Recent understandings in the development and spread of cancer have led to the realization of novel single cell analysis platforms focused on circulating tumor cells (CTCs). A simple, rapid, and inexpensive analytical platform capable of providing genetic information on these rare cells is highly desirable to support clinicians and researchers alike to either support the selection or adjustment of therapy or provide fundamental insights into cell function and cancer progression mechanisms. We report on the genetic profiling of single cancer cells, exploiting a combination of multiplex ligation-dependent probe amplification (MLPA) and electrochemical detection. Cells were isolated using laser capture and lysed, and the mRNA was extracted and transcribed into DNA. Seven markers were amplified by MLPA, which allows for the simultaneous amplification of multiple targets with a single primer pair, using MLPA probes containing unique barcode sequences. Capture probes complementary to each of these barcode sequences were immobilized on a printed circuit board (PCB) manufactured electrode array and exposed to single-stranded MLPA products and subsequently to a single stranded DNA reporter probe bearing a HRP molecule, followed by substrate addition and fast electrochemical pulse amperometric detection. We present asimple, rapid, flexible, and inexpensive approach for the simultaneous quantification of multiple breast cancer related mRNA markers, with single tumor cell sensitivity.
Here we show that an affinity proteomics strategy using affinity-purified antibodies raised against recombinant human protein fragments can be used for chromosome-wide protein profiling. The approach is based on affinity reagents raised toward bioinformatics-designed protein epitope signature tags corresponding to unique regions of individual gene loci. The genes of human chromosome 21 identified by the genome efforts were investigated, and the success rates for de novo cloning, protein production, and antibody generation were 85, 76, and 56%, respectively. Using human tissue arrays, a systematic profiling of protein expression and subcellular localization was undertaken for the putative gene products. The results suggest that this affinity proteomics strategy can be used to produce a proteome atlas, describing distribution and expression of proteins in normal tissues as well as in common cancers and other forms of diseased tissues.
We describe a novel method for transcript profiling based on high-throughput parallel sequencing of signature tags using a non-gel-based microtiter plate format. The method relies on the identification of cDNA clones by pyrosequencing of the region corresponding to the 3'-end of the mRNA preceding the poly(A) tail. Simultaneously, the method can be used for gene discovery, since tags corresponding to unknown genes can be further characterized by extended sequencing. The protocol was validated using a model system for human atherosclerosis. Two 3'-tagged cDNA libraries, representing macrophages and foam cells, which are key components in the development of atherosclerotic plaques, were constructed using a solid phase approach. The libraries were analyzed by pyrosequencing, giving on average 25 bases. As a control, conventional expressed sequence tag (EST) sequencing using slab gel electrophoresis was performed. Homology searches were used to identify the genes corresponding to each tag. Comparisons with EST sequencing showed identical, unique matches in the majority of cases when the pyrosignature was at least 18 bases. A visualization tool was developed to facilitate differential analysis using a virtual chip format. The analysis resulted in identification of genes with possible relevance for development of atherosclerosis. The use of the method for automated massive parallel signature sequencing is discussed.
There is a growing demand for high-throughput methods for analysis of single-nucleotide polymorphic (SNP) positions. Here, we have evaluated a novel sequencing approach, pyrosequencing, for such purposes. Pyrosequencing is a sequencing-by-synthesis method in which a cascade of enzymatic reactions yields detectable light, which is proportional to incorporated nucleotides. One feature of typing SNPs with pyrosequencing is that each allelic variant will give a unique sequence compared to the two other variants. These variants can easily be distinguished by a pattern recognition software. The software displays the allelic: alternatives and allows for direct comparison with the pyrosequencing raw data. For optimal determination of SNPs, various protocols of nucleotide dispensing order were investigated. Here, we demonstrate that typing of SNPs can efficiently be performed by pyrosequencing using an automated system for parallel analysis of 96 samples in approximately 5 min, suitable for large-scale screening and typing of SNPs.
This report describes a single-step extension approach suitable for high-throughput single-nucleotide polymorphism typing applications. The method relies on extension of paired allele-specific primers and we demonstrate that the reaction kinetics were slower for mismatched configurations compared with matched configurations. In our approach we employ apyrase, a nucleotide degrading enzyme, to allow accurate discrimination between matched and mismatched primer-template configurations. This apyrase-mediated allele-specific extension (AMASE) protocol allows incorporation of nucleotides when the reaction kinetics are fast (matched 3'-end primer) but degrades the nucleotides before extension when the reaction kinetics are slow (mismatched 3'-end primer). Thus, AMASE circumvents the major limitation of previous allele-specific extension assays in which slow reaction kinetics will still give rise to extension products from mismatched 3'-end primers, hindering proper discrimination. It thus represents a significant improvement of the allele-extension method. AMASE was evaluated by a bioluminometric assay in which successful incorporation of unmodified nucleotides is monitored in real-time using an enzymatic cascade.
