Systematic detection of putative tumor suppressor genes through the combined use of exome and transcriptome sequencing

Abstract Background To identify potential tumor suppressor genes, genome-wide data from exome and transcriptome sequencing were combined to search for genes with loss of heterozygosity and allele-specific expression. The analysis was conducted on the breast cancer cell line HCC1954, and a lymphoblast cell line from the same individual, HCC1954BL. Results By comparing exome sequences from the two cell lines, we identified loss of heterozygosity events at 403 genes in HCC1954 and at one gene in HCC1954BL. The combination of exome and transcriptome sequence data also revealed 86 and 50 genes with allele specific expression events in HCC1954 and HCC1954BL, which comprise 5.4% and 2.6% of genes surveyed, respectively. Many of these genes identified by loss of heterozygosity and allele-specific expression are known or putative tumor suppressor genes, such as BRCA1, MSH3 and SETX, which participate in DNA repair pathways. Conclusions Our results demonstrate that the combined application of high throughput sequencing to exome and allele-specific transcriptome analysis can reveal genes with known tumor suppressor characteristics, and a shortlist of novel candidates for the study of tumor suppressor activities

Simulating the interannual variability of major dust storms on Mars using variable lifting thresholds

The redistribution of a finite amount of martian surface dust during global dust storms and in the intervening periods has been modelled in a dust lifting version of the UK Mars General Circulation Model. When using a constant, uniform threshold in the model’s wind stress lifting parameterisation and assuming an unlimited supply of surface dust, multiannual simulations displayed some variability in dust lifting activity from year to year, arising from internal variability manifested in surface wind stress, but dust storms were limited in size and formed within a relatively short seasonal window. Lifting thresholds were then allowed to vary at each model gridpoint, dependent on the rates of emission or deposition of dust. This enhanced interannual variability in dust storm magnitude and timing, such that model storms covered most of the observed ranges in size and initiation date within a single multiannual simulation. Peak storm magnitude in a given year was primarily determined by the availability of surface dust at a number of key sites in the southern hemisphere. The observed global dust storm (GDS) frequency of roughly one in every 3 years was approximately reproduced, but the model failed to generate these GDSs spontaneously in the southern hemisphere, where they have typically been observed to initiate. After several years of simulation, the surface threshold field—a proxy for net change in surface dust density—showed good qualitative agreement with the observed pattern of martian surface dust cover. The model produced a net northward cross-equatorial dust mass flux, which necessitated the addition of an artificial threshold decrease rate in order to allow the continued generation of dust storms over the course of a multiannual simulation. At standard model resolution, for the southward mass flux due to cross-equatorial flushing storms to offset the northward flux due to GDSs on a timescale of ∼3 years would require an increase in the former by a factor of 3–4. Results at higher model resolution and uncertainties in dust vertical profiles mean that quasi-periodic redistribution of dust on such a timescale nevertheless appears to be a plausible explanation for the observed GDS frequency

Exclusive neuronal expression of SUCLA2 in the human brain

SUCLA2 encodes the ATP-forming subunit (A-SUCL-) of succinyl-CoA ligase, an enzyme of the citric acid cycle. Mutations in SUCLA2 lead to a mitochondrial disorder manifesting as encephalomyopathy with dystonia, deafness and lesions in the basal ganglia. Despite the distinct brain pathology associated with SUCLA2 mutations, the precise localization of SUCLA2 protein has never been investigated. Here we show that immunoreactivity of A-SUCL- in surgical human cortical tissue samples was present exclusively in neurons, identified by their morphology and visualized by double labeling with a fluorescent Nissl dye. A-SUCL- immunoreactivity co-localized >99% with that of the d subunit of the mitochondrial F0-F1 ATP synthase. Specificity of the anti-A-SUCL- antiserum was verified by the absence of labeling in fibroblasts from a patient with a complete deletion of SUCLA2. A-SUCL- immunoreactivity was absent in glial cells, identified by antibodies directed against the glial markers GFAP and S100. Furthermore, in situ hybridization histochemistry demonstrated that SUCLA2 mRNA was present in Nissl-labeled neurons but not glial cells labeled with S100. Immunoreactivity of the GTP-forming subunit (G-SUCL-) encoded by SUCLG2, or in situ hybridization histochemistry for SUCLG2 mRNA could not be demonstrated in either neurons or astrocytes. Western blotting of post mortem brain samples revealed minor G-SUCL- immunoreactivity that was however, not upregulated in samples obtained from diabetic versus non-diabetic patients, as has been described for murine brain. Our work establishes that SUCLA2 is expressed exclusively in neurons in the human cerebral cortex

