Species trees from consensus single nucleotide polymorphism (SNP) data: Testing phylogenetic approaches with simulated and empirical data

Datasets of hundreds or thousands of SNPs (Single Nucleotide Polymorphisms) from multiple individuals per species are increasingly used to study population structure, species delimitation and shallow phylogenetics. The principal software tool to infer species or population trees from SNP data is currently the BEAST template SNAPP which uses a Bayesian coalescent analysis. However, it is computationally extremely demanding and tolerates only small amounts of missing data. We used simulated and empirical SNPs from plants (Australian Craspedia, Asteraceae, and Pelargonium, Geraniaceae) to compare species trees produced (1) by SNAPP, (2) using SVD quartets, and (3) using Bayesian and parsimony analysis with several different approaches to summarising data from multiple samples into one set of traits per species. Our aims were to explore the impact of tree topology and missing data on the results, and to test which data summarising and analyses approaches would best approximate the results obtained from SNAPP for empirical data. SVD quartets retrieved the correct topology from simulated data, as did SNAPP except in the case of a very unbalanced phylogeny. Both methods failed to retrieve the correct topology when large amounts of data were missing. Bayesian analysis of species level summary data scoring the two alleles of each SNP as independent characters and parsimony analysis of data scoring each SNP as one character produced trees with branch length distributions closest to the true trees on which SNPs were simulated. For empirical data, Bayesian inference and Dollo parsimony analysis of data scored allele-wise produced phylogenies most congruent with the results of SNAPP. In the case of study groups divergent enough for missing data to be phylogenetically informative (because of additional mutations preventing amplification of genomic fragments or bioinformatic establishment of homology), scoring of SNP data as a presence/absence matrix irrespective of allele content might be an additional option. As this depends on sampling across species being reasonably even and a random distribution of non-informative instances of missing data, however, further exploration of this approach is needed. Properly chosen data summary approaches to inferring species trees from SNP data may represent a potential alternative to currently available individual-level coalescent analyses especially for quick data exploration and when dealing with computationally demanding or patchy datasets.This study was partly supported by a Centre of Biodiversity Analysis Ignition Grant to A.N.S.-L. and Justin Borevitz in 2013/14

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

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

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

Mudanças nos compostos bioativos e atividade antioxidante de pimentas da região amazônica.

A Embrapa Amazônia Oriental possui um Banco Ativo de Pimenteira com diferentes genótipos do gênero Capsicum, os quais ainda não foram analisados, quanto às suas características funcionais e capacidade antioxidante. Este estudo objetivou determinar os teores de ácido ascórbico, compostos fenólicos, carotenoides totais e a atividade antioxidante total, em frutos imaturos e maduros de genótipos de pimentas Capsicum spp. As concentrações de vitamina C (100,76-361,65 mg 100 g-1 nos frutos imaturos e 36,70-157,76 mg 100 g-1 nos maduros) decresceram com a maturação dos frutos. Carotenoides totais não foram detectados nos frutos imaturos, porém, nos frutos maduros, observaram-se valores de 73,80-1349,97 mg g-1, em função do genótipo. Os teores de compostos fenólicos aumentaram nos frutos maduros (147,40-718,64 mg GAE 100 g-1), para oito dos nove genótipos avaliados. Os frutos de pimenteira apresentaram significativa atividade antioxidante (55,02-92,03 mM trolox g-1 nos frutos imaturos e 39,60-113,08 mM trolox g- 1 nos maduros). Concluiu-se que o grau de maturação dos frutos influenciou nos teores de compostos bioativos dos genótipos estudados. Destacaram-se, como genótipos promissores com potencial para serem utilizados em programas de melhoramento genético, IAN-186301 e IAN-186324, pelos altos teores de carotenoides totais; IAN-186301, IAN-186311, IAN-186312 e IAN-186313, com relação às altas concentrações de ácido ascórbico; IAN-186304 e IAN-186311, pelos altos teores de compostos fenólicos; e IAN-186311, para atividade antioxidante

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

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

The completion of the Mammalian Gene Collection (MGC)

Since its start, the Mammalian Gene Collection (MGC) has sought to provide at least one full-protein-coding sequence cDNA clone for every human and mouse gene with a RefSeq transcript, and at least 6200 rat genes. The MGC cloning effort initially relied on random expressed sequence tag screening of cDNA libraries. Here, we summarize our recent progress using directed RT-PCR cloning and DNA synthesis. The MGC now contains clones with the entire protein-coding sequence for 92% of human and 89% of mouse genes with curated RefSeq (NM-accession) transcripts, and for 97% of human and 96% of mouse genes with curated RefSeq transcripts that have one or more PubMed publications, in addition to clones for more than 6300 rat genes. These high-quality MGC clones and their sequences are accessible without restriction to researchers worldwide