Genomic characterization of Gli-activator targets in sonic hedgehog-mediated neural patterning

Sonic hedgehog (Shh) acts as a morphogen to mediate the specification of distinct cell identities in the ventral neural tube through a Gli-mediated (Gli1-3) transcriptional network. Identifying Gli targets in a systematic fashion is central to the understanding of the action of Shh. We examined this issue in differentiating neural progenitors in mouse. An epitope-tagged Gli-activator protein was used to directly isolate cis-regulatory sequences by chromatin immunoprecipitation (ChIP). ChIP products were then used to screen custom genomic tiling arrays of putative Hedgehog (Hh) targets predicted from transcriptional profiling studies, surveying 50-150 kb of non-transcribed sequence for each candidate. In addition to identifying expected Gli-target sites, the data predicted a number of unreported direct targets of Shh action. Transgenic analysis of binding regions in Nkx2.2, Nkx2.1 (Titf1) and Rab34 established these as direct Hh targets. These data also facilitated the generation of an algorithm that improved in silico predictions of Hh target genes. Together, these approaches provide significant new insights into both tissue-specific and general transcriptional targets in a crucial Shh-mediated patterning process

Stratigraphy and chronology of a 15ka sequence of multi-sourced silicic tephras in a montane peat bog, eastern North Island, New Zealand.

We document the stratigraphy, composition, and chronology of a succession of 16 distal, silicic tephra layers interbedded with lateglacial and Holocene peats and muds up to c. 15 000 radiocarbon years (c. 18 000 calendar years) old at a montane site (Kaipo Bog) in eastern North Island, New Zealand. Aged from 665 +/- 15 to 14 700 +/- 95 14C yr BP, the tephras are derived from six volcanic centres in North Island, three of which are rhyolitic (Okataina, Taupo, Maroa), one peralkaline (Tuhua), and two andesitic (Tongariro, Egmont). Correlations are based on multiple criteria: field properties and stratigraphic interrelationships, ferromagnesian silicate mineral assemblages, glass-shard major element composition (from electron microprobe analysis), and radiocarbon dating. We extend the known distribution of tephras in eastern North Island and provide compositional data that add to their potential usefulness as isochronous markers. The chronostratigraphic framework established for the Kaipo sequence, based on both site-specific and independently derived tephra-based radiocarbon ages, provides the basis for fine-resolution paleoenvironmental studies at a climatically sensitive terrestrial site from the mid latitudes of the Southern Hemisphere. Tephras identified as especially useful paleoenvironmental markers include Rerewhakaaitu and Waiohau (lateglacial), Konini (lateglacial-early Holocene), Tuhua (middle Holocene), and Taupo and Kaharoa (late Holocene)

Functional brain defects in a mouse model of a chromosomal t(1;11) translocation that disrupts DISC1 and confers increased risk of psychiatric illness

A balanced t(1;11) translocation that directly disrupts DISC1 is linked to schizophrenia and affective disorders. We previously showed that a mutant mouse, named Der1, recapitulates the effect of the translocation upon DISC1 expression. Here, RNAseq analysis of Der1 mouse brain tissue found enrichment for dysregulation of the same genes and molecular pathways as in neuron cultures generated previously from human t(1;11) translocation carriers via the induced pluripotent stem cell route. DISC1 disruption therefore apparently accounts for a substantial proportion of the effects of the t(1;11) translocation. RNAseq and pathway analysis of the mutant mouse predicts multiple Der1-induced alterations converging upon synapse function and plasticity. Synaptosome proteomics confirmed that the Der1 mutation impacts synapse composition, and electrophysiology found reduced AMPA:NMDA ratio in hippocampal neurons, indicating changed excitatory signalling. Moreover, hippocampal parvalbumin-positive interneuron density is increased, suggesting that the Der1 mutation affects inhibitory control of neuronal circuits. These phenotypes predict that neurotransmission is impacted at many levels by DISC1 disruption in human t(1;11) translocation carriers. Notably, genes implicated in schizophrenia, depression and bipolar disorder by large-scale genetic studies are enriched among the Der1-dysregulated genes, just as we previously observed for the t(1;11) translocation carrier-derived neurons. Furthermore, RNAseq analysis predicts that the Der1 mutation primarily targets a subset of cell types, pyramidal neurons and interneurons, previously shown to be vulnerable to the effects of common schizophrenia-associated genetic variants. In conclusion, DISC1 disruption by the t(1;11) translocation may contribute to the psychiatric disorders of translocation carriers through commonly affected pathways and processes in neurotransmission

