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Abstract While triple-negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigate TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We perform an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures leads to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identifies nine TNBC spatial archetypes, further validated in external datasets. Several spatial archetypes are associated with disease outcome and characterized by potentially actionable features. In this work, we provide a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy.

Abstract The respiratory system, including the lungs, is essential for terrestrial life. While recent research has advanced our understanding of lung development, much still relies on animal models and transcriptome analyses. In this study conducted within the Human Developmental Cell Atlas (HDCA) initiative, we describe the protein-level spatiotemporal organization of the lung during the first trimester of human gestation. Using high-parametric tissue imaging with a 30-plex antibody panel, we analyzed human lung samples from 6 to 13 post-conception weeks, generating data from over 2 million cells across five developmental timepoints. We present a resource detailing spatially resolved cell type composition of the developing human lung, including proliferative states, immune cell patterns, spatial arrangement traits, and their temporal evolution. This represents an extensive single-cell resolved protein-level examination of the developing human lung and provides a valuable resource for further research into the developmental roots of human respiratory health and disease.

Abstract Formalin-fixed paraffin-embedded (FFPE) samples are valuable but underutilized in single-cell omics research due to their low RNA quality. In this study, leveraging a recent advance in single-cell genomic technology, we introduce snPATHO-seq, a versatile method to derive high-quality single-nucleus transcriptomic data from FFPE samples. We benchmarked the performance of the snPATHO-seq workflow against existing 10x 3’ and Flex assays designed for frozen or fresh samples and highlighted the consistency in snRNA-seq data produced by all workflows. The snPATHO-seq workflow also demonstrated high robustness when tested across a wide range of healthy and diseased FFPE tissue samples. When combined with FFPE spatial transcriptomic technologies such as FFPE Visium, the snPATHO-seq provides a multi-modal sampling approach for FFPE samples, allowing more comprehensive transcriptomic characterization.

Abstract Upon infecting its vertebrate host, the malaria parasite initially invades the liver where it undergoes massive replication, whilst remaining clinically silent. The coordination of host responses across the complex liver tissue during malaria infection remains unexplored. Here, we perform spatial transcriptomics in combination with single-nuclei RNA sequencing over multiple time points to delineate host-pathogen interactions across Plasmodium berghei-infected liver tissues. Our data reveals significant changes in spatial gene expression in the malaria-infected tissues. These include changes related to lipid metabolism in the proximity to sites of Plasmodium infection, distinct inflammation programs between lobular zones, and regions with enrichment of different inflammatory cells, which we term ‘inflammatory hotspots’. We also observe significant upregulation of genes involved in inflammation in the control liver tissues of mice injected with mosquito salivary gland components. However, this response is considerably delayed compared to that observed in P. berghei-infected mice. Our study establishes a benchmark for investigating transcriptome changes during host-parasite interactions in tissues, it provides informative insights regarding in vivo study design linked to infection and offers a useful tool for the discovery and validation of de novo intervention strategies aimed at malaria liver stage infection.

Abstract Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.

Spatial transcriptomics relies on RNA quality, which is variable and dependent on sample handling, storage, and/or intrinsic factors. Here, authors present a genome-wide spatial gene expression profiling method called RNA Rescue Spatial Transcriptomics (RRST), designed for the analysis of moderate to low quality fresh frozen tissue samples and demonstrate its robustness on 7 different tissue types.

Spatial heterogeneity in prostate cancer can contribute to its resistance to androgen deprivation therapy (ADT). Here, the authors analyse prostate cancer samples before and after ADT using Spatial Transcriptomics, and find heterogeneous pre-treatment tumour cell populations and stromal cells that are associated with resistance.

Abstract The intestinal barrier is composed of a complex cell network defining highly compartmentalized and specialized structures. Here, we use spatial transcriptomics to define how the transcriptomic landscape is spatially organized in the steady state and healing murine colon. At steady state conditions, we demonstrate a previously unappreciated molecular regionalization of the colon, which dramatically changes during mucosal healing. Here, we identified spatially-organized transcriptional programs defining compartmentalized mucosal healing, and regions with dominant wired pathways. Furthermore, we showed that decreased p53 activation defined areas with increased presence of proliferating epithelial stem cells. Finally, we mapped transcriptomics modules associated with human diseases demonstrating the translational potential of our dataset. Overall, we provide a publicly available resource defining principles of transcriptomic regionalization of the colon during mucosal healing and a framework to develop and progress further hypotheses.

Global transcriptional differences across lobular units in the liver remain unknown. Here the authors perform spatial transcriptomics of liver tissue to delineate transcriptional differences in physical space, confirm lobular zonation along transcriptional gradients and suggest the presence of previously uncharacterized structures within liver tissue.

While transcriptomics have enhanced our understanding for cancer, spatial transcriptomics enable the characterisation of cellular interactions. Here, the authors integrate single cell data with spatial information for HER2 + tumours and develop tools for the prediction of interactions between tumour-infiltrating cells.

