and neurodegeneration. Here studies are outlined that aimed at determining the mechanisms responsible for the anti-inflammatory and neuroprotective actions of luteolin using a rodent model of Parkinson's disease (PD) and specifically focusing on the role of TLR4 in this process. The mouse model of PD used in this experiment was established through a single injection of lipopolysaccharide (LPS). Mice were then subsequently randomly allocated to either the luteolin or vehicle-treated group, then motor performance and dopaminergic neuronal injury were evaluated. BV2 microglial cells were treated with luteolin or vehicle saline prior to LPS challenge. MRNA expression of microglial specific marker ionized calcium-binding adapter molecule 1 (IBA-1) and M1/M2 polarization markers, as well as the abundance of indicated pro-inflammatory cytokines in the mesencephalic tissue and BV2 were quantified by real time-polymerase chain reaction (RT-PCR) and Enzyme-linked Immunosorbent Assay (ELISA), respectively. Cell viability and apoptosis of neuron-like PC12 cell line co-cultured with BV2 were detected. TLR4 RNA transcript and protein abundance in mesencephalic tissue and BV2 cells were detected. Nuclear factor kappa-gene binding (NF-κB) p65 subunit phosphorylation both in vitro and in vivo was evaluated by immunoblotting. Luteolin treatment induced functional improvements and alleviated dopaminergic neuronal loss in the PD model. Luteolin inhibited apoptosis and promoted cell survival in PC12 cells. Luteolin treatment shifted microglial M1/M2 polarization towards an anti-inflammatory M2 phenotype both in vitro and in vivo. Finally, it was found that luteolin treatment significantly downregulated both TLR4 mRNA and protein expression as well as restraining NF-κB p65 subunit phosphorylation. Luteolin restrained dopaminergic degeneration in vitro and in vivo by blocking TLR4-mediated neuroinflammation.

Experimental and analytical pipeline for sub-genomic RNA landscape of coronavirus by Nanopore sequencer.

Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2, can infect a variety of mammalian and avian hosts with significant medical and economic consequences. During the life cycle of CoV, a coordinated series of subgenomic RNAs, including canonical subgenomic messenger RNA and non-canonical defective viral genomes (DVGs), are generated with different biological implications. Studies that adopted the Nanopore sequencer (ONT) to investigate the landscape and dynamics of viral RNA subgenomic transcriptomes applied arbitrary bioinformatics parameters without justification or experimental validation. The current study used bovine coronavirus (BCoV), which can be performed under biosafety level 2 for library construction and experimental validation using traditional colony polymerase chain reaction and Sanger sequencing. Four different ONT protocols, including RNA direct and cDNA direct sequencing with or without exonuclease treatment, were used to generate RNA transcriptomic libraries from BCoV-infected cell lysates. Through rigorously examining the k-mer, gap size, segment size, and bin size, the optimal cutoffs for the bioinformatic pipeline were determined to remove the sequence noise while keeping the informative DVG reads. The sensitivity and specificity of identifying DVG reads using the proposed pipeline can reach 82.6% and 99.6% under the k-mer size cutoff of 15. Exonuclease treatment reduced the abundance of RNA transcripts; however, it was not necessary for future library preparation. Additional recovery of clipped BCoV nucleotide sequences with experimental validation expands the landscape of the CoV discontinuous RNA transcriptome, whose biological function requires future investigation. The results of this study provide the benchmarks for library construction and bioinformatic parameters for studying the discontinuous CoV RNA transcriptome.IMPORTANCEFunctional defective viral genomic RNA, containing all the cis-acting elements required for translation or replication, may play different roles in triggering cell innate immune signaling, interfering with the canonical subgenomic messenger RNA transcription/translation or assisting in establishing persistence infection. This study does not only provide benchmarks for library construction and bioinformatic parameters for studying the discontinuous coronavirus RNA transcriptome but also reveals the complexity of the bovine coronavirus transcriptome, whose functional assays will be critical in future studies.