As the human genome sequence is determined, there is an emerging need for the analysis of human sequence variations as genetic markers in diagnosis, linkage and association studies, cancer research, and pharmacogenomics. There are several different techniques and approaches for detecting these genetic variations, and here we review some of these techniques and their application fields. However, all the techniques have advantages and disadvantages, and factors such as laboratory instrumentation, personnel experience, required accuracy, required throughput, and cost often have to be taken into account before selecting a method.
Tumor suppressor genes are implicated in cell cycle progression. Inactivation of these genes predominantly occurs through mutations and/or allelic loss that involves both alleles. With inactivation by multiple mutations in a single gene, cloning of the amplified gene is necessary to determine whether the mutations reside on one ol both alleles. Using pyrosequencing, a recently developed approach based on sequencing-by-synthesis, we studied genetic variability in the p53 tumor suppressor gene and could quantify the ratio between the mutated and wild-type amplified fragments. Further-more, this sequencing technique also allows allelic determination of adjacent mutations with no cloning of amplified fragments.
The invention refers to a method for multiplex amplification of at least one specific nucleic acid locus, comprising the steps of: providing at least one oligonucleotide probe pair that is designed so that the first and second probe of the pair anneal to a specific nucleic acid locus on a target molecule, in which pair the first probe has an extendable 3'-end, and a second probe has a 5'-end that is directly or indirectly labelled with a phosphate group; providing a target molecule comprising at least one specific nucleic acid locus; allowing the probe pair to anneal to the target molecule; allowing the 3'-end of the first probe to extend by influence of polymerase by adding a set of three different dNTPs; ligating the 3'-end of the extended first probe to the 5'-end of the second probe. Hereby, a method is provided which allows a high specificity for simultaneous amplification of several loci. Further, the invention involves a kit for use in the method of the invention.
Squamous cell carcinoma (SCC) of the skin represents a group of neoplasms which is associated with exposure to UV light. Recently, we obtained data suggesting that invasive skin cancer and its precursors derive from one original neoplastic clone. Here, the analysis were extended by loss of heterozygosity (LOH) analysis in the chromosome 9q22.3 region. A total of 85 samples, taken from twenty-two sections of sun-exposed sites, corresponding to normal epidermis, morphological normal cells with positive immuno-staining for the p53 protein (p53 patches), dysplasias, cancer in situ (CIS) and squamous cell carcinomas (SCC) of the skin were analysed. Overall, about 70% of p53 patches had mutations in the p53 gene but not LOH in the p53 gene or 9q22.3 region. Approximately 70% of the dysplasias showed p53 mutations of which about 40% had LOH in the p53 region but not in the 9q22.3 region. In contrast, about 65% of SCC and CIS displayed LOH in the 9q22.3 region, as well as frequent (80%) mutations and/or LOH in the p53 gene. These findings strongly suggest that alterations in the p53 gene is an early event in the progression towards SCC, whereas malignant development involves LOH and alterations in at least one (or several) tumor suppressor genes located in chromosome 9q22.3.
We here present a comparative genome, transcriptome and functional network analysis of three human cancer cell lines (A431, U251MG and U2OS), and investigate their relation to protein expression. Gene copy numbers significantly influenced corresponding transcript levels; their effect on protein levels was less pronounced. We focused on genes with altered mRNA and/or protein levels to identify those active in tumor maintenance. We provide comprehensive information for the three genomes and demonstrate the advantage of integrative analysis for identifying tumor-related genes amidst numerous background mutations by relating genomic variation to expression/protein abundance data and use gene networks to reveal implicated pathways.
Background: Sampling genomes with Fosmid vectors and sequencing of pooled Fosmid libraries on the Illumina platform for massive parallel sequencing is a novel and promising approach to optimizing the trade-off between sequencing costs and assembly quality. Results: In order to sequence the genome of Norway spruce, which is of great size and complexity, we developed and applied a new technology based on the massive production, sequencing, and assembly of Fosmid pools (FP). The spruce chromosomes were sampled with similar to 40,000 bp Fosmid inserts to obtain around two-fold genome coverage, in parallel with traditional whole genome shotgun sequencing (WGS) of haploid and diploid genomes. Compared to the WGS results, the contiguity and quality of the FP assemblies were high, and they allowed us to fill WGS gaps resulting from repeats, low coverage, and allelic differences. The FP contig sets were further merged with WGS data using a novel software package GAM-NGS. Conclusions: By exploiting FP technology, the first published assembly of a conifer genome was sequenced entirely with massively parallel sequencing. Here we provide a comprehensive report on the different features of the approach and the optimization of the process. We have made public the input data (FASTQ format) for the set of pools used in this study: ftp://congenie.org/congenie/Nystedt_2013/Assembly/ProcessedData/FosmidPools/.(alternatively accessible via http://congenie.org/downloads).The software used for running the assembly process is available at http://research.scilifelab.se/andrej_alexeyenko/downloads/fpools/.
Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.