Kvastad et al. develop the spatial RNA Integrity Number (sRIN) assay that evaluates the RNA integrity at cellular resolution. This method improves the resolution of a similar method called the RNA Integrity Number (RIN), demonstrating spatial variation in the quality of RNA samples.

Abstract Background Recent advancements in in situ gene expression technologies constitute a new and rapidly evolving field of transcriptomics. With the recent launch of the 10x Genomics Visium platform, such methods have started to become widely adopted. The experimental protocol is conducted on individual tissue sections collected from a larger tissue sample. The two-dimensional nature of this data requires multiple consecutive sections to be collected from the sample in order to construct a comprehensive three-dimensional map of the tissue. However, there is currently no software available that lets the user process the images, align stacked experiments, and finally visualize them together in 3D to create a holistic view of the tissue. Results We have developed an R package named STUtility that takes 10x Genomics Visium data as input and provides features to perform standardized data transformations, alignment of multiple tissue sections, regional annotation, and visualizations of the combined data in a 3D model framework. Conclusions STUtility lets the user process, analyze and visualize multiple samples of spatially resolved RNA sequencing and image data from the 10x Genomics Visium platform. The package builds on the Seurat framework and uses familiar APIs and well-proven analysis methods. An introduction to the software package is available at https://ludvigla.github.io/STUtility_web_site/ .

Abstract Background Technological developments in the emerging field of spatial transcriptomics have opened up an unexplored landscape where transcript information is put in a spatial context. Clustering commonly constitutes a central component in analyzing this type of data. However, deciding on the number of clusters to use and interpreting their relationships can be difficult. Results We introduce SpatialCPie, an R package designed to facilitate cluster evaluation for spatial transcriptomics data. SpatialCPie clusters the data at multiple resolutions. The results are visualized with pie charts that indicate the similarity between spatial regions and clusters and a cluster graph that shows the relationships between clusters at different resolutions. We demonstrate SpatialCPie on several publicly available datasets. Conclusions SpatialCPie provides intuitive visualizations of cluster relationships when dealing with Spatial Transcriptomics data.

Abstract Background Interest in studying the spatial distribution of gene expression in tissues is rapidly increasing. Spatial Transcriptomics is a novel sequencing-based technology that generates high-throughput information on the distribution, heterogeneity and co-expression of cells in tissues. Unfortunately, manual preparation of high-quality sequencing libraries is time-consuming and subject to technical variability due to human error during manual pipetting, which results in sample swapping and the accidental introduction of batch effects. All these factors complicate the production and interpretation of biological datasets. Results We have integrated an Agilent Bravo Automated Liquid Handling Platform into the Spatial Transcriptomics workflow. Compared to the previously reported Magnatrix 8000+ automated protocol, this approach increases the number of samples processed per run, reduces sample preparation time by 35%, and minimizes batch effects between samples. The new approach is also shown to be highly accurate and almost completely free from technical variability between prepared samples. Conclusions The new automated Spatial Transcriptomics protocol using the Agilent Bravo Automated Liquid Handling Platform rapidly generates high-quality Spatial Transcriptomics libraries. Given the wide use of the Agilent Bravo Automated Liquid Handling Platform in research laboratories and facilities, this will allow many researchers to quickly create robust Spatial Transcriptomics libraries.

Summary: Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here, we report a procedure to perform genome-wide spatial analysis of mRNA in FFPE-fixed tissue sections, using well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3′ end of mRNA molecules in tissue sections. We applied this method for expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method’s capability to delineate anatomical regions from a molecular perspective. We also profiled the spatial composition of transcriptomic signatures in two ovarian carcinosarcoma samples, exemplifying the method’s potential to elucidate molecular mechanisms in heterogeneous clinical samples. Finally, we demonstrate the applicability of the assay to characterize human lung and kidney organoids and a human lung biopsy specimen infected with SARS-CoV-2. We anticipate that genome-wide spatial gene expression profiling in FFPE biospecimens will be used for retrospective analysis of biobank samples, which will facilitate longitudinal studies of biological processes and biomarker discovery.

Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory tract infections in young children. Currently, there is no RSV vaccine or universally accessible antiviral treatment available. Addressing the urgent need for new antiviral agents, we have investigated the capacity of a non-coding single-stranded oligonucleotide (ssON) to inhibit RSV infection. By utilizing a GFP-expressing RSV, we demonstrate that the ssON significantly reduced the proportion of RSV infected A549 cells (lung epithelial cells). Furthermore, we show that ssON’s antiviral activity was length dependent and that both RNA and DNA of this class of oligonucleotides have antiviral activity. We reveal that ssON inhibited RSV infection by competing with the virus for binding to the cellular receptor nucleolin in vitro. Additionally, using a recombinant RSV that expresses luciferase we show that ssON effectively blocked RSV infection in mice. Treatment with ssON in vivo resulted in the upregulation of RSV-induced interferon stimulated genes (ISGs) such as Stat1, Stat2, Cxcl10, and Ccl2. This study highlights the possibility of using oligonucleotides as therapeutic agents against RSV infection. We demonstrate that the mechanism of action of ssON is the inhibition of viral entry in vitro, likely through the binding of the receptor, nucleolin and that ssON treatment against RSV infection in vivo additionally results in the upregulation of ISGs.

