13273 research outputs found
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Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato
No full textStructural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement
Multiplexed Evaluation of Microdosed Antineoplastic Agents In Situ in the Tumor Microenvironment of Patients with Soft Tissue Sarcoma
No full textPURPOSE: A persistent issue in cancer drug development is the discordance between robust antitumor drug activity observed in laboratory models and the limited benefit frequently observed when patients are treated with the same agents in clinical trials. Difficulties in accurately modeling the complexities of human tumors may underlie this problem. To address this issue, we developed Comparative In Vivo Oncology (CIVO), which enables in situ investigation of multiple microdosed drugs simultaneously in a patient's tumor. This study was designed to test CIVO's safety and feasibility in patients with soft tissue sarcoma (STS). PATIENTS AND METHODS: We conducted a single arm, prospective, 13-patient pilot study. Patients scheduled for incisional biopsy or tumor resection were CIVO-injected 1 to 3 days prior to surgery. Saline or microdoses of anticancer agents were percutaneously injected into the tumor in a columnar fashion through each of eight needles. Following excision, drug responses were evaluated in the injected tissue. RESULTS: The primary objective was met, establishing CIVO's feasibility and safety. Device-related adverse events were limited to transient grade 1 nonserious events. In addition, biomarker evaluation of localized tumor response to CIVO microinjected drugs by IHC or with NanoString GeoMx Digital Spatial Profiler demonstrated consistency with known mechanisms of action of each drug, impact on the tumor microenvironment, and historic clinical activity. CONCLUSIONS: These results are an advance toward use of CIVO as a translational research tool for early evaluation of investigational agents and drug combinations in a novel approach to phase 0 trials.See related commentary by Sleijfer and Lolkema, p. 3897
Dissecting cell-type-specific metabolism in pancreatic ductal adenocarcinoma
No full textTumors are composed of many different cell types including cancer cells, fibroblasts, and immune cells. Dissecting functional metabolic differences between cell types within a mixed population can be challenging due to the rapid turnover of metabolites relative to the time needed to isolate cells. To overcome this challenge, we traced isotope-labeled nutrients into macromolecules that turn over more slowly than metabolites. This approach was used to assess differences between cancer cell and fibroblast metabolism in murine pancreatic cancer organoid-fibroblast co-cultures and tumors. Pancreatic cancer cells exhibited increased pyruvate carboxylation relative to fibroblasts, and this flux depended on both pyruvate carboxylase and malic enzyme 1 activity. Consequently, expression of both enzymes in cancer cells was necessary for organoid and tumor growth, demonstrating that dissecting the metabolism of specific cell populations within heterogeneous systems can identify dependencies that may not be evident from studying isolated cells in culture or bulk tissue.
Tumors contain a mixture of many different types of cells, including cancer cells and non-cancer cells. The interactions between these two groups of cells affect how the cancer cells use nutrients, which, in turn, affects how fast these cells grow and divide. Furthermore, different cell types may use nutrients in diverse ways to make other molecules – known as metabolites – that the cell needs to survive. Fibroblasts are a subset of non-cancer cells that are typically found in tumors and can help them form. Separating fibroblasts from cancer cells in a tumor takes a lot longer than the chemical reactions in each cell of the tumor that produce and use up nutrients, also known as the cell’s metabolism. Therefore, measuring the levels of glucose (the sugar that is the main energy source for cells) and other metabolites in each tumor cell after separating them does not necessarily provide accurate information about the tumor cell’s metabolism. This makes it difficult to study how cancer cells and fibroblasts use nutrients differently. Lau et al. have developed a strategy to study the metabolism of cancer cells and fibroblasts in tumors. Mice with tumors in their pancreas were provided glucose that had been labelled using biochemical techniques. As expected, when the cell processed the glucose, the label was transferred into metabolites that got used up very quickly. But the label also became incorporated into larger, more stable molecules, such as proteins. Unlike the small metabolites, these larger molecules do not change in the time it takes to separate the cancer cells from the fibroblasts. Lau et al. sorted cells from whole pancreatic tumors and analyzed large, stable molecules that can incorporate the label from glucose in cancer cells and fibroblasts. The experiments showed that, in cancer cells, these molecules were more likely to have labeling patterns that are characteristic of two specific enzymes called pyruvate carboxylase and malic enzyme 1. This suggests that these enzymes are more active in cancer cells. Lau et al. also found that pancreatic cancer cells needed these two enzymes to metabolize glucose and to grow into large tumors. Pancreatic cancer is one of the most lethal cancers and current therapies offer limited benefit to many patients. Therefore, it is important to develop new drugs to treat this disease. Understanding how cancer cells and non-cancer cells in pancreatic tumors use nutrients differently is important for developing drugs that only target cancer cells.
