The majority of published gene-expression studies have used RNA isolated from whole cells, overlooking the potential impact of including nuclear transcriptome in the analyses. In this study, mRNA fractions from the cytoplasm and from whole cells (total RNA) were prepared from three human cell lines and sequenced using massive parallel sequencing. For all three cell lines, of about 15000 detected genes approximately 400 to 1400 genes were detected in different amounts in the cytoplasmic and total RNA fractions. Transcripts detected at higher levels in the total RNA fraction had longer coding sequences and higher number of miRNA target sites. Transcripts detected at higher levels in the cytoplasmic fraction were shorter or contained shorter untranslated regions. Nuclear retention of transcripts and mRNA degradation via miRNA pathway might contribute to this differential detection of genes. The consequence of the differential detection was further investigated by comparison to proteomics data. Interestingly, the expression profiles of cytoplasmic and total RNA correlated equally well with protein abundance levels indicating regulation at a higher level. We conclude that expression levels derived from the total RNA fraction be regarded as an appropriate estimate of the amount of mRNAs present in a given cell population, independent of the coding sequence length or UTRs.

New generation sequencing technologies producing increasingly complex datasets demand new efficient and specialized sequence analysis algorithms. Often, it is only the 'novel' sequences in a complex dataset that are of interest and the superfluous sequences need to be removed. A novel algorithm, fast and accurate classification of sequences (FACSs), is introduced that can accurately and rapidly classify sequences as belonging or not belonging to a reference sequence. FACS was first optimized and validated using a synthetic metagenome dataset. An experimental metagenome dataset was then used to show that FACS achieves comparable accuracy as BLAT and SSAHA2 but is at least 21 times faster in classifying sequences. Source code for FACS, Bloom filters and MetaSim dataset used is available at http://facs.biotech.kth.se. The Bloom::Faster 1.6 Perl module can be downloaded from CPAN at http://search.cpan.org/ approximately palvaro/Bloom-Faster-1.6/ henrik.stranneheim@biotech.kth.se; joakiml@biotech.kth.se Supplementary data are available at Bioinformatics online.

We report a child with an antenatally detected brain tumor that progressed over three years' time despite surgery, chemo- and proton therapy. Retrospective whole-genome and transcriptome sequencing with methylation analysis of primary tumor tissue led to the molecular diagnosis infant-type hemispheric glioma, and identified a novel SNRNP70::ALK fusion, providing a therapeutic target for compassionate-use precision treatment with the ALK tyrosine kinase inhibitor lorlatinib. Functional studies confirmed the fusion protein to be expressed and active in the patient's tumor. After two years of therapy, the child has sustained partial tumor regression on MRI and no new neurological symptoms. We conclude that comprehensive multi-omics analyses are required for correct molecular diagnosis in childhood CNS tumors and can radically impact patient outcome by identifying molecular targets for precision treatment.

PDZ domains play key roles in mediating protein-protein interactions by recognizing short PDZ-binding motifs, typically at the C-termini of target proteins. Zonula occludens 1 (ZO-1) is a scaffolding protein that links tight junction proteins to the actin cytoskeleton, and contains three PDZ domains. Here, we focus on its third PDZ (PDZ3_ZO-1) domain, which interacts with the C-terminus of junctional adhesion protein A as well as connexin 45. To investigate how the domain context of the PDZ3_ZO-1 domain affects its folding and function, we previously established two distinct fusions of PDZ3_ZO-1 and a Trp-cage mini-protein. These fusions with swapped domain order result in FD3A with Trp-cage fused C-terminally and FD4A with Trp-cage fused N-terminally. This study aims to explore the extent to which the distinct Trp-cage fusions affect the function of PDZ3_ZO-1 domain in peptide binding. We find that PDZ3_ZO-1 retains its function, interaction with the connexin 45 peptide, also as part of the fusion proteins. Furthermore, using a phage display approach, we identified a new PDZ3_ZO-1 binding peptide derived from the C-terminal region of methylcytosine dioxygenase TET3. Subsequent validation revealed a significantly higher affinity of PDZ3_ZO-1 for the TET3 peptide as compared to the connexin 45 peptide. Thermodynamic analyses revealed that the swapped domain order conferred distinct effects on the thermodynamic parameters. These results provide insights into the structural and functional adaptability of PDZ domains in engineered proteins, and offer useful principles for the rational design of functional fusion proteins.

The transcriptomes of cells infected with lytic and non-lytic variants of coxsackievirus B2 Ohio-1 (CVB2O) were analyzed using next generation sequencing. This approach was selected with the purpose of elucidating the effects of lytic and non-lytic viruses on host cell transcription. Total RNA was extracted from infected cells and sequenced. The resulting reads were subsequently mapped against the human and CVB2O genomes. The amount of intracellular RNA was measured, indicating lower proportions of human RNA in the cells infected with the lytic virus compared to the non-lytic virus after 48 hours. This may be explained by reduced activity of the cellular transcription/translation machinery in lytic enteroviral replication due to activities of the enteroviral proteases 2A and/or 3C. Furthermore, differential expression in the cells infected with the two virus variants was identified and a number of transcripts were singled out as possible answers to the question of how the viruses interact with the host cells, resulting in lytic or non-lytic infections.

In mechanical thrombectomy (MT) for ischemic stroke, endothelial cells (ECs) from intracranial blood vessels adhere to the stent retriever device and can be harvested. However, understanding the molecular biology and the role of the endothelium in different pathological conditions remains insufficient. The purpose of the study was to characterize and analyze the molecular aspect of harvested ECs using cell culture and transcriptomic techniques in an MT swine model relevant to clinical ischemic stroke. In swine, preformed thrombi were injected into the external carotid and subclavian arteries to occlude their branches. MT was performed according to clinical routine. The stent retriever device and thrombus were treated with cell dissociation buffer. The resulting cell suspension was analyzed by immunohistochemistry and was cultured. Cultured cells were analyzed using single-cell RNA sequencing (scRNA-seq) after fluorescence-activated cell sorting (FACS). A total number of 37 samples were obtained containing CD31-positive cells. Cell culture was successful in 90% of samples, and the cells expressed multiple typical EC protein markers. Eighty-nine percent of the sorted cells yielded high-quality transcriptomes, and single-cell transcriptomes from cultured cells showed that they expressed typical endothelial gene patterns. Gene expression analysis of ECs from an occluded artery did not show distinctive clustering into subtypes. ECs harvested during MT can be cultured and analyzed using single-cell transcriptomic techniques. This analysis can be implemented in clinical practice to study the EC gene expression of comorbidities, such as hypertension, diabetes mellitus, and metabolic syndrome, in patients suffering from acute ischemic stroke.

Understanding complex biological systems requires functional characterization of specialized tissue domains. However, existing strategies for generating and analysing high-throughput spatial expression profiles were developed for a limited range of organisms, primarily mammals. Here we present the first available approach to generate and study high-resolution, spatially resolved functional profiles in a broad range of model plant systems. Our process includes high-throughput spatial transcriptome profiling followed by spatial gene and pathway analyses. We first demonstrate the feasibility of the technique by generating spatial transcriptome profiles from model angiosperms and gymnosperms microsections. In Arabidopsis thaliana we use the spatial data to identify differences in expression levels of 141 genes and 189 pathways in eight inflorescence tissue domains. Our combined approach of spatial transcriptomics and functional profiling offers a powerful new strategy that can be applied to a broad range of plant species, and is an approach that will be pivotal to answering fundamental questions in developmental and evolutionary biology.