Allometric scaling improves the characterization of complex community transcriptomes.

Allometric scaling, that is scaling patterns in physiological processes relative to body size, can be used to overcome the current limitations in metatranscriptomics. Metatranscriptomics refers to the use of RNA transcripts to characterize a complex community. In contrast to metagenomics, metatranscriptomics allows one to simultaneously address community composition and functionality through the characterization of the community transcriptome. Hence, insights into metabolic processes and molecular pathways can also be obtained. Despite its increasing use in community ecology, a major limitation and source of error is the variation in RNA transcript abundance across organisms varying in body size. Hence, this may lead to incorrect estimations of the community structure and functioning as larger RNA quantities from larger individuals may overestimate their community contribution.

Allometric scaling of interspecific RNA transcript abundance to extend the use of metatranscriptomics in characterizing complex communities.

Metatranscriptomics allows profiling of community mRNA and rRNA transcript abundance under certain environmental conditions. However, variations in the proportion of RNA transcripts across different community size structures remain less explained, thus limiting the possible applications of metatranscriptomics in community studies. Here, we extended the assumptions of the growth-rate hypothesis (GRH) and the metabolic theory of ecology (MTE) to validate the allometric scaling of interspecific RNA transcript (mRNA and rRNA) abundance through metatranscriptomic analysis of mock communities consisting of model organisms. The results suggest that body size imposes significant constraints on RNA transcript abundance. Interestingly, the relationship between the total mitochondrial transcript abundance (mRNA and rRNA slopes were -0.30 and -0.28, respectively) and body size aligned with the MTE assumptions with slopes close to -¼, while the nuclear transcripts displayed much steeper slopes (mRNA and rRNA slopes were -0.33 and -0.40, respectively). The assumed temperature dependence was not observed in this study. At the gene level, the allometric slopes range from 0 to -1. Overall, the above results showed that larger individuals have lesser RNA transcript abundance per tissue mass than smaller ones regardless of temperature. Analyses of field-collected microcrustacean zooplankton samples demonstrated that the correction of size effect, using the allometric exponents derived from the model organism mock community, explains better the patterns of interspecific RNA transcripts abundance within the metatranscriptome. Integrating allometry with metatranscriptomics can extend the use of RNA transcript reads in estimating ecological processes within complex communities.

Internally controlled RNA sequencing comparisons using nucleoside recoding chemistry.

Quantitative comparisons of RNA levels from different samples can lead to new biological understanding if they are able to distinguish biological variation from variable sample preparation. These challenges are pronounced in comparisons that require complex biochemical manipulations (e.g.isolating polysomes to study translation). Here, we present Transcript Regulation Identified by Labeling with Nucleoside Analogues in Cell Culture (TILAC), an internally controlled approach for quantitative comparisons of RNA content. TILAC uses two metabolic labels, 4-thiouridine (s4U) and 6-thioguanosine (s6G), to differentially label RNAs in cells, allowing experimental and control samples to be pooled prior to downstream biochemical manipulations. TILAC leverages nucleoside recoding chemistry to generate characteristic sequencing signatures for each label and uses statistical modeling to compare the abundance of RNA transcripts between samples. We verified the performance of TILAC in transcriptome-scale experiments involving RNA polymerase II inhibition and heat shock. We then applied TILAC to quantify changes in mRNA association with actively translating ribosomes during sodium arsenite stress and discovered a set of transcripts that are translationally upregulated, including MCM2 and DDX5. TILAC is broadly applicable to uncover differences between samples leading to improved biological insights.

Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering.

SUMMARYSingle-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low-abundance proteins. Herein, we describe an ion-mobility-enhanced mass spectrometry acquisition and peptide identification method, transferring identification based on FAIMS filtering (TIFF), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells, with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes. A record of this paper’s transparent peer review process is included in the supplemental information.

