Deeper insights from data density, disentangling diverse genetic data, and delving into T cell states
Research Roundup: January 22, 2021
Welcome to the January 22, 2021 installment of Research Roundup, a recurring snapshot of recent studies published by scientists at the Broad Institute and their collaborators.
Data density, displayed
Nonlinear data visualizations used to find patterns in single-cell RNA sequencing datasets can be misleading, because they neglect the local density of data points in the original space. Ashwin Narayan, associate member Bonnie Berger of the Cell Circuits Program and of MIT, and Schmidt Fellow Hyunghoon Cho designed density-preserving data visualization methods, den-SNE and densMAP, that can more accurately extract deeper biological insights. Applied to diverse datasets, the methods revealed significant changes in transcriptomic variability in a range of biological processes, including heterogeneity in transcriptomic variability of immune cells in blood and tumor, human immune cell specialization, and the developmental trajectory of C. elegans. Read more in Nature Biotechnology.
A new tool helps increase genetic studies' diversity
Researchers often exclude admixed individuals — those whose ancestry reflects multiple populations — from genome-wide association studies (GWAS), as distinguishing disease-causing and ancestry-based variants can be difficult. In Nature Genetics, Elizabeth Atkinson, institute members Mark Daly and Benjamin Neale, and colleagues in the Program in Medical and Population Genetics, the Stanley Center for Psychiatric Research, and elsewhere introduce Tractor, which improves genetic tools’ ability to tell the difference. Tractor infers the ancestry of each individual section of the genome, allowing variants in each section to be compared to those from genomes of similar ancestry. This is especially promising for African Americans, Latinos, and other admixed populations, as exclusion from GWAS may contribute to health disparities.
Mapping immune responses in the gut
CD4+ effector lymphocytes, also called Teff cells, are key drivers of immune responses. Evgeny Kiner, associate members Diane Mathis and Christophe Benoist of the Klarman Cell Observatory, and members of the Immunological Genome Project Consortium used single-cell genomics to assess the spectrum of phenotypic states that Teff cells in the guts of mice can adopt when stressed by microbial infections. The results from the study show that the Teff cell response does not neatly conform to textbook dogma, fitting a continuum model of differentiation expression rather than discrete cell states. Read more in Nature Immunology.