Age-related differences in adaptation during childhood: The influences of muscular power production and segmental energy flow caused by muscles

Acquisition of skillfulness is not only characterized by a task-appropriate application of muscular forces but also by the ability to adapt performance to changing task demands. Previous research suggests that there is a different developmental schedule for adaptation at the kinematic compared to the neuro-muscular level. The purpose of this study was to determine how age-related differences in neuro-muscular organization affect the mechanical construction of pedaling at different levels of the task. By quantifying the flow of segmental energy caused by muscles, we determined the muscular synergies that construct the movement outcome across movement speeds. Younger children (5-7 years; n = 11), older children (8-10 years; n = 8), and adults (22-31 years; n = 8) rode a stationary ergometer at five discrete cadences (60, 75, 90, 105, and 120 rpm) at 10% of their individually predicted peak power output. Using a forward dynamics simulation, we determined the muscular contributions to crank power, as well as muscular power delivered to the crank directly and indirectly (through energy absorption and transfer) during the downstroke and the upstroke of the crank cycle. We found significant age × cadence interactions for (1) peak muscular power at the hip joint [Wilks' Lambda = 0.441, F(8,42) = 2.65, p = 0.019] indicating that at high movement speeds children produced less peak power at the hip than adults, (2) muscular power delivered to the crank during the downstroke and the upstroke of the crank cycle [Wilks' Lambda = 0.399, F(8,42) = 3.07, p = 0.009] indicating that children delivered a greater proportion of the power to the crank during the upstroke when compared to adults, (3) hip power contribution to limb power [Wilks' Lambda = 0.454, F(8,42) = 2.54, p = 0.023] indicating a cadence-dependence of age-related differences in the muscular synergy between hip extensors and plantarflexors. The results demonstrate that in spite of a successful performance, children construct the task of pedaling differently when compared to adults, especially when they are pushed to their performance limits. The weaker synergy between hip extensors and plantarflexors suggests that a lack of inter-muscular coordination, rather than muscular power production per se, is a factor that limits children's performance ranges

The Effect of Bound Dineutrons upon BBN

We have examined the effects of a bound dineutron, n2, upon big bang nucleosynthesis (BBN) as a function of its binding energy B_n2. We find a weakly bound dineutron has little impact but as B_n2 increases its presence begins to alter the flow of free nucleons to helium-4. Due to this disruption, and in the absence of changes to other binding energies or fundamental constants, BBN sets a reliable upper limit of B_n2 <~ 2.5 MeV in order to maintain the agreement with the observations of the primordial helium-4 mass fraction and D/H abundance

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

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

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

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

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

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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

