Use of Systems Biology Approaches to Analysis of Genome-Wide Association Studies of Myocardial Infarction and Blood Cholesterol in the Nurses' Health Study and Health Professionals’ Follow-Up Study

With the advance of genome-wide association studies and newly identified SNP (single-nucleotide polymorphism) associations with complex disease, important discoveries have emerged focusing not only on individual genes but on disease-associated pathways and gene sets. The authors used prospective myocardial infarction case-control studies nested in the Nurses’ Health and Health Professionals Follow-Up Studies to investigate genetic variants associated with myocardial infarction or LDL, HDL, triglycerides, adiponectin and apolipoprotein B (apoB). Using these case-control studies to illustrate an integrative systems biology approach, the authors applied SNP set enrichment analysis to identify gene sets where expression SNPs representing genes from these sets show enrichment in their association with endpoints of interest. The authors also explored an aggregate score approach. While power limited one’s ability to detect significance for association of individual loci with myocardial infarction, the authors found significance for loci associated with LDL, HDL, apoB and triglycerides, replicating previous observations. Applying SNP set enrichment analysis and risk score methods, the authors also found significance for three gene sets and for aggregate scores associated with myocardial infarction as well as for loci-related to cardiovascular risk factors, supporting the use of these methods in practice

Electric-field-induced phase transition of <001> oriented Pb(Mg1/3Nb2/3)O3-PbTiO3 single crystals

oriented 0.7Pb(Mg1/3Nb2/3)O3-0.3PbTiO3 single crystals were poled under different electric fields, i.e. Epoling=4 kV/cm and Epoling=13 kV/cm. In addition to the temperature-dependent dielectric constant measurement, X-ray diffraction was also used to identify the poling-induced phase transitions. Results showed that the phase transition significantly depends on the poling intensity. A weaker field (Epoling=4 kV/cm) can overcome the effect of random internal field to perform the phase transition from rhombohedral ferroelectric state with short range ordering (microdomain) FESRO to rhombohedral ferroelectric state with long range ordering (macrodomain) FElRO. But the rhombohedral ferroelectric to tetragonal ferroelectric phase transition originating from to polarization rotation can only be induced by a stronger field (Epoling=13 kV/cm). The sample poled at Epoling=4 kV/cm showed higher piezoelectric constant, d33>1500 pC/N, than the sample poled at Epoling=13 kV/cm.Comment: 7 pages, 2 figure

Imaging cell lineage with a synthetic digital recording system

Cell lineage plays a pivotal role in cell fate determination. Chow et al. demonstrate the use of an integrase-based synthetic barcode system called intMEMOIR, which uses the serine integrase Bxb1 to perform irreversible nucleotide edits. Inducible editing either deletes or inverts its target region, thus encoding information in three-state memory elements, or trits, and avoiding undesired recombination events. Using intMEMOIR combined with single-molecule fluorescence in situ hybridization, the authors were able to identify clonal structures as well as gene expression patterns in the fly brain, enabling both clonal analysis and expression profiling with intact spatial information. The ability to visualize cell lineage relationships directly within their native tissue context provides insights into development and disease

Imaging cell lineage with a synthetic digital recording system

Multicellular development depends on the differentiation of cells into specific fates with precise spatial organization. Lineage history plays a pivotal role in cell fate decisions, but is inaccessible in most contexts. Engineering cells to actively record lineage information in a format readable in situ would provide a spatially resolved view of lineage in diverse developmental processes. Here, we introduce a serine integrase-based recording system that allows in situ readout, and demonstrate its ability to reconstruct lineage relationships in cultured stem cells and flies. The system, termed intMEMOIR, employs an array of independent three-state genetic memory elements that can recombine stochastically and irreversibly, allowing up to 59,049 distinct digital states. intMEMOIR accurately reconstructed lineage trees in stem cells and enabled simultaneous analysis of single cell clonal history, spatial position, and gene expression in Drosophila brain sections. These results establish a foundation for microscopy-readable clonal analysis and recording in diverse systems

