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Abstract BackgroundLow-depth sequencing allows researchers to increase sample size at the expense of lower accuracy. To incorporate uncertainties while maintaining statistical power, we introduce to analyze population structure of low-depth sequencing data. ResultsThe method optimizes the choice of nonlinear transformations of dosages to maximize the Ky Fan norm of the covariance matrix. The transformation incorporates the uncertainty in calling between heterozygotes and the common homozygotes for loci having a rare allele and is more linear when both variants are common. ConclusionsWe apply to samples from two indigenous Siberian populations and reveal hidden population structure accurately using only a single chromosome. The package is available onhttps://github.com/yiwenstat/MCPCA_PopGen. 

Abstract The ability to reconstitute natural glycosylation pathways or prototype entirely new ones from scratch is hampered by the limited availability of functional glycoenzymes, many of which are membrane proteins that fail to express in heterologous hosts. Here, we describe a strategy for topologically converting membrane-bound glycosyltransferases (GTs) into water soluble biocatalysts, which are expressed at high levels in the cytoplasm of living cells with retention of biological activity. We demonstrate the universality of the approach through facile production of 98 difficult-to-express GTs, predominantly of human origin, across several commonly used expression platforms. Using a subset of these water-soluble enzymes, we perform structural remodeling of both free and protein-linked glycans including those found on the monoclonal antibody therapeutic trastuzumab. Overall, our strategy for rationally redesigning GTs provides an effective and versatile biosynthetic route to large quantities of diverse, enzymatically active GTs, which should find use in structure-function studies as well as in biochemical and biomedical applications involving complex glycomolecules.