Expression Of Various Genes Research Articles

Exercise training modifies skeletal muscle clock gene expression but not 24-hour rhythmicity in substrate metabolism of men with insulin resistance.

Twenty-four hour rhythmicity in whole-body substrate metabolism, skeletal muscle clock gene expression and mitochondrial respiration is compromised upon insulin resistance. With exercise training known to ameliorate insulin resistance, our objective was to test if exercise training can reinforce diurnal variation in whole-body and skeletal muscle metabolism in men with insulin resistance. In a single-arm longitudinal design, 10 overweight and obese men with insulin resistance performed 12weeks of high-intensity interval training recurrently in the afternoon (between 14.00 and 18.00h) and were tested pre- and post-exercise training, while staying in a metabolic research unit for 2days under free-living conditions with regular meals. On the seconddays, indirect calorimetry was performed at 08.00, 13.00, 18.00, 23.00 and 04.00h, muscle biopsies were taken from the vastus lateralis at 08.30, 13.30 and 23.30h, and blood was drawn at least bi-hourly over 24h. Participants did not lose body weight over 12weeks, but improved body composition and exercise capacity. Exercise training resulted in reduced 24-h plasma glucose levels, but did not modify free fatty acid and triacylglycerol levels. Diurnal variation of muscle clock gene expression was modified by exercise training with period genes showing an interaction (time × exercise) effect and reduced mRNA levels at 13.00h. Exercise training increased mitochondrial respiration without inducing diurnal variation. Twenty-four-hour substrate metabolism and energy expenditure remained unchanged. Future studies should investigate alternative exercise strategies or types of interventions (e.g. diet or drugs aiming at improving insulin sensitivity) for their capacity to reinforce diurnal variation in substrate metabolism and mitochondrial respiration. KEY POINTS: Insulin resistance is associated with blunted 24-h flexibility in whole-body substrate metabolism and skeletal muscle mitochondrial respiration, and disruptions in the skeletal muscle molecular circadian clock. We hypothesized that exercise training modifies 24-h rhythmicity in whole-body substrate metabolism and diurnal variation in skeletal muscle molecular clock and mitochondrial respiration in men with insulin resistance. We found that metabolic inflexibility over 24h persisted after exercise training, whereas mitochondrial respiration increased independent of time of day. Gene expression of Per1-3 and Rorα in skeletal muscle changed particularly close to the time of day at which exercise training was performed. These results provide the rationale to further investigate the differential metabolic impact of differently timed exercise to treat metabolic defects of insulin resistance that manifest at a particular time of day.

Transcriptomic and metabolomic analyses reveal the differential accumulation of phenylpropanoids and terpenoids in hemp autotetraploid and its diploid progenitor

BackgroundCannabis sativa, a dioecious plant that has been cultivated worldwide for thousands of years, is known for its secondary metabolites, especially cannabinoids, which possess several medicinal effects. In this study, we investigated the autopolyploidization effects on the biosynthesis and accumulation of these metabolites, transcriptomic and metabolomic analyses were performed to explore the gene expression and metabolic variations in industrial hemp autotetraploids and their diploid progenitors.ResultsThrough these analyses, we obtained 1,663 differentially expressed metabolites and 1,103 differentially expressed genes. Integrative analysis revealed that phenylpropanoid and terpenoid biosynthesis were regulated by polyploidization. No substantial differences were found in the cannabidiol or tetrahydrocannabinol content between tetraploids and diploids. Following polyploidization, some transcription factors, including nine bHLH and eight MYB transcription factors, affected the metabolic biosynthesis as regulators. Additionally, several pivotal catalytic genes, such as flavonol synthase/flavanone 3-hydroxylase, related to the phenylpropanoid metabolic pathway, were identified as being modulated by polyploidization.ConclusionsThis study enhances the overall understanding of the impact of autopolyploidization in C. sativa and the findings may encourage the application of polyploid breeding for increasing the content of important secondary metabolites in industrial hemp.