The field of spatial transcriptomics is rapidly expanding, and with it the repertoire of available technologies. However, several of the transcriptome-wide spatial assays do not operate on a single cell level, but rather produce data comprised of contributions from a – potentially heterogeneous – mixture of cells. Still, these techniques are attractive to use when examining complex tissue specimens with diverse cell populations, where complete expression profiles are required to properly capture their richness. Motivated by an interest to put gene expression into context and delineate the spatial arrangement of cell types within a tissue, we here present a model-based probabilistic method that uses single cell data to deconvolve the cell mixtures in spatial data. To illustrate the capacity of our method, we use data from different experimental platforms and spatially map cell types from the mouse brain and developmental heart, which arrange as expected.
In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon response overlapping with regions of T-cell and macrophage subset colocalization. We construct a predictive model to infer presence of tertiary lymphoid-like structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define a high resolution map of cellular interactions in tumors and provide tools generalizing across tissues and diseases. 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.
Motivation: Collection of spatial signals in large numbers has become a routine task in multiple omics-fields, but parsing of these rich datasets still pose certain challenges. In whole or near-full transcriptome spatial techniques, spurious expression profiles are intermixed with those exhibiting an organized structure. To distinguish profiles with spatial patterns from the background noise, a metric that enables quantification of spatial structure is desirable. Current methods designed for similar purposes tend to be built around a framework of statistical hypothesis testing, hence we were compelled to explore a fundamentally different strategy. Results: We propose an unexplored approach to analyze spatial transcriptomics data, simulating diffusion of individual transcripts to extract genes with spatial patterns. The method performed as expected when presented with synthetic data. When applied to real data, it identified genes with distinct spatial profiles, involved in key biological processes or characteristic for certain cell types. Compared to existing methods, ours seemed to be less informed by the genes' expression levels and showed better time performance when run with multiple cores.
Background: We have developed genomic tools to allow the genus Populus ( aspens and cottonwoods) to be exploited as a full-featured model for investigating fundamental aspects of tree biology. We have undertaken large-scale expressed sequence tag ( EST) sequencing programs and created Populus microarrays with significant gene coverage. One of the important aspects of plant biology that cannot be studied in annual plants is the gene activity involved in the induction of autumn leaf senescence. Results: On the basis of 36,354 Populus ESTs, obtained from seven cDNA libraries, we have created a DNA microarray consisting of 13,490 clones, spotted in duplicate. Of these clones, 12,376 (92%) were confirmed by resequencing and all sequences were annotated and functionally classified. Here we have used the microarray to study transcript abundance in leaves of a free-growing aspen tree ( Populus tremula) in northern Sweden during natural autumn senescence. Of the 13,490 spotted clones, 3,792 represented genes with significant expression in all leaf samples from the seven studied dates. Conclusions: We observed a major shift in gene expression, coinciding with massive chlorophyll degradation, that reflected a shift from photosynthetic competence to energy generation by mitochondrial respiration, oxidation of fatty acids and nutrient mobilization. Autumn senescence had much in common with senescence in annual plants; for example many proteases were induced. We also found evidence for increased transcriptional activity before the appearance of visible signs of senescence, presumably preparing the leaf for degradation of its components.
Objectives: To analyze the early gene expression in macrophages accompanying the phenotypic changes into foam cells upon exposure to oxidized low-density lipoprotein. To identify candidate genes and markers for further studies into the pathogenesis of atherosclerosis. Methods: Cells of the monocytic cell line THP-1 were activated by PMA and exposed to oxidized low-density lipoprotein. Gene expression profiles were investigated after 24 h, using a solid phase cDNA representational difference analysis (RDA) method and shotgun sequencing. Results were verified by microarray hybridization, and analyzed in the virtual chip display of a novel software tool for transcript profile exploration. Results: By comparing transcript profiles of exposed/unexposed cells, 1,984 transcript sequences, representing a total of 921 genes with altered expression levels in response to oxidized low-density lipoprotein exposure, were identified. Genes that are central to cell cycle control and proliferation, inflammatory response, and of pathways not previously implicated in atherosclerosis were identified. The data obtained is also made available on-line at http:// biobase.biotech.kth.se/thp1a for further exploration. Conclusion: The identification of new candidate genes for atherosclerotic disease through RDA-based transcript profiling facilitates further functional genomic studies in coronary artery disease. Candidate genetic polymorphism markers of potential clinical relevance can be identified by filtering information in genome variation databases through the virtual chip analysis of the transcript profiles and subsequently tested in association studies.