Summary: Alzheimer disease (AD) is a devastating neurological disease associated with progressive loss of mental skills and cognitive and physical functions whose etiology is not completely understood. Here, our goal was to simultaneously uncover novel and known molecular targets in the structured layers of the hippocampus and olfactory bulbs that may contribute to early hippocampal synaptic deficits and olfactory dysfunction in AD mice. Spatially resolved transcriptomics was used to identify high-confidence genes that were differentially regulated in AD mice relative to controls. A diverse set of genes that modulate stress responses and transcription were predominant in both hippocampi and olfactory bulbs. Notably, we identify Bok, implicated in mitochondrial physiology and cell death, as a spatially downregulated gene in the hippocampus of mouse and human AD brains. In summary, we provide a rich resource of spatially differentially expressed genes, which may contribute to understanding AD pathology.

Abstract Recognition of nucleic acids by endosomal Toll-like receptors (TLR) is essential to combat pathogens, but requires strict control to limit inflammatory responses. The mechanisms governing this tight regulation are unclear. We found that single-stranded oligonucleotides (ssON) inhibit endocytic pathways used by cargo destined for TLR3/4/7 signaling endosomes. Both ssDNA and ssRNA conferred the endocytic inhibition, it was concentration dependent, and required a certain ssON length. The ssON-mediated inhibition modulated signaling downstream of TLRs that localized within the affected endosomal pathway. We further show that injection of ssON dampens dsRNA-mediated inflammatory responses in the skin of non-human primates. These studies reveal a regulatory role for extracellular ssON in the endocytic uptake of TLR ligands and provide a mechanistic explanation of their immunomodulation. The identified ssON-mediated interference of endocytosis (SOMIE) is a regulatory process that temporarily dampens TLR3/4/7 signaling, thereby averting excessive immune responses.

Heterogeneity within tumors presents a challenge to cancer treatment. Here, the authors investigate transcriptional heterogeneity in prostate cancer, examining expression profiles of different tissue components and highlighting expression gradients in the tumor microenvironment.

The initiation of an immune response is dependent on the activation and maturation of dendritic cells after sensing pathogen associated molecular patterns by pattern recognition receptors. However, the response needs to be balanced as excessive pro-inflammatory cytokine production in response to viral or stress-induced pattern recognition receptor signaling has been associated with severe influenza A virus (IAV) infection. Here, we use an inhibitor of Toll-like receptor (TLR)3, a single-stranded oligonucleotide (ssON) with the capacity to inhibit certain endocytic routes, or a TLR3 agonist (synthetic double-stranded RNA PolyI:C), to evaluate modulation of innate responses during H1N1 IAV infection. Since IAV utilizes cellular endocytic machinery for viral entry, we also assessed ssON's capacity to affect IAV infection. We first show that IAV infected human monocyte-derived dendritic cells (MoDC) were unable to up-regulate the co-stimulatory molecules CD80 and CD86 required for T cell activation. Exogenous TLR3 stimulation did not overcome the IAV-mediated inhibition of co-stimulatory molecule expression in MoDC. However, TLR3 stimulation using PolyI:C led to an augmented pro-inflammatory cytokine response. We reveal that ssON effectively inhibited PolyI:C-mediated pro-inflammatory cytokine production in MoDC, notably, ssON treatment maintained an interferon response induced by IAV infection. Accordingly, RNAseq analyses revealed robust up-regulation of interferon-stimulated genes in IAV cultures treated with ssON. We next measured reduced IAV production in MoDC treated with ssON and found a length requirement for its anti-viral activity, which overlapped with its capacity to inhibit uptake of PolyI:C. Hence, in cases wherein an overreacting TLR3 activation contributes to IAV pathogenesis, ssON can reduce this signaling pathway. Furthermore, concomitant treatment with ssON and IAV infection in mice resulted in maintained weight and reduced viral load in the lungs. Therefore, extracellular ssON provides a mechanism for immune regulation of TLR3-mediated responses and suppression of IAV infection in vitro and in vivo in mice.

Currently available single-cell transcriptomic analyses are expensive and low throughput. Here, Vickovicet al. describe a new method called MASC-seq that is based on microarray barcoding of expression pattern and of low cost with high robustness.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

BACKGROUND:Whole genome amplification (WGA) is currently a prerequisite for single cell whole genome or exome sequencing. Depending on the method used the rate of artifact formation, allelic dropout and sequence coverage over the genome may differ significantly. RESULTS:The largest difference between the evaluated protocols was observed when analyzing the target coverage and read depth distribution. These differences also had impact on the downstream variant calling. Conclusively, the products from the AMPLI1 and MALBAC kits were shown to be most similar to the bulk samples and are therefore recommended for WGA of single cells. DISCUSSION:In this study four commercial kits for WGA (AMPLI1, MALBAC, Repli-G and PicoPlex) were used to amplify human single cells. The WGA products were exome sequenced together with non-amplified bulk samples from the same source. The resulting data was evaluated in terms of genomic coverage, allelic dropout and SNP calling.

