Mingfeng Li

Dr. Mingfeng Li

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Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 December 2018 in Science
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MLMingfeng Li
Mingfeng Li
Gabriel SantpereGabriel Santpere
Gabriel Santpere
YKYuka Imamura Kawasawa
Yuka Imamura Kawasawa
OEOleg V. Evgrafov
Oleg V. Evgrafov
FGForrest O. Gulden
Forrest O. Gulden
NSNenad Sestan
Nenad Sestan
INTRODUCTION: The brain is responsible for cognition, behavior, and much of what makes us uniquely human. The development of the brain is a highly complex process, and this process is reliant on precise regulation of molecular and cellular events grounded in the spatiotemporal regulation of the transcriptome. Disruption of this regulation can lead to neuropsychiatric disorders.RATIONALE: The regulatory, epigenomic, and transcriptomic features of the human brain have not been comprehensively compiled across time, regions, or cell types. Understanding the etiology of neuropsychiatric disorders requires knowledge not just of endpoint differences between healthy and diseased brains but also of the developmental and cellular contexts in which these differences arise. Moreover, an emerging body of research indicates that many aspects of the development and physiology of the human brain are not well recapitulated in model organisms, and therefore it is necessary that neuropsychiatric disorders be understood in the broader context of the developing and adult human brain.RESULTS: Here we describe the generation and analysis of a variety of genomic data modalities at the tissue and single-cell levels, including transcriptome, DNA methylation, and histone modifications across multiple brain regions ranging in age from embryonic development through adulthood. We observed a widespread transcriptomic transition beginning during late fetal development and consisting of sharply decreased regional differences. This reduction coincided with increases in the transcriptional signatures of mature neurons and the expression of genes associated with dendrite development, synapse development, and neuronal activity, all of which were temporally synchronous across neocortical areas, as well as myelination and oligodendrocytes, which were asynchronous. Moreover, genes includingMEF2C,SATB2, andTCF4,with genetic associations to multiple brain-related traits and disorders, converged in a small number of modules exhibiting spatial or spatiotemporal specificity.CONCLUSION: We generated and applied our dataset to document transcriptomic and epigenetic changes across human development and then related those changes to major neuropsychiatric disorders. These data allowed us to identify genes, cell types, gene coexpression modules, and spatiotemporal loci where disease risk might converge, demonstrating the utility of the dataset and providing new insights into human development and disease. Spatiotemporal dynamics of human brain development and neuropsychiatric risks.: Human brain development begins during embryonic development and continues through adulthood (top). Integrating data modalities (bottom left) revealed age- and cell type–specific properties and global patterns of transcriptional dynamics, including a late fetal transition (bottom middle). We related the variation in gene expression (brown, high; purple, low) to regulatory elements in the fetal and adult brains, cell type–specific signatures, and genetic loci associated with neuropsychiatric disorders (bottom right; gray circles indicate enrichment for corresponding features among module genes). Relationships depicted in this panel do not correspond to specific observations. CBC, cerebellar cortex; STR, striatum; HIP, hippocampus; MD, mediodorsal nucleus of thalamus; AMY, amygdala.

14 December 2018 in Science
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Journal Article
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YZYing Zhu
Ying Zhu
ASAndré M. M. Sousa
André M. M. Sousa
TGTianliuyun Gao
Tianliuyun Gao
MSMario Skarica
Mario Skarica
MLMingfeng Li
Mingfeng Li
NSNenad Sestan
Nenad Sestan
INTRODUCTION: Improved understanding of how the developing human nervous system differs from that of closely related nonhuman primates is fundamental for teasing out human-specific aspects of behavior, cognition, and disorders. RATIONALE: The shared and unique functional properties of the human nervous system are rooted in the complex transcriptional programs governing the development of distinct cell types, neural circuits, and regions. However, the precise molecular mechanisms underlying shared and unique features of the developing human nervous system have been only minimally characterized. RESULTS: We generated complementary tissue-level and single-cell transcriptomic datasets from up to 16 brain regions covering prenatal and postnatal development in humans and rhesus macaques ( Macaca mulatta ), a closely related species and the most commonly studied nonhuman primate. We created and applied TranscriptomeAge and TempShift algorithms to age-match developing specimens between the species and to more rigorously identify temporal differences in gene expression within and across the species. By analyzing regional and temporal patterns of gene expression in both the developing human and macaque brain, and comparing these patterns to a complementary dataset that included transcriptomic information from the adult chimpanzee, we identified shared and divergent transcriptomic features of human brain development. Furthermore, integration with single-cell and single-nucleus transcriptomic data covering prenatal and adult periods of both species revealed that the developmental divergence between humans and macaques can be traced to distinct cell types enriched in different developmental times and brain regions, including the prefrontal cortex, a region of the brain associated with distinctly human aspects of cognition and behavior. We found two phases of prominent species differences: embryonic to late midfetal development and adolescence/young adulthood. This evolutionary cup-shaped or hourglass-like pattern, with high divergence in prenatal development and adolescence/young adulthood and lower divergence in early postnatal development, resembles the developmental cup-shaped pattern described in the accompanying study by Li et al . Even though the developmental (ontogenetic) and evolutionary (phylogenetic) patterns have similar profiles, the overlap of genes driving these two patterns is not substantial, indicating the existence of different molecular mechanisms and constraints for regional specification and species divergence. Notably, we also identified numerous genes and gene coexpression modules exhibiting human-distinct patterns in either temporal (heterochronic) or spatial (heterotopic) gene expression, as well as genes with human-distinct developmental expression, linked to autism spectrum disorder, schizophrenia, and other neurological or psychiatric diseases. This finding potentially suggests mechanistic underpinnings of these disorders. CONCLUSION: Our study provides insights into the evolution of gene expression in the developing human brain and may shed some light on potentially human-specific underpinnings of certain neuropsychiatric disorders. Concerted ontogenetic and phylogenetic transcriptomic divergence in human and macaque brain.: Left: Human and macaque brain regions spanning both prenatal and postnatal development were age-matched using TranscriptomeAge. Right: Phylogenetic transcriptomic divergence between humans and macaques resembles the developmental (ontogenetic) cup-shaped pattern of each species, with high divergence in prenatal development and adolescence/young adulthood and lower divergence during the early postnatal period (from perinatal to adolescence). Single-cell transcriptomics revealed shared and divergent transcriptomic features of distinct cell types.

