Long-read sequencing of diverse brains reveals how structural variations affect gene expression and DNA methylation
Author Information
Author(s): Billingsley Kimberley J., Meredith Melissa, Daida Kensuke, Jerez Pilar Alvarez, Negi Shloka, Malik Laksh, Genner Rylee M., Moller Abraham, Zheng Xinchang, Gibson Sophia B., Mastoras Mira, Baker Breeana, Kouam Cedric, Paquette Kimberly, Jarreau Paige, Makarious Mary B., Moore Anni, Hong Samantha, Vitale Dan, Shah Syed, Monlong Jean, Pantazis Caroline B., Asri Mobin, Shafin Kishwar, Carnevali Paolo, Marenco Stefano, Auluck Pavan, Mandal Ajeet, Miga Karen H., Rhie Arang, Reed Xylena, Ding Jinhui, Cookson Mark R., Nalls Mike, Singleton Andrew, Miller Danny E., Chaisson Mark, Timp Winston, Gibbs J.Raphael, Phillippy Adam M., Kolmogorov Mikhail, Jain Miten, Sedlazeck Fritz J., Paten Benedict, Blauwendraat Cornelis
Primary Institution: Center for Alzheimer’s and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
Hypothesis
How do structural variants influence gene expression and DNA methylation in the human brain?
Conclusion
The study shows that long-read sequencing can uncover complex regulatory mechanisms in the brain that were previously inaccessible.
Supporting Evidence
- Long-read sequencing can detect more structural variants than short-read methods.
- Structural variants are linked to various neurological conditions.
- Approximately 234,905 structural variants were identified in the study.
- Significant associations were found between structural variants and gene expression.
- Long-read sequencing provides a more complete view of genetic variation.
Takeaway
Scientists looked at brain samples to see how changes in DNA affect how genes work and how they are turned on or off. They found that these changes can be important for understanding brain health.
Methodology
The study used long-read sequencing to analyze brain samples from two cohorts, identifying structural variants and their effects on gene expression and methylation.
Potential Biases
The historical focus on European populations in genomic research may limit understanding of genetic variation in other ancestries.
Limitations
Differences in sequencing technology between cohorts may affect consistency, and the accuracy of structural variant genotyping remains lower than for small variants.
Participant Demographics
Participants included 205 individuals of European ancestry and 154 individuals of African or African admixed ancestry.
Statistical Information
P-Value
8.78 × 10−7
Confidence Interval
95% CI: 8.16–11.91
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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