MicroRNA172 targets APETALA2 to regulate flavonoid biosynthesis in apple (Malus domestica).

MicroRNA172 (miR172) plays a role in regulating a diverse range of plant developmental processes, including flowering, fruit development and nodulation. However, its role in regulating flavonoid biosynthesis is unclear. In this study, we show that transgenic apple plants over-expressing miR172 show a reduction in red coloration and anthocyanin accumulation in various tissue types. This reduction was consistent with decreased expression of APETALA2 homolog MdAP2_1a (a miR172 target gene), MdMYB10, and targets of MdMYB10, as demonstrated by both RNA-seq and qRT-PCR analyses. The positive role of MdAP2_1a in regulating anthocyanin biosynthesis was supported by the enhanced petal anthocyanin accumulation in transgenic tobacco plants overexpressing MdAP2_1a, and by the reduction in anthocyanin accumulation in apple and cherry fruits transfected with an MdAP2_1a virus-induced-gene-silencing construct. We demonstrated that MdAP2_1a could bind directly to the promoter and protein sequences of MdMYB10 in yeast and tobacco, and enhance MdMYB10 promotor activity. In Arabidopsis, over-expression of miR172 reduced flavonoid (including anthocyanins and flavonols) concentration and RNA transcript abundance of flavonoid genes in plantlets cultured on medium containing 7% sucrose. The anthocyanin content and RNA abundance of anthocyanin genes could be partially restored by using a synonymous mutant of MdAP2_1a, which had lost the miR172 target sequences at mRNA level, but not restored by using a WT MdAP2_1a. These results indicate that miR172 inhibits flavonoid biosynthesis through suppressing the expression of an AP2 transcription factor that positively regulates MdMYB10.

Abstract PO-001: ARNTL2 is a hypoxia-responsive master regulator of PDAC malignancy

Abstract Large-scale sequencing studies have identified a limited number of genetic drivers of PDAC malignancy, with only four genes found mutated a high penetrance across human pancreatic tumors. This suggests that the cell-autonomous ability to progress, dedifferentiate and metastasize is determined by non-genetic alterations to transcriptional regulation. Regulatory network analysis is a computational means of identifying changes in the activity of transcription factors on a genome-wide scale. Briefly, the approach calculates the activity of each regulatory protein (i.e. transcription factors, co-factors, and other proteins that regulate RNA transcript abundance) based on the expression of its positive and negative transcriptional targets (which are inferred de novo in a context-specific manner using the ARACNe algorithm). In this way, it is possible to identify the most hyper-activated and hyper-repressed regulatory proteins between groups of samples that represent different phenotypes – i.e. the “master regulators” (MRs) of those phenotypes. We applied regulatory network analysis to identify MRs of PDAC malignancy by comparing groups of samples representing several phenotypes. First, we performed laser capture microdissection and RNA sequencing (LCM-RNAseq) on 199 human PDAC samples, 26 low-grade PanIN, and 19 low-grade IPMN, isolating just the epithelial cells for transcriptional profiling. We then identified MRs of four different phenotypes among these samples: 1) precursor versus PDAC; 2) low-grade versus high-grade PDAC (based on histopathology); 3) low versus high Kras signaling; and long versus short overall survival. Integrating these analyses, the most highly activated regulatory protein in the genome across these four phenotypes was ARNTL2, an understudied member of the ARNT (HIF1β) superfamily. Notably, this protein was only modestly differentially expressed at the RNA level, indicating that its activation occurs primarily at a post-translational level. Computational analysis of the function of ARNTL2 indicated an enrichment of pathways involved in hypoxia responsiveness. Experimental analysis found that ARNTL2 had little impact in proliferation or survival under normoxic conditions, but drove increased invasiveness under hypoxic conditions. The functional associations of ARNTL2 in cultured cells expanded substantially under hypoxic conditions. Together, these findings suggest that ARNTL2 may serve as a Kras-associated, hypoxia-responsive driver of PDAC malignancy. Citation Format: Alvaro Curiel-Garcia, Carlo H. Maurer, Pasquale Laise, Irina Sagalovskiy, John A. Chabot, Gulam A. Manji, Alina Iuga, Kristen Johnson, Andrea Califano, Kenneth P. Olive. ARNTL2 is a hypoxia-responsive master regulator of PDAC malignancy [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-001.

