Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

BackgroundVariants of microRNAs (miRNAs), called isomiRs, are commonly reported in deep-sequencing studies; however, the functional significance of these variants remains controversial. Observational studies show that isomiR patterns are non-random, hinting that these molecules could be regulated and therefore functional, although no conclusive biological role has been demonstrated for these molecules.ResultsTo assess the biological relevance of isomiRs, we have performed ultra-deep miRNA-seq on ten adult human tissues, and created an analysis pipeline called miRNA-MATE to align, annotate, and analyze miRNAs and their isomiRs. We find that isomiRs share sequence and expression characteristics with canonical miRNAs, and are generally strongly correlated with canonical miRNA expression. A large proportion of isomiRs potentially derive from AGO2 cleavage independent of Dicer. We isolated polyribosome-associated mRNA, captured the mRNA-bound miRNAs, and found that isomiRs and canonical miRNAs are equally associated with translational machinery. Finally, we transfected cells with biotinylated RNA duplexes encoding isomiRs or their canonical counterparts and directly assayed their mRNA targets. These studies allow us to experimentally determine genome-wide mRNA targets, and these experiments showed substantial overlap in functional mRNA networks suppressed by both canonical miRNAs and their isomiRs.ConclusionsTogether, these results find isomiRs to be biologically relevant and functionally cooperative partners of canonical miRNAs that act coordinately to target pathways of functionally related genes. This work exposes the complexity of the miRNA-transcriptome, and helps explain a major miRNA paradox: how specific regulation of biological processes can occur when the specificity of miRNA targeting is mediated by only 6 to 11 nucleotides.

SUMMARYThere is a pressing need for patient-derived cell models of brain diseases that are relevant and robust enough to produce the large quantities of cells required for molecular and functional analyses. We describe here a new cell model based on patient-derived cells from the human olfactory mucosa, the organ of smell, which regenerates throughout life from neural stem cells. Olfactory mucosa biopsies were obtained from healthy controls and patients with either schizophrenia, a neurodevelopmental psychiatric disorder, or Parkinson's disease, a neurodegenerative disease. Biopsies were dissociated and grown as neurospheres in defined medium. Neurosphere-derived cell lines were grown in serum-containing medium as adherent monolayers and stored frozen. By comparing 42 patient and control cell lines we demonstrated significant disease-specific alterations in gene expression, protein expression and cell function, including dysregulated neurodevelopmental pathways in schizophrenia and dysregulated mitochondrial function, oxidative stress and xenobiotic metabolism in Parkinson's disease. The study has identified new candidate genes and cell pathways for future investigation. Fibroblasts from schizophrenia patients did not show these differences. Olfactory neurosphere-derived cells have many advantages over embryonic stem cells and induced pluripotent stem cells as models for brain diseases. They do not require genetic reprogramming and they can be obtained from adults with complex genetic diseases. They will be useful for understanding disease aetiology, for diagnostics and for drug discovery.

Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ), Parkinson's disease (PD), and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.

The study of Parkinson's disease (PD), like other complex neurodegenerative disorders, is limited by access to brain tissue from patients with a confirmed diagnosis. Alternatively the study of peripheral tissues may offer some insight into the molecular basis of disease susceptibility and progression, but this approach still relies on brain tissue to benchmark relevant molecular changes against. Several studies have reported whole-genome expression profiling in post-mortem brain but reported concordance between these analyses is lacking. Here we apply a standardised pathway analysis to seven independent case-control studies, and demonstrate increased concordance between data sets. Moreover data convergence increased when the analysis was limited to the five substantia nigra (SN) data sets; this highlighted the down regulation of dopamine receptor signaling and insulin-like growth factor 1 (IGF1) signaling pathways. We also show that case-control comparisons of affected post mortem brain tissue are more likely to reflect terminal cytoarchitectural differences rather than primary pathogenic mechanisms. The implementation of a correction factor for dopaminergic neuronal loss predictably resulted in the loss of significance of the dopamine signaling pathway while axon guidance pathways increased in significance. Interestingly the IGF1 signaling pathway was also over-represented when data from non-SN areas, unaffected or only terminally affected in PD, were considered. Our findings suggest that there is greater concordance in PD whole-genome expression profiling when standardised pathway membership rather than ranked gene list is used for comparison.

