Статті в журналах: "Transcriptome atla"

1

Packer, Jonathan S., Qin Zhu, Chau Huynh, Priya Sivaramakrishnan, Elicia Preston, Hannah Dueck, Derek Stefanik, et al. "A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution." Science 365, no. 6459 (September 5, 2019): eaax1971. http://dx.doi.org/10.1126/science.aax1971.

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Caenorhabditis elegans is an animal with few cells but a wide diversity of cell types. In this study, we characterize the molecular basis for their specification by profiling the transcriptomes of 86,024 single embryonic cells. We identify 502 terminal and preterminal cell types, mapping most single-cell transcriptomes to their exact position in C. elegans’ invariant lineage. Using these annotations, we find that (i) the correlation between a cell’s lineage and its transcriptome increases from middle to late gastrulation, then falls substantially as cells in the nervous system and pharynx adopt their terminal fates; (ii) multilineage priming contributes to the differentiation of sister cells at dozens of lineage branches; and (iii) most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state.

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2

Callaway, Edward M., Hong-Wei Dong, Joseph R. Ecker, Michael J. Hawrylycz, Z. Josh Huang, Ed S. Lein, John Ngai, et al. "A multimodal cell census and atlas of the mammalian primary motor cortex." Nature 598, no. 7879 (October 6, 2021): 86–102. http://dx.doi.org/10.1038/s41586-021-03950-0.

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AbstractHere we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

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3

Altıntaş, Ali, Rhianna C. Laker, Christian Garde, Romain Barrès, and Juleen R. Zierath. "Transcriptomic and epigenomics atlas of myotubes reveals insight into the circadian control of metabolism and development." Epigenomics 12, no. 8 (April 2020): 701–13. http://dx.doi.org/10.2217/epi-2019-0391.

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Aim: Innate circadian rhythms are critical for optimal tissue-specific functions, including skeletal muscle, a major insulin-sensitive tissue responsible for glucose homeostasis. We determined whether transcriptional oscillations are associated with CpG methylation changes in skeletal muscle. Materials & methods: We performed rhythmicity analysis on the transcriptome and CpG methylome of circadian synchronized myotubes. Results: We identified several transcripts and CpG-sites displaying oscillatory behavior, which were enriched with Gene Ontology terms related to metabolism and development. Oscillating CpG methylation was associated with rhythmic expression of 31 transcripts. Conclusion: Although circadian oscillations may be regulated by rhythmic DNA methylation, strong rhythmic associations between transcriptome and CpG methylation were not identified. This resource constitutes a transcriptomic/epigenomic atlas of skeletal muscle and regulation of circadian rhythms.

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4

D’Mello, Adonis, Ashleigh N. Riegler, Eriel Martínez, Sarah M. Beno, Tiffany D. Ricketts, Ellen F. Foxman, Carlos J. Orihuela, and Hervé Tettelin. "An in vivo atlas of host–pathogen transcriptomes during Streptococcus pneumoniae colonization and disease." Proceedings of the National Academy of Sciences 117, no. 52 (December 14, 2020): 33507–18. http://dx.doi.org/10.1073/pnas.2010428117.

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Streptococcus pneumoniae (Spn) colonizes the nasopharynx and can cause pneumonia. From the lungs it spreads to the bloodstream and causes organ damage. We characterized the in vivo Spn and mouse transcriptomes within the nasopharynx, lungs, blood, heart, and kidneys using three Spn strains. We identified Spn genes highly expressed at all anatomical sites and in an organ-specific manner; highly expressed genes were shown to have vital roles with knockout mutants. The in vivo bacterial transcriptome during colonization/disease was distinct from previously reported in vitro transcriptomes. Distinct Spn and host gene-expression profiles were observed during colonization and disease states, revealing specific genes/operons whereby Spn adapts to and influences host sites in vivo. We identified and experimentally verified host-defense pathways induced by Spn during invasive disease, including proinflammatory responses and the interferon response. These results shed light on the pathogenesis of Spn and identify therapeutic targets.

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5

Song, Liting, Shaojun Pan, Zichao Zhang, Longhao Jia, Wei-Hua Chen, and Xing-Ming Zhao. "STAB: a spatio-temporal cell atlas of the human brain." Nucleic Acids Research 49, no. D1 (September 25, 2020): D1029—D1037. http://dx.doi.org/10.1093/nar/gkaa762.

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Abstract The human brain is the most complex organ consisting of billions of neuronal and non-neuronal cells that are organized into distinct anatomical and functional regions. Elucidating the cellular and transcriptome architecture underlying the brain is crucial for understanding brain functions and brain disorders. Thanks to the single-cell RNA sequencing technologies, it is becoming possible to dissect the cellular compositions of the brain. Although great effort has been made to explore the transcriptome architecture of the human brain, a comprehensive database with dynamic cellular compositions and molecular characteristics of the human brain during the lifespan is still not available. Here, we present STAB (a Spatio-Temporal cell Atlas of the human Brain), a database consists of single-cell transcriptomes across multiple brain regions and developmental periods. Right now, STAB contains single-cell gene expression profiling of 42 cell subtypes across 20 brain regions and 11 developmental periods. With STAB, the landscape of cell types and their regional heterogeneity and temporal dynamics across the human brain can be clearly seen, which can help to understand both the development of the normal human brain and the etiology of neuropsychiatric disorders. STAB is available at http://stab.comp-sysbio.org.

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6

Dargahi, Daryanaz, Richard D. Swayze, Leanna Yee, Peter J. Bergqvist, Bradley J. Hedberg, Alireza Heravi-Moussavi, Edie M. Dullaghan, et al. "A Pan-Cancer Analysis of Alternative Splicing Events Reveals Novel Tumor-Associated Splice Variants of Matriptase." Cancer Informatics 13 (January 2014): CIN.S19435. http://dx.doi.org/10.4137/cin.s19435.

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High-throughput transcriptome sequencing allows identification of cancer-related changes that occur at the stages of transcription, pre-messenger RNA (mRNA), and splicing. In the current study, we devised a pipeline to predict novel alternative splicing (AS) variants from high-throughput transcriptome sequencing data and applied it to large sets of tumor transcriptomes from The Cancer Genome Atlas (TCGA). We identified two novel tumor-associated splice variants of matriptase, a known cancer-associated gene, in the transcriptome data from epithelial-derived tumors but not normal tissue. Most notably, these variants were found in 69% of lung squamous cell carcinoma (LUSC) samples studied. We confirmed the expression of matriptase AS transcripts using quantitative reverse transcription PCR (qRT-PCR) in an orthogonal panel of tumor tissues and cell lines. Furthermore, flow cytometric analysis confirmed surface expression of matriptase splice variants in chinese hamster ovary (CHO) cells transiently transfected with cDNA encoding the novel transcripts. Our findings further implicate matriptase in contributing to oncogenic processes and suggest potential novel therapeutic uses for matriptase splice variants.

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7

Wucher, Valentin, Reza Sodaei, Raziel Amador, Manuel Irimia, and Roderic Guigó. "Day-night and seasonal variation of human gene expression across tissues." PLOS Biology 21, no. 2 (February 6, 2023): e3001986. http://dx.doi.org/10.1371/journal.pbio.3001986.

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Circadian and circannual cycles trigger physiological changes whose reflection on human transcriptomes remains largely uncharted. We used the time and season of death of 932 individuals from GTEx to jointly investigate transcriptomic changes associated with those cycles across multiple tissues. Overall, most variation across tissues during day-night and among seasons was unique to each cycle. Although all tissues remodeled their transcriptomes, brain and gonadal tissues exhibited the highest seasonality, whereas those in the thoracic cavity showed stronger day-night regulation. Core clock genes displayed marked day-night differences across multiple tissues, which were largely conserved in baboon and mouse, but adapted to their nocturnal or diurnal habits. Seasonal variation of expression affected multiple pathways, and it was enriched among genes associated with the immune response, consistent with the seasonality of viral infections. Furthermore, they unveiled cytoarchitectural changes in brain regions. Altogether, our results provide the first combined atlas of how transcriptomes from human tissues adapt to major cycling environmental conditions. This atlas may have multiple applications; for example, drug targets with day-night or seasonal variation in gene expression may benefit from temporally adjusted doses.