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions.

Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

SCISSOR: a framework for identifying structural changes in RNA transcripts

High-throughput sequencing protocols such as RNA-seq have made it possible to interrogate the sequence, structure and abundance of RNA transcripts at higher resolution than previous microarray and other molecular techniques. While many computational tools have been proposed for identifying mRNA variation through differential splicing/alternative exon usage, challenges in its analysis remain. Here, we propose a framework for unbiased and robust discovery of aberrant RNA transcript structures using short read sequencing data based on shape changes in an RNA-seq coverage profile. Shape changes in selecting sample outliers in RNA-seq, SCISSOR, is a series of procedures for transforming and normalizing base-level RNA sequencing coverage data in a transcript independent manner, followed by a statistical framework for its analysis (https://github.com/hyochoi/SCISSOR). The resulting high dimensional object is amenable to unsupervised screening of structural alterations across RNA-seq cohorts with nearly no assumption on the mutational mechanisms underlying abnormalities. This enables SCISSOR to independently recapture known variants such as splice site mutations in tumor suppressor genes as well as novel variants that are previously unrecognized or difficult to identify by any existing methods including recurrent alternate transcription start sites and recurrent complex deletions in 3′ UTRs.

Hyperandrogenemia alters mitochondrial structure and function in the oocytes of obese mouse with polycystic ovary syndrome

Hyperandrogenemia in an obese PCOS mouse model results in altered glucose/insulin metabolism and mitochondrial structure and function in the oocytes, in part explaining adverse outcomes and inheritance patterns seen in PCOS. To study the oocyte quality by means of mitochondrial structure and function in a well-established classic PCOS mouse model. Animal study using an obese PCOS mouse model compared with control. Animal research facility in a tertiary care university hospital setting. C57/B6J mice. Three week old mice had subdermal implants of DHT controlled release pellet or placebo for 90 days. The mouse model was validated by performing glucose tolerance test, HbA1c levels, body weight and estrous cycle analyses. Oocytes were subsequently isolated and were used to investigate mitochondrial membrane potential, oxidative stress, lipid peroxidation, ATP production, mtDNA copy number, transcript abundance, histology and electron microscopy. Results showed glucose intolerance and hyperinsulinemia along with dysregulated estrus cycle. Analysis of the oocytes demonstrated impaired inner mitochondrial membrane function, increased ATP production and mtDNA copy number, altered RNA transcript abundance and aberrant ovarian histology. Electron microscopy of the oocytes showed severely impaired mitochondrial ultrastructure. The obese PCOS mouse model shows a decreased oocyte quality related to impaired mitochondrial function.

De novo duplication on Chromosome 19 observed in nuclear family displaying neurodevelopmental disorders.

Pleiotropy and variable expressivity have been cited to explain the seemingly distinct neurodevelopmental disorders due to a common genetic etiology within the same family. Here we present a family with a de novo 1-Mb duplication involving 18 genes on Chromosome 19. Within the family there are multiple cases of neurodevelopmental disorders including autism spectrum disorder, attention deficit/hyperactivity disorder, intellectual disability, and psychiatric disease in individuals carrying this copy-number variant (CNV). Quantitative polymerase chain reaction (PCR) confirmed the CNV was de novo in the mother and inherited by both sons. Whole-exome sequencing did not uncover further genetic risk factors segregating within the family. Transcriptome analysis of peripheral blood demonstrated a ∼1.5-fold increase in RNA transcript abundance in 12 of the 15 detected genes within the CNV region for individuals carrying the CNV compared with their noncarrier relatives. Examination of transcript abundance across the rest of the transcriptome identified 407 differentially expressed genes (P-value < 0.05; adjusted P-value < 0.1) mapping to immune response, response to endoplasmic reticulum stress, and regulation of epithelial cell proliferation pathways. 16S microbiome profiling demonstrated compositional difference in the gut bacteria between the half-brothers. These results raise the possibility that the observed CNV may contribute to the varied phenotypic characteristics in family members through alterations in gene expression and/or dysbiosis of the gut microbiome. More broadly, there is growing evidence that different neurodevelopmental and psychiatric disorders can share the same genetic variant, which lays a framework for later neurodevelopmental and psychiatric manifestations.