Non-additive genetic components contribute significantly to population-wide gene expression variation

Gene expression variation, an essential step between genotype and phenotype, is collectively controlled by local (cis) and distant (trans) regulatory changes. Nevertheless, how these regulatory elements differentially influence gene expression variation remains unclear. Here, we bridge this gap by analyzing the transcriptomes of a large diallel panel consisting of 323 unique hybrids originating from genetically divergent Saccharomyces cerevisiae isolates. Our analysis across 5,087 transcript abundance traits showed that non-additive components account for 36% of the gene expression variance on average. By comparing allele-specific read counts in parent-hybrid trios, we found that trans-regulatory changes underlie the majority of gene expression variation in the population. Remarkably, most cis-regulatory variations are also exaggerated or attenuated by additional trans effects. Overall, we showed that the transcriptome is globally buffered at the genetic level mainly due to trans-regulatory variation in the population.

Local manufacturing processes contribute to variability in human mesenchymal stromal cell expansion while growth media supplements contribute to variability in gene expression and cell function: a Biomedical Excellence for Safer Transfusion (BEST) collaborative study

Background aimsCulture-derived mesenchymal stromal cells (MSCs) exhibit variable characteristics when manufactured using different methods, source material and culture media. The purpose of this multicenter study was to assess the impact on MSC expansion, gene expression and other characteristics when different laboratories expanded MSCs from cultures initiated with bone marrow−MSC aliquots derived from the same donor source material yet with different growth media. MethodsEight centers expanded MSCs using four human platelet lysate (HPL) and one fetal bovine serum (FBS) products as media supplements. The expanded cells were taken through two passages then assessed for cell count, viability, doubling time, immunophenotype, cell function, immunosuppression and gene expression. Results were analyzed by growth media and by center. ResultsCenter methodologies varied by their local seeding density, feeding regimen, inoculation density, base media and other growth media features (antibiotics, glutamine, serum). Doubling times were more dependent on center than on media supplements. Two centers had appropriate immunophenotyping showing all MSC cultures were positive for CD105, CD73, CD90 and negative for CD34, CD45, CD14, HLA-DR. MSCs cultured in media supplemented with FBS compared with HPL featured greater T-cell inhibition potential. Gene expression analysis showed greater impact of the type of media supplement (HPL versus FBS) than the manufacturing center. Specifically, nine genes were decreased in expression and six increased when combining the four HPL-grown MSCs versus FBS (false discovery rate [FDR] <0.01), however, without significant difference between different sources of HPL (FDR <0.01). ConclusionsLocal manufacturing process plays a critical role in MSC expansion while growth media may influence function and gene expression. All HPL and FBS products supported cell growth.

Molecular and Metabolic Analysis of Arsenic-Exposed Humanized AS3MT Mice.

Chronic exposure to inorganic arsenic (iAs) has been associated with type 2 diabetes (T2D). However, potential sex divergence and the underlying mechanisms remain understudied. iAs is not metabolized uniformly across species, which is a limitation of typical exposure studies in rodent models. The development of a new "humanized" mouse model overcomes this limitation. In this study, we leveraged this model to study sex differences in the context of iAs exposure. The aim of this study was to determine if males and females exhibit different liver and adipose molecular profiles and metabolic phenotypes in the context of iAs exposure. Our study was performed on wild-type (WT) 129S6/SvEvTac and humanized arsenic methyl transferase (human AS3MT) 129S6/SvEvTac mice treated with of iAs via drinking water ad libitum. After 1 month, mice were sacrificed and the liver and gonadal adipose depots were harvested for iAs quantification and sequencing-based microRNA and gene expression analysis. Serum blood was collected for fasting blood glucose, fasting plasma insulin, and homeostatic model assessment for insulin resistance (HOMA-IR). We detected sex divergence in liver and adipose markers of diabetes (e.g., miR-34a, insulin signaling pathways, fasting blood glucose, fasting plasma insulin, and HOMA-IR) only in humanized (not WT) mice. In humanized female mice, numerous genes that promote insulin sensitivity and glucose tolerance in both the liver and adipose are elevated compared to humanized male mice. We also identified Klf11 as a putative master regulator of the sex divergence in gene expression in humanized mice. Our study underscored the importance of future studies leveraging the humanized mouse model to study iAs-associated metabolic disease. The findings suggested that humanized males are at increased risk for metabolic dysfunction relative to humanized females in the context of iAs exposure. Future investigations should focus on the detailed mechanisms that underlie the sex divergence. https://doi.org/10.1289/EHP12785.