Monitoring of differential gene expression is an important step towards understanding of gene function. We describe a comparison of the representational difference analysis (RDA) subtraction process with corresponding microarray analysis. The subtraction steps are followed in a quantitative manner using a shotgun cloning and sequencing procedure that includes over 1900 gene sequences. In parallel, the enriched transcripts are spotted onto microarrays facilitating large scale hybridization analysis of the representations and the difference products. We show by the shotgun procedure that there is a high diversity of gene fragments represented in the iterative RDA products (92-67% singletons) with a low number of shared sequences (<9%) between subsequent subtraction cycles. A non redundant set of 1141 RDA clones were immobilized on glass slides and the majority of these clones (97%) gave repeated good fluorescent signals in a subsequent hybridization of the labelled and amplified original cDNA. We observed only a low number of false positives (<2%) and a more than twofold differential expression for 32% (363) of the immobilized RDA clones. In conclusion, we show that by random sequencing of the difference products we obtained an accurate transcript profile of the individual steps and that large-scale confirmation of the obtained transcripts can be achieved by microarray analysis.
Various approaches to the study of differential gene expression are applied to compare cell lines and tissue samples in a wide range of biological contexts. The compromise between focusing on only the important genes in certain cellular processes and achieving a complete picture is critical for the selection of strategy. We demonstrate how global microarray technology can be used for the exploration of the differentially expressed genes extracted through representational difference analysis (RDA). The subtraction of ubiquitous gene fragments from the two samples was demonstrated using cDNA microarrays including more than 32 000 spotted, PCR-amplified human clones. Hybridizations indicated the expression of 9100 of the microarray elements in a macrophage/foam cell atherosclerosis model system, of which many were removed during the RDA process. The stepwise subtraction procedure was demonstrated to yield an efficient enrichment of gene fragments overrepresented in either sample (18% in the representations, 86% after the first subtraction, and 88% after the second subtraction), many of which were impossible to detect in the starting material. Interestingly, the method allowed for the observation of the differential expression of several members of the low-abundant nuclear receptor gene family. We also observed a certain background level in the difference products of nondifferentially expressed gene fragments, warranting a verification strategy for selected candidate genes. The differential expression of several genes was verified by real-time PCR.
The discriminatory power of the noncoding control region (CR) of domestic dog mitochondrial DNA alone is relatively low. The extent to which the discriminatory power could be increased by analyzing additional highly variable coding regions of the mitochondrial genome (mtGenome) was therefore investigated. Genetic variability across the mtGenome was evaluated by phylogenetic analysis, and the three most variable similar to 1kb coding regions identified. We then sampled 100 Swedish dogs to represent breeds in accordance with their frequency in the Swedish population. A previously published dataset of 59 dog mtGenomes collected in the United States was also analyzed. Inclusion of the three coding regions increased the exclusion capacity considerably for the Swedish sample, from 0.920 for the CR alone to 0.964 for all four regions. The number of mtDNA types among all 159 dogs increased from 41 to 72, the four most frequent CR haplotypes being resolved into 22 different haplotypes.
During late developmental phases individual sympathetic neurons undergo a switch from noradrenergic to cholinergic neurotransmission. This phenomenon of plasticity depends on target-derived signals in vivo and is triggered by neurotrophic factors in neuronal cultures. To analyze genome-wide expression differences between the two transmitter phenotypes we employed DNA microarrays. RNA expression profiles were obtained from chick paravertebral sympathetic ganglia, treated with neurotrophin 3, glial cell line-derived neurotrophic factor or ciliary neurotrophic factor, all of which stimulate cholinergic differentiation. Results were compared with the effect of nerve growth factor, which functions as a pro-noradrenergic stimulus. The gene set common to all three comparisons defined the noradrenergic and cholinergic synexpression groups. Several functional categories, such as signal transduction, G-protein-coupled signaling, cation transport, neurogenesis and synaptic transmission, were enriched in these groups. Experiments based on the prediction that some of the identified genes play a role in the neurotransmitter switch identified bone morphogenetic protein signaling as an inhibitor of cholinergic differentiation.
The development of low-cost, accurate, and equipment-free diagnostic tests is crucial to many clinical, laboratory, and field applications, including forensics and medical diagnostics. Cellulose fiber-based paper is an inexpensive, biodegradable, and renewable resource, the use of which as a biomolecule detection matrix and support confers several advantages compared to traditional materials such as glass. In this context, a new, facile method for the preparation of surface functionalized papers bearing single-stranded probe DNA (ssDNA) for rapid target hybridization via capillary transport is presented. Optimized reaction conditions were developed that allowed the direct, one-step activation of standard laboratory filters by the inexpensive and readily available bifunctional linking reagent, 1,4-phenylenediisothiocyanate. Such papers were thus amenable to subsequent coupling of amine-labeled ssDNA under standard conditions widely used for glass-based supports. The intrinsic wicking ability of the paper matrix facilitated rapid sample elution through arrays of probe DNA, leading to significant, detectable hybridization in the time required for the sample liquid to transit the vertical length of the strip (less than 2 min). The broad applicability of these paper test strips as rapid and specific diagnostics in "real-life" situations was exemplified by the discrimination of amplicons generated from canine and human mitochondrial and genomic DNA in mock forensic samples.