Prenatal androgen induced lean PCOS impairs mitochondria and mRNA profiles in oocytes.

Polycystic ovary syndrome (PCOS) is the most common ovulatory defect in women. Although most PCOS patients are obese, a subset of PCOS women are lean but show similar risks for adverse fertility outcomes. A lean PCOS mouse model was created using prenatal androgen administration. This developmentally programmed mouse model was used for this study. Our objective was to investigate if mitochondrial structure and functions were compromised in oocytes obtained from lean PCOS mouse. The lean PCOS mouse model was validated by performing glucose tolerance test, HbA1c levels, body weight and estrous cycle analyses. Oocytes were isolated and were used to investigate inner mitochondrial membrane potential, oxidative stress, lipid peroxidation, ATP production, mtDNA copy number, transcript abundance and electron microscopy. Our results demonstrate that lean PCOS mice have similar weight to that of the controls but exhibit glucose intolerance and hyperinsulinemia along with dysregulated estrus cycle. Analysis of their oocytes show impaired inner mitochondrial membrane function, elevated reactive oxygen species (ROS) and increased RNA transcript abundance. Electron microscopy of the oocytes showed impaired mitochondrial ultrastructure. In conclusion, the lean PCOS mouse model shows a decreased oocyte quality related to impaired mitochondrial ultrastructure and function.

SplintQuant: a method for accurately quantifying circular RNA transcript abundance without reverse transcription bias.

Reverse transcription of RNA is fallible, introducing biases and confounding the quantification of transcript abundance. We demonstrate that circular RNAs (circRNAs) are more subjective to overestimation of transcript abundance than cognate linear RNAs due to their covalently closed, circular form, producing multiple concatameric products from a single priming of reverse transcriptase. We developed SplintQuant, where custom DNA oligonucleotides are ligated by PBCV-1 DNA ligase only when bound to their target RNA. These circRNA-specific DNA oligonucleotides are terminally tagged with universal primers, allowing SplintQuant to accurately quantify even lowly abundant circRNAs through highly specific quantitative PCR (qPCR) in the absence of reverse transcription. SplintQuant is sensitive, specific, highly reproducible, and applicable to the quantification of canonical and noncanonical RNA transcripts including alternative splice variants, gene fusions, and offers a gold-standard approach for accurately quantifying circRNAs.

Transcription Is Just the Beginning of Gene Expression Regulation: The Functional Significance of RNA-Binding Proteins to Post-transcriptional Processes in Plants.

Plants have developed sophisticated mechanisms to compensate and respond to ever-changing environmental conditions. Research focus in this area has recently shifted towards understanding the post-transcriptional mechanisms that contribute to RNA transcript maturation, abundance and function as key regulatory steps in allowing plants to properly react and adapt to these never-ending shifts in their environments. At the center of these regulatory mechanisms are RNA-binding proteins (RBPs), the functional mediators of all post-transcriptional processes. In plants, RBPs are becoming increasingly appreciated as the critical modulators of core cellular processes during development and in response to environmental stimuli. With the majority of research on RBPs and their functions historically in prokaryotic and mammalian systems, it has more recently been unveiled that plants have expanded families of conserved and novel RBPs compared with their eukaryotic counterparts. To better understand the scope of RBPs in plants, we present past and current literature detailing specific roles of RBPs during stress response, development and other fundamental transition periods. In this review, we highlight examples of complex regulation coordinated by RBPs with a focus on the diverse mechanisms of plant RBPs and the unique processes they regulate. Additionally, we discuss the importance for additional research into understanding global interactions of RBPs on a systems and network-scale, with genome mining and annotation providing valuable insight for potential uses in improving crop plants in order to maintain high-level production in this era of global climate change.