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8

Penin, Aleksey A., Anna V. Klepikova, Artem S. Kasianov, Evgeny S. Gerasimov, and Maria D. Logacheva. "Comparative Analysis of Developmental Transcriptome Maps of Arabidopsis thaliana and Solanum lycopersicum." Genes 10, no. 1 (January 15, 2019): 50. http://dx.doi.org/10.3390/genes10010050.

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The knowledge of gene functions in model organisms is the starting point for the analysis of gene function in non-model species, including economically important ones. Usually, the assignment of gene functions is based on sequence similarity. In plants, due to a highly intricate gene landscape, this approach has some limitations. It is often impossible to directly match gene sets from one plant species to another species based only on their sequences. Thus, it is necessary to use additional information to identify functionally similar genes. Expression patterns have great potential to serve as a source of such information. An important prerequisite for the comparative analysis of transcriptomes is the existence of high-resolution expression maps consisting of comparable samples. Here, we present a transcriptome atlas of tomato (Solanum lycopersicum) consisting of 30 samples of different organs and developmental stages. The samples were selected in a way that allowed for side-by-side comparison with the Arabidopsis thaliana transcriptome map. Newly obtained data are integrated in the TraVA database and are available online, together with tools for their analysis. In this paper, we demonstrate the potential of comparing transcriptome maps for inferring shifts in the expression of paralogous genes.

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9

Nomburg, Jason, Wei Zou, Thomas C. Frost, Chandreyee Datta, Shobha Vasudevan, Gabriel J. Starrett, Michael J. Imperiale, Matthew Meyerson, and James A. DeCaprio. "Long-read sequencing reveals complex patterns of wraparound transcription in polyomaviruses." PLOS Pathogens 18, no. 4 (April 1, 2022): e1010401. http://dx.doi.org/10.1371/journal.ppat.1010401.

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Polyomaviruses (PyV) are ubiquitous pathogens that can cause devastating human diseases. Due to the small size of their genomes, PyV utilize complex patterns of RNA splicing to maximize their coding capacity. Despite the importance of PyV to human disease, their transcriptome architecture is poorly characterized. Here, we compare short- and long-read RNA sequencing data from eight human and non-human PyV. We provide a detailed transcriptome atlas for BK polyomavirus (BKPyV), an important human pathogen, and the prototype PyV, simian virus 40 (SV40). We identify pervasive wraparound transcription in PyV, wherein transcription runs through the polyA site and circles the genome multiple times. Comparative analyses identify novel, conserved transcripts that increase PyV coding capacity. One of these conserved transcripts encodes superT, a T antigen containing two RB-binding LxCxE motifs. We find that superT-encoding transcripts are abundant in PyV-associated human cancers. Together, we show that comparative transcriptomic approaches can greatly expand known transcript and coding capacity in one of the simplest and most well-studied viral families.

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10

Wang, Jiabin, Shi Yan, Xiaoli Chen, Aowen Wang, Zhibin Han, Binchao Liu, and Hong Shen. "Identification of Prognostic Biomarkers for Glioblastoma Based on Transcriptome and Proteome Association Analysis." Technology in Cancer Research & Treatment 21 (January 1, 2022): 153303382110352. http://dx.doi.org/10.1177/15330338211035270.

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Objective: Glioblastoma multiforme (GBM) is the most malignant primary brain tumor in adults. This study aimed to identify significant prognostic biomarkers related to GBM. Methods: We collected 3 GBM and 3 healthy human brain samples for transcriptome and proteomic sequencing analysis. Differentially expressed genes (DEGs) between GBM and control samples were identified using the edge R package in R. Functional enrichment analyses, prediction of long noncoding RNA target genes, and protein-protein interaction network analyses were performed. Subsequently, transcriptomic and proteomic association analyses, validation using The Cancer Genome Atlas (TCGA) database, and survival and prognostic analyses were conducted. Then the hub genes directly related to GBM were screened. Finally, the expression of key genes was verified by quantitative polymerase chain reaction (qPCR). Results: Totally, 1140 transcripts and 503 proteins were significantly up- or down-regulated. A total of 25 genes were upregulated and 62 were downregulated at both the transcriptome and proteome levels. Results from TCGA database showed that 84 of these 87 genes matched with transcriptome sequencing results. A Cox regression analysis suggested that Fibronectin 1( FN1) was a prognostic risk factor. The qPCR results showed that FN1 was significantly upregulated in GBM samples. Conclusions: FN1 may play a role in GBM progression through ECM-receptor interaction and PI3K-Akt signaling pathways. FN1 may be considered as a prognostic biomarkers related to GBM.

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11

Ruberto, Anthony A., Caitlin Bourke, Amélie Vantaux, Steven P. Maher, Aaron Jex, Benoit Witkowski, Georges Snounou, and Ivo Mueller. "Single-cell RNA sequencing of Plasmodium vivax sporozoites reveals stage- and species-specific transcriptomic signatures." PLOS Neglected Tropical Diseases 16, no. 8 (August 4, 2022): e0010633. http://dx.doi.org/10.1371/journal.pntd.0010633.

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Background Plasmodium vivax sporozoites reside in the salivary glands of a mosquito before infecting a human host and causing malaria. Previous transcriptome-wide studies in populations of these parasite forms were limited in their ability to elucidate cell-to-cell variation, thereby masking cellular states potentially important in understanding malaria transmission outcomes. Methodology/Principal findings In this study, we performed transcription profiling on 9,947 P. vivax sporozoites to assess the extent to which they differ at single-cell resolution. We show that sporozoites residing in the mosquito’s salivary glands exist in distinct developmental states, as defined by their transcriptomic signatures. Additionally, relative to P. falciparum, P. vivax displays overlapping and unique gene usage patterns, highlighting conserved and species-specific gene programs. Notably, distinguishing P. vivax from P. falciparum were a subset of P. vivax sporozoites expressing genes associated with translational regulation and repression. Finally, our comparison of single-cell transcriptomic data from P. vivax sporozoite and erythrocytic forms reveals gene usage patterns unique to sporozoites. Conclusions/Significance In defining the transcriptomic signatures of individual P. vivax sporozoites, our work provides new insights into the factors driving their developmental trajectory and lays the groundwork for a more comprehensive P. vivax cell atlas.

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12

Ahn, Taejin, Kidong Kim, Hyojin Kim, Sarah Kim, Sangick Park, and Kyoungbun Lee. "A transcriptome-Based Deep Neural Network Classifier for Identifying the Site of Origin in Mucinous Cancer." Cancer Informatics 21 (January 2022): 117693512211351. http://dx.doi.org/10.1177/11769351221135141.

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Purpose: There is a lack of tools for identifying the site of origin in mucinous cancer. This study aimed to evaluate the performance of a transcriptome-based classifier for identifying the site of origin in mucinous cancer. Materials And Methods: Transcriptomic data of 1878 non-mucinous and 82 mucinous cancer specimens, with 7 sites of origin, namely, the uterine cervix (CESC), colon (COAD), pancreas (PAAD), stomach (STAD), uterine endometrium (UCEC), uterine carcinosarcoma (UCS), and ovary (OV), obtained from The Cancer Genome Atlas, were used as the training and validation sets, respectively. Transcriptomic data of 14 mucinous cancer specimens from a tissue archive were used as the test set. For identifying the site of origin, a set of 100 differentially expressed genes for each site of origin was selected. After removing multiple iterations of the same gene, 427 genes were chosen, and their RNA expression profiles, at each site of origin, were used to train the deep neural network classifier. The performance of the classifier was estimated using the training, validation, and test sets. Results: The accuracy of the model in the training set was 0.998, while that in the validation set was 0.939 (77/82). In the test set which is newly sequenced from a tissue archive, the model showed an accuracy of 0.857 (12/14). t-SNE analysis revealed that samples in the test set were part of the clusters obtained for the training set. Conclusion: Although limited by small sample size, we showed that a transcriptome-based classifier could correctly identify the site of origin of mucinous cancer.