Abstract An essential question in human biology is how cells and tissues differ in gene and protein expression and how these differences delineate specific biological function. Here, we have performed a global analysis of both mRNA and protein levels based on sequence‐based transcriptome analysis (RNA‐seq), SILAC‐based mass spectrometry analysis and antibody‐based confocal microscopy. The study was performed in three functionally different human cell lines and based on the global analysis, we estimated the fractions of mRNA and protein that are cell specific or expressed at similar/different levels in the cell lines. A highly ubiquitous RNA expression was found with >60% of the gene products detected in all cells. The changes of mRNA and protein levels in the cell lines using SILAC and RNA ratios show high correlations, even though the genome‐wide dynamic range is substantially higher for the proteins as compared with the transcripts. Large general differences in abundance for proteins from various functional classes are observed and, in general, the cell‐type specific proteins are low abundant and highly enriched for cell‐surface proteins. Thus, this study shows a path to characterize the transcriptome and proteome in human cells from different origins.

Restriction enzymes that recognize specific sequences but cleave unknown sequence outside the recognition site are extensively utilized tools in molecular biology. Despite this, systematic functional categorization of cleavage performance has largely been lacking. We established a simple and automatable model system to assay cleavage distance variation (termed slippage) and the sequence dependence thereof. We coupled this to massively parallel sequencing in order to provide sensitive and accurate measurement. With this system 14 enzymes were assayed (AcuI, BbvI, BpmI, BpuEI, BseRI, BsgI, Eco57I, Eco57MI, EcoP15I, FauI, FokI, GsuI, MmeI and SmuI). We report significant variation of slippage ranging from 1-54%, variations in sequence context dependence, as well as variation between isoschizomers. We believe this largely overlooked property of enzymes with shifted cleavage would benefit from further large scale classification and engineering efforts seeking to improve performance. The gained insights of in-vitro performance may also aid the in-vivo understanding of these enzymes.

After performing de novo transcript assembly of >1 billion RNA-Sequencing reads obtained from 22 samples of different Norway spruce (Picea abies) tissues that were not surface sterilized, we found that assembled sequences captured a mix of plant, lichen, and fungal transcripts. The latter were likely expressed by endophytic and epiphytic symbionts, indicating that these organisms were present, alive, and metabolically active. Here, we show that these serendipitously sequenced transcripts need not be considered merely as contamination, as is common, but that they provide insight into the plant's phyllosphere. Notably, we could classify these transcripts as originating predominantly from Dothideomycetes and Leotiomycetes species, with functional annotation of gene families indicating active growth and metabolism, with particular regards to glucose intake and processing, as well as gene regulation.

Here we describe an amplification method for global transcript analysis. The strategy relies on amplification of cDNA tags (signature tags) achieved by random fragmentation of the cDNAs to short tags of similar length, isolation of the 3′ ends and then PCR amplification of the 3′-end signature tag population. This method minimizes biased amplification that may occur during parallel amplification of long and short templates. The amplified tags can be either cloned and sequenced or labeled and hybridized to DNA arrays to identify the expressed transcripts. To verify that the relative levels between transcripts in different mRNA/cDNA populations are maintained during the amplification protocol, we have used the Affymetrix oligonucleotide platform and real-time PCR.

In order to obtain information on genes specifically expressed in the ectomycorrhizal symbiosis, 3,555 expressed sequence tags (ESTs) were analyzed from a cDNA library constructed from ectomycorrhiza formed between the basidiomycete Paxillus involutus and birch (Betula pendula). cDNA libraries from saprophytically growing fungus (3,964 ESTs) and from axenic plants (2,532 ESTs) were analyzed in parallel. By clustering all the EST obtained, a nonredundant set of 2,284 unique transcripts of either fungal or plant origin were identified. The expression pattern of these genes was analyzed using cDNA microarrays. The analyses showed that the plant and fungus responded to the symbiosis by altering the expression levels of a number of enzymes involved in carbon metabolism. Several plant transcripts with sequence similarities to genes encoding enzymes in the tricarboxylic cycle and electron transport chain were down regulated as compared with the levels in free-living roots. In the fungal partner, a number of genes encoding enzymes in the lipid and secondary metabolism were down regulated in mycorrhiza as compared with the saprophytically growing mycelium. A substantial number of the ESTs analyzed displayed significant sequence similarities to proteins involved in biotic stress responses, but only a few of them showed differential expression in the mycorrhizal tissue, including plant and fungal metal-lothioneins and a plant defensin homologue. Several of the genes that were differentially expressed in the mycorrhizal root tissue displayed sequence similarity to genes that are known to regulate growth and development of plant roots and fungal hyphae, including transcription factors and Rho-like GTPases.

