Neuroscience

2021
Sherman MA, Rodin RE, Genovese G, Dias C, Barton AR, Mukamel RE, Berger B, Park PJ**, Walsh CA**, Loh P-R**. Large mosaic copy number variations confer autism risk. Nat Neurosci 2021;24(2):197-203.Abstract
Although germline de novo copy number variants (CNVs) are known causes of autism spectrum disorder (ASD), the contribution of mosaic (early-developmental) copy number variants (mCNVs) has not been explored. In this study, we assessed the contribution of mCNVs to ASD by ascertaining mCNVs in genotype array intensity data from 12,077 probands with ASD and 5,500 unaffected siblings. We detected 46 mCNVs in probands and 19 mCNVs in siblings, affecting 2.8-73.8% of cells. Probands carried a significant burden of large (>4-Mb) mCNVs, which were detected in 25 probands but only one sibling (odds ratio = 11.4, 95% confidence interval = 1.5-84.2, P = 7.4 × 10). Event size positively correlated with severity of ASD symptoms (P = 0.016). Surprisingly, we did not observe mosaic analogues of the short de novo CNVs recurrently observed in ASD (eg, 16p11.2). We further experimentally validated two mCNVs in postmortem brain tissue from 59 additional probands. These results indicate that mCNVs contribute a previously unexplained component of ASD risk.
2020
Dou Y, Kwon M, Rodin RE, Cortés-Ciriano I, Doan R, J. Luquette L, Galor A, Bohrson C, Walsh CA, Park PJ. Accurate detection of mosaic variants in sequencing data without matched controls [Internet]. Nature Biotechnology 2020;38(3):314-319. Publisher's VersionAbstract

Detection of mosaic mutations that arise in normal development is challenging, as such mutations are typically present in only a minute fraction of cells and there is no clear matched control for removing germline variants and systematic artifacts. We present MosaicForecast, a machine-learning method that leverages read-based phasing and read-level features to accurately detect mosaic single-nucleotide variants and indels, achieving a multifold increase in specificity compared with existing algorithms. Using single-cell sequencing and targeted sequencing, we validated 80–90{\%} of the mosaic single-nucleotide variants and 60–80{\%} of indels detected in human brain whole-genome sequencing data. Our method should help elucidate the contribution of mosaic somatic mutations to the origin and development of disease.