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13

Klepikova, Anna V., Artem S. Kasianov, Margarita A. Ezhova, Aleksey A. Penin, and Maria D. Logacheva. "Transcriptome atlas of Phalaenopsis equestris." PeerJ 9 (December 10, 2021): e12600. http://dx.doi.org/10.7717/peerj.12600.

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The vast diversity of Orchidaceae together with sophisticated adaptations to pollinators and other unique features make this family an attractive model for evolutionary and functional studies. The sequenced genome of Phalaenopsis equestris facilitates Orchidaceae research. Here, we present an RNA-seq-based transcriptome map of P. equestris that covers 19 organs of the plant, including leaves, roots, floral organs and the shoot apical meristem. We demonstrated the high quality of the data and showed the similarity of the P. equestris transcriptome map with the gene expression atlases of other plants. The transcriptome map can be easily accessed through our database Transcriptome Variation Analysis (TraVA) for visualizing gene expression profiles. As an example of the application, we analyzed the expression of Phalaenopsis “orphan” genes–those that do not have recognizable similarity with the genes of other plants. We found that approximately half of these genes were not expressed; the ones that were expressed were predominantly expressed in reproductive structures.

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14

Riccio, Gennaro, Daniele De Luca, and Chiara Lauritano. "Monogalactosyldiacylglycerol and Sulfolipid Synthesis in Microalgae." Marine Drugs 18, no. 5 (May 1, 2020): 237. http://dx.doi.org/10.3390/md18050237.

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Microalgae, due to their huge taxonomic and metabolic diversity, have been shown to be a valuable and eco-friendly source of bioactive natural products. The increasing number of genomic and transcriptomic data will give a great boost for the study of metabolic pathways involved in the synthesis of bioactive compounds. In this study, we analyzed the presence of the enzymes involved in the synthesis of monogalactosyldiacylglycerols (MGDGs) and sulfoquinovosyldiacylglycerols (SQDG). Both compounds have important biological properties. MGDGs present both anti-inflammatory and anti-cancer activities while SQDGs present immunostimulatory activities and inhibit the enzyme glutaminyl cyclase, which is involved in Alzheimer’s disease. The Ocean Global Atlas (OGA) database and the Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP) were used to search MGDG synthase (MGD), UDP-sulfoquinovose synthase (SQD1), and sulfoquinovosyltransferase (SQD2) sequences along microalgal taxa. In silico 3D prediction analyses for the three enzymes were performed by Phyre2 server, while binding site predictions were performed by the COACH server. The analyzed enzymes are distributed across different taxa, which confirms the importance for microalgae of these two pathways for thylakoid physiology. MGD genes have been found across almost all analyzed taxa and can be separated in two different groups, similarly to terrestrial plant MGD. SQD1 and SQD2 genes are widely distributed along the analyzed taxa in a similar way to MGD genes with some exceptions. For Pinguiophyceae, Raphidophyceae, and Synurophyceae, only sequences coding for MGDG were found. On the contrary, sequences assigned to Ciliophora and Eustigmatophyceae were exclusively corresponding to SQD1 and SQD2. This study reports, for the first time, the presence/absence of these enzymes in available microalgal transcriptomes, which gives new insights on microalgal physiology and possible biotechnological applications for the production of bioactive lipids.

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15

Song, Young Shin, Byung-Hee Kang, Seungbok Lee, Seong-Keun Yoo, Young Sik Choi, Jungsun Park, Dong Yoon Park, Kyu Eun Lee, Jeong-Sun Seo, and Young Joo Park. "Genomic and Transcriptomic Characteristics According to Size of Papillary Thyroid Microcarcinoma." Cancers 12, no. 5 (May 25, 2020): 1345. http://dx.doi.org/10.3390/cancers12051345.

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It is controversial as to whether papillary thyroid microcarcinoma (PTMC) has some genomic and transcriptomic characteristics that differentiate between an early-stage lesion that would eventually evolve into the larger papillary thyroid cancer (PTC), and an occult indolent cancer in itself. To investigate this, we comprehensively elucidated the genomic and transcriptomic landscapes of PTMCs of different sizes, using a large-scaled database. This study included 3435 PTCs, 1985 of which were PTMCs. We performed targeted next-generation sequencing for 221 PTCs and integrated these data with the data including The Cancer Genome Atlas (TCGA) project. The frequency of v-raf murine sarcoma viral oncogene homolog B (BRAF)V600E mutation was higher in PTMCs >0.5 cm than that in very small PTMCs (≤0.5 cm) and decreased again in PTCs >2 cm. Among PTMCs, the prevalence of mutations in rat sarcoma (RAS) and telomerase reverse transcriptase (TERT) promoter was not significantly different according to their size, but lower than in large PTCs. There was no change in the tumor mutational burden, the number of driver mutations, and transcriptomic profiles with tumor size, among PTMCs and all PTCs. Although a few genes with differential expression and TERT promoter mutations were found in a few PTMCs, our findings showed that there were no useful genomic or transcriptomic characteristics for the prediction of the future progression of PTMC.

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16

Nakshatri, Harikrishna, Poornima Bhat-Nakshatri, Duojiao Chen, Katie Chen, Henry Mang, Christopher A. Herodotou, Aditi S. Khatpe, et al. "Abstract P3-07-09: Single cell transcriptomic analysis reveals the effects of BRCA1 and BRCA2 mutations on distinct signaling networks and cancer susceptibility." Cancer Research 82, no. 4_Supplement (February 15, 2022): P3–07–09—P3–07–09. http://dx.doi.org/10.1158/1538-7445.sabcs21-p3-07-09.

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Abstract Background: Inheritance of BRCA1 and BRCA2 mutations is associated with increased risk of breast and ovarian cancers. Previous studies with low-throughput flow cytometry-based assays suggested elevated number of luminal progenitor cells in the breast tissues of BRCA1 mutation carriers compared to breast tissues of non-carriers. However, breast epithelial cell-specific transcriptome differences between BRCA1, BRCA2 mutation carriers, and non-carriers and how these differences alter susceptibility to transformation are yet to be elucidated. Methods: We generated a single cell transcriptome atlas of breast tissues from BRCA1 (six samples, 17,220 cells), BRCA2 (four samples, 25,046 cells) mutation carriers and non-carriers (11 samples, >50,000 cells). Using previously described markers, epithelial cells were sub-clustered into basal, luminal progenitor, and mature luminal cells. Genes differentially expressed in epithelial cells of BRCA1 and BRCA2 mutation carriers compared to those in non-carrier donors were subjected to Ingenuity Pathway Analysis to determine signaling pathways uniquely active in BRCA1 and BRCA2 mutant epithelial cells. Breast epithelial cells derived from three donor types were immortalized using hTERT and then transformed with PIK3CAH1047R mutant or H-RasG12V ± SV40-T/t antigens, and tumorigenicity was determined in vivo. Results: BRCA1 but not BRCA2 mutations altered the ratio between basal, luminal progenitor and mature luminal cells in breast tissues compared to breast tissues in non-carriers. A unique cluster of cells within luminal progenitors was underrepresented in case of BRCA2 mutation carriers compared to non-carriers or BRCA1 mutation carriers. BRCA1 or BRCA2 mutations specifically altered transcriptomes which are an integral part of mTOR and MYCN signaling, and the translational machinery. Signaling pathway alterations in epithelial cells unique to BRCA1 mutations included YAP1, BRD4, SMARCA4, and TGFβ1 signaling. BRCA2 mutations were associated with upregulation of IL-6, FOXO3, and TNFSF11 signaling. Breast epithelial cells from BRCA2 mutation carriers but not BRCA1 mutation carriers or non-carriers modified to overexpress hTERT + PIK3CAH1047R generated tumors in NSG mice. These tumors displayed large cystic structures with basilar epithelial cells lining the rim of cysts with focal areas of cellular hyperplasia and neoplastic cells that extended into the lumen. However, BRCA1/2 mutation status did not influence tumorigenicity by hTERT+ H-RASG12V +SV40-T/t antigens. Conclusions: Our studies provide a high resolution transcriptome atlas of breast epithelial cells of BRCA1 and BRCA2 mutation carriers, which also reveal potentially targetable signaling networks uniquely deregulated in these cells. BRCA2 mutations are associated with distinct susceptibility to PIK3CA mutation-driven transformation. Since PIK3CA mutations are observed in clinically normal breast tissues, screening for such mutations in BRCA2 mutation carriers may help to detect pre-neoplastic or early stage breast cancer. Citation Format: Harikrishna Nakshatri, Poornima Bhat-Nakshatri, Duojiao Chen, Katie Chen, Henry Mang, Christopher A Herodotou, Aditi S Khatpe, Patrick C McGuire, Xiaoling Xuei, Yunlong Liu, George Sandusky, Anna Maria Storniolo. Single cell transcriptomic analysis reveals the effects of BRCA1 and BRCA2 mutations on distinct signaling networks and cancer susceptibility [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-07-09.

