Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls

Clinical adoption of human genome sequencing requires methods that output genotypes with known accuracy at millions or billions of positions across a genome. Because of substantial discordance among calls made by existing sequencing methods and algorithms, there is a need for a highly accurate set of genotypes across a genome that can be used as a benchmark. Here we present methods to make high-confidence, single-nucleotide polymorphism (SNP), indel and homozygous reference genotype calls for NA12878, the pilot genome for the Genome in a Bottle Consortium. We minimize bias toward any method by integrating and arbitrating between 14 data sets from five sequencing technologies, seven read mappers and three variant callers. We identify regions for which no confident genotype call could be made, and classify them into different categories based on reasons for uncertainty. Our genotype calls are publicly available on the Genome Comparison and Analytic Testing website to enable real-time benchmarking of any method

In Vitro Ceramic Scaffold Mineralization: Comparison Between Histological and Micro-Computed Tomographical Analysis

The porous structure of beta-tricalcium phosphate (β-TCP) scaffolds was assessed by conventional histomorphometry and micro-computed tomography (micro-CT) to evaluate the substitutability of time-consuming histomorphometry by rapid micro-CT. Extracellular matrix mineralization on human mesenchymal stem cell seeded β-TCP scaffolds was scanned by means of micro-CT after 6weeks in cultivation and evaluated morphometrically. For the histomorphometric analysis, undecalcified sections were prepared in the mediosagittal plane of the cylindrical tissue-engineered constructs. The sections were scanned at a nominal resolution of 8μm and stained with von Kossa and Toluidine Blue. Pores were analyzed with both methods for morphometrical parameters such as horizontal/vertical diameter and pore/mineralized tissue area. Results showed highly significant correlations between histomorphometry and micro-CT for pore horizontal length (r=0.95), pore vertical length (r=0.96), pore area (r=0.97), and mineralized tissue area (r=0.82). Mean percentage differences between histomorphometry and micro-CT measurements ranged from 1.4% (pore vertical diameter) to 14.0% (area of mineralized tissue). With its high image precision, micro-CT qualifies as an additional tool for endpoint evaluation measurements of mineralized tissue development within tissue-engineered constructs also in ceramic scaffold

A comprehensive promoter landscape identifies a novel promoter for CD133 in restricted tissues, cancers, and stem cells

PROM1 is the gene encoding prominin-1 or CD133, an important cell surface marker for the isolation of both normal and cancer stem cells. PROM1 transcripts initiate at a range of transcription start sites (TSS) associated with distinct tissue and cancer expression profiles. Using high resolution Cap Analysis of Gene Expression (CAGE) sequencing we characterize TSS utilization across a broad range of normal and developmental tissues. We identify a novel proximal promoter (P6) within CD133+ melanoma cell lines and stem cells. Additional exon array sampling finds P6 to be active in populations enriched for mesenchyme, neural stem cells and within CD133+ enriched Ewing sarcomas. The P6 promoter is enriched with respect to previously characterized PROM1 promoters for a HMGI/Y (HMGA1) family transcription factor binding site motif and exhibits different epigenetic modifications relative to the canonical promoter region of PROM1

Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis

Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable in the clinical management or treatment of ovarian cancer

Integrating Murine Gene Expression Studies to Understand Obstructive Lung Disease due to Chronic Inhaled Endotoxin

Rationale: Endotoxin is a near ubiquitous environmental exposure that that has been associated with both asthma and chronic obstructive pulmonary disease (COPD). These obstructive lung diseases have a complex pathophysiology, making them difficult to study comprehensively in the context of endotoxin. Genome-wide gene expression studies have been used to identify a molecular snapshot of the response to environmental exposures. Identification of differentially expressed genes shared across all published murine models of chronic inhaled endotoxin will provide insight into the biology underlying endotoxin-associated lung disease. Methods: We identified three published murine models with gene expression profiling after repeated low-dose inhaled endotoxin. All array data from these experiments were re-analyzed, annotated consistently, and tested for shared genes found to be differentially expressed. Additional functional comparison was conducted by testing for significant enrichment of differentially expressed genes in known pathways. The importance of this gene signature in smoking-related lung disease was assessed using hierarchical clustering in an independent experiment where mice were exposed to endotoxin, smoke, and endotoxin plus smoke. Results: A 101-gene signature was detected in three murine models, more than expected by chance. The three model systems exhibit additional similarity beyond shared genes when compared at the pathway level, with increasing enrichment of inflammatory pathways associated with longer duration of endotoxin exposure. Genes and pathways important in both asthma and COPD were shared across all endotoxin models. Mice exposed to endotoxin, smoke, and smoke plus endotoxin were accurately classified with the endotoxin gene signature. Conclusions: Despite the differences in laboratory, duration of exposure, and strain of mouse used in three experimental models of chronic inhaled endotoxin, surprising similarities in gene expression were observed. The endotoxin component of tobacco smoke may play an important role in disease development

