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Aging is a complex process involving transcriptomic changes associated with deterioration across multiple tissues and organs, including the brain. Recent studies using heterochronic parabiosis have shown that various aspects of aging-associated decline are modifiable or even reversible. To better understand how this occurs, we performed single-cell transcriptomic profiling of young and old mouse brains after parabiosis. For each cell type, we cataloged alterations in gene expression, molecular pathways, transcriptional networks, ligand–receptor interactions and senescence status. Our analyses identified gene signatures, demonstrating that heterochronic parabiosis regulates several hallmarks of aging in a cell-type-specific manner. Brain endothelial cells were found to be especially malleable to this intervention, exhibiting dynamic transcriptional changes that affect vascular structure and function. These findings suggest new strategies for slowing deterioration and driving regeneration in the aging brain through approaches that do not rely on disease-specific mechanisms or actions of individual circulating factors.

Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions

BACKGROUNDIn droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events. Here, we characterize this background noise exemplified by three single-cell RNA-seq (scRNA-seq) and two single-nucleus RNA-seq (snRNA-seq) replicates of mouse kidney cells. For each experiment, kidney cells from two mouse subspecies were pooled, allowing to identify cross-genotype contaminating molecules and estimate the levels of background noise.RESULTSWe find that background noise is highly variable across replicates and individual cells, making up on average 3-35% of the total counts (UMIs) per cell and show that this has a considerable impact on the specificity and detectability of marker genes. In search of the source of background noise, we find that expression profiles of cell-free droplets are very similar to expression profiles of cross-genotype contamination and hence that the majority of background molecules originates from ambient RNA. Finally, we use our genotype-based estimates to evaluate the performance of three methods (CellBender, DecontX, SoupX) that are designed to quantify and remove background noise. We find that CellBender provides the most precise estimates of background noise levels and also yields the highest improvement for marker gene detection. By contrast, clustering and classification of cells are fairly robust towards background noise and only small improvements can be achieved by background removal that may come at the cost of distortions in fine structure.CONCLUSIONOur findings help to better understand the extent, sources and impact of background noise in single-cell experiments and provide guidance on how to deal with it.

De novoheterozygous loss-of-function mutations inPTENare strongly associated with Autism spectrum disorders (ASD); however, it is unclear how heterozygous mutations in this gene affects different cell types during human brain development, and how these effects vary across individuals. Here, we used human cortical organoids from different donors to identify cell-type-specific developmental events that are affected by heterozygous mutations inPTEN. We profiled individual organoids by single-cell RNA-seq, proteomics and spatial transcriptomics, and revealed abnormalities in developmental timing in human outer radial glia progenitors and deep layer cortical projection neurons, which varied with the donor genetic background. Calcium imaging in intact organoids showed that both accelerated and delayed neuronal development phenotypes resulted in similar abnormal activity of local circuits, irrespective of genetic background. The work reveals donor-dependent, cell-type specific developmental phenotypes ofPTENheterozygosity that later converge on disrupted neuronal activity.

Background Many neurodegenerative diseases develop only later in life, when cells in the nervous system lose their structure or function. In many forms of neurodegenerative diseases, this late-onset phenomenon remains largely unexplained. Results Analyzing single-cell RNA sequencing from Alzheimer’s disease (AD) and Huntington’s disease (HD) patients, we find increased transcriptional heterogeneity in disease-state neurons. We hypothesize that transcriptional heterogeneity precedes neurodegenerative disease pathologies. To test this idea experimentally, we use juvenile forms (72Q; 180Q) of HD iPSCs, differentiate them into committed neuronal progenitors, and obtain single-cell expression profiles. We show a global increase in gene expression variability in HD. Autophagy genes become more stable, while energy and actin-related genes become more variable in the mutant cells. Knocking down several differentially variable genes results in increased aggregate formation, a pathology associated with HD. We further validate the increased transcriptional heterogeneity in CHD8+/− cells, a model for autism spectrum disorder. Conclusions Overall, our results suggest that although neurodegenerative diseases develop over time, transcriptional regulation imbalance is present already at very early developmental stages. Therefore, an intervention aimed at this early phenotype may be of high diagnostic value.