Sepsis is a severe medical condition characterized by a systemic inflammatory response of the body caused by pathogenic microorganisms in the bloodstream. Blood or plasma is typically used for diagnosis, both containing large amount of human DNA, greatly exceeding the DNA of microbial origin. In order to enrich bacterial DNA, we applied the C0t effect to reduce human DNA background: a model system was set up with human and Escherichia coli (E. coli) DNA to mimic the conditions of bloodstream infections; and this system was adapted to plasma and blood samples from septic patients. As a consequence of the C0t effect, abundant DNA hybridizes faster than rare DNA. Following denaturation and re-hybridization, the amount of abundant DNA can be decreased with the application of double strand specific nucleases, leaving the non-hybridized rare DNA intact. Our experiments show that human DNA concentration can be reduced approximately 100,000-fold without affecting the E. coli DNA concentration in a model system with similarly sized amplicons. With clinical samples, the human DNA background was decreased 100-fold, as bacterial genomes are approximately 1,000-fold smaller compared to the human genome. According to our results, background suppression can be a valuable tool to enrich rare DNA in clinical samples where a high amount of background DNA can be found.

RNA sequencing has become widely used in gene expression profiling experiments. Prior to any RNA sequencing experiment the quality of the RNA must be measured to assess whether or not it can be used for further downstream analysis. The RNA integrity number (RIN) is a scale used to measure the quality of RNA that runs from 1 (completely degraded) to 10 (intact). Ideally, samples with high RIN (> 8) are used in RNA sequencing experiments. RNA, however, is a fragile molecule which is susceptible to degradation and obtaining high quality RNA is often hard, or even impossible when extracting RNA from certain clinical tissues. Thus, occasionally, working with low quality RNA is the only option the researcher has. Here we investigate the effects of RIN on RNA sequencing and suggest a computational method to handle data from samples with low quality RNA which also enables reanalysis of published datasets. Using RNA from a human cell line we generated and sequenced samples with varying RINs and illustrate what effect the RIN has on the basic procedure of RNA sequencing; both quality aspects and differential expression. We show that the RIN has systematic effects on gene coverage, false positives in differential expression and the quantification of duplicate reads. We introduce 3' tag counting (3TC) as a computational approach to reliably estimate differential expression for samples with low RIN. We show that using the 3TC method in differential expression analysis significantly reduces false positives when comparing samples with different RIN, while retaining reasonable sensitivity.

Exome sequence capture and massively parallel sequencing can be combined to achieve inexpensive and rapid global analyses of the functional sections of the genome. The difficulties of working with relatively small quantities of genetic material, as may be necessary when sharing tumor biopsies between collaborators for instance, can be overcome using whole genome amplification. However, the potential drawbacks of using a whole genome amplification technology based on random primers in combination with sequence capture followed by massively parallel sequencing have not yet been examined in detail, especially in the context of mutation discovery in tumor material. In this work, we compare mutations detected in sequence data for unamplified DNA, whole genome amplified DNA, and RNA originating from the same tumor tissue samples from 16 patients diagnosed with non-small cell lung cancer. The results obtained provide a comprehensive overview of the merits of these techniques for mutation analysis. We evaluated the identified genetic variants, and found that most (74%) of them were observed in both the amplified and the unamplified sequence data. Eighty-nine percent of the variations found by WGA were shared with unamplified DNA. We demonstrate a strategy for avoiding allelic bias by including RNA-sequencing information.

ABSTRACT Malassezia commensal yeasts are associated with a number of skin disorders, such as atopic eczema/dermatitis and dandruff, and they also can cause systemic infections. Here we describe the 7.67-Mbp genome of Malassezia sympodialis, a species associated with atopic eczema, and contrast its genome repertoire with that of Malassezia globosa, associated with dandruff, as well as those of other closely related fungi. Ninety percent of the predicted M. sympodialis protein coding genes were experimentally verified by mass spectrometry at the protein level. We identified a relatively limited number of genes related to lipid biosynthesis, and both species lack the fatty acid synthase gene, in line with the known requirement of these yeasts to assimilate lipids from the host. Malassezia species do not appear to have many cell wall-localized glycosylphosphatidylinositol (GPI) proteins and lack other cell wall proteins previously identified in other fungi. This is surprising given that in other fungi these proteins have been shown to mediate interactions (e.g., adhesion and biofilm formation) with the host. The genome revealed a complex evolutionary history for an allergen of unknown function, Mala s 7, shown to be encoded by a member of an amplified gene family of secreted proteins. Based on genetic and biochemical studies with the basidiomycete human fungal pathogen Cryptococcus neoformans, we characterized the allergen Mala s 6 as the cytoplasmic cyclophilin A. We further present evidence that M. sympodialis may have the capacity to undergo sexual reproduction and present a model for a pseudobipolar mating system that allows limited recombination between two linked MAT loci. IMPORTANCE Malassezia commensal yeasts are associated with a number of skin disorders. The previously published genome of M. globosa provided some of the first insights into Malassezia biology and its involvement in dandruff. Here, we present the genome of M. sympodialis, frequently isolated from patients with atopic eczema and healthy individuals. We combined comparative genomics with sequencing and functional characterization of specific genes in a population of clinical isolates and in closely related model systems. Our analyses provide insights into the evolution of allergens related to atopic eczema and the evolutionary trajectory of the machinery for sexual reproduction and meiosis. We hypothesize that M. sympodialis may undergo sexual reproduction, which has important implications for the understanding of the life cycle and virulence potential of this medically important yeast. Our findings provide a foundation for the development of genetic and genomic tools to elucidate host-microbe interactions that occur on the skin and to identify potential therapeutic targets.