6 March 2014 in Molecular Autism
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LLLi Liu
Li Liu
JLJing Lei
Jing Lei
JSJan Stefan Sanders
Jan Stefan Sanders
AWArthur Jeremy Willsey
Arthur Jeremy Willsey
YKYan Kou
Yan Kou
KRKathryn Roeder
Kathryn Roeder
De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes. To accelerate the search for ASD genes, we developed a novel algorithm, DAWN, to model two kinds of data: rare variations from exome sequencing and gene co-expression in the mid-fetal prefrontal and motor-somatosensory neocortex, a critical nexus for risk. The algorithm casts the ensemble data as a hidden Markov random field in which the graph structure is determined by gene co-expression and it combines these interrelationships with node-specific observations, namely gene identity, expression, genetic data and the estimated effect on risk. Using currently available genetic data and a specific developmental time period for gene co-expression, DAWN identified 127 genes that plausibly affect risk, and a set of likely ASD subnetworks. Validation experiments making use of published targeted resequencing results demonstrate its efficacy in reliably predicting ASD genes. DAWN also successfully predicts known ASD genes, not included in the genetic data used to create the model. Validation studies demonstrate that DAWN is effective in predicting ASD genes and subnetworks by leveraging genetic and gene expression data. The findings reported here implicate neurite extension and neuronal arborization as risks for ASD. Using DAWN on emerging ASD sequence data and gene expression data from other brain regions and tissues would likely identify novel ASD genes. DAWN can also be used for other complex disorders to identify genes and subnetworks in those disorders.

5 March 2024 in Journal of Experimental Medicine
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LBLigia Simoes Braga Boisserand
Ligia Simoes Braga Boisserand
LGLuiz Henrique Geraldo
Luiz Henrique Geraldo
JBJean Bouchart
Jean Bouchart
MKMarie-Renee El Kamouh
Marie-Renee El Kamouh
SLSeyoung Lee
Seyoung Lee
JTJean-Leon Thomas
Jean-Leon Thomas
Meningeal lymphatic vessels (MLVs) promote tissue clearance and immune surveillance in the central nervous system (CNS). Vascular endothelial growth factor-C (VEGF-C) regulates MLV development and maintenance and has therapeutic potential for treating neurological disorders. Herein, we investigated the effects of VEGF-C overexpression on brain fluid drainage and ischemic stroke outcomes in mice. Intracerebrospinal administration of an adeno-associated virus expressing mouse full-length VEGF-C (AAV-mVEGF-C) increased CSF drainage to the deep cervical lymph nodes (dCLNs) by enhancing lymphatic growth and upregulated neuroprotective signaling pathways identified by single nuclei RNA sequencing of brain cells. In a mouse model of ischemic stroke, AAV-mVEGF-C pretreatment reduced stroke injury and ameliorated motor performances in the subacute stage, associated with mitigated microglia-mediated inflammation and increased BDNF signaling in brain cells. Neuroprotective effects of VEGF-C were lost upon cauterization of the dCLN afferent lymphatics and not mimicked by acute post-stroke VEGF-C injection. We conclude that VEGF-C prophylaxis promotes multiple vascular, immune, and neural responses that culminate in a protection against neurological damage in acute ischemic stroke.

3 August 2022 in Nature
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DADavid Andrijevic
David Andrijevic
ZVZvonimir Vrselja
Zvonimir Vrselja
TLTaras Lysyy
Taras Lysyy
SZShupei Zhang
Shupei Zhang
MSMario Skarica
Mario Skarica
NSNenad Sestan
Nenad Sestan

4 April 2022 in Nature Neuroscience
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PDPhan Q. Duy
Phan Q. Duy
SWStefan C. Weise
Stefan C. Weise
CMClaudia Marini
Claudia Marini
XLXiao-Jun Li
Xiao-Jun Li
DLDan Liang
Dan Liang
Kristopher T. KahleKristopher T. Kahle
Kristopher T. Kahle