Realizing the full utility of brain organoids as experimental systems to study human cortical development requires understanding whether organoids replicate the cellular and molecular events of this complex process precisely, reproducibly, and with fidelity to the embryo. Here we present a comprehensive single-cell transcriptomic, epigenetic, and spatial atlas of human cortical organoid development, comprising over 610,000 cells, spanning initial generation of neural progenitors through production of differentiated neuronal and glial subtypes. We define the lineage relationships and longitudinal molecular trajectories of cortical cell types during development in organoids, and show that developmental processes of cellular diversification in organoids correlate closely to endogenous ones, irrespective of metabolic state. Using this data, we identify genes with predicted human-specific roles in lineage establishment, and discover a developmental origin for the transcriptional diversity of human callosal projection neurons, a population that has undergone dramatic expansion and diversification during human evolution. Our work provides a comprehensive, single-cell molecular map of human corticogenesis in vitro, identifying developmental trajectories and molecular mechanisms associated with human cellular diversification.

Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal phenotype, and fitness(1–3). Constructing complete fitness landscapes, mapping DNA sequences to fitness, is a long-standing goal in biology, but has remained elusive because it is challenging to generalize reliably to vast sequence spaces(4–6). Here, we construct sequence-to-expression models that capture fitness landscapes and use them to decipher principles of regulatory evolution. Using millions of randomly-sampled promoter DNA sequences and their measured expression levels in the yeast Saccharomyces cerevisiae, we learn deep neural network models that generalize with excellent prediction performance, and enable sequence design for expression engineering. Using our models, we study expression divergence under genetic drift and strong-selection weak-mutation regimes to find that regulatory evolution is rapid and subject to diminishing returns epistasis, that conflicting expression objectives in different environments constrain expression adaptation, and that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for using our models to detect signatures of selection on expression from natural variation in regulatory sequences and use it to discover an instance of convergent regulatory evolution. We assess mutational robustness, finding that regulatory mutation effect sizes follow a power law, characterize regulatory evolvability, visualize promoter fitness landscapes, discover evolvability archetypes and highlight the mutational robustness of natural regulatory sequence populations. Our work provides a general framework for addressing fundamental questions in regulatory evolution.

Here we introduce a mostly natural sequencing-by-synthesis (mnSBS) method for single-cell RNA sequencing (scRNA-seq), adapted to the Ultima genomics platform, and systematically benchmark it against current scRNA-seq technology. mnSBS uses mostly natural, unmodified nucleotides and only a low fraction of fluorescently labeled nucleotides, which allows for high polymerase processivity and lower costs. We demonstrate successful application in four scRNA-seq case studies of different technical and biological types, including 5′ and 3′ scRNA-seq, human peripheral blood mononuclear cells from a single individual and in multiplex, as well as Perturb-Seq. Benchmarking shows that results from mnSBS-based scRNA-seq are very similar to those using Illumina sequencing, with minor differences in results related to the position of reads relative to annotated gene boundaries, owing to single-end reads of Ultima being closer to gene ends than reads from Illumina. The method is thus compatible with state-of-the-art scRNA-seq libraries independent of the sequencing technology. We expect mnSBS to be of particular utility for cost-effective large-scale scRNA-seq projects.

Aging is a complex process involving transcriptomic changes associated with deterioration across multiple tissues and organs, including the brain. Recent studies using heterochronic parabiosis have shown that various aspects of aging-associated decline are modifiable or even reversible. To better understand how this occurs, we performed single-cell transcriptomic profiling of young and old mouse brains following parabiosis. For each cell type, we catalogued alterations in gene expression, molecular pathways, transcriptional networks, ligand-receptor interactions, and senescence status. Our analyses identified gene signatures demonstrating that heterochronic parabiosis regulates several hallmarks of aging in a cell-type-specific manner. Brain endothelial cells were found to be especially malleable to this intervention, exhibiting dynamic transcriptional changes that affect vascular structure and function. These findings suggest novel strategies for slowing deterioration and driving regeneration in the aging brain through approaches that do not rely on disease-specific mechanisms or actions of individual circulating factors.

The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

The four voltage-gated sodium channels SCN1/2/3/8A have been associated with heterogeneous types of developmental disorders, each presenting with disease specific temporal and cell type specific gene expression. Using single-cell RNA sequencing transcriptomic data from humans and mice, we observe that SCN1A is predominantly expressed in inhibitory neurons. In contrast, SCN2/3/8A are profoundly expressed in excitatory neurons with SCN2/3A starting prenatally, followed by SCN1/8A neonatally. In contrast to previous observations from low resolution RNA screens, we observe that all four genes are expressed in both excitatory and inhibitory neurons, however, exhibit differential expression strength. These findings provide molecular evidence, at single-cell resolution, to support the hypothesis that the excitatory/inhibitory (E/I) neuronal expression ratios of sodium channels are important regulatory mechanisms underlying brain homeostasis and neurological diseases. Modulating the E/I expression balance within cell types of sodium channels could serve as a potential strategy to develop targeted treatment for NaV-associated neuronal developmental disorders.