Expressed sequence tags (ESTs) were generated from two Chironomus tentans cDNA libraries, constructed from an embryo epithelial cell line and from larva midgut tissue. 8584 5'-end ESTs were generated and assembled into 3110 tentative unique transcripts, providing the largest contribution of C. tentans sequences to public databases to date. Annotation using BLAST gave 1975 (63.5%) transcripts with a significant match in the major gene/protein databases, 1170 with a best match to Anopheles gambiae and 480 to Drosophila melanogaster. 1091 transcripts (35.1%) had no match to any database. Studies of open reading frames suggest that at least 323 of these contain a coding sequence, indicating that a large proportion of the genes in C. tentans belong to previously unknown gene families.
Recent advances in spatially resolved transcriptomics have greatly expandedthe knowledge of complex multicellular biological systems. The field hasquickly expanded in recent years, and several new technologies have beendeveloped that all aim to combine gene expression data with spatialinformation. The vast array of methodologies displays fundamentaldierences in their approach to obtain this information, and thus,demonstrate method-specific advantages and shortcomings. While the field ismoving forward at a rapid pace, there are still multiple challenges presentedto be addressed, including sensitivity, labor extensiveness, tissue-typedependence, and limited capacity to obtain detailed single-cell information.No single method can currently address all these key parameters. In thisreview, available spatial transcriptomics methods are described and theirapplications as well as their strengths and weaknesses are discussed. Futuredevelopments are explored and where the field is heading to is deliberatedupon.
Spatial Transcriptomics has been shown to be a persuasive RNA sequencing
technology for analyzing cellular heterogeneity within tissue sections. The
technology efficiently captures and barcodes 3’ tags of all polyadenylated
transcripts from a tissue section, and thus provides a powerful platform when
performing quantitative spatial gene expression studies. However, the current
protocol does not recover the full-length information of transcripts, and
consequently lack information regarding alternative splice variants. Here, we
introduce a novel protocol for spatial isoform profiling, using Spatial
Transcriptomics barcoded arrays.
The human developing heart holds a greater proportion of stem-cell-like cells than the adult heart. However, it is not completely understood how these stem cells differentiate into various cardiac cell types. We have performed an organ-wide transcriptional landscape analysis of the developing heart to advance our understanding of cardiac morphogenesis in humans. Comprehensive spatial gene expression analyses identified distinct profiles that correspond not only to individual chamber compartments, but also distinctive regions within the outflow tract. Furthermore, the generated spatial expression reference maps facilitated the assignment of 3,787 human embryonic cardiac cells obtained from single-cell RNA-sequencing to an in situlocation. Through this approach we reveal that the outflow tract contains a wider range of cell types than the chambers, and that the epicardium expression profile can be traced to several cell types that are activated at different stages of development. We also provide a 3D spatial model of human embryonic cardiac cells to enable further studies of the developing human heart.
The process of cardiac morphogenesis in humans is incompletely understood. Its full characterization requires a deep exploration of the organ-wide orchestration of gene expression with a single-cell spatial resolution. Here, we present a molecular approach that reveals the comprehensive transcriptional landscape of cell types populating the embryonic heart at three developmental stages and that maps cell-type-specific gene expression to specific anatomical domains. Spatial transcriptomics identified unique gene profiles that correspond to distinct anatomical regions in each developmental stage. Human embryonic cardiac cell types identified by single-cell RNA sequencing confirmed and enriched the spatial annotation of embryonic cardiac gene expression. In situ sequencing was then used to refine these results and create a spatial subcellular map for the three developmental phases. Finally, we generated a publicly available web resource of the human developing heart to facilitate future studies on human cardiogenesis.
Heart failure is a major health problem linked to poor quality of life and high mortality rates. Hence, novel biomarkers, such as fetal marker genes with low expression levels, could potentially differentiate disease states in order to improve therapy. In many studies on heart failure, cardiac biopsies have been analyzed as uniform pieces of tissue with bulk techniques, but this homogenization approach can mask medically relevant phenotypes occurring only in isolated parts of the tissue. This study examines such spatial variations within and between regions of cardiac biopsies. In contrast to standard RNA sequencing, this approach provides a spatially resolved transcriptome- and tissue-wide perspective of the adult human heart, and enables detection of fetal marker genes expressed by minor subpopulations of cells within the tissue. Analysis of patients with heart failure, with preserved ejection fraction, demonstrated spatially divergent expression of fetal genes in cardiac biopsies.
