Identification of New SRF Binding Sites in Genes Modulated by SRF Over-Expression in Mouse Hearts

Background To identify in vivo new cardiac binding sites of serum response factor (SRF) in genes and to study the response of these genes to mild over-expression of SRF, we employed a cardiac-specific, transgenic mouse model, with mild over-expression of SRF (Mild-O SRF Tg). Methodology Microarray experiments were performed on hearts of Mild-O-SRF Tg at 6 months of age. We identified 207 genes that are important for cardiac function that were differentially expressed in vivo. Among them the promoter region of 192 genes had SRF binding motifs, the classic CArG or CArG-like (CArG-L) elements. Fifty-one of the 56 genes with classic SRF binding sites had not been previously reported. These SRF-modulated genes were grouped into 12 categories based on their function. It was observed that genes associated with cardiac energy metabolism shifted toward that of carbohydrate metabolism and away from that of fatty acid metabolism. The expression of genes that are involved in transcription and ion regulation were decreased, but expression of cytoskeletal genes was significantly increased. Using public databases of mouse models of hemodynamic stress (GEO database), we also found that similar altered expression of the SRF-modulated genes occurred in these hearts with cardiac ischemia or aortic constriction as well. Conclusion and significance SRF-modulated genes are actively regulated under various physiological and pathological conditions. We have discovered that a large number of cardiac genes have classic SRF binding sites and were significantly modulated in the Mild-O-SRF Tg mouse hearts. Hence, the mild elevation of SRF protein in the heart that is observed during typical adult aging may have a major impact on many SRF-modulated genes, thereby affecting Cardiac structure and performance. The results from our study could help to enhance our understanding of SRF regulation of cellular processes in the aged heart

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease