Revealing the missing expressed genes beyond the human reference genome by RNA-Seq

<p>Abstract</p> <p>Background</p> <p>The complete and accurate human reference genome is important for functional genomics researches. Therefore, the incomplete reference genome and individual specific sequences have significant effects on various studies.</p> <p>Results</p> <p>we used two RNA-Seq datasets from human brain tissues and 10 mixed cell lines to investigate the completeness of human reference genome. First, we demonstrated that in previously identified ~5 Mb Asian and ~5 Mb African novel sequences that are absent from the human reference genome of NCBI build 36, ~211 kb and ~201 kb of them could be transcribed, respectively. Our results suggest that many of those transcribed regions are not specific to Asian and African, but also present in Caucasian. Then, we found that the expressions of 104 RefSeq genes that are unalignable to NCBI build 37 in brain and cell lines are higher than 0.1 RPKM. 55 of them are conserved across human, chimpanzee and macaque, suggesting that there are still a significant number of functional human genes absent from the human reference genome. Moreover, we identified hundreds of novel transcript contigs that cannot be aligned to NCBI build 37, RefSeq genes and EST sequences. Some of those novel transcript contigs are also conserved among human, chimpanzee and macaque. By positioning those contigs onto the human genome, we identified several large deletions in the reference genome. Several conserved novel transcript contigs were further validated by RT-PCR.</p> <p>Conclusion</p> <p>Our findings demonstrate that a significant number of genes are still absent from the incomplete human reference genome, highlighting the importance of further refining the human reference genome and curating those missing genes. Our study also shows the importance of <it>de novo </it>transcriptome assembly. The comparative approach between reference genome and other related human genomes based on the transcriptome provides an alternative way to refine the human reference genome.</p

Gamification through leaderboards : an empirical study in engineering education

Universities are looking for solutions to engage more students in STEM domains and enhance their learning performance (LP). In this context, gamification is put forward as a solution to achieve this aim. The present study examined the effect of gamification – building on leaderboards ‐ on LP. Furthermore, mediating variables, such as intrinsic motivation, self‐efficacy, engagement, and background variables, such as sex, previous gaming experience, and undergraduate major, were considered. A pretest‐posttest quasi‐experimental design with an experimental and a control condition was set up (n = 89) in an Introductory Computer Programming course. We observed a significant improvement in the LP of students in the gamified condition. However, no interaction effect was detected, due to mediating and background variables. The high learning gain is a favorable indicator that gamification might be a promising approach to promote STEM programs

Titanium based cranial reconstruction using incremental sheet forming

In this paper, we report recent work in cranial plate manufacturing using incremental sheet forming (ISF) process. With a typical cranial shape, the ISF process was used to manufacture the titanium cranial shape by using different ISF tooling solutions with and without backing plates. Detailed evaluation of the ISF process including material deformation and thinning, geometric accuracy and surface finish was conducted by using a combination of experimental testing and Finite Element (FE) simulation. The results show that satisfactory cranial shape can be achieved with sufficient accuracy and surface finish by using a feature based tool path generation method and new ISF tooling design. The results also demonstrate that the ISF based cranial reconstruction has the potential to achieve considerable lead time reduction as compared to conventional methods for cranial plate manufacturing. This outcome indicates that there is a potential for the ISF process to achieve technological advances and economic benefits as well as improvement to quality of life

Pretreatment metabotype as a predictor of response to sertraline or placebo in depressed outpatients: a proof of concept

The purpose of this study was to determine whether the baseline metabolic profile (that is, metabotype) of a patient with major depressive disorder (MDD) would define how an individual will respond to treatment. Outpatients with MDD were randomly assigned to sertraline (up to 150 mg per day) (N=43) or placebo (N=46) in a double-blind 4-week trial. Baseline serum samples were profiled using the liquid chromatography electrochemical array; the output was digitized to create a ‘digital map' of the entire measurable response for a particular sample. Response was defined as ⩾50% reduction baseline to week 4 in the 17-item Hamilton Rating Scale for Depression total score. Models were built using the one-out method for cross-validation. Multivariate analyses showed that metabolic profiles partially separated responders and non-responders to sertraline or to placebo. For the sertraline models, the overall correct classification rate was 81% whereas it was 72% for the placebo models. Several pathways were implicated in separation of responders and non-responders on sertraline and on placebo including phenylalanine, tryptophan, purine and tocopherol. Dihydroxyphenylacetic acid, tocopherols and serotonin were common metabolites in separating responders and non-responders to both drug and placebo. Pretreatment metabotypes may predict which depressed patients will respond to acute treatment (4 weeks) with sertraline or placebo. Some pathways were informative for both treatments whereas other pathways were unique in predicting response to either sertraline or placebo. Metabolomics may inform the biochemical basis for the early efficacy of sertraline