Multiplexing is of vital importance for utilizing the full potential of next generation sequencing technologies. We here report TagGD (DNA-based Tag Generator and Demultiplexor), a fully-customisable, fast and accurate software package that can generate thousands of barcodes satisfying user-defined constraints and can guarantee full demultiplexing accuracy. The barcodes are designed to minimise their interference with the experiment. Insertion, deletion and substitution events are considered when designing and demultiplexing barcodes. 20,000 barcodes of length 18 were designed in 5 minutes and 2 million barcoded Illumina HiSeq-like reads generated with an error rate of 2% were demultiplexed with full accuracy in 5 minutes. We believe that our software meets a central demand in the current high-throughput biology and can be utilised in any field with ample sample abundance. The software is available on GitHub (https://github.com/pelinakan/UBD.git).

Periodontitis is a chronic inflammatory disease affecting the soft tissue and bone that surrounds the teeth. Despite extensive research, distinctive genes responsible for the disease have not been identified. The objective of this study was to elucidate transcriptome changes in periodontitis, by investigating gene expression profiles in gingival tissue obtained from periodontitis-affected and healthy gingiva from the same patient, using RNA-sequencing. Gingival biopsies were obtained from a disease-affected and a healthy site from each of 10 individuals diagnosed with periodontitis. Enrichment analysis performed among uniquely expressed genes for the periodontitis-affected and healthy tissues revealed several regulated pathways indicative of inflammation for the periodontitis-affected condition. Hierarchical clustering of the sequenced biopsies demonstrated clustering according to the degree of inflammation, as observed histologically in the biopsies, rather than clustering at the individual level. Among the top 50 upregulated genes in periodontitis-affected tissues, we investigated two genes which have not previously been demonstrated to be involved in periodontitis. These included interferon regulatory factor 4 and chemokine (C-C motif) ligand 18, which were also expressed at the protein level in gingival biopsies from patients with periodontitis. In conclusion, this study provides a first step towards a quantitative comprehensive insight into the transcriptome changes in periodontitis. We demonstrate for the first time site-specific local variation in gene expression profiles of periodontitis-affected and healthy tissues obtained from patients with periodontitis, using RNA-seq. Further, we have identified novel genes expressed in periodontitis tissues, which may constitute potential therapeutic targets for future treatment strategies of periodontitis.

BACKGROUND: The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity. METHODOLOGY: In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation. CONCLUSION/SIGNIFICANCE: The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods.

Biomarker identification is of utmost importance for the development of novel diagnostics and therapeutics. Here we make use of a translational database selection strategy, utilizing data from the Human Protein Atlas (HPA) on differentially expressed protein patterns in healthy and breast cancer tissues as a means to filter out potential biomarkers for underlying genetic causatives of the disease. DNA was isolated from ten breast cancer biopsies, and the protein coding and flanking non-coding genomic regions corresponding to the selected proteins were extracted in a multiplexed format from the samples using a single DNA sequence capture array. Deep sequencing revealed an even enrichment of the multiplexed samples and a great variation of genetic alterations in the tumors of the sampled individuals. Benefiting from the upstream filtering method, the final set of biomarker candidates could be completely verified through bidirectional Sanger sequencing, revealing a 40 percent false positive rate despite high read coverage. Of the variants encountered in translated regions, nine novel non-synonymous variations were identified and verified, two of which were present in more than one of the ten tumor samples.

BACKGROUND: Large efforts have recently been made to automate the sample preparation protocols for massively parallel sequencing in order to match the increasing instrument throughput. Still, the size selection through agarose gel electrophoresis separation is a labor-intensive bottleneck of these protocols. METHODOLOGY/PRINCIPAL FINDINGS: In this study a method for automatic library preparation and size selection on a liquid handling robot is presented. The method utilizes selective precipitation of certain sizes of DNA molecules on to paramagnetic beads for cleanup and selection after standard enzymatic reactions. CONCLUSIONS/SIGNIFICANCE: The method is used to generate libraries for de novo and re-sequencing on the Illumina HiSeq 2000 instrument with a throughput of 12 samples per instrument in approximately 4 hours. The resulting output data show quality scores and pass filter rates comparable to manually prepared samples. The sample size distribution can be adjusted for each application, and are suitable for all high throughput DNA processing protocols seeking to control size intervals.

