Whole Population, Genomewide Mapping of Hidden Relatedness

The ability to identify and quantify genealogical relationships between individuals within a population is an important step in accurately using such data for disease analysis and improving our understanding of demography. However, exhaustive pair-wise analysis which has been successful in small cohorts cannot keep up with the current torrent of genotype data. We present GERMLINE, a robust algorithm for identifying pairwise segmental sharing which scales linearly with the number of input individuals. Our approach is based on a dictionary of haplotypes, used to efficiently discover short exact matches between individuals and then expand these matches to identify long nearly-identical segmental sharing that is indicative of relatedness. We use GERMLINE to comprehensively survey hidden relatedness both in the HapMap as well as in a densely typed island population of 3,000 individuals. We verify that GERMLINE is in concordance with other methods when they can process the data, and also facilitates analysis of larger scale studies. We also demonstrate novel applications of precise analysis of hidden relatedness to detection of haplotype phasing errors and structural variation. We show that shared segment discovery can help identifying phasing errors and potentially resolve them. Finally, we use detected identity of genomic segments for exposing polymorphic deletions that are otherwise challenging to detect, with 8/14 deletions in the HapMap samples and 153/200 deletions in the island data having independent experimental validation

Efficiency and Power as a Function of Sequence Coverage, SNP Array Density, and Imputation

High coverage whole genome sequencing provides near complete information about genetic variation. However, other technologies can be more efficient in some settings by (a) reducing redundant coverage within samples and (b) exploiting patterns of genetic variation across samples. To characterize as many samples as possible, many genetic studies therefore employ lower coverage sequencing or SNP array genotyping coupled to statistical imputation. To compare these approaches individually and in conjunction, we developed a statistical framework to estimate genotypes jointly from sequence reads, array intensities, and imputation. In European samples, we find similar sensitivity (89%) and specificity (99.6%) from imputation with either 1× sequencing or 1 M SNP arrays. Sensitivity is increased, particularly for low-frequency polymorphisms (MAF <5%), when low coverage sequence reads are added to dense genome-wide SNP arrays — the converse, however, is not true. At sites where sequence reads and array intensities produce different sample genotypes, joint analysis reduces genotype errors and identifies novel error modes. Our joint framework informs the use of next-generation sequencing in genome wide association studies and supports development of improved methods for genotype calling

Bistability in the Tunnelling Current through a Ring of NN Coupled Quantum Dots

We study bistability in the electron transport through a ring of N coupled quantum dots with two orbitals in each dot. One orbital is localized (called b orbital) and coupling of the b orbitals in any two dots is negligible; the other is delocalized in the plane of the ring (called d orbital), due to coupling of the d orbitals in the neighboring dots, as described by a tight-binding model. The d orbitals thereby form a band with finite width. The b and d orbitals are connected to the source and drain electrodes with a voltage bias V, allowing the electron tunnelling. Tunnelling current is calculated by using a nonequilibrium Green function method recently developed to treat nanostructures with multiple energy levels. We find a bistable effect in the tunnelling current as a function of bias V, when the size N>50; this effect scales with the size N and becomes sizable at N~100. The temperature effect on bistability is also discussed. In comparison, mean-field treatment tends to overestimate the bistable effect.Comment: Published in JPSJ; minor typos correcte

Spectroscopy, Interactions and Level Splittings in Au Nanoparticles

We have measured the electronic energy spectra of nm-scale Au particles using a new tunneling spectroscopy configuration. The particle diameters ranged from 5nm to 9nm, and at low energies the spectrum is discrete, as expected by the electron-in-a-box model. The density of tunneling resonances increases rapidly with energy, and at higher energies the resonances overlap forming broad resonances. Near the Thouless energy, the broad resonances merge into a continuum. The tunneling resonances display Zeeman splitting in a magnetic field. Surprisingly, the g-factors (~0.3) of energy levels in Au nano-particles are much smaller than the g-factor (2.1) in bulk gold

The Role of CD 133+ Cells in a Recurrent Embryonal Tumor with Abundant Neuropil and True Rosettes ( ETANTR )

Embryonal tumor with abundant neuropil and true rosettes ( ETANTR ) is a recently described embryonal neoplasm of the central nervous system, consisting of a well‐circumscribed embryonal tumor of infancy with mixed features of ependymoblastoma (multilayer ependymoblastic rosettes and pseudorosettes) and neuroblastoma (neuroblastic rosettes) in the presence of neuropil‐like islands. We present the case of a young child with a very aggressive tumor that rapidly recurred after gross total resection, chemotherapy and radiation. Prominent vascular sclerosis and circumscribed tumor led to the diagnosis of malignant astroblastoma; however, rapid recurrence and progression of this large tumor after gross total resection prompted review of the original pathology. ETANTR is histologically distinct with focal glial fibrillary acid protein ( GFAP ) and synaptophysin expression in the presence of neuronal and ependymoblastic rosettes with focal neuropil islands. These architectural features, combined with unique chromosome 19q13.42 amplification, confirmed the diagnosis. In this report, we describe tumor stem cell ( TSC ) marker CD 133, CD 15 and nestin alterations in ETANTR before and after chemotherapy. We found that TSC marker CD 133 was richly expressed after chemotherapy in recurrent ETANTR , while CD 15 is depleted compared with that expressed in the original tumor, suggesting that CD 133+ cells likely survived initial treatment, further contributing to formation of the recurrent tumor.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102077/1/bpa12079.pd

Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population

The potential benefits of using population isolates in genetic mapping, such as reduced genetic, phenotypic and environmental heterogeneity, are offset by the challenges posed by the large amounts of direct and cryptic relatedness in these populations confounding basic assumptions of independence. We have evaluated four representative specialized methods for association testing in the presence of relatedness; (i) within-family (ii) within- and between-family and (iii) mixed-models methods, using simulated traits for 2906 subjects with known genome-wide genotype data from an extremely isolated population, the Island of Kosrae, Federated States of Micronesia. We report that mixed models optimally extract association information from such samples, demonstrating 88% power to rank the true variant as among the top 10 genome-wide with 56% achieving genome-wide significance, a >80% improvement over the other methods, and demonstrate that population isolates have similar power to non-isolate populations for observing variants of known effects. We then used the mixed-model method to reanalyze data for 17 published phenotypes relating to metabolic traits and electrocardiographic measures, along with another 8 previously unreported. We replicate nine genome-wide significant associations with known loci of plasma cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, thyroid stimulating hormone, homocysteine, C-reactive protein and uric acid, with only one detected in the previous analysis of the same traits. Further, we leveraged shared identity-by-descent genetic segments in the region of the uric acid locus to fine-map the signal, refining the known locus by a factor of 4. Finally, we report a novel associations for height (rs17629022, P< 2.1 × 10−8

Analysis of 6,515 exomes reveals a recent origin of most human protein-coding variants

Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history1,2 and will help facilitate the development of new approaches for disease gene discovery3. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth4-6, notable for an excess of rare genetic variants, qualitatively suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European (n=4,298) and African (n=2,217) American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that ~73% of all protein-coding SNVs and ~86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs compared to other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker purifying selection due to the out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, illustrate the profound effect recent human history has had on the burden of deleterious SNVs segregating in contemporary populations, and provides important practical information that can be used to prioritize variants in disease gene discovery

Genetic Modulation of Lipid Profiles following Lifestyle Modification or Metformin Treatment: the Diabetes Prevention Program

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P=0.04–1×10$^{−17}$). Except for total HDL particles (r=−0.03, P=0.26), all components of the lipid profile correlated with the GRS (partial |r|=0.07–0.17, P=5×10$^{−5}$–1×10$^{−19}$). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β=+0.87, SEE±0.22 mg/dl/allele, P=8×10−5, P$_{interaction}$=0.02) in the lifestyle intervention group, but not in the placebo (β=+0.20, SEE±0.22 mg/dl/allele, P=0.35) or metformin (β=−0.03, SEE±0.22 mg/dl/allele, P=0.90; P$_{interaction}$=0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β=+0.30, SEE±0.012 ln nmol/L/allele, P=0.01, P$_{interaction}$=0.01) but not in the placebo (β=−0.002, SEE±0.008 ln nmol/L/allele, P=0.74) or metformin (β=+0.013, SEE±0.008 nmol/L/allele, P=0.12; P$_{interaction}$ = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss

A Theory of the Longitudinal and Hall Conductivities of the Cuprate Superconductors

We establish the applicability to transport phenomena in the cuprate superconductors of a nearly antiferromagnetic Fermi liquid (NAFL) description of the magnetic interaction between planar quasiparticles by using it to obtain the temperature dependent resistivity and Hall conductivity seen experimentally in the normal state. Following a perturbative calculation of the anisotropic (as one goes around the Fermi surface) quasiparticle lifetimes which are the hallmark of a NAFL, we obtain simple approximate expressions for the longitudinal, $\sigma_{xx}$, and Hall, $\sigma_{xy}$, conductivities which reflect the magnetic crossovers seen experimentally as one varies the doping level and temperature. We present a simple phenomenological model for the variation in mean free path around the Fermi surface, and use this to extract from experiments on $\sigma_{xx}$ and $\sigma_{xy}$ quasiparticle lifetimes in the hot (strongly coupled quasiparticle) and cold (weakly coupled quasiparticle) regions of the Fermi surface which are consistent with the perturbation theory estimates. We improve upon the latter by carrying out direct numerical (non-variational) solutions of the Boltzmann equation for representative members of the YBa$_2$Cu$_3$O$_{6+x}$ and La$_{2-x}$Sr$_x$CuO$_4$ systems, with results for transport properties in quantitative agreement with experiment. Using the same numerical approach we study the influence of CuO chains on the a-b plane anisotropy and find results in agreement with experimental findings in YBa$_2$Cu$_4$O$_8$.Comment: 49 pages + 24 PostScript figure