Background Basal cell carcinomas (BCCs) are prevalent tumours with uniform histology that develop without any known precursor lesion. Alterations in the sonic hedgehog-patched1 signalling pathway are accepted as necessary events for tumorigenesis, and mutations in the patched1 gene are frequently present in tumours. Objectives To analyse transcript profiles in BCC. Methods We used laser-assisted microdissection to isolate and collect cell populations defined under the microscope. Peripheral cells from nests of BCC were selected to represent tumour cells, and normal keratinocytes from epidermis basal layer were used as control. Extracted RNA was amplified and hybridized on to a cDNA microarray. Results Our results show that BCC cells express a transcript signature that is significantly different from that of normal keratinocytes, and over 350 genes with various functions were identified as differentially expressed. The compiled data suggest an upregulation of the Wnt signalling pathway as a major event in BCC cells. Furthermore, tumour cells appear to have an increased sensitivity to oxygen radicals and dysregulated genes involved in antigen presentation. Results were validated at both the transcriptional level using real-time polymerase chain reaction and at the protein level using immunohistochemistry. Conclusions We show that microdissection in combination with robust strategies for RNA extraction, amplification and cDNA microarray analysis allow for reliable transcript profiling and that antibody-based proteomics provides an advantageous strategy for the analysis of corresponding differentially expressed proteins. We found that expression patterns were significantly altered in BCC cells compared with basal keratinocytes and that the Wnt signalling pathway was upregulated in tumour cells.
Background The PTCH tumour suppressor gene is involved in the development of nearly all basal cell carcinomas (BCCs) of the skin and a fraction of squamous cell carcinomas (SCCs). A nonconservative Pro/Leu nucleotide polymorphism within PTCH exon 23 at codon 1315 was recently reported to be potentially important for the development of breast epithelial cell cancers. Objectives Accordingly, the status of PTCH codon 1315 was analysed for a possible association with the development of nonmelanoma skin cancers (NMSCs) in a pilot study. Because skin cancer risk is affected by specific population-dependent phenotypes such as skin and hair colour, codon 1315 was also analysed for normal allele frequency variation in human populations having differing extents of eumelanin vs. phaeomelanin. Methods The single nucleotide polymorphism in codon 1315 of the human PTCH gene was analysed in genomic DNA from six different populations comprising 472 blood samples and from 170 patients in four different categories with NMSC. Polymerase chain reaction and pyrosequencing were used to determine the allele frequencies. Allelic loss was furthermore determined in tumours following microdissection. Results The Pro/Pro genotype frequency ranged from 30% to 65% between populations, with a significant trend for a reduced frequency of the Pro/Pro genotype in populations having lighter pigmentation (P = 0.020). Pro/Pro frequency showed an increasing trend with increasing tumour case severity (P = 0.027). In 260 samples from 180 Swedish patients with NMSC and a control group of 96 healthy ethnically matched volunteers, no statistically significant pairwise differences between groups were detected in the PTCH codon 1315 allelic distribution, neither was a difference seen for multiple or early onset cases of BCC in the Swedish population. In Swedish patients with single tumours, allelic loss (loss of heterozygosity) was observed in 20 of 30 (67%) patients with BCC and four of 22 (18%) patients with SCC, with no preference in the allele lost. In contrast, the Pro/Pro genotype was frequent in seven U.S. patients having multiple independent BCCs. One of these patients was heterozygous, enabling allelic loss studies. Of 20 independent tumours, 11 had lost an allele; 10 of the 11 had lost Leu, suggesting nonrandom loss that favoured retention of Pro (P = 0.0059). Conclusions Our results indicate an association between the eumelanin-to-phaeomelanin shift and a shift from the Pro/Pro genotype to Leu-containing genotypes. Failure to lose Pro during the shift to phaeomelanin may be associated with an increased population risk for BCC and increased individual risk for multiple BCC. During development of a tumour, the effect of Pro may be magnified by loss of the Leu allele.
Human basal cell cancer (BCC) shows unique growth characteristics, including a virtual inability to metastasize, absence of a precursor stage and lack of tumour progression. The clonal nature of BCC has long been a subject for debate because of the tumour growth pattern. Despite a morphologically multifocal appearance, genetic analysis and three-dimensional reconstructions of tumours have favoured a unicellular origin. We have utilized the X-chromosome inactivation assay in order to examine clonality in 13 cases of BCC. Four parts of each individual tumour plus isolated samples of stroma were analysed following laser-assisted microdissection. In 12/13 tumours, the epithelial component of the tumour showed a monoclonal pattern suggesting a unicellular origin. Surprisingly, one tumour showed evidence of being composed of at least two non-related monoclonal clones. This finding was supported by the analysis of the ptch and p53 gene. Clonality analysis of tumour stroma showed both mono- and polyclonal patterns. A prerequisite for this assay is that the extent of skewing is determined and compensated for in each case. Owing to the mosaic pattern of normal human epidermis, accurate coefficients are difficult to obtain; we, therefore, performed all analyses both with and without considering skewing. This study concludes that BCC are monoclonal neoplastic growths of epithelial cells, embedded in a connective tissue stroma at least in part of polyclonal origin. The study results show that what appears to be one tumour may occasionally constitute two or more independent tumours intermingled or adjacent to each other, possibly reflecting a local predisposition to malignant transformation.
