19 research outputs found
Single-Cell Analysis Uncovers a Vast Diversity in Intracellular Viral Defective Interfering RNA Content Affecting the Large Cell-to-Cell Heterogeneity in Influenza A Virus Replication
Virus replication displays a large cell-to-cell heterogeneity; yet, not all sources of this variability are known. Here, we study the effect of defective interfering (DI) particle (DIP) co-infection on cell-to-cell variability in influenza A virus (IAV) replication. DIPs contain a large internal deletion in one of their eight viral RNAs (vRNA) and are, thus, defective in virus replication. Moreover, they interfere with virus replication. Using single-cell isolation and reverse transcription polymerase chain reaction, we uncovered a large between-cell heterogeneity in the DI vRNA content of infected cells, which was confirmed for DI mRNAs by single-cell RNA sequencing. A high load of intracellular DI vRNAs and DI mRNAs was found in low-productive cells, indicating their contribution to the large cell-to-cell variability in virus release. Furthermore, we show that the magnitude of host cell mRNA expression (some factors may inhibit virus replication), but not the ribosome content, may further affect the strength of single-cell virus replication. Finally, we show that the load of viral mRNAs (facilitating viral protein production) and the DI mRNA content are, independently from one another, connected with single-cell virus production. Together, these insights advance single-cell virology research toward the elucidation of the complex multi-parametric origin of the large cell-to-cell heterogeneity in virus infections
Iranome: A catalogue of genomic variations in the Iranian population
Considering the application of human genome variation databases in precision medicine, population-specific genome projects are continuously being developed. However, the Middle Eastern population is underrepresented in current databases. Accordingly, we established Iranome database (www.iranome.com) by performing whole exome sequencing on 800 individuals from eight major Iranian ethnic groups representing the second largest population of Middle East. We identified 1,575,702 variants of which 308,311 were novel (19.6%). Also, by presenting higher frequency for 37,384 novel or known rare variants, Iranome database can improve the power of molecular diagnosis. Moreover, attainable clinical information makes this database a good resource for classifying pathogenicity of rare variants. Principal components analysis indicated that, apart from Iranian-Baluchs, Iranian-Turkmen, and Iranian-Persian Gulf Islanders, who form their own clusters, rest of the population were genetically linked, forming a super-population. Furthermore, only 0.6% of novel variants showed counterparts in "Greater Middle East Variome Project", emphasizing the value of Iranome at national level by releasing a comprehensive catalog of Iranian genomic variations and also filling another gap in the catalog of human genome variations at international level. We introduce Iranome as a resource which may also be applicable in other countries located in neighboring regions historically called Greater Iran (Persia)
MicroRNA in prostate cancer: functional importance and potential as circulating biomarkers
Identification of microRNA profile specific to cancer stem-like cells directly isolated from human larynx cancer specimens
Sleep neuron depolarization promotes protective gene expression changes and FOXO activation
Sleep is an essential state that allows for recuperation and survival processes. Disturbing sleep triggers stress responses that promote protective gene expression. Sleep and its deprivation grossly impact gene expression, but little is known about how normal or disturbed sleep control gene expression. Central to the induction of sleep are sleep-active neurons, which inhibit wakefulness and promote survival. Sleep and sleep-active neurons are highly conserved. In Caenorhabditis elegans, the sleep-active RIS neuron is crucial for sleep and survival. Here, we show that RIS depolarization promotes the protective gene expression response that occurs during developmental arrest. This response includes the activation of FOXO/DAF-16 and expression of DAF-16 target genes such as HSP-12.6, a small heat-shock protein that is required for starvation survival. Disturbing sleep by mechanical stimulation increases RIS depolarization. RIS activation in turn activates DAF-16 and other genes required for survival. Hence, during normal sleep, RIS depolarization promotes protective gene expression. When sleep is disturbed, protective gene expression gets further increased by raised RIS depolarization. We thus link sleep-active neuron depolarization to protective gene expression changes and suggest that the cellular stress response following sleep deprivation could be understood as a safeguarding process that is caused by the overactivation of sleep-active neurons
Health monitoring in birds using bio-loggers and whole blood transcriptomics