The solsticial pause on Mars: 1. A planetary wave reanalysis

Large-scale planetary waves are diagnosed from an analysis of profiles retrieved from the Thermal Emission Spectrometer aboard the Mars Global Surveyor spacecraft during its scientific mapping phase. The analysis is conducted by assimilating thermal profiles and total dust opacity retrievals into a Mars global circulation model. Transient waves are largest throughout the northern hemisphere autumn, winter and spring period and almost absent during the summer. The southern hemisphere exhibits generally weaker transient wave behaviour. A striking feature of the low-altitude transient waves in the analysis is that they show a broad subsidiary minimum in amplitude centred on the winter solstice, a period when the thermal contrast between the summer hemisphere and the winter pole is strongest and baroclinic wave activity might be expected to be strong. This behaviour, here called the ‘solsticial pause,’ is present in every year of the analysis. This strong pause is under-represented in many independent model experiments, which tend to produce relatively uniform baroclinic wave activity throughout the winter. This paper documents and diagnoses the transient wave solsticial pause found in the analysis; a companion paper investigates the origin of the phenomenon in a series of model experiments

Whole-genome cancer analysis as an approach to deeper understanding of tumour biology

Recent advances in DNA sequencing technology are providing unprecedented opportunities for comprehensive analysis of cancer genomes, exomes, transcriptomes, as well as epigenomic components. The integration of these data sets with well-annotated phenotypic and clinical data will expedite improved interventions based on the individual genomics of the patient and the specific disease

Quantitative PCR tissue expression profiling of the human SGLT2 gene and related family members

SGLT2 (for “Sodium GLucose coTransporter” protein 2) is the major protein responsible for glucose reabsorption in the kidney and its inhibition has been the focus of drug discovery efforts to treat type 2 diabetes. In order to better clarify the human tissue distribution of expression of SGLT2 and related members of this cotransporter class, we performed TaqMan™ (Applied Biosystems, Foster City, CA, USA) quantitative polymerase chain reaction (PCR) analysis of SGLT2 and other sodium/glucose transporter genes on RNAs from 72 normal tissues from three different individuals. We consistently observe that SGLT2 is highly kidney specific while SGLT5 is highly kidney abundant; SGLT1, sodium-dependent amino acid transporter (SAAT1), and SGLT4 are highly abundant in small intestine and skeletal muscle; SGLT6 is expressed in the central nervous system; and sodium myoinositol cotransporter is ubiquitously expressed across all human tissues

Aspects of coverage in medical DNA sequencing

<p>Abstract</p> <p>Background</p> <p>DNA sequencing is now emerging as an important component in biomedical studies of diseases like cancer. Short-read, highly parallel sequencing instruments are expected to be used heavily for such projects, but many design specifications have yet to be conclusively established. Perhaps the most fundamental of these is the redundancy required to detect sequence variations, which bears directly upon genomic coverage and the consequent resolving power for discerning somatic mutations.</p> <p>Results</p> <p>We address the medical sequencing coverage problem via an extension of the standard mathematical theory of haploid coverage. The expected diploid multi-fold coverage, as well as its generalization for aneuploidy are derived and these expressions can be readily evaluated for any project. The resulting theory is used as a scaling law to calibrate performance to that of standard BAC sequencing at 8× to 10× redundancy, i.e. for expected coverages that exceed 99% of the unique sequence. A differential strategy is formalized for tumor/normal studies wherein tumor samples are sequenced more deeply than normal ones. In particular, both tumor alleles should be detected at least twice, while both normal alleles are detected at least once. Our theory predicts these requirements can be met for tumor and normal redundancies of approximately 26× and 21×, respectively. We explain why these values do not differ by a factor of 2, as might intuitively be expected. Future technology developments should prompt even deeper sequencing of tumors, but the 21× value for normal samples is essentially a constant.</p> <p>Conclusion</p> <p>Given the assumptions of standard coverage theory, our model gives pragmatic estimates for required redundancy. The differential strategy should be an efficient means of identifying potential somatic mutations for further study.</p

Bayesian profiling of molecular signatures to predict event times

BACKGROUND: It is of particular interest to identify cancer-specific molecular signatures for early diagnosis, monitoring effects of treatment and predicting patient survival time. Molecular information about patients is usually generated from high throughput technologies such as microarray and mass spectrometry. Statistically, we are challenged by the large number of candidates but only a small number of patients in the study, and the right-censored clinical data further complicate the analysis. RESULTS: We present a two-stage procedure to profile molecular signatures for survival outcomes. Firstly, we group closely-related molecular features into linkage clusters, each portraying either similar or opposite functions and playing similar roles in prognosis; secondly, a Bayesian approach is developed to rank the centroids of these linkage clusters and provide a list of the main molecular features closely related to the outcome of interest. A simulation study showed the superior performance of our approach. When it was applied to data on diffuse large B-cell lymphoma (DLBCL), we were able to identify some new candidate signatures for disease prognosis. CONCLUSION: This multivariate approach provides researchers with a more reliable list of molecular features profiled in terms of their prognostic relationship to the event times, and generates dependable information for subsequent identification of prognostic molecular signatures through either biological procedures or further data analysis