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

Data-driven modeling of electron recoil nucleation in PICO C3F8 bubble chambers

[EN] The primary advantage of moderately superheated bubble chamber detectors is their simultaneous sensitivity to nuclear recoils from weakly interacting massive particle (WIMP) dark matter and insensitivity to electron recoil backgrounds. A comprehensive analysis of PICO gamma calibration data demonstrates for the first time that electron recoils in C3F8 scale in accordance with a new nucleation mechanism, rather than one driven by a hot spike as previously supposed. Using this semiempirical model, bubble chamber nucleation thresholds may be tuned to be sensitive to lower energy nuclear recoils while maintaining excellent electron recoil rejection. The PICO-40L detector will exploit this model to achieve thermodynamic thresholds as low as 2.8 keV while being dominated by single-scatter events from coherent elastic neutrino-nucleus scattering of solar neutrinos. In one year of operation, PICO-401, can improve existing leading limits from PICO on spin-dependent WIMP-proton coupling by nearly an order of magnitude for WIMP masses greater than 3 GeV c(-2) and will have the ability to surpass all existing non-xenon bounds on spin-independent WIMP-nucleon coupling for WIMP masses from 3 to 40 GeV c(-2).The PICO Collaboration wishes to thank SNOLAB and its staff for support through underground space, logistical and technical services. SNOLAB operations are supported by the Canada Foundation for Innovation and the Province of Ontario Ministry of Research and Innovation, with underground access provided by Vale at the Creighton mine site. We wish to acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canada Foundation for Innovation (CFI) for funding. We acknowledge the support from National Science Foundation (NSF) (Grants No. 0919526, No. 1506337, No. 1242637, No. 1205987, and No. 1806722). We acknowledge that this work is supported by the U.S. Department of Energy (DOE) Office of Science, Office of High Energy Physics (under Award No. DE-SC-0012161), by DGAPA-UNAM (PAPIIT No. IA100118) and Consejo Nacional de Ciencia y Tecnología (CONACyT, M¿exico, Grants No. 252167 and No. A1-S-8960), by the Department of Atomic Energy (DAE), Government of India, under the Centre for AstroParticle Physics II project (CAPP-II) at the Saha Institute of Nuclear Physics (SINP), European Regional Development Fund¿Project ¿Engineering Applications of Microworld Physics¿ (Project No. CZ.02.1.01/0.0/0.0/ 16_019/0000766), and the Spanish Ministerio de Ciencia, Innovación y Universidades (Red Consolider MultiDark, Grant No. FPA2017-90566-REDC). This work is partially supported by the Kavli Institute for Cosmological Physics at the University of Chicago through NSF Grant No. 1125897, and an endowment from the Kavli Foundation and its founder Fred Kavli. We also wish to acknowledge the support from Fermi National Accelerator Laboratory under Contract No. DE-AC02-07CH11359, and Pacific Northwest National Laboratory, which is operated by Battelle for the U.S. Department of Energy under Contract No. DE-AC05- 76RL01830. We also thank Compute Canada [75] and the Center for Advanced Computing, ACENET, Calcul Qu¿ebec, Compute Ontario, and WestGrid for computational support.Amole, C.; Ardid Ramírez, M.; Arnquist, I.; Asner, DM.; Baxter, D.; Behnke, E.; Bressler, M.... (2019). Data-driven modeling of electron recoil nucleation in PICO C3F8 bubble chambers. Physical Review D: covering particles, fields, gravitation, and cosmology. 100(8):1-18. https://doi.org/10.1103/PhysRevD.100.082006S1181008Amole, C., Ardid, M., Arnquist, I. J., Asner, D. M., Baxter, D., Behnke, E., … Chen, C. J. (2019). Dark matter search results from the complete exposure of the PICO-60 C3F8 bubble chamber. 