SUMMARYHereditary spastic paraplegia (HSP) leads to progressive gait disturbances with lower limb muscle weakness and spasticity. Mutations in SPAST are a major cause of adult-onset, autosomal-dominant HSP. Spastin, the protein encoded by SPAST, is a microtubule-severing protein that is enriched in the distal axon of corticospinal motor neurons, which degenerate in HSP patients. Animal and cell models have identified functions of spastin and mutated spastin but these models lack the gene dosage, mutation variability and genetic background that characterize patients with the disease. In this study, this genetic variability is encompassed by comparing neural progenitor cells derived from biopsies of the olfactory mucosa from healthy controls with similar cells from HSP patients with SPAST mutations, in order to identify cell functions altered in HSP. Patient-derived cells were similar to control-derived cells in proliferation and multiple metabolic functions but had major dysregulation of gene expression, with 57% of all mRNA transcripts affected, including many associated with microtubule dynamics. Compared to control cells, patient-derived cells had 50% spastin, 50% acetylated α-tubulin and 150% stathmin, a microtubule-destabilizing enzyme. Patient-derived cells were smaller than control cells. They had altered intracellular distributions of peroxisomes and mitochondria and they had slower moving peroxisomes. These results suggest that patient-derived cells might compensate for reduced spastin, but their increased stathmin expression reduced stabilized microtubules and altered organelle trafficking. Sub-nanomolar concentrations of the microtubule-binding drugs, paclitaxel and vinblastine, increased acetylated α-tubulin levels in patient cells to control levels, indicating the utility of this cell model for screening other candidate compounds for drug therapies.

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PURPOSE Understanding the immunobiology of the 15% to 30% of patients with follicular lymphoma (FL) who experience progression of disease within 24 months (POD24) remains a priority. Solid tumors with low levels of intratumoral immune infiltration have inferior outcomes. It is unknown whether a similar relationship exists between POD24 in FL. PATIENTS AND METHODS Digital gene expression using a custom code set—five immune effector, six immune checkpoint, one macrophage molecules—was applied to a discovery cohort of patients with early- and advanced-stage FL (n = 132). T-cell receptor repertoire analysis, flow cytometry, multispectral immunofluorescence, and next-generation sequencing were performed. The immune infiltration profile was validated in two independent cohorts of patients with advanced-stage FL requiring systemic treatment (n = 138, rituximab plus cyclophosphamide, vincristine, prednisone; n = 45, rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone), with the latter selected to permit comparison of patients experiencing a POD24 event with those having no progression at 5 years or more. RESULTS Immune molecules showed distinct clustering, characterized by either high or low expression regardless of categorization as an immune effector, immune checkpoint, or macrophage molecule. Low programmed death-ligand 2 (PD-L2) was the most sensitive/specific marker to segregate patients with adverse outcomes; therefore, PD-L2 expression was chosen to distinguish immune infiltrationHI (ie, high PD-L2) FL biopsies from immune infiltrationLO (ie, low PD-L2) tumors. Immune infiltrationHI tissues were highly infiltrated with macrophages and expanded populations of T-cell clones. Of note, the immune infiltrationLO subset of patients with FL was enriched for POD24 events (odds ratio [OR], 4.32; c-statistic, 0.81; P = .001), validated in the independent cohorts (rituximab plus cyclophosphamide, vincristine, prednisone: OR, 2.95; c-statistic, 0.75; P = .011; and rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone: OR, 7.09; c-statistic, 0.88; P = .011). Mutations were equally proportioned across tissues, which indicated that degree of immune infiltration is capturing aspects of FL biology distinct from its mutational profile. CONCLUSION Assessment of immune-infiltration by PD-L2 expression is a promising tool with which to help identify patients who are at risk for POD24.