Several recent studies have indicated that transcription is pervasive in regions outside of protein coding genes and that short antisense transcripts can originate from the promoter and terminator regions of genes. Here we investigate transcription of fragments longer than 200 nucleotides, focusing on antisense transcription for known protein coding genes and intergenic transcription. We find that roughly 12% to 16% of all reads that originate from promoter and terminator regions, respectively, map antisense to the gene in question. Furthermore, we detect a high number of novel transcriptionally active regions (TARs) that are generally expressed at a lower level than protein coding genes. We find that the correlation between RNA-seq data and microarray data is dependent on the gene length, with longer genes showing a better correlation. We detect high antisense transcriptional activity from promoter, terminator and intron regions of protein-coding genes and identify a vast number of previously unidentified TARs, including putative novel EGFR transcripts. This shows that in-depth analysis of the transcriptome using RNA-seq is a valuable tool for understanding complex transcriptional events. Furthermore, the development of new algorithms for estimation of gene expression from RNA-seq data is necessary to minimize length bias.

BACKGROUND: Although the use of TNF inhibitors has fundamentally changed the way rheumatoid arthritis (RA) is treated, not all patients respond well. It is desirable to facilitate the identification of responding and non-responding patients prior to treatment, not only to avoid unnecessary treatment but also for financial reasons. In this work we have investigated the transcriptional profile of synovial tissue sampled from RA patients before anti-TNF treatment with the aim to identify biomarkers predictive of response. METHODOLOGY/PRINCIPAL FINDINGS: Synovial tissue samples were obtained by arthroscopy from 62 RA patients before the initiation of infliximab treatment. RNA was extracted and gene expression profiling was performed using an in-house spotted long oligonucleotide array covering 17972 unique genes. Tissue sections were also analyzed by immunohistochemistry to evaluate cell infiltrates. Response to infliximab treatment was assessed according to the EULAR response criteria. The presence of lymphocyte aggregates dominated the expression profiles and a significant overrepresentation of lymphocyte aggregates in good responding patients confounded the analyses. A statistical model was set up to control for the effect of aggregates, but no differences could be identified between responders and non-responders. Subsequently, the patients were split into lymphocyte aggregate positive- and negative patients. No statistically significant differences could be identified except for 38 transcripts associated with differences between good- and non-responders in aggregate positive patients. A profile was identified in these genes that indicated a higher level of metabolism in good responding patients, which indirectly can be connected to increased inflammation. CONCLUSIONS/SIGNIFICANCE: It is pivotal to account for the presence of lymphoid aggregates when studying gene expression patterns in rheumatoid synovial tissue. In spite of our original hypothesis, the data do not support the notion that microarray analysis of whole synovial biopsy specimens can be used in the context of personalized medicine to identify non-responders to anti-TNF therapy before the initiation of treatment.

BACKGROUND: Ultra-deep pyrosequencing (UDPS) allows identification of rare HIV-1 variants and minority drug resistance mutations, which are not detectable by standard sequencing. PRINCIPAL FINDINGS: Here, UDPS was used to analyze the dynamics of HIV-1 genetic variation in reverse transcriptase (RT) (amino acids 180-220) in six individuals consecutively sampled before, during and after failing 3TC and AZT containing antiretroviral treatment. Optimized UDPS protocols and bioinformatic software were developed to generate, clean and analyze the data. The data cleaning strategy reduced the error rate of UDPS to an average of 0.05%, which is lower than previously reported. Consequently, the cut-off for detection of resistance mutations was very low. A median of 16,016 (range 2,406-35,401) sequence reads were obtained per sample, which allowed detection and quantification of minority resistance mutations at amino acid position 181, 184, 188, 190, 210, 215 and 219 in RT. In four of five pre-treatment samples low levels (0.07-0.09%) of the M184I mutation were observed. Other resistance mutations, except T215A and T215I were below the detection limit. During treatment failure, M184V replaced M184I and dominated the population in combination with T215Y, while wild-type variants were rarely detected. Resistant virus disappeared rapidly after treatment interruption and was undetectable as early as after 3 months. In most patients, drug resistant variants were replaced by wild-type variants identical to those present before treatment, suggesting rebound from latent reservoirs. CONCLUSIONS: With this highly sensitive UDPS protocol preexisting drug resistance was infrequently observed; only M184I, T215A and T215I were detected at very low levels. Similarly, drug resistant variants in plasma quickly decreased to undetectable levels after treatment interruption. The study gives important insights into the dynamics of the HIV-1 quasispecies and is of relevance for future research and clinical use of the UDPS technology.