Realizing the full utility of brain organoids to study human development requires understanding whether organoids precisely replicate endogenous cellular and molecular events, particularly since acquisition of cell identity in organoids can be impaired by abnormal metabolic states. We present a comprehensive single-cell transcriptomic, epigenetic, and spatial atlas of human cortical organoid development, comprising over 610,000 cells, from generation of neural progenitors through production of differentiated neuronal and glial subtypes. We show that processes of cellular diversification correlate closely to endogenous ones, irrespective of metabolic state, empowering the use of this atlas to study human fate specification. We define longitudinal molecular trajectories of cortical cell types during organoid development, identify genes with predicted human-specific roles in lineage establishment, and uncover early transcriptional diversity of human callosal neurons. The findings validate this comprehensive atlas of human corticogenesis in vitro as a resource to prime investigation into the mechanisms of human cortical development.

The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of aging-related genes, pathways and ligand-receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell-type specific manner, even at times in opposite directions. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets (accessible online at https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain ) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.

Experimental models of the human brain are needed for basic understanding of its development and disease1. Human brain organoids hold unprecedented promise for this purpose; however, they are plagued by high organoid-to-organoid variability2,3. This has raised doubts as to whether developmental processes of the human brain can occur outside the context of embryogenesis with a degree of reproducibility that is comparable to the endogenous tissue. Here we show that an organoid model of the dorsal forebrain can reliably generate a rich diversity of cell types appropriate for the human cerebral cortex. We performed single-cell RNA-sequencing analysis of 166,242 cells isolated from 21 individual organoids, finding that 95% of the organoids generate a virtually indistinguishable compendium of cell types, following similar developmental trajectories and with a degree of organoid-to-organoid variability comparable to that of individual endogenous brains. Furthermore, organoids derived from different stem cell lines show consistent reproducibility in the cell types produced. The data demonstrate that reproducible development of the complex cellular diversity of the central nervous system does not require the context of the embryo, and that establishment of terminal cell identity is a highly constrained process that can emerge from diverse stem cell origins and growth environments.

Mutations in non-coding cis-regulatory DNA sequences can alter gene expression, organismal phenotype, and fitness. Fitness landscapes, which map DNA sequence to organismal fitness, are a long-standing goal in biology, but have remained elusive because it is challenging to generalize accurately to the vast space of possible sequences using models built on measurements from a limited number of endogenous regulatory sequences. Here, we construct a sequence-to-expression model for such a landscape and use it to decipher principles of cis-regulatory evolution. Using tens of millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Sacccharomyces cerevisiae, we construct a deep transformer neural network model that generalizes with exceptional accuracy, and enables sequence design for gene expression engineering. Using our model, we predict and experimentally validate expression divergence under random genetic drift and strong selection weak mutation regimes, show that conflicting expression objectives in different environments constrain expression adaptation, and find that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for detecting selective constraint on gene expression using our model and natural sequence variation, and validate it using observed cis-regulatory diversity across 1,011 yeast strains, cross-species RNA-seq from three different clades, and measured expression-to-fitness curves. Finally, we develop a characterization of regulatory evolvability, use it to visualize fitness landscapes in two dimensions, discover evolvability archetypes, quantify the mutational robustness of individual sequences and highlight the mutational robustness of extant natural regulatory sequence populations. Our work provides a general framework that addresses key questions in the evolution of cis-regulatory sequences.

BackgroundMany neurodegenerative diseases (NDs) develop only later in life, when cells in the nervous system lose their structure or function. In genetic forms of NDs, this late onset phenomenon remains largely unexplained.ResultsAnalyzing single cell RNA sequencing (scRNA-seq) from Alzheimer’s disease (AD) patients, we find increased transcriptional heterogeneity in AD excitatory neurons. We hypothesized that transcriptional heterogeneity precedes ND pathologies. To test this idea experimentally, we used juvenile forms (72Q; 180Q) of Huntington’s disease (HD) iPSCs, differentiated them into committed neuronal progenitors, and obtained single cell expression profiles. We show a global increase in gene expression variability in HD. Autophagy genes become more stable, while energy and actin-related genes become more variable in the mutant cells. Knocking-down several differentially-variable genes resulted in increased aggregate formation, a pathology associated with HD. We further validated the increased transcriptional heterogeneity in CHD8+/- cells, a model for autism spectrum disorder.ConclusionsOverall, our results suggest that although NDs develop over time, transcriptional regulation imbalance is present already at very early developmental stages. Therefore, an intervention aimed at this early phenotype may be of high diagnostic value.

