Estimating quantitative genetic parameters ideally takes place in natural populations, but relatively few studies have overcome the inherent logistical difficulties. For this reason, no estimates currently exist for the genetic basis of life-history traits in natural populations of large marine vertebrates. And yet such estimates are likely to be important given the exposure of this taxon to changing selection pressures, and the relevance of life-history traits to population productivity. We report such estimates from a long-term (1995-2007) study of lemon sharks (Negaprion brevirostris) conducted at Bimini, Bahamas. We obtained these estimates by genetically reconstructing a population pedigree (117 dams, 487 sires, and 1351 offspring) and then using an "animal model" approach to estimate quantitative genetic parameters. We find significant additive genetic (co)variance, and hence moderate heritability, for juvenile length and mass. We also find substantial maternal effects for these traits at age-0, but not age-1, confirming that genotype-phenotype interactions between mother and offspring are strongest at birth; although these effects could not be parsed into their genetic and nongenetic components. Our results suggest that human-imposed selection pressures (e.g., size-selective harvesting) might impose noteworthy evolutionary change even in large marine vertebrates. We therefore use our findings to explain how maternal effects may sometimes promote maladaptive juvenile traits, and how lemon sharks at different nursery sites may show "constrained local adaptation." We also show how single-generation pedigrees, and even simple marker-based regression methods, can provide accurate estimates of quantitative genetic parameters in at least some natural systems.
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http://dx.doi.org/10.1111/j.1558-5646.2008.00605.x | DOI Listing |
It is known that inhibition of the endoplasmic reticulum transmembrane signaling protein (ERN1) suppresses the glioblastoma cells proliferation. The present study aims to investigate the impact of inhibition of ERN1 endoribonuclease and protein kinase activities on the , , and gene expression in U87MG glioblastoma cells with an intent to reveal the role of ERN1 signaling in the regulation of expression of these genes. The U87MG glioblastoma cells with inhibited ERN1 endoribonuclease (dnrERN1) or both enzymatic activities of ERN1 (endoribonuclease and protein kinase; dnERN1) were used.
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January 2025
1Department of Molecular Biology, Palladin Institute of Biochemistry, National Academy of Sciences of Ukraine, Kyiv, Ukraine.
For the effective growth of malignant tumors, including glioblastoma, the necessary factors involve endoplasmic reticulum (ER) stress, hypoxia, and the availability of nutrients, particularly glucose. The ER degradation enhancing alpha-mannosidase like protein 1 (EDEM1) is involved in ER-associated degradation (ERAD) targeting misfolded glycoproteins for degradation in an N-glycan-independent manner. EDEM1 was also identified as a new modulator of insulin synthesis and secretion.
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March 2025
Clinical Cardiac Academic Group, Genetic and Cardiovascular Sciences Institute, City-St George's University of London, London, UK.
Atrial fibrillation (AF) is one of the most common cardiac diseases and a complicating comorbidity for multiple associated diseases. Many clinical decisions regarding AF are currently based on the binary recognition of AF being present or absent with the categorical appraisal of AF as continued or intermittent. Assessment of AF in clinical trials is largely limited to the time to (first) detection of an AF episode.
View Article and Find Full Text PDFSci Adv
March 2025
College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
Brain age gap (BAG), the deviation between estimated brain age and chronological age, is a promising marker of brain health. However, the genetic architecture and reliable targets for brain aging remains poorly understood. In this study, we estimate magnetic resonance imaging (MRI)-based brain age using deep learning models trained on the UK Biobank and validated with three external datasets.
View Article and Find Full Text PDFElife
March 2025
Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States.
Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses.
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