Monitoring and early detection of emerging infectious diseases in wild animals is of crucial global importance, yet reliable ways to measure immune status and responses are lacking for animals in the wild. Here we assess the usefulness of bio-loggers for detecting disease outbreaks in free-living birds and confirm detailed responses using leukocyte composition and large-scale transcriptomics. We simulated natural infections by viral and bacterial pathogens in captive mallards (Anas platyrhynchos), an important natural vector for avian influenza virus. We show that body temperature, heart rate and leukocyte composition change reliably during an acute phase immune response. Using genome-wide gene expression profiling of whole blood across time points we confirm that immunostimulants activate pathogen-specific gene regulatory networks. By reporting immune response related changes in physiological and behavioural traits that can be studied in free-ranging populations, we provide baseline information with importance to the global monitoring of zoonotic diseases.publishe
Haplotype-resolved sweet potato genome traces back its hexaploidization history
Here we present the 15 pseudochromosomes of sweet potato, Ipomoea batatas, the seventh most important crop in the world and the fourth most significant in China. By using a novel haplotyping method based on genome assembly, we have produced a half haplotype-resolved genome from ~296âGb of paired-end sequence reads amounting to roughly 67-fold coverage. By phylogenetic tree analysis of homologous chromosomes, it was possible to estimate the time of two recent whole-genome duplication events as occurring about 0.8 and 0.5 million years ago. This half haplotype-resolved hexaploid genome represents the first successful attempt to investigate the complexity of chromosome sequence composition directly in a polyploid genome, using sequencing of the polyploid organism itself rather than any of its simplified proxy relatives. Adaptation and application of our approach should provide higher resolution in future genomic structure investigations, especially for similarly complex genomes.Assembly of polyploid plant genomes has been technically challenging. Now, a study presents a half haplotype-resolved hexaploid genome of sweet potato, Ipomoea batatas, using a novel haplotyping method
The metabolic background is a global player in Saccharomyces gene expression epistasis
The regulation of gene expression in response to nutrient availability is fundamental to the genotypeâphenotype relationship. The metabolicâgenetic make-up of the cell, as reflected in auxotrophy, is hence likely to be a determinant of gene expression. Here, we address the importance of the metabolicâgenetic background by monitoring transcriptome, proteome and metabolome in a repertoire of 16 Saccharomyces cerevisiae laboratory backgrounds, combinatorially perturbed in histidine, leucine, methionine and uracil biosynthesis. The metabolic background affected up to 85% of the coding genome. Suggesting widespread confounding, these transcriptional changes show, on average, 83% overlap between unrelated auxotrophs and 35% with previously published transcriptomes generated for non-metabolic gene knockouts. Background-dependent gene expression correlated with metabolic flux and acted, predominantly through masking or suppression, on 88% of transcriptional interactions epistatically. As a consequence, the deletion of the same metabolic gene in a different background could provoke an entirely different transcriptional response. Propagating to the proteome and scaling up at the metabolome, metabolic background dependencies reveal the prevalence of metabolism-dependent epistasis at all regulatory levels. Urging a fundamental change of the prevailing laboratory practice of using auxotrophs and nutrient supplemented media, these results reveal epistatic intertwining of metabolism with gene expression on the genomic scale
Genome-wide DNA Methylation Events in TMPRSS2âERG
Prostate cancer is the second most common cancer among men worldwide. Alterations in the DNA methylation pattern can be one of the leading causes for prostate cancer formation. This study is the first high-throughput sequencing study investigating genome-wide DNA methylation patterns in a large cohort of 51 tumor and 53 benign prostate samples using methylated DNA immunoprecipitation sequencing. Comparative analyses identified more than 147,000 cancer-associated epigenetic alterations. In addition, global methylation patterns show significant differences based on the TMPRSS2-ERG rearrangement status. We propose the hypermethylation of miR-26a as an alternative pathway of ERG rearrangement-independent EZH2 activation. The observed increase in differential methylation events in fusion-negative tumors can explain the tumorigenic process in the absence of genomic rearrangements. SIGNIFICANCE: In contrast to TMPRSS2-ERG -rearranged tumors, the pathomechanism for gene fusion-negative tumors is completely unclear. Using a sequencing-based approach, our work uncovers significant global epigenetic alterations in TMPRSS2-ERG gene fusion-negative tumors and provides a mechanistic explanation for the tumor formation process