Genetic risk for autism spectrum disorder (ASD) has been associated with hundreds of genes spanning a wide range of biological functions. The phenotypic alterations in the human brain resulting from mutations in ASD risk genes remain unclear, and the level at which these alterations converge on shared disease pathology is poorly understood. Here, we leveraged reproducible organoid models of the human cerebral cortex to identify cell type-specific developmental abnormalities associated with haploinsufficiency in three ASD risk genes,SUV420H1(KMT5B),PTEN, andCHD8. We performed comprehensive single-cell RNA-sequencing (scRNA-seq) of over 400,000 cells, and proteomic analysis on individual organoids sampled at different developmental stages to investigate phenotypic convergence among these genes. We find that within a defined period of early cortical development, each of the three mutations demonstrates accelerated development of cortical neurons. Notably, they do so by affecting different neuronal populations: excitatory deep layer (SUV420H1) and callosal (PTEN) neurons, and inhibitory interneurons (CHD8). This work shows that haploinsufficiency in ASD risk genes converge on early developmental defects in the generation of neurons of the cortical microcircuit.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and are being used to compile cell atlases of tissues, organs and organisms. However, the protocols differ substantially with respect to their RNA capture efficiency, bias, scale and costs, and their relative advantages for different applications are unclear. In the present study, we generated benchmark datasets to systematically evaluate protocols in terms of their power to comprehensively describe cell types and states. We performed a multicenter study comparing 13 commonly used scRNA-seq and single-nucleus RNA-seq protocols applied to a heterogeneous reference sample resource. Comparative analysis revealed marked differences in protocol performance. The protocols differed in library complexity and their ability to detect cell-type markers, impacting their predictive value and suitability for integration into reference cell atlases. These results provide guidance both for individual researchers and for consortium projects such as the Human Cell Atlas. This project has been made possible in part by grant no. 2018-182827 from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation. H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII). C.M. is supported by an AECC postdoctoral fellowship. This work has received funding from the European Union’s Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. H2020-MSCA-ITN-2015-675752 (Singek), and the Ministerio de Ciencia, Innovación y Universidades (SAF2017-89109-P; AEI/FEDER, UE). S. was supported by the German Research Foundation’s (DFG’s) (GR4980) Behrens-Weise-Foundation. C.Z. was supported by the European Molecular Biology Organization through the long-term fellowship ALTF 673-2017. The snRNA-seq data were generated with support from the National Institute of Allergy and Infectious Diseases (grant no. U24AI118672), I.N. was supported by JST CREST (grant no. JPMJCR16G3) , Japan. A.J., L.E.W., J.W.B. and W.E. were supported by funding from the DFG (EN 1093/2-1 and SFB1243 TP A14). This publication is part of a project (BCLLATLAS) that received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 810287). Core funding was from the ISCIII and the Generalitat de Catalunya

© 2019 Elsevier Inc. Neuronal types in the central nervous system differ dramatically in their resilience to injury or other insults. Here we studied the selective resilience of mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC), which severs their axons and leads to death of ∼80% of RGCs within 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 46 RGC types in adult retina. We then tracked their survival after ONC; characterized transcriptomic, physiological, and morphological changes that preceded degeneration; and identified genes selectively expressed by each type. Finally, using loss- and gain-of-function assays in vivo, we showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury and demonstrates that differential gene expression can be used to reveal molecular targets for intervention.

SummaryNeuronal types in the central nervous system differ dramatically in their resilience to injury or insults. Here we studied the selective resilience of mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC), which severs their axons and leads to death of ~80% of RGCs within 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 46 RGC types in adult retina. We then tracked their survival after ONC, characterized transcriptomic, physiological, and morphological changes that preceded degeneration, and identified genes selectively expressed by each type. Finally, using loss- and gain-of-function assays in vivo, we showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury, and demonstrates that differential gene expression can be used to reveal molecular targets for intervention.

A multitude of single-cell RNA sequencing methods have been developed in recent years, with dramatic advances in scale and power, and enabling major discoveries and large scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single cell and/or single nucleus profiling from three types of samples – cell lines, peripheral blood mononuclear cells and brain tissue – generating 36 libraries in six separate experiments in a single center. To analyze these datasets, we developed and applied scumi, a flexible computational pipeline that can be used for any scRNA-seq method. We evaluated the methods for both basic performance and for their ability to recover known biological information in the samples. Our study will help guide experiments with the methods in this study as well as serve as a benchmark for future studies and for computational algorithm development.