Microglia from individuals with mild cognitive impairment (MCI) and AD show differences in transcriptional burst kinetics

AbstractBackgroundMicroglia are the innate immune cells in the central nervous system that responds to brain injury and pathogens. The loss of homeostatic microglia is associated with neurodegenerative diseases. Multiple studies of AD mouse models have identified AD‐associated microglia subtypes, e.g., disease associated microglia (DAM). However, studies of human microglia have not reported similar microglia subtypes. Therefore, how human microglia change in the presence of amyloid‐ protein deposition and phosphorylated Tau remains an open question.MethodWe have developed an approach that estimates transcriptional kinetics from scRNA‐seq data. This approach models how “bursty” and variable a gene expression is. We hypothesize that transcriptional bursts of key genes are different within AD cases compared to MCI individuals. We used the ROSMAP scRNAseq microglia dataset of 8 AD cases and 4 MCI cases and applied our approach to estimate the transcriptional kinetics for each subject. We then compared the difference in transcriptional kinetics of genes that are estimated both in AD and MCI.ResultFirst, we found that 96% of microglia cells in AD and MCI shows a similar co‐occurrence pattern of expressed genes and, therefore, likely reflect the same cell type. Within the assumed homogeneous microglia cells, we identified two genes, C1QC and ACTB, showing significant differences in their transcriptional kinetics between AD and MCI cases. Both C1QC and ACTB show larger burst sizes in MCI than in AD cases (p‐value for C1QC:0.0038; p‐value for ACTB: 0.00918). Consequently, C1QC and ACTB show a higher expression level variability among microglia cells in MCI cases than AD.ConclusionOur result suggests C1QC and ACTB may be associated with AD risk via changes in variability of gene expression rather than total gene expression levels. The increased variability in transcription of C1QC and ACTB in MCI individuals relative to AD cases might indicate more mobile and active physiological states of microglia. These results may point to functional changes in these genes with AD progression and are prime targets for further experimental validation.

De novo transcriptome assembly of mouse male germ cells reveals novel genes, stage-specific bidirectional promoter activity, and noncoding RNA expression.

In mammals, the adult testis is the tissue with the highest diversity in gene expression. Much of that diversity is attributed to germ cells, primarily meiotic spermatocytes and postmeiotic haploid spermatids. Exploiting a newly developed cell purification method, we profiled the transcriptomes of such postmitotic germ cells of mice. We used a de novo transcriptome assembly approach and identified thousands of novel expressed transcripts characterized by features distinct from those of known genes. Novel loci tend to be short in length, monoexonic, and lowly expressed. Most novel genes have arisen recently in evolutionary time and possess low coding potential. Nonetheless, we identify several novel protein-coding genes harboring open reading frames that encode proteins containing matches to conserved protein domains. Analysis of mass-spectrometry data from adult mouse testes confirms protein production from several of these novel genes. We also examine overlap between transcripts and repetitive elements. We find that although distinct families of repeats are expressed with differing temporal dynamics during spermatogenesis, we do not observe a general mode of regulation wherein repeats drive expression of nonrepetitive sequences in a cell type-specific manner. Finally, we observe many fairly long antisense transcripts originating from canonical gene promoters, pointing to pervasive bidirectional promoter activity during spermatogenesis that is distinct and more frequent compared with somatic cells.

