LCM-seq reveals unique transcriptional adaptation mechanisms of resistant neurons and identifies protective pathways in spinal muscular atrophy.

Somatic motor neurons are selectively vulnerable in spinal muscular atrophy (SMA), which is caused by a deficiency of the ubiquitously expressed survival of motor neuron protein. However, some motor neuron groups, including oculomotor and trochlear (ocular), which innervate eye muscles, are for unknown reasons spared. To reveal mechanisms of vulnerability and resistance in SMA, we investigate the transcriptional dynamics in discrete neuronal populations using laser capture microdissection coupled with RNA sequencing (LCM-seq). Using gene correlation network analysis, we reveal a TRP53-mediated stress response that is intrinsic to all somatic motor neurons independent of their vulnerability, but absent in relatively resistant red nucleus and visceral motor neurons. However, the temporal and spatial expression analysis across neuron types shows that the majority of SMA-induced modulations are cell type-specific. Using Gene Ontology and protein network analyses, we show that ocular motor neurons present unique disease-adaptation mechanisms that could explain their resilience. Specifically, ocular motor neurons up-regulate (1) Syt1, Syt5, and Cplx2, which modulate neurotransmitter release; (2) the neuronal survival factors Gdf15, Chl1, and Lif; (3) Aldh4, that protects cells from oxidative stress; and (4) the caspase inhibitor Pak4. Finally, we show that GDF15 can rescue vulnerable human spinal motor neurons from degeneration. This confirms that adaptation mechanisms identified in resilient neurons can be used to reduce susceptibility of vulnerable neurons. In conclusion, this in-depth longitudinal transcriptomics analysis in SMA reveals novel cell type-specific changes that, alone and combined, present compelling targets, including Gdf15, for future gene therapy studies aimed toward preserving vulnerable motor neurons.

Mouse Model of Alagille Syndrome and Mechanisms of Jagged1 Missense Mutations.

BACKGROUND & AIMS: Alagille syndrome is a genetic disorder characterized by cholestasis, ocular abnormalities, characteristic facial features, heart defects, and vertebral malformations. Most cases are associated with mutations in JAGGED1 (JAG1), which encodes a Notch ligand, although it is not clear how these contribute to disease development. We aimed to develop a mouse model of Alagille syndrome to elucidate these mechanisms. METHODS: Mice with a missense mutation (H268Q) in Jag1 (Jag1+/Ndr mice) were outbred to a C3H/C57bl6 background to generate a mouse model for Alagille syndrome (Jag1Ndr/Ndr mice). Liver tissues were collected at different timepoints during development, analyzed by histology, and liver organoids were cultured and analyzed. We performed transcriptome analysis of Jag1Ndr/Ndr livers and livers from patients with Alagille syndrome, cross-referenced to the Human Protein Atlas, to identify commonly dysregulated pathways and biliary markers. We used species-specific transcriptome separation and ligand-receptor interaction assays to measure Notch signaling and the ability of JAG1Ndr to bind or activate Notch receptors. We studied signaling of JAG1 and JAG1Ndr via NOTCH 1, NOTCH2, and NOTCH3 and resulting gene expression patterns in parental and NOTCH1-expressing C2C12 cell lines. RESULTS: Jag1Ndr/Ndr mice had many features of Alagille syndrome, including eye, heart, and liver defects. Bile duct differentiation, morphogenesis, and function were dysregulated in newborn Jag1Ndr/Ndr mice, with aberrations in cholangiocyte polarity, but these defects improved in adult mice. Jag1Ndr/Ndr liver organoids collapsed in culture, indicating structural instability. Whole-transcriptome sequence analyses of liver tissues from mice and patients with Alagille syndrome identified dysregulated genes encoding proteins enriched at the apical side of cholangiocytes, including CFTR and SLC5A1, as well as reduced expression of IGF1. Exposure of Notch-expressing cells to JAG1Ndr, compared with JAG1, led to hypomorphic Notch signaling, based on transcriptome analysis. JAG1-expressing cells, but not JAG1Ndr-expressing cells, bound soluble Notch1 extracellular domain, quantified by flow cytometry. However, JAG1 and JAG1Ndr cells each bound NOTCH2, and signaling from NOTCH2 signaling was reduced but not completely inhibited, in response to JAG1Ndr compared with JAG1. CONCLUSIONS: In mice, expression of a missense mutant of Jag1 (Jag1Ndr) disrupts bile duct development and recapitulates Alagille syndrome phenotypes in heart, eye, and craniofacial dysmorphology. JAG1Ndr does not bind NOTCH1, but binds NOTCH2, and elicits hypomorphic signaling. This mouse model can be used to study other features of Alagille syndrome and organ development.

Single-Cell Analysis Reveals a Close Relationship between Differentiating Dopamine and Subthalamic Nucleus Neuronal Lineages.