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Il Nuovo Cimento A, 107(2), 291-298. doi:10.1007/bf02781560Amole, C., Ardid, M., Asner, D. M., Baxter, D., Behnke, E., Bhattacharjee, P., … Broemmelsiek, D. (2016). Dark matter search results from the PICO-60CF3Ibubble chamber. Physical Review D, 93(5). doi:10.1103/physrevd.93.052014Amole, C., Ardid, M., Arnquist, I. J., Asner, D. M., Baxter, D., Behnke, E., … Campion, P. (2017). Dark Matter Search Results from the PICO−60 C3F8 Bubble Chamber. Physical Review Letters, 118(25). doi:10.1103/physrevlett.118.251301Amole, C., Ardid, M., Arnquist, I. J., Asner, D. M., Baxter, D., Behnke, E., … Brice, S. J. (2016). Improved dark matter search results from PICO-2L Run 2. Physical Review D, 93(6). doi:10.1103/physrevd.93.061101Amole, C., Ardid, M., Asner, D. M., Baxter, D., Behnke, E., Bhattacharjee, P., … Broemmelsiek, D. (2015). Dark Matter Search Results from the PICO-2LC3F8Bubble Chamber. Physical Review Letters, 114(23). doi:10.1103/physrevlett.114.231302Hasert, F. J., Faissner, H., Krenz, W., Von Krogh, J., Lanske, D., Morfin, J., … Lemonne, J. (1973). Search for elastic muon-neutrino electron scattering. Physics Letters B, 46(1), 121-124. doi:10.1016/0370-2693(73)90494-2Hasert, F. J., Kabe, S., Krenz, W., Von Krogh, J., Lanske, D., Morfin, J., … Sacton, J. (1973). Observation of neutrino-like interactions without muon or electron in the gargamelle neutrino experiment. Physics Letters B, 46(1), 138-140. doi:10.1016/0370-2693(73)90499-1Behnke, E., Benjamin, T., Brice, S. J., Broemmelsiek, D., Collar, J. I., … Cooper, P. S. (2013). Direct measurement of the bubble-nucleation energy threshold in aCF3Ibubble chamber. Physical Review D, 88(2). doi:10.1103/physrevd.88.021101Tenner, A. G. (1963). Nucleation in bubble chambers. Nuclear Instruments and Methods, 22, 1-42. doi:10.1016/0029-554x(63)90224-6Kozynets, T., Fallows, S., & Krauss, C. B. (2019). Modeling emission of acoustic energy during bubble expansion in PICO bubble chambers. Physical Review D, 100(5). doi:10.1103/physrevd.100.052001Seitz, F. (1958). On the Theory of the Bubble Chamber. Physics of Fluids, 1(1), 2. doi:10.1063/1.1724333Behnke, E., Collar, J. I., Cooper, P. S., Crum, K., Crisler, M., Hu, M., … Tschirhart, R. (2008). Spin-Dependent WIMP Limits from a Bubble Chamber. Science, 319(5865), 933-936. doi:10.1126/science.1149999Barnabé-Heider, M., Di Marco, M., Doane, P., Genest, M.-H., Gornea, R., Guénette, R., … Noulty, R. (2005). Response of superheated droplet detectors of the PICASSO dark matter search experiment. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 555(1-2), 184-204. doi:10.1016/j.nima.2005.09.015Ziegler, J. F., Ziegler, M. D., & Biersack, J. P. (2010). SRIM – The stopping and range of ions in matter (2010). Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 268(11-12), 1818-1823. doi:10.1016/j.nimb.2010.02.091Bressler, M., Campion, P., Cushman, V. S., Morrese, A., Wagner, J. M., Zerbo, S., … Dahl, C. E. (2019). A buffer-free concept bubble chamber for PICO dark matter searches. Journal of Instrumentation, 14(08), P08019-P08019. doi:10.1088/1748-0221/14/08/p08019Agostinelli, S., Allison, J., Amako, K., Apostolakis, J., Araujo, H., Arce, P., … Barrand, G. (2003). Geant4—a simulation toolkit. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 506(3), 250-303. doi:10.1016/s0168-9002(03)01368-8Pozzi, S. A., Padovani, E., & Marseguerra, M. (2003). MCNP-PoliMi: a Monte-Carlo code for correlation measurements. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 513(3), 550-558. doi:10.1016/j.nima.2003.06.012Archambault, S., Aubin, F., Auger, M., Beleshi, M., Behnke, E., … Behnke, J. (2011). New insights into particle detection with superheated liquids. New Journal of Physics, 13(4), 043006. doi:10.1088/1367-2630/13/4/043006Glaser, D. A. (1954). Progress report on the development of bubble chambers. Il Nuovo Cimento, 11(S2), 361-368. doi:10.1007/bf02781098Fabian, B. N., Place, R. L., Riley, W. A., Sims, W. H., & Kenney, V. P. (1963). Density of Particle Tracks in the Hydrogen Bubble Chamber. Review of Scientific Instruments, 34(5), 484-495. doi:10.1063/1.1718415Willis, W. J., Fowler, E. C., & Rahm, D. C. (1957). Bubble Density in a Propane Bubble Chamber. Physical Review, 108(4), 1046-1047. doi:10.1103/physrev.108.1046Hahn, B., & Hugentobler, E. (1960). Relativistic increase in bubble density in a CBrF3 bubble chamber. Il Nuovo Cimento, 17(6), 983-985. doi:10.1007/bf02732145Brown, J. L., Glaser, D. A., & Perl, M. L. (1956). Liquid Xenon Bubble Chamber. Physical Review, 102(2), 586-587. doi:10.1103/physrev.102.586Baxter, D., Chen, C. J., Crisler, M., Cwiok, T., Dahl, C. E., Grimsted, A., … Zhang, J. (2017). First Demonstration of a Scintillating Xenon Bubble Chamber for Detecting Dark Matter and Coherent Elastic Neutrino-Nucleus Scattering. Physical Review Letters, 118(23). doi:10.1103/physrevlett.118.231301Durup, J., & Platzman, R. L. (1961). Role of the Auger effect in the displacement of atoms in solids by ionizing radiation. Discussions of the Faraday Society, 31, 156. doi:10.1039/df9613100156Schönfeld, E., & Janßen, H. (2000). Calculation of emission probabilities of X-rays and Auger electrons emitted in radioactive disintegration processes. Applied Radiation and Isotopes, 52(3), 595-600. doi:10.1016/s0969-8043(99)00216-xStrigari, L. E. (2009). Neutrino coherent scattering rates at direct dark matter detectors. New Journal of Physics, 11(10), 105011. doi:10.1088/1367-2630/11/10/105011Lewin, J. D., & Smith, P. F. (1996). Review of mathematics, numerical factors, and corrections for dark matter experiments based on elastic nuclear recoil. Astroparticle Physics, 6(1), 87-112. doi:10.1016/s0927-6505(96)00047-3Fitzpatrick, A. L., Haxton, W., Katz, E., Lubbers, N., & Xu, Y. (2013). The effective field theory of dark matter direct detection. Journal of Cosmology and Astroparticle Physics, 2013(02), 004-004. doi:10.1088/1475-7516/2013/02/004Anand, N., Fitzpatrick, A. L., & Haxton, W. C. (2014). Weakly interacting massive particle-nucleus elastic scattering response. Physical Review C, 89(6). doi:10.1103/physrevc.89.065501Gresham, M. I., & Zurek, K. M. (2014). Effect of nuclear response functions in dark matter direct detection. Physical Review D, 89(12). doi:10.1103/physrevd.89.123521Gluscevic, V., Gresham, M. I., McDermott, S. D., Peter, A. H. G., & Zurek, K. M. (2015). Identifying the theory of dark matter with direct detection. Journal of Cosmology and Astroparticle Physics, 2015(12), 057-057. doi:10.1088/1475-7516/2015/12/057Aprile, E., Aalbers, J., Agostini, F., Alfonsi, M., Althueser, L., Amaro, F. D., … Baudis, L. (2019). Constraining the Spin-Dependent WIMP-Nucleon Cross Sections with XENON1T. Physical Review Letters, 122(14). doi:10.1103/physrevlett.122.141301Akerib, D. S., Alsum, S., Araújo, H. M., Bai, X., Bailey, A. J., Balajthy, J., … Biesiadzinski, T. P. (2017). Limits on Spin-Dependent WIMP-Nucleon Cross Section Obtained from the Complete LUX Exposure. Physical Review Letters, 118(25). doi:10.1103/physrevlett.118.251302Fu, C., Cui, X., Zhou, X., Chen, X., Chen, Y., … Fang, D. (2017). Spin-Dependent Weakly-Interacting-Massive-Particle–Nucleon Cross Section Limits from First Data of PandaX-II Experiment. Physical Review Letters, 118(7). doi:10.1103/physrevlett.118.071301Behnke, E., Besnier, M., Bhattacharjee, P., Dai, X., Das, M., Davour, A., … Zacek, V. (2017). Final results of the