The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how the brain is affected with aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide a comprehensive dataset of aging-related genes, pathways and ligand-receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell type specific manner, even at times in opposite directions. Thus, our data reveals that aging, rather than inducing a universal program drives a distinct transcriptional course in each cell population. These data provide an important resource for the aging community and highlight key molecular processes, including ribosomal biogenesis, underlying aging. We believe that this large-scale dataset, which is publicly accessible online (aging-mouse-brain), will facilitate additional discoveries directed towards understanding and modifying the aging process.

The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of aging-related genes, pathways and ligand-receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell-type specific manner, even at times in opposite directions. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets (accessible online at https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain ) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.

The contribution and mechanism of cerebrovascular pathology in Alzheimer's disease (AD) pathogenesis are still unclear. Here, we show that venular and capillary cerebral endothelial cells (ECs) are selectively vulnerable to necroptosis in AD. We identify reduced cerebromicrovascular expression of murine N-acetyltransferase 1 (mNat1) in two AD mouse models and hNat2, the human ortholog of mNat1 and a genetic risk factor for type-2 diabetes and insulin resistance, in human AD. mNat1 deficiency in Nat1-/- mice and two AD mouse models promotes blood-brain barrier (BBB) damage and endothelial necroptosis. Decreased mNat1 expression induces lysosomal degradation of A20, an important regulator of necroptosis, and LRP1β, a key component of LRP1 complex that exports Aβ in cerebral ECs. Selective restoration of cerebral EC expression of mNAT1 delivered by adeno-associated virus (AAV) rescues cerebromicrovascular levels of A20 and LRP1β, inhibits endothelial necroptosis and activation, ameliorates mitochondrial fragmentation, reduces Aβ deposits, and improves cognitive function in the AD mouse model. Published version

Magnaporthaceae is a family of ascomycetes that includes three fungi of great economic importance: Magnaporthe oryzae, Gaeumannomyces graminis var. tritici, and Magnaporthe poae. These three fungi cause widespread disease and loss in cereal and grass crops, including rice blast disease (M. oryzae), take-all disease in wheat and other grasses (G. graminis), and summer patch disease in turf grasses (M. poae). Here, we present the finished genome sequence for M. oryzae and draft sequences for M. poae and G. graminis var. tritici. We used multiple technologies to sequence and annotate the genomes of M. oryzae, M. poae, and G. graminis var. tritici. The M. oryzae genome is now finished to seven chromosomes whereas M. poae and G. graminis var. tritici are sequenced to 40.0× and 25.0× coverage respectively. Gene models were developed by the use of multiple computational techniques and further supported by RNAseq data. In addition, we performed preliminary analysis of genome architecture and repetitive element DNA.

RNA-Seq is an effective method to study the transcriptome, but specialized methods are required to identify 5’ ends of transcripts. Several published strategies exist for this specific purpose, but their relative merits have not been systematically analyzed. Here, we directly compare the performance of six such methods – testing five with cellular RNA as well as a novel spike-in RNA assay that helps address interpretation challenges that arise from uncertainties in annotation or RNA processing. Using a single human RNA sample, we constructed and sequenced 18 libraries with these methods and one standard, control RNA-Seq library. We find that the CAGE method performed best for mRNA and that most of its unannotated peaks are supported by evidence from other genomic methods. We then applied CAGE to eight brain-related samples and revealed sample-specific transcription start site (TSS) usage as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

Dysfunction of microglia is known to play an important role in Alzheimer’s disease (AD). Here, we investigated the role of RIPK1 in microglia mediating the pathogenesis of AD. RIPK1 is highly expressed by microglial cells in human AD brains. Using the amyloid precursor protein (APP)/presenilin 1 (PS1) transgenic mouse model, we found that inhibition of RIPK1, using both pharmacological and genetic means, reduced amyloid burden, the levels of inflammatory cytokines, and memory deficits. Furthermore, inhibition of RIPK1 promoted microglial degradation of Aβ in vitro. We characterized the transcriptional profiles of adult microglia from APP/PS1 mice and identified a role for RIPK1 in regulating the microglial expression of CH25H and Cst7, a marker for disease-associated microglia (DAM), which encodes an endosomal/lysosomal cathepsin inhibitor named Cystatin F. We present evidence that RIPK1-mediated induction of Cst7 leads to an impairment in the lysosomal pathway. These data suggest that RIPK1 may mediate a critical checkpoint in the transition to the DAM state. Together, our study highlights a non-cell death mechanism by which the activation of RIPK1 mediates the induction of a DAM phenotype, including an inflammatory response and a reduction in phagocytic activity, and connects RIPK1-mediated transcription in microglia to the etiology of AD. Our results support that RIPK1 is an important therapeutic target for the treatment of AD.

