352 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.

    hHSS1: a novel secreted factor and suppressor of glioma growth located at chromosome 19q13.33

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    The completion of the Human Genome Project resulted in discovery of many unknown novel genes. This feat paved the way for the future development of novel therapeutics for the treatment of human disease based on novel biological functions and pathways. Towards this aim, we undertook a bioinformatics analysis of in-house microarray data derived from purified hematopoietic stem cell populations. This effort led to the discovery of HSS1 (Hematopoietic Signal peptide-containing Secreted 1) and its splice variant HSM1 (Hematopoietic Signal peptide-containing Membrane domain-containing 1). HSS1 gene is evolutionarily conserved across species, phyla and even kingdoms, including mammals, invertebrates and plants. Structural analysis showed no homology between HSS1 and known proteins or known protein domains, indicating that it was a truly novel protein. Interestingly, the human HSS1 (hHSS1) gene is located at chromosome 19q13.33, a genomic region implicated in various cancers, including malignant glioma. Stable expression of hHSS1 in glioma-derived A172 and U87 cell lines greatly reduced their proliferation rates compared to mock-transfected cells. hHSS1 expression significantly affected the malignant phenotype of U87 cells both in vitro and in vivo. Further, preliminary immunohistochemical analysis revealed an increase in hHSS1/HSM1 immunoreactivity in two out of four high-grade astrocytomas (glioblastoma multiforme, WHO IV) as compared to low expression in all four low-grade diffuse astrocytomas (WHO grade II). High-expression of hHSS1 in high-grade gliomas was further supported by microarray data, which indicated that mesenchymal subclass gliomas exclusively up-regulated hHSS1. Our data reveal that HSS1 is a truly novel protein defining a new class of secreted factors, and that it may have an important role in cancer, particularly glioma

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Anatomy of STEM Teaching in American Universities: A Snapshot from a Large-Scale Observation Study

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    National and local initiatives focused on the transformation of STEM teaching in higher education have multiplied over the last decade. These initiatives often focus on measuring change in instructional practices, but it is difficult to monitor such change without a national picture of STEM educational practices, especially as characterized by common observational instruments. We characterized a snapshot of this landscape by conducting the first large scale observation-based study. We found that lecturing was prominent throughout the undergraduate STEM curriculum, even in classrooms with infrastructure designed to support active learning, indicating that further work is required to reform STEM education. Additionally, we established that STEM faculty’s instructional practices can vary substantially within a course, invalidating the commonly-used teaching evaluations based on a one-time observation

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Allelic diversity of S‑RNase alleles in diploid potato species

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    S-ribonucleases (S-RNases) control the pistil specificity of the self-incompatibility (SI) response in the genus Solanum and several other members of the Solanaceae. The nucleotide sequences of S-RNases corresponding to a large number of S-alleles or S-haplotypes have been characterised. However, surprisingly few S-RNase sequences are available for potato species. The identification of new S-alleles in diploid potato species is desirable as these stocks are important sources of traits such as biotic and abiotic resistance. S-RNase sequences are reported here from three distinct diploid types of potato: cultivated Solanum tuberosum Group Phureja, S. tuberosum Group Stenotomum, and the wild species Solanum okadae. Partial S-RNase sequences were obtained from pistil RNA by RT-PCR or 3’RACE (Rapid Amplification of cDNA Ends) using a degenerate primer. Full length sequences were obtained for two alleles by 5’RACE. Database searches with these sequences, identified sixteen S-RNases in total, all of which are novel. The sequence analysis revealed all the expected features of functional S-RNases. Phylogenetic analysis with selected published S-RNase and S-like-RNase sequences from the Solanaceae revealed extensive trans-generic evolution of the S-RNases and a clear distinction from S-like-RNases. Pollination tests were used to confirm the self-incompatibility status and cross-compatibility relationships of the S. okadae accessions. All the S. okadae accessions were found to be self-incompatible as expected with crosses amongst them exhibiting both cross-compatibility and semi-compatibility consistent with the S-genotypes determined from the S-RNase sequence data. The progeny analysis of four semi-compatible crosses examined by allele-specific PCR provided further confirmation that these are functional S-RNases
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