PICASSO dark matter search experiment. Astroparticle Physics, 90, 85-92. doi:10.1016/j.astropartphys.2017.02.005Aartsen, M. G., Ackermann, M., Adams, J., Aguilar, J. A., Ahlers, M., Ahrens, M., … Ansseau, I. (2017). Search for annihilating dark matter in the Sun with 3 years of IceCube data. The European Physical Journal C, 77(3). doi:10.1140/epjc/s10052-017-4689-9Choi, K., Abe, K., Haga, Y., Hayato, Y., Iyogi, K., Kameda, J., … Nakahata, M. (2015). Search for Neutrinos from Annihilation of Captured Low-Mass Dark Matter Particles in the Sun by Super-Kamiokande. Physical Review Letters, 114(14). doi:10.1103/physrevlett.114.141301Ruppin, F., Billard, J., Figueroa-Feliciano, E., & Strigari, L. (2014). Complementarity of dark matter detectors in light of the neutrino background. Physical Review D, 90(8). doi:10.1103/physrevd.90.083510Felizardo, M., Girard, T. A., Morlat, T., Fernandes, A. C., Ramos, A. R., Marques, J. G., … Marques, R. (2014). The SIMPLE Phase II dark matter search. Physical Review D, 89(7). doi:10.1103/physrevd.89.072013Adrián-Martínez, S., Albert, A., André, M., Anton, G., Ardid, M., Aubert, J.-J., … Basa, S. (2016). Limits on dark matter annihilation in the sun using the ANTARES neutrino telescope. Physics Letters B, 759, 69-74. doi:10.1016/j.physletb.2016.05.019Adrián-Martínez, S., Albert, A., André, M., Anton, G., Ardid, M., Aubert, J.-J., … Basa, S. (2016). A search for Secluded Dark Matter in the Sun with the ANTARES neutrino telescope. Journal of Cosmology and Astroparticle Physics, 2016(05), 016-016. doi:10.1088/1475-7516/2016/05/016Aprile, E., Aalbers, J., Agostini, F., Alfonsi, M., Althueser, L., Amaro, F. D., … Bauermeister, B. (2018). Dark Matter Search Results from a One Ton-Year Exposure of XENON1T. Physical Review Letters, 121(11). doi:10.1103/physrevlett.121.111302Akerib, D. S., Alsum, S., Araújo, H. M., Bai, X., Bailey, A. J., Balajthy, J., … Biesiadzinski, T. P. (2017). Results from a Search for Dark Matter in the Complete LUX Exposure. Physical Review Letters, 118(2). doi:10.1103/physrevlett.118.021303Agnes, P., Albuquerque, I. F. M., Alexander, T., Alton, A. K., Araujo, G. R., Asner, D. M., … Batignani, G. (2018). Low-Mass Dark Matter Search with the DarkSide-50 Experiment. Physical Review Letters, 121(8). doi:10.1103/physrevlett.121.081307Agnes, P., Albuquerque, I. F. M., Alexander, T., Alton, A. K., Araujo, G. R., Ave, M., … Biery, K. (2018). DarkSide-50 532-day dark matter search with low-radioactivity argon. Physical Review D, 98(10). doi:10.1103/physrevd.98.102006Agnese, R., Anderson, A. J., Aralis, T., Aramaki, T., Arnquist, I. J., Baker, W., … Bauer, D. A. (2018). Low-mass dark matter search with CDMSlite. Physical Review D, 97(2). doi:10.1103/physrevd.97.022002Agnese, R., Aramaki, T., Arnquist, I. J., Baker, W., Balakishiyeva, D., Banik, S., … Binder, T. (2018). Results from the Super Cryogenic Dark Matter Search Experiment at Soudan. Physical Review Letters, 120(6). doi:10.1103/physrevlett.120.061802Hehn, L., Armengaud, E., Arnaud, Q., Augier, C., Benoît, A., Bergé, L., … Yakushev, E. (2016). Improved EDELWEISS-III sensitivity for low-mass WIMPs using a profile likelihood approach. The European Physical Journal C, 76(10). doi:10.1140/epjc/s10052-016-4388-yTolman, R. C. (1949). The Effect of Droplet Size on Surface Tension. The Journal of Chemical Physics, 17(3), 333-337. doi:10.1063/1.1747247Kirkwood, J. G., & Buff, F. P. (1949). The Statistical Mechanical Theory of Surface Tension. The Journal of Chemical Physics, 17(3), 338-343. doi:10.1063/1.1747248Xue, Y.-Q., Yang, X.-C., Cui, Z.-X., & Lai, W.-P. (2010). The Effect of Microdroplet Size on the Surface Tension and Tolman Length. The Journal of Physical Chemistry B, 115(1), 109-112. doi:10.1021/jp108431

Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

: O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s disease Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types C. A. Semple O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu O16 Modeling genetic interactions associated with molecular subtypes of breast cancer B. Ji, A. Tyler, G. Ananda, G. Carter O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski O18 Predictive biomarkers to metastatic pancreatic cancer treatment J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman O19 DDIT4 gene expression as a prognostic marker in several malignant tumors L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto O20 Spatial organization of the genome and genomic alterations in human cancers K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group O21 Landscape of targeted therapies in solid tumors S. Patterson, C. Statz, S. Mockus O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis S. Likhitrattanapisal O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4 C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13 K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle O32 Legal interoperability: a sine qua non for international data sharing A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes R. Ghosh, S. Plon O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker O40 A general statistic framework for genome-based disease risk prediction M. Xiong, L. Ma, N. Lin, C. Amos O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong O42 Big data and NGS data analysis: the cloud to the rescue O. Dobretsberger, M. Egger, F. Leimgruber O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data V. A. A. Antonio, N. Ono, Clark Kendrick C. Go O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans C. Zeng, J. Shao O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes? I. Campbell, M.-A. Young, P. James, Lifepool O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS C. Schumacher, S. Sandhu, T. Harkins, V. Makarov O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs O55 Rapid capture methods for clinical sequencing J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs O56 A diploid personal human genome model for better genomes from diverse sequence data K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs O57 Development of PacBio long range capture for detection of pathogenic structural variants Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers O59 Assessing RNA structure disruption induced by single-nucleotide variation J. Lin, Y. Zhang, Z. Ouyang P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility E. S. Chen P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients H. Bahrami, A. Khoshzaban, S. Heidari Keshal P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population K. K. R. Alharbi P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population M. Matar P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization N. Mili, R. Molinari, Y. Ma, S. Guerrier P9 Vulnerability of genetic variants to the risk of autism among Saudi children N. Elhawary, M. Tayeb, N. Bogari, N. Qotb P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7 mice Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome D. Graur P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns B. S. Soibam P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes J. J. Gruber, N. Jaeger, M. Snyder P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson P23 RNA sequencing identifies gene mutations for neuroblastoma K. Zhang P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales P25 Targeted Methylation Sequencing of Prostate Cancer N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía P28 Genetic modifiers of Alström syndrome J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess P34 Molecular regulation of chondrogenic human induced pluripotent stem cells M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid P36 Accessing genomic evidence for clinical variants at NCBI S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA C. Xiao, E. Yaschenko, S. Sherry P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling C. Rangel-Escareño, H. Rueda-Zarate P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium P43 Rapid and scalable typing of structural variants for disease cohorts W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu P49 Common variants in casr gene are associated with serum calcium levels in koreans S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions Y. Zhou, S. Xu P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies X. Wang, V. Philip, G. Carter P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar P54 Direct enrichment for the rapid preparation of targeted NGS libraries C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System R. Nitsche, L. Prieto-Lafuente P57 ClinVar: a multi-source archive for variant interpretation M. Landrum, J. Lee, W. Rubinstein, D. Maglott P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler P61 Compound heterozygous mutation in the LDLR gene in Saudi patients suffering severe hypercholesterolemia F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Atha

Somatic mutations affect key pathways in lung adenocarcinoma

Determining the genetic basis of cancer requires comprehensive analyses of large collections of histopathologically well- classified primary tumours. Here we report the results of a collaborative study to discover somatic mutations in 188 human lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are probably involved in carcinogenesis. The frequently mutated genes include tyrosine kinases, among them the EGFR homologue ERBB4; multiple ephrin receptor genes, notably EPHA3; vascular endothelial growth factor receptor KDR; and NTRK genes. These data provide evidence of somatic mutations in primary lung adenocarcinoma for several tumour suppressor genes involved in other cancers - including NF1, APC, RB1 and ATM - and for sequence changes in PTPRD as well as the frequently deleted gene LRP1B. The observed mutational profiles correlate with clinical features, smoking status and DNA repair defects. These results are reinforced by data integration including single nucleotide polymorphism array and gene expression array. Our findings shed further light on several important signalling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.National Human Genome Research InstituteWe thank A. Lash, M.F. Zakowski, M.G. Kris and V. Rusch for intellectual contributions, and many members of the Baylor Human Genome Sequencing Center, the Broad Institute of Harvard and MIT, and the Genome Center at Washington University for support. This work was funded by grants from the National Human Genome Research Institute to E.S.L., R.A.G. and R.K.W.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62885/1/nature07423.pd