The original version of this paper contained an incorrect primer sequence. In the Methods subsection “Rampage libraries,” the text for modification 3 stated that the reverse primer used for library indexing was 5′-CAAGCAGAAGACGGCATACGAGATXXXXXXXXGTGACTGGAGT-3′. The correct sequence of the oligonucleotide used is 5′-CAAGCAGAAGACGGCATACGAGATXXXXXXXXGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT-3′. This error has been corrected in the PDF and HTML versions of the paper.

Recent molecular studies have revealed that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels, and phenotypic output 1–5 , with important functional consequences 4,5 . Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs 1,2 or proteins 5,6 simultaneously because genomic profiling methods 3 could not be applied to single cells until very recently 7–10 . Here, we use single-cell RNA-Seq to investigate heterogeneity in the response of bone marrow derived dendritic cells (BMDCs) to lipopolysaccharide (LPS). We find extensive, and previously unobserved, bimodal variation in mRNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization (RNA-FISH) for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.

Three members of the Puccinia genus, Puccinia triticina (Pt), P. striiformis f.sp. tritici (Pst), and P. graminis f.sp. tritici (Pgt), cause the most common and often most significant foliar diseases of wheat. While similar in biology and life cycle, each species is uniquely adapted and specialized. The genomes of Pt and Pst were sequenced and compared to that of Pgt to identify common and distinguishing gene content, to determine gene variation among wheat rust pathogens, other rust fungi, and basidiomycetes, and to identify genes of significance for infection. Pt had the largest genome of the three, estimated at 135 Mb with expansion due to mobile elements and repeats encompassing 50.9% of contig bases; in comparison, repeats occupy 31.5% for Pst and 36.5% for Pgt. We find all three genomes are highly heterozygous, with Pst [5.97 single nucleotide polymorphisms (SNPs)/kb] nearly twice the level detected in Pt (2.57 SNPs/kb) and that previously reported for Pgt. Of 1358 predicted effectors in Pt, 784 were found expressed across diverse life cycle stages including the sexual stage. Comparison to related fungi highlighted the expansion of gene families involved in transcriptional regulation and nucleotide binding, protein modification, and carbohydrate degradation enzymes. Two allelic homeodomain pairs, HD1 and HD2, were identified in each dikaryotic Puccinia species along with three pheromone receptor (STE3) mating-type genes, two of which are likely representing allelic specificities. The HD proteins were active in a heterologous Ustilago maydis mating assay and host-induced gene silencing (HIGS) of the HD and STE3 alleles reduced wheat host infection., Supplemental files are available on the publisher's website

Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.

Summary Aging is a major risk factor for both genetic and sporadic neurodegenerative disorders. However, it is unclear how aging interacts with genetic predispositions to promote neurodegeneration. Here, we investigate how partial loss of function of TBK1, a major genetic cause for amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) comorbidity, leads to age-dependent neurodegeneration. We show that TBK1 is an endogenous inhibitor of RIPK1 and the embryonic lethality of Tbk1−/− mice is dependent on RIPK1 kinase activity. In aging human brains, another endogenous RIPK1 inhibitor, TAK1, exhibits a marked decrease in expression. We show that in Tbk1+/− mice, the reduced myeloid TAK1 expression promotes all the key hallmarks of ALS/FTD, including neuroinflammation, TDP-43 aggregation, axonal degeneration, neuronal loss, and behavior deficits, which are blocked upon inhibition of RIPK1. Thus, aging facilitates RIPK1 activation by reducing TAK1 expression, which cooperates with genetic risk factors to promote the onset of ALS/FTD.

available in PMC 2010 November 2., RNA-Seq provides an unbiased way to study a transcriptome, including both coding and noncoding genes. To date, most RNA-Seq studies have critically depended on existing annotations, and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We apply it to mouse embryonic stem cells, neuronal precursor cells, and lung fibroblasts to accurately reconstruct the full-length gene structures for the vast majority of known expressed genes. We identify substantial variation in protein-coding genes, including thousands of novel 5′-start sites, 3′-ends, and internal coding exons. We then determine the gene structures of over a thousand lincRNA and antisense loci. Our results open the way to direct experimental manipulation of thousands of non-coding RNAs, and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes., Merkin Family Foundation for Stem Cell Research, Howard Hughes Medical Institute, National Human Genome Research Institute (U.S.), Burroughs Wellcome Fund, Broad Institute