Differential expression of 5mC epigenomic regulators in Alzheimer’s disease

AbstractBackgroundEpigenetic processes are molecular mechanisms that contribute to the pathogenesis of neurodegenerative diseases. 5‐methylcytosine (5mC) and the oxidised state, 5‐formilcytosine (5fC), are known transcriptional regulators moderated by sets of writer, reader, and eraser effector proteins. We propose that gene expression variation in DNA effector proteins may contribute to Alzheimer’s Disease (AD) neuropathology. We also aimed to characterize the distribution of 5fC modifications across brain regions and within cellular compartments to better understand the role of 5mC/5fC modifications in AD.MethodsRNA sequencing data for 17 effector proteins obtained from the Aging, Dementia and Traumatic Brain Injury Study was analysed to assess variation in abundance of 5mC writers, readers, and erasers. Gene expression data were compared across four brain regions in 51 AD and 56 healthy control samples, and between Braak and CERAD neuropathological scales. In addition, we examined the presence and distribution of 5fC by immunofluorescence (IF) across four brain regions in sections from healthy individuals.ResultsTranscripts of DNA methylation writers DNMT1, DNMT3A and DNMT3B were found increased in the AD cohort across 3 brain regions, whilst the reader UHRF1 mRNA was decreased in the same assessment. GADD45B and AICDA, DNA methylation erasers, showed changes in mRNA abundance across Braak and CERAD neuropathological load groupings. IF analysis indicated 5fC modification to be highly abundant in dentate gyrus and within the cytoplasm of hippocampal mossy cells and of neurons in cortical layer III. Within neuronal cells, we observed 5fC partially colocalizing with mitochondria especially within hippocampal neurons.ConclusionOur findings indicate that changes in 5mC/5hmC/5fC effector protein expression are associated with AD and its neuropathology. The characterisation of 5fC localisation in human brain indicates high abundance within the cytoplasm of hippocampal cells suggesting that 5fC may be involved in pre‐ and post‐transcriptional control of memory processing pathways and, when disrupted, may lead to neurodegenerative disease.

Research progress in epigenetic pharmacological effects of rhein

Rhein, which is one of the main active components of Rheum palmatum, has a range of pharmacological activities such as the regulation of the metabolism of glucose and lipids, anti-inflammatory, anti-tumor, anti-fibrosis, etc. Epigenetics refers to the heritable variation of gene expression without altering the DNA sequence. It is involved in the emergence and development of inflammation, renal fibrosis, diabetes, cancer, atherosclerosis, and other diseases, thus becoming a new strategy for the treatment of many di-seases. A series of studies have shown that epigenetic modification may be a common molecular mechanism of various pharmacological effects of rhein. This paper summarized the effects of rhein on the regulation of epigenetic modification and its underlying mechanisms, which involve the regulation of DNA methylation, protein acetylation, and RNA methylation, so as to provide a basis for the development and application of rhein.

Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings.

Deep learning methods have recently become the state of the art in a variety of regulatory genomic tasks1-6, including the prediction of gene expression from genomic DNA. As such, these methods promise to serve as important tools in interpreting the full spectrum of genetic variation observed in personal genomes. Previous evaluation strategies have assessed their predictions of gene expression across genomic regions; however, systematic benchmarking is lacking to assess their predictions across individuals, which would directly evaluate their utility as personal DNA interpreters. We used paired whole genome sequencing and gene expression from 839 individuals in the ROSMAP study7 to evaluate the ability of current methods to predict gene expression variation across individuals at varied loci. Our approach identifies a limitation of current methods to correctly predict the direction of variant effects. We show that this limitation stems from insufficiently learned sequence motif grammar and suggest new model training strategies to improve performance.

The effect of developmental variation on expression QTLs in a multi parental Caenorhabditis elegans population.

Regulation of gene expression plays a crucial role in developmental processes and adaptation to changing environments. expression quantitative trait locus (eQTL) mapping is a technique used to study the genetic regulation of gene expression using the transcriptomes of recombinant inbred lines (RILs). Typically, the age of the inbred lines at the time of RNA sampling is carefully controlled. This is necessary because the developmental process causes changes in gene expression, complicating the interpretation of eQTL mapping experiments. However, due to genetics and variation in ambient micro-environments, organisms can differ in their "developmental age," even if they are of the same chronological age. As a result, eQTL patterns are affected by developmental variation in gene expression. The model organism Caenorhabditis elegans is particularly suited for studying the effect of developmental variation on eQTL mapping patterns. In a span of days, C. elegans transitions from embryo through 4 larval stages to adult while undergoing massive changes to its transcriptome. Here, we use C. elegans to investigate the effect of developmental age variation on eQTL patterns and present a normalization procedure. We used dynamical eQTL mapping, which includes the developmental age as a cofactor, to separate the variation in development from genotypic variation and explain variation in gene expression levels. We compare classical single marker eQTL mapping and dynamical eQTL mapping using RNA-seq data of ∼200 multi-parental RILs of C. elegans. The results show that (1) many eQTLs are caused by developmental variation, (2) most trans-bands are developmental QTLs, and (3) dynamical eQTL mapping detects additional eQTLs not found with classical eQTL mapping. We recommend that correction for variation in developmental age should be strongly considered in eQTL mapping studies given the large impact of processes like development on the transcriptome.