The EIF4EBP3 translational repressor is a marker of CDC73 tumor suppressor haploinsufficiency in a parathyroid cancer syndrome

Germline mutation of the tumor suppressor gene CDC73 confers susceptibility to the hyperparathyroidism-jaw tumor syndrome associated with a high risk of parathyroid malignancy. Inactivating CDC73 mutations have also been implicated in sporadic parathyroid cancer, but are rare in sporadic benign parathyroid tumors. The molecular pathways that distinguish malignant from benign parathyroid transformation remain elusive. We previously showed that a hypomorphic allele of hyrax (hyx), the Drosophila homolog of CDC73, rescues the loss-of-ventral-eye phenotype of lobe, encoding the fly homolog of Akt1s1/ PRAS40. We report now an interaction between hyx and Tor, a central regulator of cell growth and autophagy, and show that eukaryotic translation initiation factor 4E-binding protein (EIF4EBP), a translational repressor and effector of mammalian target of rapamycin (mTOR), is a conserved target of hyx/CDC73. Flies heterozygous for Tor and hyx, but not Mnn1, the homolog of the multiple endocrine neoplasia type 1 (MEN1) tumor suppressor associated with benign parathyroid tumors, are starvation resistant with reduced basal levels of Thor/4E-BP. Human peripheral blood cell levels of EIF4EBP3 were reduced in patients with CDC73, but not MEN1, heterozygosity. Chromatin immunoprecipitation demonstrated occupancy of EIF4EBP3 by endogenous parafibromin. These results show that EIF4EBP3 is a peripheral marker of CDC73 function distinct from MEN1-regulated pathways, and suggest a model whereby starvation resistance and/or translational de-repression contributes to parathyroid malignant transformation

Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk

Studies in post-mortem human brain tissue have associated major depressive disorder (MDD) with cortical transcriptomic changes, whose potential in vivo impact remains unexplored. To address this translational gap, we recently developed a transcriptome-based polygenic risk score (T-PRS) based on common functional variants capturing ‘depression-like’ shifts in cortical gene expression. Here, we used a non-clinical sample of young adults (n = 482, Duke Neurogenetics Study: 53% women; aged 19.8 ± 1.2 years) to map T-PRS onto brain morphology measures, including Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index, as well as broad MDD risk, indexed by self-reported family history of depression. We conducted side-by-side comparisons with a PRS independently derived from a Psychiatric Genomics Consortium (PGC) MDD GWAS (PGC-PRS), and sought to link T-PRS with diagnosis and symptom severity directly in PGC-MDD participants (n = 29,340, 59% women; 12,923 MDD cases, 16,417 controls). T-PRS was associated with smaller amygdala volume in women (t = −3.478, p = 0.001) and lower prefrontal gyrification across sexes. In men, T-PRS was associated with hypergyrification in temporal and occipital regions. Prefrontal hypogyrification mediated a male-specific indirect link between T-PRS and familial depression (b = 0.005, p = 0.029). PGC-PRS was similarly associated with lower amygdala volume and cortical gyrification; however, both effects were male-specific and hypogyrification emerged in distinct parietal and temporo-occipital regions, unassociated with familial depression. In PGC-MDD, T-PRS did not predict diagnosis (OR = 1.007, 95% CI = [0.997–1.018]) but correlated with symptom severity in men (rho = 0.175, p = 7.957 × 10−4) in one cohort (N = 762, 48% men). Depression-like shifts in cortical gene expression have sex-specific effects on brain morphology and may contribute to broad depression vulnerability in men

Long-Term Outcomes in Percutaneous Radiofrequency Ablation for Histologically Proven Colorectal Lung Metastasis

Introduction To evaluate the long-term outcome of image-guided radiofrequency ablation (RFA) when treating histologically confirmed colorectal lung metastasis in terms of overall survival (OS), progression-free survival (PFS) and local tumour control (LTC). Materials and Methods Retrospective single-centre study. Consecutive RFA treatments of histologically proven lung colorectal metastases between 01/01/2008 and 31/12/14. The primary outcome was patient survival (OS and PFS). Secondary outcomes were local tumour progression (LTP) and complications. Prognostic factors associated with OS/ PFS were determined by univariate and multivariate analyses. Results Sixty patients (39 males: 21 females; median age 69 years) and 125 colorectal lung metastases were treated. Eighty percent (n = 48) also underwent lung surgery for lung metastases. Mean metastasis size (cm) was 1.4 ± 0.6 (range 0.3–4.0). Median number of RFA sessions was 1 (1–4). During follow-up (median 45.5 months), 45 patients died (75%). The estimated OS and PFS survival rates at 1, 3, 5, 7, 9 years were 96.7%, 74.7%, 44.1%, 27.5%, 16.3% (median OS, 52 months) and 66.7%, 31.2%, 25.9%, 21.2% and 5.9% (median PFS, 19 months). The LTC rate was 90% with 6 patients developing LTP with 1-, 2-, 3- and 4-year LTP rates of 3.3%, 8.3%, 10.0% and 10.0%. Progression-free interval < 1 year (P = 0.002, HR = 0.375) and total number of pulmonary metastases (≥ 3) treated (P = 0.037, HR = 0.480) were independent negative prognostic factors. Thirty-day mortality rate was 0% with no intra-procedural deaths. Conclusion The long-term OS and PFS following RFA for the treatment of histologically confirmed colorectal lung metastases demonstrate comparable oncological durability to surgery