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DeCaprio, James A., Jason Nomburg, and Matthew Meyerson. "Abstract SY11-02: Long-read sequencing reveals complex patterns of wraparound transcription in polyomaviruses." Cancer Research 82, no. 12_Supplement (June 15, 2022): SY11–02—SY11–02. http://dx.doi.org/10.1158/1538-7445.am2022-sy11-02.

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Abstract Polyomaviruses (PyV) are ubiquitous pathogens that can cause devastating human diseases. Due to the small size of their genomes, PyV utilize complex patterns of RNA splicing to maximize their coding capacity. Despite the importance of PyV to human disease, their transcriptome architecture is poorly characterized. Here, we compare short- and long-read RNA sequencing data from eight human and non-human PyV. We provide a detailed transcriptome atlas for BK polyomavirus (BKPyV), an important human pathogen, and the prototype PyV, simian virus 40 (SV40). We identify pervasive wraparound transcription in PyV, wherein transcription runs through the polyA site and circles the genome multiple times. Comparative analyses identify novel, conserved transcripts that increase PyV coding capacity. One of these conserved transcripts encodes superT, a T antigen containing two RB-binding LxCxE motifs. We find that superT-encoding transcripts are abundant in PyV-associated human cancers. Together, we show that comparative transcriptomic approaches can greatly expand known transcript and coding capacity in one of the simplest and most well-studied viral families. Citation Format: James A. DeCaprio, Jason Nomburg, Matthew Meyerson. Long-read sequencing reveals complex patterns of wraparound transcription in polyomaviruses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr SY11-02.

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18

Wood, Colin, Holly Leslie, Assya Legrini, Lydia Melissourgou-Syka, Kathryn AF Pennel, Joanne Edwards, Colin William Steele, and Nigel Balfour Jamieson. "Spatially resolved transcriptomics deconvolutes histological prognostic subgroups in patients with colorectal cancer and synchronous liver metastases." Journal of Clinical Oncology 40, no. 4_suppl (February 1, 2022): 165. http://dx.doi.org/10.1200/jco.2022.40.4_suppl.165.

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165 Background: Up to 50% of patients with Colorectal Cancer (CRC) will metastasise to the liver (CRLM). KRAS-mt liver metastases particularly when co-mutated with TP53 are associated with poor prognosis. We have used the Glasgow Microenvironment Score (GMS), a histological score performed on H+E slides utilising immune and stromal components of the microenvironment to robustly stratify outcome in primary CRC. The aim of the current study was firstly to determine the utility of GMS in metastatic CRC and secondly to employ the NanostringTM GeoMx Digital Spatial Profiler (DSP), a state-of-the art analysis platform enabling spatial transcriptomic characterisation while maintaining tumour microenvironment (TME) topographical features, to interrogate the functional biology underlying the GMS. Methods: FFPE specimens from primary and metastatic lesions from 44 patients undergoing synchronous resection of CRLM underwent GMS, IHC and panel genomic assessment. Primary endpoints were recurrence-free survival (RFS) and cancer-specific survival (CSS). In addition to bulk transcriptomic assessment, 4 matched pairs from the cohort were selected for GeoMx analysis: 2 samples were GMS0 (high-immune) and 2 were GMS1 (low-immune) with an equal distribution of KRASmt and wt. After multiplex IF staining (PanCK, CD45, DAPI, αSMA), 48 regions of interest were selected and Cancer Transcriptome Atlas Transcriptomic outputs (2000 genes) were analysed using Pathway enrichment analysis with immune deconvolution of the transcriptome performed. Results: GMS0 (high-immune) was associated with improved RFS (p=0.0048) and CSS (p=0.0012) remaining an independent predictor of survival on multivariate analysis (HR 2.90, 95% C.I 1.18-7.16 P=0.021). GMS0 lesions were enriched for adaptive immune (NES=2.20 p.adj<0.0005) and IL-10 (NES=1.9 p.adj<0.0005) pathways specifically at the invasive edge. In contrast, a poor prognostic KRAS/TP53 lesion demonstrated profound immunosuppression, upregulated NOTCH signalling (NES=2.13 p.adj<0.0005) and neutrophil degranulation (NES=1.99 p.adj<0.0005). Topographical Immune-cell deconvolution demonstrated significantly higher populations of CD4 (p=0.05) and CD8 (p=0.0003) cells in GMS0 leading edges. Conclusions: We have demonstrated that spatial transcriptomic analysis using the Nanostring GeoMx tool can reveal potential novel mechanisms underlying biologically relevant histological and mutational subgroups (KRAS-mt) of CRC, providing potential therapeutic targets requiring further investigation. Future studies will apply this technology to pre and post treatment biopsy samples.

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Xu, Jason, Changya Chen, Tiffaney Vincent, Elizabeth Li, Yusha Sun, Chia-hui Chen, David Frank, David T. Teachey, and Kai Tan. "Reference Mapping Pediatric Leukemia Using Single Cell Multiomic Atlas of Pediatric Hematopoiesis." Blood 138, Supplement 1 (November 5, 2021): 3265. http://dx.doi.org/10.1182/blood-2021-153428.

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Abstract Acute lymphoblastic leukemia is the most common pediatric cancer and leading cause of cancer related mortality in pediatric populations. A key challenge to bridge better therapies to patients that fail conventional therapy are to understand their tumor landscape and aberrations in cell signaling, particularly in relation to normal hematopoietic development. To address this gap, we produced a unified reference map of pediatric T, B, and myeloid cell development from the HSPC using single cell RNA-seq and single-cell ATAC-seq on healthy pediatric bone marrow and thymus. We employed 6 different FACS sorting strategies in order to capture rare, but informative, progenitor cell states, including those of the CCR9+ CD34+ CD1A- CD4- CD8- early-T-cell precursor, CD34+ CD1A- CD4- CD8- pro-T cell, and CD34+ CD1A+ CD4- CD8- pre-T cell and Lin-CD34+CD38- multipotent, lymphoid, and myeloid progenitors from the bone marrow. We mapped leukemic cells from patients from 4 different subtypes of pediatric leukemia (T-ALL, ETP-ALL, MPAL, AML) to our healthy reference and found that our reference map can distinguish between subtle differences in transcriptome and epigenome that were undetectable using surface marker or canonical gene expression. Notably, using trajectories inferred from our healthy reference map, we discovered a large amount of inter-tumoral and intra-tumoral heterogeneity, with leukemic blasts from different patients and different populations within any one patient projecting to different cell states along normal development. Finally, we mapped engrafted leukemic cells from patient derived xenografts (PDX) back to our healthy reference. While we observed patient-specific transcriptomic shifts in engrafted versus primary leukemic blasts, we found that the overall transcriptomic hierarchy is maintained in the most PDX, with engrafted cells projecting to near-identical stages of arrest along our healthy hematopoietic trajectory. Interestingly, for PDX that projected to different areas in development compared to primary sample, we discovered alterations in expression of key transcription factors that regulate hematopoietic development. Our single cell multi-omic reference map of pediatric hematopoiesis serves as a valuable reference for mapping RNA-seq and ATAC-seq data back to nearest healthy precursors in normal hematopoietic development. On-going analysis is utilizing single cell transcriptomic, chromatin accessibility data from additional leukemic patients, including patients with B-ALL, to determined key genes and regulators that are altered in comparison to nearest healthy cell-types. In addition, population level signatures learned from healthy reference are being tested in bulk-transcriptomic ALL datasets. We are eager to present the results of these analyses at ASH. *CC and JX, as well as, DTT and KT contributed equally to this work Figure 1 Figure 1. Disclosures Teachey: Janssen: Consultancy; NeoImmune Tech: Research Funding; Sobi: Consultancy; BEAM Therapeutics: Consultancy, Research Funding.