Carcinogenesis is a multi-step series of somatic genetic events. The complexity of this multi-hit process makes it difficult to determine each single event and the definitive outcome of such events. To investigate the genetic alterations in cancer-related genes, sensitive and reliable detection methods are of major importance for generating relevant results. Another critical issue is the quality of starting material which largely affects the outcome of the analysis. Microdissection of cells defined under the microscope ensures a selection of representative material for subsequent genetic analysis. Skin cancer provides an advantageous model for studying the development of cancer. Detectable lesions occur early during tumor progression, facilitating molecular analysis of the cell populations from both preneoplastic and neoplastic lesions. Alterations of the p53 tumor suppressor gene are very common in non-melanoma skin cancer, and dysregulation of p53 pathways appear to be an early event in the tumor development. A high frequency of epidermal p53 clones has been detected in chronically sun-exposed skin. The abundance of clones containing p53 mutated keratinocytes adjacent to basal cell (BCC) and squamous cell carcinoma (SCC) suggests a role in human skin carcinogenesis. Studies using p53 mutations as a clonality marker have suggested a direct link between actinic keratosis, SCC in situ and invasive SCC. Microdissection-based studies have also shown that different parts of individual BCC tumors can share a common p53 mutation yet differ with respect to additional alterations within the p53 gene, consistent with subclonal development within tumors. Here, we present examples of using well-defined cell populations, including single cells, from complex tissue in combination with molecular tools to reveal features involved in skin carcinogenesis.
Foci of normal keratinocytes overexpressing p53 protein are frequently found in normal human skin. Such epidermal p53 clones are common in chronically sun-exposed skin and have been suggested to play a role in skin cancer development. In the present study, we have analyzed the prevalence of p53 mutations in epidermal p53 clones from normal skin surrounding basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). Using laser-assisted microdissection, 37 epidermal p53 clones adjacent to BCC (21) and SCC (16) were collected. Genetic analysis was performed using a multiplex/nested polymerase chain reaction followed by direct DNA sequencing of p53 exons 2-11. In total, 21 of 37 analyzed p53 clones consisted of p53-mutated keratinocytes. The identified mutations were located in p53 exons 4-8, corresponding to the sequence-specific DNA-binding domain. All mutations were missense, and 78% displayed a typical ultraviolet signature. The frequency of p53 mutations was similar in skin adjacent to BCC compared to SCC. The presented data confirm and extend previous knowledge on the genetic background of epidermal p53 clones. The mutation spectra found in epidermal p53 clones resemble that of non-melanoma skin cancer. Approximately, 40% of the epidermal p53 clones lacked an underlying p53 mutation, suggesting that other genetic events in genes up- or downstream of the p53 gene can generate foci of normal keratinocytes overexpressing p53 protein.
Despite the fact that the human Respiratory Syncytial Virus (RSV) was first discoveredback in 1956, it remains one of the leading causes of morbidity and mortality inyoung children. Transcriptome-wide spatially resolved transcriptomics is a technologyunder rapid development that introduces a new modality for exploratory examinationof cellular behavior. With this modality, we examine how RSV infection changes thelocal cellular environment in the lung by infecting mice with RSV and comparing itto control samples four days after infection. We find viral presence in all compartmentsof the tissue, well-defined induced tertiary lymphoid tissue within some of thesamples, compartmentalized infiltration of innate immune cells, as well as functionalenrichment of airway epithelial repair pathways.
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/.
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.
Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.
We introduce a new optimization algorithm, termed contrastive adjustment, for learning Markov transition kernels whose stationary distribution matches the data distribution. Contrastive adjustment is not restricted to a particular family of transition distributions and can be used to model data in both continuous and discrete state spaces. Inspired by recent work on noise-annealed sampling, we propose a particular transition operator, the noise kernel, that can trade mixing speed for sample fidelity. We show that contrastive adjustment is highly valuable in human-computer design processes, as the stationarity of the learned Markov chain enables local exploration of the data manifold and makes it possible to iteratively refine outputs by human feedback. We compare the performance of noise kernels trained with contrastive adjustment to current state-of-the-art generative models and demonstrate promising results on a variety of image synthesis tasks.
Spatial biology technologies provide complementary information about tissue anatomy but are often challenging or costly to combine experimentally. Here, we propose a method for multi-modal modeling of spatial biology data that integrates diverse data types and can be used for cross-modality data transfer. We demonstrate the method on histology-guided gene expression imputation and super resolution in sequencing-based spatial transcriptomics, and on feature imputation in high-resolution in situ data.
Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor micro- environment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.
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.
RNA-binding proteins (RBPs) play important roles in the regulation of gene expression through a variety of post-transcriptional mechanisms. The p53-induced RBP Wig-1 (Zmat3) binds RNA through its zinc finger domains and enhances stability of p53 and N-Myc mRNAs and decreases stability of FAS mRNA. To identify novel Wig-1-bound RNAs, we performed RNA-immunoprecipitation followed by high-throughput sequencing (RIP-Seq) in HCT116 and Saos-2 cells. We identified 286 Wig-1-bound mRNAs common between the two cell lines. Sequence analysis revealed that AU-rich elements (AREs) are highly enriched in the 3'UTR of these Wig-1-bound mRNAs. Network enrichment analysis showed that Wig-1 preferentially binds mRNAs involved in cell cycle regulation. Moreover, we identified a 2D Wig-1 binding motif in HIF1A mRNA. Our findings confirm that Wig-1 is an ARE-BP that regulates cell cycle-related processes and provide a novel view of how Wig-1 may bind mRNA through a putative structural motif. We also significantly extend the repertoire of Wig-1 target mRNAs. Since Wig-1 is a transcriptional target of the tumor suppressor p53, these results have implications for our understanding of p53-dependent stress responses and tumor suppression.