Stem cell engineering and grafting of mesencephalic dopamine (mesDA) neurons is a promising strategy for brain repair in Parkinson's disease (PD). Refinement of differentiation protocols to optimize this approach will require deeper understanding of mesDA neuron development. Here, we studied this process using transcriptome-wide single-cell RNA sequencing of mouse neural progenitors expressing the mesDA neuron determinant Lmx1a. This approach resolved the differentiation of mesDA and neighboring neuronal lineages and revealed a remarkably close relationship between developing mesDA and subthalamic nucleus (STN) neurons, while also highlighting a distinct transcription factor set that can distinguish between them. While previous hESC mesDA differentiation protocols have relied on markers that are shared between the two lineages, we found that application of these highlighted markers can help to refine current stem cell engineering protocols, increasing the proportion of appropriately patterned mesDA progenitors. Our results, therefore, have important implications for cell replacement therapy in PD.

Laser capture microscopy coupled with Smart-seq2 for precise spatial transcriptomic profiling.

Laser capture microscopy (LCM) coupled with global transcriptome profiling could enable precise analyses of cell populations without the need for tissue dissociation, but has so far required relatively large numbers of cells. Here we report a robust and highly efficient strategy for LCM coupled with full-length mRNA-sequencing (LCM-seq) developed for single-cell transcriptomics. Fixed cells are subjected to direct lysis without RNA extraction, which both simplifies the experimental procedures as well as lowers technical noise. We apply LCM-seq on neurons isolated from mouse tissues, human post-mortem tissues, and illustrate its utility down to single captured cells. Importantly, we demonstrate that LCM-seq can provide biological insight on highly similar neuronal populations, including motor neurons isolated from different levels of the mouse spinal cord, as well as human midbrain dopamine neurons of the substantia nigra compacta and the ventral tegmental area.

Decoding breast cancer tissue-stroma interactions using species-specific sequencing.

INTRODUCTION: Decoding transcriptional effects of experimental tissue-tissue or cell-cell interactions is important; for example, to better understand tumor-stroma interactions after transplantation of human cells into mouse (xenografting). Transcriptome analysis of intermixed human and mouse cells has, however, frequently relied on the need to separate the two cell populations prior to transcriptome analysis, which introduces confounding effects on gene expression. METHODS: To circumvent this problem, we here describe a bioinformatics-based, genome-wide transcriptome analysis technique, which allows the human and mouse transcriptomes to be decoded from a mixed mouse and human cell population. The technique is based on a bioinformatic separation of the mouse and human transcriptomes from the initial mixed-species transcriptome resulting from sequencing an excised tumor/stroma specimen without prior cell sorting. RESULTS: Under stringent separation criteria, i.e., with a read misassignment frequency of 0.2 %, we show that 99 % of the genes can successfully be assigned to be of mouse or human origin, both in silico, in cultured cells and in vivo. We use a new species-specific sequencing technology-referred to as S(3) ("S-cube")-to provide new insights into the Notch downstream response following Notch ligand-stimulation and to explore transcriptional changes following transplantation of two different breast cancer cell lines (luminal MCF7 and basal-type MDA-MB-231) into mammary fat pad tissue in mice of different immunological status. We find that MCF7 and MDA-MB-231 respond differently to fat pad xenografting and the stromal response to transplantation of MCF7 and MDA-MB-231 cells was also distinct. CONCLUSIONS: In conclusion, the data show that the S(3) technology allows for faithful recording of transcriptomic changes when human and mouse cells are intermixed and that it can be applied to address a broad spectrum of research questions.

The human cap-binding complex is functionally connected to the nuclear RNA exosome.

Nuclear processing and quality control of eukaryotic RNA is mediated by the RNA exosome, which is regulated by accessory factors. However, the mechanism of exosome recruitment to its ribonucleoprotein (RNP) targets remains poorly understood. Here we report a physical link between the human exosome and the cap-binding complex (CBC). The CBC associates with the ARS2 protein to form CBC-ARS2 (CBCA) and then further connects, together with the ZC3H18 protein, to the nuclear exosome targeting (NEXT) complex, thus forming CBC-NEXT (CBCN). RNA immunoprecipitation using CBCN factors as well as the analysis of combinatorial depletion of CBCN and exosome components underscore the functional relevance of CBC-exosome bridging at the level of target RNA. Specifically, CBCA suppresses read-through products of several RNA families by promoting their transcriptional termination. We suggest that the RNP 5' cap links transcription termination to exosomal RNA degradation through CBCN.

Efficient and comprehensive representation of uniqueness for next-generation sequencing by minimum unique length analyses.

As next generation sequencing technologies are getting more efficient and less expensive, RNA-Seq is becoming a widely used technique for transcriptome studies. Computational analysis of RNA-Seq data often starts with the mapping of millions of short reads back to the genome or transcriptome, a process in which some reads are found to map equally well to multiple genomic locations (multimapping reads). We have developed the Minimum Unique Length Tool (MULTo), a framework for efficient and comprehensive representation of mappability information, through identification of the shortest possible length required for each genomic coordinate to become unique in the genome and transcriptome. Using the minimum unique length information, we have compared different uniqueness compensation approaches for transcript expression level quantification and demonstrate that the best compensation is achieved by discarding multimapping reads and correctly adjusting gene model lengths. We have also explored uniqueness within specific regions of the mouse genome and enhancer mapping experiments. Finally, by making MULTo available to the community we hope to facilitate the use of uniqueness compensation in RNA-Seq analysis and to eliminate the need to make additional mappability files.