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Norreen-Thorsen, Marthe, Eike Christopher Struck, Sofia Öling, Martin Zwahlen, Kalle Von Feilitzen, Jacob Odeberg, Cecilia Lindskog, et al. "A human adipose tissue cell-type transcriptome atlas." Cell Reports 40, no. 2 (July 2022): 111046. http://dx.doi.org/10.1016/j.celrep.2022.111046.

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Zhang, Kun, and Yanbin Zhao. "Reduced Zebrafish Transcriptome Atlas toward Understanding Environmental Neurotoxicants." Environmental Science & Technology 52, no. 12 (May 21, 2018): 7120–30. http://dx.doi.org/10.1021/acs.est.8b01350.

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Kalucka, Joanna, Laura P. M. H. de Rooij, Jermaine Goveia, Katerina Rohlenova, Sébastien J. Dumas, Elda Meta, Nadine V. Conchinha, et al. "Single-Cell Transcriptome Atlas of Murine Endothelial Cells." Cell 180, no. 4 (February 2020): 764–79. http://dx.doi.org/10.1016/j.cell.2020.01.015.

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Farnsworth, Dylan R., Lauren M. Saunders, and Adam C. Miller. "A single-cell transcriptome atlas for zebrafish development." Developmental Biology 459, no. 2 (March 2020): 100–108. http://dx.doi.org/10.1016/j.ydbio.2019.11.008.

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Uhlen, Mathias, Cheng Zhang, Sunjae Lee, Evelina Sjöstedt, Linn Fagerberg, Gholamreza Bidkhori, Rui Benfeitas, et al. "A pathology atlas of the human cancer transcriptome." Science 357, no. 6352 (August 17, 2017): eaan2507. http://dx.doi.org/10.1126/science.aan2507.

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Fincher, Christopher T., Omri Wurtzel, Thom de Hoog, Kellie M. Kravarik, and Peter W. Reddien. "Cell type transcriptome atlas for the planarianSchmidtea mediterranea." Science 360, no. 6391 (April 19, 2018): eaaq1736. http://dx.doi.org/10.1126/science.aaq1736.

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Torma, Gábor, Dóra Tombácz, Zsolt Csabai, Norbert Moldován, István Mészáros, Zoltán Zádori, and Zsolt Boldogkői. "Combined Short and Long-Read Sequencing Reveals a Complex Transcriptomic Architecture of African Swine Fever Virus." Viruses 13, no. 4 (March 30, 2021): 579. http://dx.doi.org/10.3390/v13040579.

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African swine fever virus (ASFV) is a large DNA virus belonging to the Asfarviridae family. Despite its agricultural importance, little is known about the fundamental molecular mechanisms of this pathogen. Short-read sequencing (SRS) can produce a huge amount of high-precision sequencing reads for transcriptomic profiling, but it is inefficient for comprehensively annotating transcriptomes. Long-read sequencing (LRS) can overcome some of SRS’s limitations, but it also has drawbacks, such as low-coverage and high error rate. The limitations of the two approaches can be surmounted by the combined use of these techniques. In this study, we used Illumina SRS and Oxford Nanopore Technologies LRS platforms with multiple library preparation methods (amplified and direct cDNA sequencings and native RNA sequencing) for constructing the ASFV transcriptomic atlas. This work identified many novel transcripts and transcript isoforms and annotated the precise termini of previously described RNAs. This study identified a novel species of ASFV transcripts, the replication origin-associated RNAs. Additionally, we discovered several nested genes embedded into larger canonical genes. In contrast to the current view that the ASFV transcripts are monocistronic, we detected a significant extent of polycistronism, although a large proportion of these transcripts are expressed in low abundance. A multifaceted meshwork of transcriptional overlaps was also discovered.

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Van Treeck, Benjamin J., Taofic Mounajjed, Roger K. Moreira, Mushfig Orujov, Daniela S. Allende, Andrew M. Bellizzi, Stephen M. Lagana, Jaime I. Davila, Erik Jessen, and Rondell P. Graham. "Transcriptomic and Proteomic Analysis of Steatohepatitic Hepatocellular Carcinoma Reveals Novel Distinct Biologic Features." American Journal of Clinical Pathology 155, no. 1 (September 4, 2020): 87–96. http://dx.doi.org/10.1093/ajcp/aqaa114.

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Abstract Objectives Steatohepatitic hepatocellular carcinoma is a distinct variant of hepatocellular carcinoma strongly associated with underlying nonalcoholic steatohepatitis. The molecular biology of steatohepatitic hepatocellular carcinoma is not fully elucidated, and thus we aimed to investigate the molecular underpinnings of this entity. Methods Transcriptomic analysis using RNAseq was performed on eight tumor-nonneoplastic pairs of steatohepatitic hepatocellular carcinoma with comparison to conventional hepatocellular carcinoma transcriptomes curated in The Cancer Genome Atlas. Immunohistochemistry was used to validate key RNA-level findings. Results Steatohepatitic hepatocellular carcinoma demonstrated a distinctive differential gene expression profile compared with The Cancer Genome Atlas curated conventional hepatocellular carcinomas (n = 360 cases), indicating the distinctive steatohepatitic hepatocellular carcinoma morphology is associated with a unique gene expression profile. Pathway analysis comparing tumor-nonneoplastic pairs revealed significant upregulation of the hedgehog pathway based on GLI1 overexpression and significant downregulation of carnitine palmitoyltransferase 2 transcript. Glutamine synthetase transcript was significantly upregulated, and fatty acid binding protein 1 transcript was significantly downregulated and immunohistochemically confirmed, indicating steatohepatitic hepatocellular carcinoma tumor cells display a zone 3 phenotype. Conclusions Steatohepatitic hepatocellular carcinoma demonstrates a distinctive morphology and gene expression profile, phenotype of zone 3 hepatocytes, and activation of the hedgehog pathway and repression of carnitine palmitoyltransferase 2, which may be important in tumorigenesis.

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Krawczynski, Kamil, Jakub Godlewski, and Agnieszka Bronisz. "Oxidative Stress—Part of the Solution or Part of the Problem in the Hypoxic Environment of a Brain Tumor." Antioxidants 9, no. 8 (August 14, 2020): 747. http://dx.doi.org/10.3390/antiox9080747.

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Rapid growth of brain tumors such as glioblastoma often results in oxygen deprivation and the emergence of hypoxic zones. In consequence, the enrichment of reactive oxygen species occurs, harming nonmalignant cells and leading them toward apoptotic cell death. However, cancer cells survive such exposure and thrive in a hypoxic environment. As the mechanisms responsible for such starkly different outcomes are not sufficiently explained, we aimed to explore what transcriptome rearrangements are used by glioblastoma cells in hypoxic areas. Using metadata analysis of transcriptome in different subregions of the glioblastoma retrieved from the Ivy Glioblastoma Atlas Project, we created the reactive oxygen species-dependent map of the transcriptome. This map was then used for the analysis of differential gene expression in the histologically determined cellular tumors and hypoxic zones. The gene ontology analysis cross-referenced with the clinical data from The Cancer Genome Atlas revealed that the metabolic shift is one of the major prosurvival strategies applied by cancer cells to overcome hypoxia-related cytotoxicity.

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Bag, Pushan, Jenna Lihavainen, Nicolas Delhomme, Thomas Riquelme, Kathryn M. Robinson, and Stefan Jansson. "An atlas of the Norway spruce needle seasonal transcriptome." Plant Journal 108, no. 6 (October 21, 2021): 1815–29. http://dx.doi.org/10.1111/tpj.15530.

