Dataset Information

Low genotypic diversity and long-term ecological decline in a spatially structured seagrass population.

ABSTRACT: In isolated or declining populations, viability may be compromised further by loss of genetic diversity. Therefore, it is important to understand the relationship between long-term ecological trajectories and population genetic structure. However, opportunities to combine these types of data are rare, especially in natural systems. Using an existing panel of 15 microsatellites, we estimated allelic diversity in seagrass, Zostera marina, at five sites around the Isles of Scilly Special Area of Conservation, UK, in 2010 and compared this to 23 years of annual ecological monitoring (1996-2018). We found low diversity and long-term declines in abundance in this relatively pristine but isolated location. Inclusion of the snapshot of genotypic, but less-so genetic, diversity improved prediction of abundance trajectories; however, this was spatial scale-dependent. Selection of the appropriate level of genetic organization and spatial scale for monitoring is, therefore, important to identify drivers of eco-evolutionary dynamics. This has implications for the use of population genetic information in conservation, management, and spatial planning.

SUBMITTER: Alotaibi NM

PROVIDER: S-EPMC6895181 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Low genotypic diversity and long-term ecological decline in a spatially structured seagrass population.

Alotaibi Nahaa M NM Kenyon Emma J EJ Cook Kevan J KJ Börger Luca L Bull James C JC

Scientific reports 20191205 1

In isolated or declining populations, viability may be compromised further by loss of genetic diversity. Therefore, it is important to understand the relationship between long-term ecological trajectories and population genetic structure. However, opportunities to combine these types of data are rare, especially in natural systems. Using an existing panel of 15 microsatellites, we estimated allelic diversity in seagrass, Zostera marina, at five sites around the Isles of Scilly Special Area of Co ...[more]

PMID: 31804557

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Project description:Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTS) may provide important insight into the biology of GBM. We identified 7 patients with GBM treated at Memorial Sloan-Kettering Cancer Center (MSKCC) with survival greater than 48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTS in two independent cohorts (TCGA and REMBRANDT) and analyzed the transcriptomal characteristics of these LTS. The median overall survival of our cohort was 62.5 months. LTS were distributed between the proneural (n=2), neural (n=2), classical (n=2) and mesenchymal (n=1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identity. The majority of the MSKCC LTS (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutations, and IDH mutation occurred in a minority of the TCGA LTS as well. A set of 42 genes was found to be differentially expressed in the MSKCC and TCGA LTS. While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression. All tumors (n = 7) were obtained following surgical resection at the MSKCC as part of routine clinical care, and snap frozen. Tumors were obtained in accordance with Institutional Review Board policies at the MSKCC. Each sample was examined histologically by 3 independent neuropathologists and confirmed to be World Health Organization (WHO) grade IV glioma (GBM). Before analysis, tumors were sectioned and microdissected. Genomic DNA or RNA was extracted using the DNeasy kit (Qiagen) or RNeasy Lipid Tissue Mini Kit (Qiagen) as per the manufacturer’s instructions. Expression analysis of tumors was performed using the Affymetrics U133 2.0 microarray (Affymetrix). Affymetrix CEL files were imported into the Partek Genomics Suite (Partek). The TCGA gene expression data (HT-HG-U133A) was accessed from the TCGA data repositories (http://cancergenome.nih.gov, date of download 12/2013).

Dataset Information

Low genotypic diversity and long-term ecological decline in a spatially structured seagrass population.

Publications

Low genotypic diversity and long-term ecological decline in a spatially structured seagrass population.

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