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Autophagy is a cellular catabolic process that relies on the cooperation of autophagosomes and lysosomes. During starvation, the cell expands both compartments to enhance degradation processes. We found that starvation activates a transcriptional program that controls major steps of the autophagic pathway, including autophagosome formation, autophagosome-lysosome fusion, and substrate degradation. The transcription factor EB (TFEB), a master gene for lysosomal biogenesis, coordinated this program by driving expression of autophagy and lysosomal genes. Nuclear localization and activity of TFEB were regulated by serine phosphorylation mediated by the extracellular signal—regulated kinase 2, whose activity was tuned by the levels of extracellular nutrients. Thus, a mitogen-activated protein kinase—dependent mechanism regulates autophagy by controlling the biogenesis and partnership of two distinct cellular organelles.

Background Functional analyses of genomic data within the context of a priori biomolecular networks can give valuable mechanistic insights. However, such analyses are not a trivial task, owing to the complexity of biological networks and lack of computational methods for their effective integration with experimental data. Results We developed a software application suite, NetWalker, as a one-stop platform featuring a number of novel holistic (i.e. assesses the whole data distribution without requiring data cutoffs) data integration and analysis methods for network-based comparative interpretations of genome-scale data. The central analysis components, NetWalk and FunWalk, are novel random walk-based network analysis methods that provide unique analysis capabilities to assess the entire data distributions together with network connectivity to prioritize molecular and functional networks, respectively, most highlighted in the supplied data. Extensive inter-operability between the analysis components and with external applications, including R, adds to the flexibility of data analyses. Here, we present a detailed computational analysis of our microarray gene expression data from MCF7 cells treated with lethal and sublethal doses of doxorubicin. Conclusion NetWalker, a detailed step-by-step tutorial containing the analyses presented in this paper and a manual are available at the web site http://netwalkersuite.org .

Pre-mRNA splicing is a key controller of human gene expression. Disturbances in splicing due to mutation lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of splicing modulator compounds (SMCs) have been recently identified and establish that pre-mRNA splicing represents a target for therapy. We describe herein the identification of BPN-15477, a SMC that restores correct splicing of ELP1 exon 20. Using transcriptome sequencing from treated fibroblast cells and a machine learning approach, we identify BPN-15477 responsive sequence signatures. We then leverage this model to discover 155 human disease genes harboring ClinVar mutations predicted to alter pre-mRNA splicing as targets for BPN-15477. Splicing assays confirm successful correction of splicing defects caused by mutations in CFTR , LIPA , MLH1 and MAPT . Subsequent validations in two disease-relevant cellular models demonstrate that BPN-15477 increases functional protein, confirming the clinical potential of our predictions. Drugs that modify RNA splicing are promising treatments for many genetic diseases. Here the authors show that deep learning strategies can predict drug targets, strongly supporting the use of in silico approaches to expand the therapeutic potential of drugs that modulate RNA splicing.

Familial dysautonomia (FD) is a rare recessive neurodevelopmental disease caused by a splice mutation in the Elongator acetyltransferase complex subunit 1 ( ELP1 ) gene. This mutation results in a tissue-specific reduction of ELP1 protein, with the lowest levels in the central and peripheral nervous systems (CNS and PNS, respectively). FD patients exhibit complex neurological phenotypes due to the loss of sensory and autonomic neurons. Disease symptoms include decreased pain and temperature perception, impaired or absent myotatic reflexes, proprioceptive ataxia, and progressive retinal degeneration. While the involvement of the PNS in FD pathogenesis has been clearly recognized, the underlying mechanisms responsible for the preferential neuronal loss remain unknown. In this study, we aimed to elucidate the molecular mechanisms underlying FD by conducting a comprehensive transcriptome analysis of neuronal tissues from the phenotypic mouse model TgFD9 ; Elp1 Δ20/flox . This mouse recapitulates the same tissue-specific ELP1 mis-splicing observed in patients while modeling many of the disease manifestations. Comparison of FD and control transcriptomes from dorsal root ganglion (DRG), trigeminal ganglion (TG), medulla (MED), cortex, and spinal cord (SC) showed significantly more differentially expressed genes (DEGs) in the PNS than the CNS. We then identified genes that were tightly co-expressed and functionally dependent on the level of full-length ELP1 transcript. These genes, defined as ELP1 dose-responsive genes, were combined with the DEGs to generate tissue-specific dysregulated FD signature genes and networks. Within the PNS networks, we observed direct connections between Elp1 and genes involved in tRNA synthesis and genes related to amine metabolism and synaptic signaling. Importantly, transcriptomic dysregulation in PNS tissues exhibited enrichment for neuronal subtype markers associated with peptidergic nociceptors and myelinated sensory neurons, which are known to be affected in FD. In summary, this study has identified critical tissue-specific gene networks underlying the etiology of FD and provides new insights into the molecular basis of the disease.

Cerebral organoids can be used to gain insights into cell type specific processes perturbed by genetic variants associated with neuropsychiatric disorders. However, robust and scalable phenotyping of organoids remains challenging. Here, we perform RNA sequencing on 71 samples comprising 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to integrate bulk RNA and single-cell RNA sequence data. We apply Orgo-Seq to 16p11.2 deletions and 15q11–13 duplications, two loci associated with autism spectrum disorder, to identify immature neurons and intermediate progenitor cells as critical cell types for 16p11.2 deletions. We further applied Orgo-Seq to identify cell type-specific driver genes. Our work presents a quantitative phenotyping framework to integrate multi-transcriptomic datasets for the identification of cell types and cell type-specific co-expressed driver genes associated with neuropsychiatric disorders. Cerebral organoids can be used to gain insights into neuropsychiatric disorders. Here the authors carry out RNAseq characterization from organoids derived from donors with autism spectrum disorder to identify associated cell type specific driver genes.