A singlet triplet hole spin qubit in planar Ge

Spin qubits are considered to be among the most promising candidates for building a quantum processor. GroupIV hole spin qubits have moved into the focus of interest due to the ease of operation and compatibility with Si technology. In addition, Ge offers the option for monolithic superconductor-semiconductor integration. Here we demonstrate a hole spin qubit operating at fields below 10 mT, the critical field of Al, by exploiting the large out-of-plane hole g-factors in planar Ge and by encoding the qubit into the singlet-triplet states of a double quantum dot. We observe electrically controlled g-factor-difference-driven and exchange-driven rotations with tunable frequencies exceeding 100 MHz and dephasing times of 1 $\mu$s which we extend beyond 150 $\mu$s with echo techniques. These results demonstrate that Ge hole singlet-triplet qubits are competing with state-of-the art GaAs and Si singlet-triplet qubits. In addition, their rotation frequencies and coherence are on par with Ge single spin qubits, but they can be operated at much lower fields underlining their potential for on chip integration with superconducting technologies

The Fermi energy as common parameter to describe charge compensation mechanisms: A path to Fermi level engineering of oxide electroceramics

Chemical substitution, which can be iso- or heterovalent, is the primary strategy to tailor material properties. There are various ways how a material can react to substitution. Isovalent substitution changes the density of states while heterovalent substitution, i.e. doping, can induce electronic compensation, ionic compensation, valence changes of cations or anions, or result in the segregation or neutralization of the dopant. While all these can, in principle, occur simultaneously, it is often desirable to select a certain mechanism in order to determine material properties. Being able to predict and control the individual compensation mechanism should therefore be a key target of materials science. This contribution outlines the perspective that this could be achieved by taking the Fermi energy as a common descriptor for the different compensation mechanisms. This generalization becomes possible since the formation enthalpies of the defects involved in the various compensation mechanisms do all depend on the Fermi energy. In order to control material properties, it is then necessary to adjust the formation enthalpies and charge transition levels of the involved defects. Understanding how these depend on material composition will open up a new path for the design of materials by Fermi level engineering

Genetic resistance to JAK2 enzymatic inhibitors is overcome by HSP90 inhibition

Enzymatic inhibitors of Janus kinase 2 (JAK2) are in clinical development for the treatment of myeloproliferative neoplasms (MPNs), B cell acute lymphoblastic leukemia (B-ALL) with rearrangements of the cytokine receptor subunit cytokine receptor–like factor 2 (CRLF2), and other tumors with constitutive JAK2 signaling. In this study, we identify G935R, Y931C, and E864K mutations within the JAK2 kinase domain that confer resistance across a panel of JAK inhibitors, whether present in cis with JAK2 V617F (observed in MPNs) or JAK2 R683G (observed in B-ALL). G935R, Y931C, and E864K do not reduce the sensitivity of JAK2-dependent cells to inhibitors of heat shock protein 90 (HSP90), which promote the degradation of both wild-type and mutant JAK2. HSP90 inhibitors were 100–1,000-fold more potent against CRLF2-rearranged B-ALL cells, which correlated with JAK2 degradation and more extensive blockade of JAK2/STAT5, MAP kinase, and AKT signaling. In addition, the HSP90 inhibitor AUY922 prolonged survival of mice xenografted with primary human CRLF2-rearranged B-ALL further than an enzymatic JAK2 inhibitor. Thus, HSP90 is a promising therapeutic target in JAK2-driven cancers, including those with genetic resistance to JAK enzymatic inhibitors