Similarity Regression predicts evolution of transcription factor sequence specificity

Transcription factor (TF) binding specificities (motifs) are essential to the analysis of noncoding DNA and gene regulation. Accurate prediction of the sequence specificities of TFs is critical, because the hundreds of sequenced eukaryotic genomes encompass hundreds of thousands of TFs, and assaying each is currently infeasible. There is ongoing controversy regarding the efficacy of motif prediction methods, as well as the degree of motif diversification among related species. Here, we describe Similarity Regression (SR), a significantly improved method for predicting motifs. We have updated and expanded the Cis-BP database using SR, and validate its predictive capacity with new data from diverse eukaryotic TFs. SR inherently quantifies TF motif evolution, and we show that previous claims of near-complete conservation of motifs between human and Drosophila are grossly inflated, with nearly half the motifs in each species absent from the other. We conclude that diversification in DNA binding motifs is pervasive, and present a new tool and updated resource to study TF diversity and gene regulation across eukaryotes

Early evolution of the T-box transcription factor family

Deèelopmental transcription factors are key players in animal multicellularity, being members of the T-box family that are among the most important. Until recently, T-box transcription factors were thought to be exclusièely present in metazoans. Here, we report the presence of T-box genes in seèeral nonmetazoan lineages, including ichthyosporeans, filastereans, and fungi. Our data confirm that Brachyury is the most ancient member of the T-box family and establish that the T-box family dièersified at the onset of Metazoa. Moreoèer, we demonstrate functional conserèation of a homolog of Brachyury of the protist Capsaspora owczarzaki in Xenopus laeèis. By comparing the molecular phenotype of C. owczarzaki Brachyury with that of homologs of early branching metazoans, we define a clear difference between unicellular holozoan and metazoan Brachyury homologs, suggesting that the specificity of Brachyury emerged at the origin of Metazoa. Experimental determination of the binding preferences of the C. owczarzaki Brachyury results in a similar motif to that of metazoan Brachyury and other T-box classes. This finding suggests that functional specificity between different T-box classes is likely achieèed by interaction with alternatièe cofactors, as opposed to differences in binding specificity

Mapping and analysis of Caenorhabditis elegans transcription factor sequence specificities

Caenorhabditis elegans is a powerful model for studying gene regulation, as it has a compact genome and a wealth of genomic tools. However, identification of regulatory elements has been limited, as DNA-binding motifs are known for only 71 of the estimated 763 sequence-specific transcription factors (TFs). To address this problem, we performed protein binding microarray experiments on representatives of canonical TF families in C. elegans, obtaining motifs for 129 TFs. Additionally, we predict motifs for many TFs that have DNA-binding domains similar to those already characterized, increasing coverage of binding specificities to 292 C. elegans TFs (~40%). These data highlight the diversification of binding motifs for the nuclear hormone receptor and C2H2 zinc finger families, and reveal unexpected diversity of motifs for T-box and DM families. Motif enrichment in promoters of functionally related genes is consistent with known biology, and also identifies putative regulatory roles for unstudied TFs

Restoration of the iconic Pando aspen clone: emerging evidence of recovery

Quaking aspen (Populus tremuloides Michx.) is being stressed across the America West from a variety of sources including drought, herbivory, fire suppression, development, and past management practices. Rich assemblages of plants and animals that utilize aspen forests, as well as economic values of tourism, grazing, hunting, and water conservation, make aspen ecosystems among the most valuable vegetation types in this region. The 43-ha Pando clone near Fish Lake, Utah, is an iconic example of an aspen community undergoing rapid decline due to overstory mortality and chronic recruitment failure. As part of a larger project to restore Pando, we fenced, treated, and monitored a portion of this famous grove with the intent of documenting regeneration responses and using such practices at larger scales. Twenty-seven randomly stratified monitoring plots were placed across this landscape in order to better understand herbivory and regeneration responses to distinct treatment categories: protected and unprotected, and passive (fenced only) and active (burning, shrub removal, selective overstory cutting) treatments. At each site, we measured basal area and mortality on mature trees, made counts of juvenile and intermediate suckers, documented browse levels and herbivore scat presence, and characterized environmental conditions in terms of aspen and common juniper cover, treatment type, elevation, slope, and aspect. Our results confirmed a positive regeneration response to browsing cessation after fencing, whereas non-fenced areas showed no improvement. Within the fence, there was a significantly better response of active treatment vs. passive and there was no significant difference between treatment types in terms of level of regeneration. Both active and passive management produced regeneration levels that were sufficient to replace dying canopy trees if managers continue to protect suckers until they exceed the reach of browsers. These results support a growing body of research suggesting managers need to invest in continuous protection from herbivory in stable aspen forests, as well as targeting additional post-treatment protection, to ensure adequate regeneration. We examine ramifications of these results for broader restoration purposes in the remainder of Pando, as well as other aspen communities regionally, with the ultimate goal of restoring ecological process toward greater ecosystem resilience

Higher susceptibility to sunburn is associated with decreased plasma glutamine and increased plasma glutamate levels among US women: An analysis of the Nurses' Health Study I and II

To the Editor: The metabolism of glutamine and glutamate, 2 important amino acids synthesized in the human body, may have an etiologic role in melanoma, an aggressive skin malignancy. 1 , 2 Preclinical experiments and clinical trials have found that metabotropic glutamate receptor 1 blocker and glutamate release inhibitor (eg, Riluzole) can suppress melanoma cell migration, invasion, and proliferation. 2 Additionally, inhibiting glutaminase, the enzyme that converts glutamine to glutamate, further reduced glutamate bioavailability and suppressed tumor progression. 1 Susceptibility to sunburn, a pigmentary trait, is a well-known risk factor for melanoma. 3 However, it is unclear whether plasma glutamate and glutamine are affected by this host factor even before cancer onset

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

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