2019
Kim J, Hu C, Moufawad El Achkar C, Black LE, Douville J, Larson A, Pendergast MK, Goldkind SF, Lee EA, Kuniholm A, Soucy A, Vaze J, Belur NR, Fredriksen K, Stojkovska I, Tsytsykova A, Armant M, DiDonato RL, Choi J, Cornelissen L, Pereira LM, Augustine EF, Genetti CA, Dies K, Barton B, Williams L, Goodlett BD, Riley BL, Pasternak A, Berry ER, Pflock KA, Chu S, Reed C, Tyndall K, Agrawal PB, Beggs AH, Grant EP, Urion DK, Snyder RO, Waisbren SE, Poduri A, Park PJ, Patterson A, Biffi A, Mazzulli JR, Bodamer O, Berde CB, Yu TW. Patient-Customized Oligonucleotide Therapy for a Rare Genetic Disease. N Engl J Med 2019;Abstract
Genome sequencing is often pivotal in the diagnosis of rare diseases, but many of these conditions lack specific treatments. We describe how molecular diagnosis of a rare, fatal neurodegenerative condition led to the rational design, testing, and manufacture of milasen, a splice-modulating antisense oligonucleotide drug tailored to a particular patient. Proof-of-concept experiments in cell lines from the patient served as the basis for launching an "N-of-1" study of milasen within 1 year after first contact with the patient. There were no serious adverse events, and treatment was associated with objective reduction in seizures (determined by electroencephalography and parental reporting). This study offers a possible template for the rapid development of patient-customized treatments. (Funded by Mila's Miracle Foundation and others.).
Bohrson CL, Barton AR, Lodato MA, Rodin RE, Luquette LJ, Viswanadham VV, Gulhan DC, Cortés-Ciriano I, Sherman MA, Kwon M, Coulter ME, Galor A, Walsh CA, Park PJ. Linked-read analysis identifies mutations in single-cell DNA-sequencing data. Nature Genetics 2019;51:749-754.Abstract
Whole-genome sequencing of DNA from single cells has the potential to reshape our understanding of mutational heterogeneity in normal and diseased tissues. However, a major difficulty is distinguishing amplification artifacts from biologically derived somatic mutations. Here, we describe linked-read analysis (LiRA), a method that accurately identifies somatic singlenucleotide variants (sSNVs) by using read-level phasing with nearby germline heterozygous polymorphisms, thereby enabling the characterization of mutational signatures and estimation of somatic mutation rates in single cells.
2018
Lodato MA*, Rodin RE*, Bohrson CL*, Coulter ME*, Barton AR*, Kwon M*, Sherman MA, Vitzthum CM, Luquette LJ, Yandava C, Yang P, Chittenden TW, Hatem NE, Ryu SC, Woodworth MB, Park PJ**, Walsh CA**. Aging and neurodegeneration are associated with increased mutations in single human neurons. Science 2018;359(6375):555-559.Abstract
It has long been hypothesized that aging and neurodegeneration are associated with somatic mutation in neurons; however, methodological hurdles have prevented testing this hypothesis directly. We used single-cell whole-genome sequencing to perform genome-wide somatic single-nucleotide variant (sSNV) identification on DNA from 161 single neurons from the prefrontal cortex and hippocampus of fifteen normal individuals (aged 4 months to 82 years) as well as nine individuals affected by early-onset neurodegeneration due to genetic disorders of DNA repair (Cockayne syndrome and Xeroderma pigmentosum). sSNVs increased approximately linearly with age in both areas (with a higher rate in hippocampus) and were more abundant in neurodegenerative disease. The accumulation of somatic mutations with age-which we term genosenium-shows age-related, region-related, and disease-related molecular signatures, and may be important in other human age-associated conditions.
Dou Y*, Gold HD*, Luquette LJ*, Park PJ. Detecting Somatic Mutations in Normal Cells. Trends in Genetics 2018;35(7):545-557.Abstract
Somatic mutations have been studied extensively in the context of cancer. Recent studies have demonstrated that high-throughput sequencing data can be used to detect somatic mutations in non-tumor cells. Analysis of such mutations allows us to better understand the mutational processes in normal cells, explore cell lineages in development, and examine potential associations with age-related disease. We describe here approaches for characterizing somatic mutations in normal and non-tumor disease tissues. We discuss several experimental designs and common pitfalls in somatic mutation detection, as well as more recent developments such as phasing and linked-read technology. With the dramatically increasing numbers of samples undergoing genome sequencing, bioinformatic analysis will enable the characterization of somatic mutations and their impact on non-cancer tissues.
Sherman MA, Barton AR, Lodato MA, Vitzthum C, Coulter ME, Walsh CA, Park PJ. PaSD-qc: quality control for single cell whole-genome sequencing data using power spectral density estimation. Nucleic Acids Research 2018;46(4):e20.Abstract
Single cell whole-genome sequencing (scWGS) is providing novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, the whole-genome amplification process required for scWGS introduces biases into the resulting sequencing that can confound downstream analysis. Here, we present a statistical method, with an accompanying package PaSD-qc (Power Spectral Density-qc), that evaluates the properties and quality of single cell libraries. It uses a modified power spectral density to assess amplification uniformity, amplicon size distribution, autocovariance and inter-sample consistency as well as to identify chromosomes with aberrant read-density profiles due either to copy alterations or poor amplification. These metrics provide a standard way to compare the quality of single cell samples as well as yield information necessary to improve variant calling strategies. We demonstrate the usefulness of this tool in comparing the properties of scWGS protocols, identifying potential chromosomal copy number variation, determining chromosomal and subchromosomal regions of poor amplification, and selecting high-quality libraries from low-coverage data for deep sequencing. The software is available free and open-source at https://github.com/parklab/PaSDqc.
2017
McConnell MJ, Moran JV, Abyzov A, Akbarian S, Bae T, Cortes-Ciriano I, Erwin JA, Fasching L, Flasch DA, Freed D, Ganz J, Jaffe AE, Kwan KY, Kwon M, Lodato MA, Mills RE, Paquola ACM, Rodin RE, Rosenbluh C, Sestan N, Sherman MA, Shin JH, Song S, Straub RE, Thorpe J, Weinberger DR, Urban AE, Zhou B, Gage FH, Lehner T, Senthil G, Walsh CA, Chess A, Courchesne E, Gleeson JG, Kidd JM, Park PJ, Pevsner J, Vaccarino FM, Brain Somatic Mosaicism Network BSM. Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. Science 2017;356(6336)Abstract

Neuropsychiatric disorders have a complex genetic architecture. Human genetic population-based studies have identified numerous heritable sequence and structural genomic variants associated with susceptibility to neuropsychiatric disease. However, these germline variants do not fully account for disease risk. During brain development, progenitor cells undergo billions of cell divisions to generate the ~80 billion neurons in the brain. The failure to accurately repair DNA damage arising during replication, transcription, and cellular metabolism amid this dramatic cellular expansion can lead to somatic mutations. Somatic mutations that alter subsets of neuronal transcriptomes and proteomes can, in turn, affect cell proliferation and survival and lead to neurodevelopmental disorders. The long life span of individual neurons and the direct relationship between neural circuits and behavior suggest that somatic mutations in small populations of neurons can significantly affect individual neurodevelopment. The Brain Somatic Mosaicism Network has been founded to study somatic mosaicism both in neurotypical human brains and in the context of complex neuropsychiatric disorders.

