Biology subjects

Bohrson, C. L.

Publications and source records attributed to Bohrson, C. L..

4 recordsLinked to original sources

bioRxiv2021

Ultraspecific somatic SNV and indel detection in single neurons using primary template-directed amplification

Primary template-directed amplification (PTA) is an improved amplification technique for single-cell DNA sequencing. We generated whole-genome analysis of 76 single neurons and developed SCAN2, a computational method to accurately identify both clonal and non-clonal somatic (i.e., limited to a single neuron) single nucleotide variants (SNVs) and small insertions and deletions (indels) using PTA data. Our analysis confirms an increase in non-clonal somatic mutation in single neurons with age, but revises estimates for the rate of this accumulation to be 15 SNVs per year. We also identify artifacts in other amplification methods. Most importantly, we show that somatic indels also increase by at least 2 indels per year per neuron and that indels may have a larger impact on gene function than somatic SNVs in human neurons.

genomics↗

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↗