Background Tuberous sclerosis complex (TSC) is a neurodevelopmental disorder with frequent occurrence of epilepsy, autism spectrum disorder (ASD), intellectual disability (ID), and tumors in multiple organs. The aberrant activation of mTORC1 in TSC has led to treatment with mTORC1 inhibitor rapamycin as a lifelong therapy for tumors, but TSC-associated neurocognitive manifestations remain unaffected by rapamycin. Methods Here, we generated patient-specific, induced pluripotent stem cells (iPSCs) from a TSC patient with a heterozygous, germline, nonsense mutation in exon 15 of TSC1 and established an isogenic set of heterozygous (Het), null and corrected wildtype (Corr-WT) iPSCs using CRISPR/Cas9-mediated gene editing. We differentiated these iPSCs into neural progenitor cells (NPCs) and examined neurodevelopmental phenotypes, signaling and changes in gene expression by RNA-seq. Results Differentiated NPCs revealed enlarged cell size in TSC1-Het and Null NPCs, consistent with mTORC1 activation. TSC1-Het and Null NPCs also revealed enhanced proliferation and altered neurite outgrowth in a genotype-dependent manner, which was not reversed by rapamycin. Transcriptome analyses of TSC1-NPCs revealed differentially expressed genes that display a genotype-dependent linear response, i.e., genes upregulated/downregulated in Het were further increased/decreased in Null. In particular, genes linked to ASD, epilepsy, and ID were significantly upregulated or downregulated warranting further investigation. In TSC1-Het and Null NPCs, we also observed basal activation of ERK1/2, which was further activated upon rapamycin treatment. Rapamycin also increased MNK1/2-eIF4E signaling in TSC1-deficient NPCs. Conclusion MEK-ERK and MNK-eIF4E pathways regulate protein translation, and our results suggest that aberrant translation distinct in TSC1/2-deficient NPCs could play a role in neurodevelopmental defects. Our data showing upregulation of these signaling pathways by rapamycin support a strategy to combine a MEK or a MNK inhibitor with rapamycin that may be superior for TSC-associated CNS defects. Importantly, our generation of isogenic sets of NPCs from TSC patients provides a valuable platform for translatome and large-scale drug screening studies. Overall, our studies further support the notion that early developmental events such as NPC proliferation and initial process formation, such as neurite number and length that occur prior to neuronal differentiation, represent primary events in neurogenesis critical to disease pathogenesis of neurodevelopmental disorders such as ASD.

Structural Genomics aims to elucidate protein structures to identify their functions. Unfortunately, the variation of just a few residues can be enough to alter activity or binding specificity and limit the functional resolution of annotations based on sequence and structure; in enzymes, substrates are especially difficult to predict. Here, large-scale controls and direct experiments show that the local similarity of five or six residues selected because they are evolutionarily important and on the protein surface can suffice to identify an enzyme activity and substrate. A motif of five residues predicted that a previously uncharacterized Silicibacter sp. protein was a carboxylesterase for short fatty acyl chains, similar to hormone-sensitive-lipase–like proteins that share less than 20% sequence identity. Assays and directed mutations confirmed this activity and showed that the motif was essential for catalysis and substrate specificity. We conclude that evolutionary and structural information may be combined on a Structural Genomics scale to create motifs of mixed catalytic and noncatalytic residues that identify enzyme activity and substrate specificity.

Rare individuals with inactivating mutations in the Huntington's disease gene (HTT) exhibit variable abnormalities that imply essential HTT roles during organ development. Here we report phenotypes produced when increasingly severe hypomorphic mutations in the murine HTT orthologue Htt, (HdhneoQ20, HdhneoQ50, HdhneoQ111), were placed over a null allele (Hdhex4/5). The most severe hypomorphic allele failed to rescue null lethality at gastrulation, while the intermediate, though still severe, alleles yielded recessive perinatal lethality and a variety of fetal abnormalities affecting body size, skin, skeletal and ear formation, and transient defects in hematopoiesis. Comparative molecular analysis of wild-type and Htt-null retinoic acid-differentiated cells revealed gene network dysregulation associated with organ development that nominate polycomb repressive complexes and miRNAs as molecular mediators. Together these findings demonstrate that Htt is required both pre- and post-gastrulation to support normal development.

Somatic expansion of the Huntington’s disease (HD) CAG repeat drives the rate of a pathogenic process ultimately resulting in neuronal cell death. Although mechanisms of toxicity are poorly delineated, transcriptional dysregulation is a likely contributor. To identify modifiers that act at the level of CAG expansion and/or downstream pathogenic processes, we tested the impact of genetic knockout, in Htt Q111 mice, of Hdac2 or Hdac3 in medium-spiny striatal neurons that exhibit extensive CAG expansion and exquisite disease vulnerability. Both knockouts moderately attenuated CAG expansion, with Hdac2 knockout decreasing nuclear huntingtin pathology. Hdac2 knockout resulted in a substantial transcriptional response that included modification of transcriptional dysregulation elicited by the Htt Q111 allele, likely via mechanisms unrelated to instability suppression. Our results identify novel modifiers of different aspects of HD pathogenesis in medium-spiny neurons and highlight a complex relationship between the expanded Htt allele and Hdac2 with implications for targeting transcriptional dysregulation in HD.