Investigation of graded levels of soybean meal diets for red drum, Sciaenops ocellatus, using quantitative PCR derived biomarkers

A twelve-week feeding trial was conducted to examine potential metabolic and gene expression changes that occur in juvenile red drum, Sciaenops ocellatus, fed diets with increasing soybean meal inclusion. Significant reduction in fish performance characteristics (feed consumption, weight gain, final weight) was observed within the soybean meal based diets as soybean meal level increased (R, linear regression); however, all soybean meal based diets performed statistically equivalent in regards to performance characteristics (weight gain, feed conversion ratio, condition factor, etc.) to a commercial (45% crude protein and 16% crude lipid) reference diet (R, ANOVA). To better understand the underlying physiological responses and metabolic changes driving performance differences, traditional aquaculture metrics were paired with high throughput –omics techniques. Nuclear magnetic resonance (NMR) spectroscopy-based metabolomics data and RNA transcript abundance differences observed in liver tissue were utilized to select multiple sets of genes to target with quantitative polymerase chain reaction (qPCR), both for pathway activity validation and as rapid and accessible biomarkers of performance as a result of soybean meal. Genes selected based on the metabolic pathways most affected by soybean meal level corroborate the metabolite profile and performance data indicating an increase in gluconeogenic precursor production as soybean meal increased. The metabolomic and gene expression tools utilized in our study present a novel framework for diet and fish health evaluation that may provide more rapid and improved techniques for evaluating dietary manipulations and improving production of juvenile fish on alternative feeds.

Base editing: precision chemistry on the genome and transcriptome ofliving cells.

RNA-guided programmable nucleases from CRISPR systems generate precise breaks in DNA or RNA at specified positions. In cells, this activity can lead to changes in DNA sequence or RNA transcript abundance. Base editing is a newer genome-editing approach that uses components from CRISPR systems together with other enzymes to directly install point mutations into cellular DNA or RNA without making double-stranded DNA breaks. DNA base editors comprise a catalytically disabled nuclease fused to a nucleobase deaminase enzyme and,in some cases, a DNA glycosylase inhibitor. RNA base editors achieve analogous changes using components that target RNA. Base editors directly convert one base or base pair into another, enabling the efficient installation of point mutations in non-dividing cells without generating excess undesired editing by-products. In this Review, we summarize base-editing strategies to generate specific and precise point mutations in genomic DNA and RNA, highlight recent developments that expand the scope, specificity, precision and in vivo delivery of baseeditors and discuss limitations and future directions of base editing for research and therapeutic applications.

Insights into carotenoid accumulation using VIGS to block different steps of carotenoid biosynthesis in petals of California poppy.

