Rainfall erosivity attributes on central and western Mauritius

Rainfall can be the most erosive agent with respect to rainfall induced erosion, particularly within the context of a tropical maritime environment. Mauritius provides an example of such an environment, which, due to its location and elevated topography, is subject to frequent erosive rainfall events as well as occasional cyclones which potentially threaten loss of soil and may accelerate land degradation. Such intense rainfall forms a key part of the “R-factor” in the USLE and RUSLE soil loss equations, which are commonly used worldwide in deriving the soil loss of an area. This project focuses on various attributes of rainfall erosivity on the central and western parts of Mauritius over a six year assessment period. A steep rainfall gradient exists; 600mm in the western plains and 4000mm per year in the higher central region. Rainfall and erosivity attributes are investigated in these two regions on the island to assess the role that topographic elevation has on rainfall erosivity. Using the EI30 method to find the “R-factor”, erosivity is calculated for the period of 2003 – 2008. Varying time intervals were used in calculating EI30 to determine the value that high resolution data has in erosivity calculations and is compared to the use of the Modified Fournier Index. This project also speculates on the potential impacts of changing rainfall intensity and erosivity associated with climate change in the future. A difference was found in the erosivity experienced in the elevated central interior and the rain-shadowed western lava plains. Stations on the western plains recorded 25% of the erosivity experienced by stations in the interior and large differences were found in the number of erosive events, rainfall, erosive rainfall totals, seasonality, and annual erosivity totals of erosivity. The central interior showed greater variability in R-factor values; however these remained similar in extent despite the large difference in total annual rainfall and the number of events that each station recorded. High resolution data did account for erosivity that lower resolution does not, but the extent of erosivity for all stations within the respective regions were markedly similar. Use of the Modified Fournier Index caused erosivity to be overestimated on the island when compared to the EI30 method. Changes in erosivity are speculated to occur with changes in rainfall intensities but the central interior of the island will notice fluctuations in climate (with respect to rainfall erosivity) more than the western plains.Dissertation (MSc)--University of Pretoria, 2012.Geography, Geoinformatics and MeteorologyUnrestricte

Temporal sensitivity analysis of erosivity estimations in a high rainfall tropical island environment

The Erosivity Index (EI) and the Modified Fournier Index (MFI) are two commonly used methods in calculating the R factor of the universal soil loss equation/ revised universal soil loss equation formula. Using Mauritius as a case study, the value of high-resolution data versus long-term totals in erosivity calculations is investigated. A limited number of four Mauritius Meteorological Services stations located on the west coast and the Central Plateau provided the study with detailed rainfall data for 6 years at 6-min intervals. Rainfall erosivity for erosive events was calculated using different set interval data. In this study, within the EI, the use of 6-min rainfall intervals during erosive rainfall gave estimates of around 10% more erosivity than the 30-min time intervals and 33% more rainfall erosivity than the 60-min rainfall measurements. When the MFI was used to determine erosivity through annual and monthly rainfall totals, substantially higher erosivity than the EI method was calculated in both regions. This stems from the large amount of non-erosive rainfall that is generated on Mauritius. Even when the MFI was used to calculate erosivity through monthly and annual rainfall totals derived purely from erosive rainfall, erosivity calculations were not comparable to those from high-resolution data within the EI. We suggest that for the computation of erosivity, rainfall data with the highest possible resolution should be utilised if available and that the application of annual and monthly rainfall totals to assess absolute soil erosion risk within a high rainfall tropical environment must be used with caution.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1468-0459hb201

The nature of erosive rainfall on a tropical volcanic island with an elevated interior

Mauritius is a typical tropical volcanic island with a distinct elevated central plateau above 550 m.a.s.l. Rainfall depth, duration, intensity, kinetic energy, and erosivity were analysed for 385 erosive rainfall events at five locations over a five-year period (2004 to 2008). Two Mauritius Meteorological Services stations located on the west coast and three sited on the Central Plateau provide detailed rainfall data at 6-minute intervals. Erosive storm events are found to differ markedly between the coastal lowlands and the elevated interior with regard to the frequency, the total rainfall generated, the duration, total kinetic energy, and total erosivity of individual events. However, mean kinetic energy, mean and maximum rainfall erosivity (EI30), and maximum intensities (I30) from individual erosive events do not show this distinct differentiation. The distribution of kinetic energy and erosivity generated by individual events at the two altitudes are also significantly different. Although erosivity measured during summer exceeds that recorded in winter, the data indicate that large percentages of winter rainfall events on Mauritius are erosive and rainfall from non-tropical cyclones can pose a substantial erosion risk. Soil erosion risk occurs from storm-scale to synoptic-scale events, and extreme rainfall events generate the bulk of the erosivity. This paper also highlights that the use of rainfall records at an event scale in soil erosion risk assessments on tropical islands with a complex topography increases the effectiveness of erosivity estimates.National Research Foundation (NRF).The Department of Geography, Geoinformatics, and Meteorology at the University of Pretoria and the Govan Mbeki Research and Development Centre at the University of Fort Hare supplied additional travel funding for WN, PS, RB, and TM.http://www.tandfonline.com/loi/tphy20hb201

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Human and mouse essentiality screens as a resource for disease gene discovery.

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery

Human and mouse essentiality screens as a resource for disease gene discovery

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery. Discovery of causal variants for monogenic disorders has been facilitated by whole exome and genome sequencing, but does not provide a diagnosis for all patients. Here, the authors propose a Full Spectrum of Intolerance to Loss-of-Function (FUSIL) categorization that integrates gene essentiality information to aid disease gene discovery