Two cDNA libraries were prepared, one from leaves of a field-grown aspen (Populus tremula) tree, harvested just before any visible sign of leaf senescence in the autumn, and one from young but fully expanded leaves of greenhouse-grown aspen (Populus tremula X tremuloides). Expressed sequence tags (ESTs; 5,128 and 4,841, respectively) were obtained from the two libraries. A semiautomatic method of annotation and functional classification of the ESTs, according to a modified Munich Institute of Protein Sequences classification scheme, was developed, utilizing information from three different databases. The patterns of gene expression in the two libraries were strikingly different. In the autumn leaf library, ESTs encoding metallothionein, early light-inducible proteins, and cysteine proteases were most abundant. Clones encoding other proteases and proteins involved in respiration and breakdown of lipids and pigments, as well as stress-related genes, were also well represented. We identified homologs to many known senescence-associated genes, as well as seven different genes encoding cysteine proteases, two encoding aspartic proteases, five encoding metallothioneins, and 35 additional genes that were up-regulated in autumn leaves. We also indirectly estimated the rate of plastid protein synthesis in the autumn leaves to be less that 10% of that in young leaves.
DNA microarray technology has evolved dramatically in recent years, and is now a common tool in researchers portfolios. The scope of the technique has expanded from small-scale studies to extensive studies such as classification of disease states. Technical knowledge regarding solid phase microarrays has also increased, and the results acquired today are more reliable than those obtained just a few years ago. Nevertheless, there are various aspects of microarray analysis that could be improved. In this article we show that the proportions of full-length probes used significantly affects the results of global analyses of transcriptomes. In particular, measurements of transcripts in low abundance are more sensitive to truncated probes, which generally increase the degree of cross hybridization and loss of specific signals. In order to improve microarray analysis, we here introduce a disiloxyl purification step, which ensures that all the probes on the microarray are at full length. We demonstrate that when the features on microarrays consist of full-length probes the signal intensity is significantly increased. The overall increase in intensity enables the hybridization stringency to be increased, and thus enhance the robustness of the results.
Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs withp <= 1 x 10(-3)for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p < 0.05). Then using 80% of the patients as training data, random LASSO reduced the number of SNVs/INDELs in the toxicity module into a feasible prediction model consisting of 62 SNVs/INDELs that accurately predict both the training and the test (remaining 20%) data with high (CTCAE 3-4) and low (CTCAE 0-1) maximal myelosuppressive toxicity completely, with the receiver-operating characteristic (ROC) area under the curve (AUC) of 100%. The present study shows how WGS, gene network modules, and random LASSO can be used to develop a feasible and tested model for predicting myelosuppressive toxicity. Although the proposed model predicts myelosuppression in this study, further evaluation in other studies is required to determine its reproducibility, usability, and clinical effect.
Four inborn errors of metabolism (IEMs) are known to cause hypermethioninemia by directly interfering with the methionine cycle. Hypermethioninemia is occasionally discovered incidentally, but it is often disregarded as an unspecific finding, particularly if liver disease is involved. In many individuals the hypermethioninemia resolves without further deterioration, but it can also represent an early sign of a severe, progressive neurodevelopmental disorder. Further investigation of unclear hypermethioninemia is therefore important. We studied two siblings affected by severe developmental delay and liver dysfunction. Biochemical analysis revealed increased plasma levels of methionine, S-adenosylmethionine (Ado Met), and S-adenosylhomocysteine (AdoHcy) but normal or mildly elevated homocysteine (Hcy) levels, indicating a block in the methionine cycle. We excluded S-adenosylhomocysteine hydrolase (SAHH) deficiency, which causes a similar biochemical phenotype, by using genetic and biochemical techniques and hypothesized that there was a functional block in the SAHH enzyme as a result of a recessive mutation in a different gene. Using exome sequencing, we identified a homozygous c.902C>A (p.Ala301Glu) missense mutation in the adenosine kinase gene (ADK), the function of which fits perfectly with this hypothesis. Increased urinary adenosine excretion confirmed ADK deficiency in the siblings. Four additional individuals from two unrelated families with a similar presentation were identified and shown to have a homozygous c.653A>C (p.Asp218Ala) and c.38G>A (p.Gly13Glu) mutation, respectively, in the same gene. All three missense mutations were deleterious, as shown by activity measurements on recombinant enzymes. ADK deficiency is a previously undescribed, severe IEM shedding light on a functional link between the methionine cycle and adenosine metabolism.