Methylation-directed regulatory networks determine enhancing and silencing of mutation disease driver genes and explain inter-patient expression variation

BackgroundCommon diseases manifest differentially between patients, but the genetic origin of this variation remains unclear. To explore possible involvement of gene transcriptional-variation, we produce a DNA methylation-oriented, driver-gene-wide dataset of regulatory elements in human glioblastomas and study their effect on inter-patient gene expression variation.ResultsIn 175 of 177 analyzed gene regulatory domains, transcriptional enhancers and silencers are intermixed. Under experimental conditions, DNA methylation induces enhancers to alter their enhancing effects or convert into silencers, while silencers are affected inversely. High-resolution mapping of the association between DNA methylation and gene expression in intact genomes reveals methylation-related regulatory units (average size = 915.1 base-pairs). Upon increased methylation of these units, their target-genes either increased or decreased in expression. Gene-enhancing and silencing units constitute cis-regulatory networks of genes. Mathematical modeling of the networks highlights indicative methylation sites, which signified the effect of key regulatory units, and add up to make the overall transcriptional effect of the network. Methylation variation in these sites effectively describe inter-patient expression variation and, compared with DNA sequence-alterations, appears as a major contributor of gene-expression variation among glioblastoma patients.ConclusionsWe describe complex cis-regulatory networks, which determine gene expression by summing the effects of positive and negative transcriptional inputs. In these networks, DNA methylation induces both enhancing and silencing effects, depending on the context. The revealed mechanism sheds light on the regulatory role of DNA methylation, explains inter-individual gene-expression variation, and opens the way for monitoring the driving forces behind deferential courses of cancer and other diseases.

Evaluating the Performance of Widely Used Phylogenetic Models for Gene Expression Evolution.

Phylogenetic comparative methods are increasingly used to test hypotheses about the evolutionary processes that drive divergence in gene expression among species. However, it is unknown whether the distributional assumptions of phylogenetic models designed for quantitative phenotypic traits are realistic for expression data and importantly, the reliability of conclusions of phylogenetic comparative studies of gene expression may depend on whether the data is well described by the chosen model. To evaluate this, we first fit several phylogenetic models of trait evolution to 8 previously published comparative expression datasets, comprising a total of 54,774 genes with 145,927 unique gene-tissue combinations. Using a previously developed approach, we then assessed how well the best model of the set described the data in an absolute (not just relative) sense. First, we find that Ornstein-Uhlenbeck models, in which expression values are constrained around an optimum, were the preferred models for 66% of gene-tissue combinations. Second, we find that for 61% of gene-tissue combinations, the best-fit model of the set was found to perform well; the rest were found to be performing poorly by at least one of the test statistics we examined. Third, we find that when simple models do not perform well, this appears to be typically a consequence of failing to fully account for heterogeneity in the rate of the evolution. We advocate that assessment of model performance should become a routine component of phylogenetic comparative expression studies; doing so can improve the reliability of inferences and inspire the development of novel models.

Identification and fine mapping of qSW2 for leaf slow wilting in soybean

Drought is one of the abiotic stresses limiting the production of soybean (Glycine max). Elucidation of the genetic and molecular basis of the slow-wilting (SW) trait of this crop offers the prospect of its genetic improvement. A panel of 188 accessions and a set of recombinant inbred lines produced from a cross between cultivars Liaodou 14 and Liaodou 21 were used to identify quantitative-trait loci (QTL) associated with SW. Plants were genotyped by Specific-locus amplified fragment sequencing and seedling leaf wilting was assessed under three water-stress treatments. A genome-wide association study identified 26 SW-associated single-nucleotide polymorphisms (SNPs), including three located in a 248-kb linkage-disequilibrium (LD) block on chromosome 2. Linkage mapping revealed a major-effect QTL, qSW2, associated with all three treatments and adjacent to the LD block. Fine mapping in a BC2F3 population derived from a backcross between Liaodou 21 and R26 confined qSW2 to a 60-kb interval. Gene expression and sequence variation analysis identified the gene Glyma.02 g218100, encoding an auxin transcription factor, as a candidate gene for qSW2. Our results will contribute significantly to improving drought-resistant soybean cultivars by providing genetic information and resources.