Twinning superlattices in indium phosphide nanowires

Here, we show that we control the crystal structure of indium phosphide (InP) nanowires by impurity dopants. We have found that zinc decreases the activation barrier for 2D nucleation growth of zinc-blende InP and therefore promotes the InP nanowires to crystallise in the zinc blende, instead of the commonly found wurtzite crystal structure. More importantly, we demonstrate that we can, by controlling the crystal structure, induce twinning superlattices with long-range order in InP nanowires. We can tune the spacing of the superlattices by the wire diameter and the zinc concentration and present a model based on the cross-sectional shape of the zinc-blende InP nanowires to quantitatively explain the formation of the periodic twinning.Comment: 18 pages, 4 figure

Calibrating the Performance of SNP Arrays for Whole-Genome Association Studies

To facilitate whole-genome association studies (WGAS), several high-density SNP genotyping arrays have been developed. Genetic coverage and statistical power are the primary benchmark metrics in evaluating the performance of SNP arrays. Ideally, such evaluations would be done on a SNP set and a cohort of individuals that are both independently sampled from the original SNPs and individuals used in developing the arrays. Without utilization of an independent test set, previous estimates of genetic coverage and statistical power may be subject to an overfitting bias. Additionally, the SNP arrays' statistical power in WGAS has not been systematically assessed on real traits. One robust setting for doing so is to evaluate statistical power on thousands of traits measured from a single set of individuals. In this study, 359 newly sampled Americans of European descent were genotyped using both Affymetrix 500K (Affx500K) and Illumina 650Y (Ilmn650K) SNP arrays. From these data, we were able to obtain estimates of genetic coverage, which are robust to overfitting, by constructing an independent test set from among these genotypes and individuals. Furthermore, we collected liver tissue RNA from the participants and profiled these samples on a comprehensive gene expression microarray. The RNA levels were used as a large-scale set of quantitative traits to calibrate the relative statistical power of the commercial arrays. Our genetic coverage estimates are lower than previous reports, providing evidence that previous estimates may be inflated due to overfitting. The Ilmn650K platform showed reasonable power (50% or greater) to detect SNPs associated with quantitative traits when the signal-to-noise ratio (SNR) is greater than or equal to 0.5 and the causal SNP's minor allele frequency (MAF) is greater than or equal to 20% (N = 359). In testing each of the more than 40,000 gene expression traits for association to each of the SNPs on the Ilmn650K and Affx500K arrays, we found that the Ilmn650K yielded 15% times more discoveries than the Affx500K at the same false discovery rate (FDR) level

Inferring Loss-of-Heterozygosity from Unpaired Tumors Using High-Density Oligonucleotide SNP Arrays

Loss of heterozygosity (LOH) of chromosomal regions bearing tumor suppressors is a key event in the evolution of epithelial and mesenchymal tumors. Identification of these regions usually relies on genotyping tumor and counterpart normal DNA and noting regions where heterozygous alleles in the normal DNA become homozygous in the tumor. However, paired normal samples for tumors and cell lines are often not available. With the advent of oligonucleotide arrays that simultaneously assay thousands of single-nucleotide polymorphism (SNP) markers, genotyping can now be done at high enough resolution to allow identification of LOH events by the absence of heterozygous loci, without comparison to normal controls. Here we describe a hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome. When we applied the method to data genotyped on 100 K arrays, we correctly identified 99% of SNP markers as either retention or loss. We also correctly identified 81% of the regions of LOH, including 98% of regions greater than 3 megabases. By integrating copy number analysis into the method, we were able to distinguish LOH from allelic imbalance. Application of this method to data from a set of prostate samples without paired normals identified known regions of prevalent LOH. We have developed a method for analyzing high-density oligonucleotide SNP array data to accurately identify of regions of LOH and retention in tumors without the need for paired normal samples