Viral-induced gene silencing of selected biosynthetic genes decreased overall carotenoid accumulation in California poppy. Regulation of carotenogenesis was linked with pigment sequestration, not changes in biosynthetic gene expression. Genes of carotenogenesis are well described, but understanding how they affect carotenoid accumulation has proven difficult because of plant lethality when the pigments are lacking. Here, we used a Tobacco Rattle Virus-based virus-induced-gene-silencing (VIGS) approach in California poppy (Eschscholzia californica) to investigate how silencing of the carotenoid biosynthetic pathway genes affects carotenoid metabolite accumulation and RNA transcript abundance of the carotenoid biosynthetic pathway genes. VIGS of upstream (PDS and ZDS) and downstream (βOH and ZEP) genes reduced transcript abundance of the targeted genes in the poppy petals while having no effect on abundance of the other carotenogenesis genes. Silencing of PDS, ZDS, βOH and ZEP genes reduced total pigment concentration by 75-90% and altered petal colour. HPLC and LC-MS measurements suggested that petal colour changes were caused by substantially altered pigment profiles and quantity. Carotenoid metabolites were different to those normally detected in wild-type petals accumulated but overall carotenoid concentration was less, suggesting the chemical form of carotenoid was important for whether it could be stored at high amounts. In poppy petals, eschscholtzxanthin and retro-carotene-triol were the predominant carotenoids, present mainly as esters. Specific esterification enzymes for specific carotenoids and/or fatty acids appear key for enabling petal carotenoids to accumulate to high amounts. Our findings argue against a direct role for carotenoid metabolites regulating carotenogenesis genes in the petals of California poppy as transcript abundance of carotenogenesis genes studied was unchanged, while the petal carotenoid metabolite profile changed substantially.

Metatranscriptomics profile of the gill microbial community during Bathymodiolus azoricus aquarium acclimatization at atmospheric pressure.

BackgroundThe deep-sea mussels Bathymodiolus azoricus (Bivalvia: Mytilidae) are the dominant macrofauna subsisting at the hydrothermal vents site Menez Gwen in the Mid-Atlantic Ridge (MAR). Their adaptive success in such challenging environments is largely due to their gill symbiotic association with chemosynthetic bacteria. We examined the response of vent mussels as they adapt to sea-level environmental conditions, through an assessment of the relative abundance of host-symbiont related RNA transcripts to better understand how the gill microbiome may drive host-symbiont interactions in vent mussels during hypothetical venting inactivity.ResultsThe metatranscriptome of B. azoricus was sequenced from gill tissues sampled at different time-points during a five-week acclimatization experiment, using Next-Generation-Sequencing. After Illumina sequencing, a total of 181,985,262 paired-end reads of 150 bp were generated with an average of 16,544,115 read per sample. Metatranscriptome analysis confirmed that experimental acclimatization in aquaria accounted for global gill transcript variation. Additionally, the analysis of 16S and 18S rRNA sequences data allowed for a comprehensive characterization of host-symbiont interactions, which included the gradual loss of gill endosymbionts and signaling pathways, associated with stress responses and energy metabolism, under experimental acclimatization. Dominant active transcripts were assigned to the following KEGG categories: “Ribosome”, “Oxidative phosphorylation” and “Chaperones and folding catalysts” suggesting specific metabolic responses to physiological adaptations in aquarium environment.ConclusionsGill metagenomics analyses highlighted microbial diversity shifts and a clear pattern of varying mRNA transcript abundancies and expression during acclimatization to aquarium conditions which indicate change in bacterial community activity. This approach holds potential for the discovery of new host-symbiont associations, evidencing new functional transcripts and a clearer picture of methane metabolism during loss of endosymbionts. Towards the end of acclimatization, we observed trends in three major functional subsystems, as evidenced by an increment of transcripts related to genetic information processes; the decrease of chaperone and folding catalysts and oxidative phosphorylation transcripts; but no change in transcripts of gluconeogenesis and co-factors-vitamins.

BayFish: Bayesian inference of transcription dynamics from population snapshots of single-molecule RNA FISH in single cells

Single-molecule RNA fluorescence in situ hybridization (smFISH) provides unparalleled resolution in the measurement of the abundance and localization of nascent and mature RNA transcripts in fixed, single cells. We developed a computational pipeline (BayFish) to infer the kinetic parameters of gene expression from smFISH data at multiple time points after gene induction. Given an underlying model of gene expression, BayFish uses a Monte Carlo method to estimate the Bayesian posterior probability of the model parameters and quantify the parameter uncertainty given the observed smFISH data. We tested BayFish on synthetic data and smFISH measurements of the neuronal activity-inducible gene Npas4 in primary neurons.