SpliceWiz: interactive analysis and visualization of alternative splicing in R.

Alternative splicing (AS) is a crucial mechanism for regulating gene expression and isoform diversity in eukaryotes. However, the analysis and visualization of AS events from RNA sequencing data remains challenging. Most tools require a certain level of computer literacy and the available means of visualizing AS events, such as coverage and sashimi plots, have limitations and can be misleading. To address these issues, we present SpliceWiz, an R package with an interactive Shiny interface that allows easy and efficient AS analysis and visualization at scale. A novel normalization algorithm is implemented to aggregate splicing levels within sample groups, thereby allowing group differences in splicing levels to be accurately visualized. The tool also offers downstream gene ontology enrichment analysis, highlighting ASEs belonging to functional pathways of interest. SpliceWiz is optimized for speed and efficiency and introduces a new file format for coverage data storage that is more efficient than BigWig. Alignment files are processed orders of magnitude faster than other R-based AS analysis tools and on par with command-line tools. Overall, SpliceWiz streamlines AS analysis, enabling reliable identification of functionally relevant AS events for further characterization. SpliceWiz is a Bioconductor package and is also available on GitHub (https://github.com/alexchwong/SpliceWiz).

Clustering malignant cell states using universally variable genes.

Single-cell RNA sequencing (scRNA-seq) has revealed important insights into the heterogeneity of malignant cells. However, sample-specific genomic alterations often confound such analysis, resulting in patient-specific clusters that are difficult to interpret. Here, we present a novel approach to address the issue. By normalizing gene expression variances to identify universally variable genes (UVGs), we were able to reduce the formation of sample-specific clusters and identify underlying molecular hallmarks in malignant cells. In contrast to highly variable genes vulnerable to a specific sample bias, UVGs led to better detection of clusters corresponding to distinct malignant cell states. Our results demonstrate the utility of this approach for analyzing scRNA-seq data and suggest avenues for further exploration of malignant cell heterogeneity.

In vitro and in vivo antimicrobial effects of domiphen combined with itraconazole against Aspergillus fumigatus

Aspergillus fumigatus, a prevalent saprophytic fungus in the atmosphere, is known to rapidly induce severe invasive aspergillosis (IA) upon inhalation of its conidia by humans or animals. The mortality rate associated with IA exceeds 50%. The misuse of antifungal agents has contributed to the emergence of numerous highly pathogenic drug-resistant strains of A. fumigatus. Our study found that the combination of domiphen and itraconazole had sound synergistic antimicrobial effects against wild-type and itraconazole-resistant A. fumigatus in vivo and in vitro through MIC, FIC, plate inoculation, growth curve experiments, and Galleria mellonella infection model. Drug cytotoxicity and pharmacological tests for acute toxicity assays demonstrated that both itraconazole and domiphen showed minimal cytotoxicity and good biocompatibility. The transcriptome sequencing experiment demonstrated that domiphen exerted a suppressive effect on the expression of various genes, including those involved in drug efflux, redox regulation, and cellular membrane and cell wall remodeling. The present investigation explores the synergistic antimicrobial mechanisms of domiphen and itraconazole, encompassing three key aspects: (i) domiphen inhibited the efflux of itraconazole by reducing the expression of drug efflux-related genes, (ii) the combination has good ability to disrupt the cell membrane and cell wall, (iii) the combination also can remove biofilm more effectively. In summary, the utilization of domiphen as a synergist of itraconazole exhibited disruptive effects on the biofilm, cell wall, and cell membrane of A. fumigatus. This subsequently led to a modified distribution of itraconazole within the fungal organism, ultimately resulting in enhanced antifungal efficacy. The results of this study may provide a new therapeutic strategy for the treatment of IA caused by drug-resistant A. fumigatus.