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Intraductal Transplantation Models of Human Pancreatic Ductal Adenocarcinoma Reveal Progressive Transition of Molecular Subtypes.
No full textPancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated; however, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present a xenotransplantation model of PDAC in which neoplasms originate from patient-derived organoids injected directly into murine pancreatic ducts. Our model enables distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively. Parameters that influence PDAC subtype specification in this intraductal model include cell plasticity and hyperactivation of the RAS pathway. Finally, through intratumoral dissection and the direct manipulation of RAS gene dosage, we identify a suite of RAS-regulated secreted and membrane-bound proteins that may represent potential candidates for therapeutic intervention in patients with PDAC. SIGNIFICANCE: Accurate modeling of the molecular subtypes of pancreatic cancer is crucial to facilitate the generation of effective therapies. We report the development of an intraductal organoid transplantation model of pancreatic cancer that models the progressive switching of subtypes, and identify stochastic and RAS-driven mechanisms that determine subtype specification.See related commentary by Pickering and Morton, p. 1448.This article is highlighted in the In This Issue feature, p. 1426
Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery
No full textCrop productivity depends on activity of meristems that produce optimized plant architectures, including that of the maize ear. A comprehensive understanding of development requires insight into the full diversity of cell types and developmental domains and the gene networks required to specify them. Until now, these were identified primarily by morphology and insights from classical genetics, which are limited by genetic redundancy and pleiotropy. Here, we investigated the transcriptional profiles of 12,525 single cells from developing maize ears. The resulting developmental atlas provides a single-cell RNA sequencing (scRNA-seq) map of an inflorescence. We validated our results by mRNA in situ hybridization and by fluorescence-activated cell sorting (FACS) RNA-seq, and we show how these data may facilitate genetic studies by predicting genetic redundancy, integrating transcriptional networks, and identifying candidate genes associated with crop yield traits
Endogenous Retroviruses Walk a Fine Line between Priming and Silencing
Get PDFEndogenous retroviruses (ERVs) in mammals are closely related to infectious retroviruses and utilize host tRNAs as a primer for reverse transcription and replication, a hallmark of long terminal repeat (LTR) retroelements. Their dependency on tRNA makes these elements vulnerable to targeting by small RNAs derived from the 3'-end of mature tRNAs (3'-tRFs), which are highly expressed during epigenetic reprogramming and potentially protect many tissues in eukaryotes. Here, we review some key functions of ERV reprogramming during mouse and human development and discuss how small RNA-mediated silencing maintains genome stability when ERVs are temporarily released from heterochromatin repression. In particular, we take a closer look at the tRNA primer binding sites (PBS) of two highly active ERV families in mice and their sequence variation that is shaped by the conflict of successful tRNA priming for replication versus evasion of silencing by 3'-tRFs
Co-expression of calcium and hERG potassium channels reduces the incidence of proarrhythmic events.
