Biology subjects

Rodin, R. E.

Publications and source records attributed to Rodin, R. E..

4 recordsLinked to original sources

bioRxiv2020

Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq) reveals cell type-specific lineage patterns in human brain

Elucidating the lineage relationships among different cell types is key to understanding human brain development. Here we developed Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq), which combines RNA analysis of neuronal cell types with analysis of nested spontaneous DNA somatic mutations as cell lineage markers, identified from joint analysis of single cell and bulk DNA sequencing by single-cell MosaicHunter (scMH). PRDD-seq enables the first-ever simultaneous reconstruction of neuronal cell type, cell lineage, and sequential neuronal formation ("birthdate") in postmortem human cerebral cortex. Analysis of two human brains showed remarkable quantitative details that relate mutation mosaic frequency to clonal patterns, confirming an early divergence of precursors for excitatory and inhibitory neurons, and an "inside-out" layer formation of excitatory neurons as seen in other species. In addition our analysis allows the first estimate of excitatory neuron-restricted precursors (about 10) that generate the excitatory neurons within a cortical column. Inhibitory neurons showed complex, subtype-specific patterns of neurogenesis, including some patterns of development conserved relative to mouse, but also some aspects of primate cortical interneuron development not seen in mouse. PRDD-seq can be broadly applied to characterize cell identity and lineage from diverse archival samples with single-cell resolution and in potentially any developmental or disease condition. Significance StatementStem cells and progenitors undergo a series of cell divisions to generate the neurons of the brain, and understanding this sequence is critical to studying the mechanisms that control cell division and migration in developing brain. Mutations that occur as cells divide are known as the basis of cancer, but have more recently been shown to occur with normal cell divisions, creating a permanent, forensic map of the clonal patterns that define the brain. Here we develop new technology to analyze both DNA mutations and RNA gene expression patterns in single cells from human postmortem brain, allowing us to define clonal patterns among different types of human brain neurons, gaining the first direct insight into how they form.

neuroscience↗

bioRxiv2020

The Landscape of Mutational Mosaicism in Autistic and Normal Human Cerebral Cortex

Although somatic mutations have well-established roles in cancer and certain focal epilepsies, the extent to which mutational mosaicism shapes the developing human brain is poorly understood. Here we characterize the landscape of somatic mutations in the human brain using ultra-deep (~250x) whole-genome sequencing of brains from 59 autism spectrum disorder (ASD) cases and 15 controls. We observe a mean of 26 ({+/-}10, range 10-60) somatic single nucleotide variants (sSNVs) per brain present in [≥]4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This rate suggests that a typical individual possesses ~80 sSNVs present in [≥]2% of cells--comparable to the number of de novo germline mutations per generation--with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. Although limited by sample size, ASD brains show an excess of somatic mutations in neural enhancer sequences compared to controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

neuroscience↗

bioRxiv2017

Aging and neurodegeneration are associated with increased mutations in single human neurons

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.\n\nOne-Sentence SummarySomatic single-nucleotide variants accumulate in human neurons in aging with regional specificity and in progeroid diseases.

genomics↗

bioRxiv2017

Linked-read analysis identifies mutations in single-cell DNA sequencing data

Whole-genome sequencing of DNA from single cells has the potential to reshape our understanding of the mutational heterogeneity in normal and disease tissues. A major difficulty, however, is distinguishing artifactual mutations that arise from DNA isolation and amplification from true mutations. Here, we describe linked-read analysis (LiRA), a method that utilizes phasing of somatic single nucleotide variants with nearby germline variants to identify true mutations, thereby allowing accurate estimation of somatic mutation rates at the single cell level.

bioinformatics↗