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Karaiskos, Nikos, Mahdieh Rahmatollahi, Anastasiya Boltengagen, Haiyue Liu, Martin Hoehne, Markus Rinschen, Bernhard Schermer, et al. "A Single-Cell Transcriptome Atlas of the Mouse Glomerulus." Journal of the American Society of Nephrology 29, no. 8 (May 24, 2018): 2060–68. http://dx.doi.org/10.1681/asn.2018030238.

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Background Three different cell types constitute the glomerular filter: mesangial cells, endothelial cells, and podocytes. However, to what extent cellular heterogeneity exists within healthy glomerular cell populations remains unknown.Methods We used nanodroplet-based highly parallel transcriptional profiling to characterize the cellular content of purified wild-type mouse glomeruli.Results Unsupervised clustering of nearly 13,000 single-cell transcriptomes identified the three known glomerular cell types. We provide a comprehensive online atlas of gene expression in glomerular cells that can be queried and visualized using an interactive and freely available database. Novel marker genes for all glomerular cell types were identified and supported by immunohistochemistry images obtained from the Human Protein Atlas. Subclustering of endothelial cells revealed a subset of endothelium that expressed marker genes related to endothelial proliferation. By comparison, the podocyte population appeared more homogeneous but contained three smaller, previously unknown subpopulations.Conclusions Our study comprehensively characterized gene expression in individual glomerular cells and sets the stage for the dissection of glomerular function at the single-cell level in health and disease.

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Carson, James P., Tao Ju, Hui-Chen Lu, Christina Thaller, Mei Xu, Sarah L. Pallas, Michael C. Crair, Joe Warren, Wah Chiu, and Gregor Eichele. "A Digital Atlas to Characterize the Mouse Brain Transcriptome." PLoS Computational Biology 1, no. 4 (September 23, 2005): e41. http://dx.doi.org/10.1371/journal.pcbi.0010041.

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Carson, James, Tao Ju, Hui-Chen Lu, Christina Thaller, Mei Xu, Sarah Pallas, Michael C. Crair, Joe Warren, Wah Chiu, and Gregor Eichele. "A Digital Atlas to Characterize the Mouse Brain Transcriptome." PLoS Computational Biology preprint, no. 2005 (2005): e41. http://dx.doi.org/10.1371/journal.pcbi.0010041.eor.

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Muraro, Mauro J., Gitanjali Dharmadhikari, Dominic Grün, Nathalie Groen, Tim Dielen, Erik Jansen, Leon van Gurp, et al. "A Single-Cell Transcriptome Atlas of the Human Pancreas." Cell Systems 3, no. 4 (October 2016): 385–94. http://dx.doi.org/10.1016/j.cels.2016.09.002.

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Chen, Xueer, Lujia Chen, Cornelius H. L. Kürten, Fattaneh Jabbari, Lazar Vujanovic, Ying Ding, Binfeng Lu, et al. "An individualized causal framework for learning intercellular communication networks that define microenvironments of individual tumors." PLOS Computational Biology 18, no. 12 (December 22, 2022): e1010761. http://dx.doi.org/10.1371/journal.pcbi.1010761.

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Cells within a tumor microenvironment (TME) dynamically communicate and influence each other’s cellular states through an intercellular communication network (ICN). In cancers, intercellular communications underlie immune evasion mechanisms of individual tumors. We developed an individualized causal analysis framework for discovering tumor specific ICNs. Using head and neck squamous cell carcinoma (HNSCC) tumors as a testbed, we first mined single-cell RNA-sequencing data to discover gene expression modules (GEMs) that reflect the states of transcriptomic processes within tumor and stromal single cells. By deconvoluting bulk transcriptomes of HNSCC tumors profiled by The Cancer Genome Atlas (TCGA), we estimated the activation states of these transcriptomic processes in individual tumors. Finally, we applied individualized causal network learning to discover an ICN within each tumor. Our results show that cellular states of cells in TMEs are coordinated through ICNs that enable multi-way communications among epithelial, fibroblast, endothelial, and immune cells. Further analyses of individual ICNs revealed structural patterns that were shared across subsets of tumors, leading to the discovery of 4 different subtypes of networks that underlie disparate TMEs of HNSCC. Patients with distinct TMEs exhibited significantly different clinical outcomes. Our results show that the capability of estimating individual ICNs reveals heterogeneity of ICNs and sheds light on the importance of intercellular communication in impacting disease development and progression.

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Ruytinx, Joske, Shingo Miyauchi, Sebastian Hartmann-Wittulsky, Maíra de Freitas Pereira, Frédéric Guinet, Jean-Louis Churin, Carine Put, et al. "A Transcriptomic Atlas of the Ectomycorrhizal Fungus Laccaria bicolor." Microorganisms 9, no. 12 (December 17, 2021): 2612. http://dx.doi.org/10.3390/microorganisms9122612.

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Trees are able to colonize, establish and survive in a wide range of soils through associations with ectomycorrhizal (EcM) fungi. Proper functioning of EcM fungi implies the differentiation of structures within the fungal colony. A symbiotic structure is dedicated to nutrient exchange and the extramatricular mycelium explores soil for nutrients. Eventually, basidiocarps develop to assure last stages of sexual reproduction. The aim of this study is to understand how an EcM fungus uses its gene set to support functional differentiation and development of specialized morphological structures. We examined the transcriptomes of Laccaria bicolor under a series of experimental setups, including the growth with Populus tremula x alba at different developmental stages, basidiocarps and free-living mycelium, under various conditions of N, P and C supply. In particular, N supply induced global transcriptional changes, whereas responses to P supply seemed to be independent from it. Symbiosis development with poplar is characterized by transcriptional waves. Basidiocarp development shares transcriptional signatures with other basidiomycetes. Overlaps in transcriptional responses of L. bicolor hyphae to a host plant and N/C supply next to co-regulation of genes in basidiocarps and mature mycorrhiza were detected. Few genes are induced in a single condition only, but functional and morphological differentiation rather involves fine tuning of larger gene sets. Overall, this transcriptomic atlas builds a reference to study the function and stability of EcM symbiosis in distinct conditions using L. bicolor as a model and indicates both similarities and differences with other ectomycorrhizal fungi, allowing researchers to distinguish conserved processes such as basidiocarp development from nutrient homeostasis.

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Kumar, Vinay, Pavneet Randhawa, Robert Bilodeau, Dan Mercola, Michael McClelland, Anshu Agrawal, James Nguyen, Patricia Castro, Michael M. Ittmann, and Farah Rahmatpanah. "Spatial Profiling of the Prostate Cancer Tumor Microenvironment Reveals Multiple Differences in Gene Expression and Correlation with Recurrence Risk." Cancers 14, no. 19 (October 8, 2022): 4923. http://dx.doi.org/10.3390/cancers14194923.

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The tumor microenvironment plays a crucial role in both the development and progression of prostate cancer. Furthermore, identifying protein and gene expression differences between different regions is valuable for treatment development. We applied Digital Spatial Profiling multiplex analysis to formalin-fixed paraffin embedded prostatectomy tissue blocks to investigate protein and transcriptome differences between tumor, tumor-adjacent stroma (TAS), CD45+ tumor, and CD45+ TAS tissue. Differential expression of an immunology/oncology protein panel (n = 58) was measured. OX40L and CTLA4 were expressed at higher levels while 22 other proteins, including CD11c, were expressed at lower levels (FDR < 0.2 and p-value < 0.05) in TAS as compared to tumor epithelia. A tissue microarray analysis of 97 patients with 1547 cores found positive correlations between high expression of CD11c and increased time to recurrence in tumor and TAS, and inverse relationships for CTLA4 and OX40L, where higher expression in tumor correlated with lower time to recurrence, but higher time to recurrence in TAS. Spatial transcriptomic analysis using a Cancer Transcriptome Atlas panel (n = 1825 genes) identified 162 genes downregulated and 69 upregulated in TAS versus tumor, 26 downregulated and 6 upregulated in CD45+ TAS versus CD45+ tumor. We utilized CIBERSORTx to estimate the relative immune cell fractions using CD45+ gene expression and found higher average fractions for memory B, naïve B, and T cells in TAS. In summary, the combination of protein expression differences, immune cell fractions, and correlations of protein expression with time to recurrence suggest that closely examining the tumor microenvironment provides valuable data that can improve prognostication and treatment techniques.