Genome-wide expression QTL mapping reveals the highly dynamic regulatory landscape of a major wheat pathogen

BackgroundIn agricultural ecosystems, outbreaks of diseases are frequent and pose a significant threat to food security. A successful pathogen undergoes a complex and well-timed sequence of regulatory changes to avoid detection by the host immune system; hence, well-tuned gene regulation is essential for survival. However, the extent to which the regulatory polymorphisms in a pathogen population provide an adaptive advantage is poorly understood.ResultsWe used Zymoseptoria tritici, one of the most important pathogens of wheat, to generate a genome-wide map of regulatory polymorphism governing gene expression. We investigated genome-wide transcription levels of 146 strains grown under nutrient starvation and performed expression quantitative trait loci (eQTL) mapping. We identified cis-eQTLs for 65.3% of all genes and the majority of all eQTL loci are within 2kb upstream and downstream of the transcription start site (TSS). We also show that polymorphism in different gene elements contributes disproportionally to gene expression variation. Investigating regulatory polymorphism in gene categories, we found an enrichment of regulatory variants for genes predicted to be important for fungal pathogenesis but with comparatively low effect size, suggesting a separate layer of gene regulation involving epigenetics. We also show that previously reported trait-associated SNPs in pathogen populations are frequently cis-regulatory variants of neighboring genes with implications for the trait architecture.ConclusionsOverall, our study provides extensive evidence that single populations segregate large-scale regulatory variation and are likely to fuel rapid adaptation to resistant hosts and environmental change.

Single-nucleus RNA sequencing of Nicotiana tabacum seedlings reveals heterogeneity among cell types

Growth of multicellular organisms relies on diversity in gene expression between cells of different functions. Single-cell transcriptomes can facilitate analysis of cell specific response to different environmental stress. By performing single-nucleus sequencing of tobacco (Nicotiana tabacum) seedlings, 13,028 single cells were profiled. We identified 29 clusters corresponding to 18 cell types, some of which were verified by in situ hybridization. Developmental trajectory results and comparisons of ligand-receptor repertoires revealed cell specific functions of different cell types in tobacco seedlings. Divergent and conserved genes between tobacco and rice (Oryza sativa) highlighted some cell specific and species specific gene features. Our study generated the first single-cell transcriptome atlas of tobacco seedling, providing a wide range of information into the role and functions of different cell types.

Analysis of Carica papaya Informs Lineage-Specific Evolution of the Aquaporin (AQP) Family in Brassicales.

Aquaporins (AQPs), a type of intrinsic membrane proteins that transport water and small solutes across biological membranes, play crucial roles in plant growth and development. This study presents a first genome-wide identification and comparative analysis of the AQP gene family in papaya (Carica papaya L.), an economically and nutritionally important fruit tree of tropical and subtropical regions. A total of 29 CpAQP genes were identified, which represent five subfamilies, i.e., nine plasma intrinsic membrane proteins (PIPs), eight tonoplast intrinsic proteins (TIPs), seven NOD26-like intrinsic proteins (NIPs), two X intrinsic proteins (XIPs), and three small basic intrinsic proteins (SIPs). Although the family is smaller than the 35 members reported in Arabidopsis, it is highly diverse, and the presence of CpXIP genes as well as orthologs in Moringa oleifera and Bretschneidera sinensis implies that the complete loss of the XIP subfamily in Arabidopsis is lineage-specific, sometime after its split with papaya but before Brassicaceae-Cleomaceae divergence. Reciprocal best hit-based sequence comparison of 530 AQPs and synteny analyses revealed that CpAQP genes belong to 29 out of 61 identified orthogroups, and lineage-specific evolution was frequently observed in Brassicales. Significantly, the well-characterized NIP3 group was completely lost; lineage-specific loss of the NIP8 group in Brassicaceae occurred sometime before the divergence with Cleomaceae, and lineage-specific loss of NIP2 and SIP3 groups in Brassicaceae occurred sometime after the split with Cleomaceae. In contrast to a predominant role of recent whole-genome duplications (WGDs) on the family expansion in B. sinensis, Tarenaya hassleriana, and Brassicaceae plants, no recent AQP repeats were identified in papaya, and ancient WGD repeats are mainly confined to the PIP subfamily. Subfamily even group-specific evolution was uncovered via comparing exon-intron structures, conserved motifs, the aromatic/arginine selectivity filter, and gene expression profiles. Moreover, down-regulation during fruit ripening and expression divergence of duplicated CpAQP genes were frequently observed in papaya. These findings will not only improve our knowledge on lineage-specific family evolution in Brassicales, but also provide valuable information for further studies of AQP genes in papaya and species beyond.