No full textAIMS: Cardiac electrical activity is extraordinarily robust. However, when it goes wrong it can have fatal consequences. Electrical activity in the heart is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. Whilst there is considerable variability in cardiac ion channel expression levels between individuals, studies in rodents have indicated that there are modules of ion channels whose expression co-vary. The aim of this study was to investigate whether meta-analytic co-expression analysis of large-scale gene expression data sets could identify modules of co-expressed cardiac ion channel genes in human hearts that are of functional importance. METHODS AND RESULTS: Meta-analysis of 3653 public human RNA-seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was also observed in human adult heart tissue samples. In silico modeling suggested that co-expression of CACNA1C and KCNH2 would limit the variability in action potential duration seen with variations in expression of ion channel genes and reduce susceptibility to early afterdepolarizations, a surrogate marker for pro-arrhythmia. We also found that levels of KCNH2 and CACNA1C expression are correlated in human induced pluripotent stem cell derived cardiac myocytes and the levels of CACNA1C and KCNH2 expression were inversely correlated with the magnitude of changes in repolarization duration following inhibition of IKr. CONCLUSIONS: Meta-analytic approaches of multiple independent human gene expression datasets can be used to identify gene modules that are important for regulating heart function. Specifically, we have verified that there is co-expression of CACNA1C and KCNH2 ion channel genes in human heart tissue, and in silico analyses suggest that CACNA1C-KCNH2 co-expression increases the robustness of cardiac electrical activity. TRANSLATIONAL PERSPECTIVE: Here, we show, using meta-analysis of multiple independent human gene expression datasets, that there is co-expression of KCNH2-CACNA1C in human heart tissue which was then confirmed in human cardiac myocytes derived from induced pluripotent stem cells. Both in silico and functional studies show that the co-expression of CACNA1C and KCNH2 increases the robustness of cardiac electrical signalling. Our data also suggest that those patients who express higher levels of CACNA1C and KCNH2 are likely to be more susceptible to arrhythmias when exposed to drugs that block IKr, the major cause of drug-induced cardiac arrhythmias
Arabidopsis DNA Replication Initiates in Intergenic, AT-rich Open Chromatin
No full textThe selection and firing of DNA replication origins play key roles in ensuring that eukaryotes accurately replicate their genomes. This process is not well documented in plants due in large measure to difficulties in working with plant systems. We developed a new functional assay to label and map very early replicating loci that must, by definition, include at least a subset of replication origins. Arabidopsis thaliana cells were briefly labeled with 5-ethynyl-2'-deoxy-uridine, and nuclei were subjected to two-parameter flow sorting. We identified more than 5500 loci as initiation regions (IRs), the first regions to replicate in very early S phase. These were classified as strong or weak IRs based on the strength of their replication signals. Strong initiation regions were evenly spaced along chromosomal arms and depleted in centromeres, while weak initiation regions were enriched in centromeric regions. IRs are AT-rich sequences flanked by more GC-rich regions and located predominantly in intergenic regions. Nuclease sensitivity assays indicated that IRs are associated with accessible chromatin. Based on these observations, initiation of plant DNA replication shows some similarity to, but is also distinct from, initiation in other well-studied eukaryotic systems
Mobile Genomics: Tools and Techniques for Tackling Transposons
No full textNext-generation sequencing approaches have fundamentally changed the types of questions that can be asked about gene function and regulation. With the goal of approaching truly genome-wide quantifications of all the interaction partners and downstream effects of particular genes, these quantitative assays have allowed for an unprecedented level of detail in exploring biological interactions. However, many challenges remain in our ability to accurately describe and quantify the interactions that take place in those hard to reach and extremely repetitive regions of our genome comprised mostly of transposable elements (TEs). Tools dedicated to TE-derived sequences have lagged behind, making the inclusion of these sequences in genome-wide analyses difficult. Recent improvements, both computational and experimental, allow for the better inclusion of TE sequences in genomic assays and a renewed appreciation for the importance of TE biology. This review will discuss the recent improvements that have been made in the computational analysis of TE-derived sequences as well as the areas where such analysis still proves difficult. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'
CoCoCoNet: conserved and comparative co-expression across a diverse set of species
Get PDFCo-expression analysis has provided insight into gene function in organisms from Arabidopsis to zebrafish. Comparison across species has the potential to enrich these results, for example by prioritizing among candidate human disease genes based on their network properties or by finding alternative model systems where their co-expression is conserved. Here, we present CoCoCoNet as a tool for identifying conserved gene modules and comparing co-expression networks. CoCoCoNet is a resource for both data and methods, providing gold standard networks and sophisticated tools for on-the-fly comparative analyses across 14 species. We show how CoCoCoNet can be used in two use cases. In the first, we demonstrate deep conservation of a nucleolus gene module across very divergent organisms, and in the second, we show how the heterogeneity of autism mechanisms in humans can be broken down by functional groups and translated to model organisms. CoCoCoNet is free to use and available to all at https://milton.cshl.edu/CoCoCoNet, with data and R scripts available at ftp://milton.cshl.edu/data