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Belgard, T. Grant, Ana C. Marques, Peter L. Oliver, Hatice Ozel Abaan, Tamara M. Sirey, Anna Hoerder-Suabedissen, Fernando García-Moreno, Zoltán Molnár, Elliott H. Margulies, and Chris P. Ponting. "A Transcriptomic Atlas of Mouse Neocortical Layers." Neuron 71, no. 4 (August 2011): 605–16. http://dx.doi.org/10.1016/j.neuron.2011.06.039.

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Orosz, Erzsébet, Károly Antal, Zoltán Gazdag, Zsuzsa Szabó, Kap-Hoon Han, Jae-Hyuk Yu, István Pócsi, and Tamás Emri. "Transcriptome-Based Modeling Reveals that Oxidative Stress Induces Modulation of the AtfA-Dependent Signaling Networks inAspergillus nidulans." International Journal of Genomics 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/6923849.

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To better understand the molecular functions of the master stress-response regulator AtfA inAspergillus nidulans, transcriptomic analyses of theatfAnull mutant and the appropriate control strains exposed to menadione sodium bisulfite- (MSB-),t-butylhydroperoxide- and diamide-induced oxidative stresses were performed. Several elements of oxidative stress response were differentially expressed. Many of them, including the downregulation of the mitotic cell cycle, as the MSB stress-specific upregulation of FeS cluster assembly and the MSB stress-specific downregulation of nitrate reduction, tricarboxylic acid cycle, and ER to Golgi vesicle-mediated transport, showed AtfA dependence. To elucidate the potential global regulatory role of AtfA governing expression of a high number of genes with very versatile biological functions, we devised a model based on the comprehensive transcriptomic data. Our model suggests that an important function of AtfA is to modulate the transduction of stress signals. Although it may regulate directly only a limited number of genes, these include elements of the signaling network, for example, members of the two-component signal transduction systems. AtfA acts in a stress-specific manner, which may increase further the number and diversity of AtfA-dependent genes. Our model sheds light on the versatility of the physiological functions of AtfA and its orthologs in fungi.

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Pucci, Michela, Inês Gomes Ferreira, Martina Orlandani, Nadia Malagolini, Manuela Ferracin, and Fabio Dall’Olio. "High Expression of the Sda Synthase B4GALNT2 Associates with Good Prognosis and Attenuates Stemness in Colon Cancer." Cells 9, no. 4 (April 11, 2020): 948. http://dx.doi.org/10.3390/cells9040948.

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Background: The carbohydrate antigen Sda and its biosynthetic enzyme B4GALNT2 are highly expressed in normal colonic mucosa but are down-regulated to a variable degree in colon cancer tissues. Here, we investigated the clinical and biological importance of B4GALNT2 in colon cancer. Methods: Correlations of B4GALNT2 mRNA with clinical data were obtained from The Cancer Genome Atlas (TCGA) database; the phenotypic and transcriptomic changes induced by B4GALNT2 were studied in LS174T cells transfected with B4GALNT2 cDNA. Results: TCGA data indicate that patients with high B4GALNT2 expression in cancer tissues display longer survival than non-expressers. In LS174T cells, expression of B4GALNT2 did not affect the ability to heal a scratch wound or to form colonies in standard growth conditions but markedly reduced the growth in soft agar, the tridimensional (3D) growth as spheroids, and the number of cancer stem cells, indicating a specific effect of B4GALNT2 on the growth in poor adherence and stemness. On the transcriptome, B4GALNT2 induced the down-regulation of the stemness-associated gene SOX2 and modulated gene expression towards an attenuation of the cancer phenotype. Conclusions: The level of B4GALNT2 can be proposed as a marker to identify higher- and lower-risk colorectal cancer patients.

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Li, Taiwen, Jingxin Fu, Zexian Zeng, David Cohen, Jing Li, Qianming Chen, Bo Li, and X. Shirley Liu. "TIMER2.0 for analysis of tumor-infiltrating immune cells." Nucleic Acids Research 48, W1 (May 22, 2020): W509—W514. http://dx.doi.org/10.1093/nar/gkaa407.

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Abstract Tumor progression and the efficacy of immunotherapy are strongly influenced by the composition and abundance of immune cells in the tumor microenvironment. Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition from bulk tumor transcriptome profiles. These estimated tumor immune infiltrate populations have been associated with genomic and transcriptomic changes in the tumors, providing insight into tumor–immune interactions. However, such investigations on large-scale public data remain challenging. To lower the barriers for the analysis of complex tumor–immune interactions, we significantly improved our previous web platform TIMER. Instead of just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms. TIMER2.0 provides four modules for investigating the associations between immune infiltrates and genetic or clinical features, and four modules for exploring cancer-related associations in the TCGA cohorts. Each module can generate a functional heatmap table, enabling the user to easily identify significant associations in multiple cancer types simultaneously. Overall, the TIMER2.0 web server provides comprehensive analysis and visualization functions of tumor infiltrating immune cells.

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Howick, Virginia M., Andrew J. C. Russell, Tallulah Andrews, Haynes Heaton, Adam J. Reid, Kedar Natarajan, Hellen Butungi, et al. "The Malaria Cell Atlas: Single parasite transcriptomes across the complete Plasmodium life cycle." Science 365, no. 6455 (August 22, 2019): eaaw2619. http://dx.doi.org/10.1126/science.aaw2619.

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Malaria parasites adopt a remarkable variety of morphological life stages as they transition through multiple mammalian host and mosquito vector environments. We profiled the single-cell transcriptomes of thousands of individual parasites, deriving the first high-resolution transcriptional atlas of the entire Plasmodium berghei life cycle. We then used our atlas to precisely define developmental stages of single cells from three different human malaria parasite species, including parasites isolated directly from infected individuals. The Malaria Cell Atlas provides both a comprehensive view of gene usage in a eukaryotic parasite and an open-access reference dataset for the study of malaria parasites.

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Wendt, George R., Michael L. Reese, and James J. Collins. "SchistoCyte Atlas: A Single-Cell Transcriptome Resource for Adult Schistosomes." Trends in Parasitology 37, no. 7 (July 2021): 585–87. http://dx.doi.org/10.1016/j.pt.2021.04.010.

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Vollmers, Apple Cortez, Honey E. Mekonen, Sophia Campos, Susan Carpenter, and Christopher Vollmers. "Generation of an isoform-level transcriptome atlas of macrophage activation." Journal of Biological Chemistry 296 (January 2021): 100784. http://dx.doi.org/10.1016/j.jbc.2021.100784.

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Adekunle, Danielle A., and Eric T. Wang. "Transcriptome-wide organization of subcellular microenvironments revealed by ATLAS-Seq." Nucleic Acids Research 48, no. 11 (May 18, 2020): 5859–72. http://dx.doi.org/10.1093/nar/gkaa334.

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Abstract Subcellular organization of RNAs and proteins is critical for cell function, but we still lack global maps and conceptual frameworks for how these molecules are localized in cells and tissues. Here, we introduce ATLAS-Seq, which generates transcriptomes and proteomes from detergent-free tissue lysates fractionated across a sucrose gradient. Proteomic analysis of fractions confirmed separation of subcellular compartments. Unexpectedly, RNAs tended to co-sediment with other RNAs in similar protein complexes, cellular compartments, or with similar biological functions. With the exception of those encoding secreted proteins, most RNAs sedimented differently than their encoded protein counterparts. To identify RNA binding proteins potentially driving these patterns, we correlated their sedimentation profiles to all RNAs, confirming known interactions and predicting new associations. Hundreds of alternative RNA isoforms exhibited distinct sedimentation patterns across the gradient, despite sharing most of their coding sequence. These observations suggest that transcriptomes can be organized into networks of co-segregating mRNAs encoding functionally related proteins and provide insights into the establishment and maintenance of subcellular organization.

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Dubois, Annick, Sebastien Carrere, Olivier Raymond, Benjamin Pouvreau, Ludovic Cottret, Aymeric Roccia, Jean-Paul Onesto, et al. "Transcriptome database resource and gene expression atlas for the rose." BMC Genomics 13, no. 1 (2012): 638. http://dx.doi.org/10.1186/1471-2164-13-638.