A miRNA-Target Prediction Case Study

Giansanti, V., Castelli, M., Beretta, S., & Merelli, I. (2019). Comparing Deep and Machine Learning Approaches in Bioinformatics: A miRNA-Target Prediction Case Study. In V. V. Krzhizhanovskaya, M. H. Lees, P. M. A. Sloot, J. J. Dongarra, J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, ... R. Lam (Eds.), Computational Science – ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part III (pp. 31-44). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11538 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-22744-9_3MicroRNAs (miRNAs) are small non-coding RNAs with a key role in the post-transcriptional gene expression regularization, thanks to their ability to link with the target mRNA through the complementary base pairing mechanism. Given their role, it is important to identify their targets and, to this purpose, different tools were proposed to solve this problem. However, their results can be very different, so the community is now moving toward the deployment of integration tools, which should be able to perform better than the single ones. As Machine and Deep Learning algorithms are now in their popular years, we developed different classifiers from both areas to verify their ability to recognize possible miRNA-mRNA interactions and evaluated their performance, showing the potentialities and the limits that those algorithms have in this field. Here, we apply two deep learning classifiers and three different machine learning models to two different miRNA-mRNA datasets, of predictions from 3 different tools: TargetScan, miRanda, and RNAhybrid. Although an experimental validation of the results is needed to better confirm the predictions, deep learning techniques achieved the best performance when the evaluation scores are taken into account.authorsversionpublishe

Lack of PPARγ in Myeloid Cells Confers Resistance to Listeria monocytogenes Infection

The peroxisomal proliferator-activated receptor γ (PPARγ) is a nuclear receptor that controls inflammation and immunity. Innate immune defense against bacterial infection appears to be compromised by PPARγ. The relevance of PPARγ in myeloid cells, that organize anti-bacterial immunity, for the outcome of immune responses against intracellular bacteria such as Listeria monocytogenes in vivo is unknown. We found that Listeria monocytogenes infection of macrophages rapidly led to increased expression of PPARγ. This prompted us to investigate whether PPARγ in myeloid cells influences innate immunity against Listeria monocytogenes infection by using transgenic mice with myeloid-cell specific ablation of PPARγ (LysMCre×PPARγflox/flox). Loss of PPARγ in myeloid cells results in enhanced innate immune defense against Listeria monocytogenes infection both, in vitro and in vivo. This increased resistance against infection was characterized by augmented levels of bactericidal factors and inflammatory cytokines: ROS, NO, IFNγ TNF IL-6 and IL-12. Moreover, myeloid cell-specific loss of PPARγ enhanced chemokine and adhesion molecule expression leading to improved recruitment of inflammatory Ly6Chi monocytes to sites of infection. Importantly, increased resistance against Listeria infection in the absence of PPARγ was not accompanied by enhanced immunopathology. Our results elucidate a yet unknown regulatory network in myeloid cells that is governed by PPARγ and restrains both listeriocidal activity and recruitment of inflammatory monocytes during Listeria infection, which may contribute to bacterial immune escape. Pharmacological interference with PPARγ activity in myeloid cells might represent a novel strategy to overcome intracellular bacterial infection

Foundations of Black Hole Accretion Disk Theory

This review covers the main aspects of black hole accretion disk theory. We begin with the view that one of the main goals of the theory is to better understand the nature of black holes themselves. In this light we discuss how accretion disks might reveal some of the unique signatures of strong gravity: the event horizon, the innermost stable circular orbit, and the ergosphere. We then review, from a first-principles perspective, the physical processes at play in accretion disks. This leads us to the four primary accretion disk models that we review: Polish doughnuts (thick disks), Shakura-Sunyaev (thin) disks, slim disks, and advection-dominated accretion flows (ADAFs). After presenting the models we discuss issues of stability, oscillations, and jets. Following our review of the analytic work, we take a parallel approach in reviewing numerical studies of black hole accretion disks. We finish with a few select applications that highlight particular astrophysical applications: measurements of black hole mass and spin, black hole vs. neutron star accretion disks, black hole accretion disk spectral states, and quasi-periodic oscillations (QPOs).Comment: 91 pages, 23 figures, final published version available at http://www.livingreviews.org/lrr-2013-