56 research outputs found

    Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia

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    This book, Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia, makes a unique and needed contribution to the mentoring field as it focuses solely on mentoring in academia. This handbook is a collaborative institutional effort between Utah State University’s (USU) Empowering Teaching Open Access Book Series and the Mentoring Institute at the University of New Mexico (UNM). This book is available through (a) an e-book through Pressbooks, (b) a downloadable PDF version on USU’s Open Access Book Series website), and (c) a print version available for purchase on the USU Empower Teaching Open Access page, and on Amazon

    Human and mouse essentiality screens as a resource for disease gene discovery.

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    The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery

    FTO genetic variants, dietary intake and body mass index: insights from 177 330 individuals

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    FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177 330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m2, P = 1.9 × 10−105), and all participants (0.30 [0.30, 0.35] kg/m2, P = 3.6 × 10−107). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10−16), and relative weak associations with lower total energy intake (−6.4 [−10.1, −2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (−0.07 [−0.11, −0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10−9) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposit

    Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

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    Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

    Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

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    Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores

    Transcriptome-wide association study of breast cancer risk by estrogen-receptor status

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    Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.Peer reviewe

    New genetic loci link adipose and insulin biology to body fat distribution.

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    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

    Ligand-independent activation of the Hedgehog pathway displays non-cell autonomous proliferation during eye development in Drosophila

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    Deregulation of the Hedgehog (Hh) signaling pathway is associated with the development of human cancer including medullobastoma and basal cell carcinoma. Loss of Patched or activation of Smoothened in mouse models increases the occurrence of tumors. Likewise, in a Drosophila eye model, deregulated Hedgehog signaling causes overgrowth of eye and head tissues. Surprisingly, we show that cells with deregulated Hh signaling do not or only little contribute to the tissue overgrowth. Instead, they become more sensitive to apoptosis and may eventually be eliminated. Nevertheless, these mutant cells increase proliferation in the adjacent wild-type tissue, i.e., in a non-cell autonomous manner. This non-cell autonomous effect is position-dependent and restricted to mutant cells in the anterior portion of the eye. We also observe precocious non-cell autonomous differentiation in genetic mosaics with deregulated Hh signaling. Together, these non-cell autonomous growth and differentiation phenotypes in the Drosophila eye model reveal another strategy by which oncogenes may generate a supportive micro-environment for tumor growth

    Folded Gastrulation, Cell Shape Change and the Control of Myosin Localization

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    A molecular study of how changes in cell shape are controlled in the fruit-fly embryo-drawing parallels to pathways involved in cancer metastasis and providing a complete chain of events from cell fate specification to physical changes in cell shape.--author supplied descriptio

    Live imaging of developing mouse retinal slices

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    Abstract Background Ex vivo, whole-mount explant culture of the rodent retina has proved to be a valuable approach for studying retinal development. In a limited number of recent studies, this method has been coupled to live fluorescent microscopy with the goal of directly observing dynamic cellular events. However, retinal tissue thickness imposes significant technical limitations. To obtain 3-dimensional images with high quality axial resolution, investigators are restricted to specific areas of the retina and require microscopes, such as 2-photon, with a higher level of depth penetrance. Here, we report a retinal live imaging method that is more amenable to a wider array of imaging systems and does not compromise resolution of retinal cross-sectional area. Results Mouse retinal slice cultures were prepared and standard, inverted confocal microscopy was used to generate movies with high quality resolution of retinal cross-sections. To illustrate the ability of this method to capture discrete, physiologically relevant events during retinal development, we imaged the dynamics of the Fucci cell cycle reporter in both wild type and Cyclin D1 mutant retinal progenitor cells (RPCs) undergoing interkinetic nuclear migration (INM). Like previously reported for the zebrafish, mouse RPCs in G1 phase migrated stochastically and exhibited overall basal drift during development. In contrast, mouse RPCs in G2 phase displayed directed, apical migration toward the ventricular zone prior to mitosis. We also determined that Cyclin D1 knockout RPCs in G2 exhibited a slower apical velocity as compared to wild type. These data are consistent with previous IdU/BrdU window labeling experiments on Cyclin D1 knockout RPCs indicating an elongated cell cycle. Finally, to illustrate the ability to monitor retinal neuron differentiation, we imaged early postnatal horizontal cells (HCs). Time lapse movies uncovered specific HC neurite dynamics consistent with previously published data showing an instructive role for transient vertical neurites in HC mosaic formation. Conclusions We have detailed a straightforward method to image mouse retinal slice culture preparations that, due to its relative ease, extends live retinal imaging capabilities to a more diverse group of scientists. We have also shown that, by using a slice technique, we can achieve excellent lateral resolution, which is advantageous for capturing intracellular dynamics and overall cell movements during retinal development and differentiation
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