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Liang, Jingjia, Wentao Shao, Qian Liu, Qifan Lu, Aihua Gu, and Zhaoyan Jiang. "Single Cell RNA-Sequencing Reveals a Murine Gallbladder Cell Transcriptome Atlas During the Process of Cholesterol Gallstone Formation." Frontiers in Cell and Developmental Biology 9 (September 28, 2021). http://dx.doi.org/10.3389/fcell.2021.714271.

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Gallstone disease is a worldwide common disease. However, the knowledge concerning the gallbladder in the pathogenesis of cholesterol gallstone formation remains limited. In this study, using single-cell RNA sequencing (scRNA-seq) to obtain the transcriptome of gallbladder cells, we showed cellular heterogeneity and transcriptomic dynamics in murine gallbladder cells during the process of lithogenesis. Our results indicated gallbladder walls were subjected to remodeling during the process of lithogenesis. The major molecular events that happened included proliferation of epithelial cells, infiltration of immune-cells, activation of angiogenesis, and extracellular matrix modulation. Furthermore, we observed partial reversal of gallbladder cell transcriptomes by ursodeoxycholic acid treatment. This work thus provides novel and integral knowledges on the cellular changes during lithogenesis, which is of great significance to the understanding of pathogenesis and treatment of cholesterol gallstone.

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Swamy, Vinay S., Temesgen D. Fufa, Robert B. Hufnagel, and David M. McGaughey. "Building the mega single-cell transcriptome ocular meta-atlas." GigaScience 10, no. 10 (October 2021). http://dx.doi.org/10.1093/gigascience/giab061.

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Abstract Background: The development of highly scalable single-cell transcriptome technology has resulted in the creation of thousands of datasets, >30 in the retina alone. Analyzing the transcriptomes between different projects is highly desirable because this would allow for better assessment of which biological effects are consistent across independent studies. However it is difficult to compare and contrast data across different projects because there are substantial batch effects from computational processing, single-cell technology utilized, and the natural biological variation. While many single-cell transcriptome-specific batch correction methods purport to remove the technical noise, it is difficult to ascertain which method functions best. Results: We developed a lightweight R package (scPOP, single-cell Pick Optimal Parameters) that brings in batch integration methods and uses a simple heuristic to balance batch merging and cell type/cluster purity. We use this package along with a Snakefile-based workflow system to demonstrate how to optimally merge 766,615 cells from 33 retina datsets and 3 species to create a massive ocular single-cell transcriptome meta-atlas. Conclusions: This provides a model for how to efficiently create meta-atlases for tissues and cells of interest.

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Cheng, Paul, Albert J. Pedroza, Disha Sharma, Chad S. Weldy, Trieu Nguyen, Alex R. Dalal, Rohan Shad, et al. "Abstract P3006: A Human Arterial Cell Atlas." Circulation Research 131, Suppl_1 (August 5, 2022). http://dx.doi.org/10.1161/res.131.suppl_1.p3006.

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Background: Human vascular diseases are the worldwide leading causes of morbidity and mortality. Nearly all human vascular diseases have arterial segment-specific tropisms despite identical exposures to genetic and environmental risk factors. Understanding the cellular and transcriptomic determinants of arterial identities may hold the key to identifying novel pathophysiology and potential therapies. Methods: To specifically determine arterial site-specific differences independent of inter-individual variation, we have generated a human arterial cellular atlas by simultaneously collecting and analyzing up to 8 arterial sites from multiple healthy transplant donors. We performed single cell transcriptomic analysis on arterial segments to determine the differences in cellular composition and transcriptomic programs. We subsequently integrated human genetic data with cell-type specific transcriptomic differences across vascular beds to identify probable causal cells and causal genes associated with human vascular phenotypes. Results/Conclusions: Single cell transcriptomic analysis of >150,000 cells sequenced at >50,000 reads per cell revealed that the dominant cellular drivers of transcriptomic differences between distinct arterial segments, i.e. determinants of arterial identity, are fibroblasts and smooth muscle cells, not endothelial cells or macrophages. Adult vascular cells transcriptomes from different segments are most influenced by their embryonic origins but not by anatomical proximity. Differentially regulated genes in fibroblast across different vascular beds were particularly enriched for vascular disease associated genetic signals, suggesting a prominent role for these cells in human disease. While the majority of endothelial cells were transcriptionally similar across vascular beds, a rare, previously undescribed, cluster of endothelial cells were identified who expressed segment-specific transcriptomic signatures. Differentially expressed genes in these cells were enriched for vascular disease signals, suggesting a possible role of these rare cells in human disease.

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Baik, Jae Young, Mansu Kim, Jingxuan Bao, Qi Long, and Li Shen. "Identifying Alzheimer’s genes via brain transcriptome mapping." BMC Medical Genomics 15, S2 (May 19, 2022). http://dx.doi.org/10.1186/s12920-022-01260-6.

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Abstract Background Alzheimer’s disease (AD) is one of the most common neurodegenerative disorders characterized by progressive decline in cognitive function. Targeted genetic analyses, genome-wide association studies, and imaging genetic analyses have been performed to detect AD risk and protective genes and have successfully identified dozens of AD susceptibility loci. Recently, brain imaging transcriptomics analyses have also been conducted to investigate the relationship between neuroimaging traits and gene expression measures to identify interesting gene-traits associations. These imaging transcriptomic studies typically do not involve the disease outcome in the analysis, and thus the identified brain or transcriptomic markers may not be related or specific to the disease outcome. Results We propose an innovative two-stage approach to identify genes whose expression profiles are related to diagnosis phenotype via brain transcriptome mapping. Specifically, we first map the effects of a diagnosis phenotype onto imaging traits across the brain using a linear regression model. Then, the gene-diagnosis association is assessed by spatially correlating the brain transcriptome map with the diagnostic effect map on the brain-wide imaging traits. To demonstrate the promise of our approach, we apply it to the integrative analysis of the brain transcriptome data from the Allen Human Brain Atlas (AHBA) and the amyloid imaging data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Our method identifies 12 genes whose brain-wide transcriptome patterns are highly correlated with six different diagnostic effect maps on the amyloid imaging traits. These 12 genes include four confirmatory findings (i.e., AD genes reported in DisGeNET) and eight novel genes that have not be associated with AD in DisGeNET. Conclusion We have proposed a novel disease-related brain transcriptomic mapping method to identify genes whose expression profiles spatially correlated with regional diagnostic effects on a studied brain trait. Our empirical study on the AHBA and ADNI data shows the promise of the approach, and the resulting AD gene discoveries provide valuable information for better understanding biological pathways from transcriptomic signatures to intermediate brain traits and to phenotypic disease outcomes.

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Song, Jinjia, Benji Fan, Xiaodie Shao, Yuwei Zang, Dayong Wang, and Yi Min. "Single-cell transcriptome sequencing atlas of cassava tuberous root." Frontiers in Plant Science 13 (January 4, 2023). http://dx.doi.org/10.3389/fpls.2022.1053669.

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IntroductionSingle-cell transcriptome sequencing (ScRNA-seq) has emerged as an effective method for examining cell differentiation and development. In non-model plants, it hasn't been employed very much, especially in sink organs that are abundant in secondary metabolites.ResultsIn this study, we sequenced the single-cell transcriptomes at two developmental phases of cassava tuberous roots using the technology known as 10x Genomics (S1, S2). In total, 14,566 cells were grouped into 15 different cell types, primarily based on the marker genes of model plants known to exist. In the pseudotime study, the cell differentiation trajectory was defined, and the difference in gene expression between the two stages on the pseudotime axis was compared. The differentiation process of the vascular tissue and cerebral tissue was identified by the trajectory. We discovered the rare cell type known as the casparian strip via the use of up-regulated genes and pseudotime analysis, and we explained how it differentiates from endodermis. The successful creation of a protoplast isolation technique for organs rich in starch was also described in our study.DiscussionTogether, we created the first high-resolution single-cell transcriptome atlas of cassava tuberous roots, which made significant advancements in our understanding of how these roots differentiate and develop.

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