Symbionts as Filters of Plant Colonization of Islands: Tests of Expected Patterns and Environmental Consequences in the Galapagos

This work is licensed under a Creative Commons Attribution 4.0 International License.The establishments of new organisms that arrive naturally or with anthropogenic assistance depend primarily on local conditions, including biotic interactions. We hypothesized that plants that rely on fungal symbionts are less likely to successfully colonize remote environments such as oceanic islands, and this can shape subsequent island ecology. We analyzed the mycorrhizal status of Santa Cruz Island, Galapagos flora compared with the mainland Ecuador flora of origin. We experimentally determined plant responsiveness and plant–soil feedback of the island flora and assessed mycorrhizal density and soil aggregate stability of island sites. We found that a greater proportion of the native island flora species belongs to families that typically do not associate with mycorrhizal fungi than expected based upon the mainland flora of origin and the naturalized flora of the island. Native plants benefited significantly less from soil fungi and had weaker negative soil feedbacks than introduced species. This is consistent with the observation that field sites dominated by native plant species had lower arbuscular mycorrhizal (AM) fungal density and lower soil aggregate stability than invaded field sites at the island. We found support for a mycorrhizal filter to the initial colonization of the Galapagos

Acaulospora colossica sp. nov. from an old field in North Carolina and morphological comparisons with similar species, A. laevis and A. koskei

A new arbuscular mycorrhizal fungal species, Acaulospora colossica, (Glomales, Acaulosporaceae) is described, and its distribution and seasonality discussed. Spores of A. colossica develop from saccules that empty their contents in the developing spores. Spore wall structure consists of 3 layers, all originating from the subtending hyphae. The two inner layers are laminated. The outermost spore wall layer is typically sloughed off before the spores mature. Two inner walls arise sequentially. Both inner walls are comprised of two layers. The outer layer of the innermost wall is beaded. Acaulospora colossica is described from a population in Durham, North Carolina. Its name refers to the relatively large size of the spores. Finally, the morphology of the new species A. colossica is compared and contrasted to two closely related species A. laevis and A. koskei

Arbuscular Mycorrhizal Fungi Taxa Show Variable Patterns of Micro-Scale Dispersal in Prairie Restorations

Human land use disturbance is a major contributor to the loss of natural plant communities, and this is particularly true in areas used for agriculture, such as the Midwestern tallgrass prairies of the United States. Previous work has shown that arbuscular mycorrhizal fungi (AMF) additions can increase native plant survival and success in plant community restorations, but the dispersal of AMF in these systems is poorly understood. In this study, we examined the dispersal of AMF taxa inoculated into four tallgrass prairie restorations. At each site, we inoculated native plant species with greenhouse-cultured native AMF taxa or whole soil collected from a nearby unplowed prairie. We monitored AMF dispersal, AMF biomass, plant growth, and plant community composition, at different distances from inoculation. In two sites, we assessed the role of plant hosts in dispersal, by placing known AMF hosts in a “bridge” and “island” pattern on either side of the inoculation points. We found that AMF taxa differ in their dispersal ability, with some taxa spreading to 2-m in the first year and others remaining closer to the inoculation point. We also found evidence that AMF spread altered non-inoculated neighboring plant growth and community composition in certain sites. These results represent the most comprehensive attempt to date to evaluate AMF spread

African Americans and Land Loss in Texas: Government Duplicity and Discrimination Based on Race and Class

African American Farmers and Land Loss in Texas, surveys the ways that discrimination at the local, state, and national levels constrained minority farmers during the twentieth century. It considers the characteristics of small-scale farming that created liabilities for landowners regardless of race, including state and federal programs that favored commercial and agribusiness interests. In addition to economic challenges African American farmers had to negotiate racism in the Jim Crow South. The Texas Agricultural Extension Service, the state branch of the USDA\u27s Extension Service, segregated in 1915. The Negro division gave black farmers access to information about USDA programs, but it emphasized their subordinate position relative to white farmers. The Civil Rights Act of 1964 did not reverse decades of racial discrimination. Instead, USDA officials relied on federalism, a theory as old as the Constitution, to justify their tolerance of civil rights violations in Texas and elsewhere. Then, special needs legislation passed during the 1970s and 1980s did not realize its potential to serve ethnically diverse and economically disadvantaged rural Texans. Discrimination based on race combined with a bias toward commercial production. This crippled most black farmers and led to their near extinction

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

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

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

ZNF274 Recruits the Histone Methyltransferase SETDB1 to the 3′ Ends of ZNF Genes

Only a small percentage of human transcription factors (e.g. those associated with a specific differentiation program) are expressed in a given cell type. Thus, cell fate is mainly determined by cell type-specific silencing of transcription factors that drive different cellular lineages. Several histone modifications have been associated with gene silencing, including H3K27me3 and H3K9me3. We have previously shown that genes for the two largest classes of mammalian transcription factors are marked by distinct histone modifications; homeobox genes are marked by H3K27me3 and zinc finger genes are marked by H3K9me3. Several histone methyltransferases (e.g. G9a and SETDB1) may be involved in mediating the H3K9me3 silencing mark. We have used ChIP-chip and ChIP-seq to demonstrate that SETDB1, but not G9a, is associated with regions of the genome enriched for H3K9me3. One current model is that SETDB1 is recruited to specific genomic locations via interaction with the corepressor TRIM28 (KAP1), which is in turn recruited to the genome via interaction with zinc finger transcription factors that contain a Kruppel-associated box (KRAB) domain. However, specific KRAB-ZNFs that recruit TRIM28 (KAP1) and SETDB1 to the genome have not been identified. We now show that ZNF274 (a KRAB-ZNF that contains 5 C2H2 zinc finger domains), can interact with KAP1 both in vivo and in vitro and, using ChIP-seq, we show that ZNF274 binding sites co-localize with SETDB1, KAP1, and H3K9me3 at the 3′ ends of zinc finger genes. Knockdown of ZNF274 with siRNAs reduced the levels of KAP1 and SETDB1 recruitment to the binding sites. These studies provide the first identification of a KRAB domain-containing ZNF that is involved in recruitment of the KAP1 and SETDB1 to specific regions of the human genome

Elucidating Poor Decision-Making in a Rat Gambling Task

Although poor decision-making is a hallmark of psychiatric conditions such as attention deficit/hyperactivity disorder, pathological gambling or substance abuse, a fraction of healthy individuals exhibit similar poor decision-making performances in everyday life and specific laboratory tasks such as the Iowa Gambling Task. These particular individuals may provide information on risk factors or common endophenotypes of these mental disorders. In a rodent version of the Iowa gambling task – the Rat Gambling Task (RGT), we identified a population of poor decision makers, and assessed how these rats scored for several behavioral traits relevant to executive disorders: risk taking, reward seeking, behavioral inflexibility, and several aspects of impulsivity. First, we found that poor decision-making could not be well predicted by single behavioral and cognitive characteristics when considered separately. By contrast, a combination of independent traits in the same individual, namely risk taking, reward seeking, behavioral inflexibility, as well as motor impulsivity, was highly predictive of poor decision-making. Second, using a reinforcement-learning model of the RGT, we confirmed that only the combination of extreme scores on these traits could induce maladaptive decision-making. Third, the model suggested that a combination of these behavioral traits results in an inaccurate representation of rewards and penalties and inefficient learning of the environment. Poor decision-making appears as a consequence of the over-valuation of high-reward-high-risk options in the task. Such a specific psychological profile could greatly impair clinically healthy individuals in decision-making tasks and may predispose to mental disorders with similar symptoms