2016
Evrony GD*, Lee E*, Park PJ**, Walsh CA**. Resolving rates of mutation in the brain using single-neuron genomics. Elife 2016;5Abstract

Whether somatic mutations contribute functional diversity to brain cells is a long-standing question. Single-neuron genomics enables direct measurement of somatic mutation rates in human brain and promises to answer this question. A recent study (Upton et al., 2015) reported high rates of somatic LINE-1 element (L1) retrotransposition in the hippocampus and cerebral cortex that would have major implications for normal brain function, and further claimed these mutation events preferentially impact genes important for neuronal function. We identify errors in single-cell sequencing approach, bioinformatic analysis, and validation methods that led to thousands of false-positive artifacts being mistakenly interpreted as somatic mutation events. Our reanalysis of the data supports a corrected mutation frequency (0.2 per cell) more than fifty-fold lower than reported, inconsistent with the authors' conclusion of 'ubiquitous' L1 mosaicism, but consistent with L1 elements mobilizing occasionally. Through consideration of the challenges and pitfalls identified, we provide a foundation and framework for designing single-cell genomics studies.

2015
Somatic mutation in single human neurons tracks developmental and transcriptional history.
Lodato MA*, Woodworth MB*, Lee S*, Evrony GD, Mehta BK, Karger A, Lee S, Chittenden TW, D'Gama AM, Cai X, Luquette LJ, Lee E, Park PJ**, Walsh CA**. Somatic mutation in single human neurons tracks developmental and transcriptional history. Science 2015;350(6256):94-8.Abstract

Neurons live for decades in a postmitotic state, their genomes susceptible to DNA damage. Here we survey the landscape of somatic single-nucleotide variants (SNVs) in the human brain. We identified thousands of somatic SNVs by single-cell sequencing of 36 neurons from the cerebral cortex of three normal individuals. Unlike germline and cancer SNVs, which are often caused by errors in DNA replication, neuronal mutations appear to reflect damage during active transcription. Somatic mutations create nested lineage trees, allowing them to be dated relative to developmental landmarks and revealing a polyclonal architecture of the human cerebral cortex. Thus, somatic mutations in the brain represent a durable and ongoing record of neuronal life history, from development through postmitotic function.

Evrony GD*, Lee E*, Mehta BK, Benjamini Y, Johnson RM, Cai X, Yang L, Haseley P, Lehmann HS, Park PJ**, Walsh CA**. Cell lineage analysis in human brain using endogenous retroelements. Neuron 2015;85(1):49-59.Abstract

Somatic mutations occur during brain development and are increasingly implicated as a cause of neurogenetic disease. However, the patterns in which somatic mutations distribute in the human brain are unknown. We used high-coverage whole-genome sequencing of single neurons from a normal individual to identify spontaneous somatic mutations as clonal marks to track cell lineages in human brain. Somatic mutation analyses in >30 locations throughout the nervous system identified multiple lineages and sublineages of cells marked by different LINE-1 (L1) retrotransposition events and subsequent mutation of poly-A microsatellites within L1. One clone contained thousands of cells limited to the left middle frontal gyrus, whereas a second distinct clone contained millions of cells distributed over the entire left hemisphere. These patterns mirror known somatic mutation disorders of brain development and suggest that focally distributed mutations are also prevalent in normal brains. Single-cell analysis of somatic mutation enables tracing of cell lineage clones in human brain.

2014
Merlo P, Frost B, Peng S, Yang YJ, Park PJ, Feany M. p53 prevents neurodegeneration by regulating synaptic genes. Proc Natl Acad Sci U S A 2014;111(50):18055-60.Abstract

DNA damage has been implicated in neurodegenerative disorders, including Alzheimer's disease and other tauopathies, but the consequences of genotoxic stress to postmitotic neurons are poorly understood. Here we demonstrate that p53, a key mediator of the DNA damage response, plays a neuroprotective role in a Drosophila model of tauopathy. Further, through a whole-genome ChIP-chip analysis, we identify genes controlled by p53 in postmitotic neurons. We genetically validate a specific pathway, synaptic function, in p53-mediated neuroprotection. We then demonstrate that the control of synaptic genes by p53 is conserved in mammals. Collectively, our results implicate synaptic function as a central target in p53-dependent protection from neurodegeneration.

2012
Evrony GD*, Cai X*, Lee E, Hills BL, Elhosary PC, Lehmann HS, Parker JJ, Atabay KD, Gilmore EC, Poduri A, Park PJ, Walsh CA. Single-neuron sequencing analysis of L1 retrotransposition and somatic mutation in the human brain. Cell 2012;151(3):483-96.Abstract

A major unanswered question in neuroscience is whether there exists genomic variability between individual neurons of the brain, contributing to functional diversity or to an unexplained burden of neurological disease. To address this question, we developed a method to amplify genomes of single neurons from human brains. Because recent reports suggest frequent LINE-1 (L1) retrotransposition in human brains, we performed genome-wide L1 insertion profiling of 300 single neurons from cerebral cortex and caudate nucleus of three normal individuals, recovering >80% of germline insertions from single neurons. While we find somatic L1 insertions, we estimate <0.6 unique somatic insertions per neuron, and most neurons lack detectable somatic insertions, suggesting that L1 is not a major generator of neuronal diversity in cortex and caudate. We then genotyped single cortical cells to characterize the mosaicism of a somatic AKT3 mutation identified in a child with hemimegalencephaly. Single-neuron sequencing allows systematic assessment of genomic diversity in the human brain.