OBJECTIVE—Individuals with type 2 diabetes exhibit higher DNA damage and increased risk of cardiovascular disease (CVD). However, mechanisms underlying the association between DNA damage and development of type 2 diabetes and CVD are not understood. We sought to link peroxisome proliferator–activated receptor-γ coactivator-1 α (PPARGC1A), a master transcriptional regulator of mitochondrial oxidative phosphorylation and cellular energy metabolism, with DNA damage, type 2 diabetes, and CVD. RESEARCH DESIGN AND METHODS—We measured DNA damage as urinary 8-hydroxydeoxyguanosine (8-OHdG) concentration and examined the relationship between nine PPARGC1A genetic variants, DNA damage, type 2 diabetes, and self-reported CVD in 959 participants of the Boston Puerto Rican Health Study. RESULTS—With respect to urinary 8-OHdG, PPARGC1A variants showed significant association, and PPARGC1A haplotypes exhibited significant association after correction for multiple testing. Two independent PPARGC1A variants associated significantly with type 2 diabetes (odds ratios [ORs] 1.35 and 2.46; P = 0.045 and CONCLUSIONS—It is plausible that low physical activity combined with risk haplotyes contribute to the high prevalence of type 2 diabetes in this population. We propose that PPARGC1A influences development of type 2 diabetes and CVD via DNA damage. Increasing physical activity, which induces PPARGC1A expression, is a potential strategy to slow DNA damage, thereby decreasing the risk of CVD for individuals with type 2 diabetes.

Background— Apolipoprotein A5 gene ( APOA5 ) variation is associated with plasma triglycerides (TGs). However, little is known about whether dietary fat modulates this association. Methods and Results— We investigated the interaction between APOA5 gene variation and dietary fat in determining plasma fasting TGs, remnant-like particle (RLP) concentrations, and lipoprotein particle size in 1001 men and 1147 women who were Framingham Heart Study participants. Polymorphisms −1131T>C and 56C>G, representing 2 independent haplotypes, were analyzed. Significant gene–diet interactions between the −1131T>C polymorphism and polyunsaturated fatty acid (PUFA) intake were found ( P G polymorphism. The −1131C allele was associated with higher fasting TGs and RLP concentrations ( P 6% of total energy). No heterogeneity by sex was found. These interactions showed a dose-response effect when PUFA intake was considered as a continuous variable ( P P Conclusions— Higher n-6 (but not n-3) PUFA intake increased fasting TGs, RLP concentrations, and VLDL size and decreased LDL size in APOA5 −1131C carriers, suggesting that n-6 PUFA–rich diets are related to a more atherogenic lipid profile in these subjects.

To determine whether APOC3 and APOA4 genotypes influence plasma cholesterol fluctuations following a high cholesterol diet, a healthy population of 40 men and 51 women were studied. The crossover intervention randomly assigned participants to an EGG (640 mg/d cholesterol) or placebo (0 mg/d cholesterol) diet for 30 days, with a 3-week washout between periods. Allele-specific oligonucleotide hybridization was utilized to determine the presence or absence of APOC3 and APOA4 polymorphisms. Differences in plasma cholesterol between hyper- and hypo-responders were not influenced by genotype. However, an interaction (P0.0001) did exist between APOA4 allele, diet and gender with regard to triglycerides (TG). While female carriers of the APOA4(347) S allele had lower TG concentrations than those with the common T/T allele, males with the S allele had higher concentrations. The APOC3 SstI polymorphism analysis revealed that heterozygous carriers of the S2 allele had higher (P0.05) plasma apo C-III and TG concentrations, regardless of gender or dietary period. In addition, carriers of the S2 allele had smaller LDL peak particle diameter than those having the common APOC3 genotype. The presence of individual alleles in this population was associated with differences in plasma lipids and LDL size. However, these relationships were independent of dietary cholesterol.

High density lipoprotein cholesterol (HDL-C) is inversely associated with coronary heart disease and has a genetic component; however, linkage to HDL-C is not conclusive. Subfractions of HDL, such as HDL(3)-C, may be better phenotypes for linkage studies. Using HDL(3)-C levels measured on 907 Framingham Heart Study subjects from 330 families around 1987, we conducted a genome-wide variance components linkage analysis with 401 microsatellite markers spaced approximately 10 centimorgan (cM) apart. Nine candidate genes were identified and annotated using a bioinformatics approach in the region of the highest linkage peak. Twenty-eight single nucleotide polymorphisms (SNPs) were selected from these candidate genes, and linkage and family-based association fine mapping were conducted using these SNPs. The highest multipoint log-of-the-odds (LOD) score from the initial linkage analysis was 3.7 at 133 cM on chromosome 6. Linkage analyses with additional SNPs yielded the highest LOD score of 4.0 at 129 cM on chromosome 6. Family-based association analysis revealed that SNP rs2257104 in PLAGL1 at approximately 143 cM was associated with multivariable adjusted HDL(3) (P = 0.03). Further study of the linkage region and exploration of other variants in PLAGL1 are warranted to define the potential functional variants of HDL-C metabolism.