BACKGROUND: Massively parallel sequencing systems continue to improve on data output, while leaving labor-intensive library preparations a potential bottleneck. Efforts are currently under way to relieve the crucial and time-consuming work to prepare DNA for high-throughput sequencing. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we demonstrate an automated parallel library preparation protocol using generic carboxylic acid-coated superparamagnetic beads and polyethylene glycol precipitation as a reproducible and flexible method for DNA fragment length separation. With this approach the library preparation for DNA sequencing can easily be adjusted to a desired fragment length. The automated protocol, here demonstrated using the GS FLX Titanium instrument, was compared to the standard manual library preparation, showing higher yield, throughput and great reproducibility. In addition, 12 libraries were prepared and uniquely tagged in parallel, and the distribution of sequence reads between these indexed samples could be improved using quantitative PCR-assisted pooling. CONCLUSIONS/SIGNIFICANCE: We present a novel automated procedure that makes it possible to prepare 36 indexed libraries per person and day, which can be increased to up to 96 libraries processed simultaneously. The yield, speed and robust performance of the protocol constitute a substantial improvement to present manual methods, without the need of extensive equipment investments. The described procedure enables a considerable efficiency increase for small to midsize sequencing centers.

With recent findings on the role of reprogramming factors on stem cells, in vitro screening assays for studying (de)-differentiation is of great interest. We developed a miniaturized stem cell screening chip that is easily accessible and provides means of rapidly studying thousands of individual stem/progenitor cell samples, using low reagent volumes. For example, screening of 700,000 substances would take less than two days, using this platform combined with a conventional bio-imaging system. The microwell chip has standard slide format and consists of 672 wells in total. Each well holds 500 nl, a volume small enough to drastically decrease reagent costs but large enough to allow utilization of standard laboratory equipment. Results presented here include weeklong culturing and differentiation assays of mouse embryonic stem cells, mouse adult neural stem cells, and human embryonic stem cells. The possibility to either maintain the cells as stem/progenitor cells or to study cell differentiation of stem/progenitor cells over time is demonstrated. Clonality is critical for stem cell research, and was accomplished in the microwell chips by isolation and clonal analysis of single mouse embryonic stem cells using flow cytometric cell-sorting. Protocols for practical handling of the microwell chips are presented, describing a rapid and user-friendly method for the simultaneous study of thousands of stem cell cultures in small microwells. This microwell chip has high potential for a wide range of applications, for example directed differentiation assays and screening of reprogramming factors, opening up considerable opportunities in the stem cell field.

BackgroundEnvironmental challenges may affect both the exposed individuals and their offspring. We investigated possible adaptive aspects of such cross-generation transmissions, and hypothesized that chronic unpredictable food access would cause chickens to show a more conservative feeding strategy and to be more dominant, and that these adaptations would be transmitted to the offspring.Methodology/principal findingsParents were raised in an unpredictable (UL) or in predictable diurnal light rhythm (PL, 12:12 h light:dark). In a foraging test, UL birds pecked more at freely available, rather than at hidden and more attractive food, compared to birds from the PL group. Female offspring of UL birds, raised in predictable light conditions without parental contact, showed a similar foraging behavior, differing from offspring of PL birds. Furthermore, adult offspring of UL birds performed more food pecks in a dominance test, showed a higher preference for high energy food, survived better, and were heavier than offspring of PL parents. Using cDNA microarrays, we found that the differential brain gene expression caused by the challenge was mirrored in the offspring. In particular, several immunoglobulin genes seemed to be affected similarly in both UL parents and their offspring. Estradiol levels were significantly higher in egg yolk from UL birds, suggesting one possible mechanism for these effects.Conclusions/significanceOur findings suggest that unpredictable food access caused seemingly adaptive responses in feeding behavior, which may have been transmitted to the offspring by means of epigenetic mechanisms, including regulation of immune genes. This may have prepared the offspring for coping with an unpredictable environment.

BackgroundStress influences many aspects of animal behaviour and is a major factor driving populations to adapt to changing living conditions, such as during domestication. Stress can affect offspring through non-genetic mechanisms, but recent research indicates that inherited epigenetic modifications of the genome could possibly also be involved.Methodology/principal findingsRed junglefowl (RJF, ancestors of modern chickens) and domesticated White Leghorn (WL) chickens were raised in a stressful environment (unpredictable light-dark rhythm) and control animals in similar pens, but on a 12/12 h light-dark rhythm. WL in both treatments had poorer spatial learning ability than RJF, and in both populations, stress caused a reduced ability to solve a spatial learning task. Offspring of stressed WL, but not RJF, raised without parental contact, had a reduced spatial learning ability compared to offspring of non-stressed animals in a similar test as that used for their parents. Offspring of stressed WL were also more competitive and grew faster than offspring of non-stressed parents. Using a whole-genome cDNA microarray, we found that in WL, the same changes in hypothalamic gene expression profile caused by stress in the parents were also found in the offspring. In offspring of stressed WL, at least 31 genes were up- or down-regulated in the hypothalamus and pituitary compared to offspring of non-stressed parents.Conclusions/significanceOur results suggest that, in WL the gene expression response to stress, as well as some behavioural stress responses, were transmitted across generations. The ability to transmit epigenetic information and behaviour modifications between generations may therefore have been favoured by domestication. The mechanisms involved remain to be investigated; epigenetic modifications could either have been inherited or acquired de novo in the specific egg environment. In both cases, this would offer a novel explanation to rapid evolutionary adaptation of a population.