Tephrochronology and its application: A review

Tephrochronology (from tephra, Gk ‘ashes’) is a unique stratigraphic method for linking, dating, and synchronizing geological, palaeoenvironmental, or archaeological sequences or events. As well as utilising the Law of Superposition, tephrochronology in practise requires tephra deposits to be characterized (or ‘fingerprinted’) using physical properties evident in the field together with those obtained from laboratory analyses. Such analyses include mineralogical examination (petrography) or geochemical analysis of glass shards or crystals using an electron microprobe or other analytical tools including laser-ablation-based mass spectrometry or the ion microprobe. The palaeoenvironmental or archaeological context in which a tephra occurs may also be useful for correlational purposes. Tephrochronology provides greatest utility when a numerical age obtained for a tephra or cryptotephra is transferrable from one site to another using stratigraphy and by comparing and matching inherent compositional features of the deposits with a high degree of likelihood. Used this way, tephrochronology is an age-equivalent dating method that provides an exceptionally precise volcanic-event stratigraphy. Such age transfers are valid because the primary tephra deposits from an eruption essentially have the same short-lived age everywhere they occur, forming isochrons very soon after the eruption (normally within a year). As well as providing isochrons for palaeoenvironmental and archaeological reconstructions, tephras through their geochemical analysis allow insight into volcanic and magmatic processes, and provide a comprehensive record of explosive volcanism and recurrence rates in the Quaternary (or earlier) that can be used to establish time-space relationships of relevance to volcanic hazard analysis. The basis and application of tephrochronology as a central stratigraphic and geochronological tool for Quaternary studies are presented and discussed in this review. Topics covered include principles of tephrochronology, defining isochrons, tephra nomenclature, mapping and correlating tephras from proximal to distal locations at metre- through to sub-millimetre-scale, cryptotephras, mineralogical and geochemical fingerprinting methods, numerical and statistical correlation techniques, and developments and applications in dating including the use of flexible depositional age-modelling techniques based on Bayesian statistics. Along with reference to wide-ranging examples and the identification of important recent advances in tephrochronology, such as the development of new geoanalytical approaches that enable individual small glass shards to be analysed near-routinely for major, trace, and rare-earth elements, potential problems such as miscorrelation, erroneous-age transfer, and tephra reworking and taphonomy (especially relating to cryptotephras) are also examined. Some of the challenges for future tephrochronological studies include refining geochemical analytical methods further, improving understanding of cryptotephra distribution and preservation patterns, improving age modelling including via new or enhanced radiometric or incremental techniques and Bayesian-derived models, evaluating and quantifying uncertainty in tephrochronology to a greater degree than at present, constructing comprehensive regional databases, and integrating tephrochronology with spatially referenced environmental and archaeometric data into 3-D reconstructions using GIS and geostatistics

A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density.

INTRODUCTION: Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. METHODS: The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. RESULTS: No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02). CONCLUSIONS: The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13058-015-0625-

Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology

Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens.Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667).Results: Upper and lower 95% limits of agreement were 7.1 and −6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = −0.42, p = 0.01, 95% confidence interval (CI) −0.22 to −0.59 for ADC; r = −0.45, p = 0.005, 95% CI −0.25 to −0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10−7, 95% CI 0.69–0.86).Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas

Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.ABCFS: The Australian Breast Cancer Family Registry (ABCFR; 1992-1995) was supported by the Australian NHMRC, the New South Wales Cancer Council, and the Victorian Health Promotion Foundation (Australia), and by grant UM1CA164920 from the USA National Cancer Institute. The Genetic Epidemiology Laboratory at the University of Melbourne has also received generous support from Mr B. Hovey and Dr and Mrs R.W. Brown to whom we are most grateful. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Breast Cancer Susceptibility Variants and Mammographic Density 5 Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. BBCC: This study was funded in part by the ELAN-Program of the University Hospital Erlangen; Katharina Heusinger was funded by the ELAN program of the University Hospital Erlangen. BBCC was supported in part by the ELAN program of the Medical Faculty, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg. EPIC-Norfolk: This study was funded by research programme grant funding from Cancer Research UK and the Medical Research Council with additional support from the Stroke Association, British Heart Foundation, Department of Health, Research into Ageing and Academy of Medical Sciences. MCBCS: This study was supported by Public Health Service Grants P50 CA 116201, R01 CA 128931, R01 CA 128931-S01, R01 CA 122340, CCSG P30 CA15083, from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. MCCS: Melissa C. Southey is a National Health and Medical Research Council Senior Research Fellow and a Victorian Breast Cancer Research Consortium Group Leader. The study was supported by the Cancer Council of Victoria and by the Victorian Breast Cancer Research Consortium. MEC: National Cancer Institute: R37CA054281, R01CA063464, R01CA085265, R25CA090956, R01CA132839. MMHS: This work was supported by grants from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. (R01 CA128931, R01 CA 128931-S01, R01 CA97396, P50 CA116201, and Cancer Center Support Grant P30 CA15083). Breast Cancer Susceptibility Variants and Mammographic Density 6 NBCS: This study has been supported with grants from Norwegian Research Council (#183621/S10 and #175240/S10), The Norwegian Cancer Society (PK80108002, PK60287003), and The Radium Hospital Foundation as well as S-02036 from South Eastern Norway Regional Health Authority. NHS: This study was supported by Public Health Service Grants CA131332, CA087969, CA089393, CA049449, CA98233, CA128931, CA 116201, CA 122340 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. OOA study was supported by CA122822 and X01 HG005954 from the NIH; Breast Cancer Research Fund; Elizabeth C. Crosby Research Award, Gladys E. Davis Endowed Fund, and the Office of the Vice President for Research at the University of Michigan. Genotyping services for the OOA study were provided by the Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096. OFBCR: This work was supported by grant UM1 CA164920 from the USA National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. SASBAC: The SASBAC study was supported by Märit and Hans Rausing’s Initiative against Breast Cancer, National Institutes of Health, Susan Komen Foundation and Agency for Science, Technology and Research of Singapore (A*STAR). Breast Cancer Susceptibility Variants and Mammographic Density 7 SIBS: SIBS was supported by program grant C1287/A10118 and project grants from Cancer Research UK (grant numbers C1287/8459). COGS grant: Collaborative Oncological Gene-environment Study (COGS) that enabled the genotyping for this study. Funding for the BCAC component is provided by grants from the EU FP7 programme (COGS) and from Cancer Research UK. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post- Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAMEON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.This is the author accepted manuscript. The final version is available via American Association for Cancer Research at http://cancerres.aacrjournals.org/content/early/2015/04/10/0008-5472.CAN-14-2012.abstract

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

Contains fulltext : 158967.pdf (publisher's version ) (Open Access)Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine

Development and validation of a targeted gene sequencing panel for application to disparate cancers

Next generation sequencing has revolutionised genomic studies of cancer, having facilitated the development of precision oncology treatments based on a tumour’s molecular profile. We aimed to develop a targeted gene sequencing panel for application to disparate cancer types with particular focus on tumours of the head and neck, plus test for utility in liquid biopsy. The final panel designed through Roche/Nimblegen combined 451 cancer-associated genes (2.01 Mb target region). 136 patient DNA samples were collected for performance and application testing. Panel sensitivity and precision were measured using well-characterised DNA controls (n = 47), and specificity by Sanger sequencing of the Aryl Hydrocarbon Receptor Interacting Protein (AIP) gene in 89 patients. Assessment of liquid biopsy application employed a pool of synthetic circulating tumour DNA (ctDNA). Library preparation and sequencing were conducted on Illumina-based platforms prior to analysis with our accredited (ISO15189) bioinformatics pipeline. We achieved a mean coverage of 395x, with sensitivity and specificity of >99% and precision of >97%. Liquid biopsy revealed detection to 1.25% variant allele frequency. Application to head and neck tumours/cancers resulted in detection of mutations aligned to published databases. In conclusion, we have developed an analytically-validated panel for application to cancers of disparate types with utility in liquid biopsy

Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the