Several polymorphisms in the APOA5 gene have been associated with increased plasma triglyceride (TG) concentrations. However, associations between APOA5 and lipoprotein subclasses, remnant-like particles (RLPs), and cardiovascular disease (CVD) risk have been less explored. We investigated associations of five APOA5 single-nucleotide polymorphisms (SNPs; −1131T>C, −3A>G, 56C>G IVS3+ 476G>A, and 1259T>C) with lipoprotein subfractions and CVD risk in 1,129 men and 1,262 women participating in the Framingham Heart Study. Except for the 56C>G SNP, the other SNPs were in significant linkage disequilibria, resulting in three haplotypes (11111, 22122, and 11211) representing 98% of the population. SNP analyses revealed that the −1131T>C and 56C>G SNPs were significantly associated with higher plasma TG concentrations in both men and women. For RLP and lipoprotein subclasses, we observed gender-specific association for the −1131T>C and 56C>G SNPs. Female carriers of the −1131C allele had higher RLP concentrations, whereas in males, significant associations for RLPs were observed for the 56G allele. Moreover, haplotype analyses confirmed these findings and revealed that the 22122 and 11211 haplotypes exhibited different associations with HDL cholesterol concentrations. In women, the −1131C allele was associated with a higher hazard ratio for CVD (1.85; 95% confidence interval, 1.03−3.34; P = 0.04), in agreement with the association of this SNP with higher RLPs.

Singapore comprises three ethnic groups: Chinese (76.7%), Malays (14%), and Asian-Indians (7.9%). Overall, Singaporeans experience coronary heart disease rates similar to those found in the United States. However, there is a dramatic interethnic gradient, with Asian-Indians having significantly higher risk than Chinese and Malays. These differences are associated with HDL cholesterol levels and cannot be solely explained by environmental exposure, and may be driven by genetic factors. The gene encoding apolipoprotein A-V (APOA5) has been located on chromosome 11, and it is emerging as an important candidate gene for lipoprotein metabolism. We investigated associations between APOA5 polymorphisms and plasma lipids in 3,971 Singaporeans to establish whether they accounted for some of the ethnic differences in plasma lipids. We found significant associations between the minor alleles at each of four common polymorphisms and higher plasma triglycerides (TGs) across ethnic groups. Haplotype analyses showed significant associations with TGs, explaining 6.9%, 5.2%, and 2.7% of the TG variance in Malays, Asian-Indians, and Chinese, respectively. Conversely, we observed significant inverse associations between the minor alleles and HDL cholesterol concentrations for Chinese and Malays. These data suggest that APOA5 plays a role in the ethnic differences observed for plasma TG and HDL cholesterol concentrations.

The Singapore population comprises Chinese, Malays and Asian Indians. Within this population, Asian Indians have the highest rates of coronary heart disease, whereas Chinese have the lowest. Conversely, Indians have the lowest high-density lipoprotein cholesterol (HDL-C) concentrations, followed by Malays and Chinese. We studied the TaqIB and -629C>A polymorphisms at the CETP locus in 1300 Chinese, 364 Malay and 282 Asian Indian men, and in 1558 Chinese, 397 Malay and 306 Asian Indian women, to determine whether these polymorphisms are responsible for the ethnic difference in HDL-C concentration. The frequency of the B2 allele in Chinese, Malays and Indians was 0.384, 0.339 and 0.449 in men, and 0.379, 0.329 and 0.415 in women, respectively (p < 0.001). For the A-629 allele, the relative frequencies were 0.477, 0.423 and 0.592 in men and 0.486, 0.416 and 0.575 in women (p < 0.001). The two polymorphisms were in linkage disequilibrium (D / Dmax= 0.9772, p < 0.00001). The B2 and the A-629 alleles were associated with increased HDL-C concentrations in a dose-dependent manner. The B2 allele continued to show an association with HDL-C concentration, even after controlling for the genotype at position -629. Dietary cholesterol showed a significant interaction with the TaqIB polymorphism in determining HDL-C concentrations in Indians and Malays, but not in Chinese. In conclusion, the high frequencies of these polymorphisms in Asian Indians could not explain the observed ethnic differences in HDL-C concentration. Moreover, we observed an ethnic-specific interaction among dietary cholesterol, the TaqIB polymorphism and HDL-C concentrations.