44 research outputs found

    Hundreds of variants clustered in genomic loci and biological pathways affect human height

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    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

    The Sail-Backed Reptile Ctenosauriscus from the Latest Early Triassic of Germany and the Timing and Biogeography of the Early Archosaur Radiation

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    Background Archosaurs (birds, crocodilians and their extinct relatives including dinosaurs) dominated Mesozoic continental ecosystems from the Late Triassic onwards, and still form a major component of modern ecosystems (>10,000 species). The earliest diverse archosaur faunal assemblages are known from the Middle Triassic (c. 244 Ma), implying that the archosaur radiation began in the Early Triassic (252.3–247.2 Ma). Understanding of this radiation is currently limited by the poor early fossil record of the group in terms of skeletal remains. Methodology/Principal Findings We redescribe the anatomy and stratigraphic position of the type specimen of Ctenosauriscus koeneni (Huene), a sail-backed reptile from the Early Triassic (late Olenekian) Solling Formation of northern Germany that potentially represents the oldest known archosaur. We critically discuss previous biomechanical work on the ‘sail’ of Ctenosauriscus, which is formed by a series of elongated neural spines. In addition, we describe Ctenosauriscus-like postcranial material from the earliest Middle Triassic (early Anisian) Röt Formation of Waldhaus, southwestern Germany. Finally, we review the spatial and temporal distribution of the earliest archosaur fossils and their implications for understanding the dynamics of the archosaur radiation. Conclusions/Significance Comprehensive numerical phylogenetic analyses demonstrate that both Ctenosauriscus and the Waldhaus taxon are members of a monophyletic grouping of poposauroid archosaurs, Ctenosauriscidae, characterised by greatly elongated neural spines in the posterior cervical to anterior caudal vertebrae. The earliest archosaurs, including Ctenosauriscus, appear in the body fossil record just prior to the Olenekian/Anisian boundary (c. 248 Ma), less than 5 million years after the Permian–Triassic mass extinction. These earliest archosaur assemblages are dominated by ctenosauriscids, which were broadly distributed across northern Pangea and which appear to have been the first global radiation of archosaurs

    VoPo leverages cellular heterogeneity for predictive modeling of single-cell data

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    High-throughput single-cell analysis technologies produce an abundance of data that is critical for profiling the heterogeneity of cellular systems. We introduce VoPo (https://github.com/stanleyn/VoPo), a machine learning algorithm for predictive modeling and comprehensive visualization of the heterogeneity captured in large single-cell datasets. In three mass cytometry datasets, with the largest measuring hundreds of millions of cells over hundreds of samples, VoPo defines phenotypically and functionally homogeneous cell populations. VoPo further outperforms state-of-the-art machine learning algorithms in classification tasks, and identified immune-correlates of clinically-relevant parameters
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