Higher eukaryotic chromosomes are organized into topologically constrained functional domains; however, the molecular mechanisms required to sustain these complex interphase chromatin structures are unknown. A stable matrix underpinning nuclear organization was hypothesized, but the idea was abandoned as more dynamic models of chromatin behavior became prevalent. Here, we report that scaffold attachment factor A (SAF-A), originally identified as a structural nuclear protein, interacts with chromatin-associated RNAs (caRNAs) via its RGG domain to regulate human interphase chromatin structures in a transcription-dependent manner. Mechanistically, this is dependent on SAF-A's AAA+ ATPase domain, which mediates cycles of protein oligomerization with caRNAs, in response to ATP binding and hydrolysis. SAF-A oligomerization decompacts large-scale chromatin structure while SAF-A loss or monomerization promotes aberrant chromosome folding and accumulation of genome damage. Our results show that SAF-A and caRNAs form a dynamic, transcriptionally responsive chromatin mesh that organizes large-scale chromosome structures and protects the genome from instability.

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdLS.

There are three human enzymes with HMG-CoA lyase activity that are able to synthesize ketone bodies in different subcellular compartments. The mitochondrial HMG-CoA lyase was the first to be described, and catalyzes the cleavage of 3-hydroxy-3-methylglutaryl CoA to acetoacetate and acetyl-CoA, the common final step in ketogenesis and leucine catabolism. This protein is mainly expressed in the liver and its function is metabolic, since it produces ketone bodies as energetic fuels when glucose levels are low. Another isoform is encoded by the same gene for the mitochondrial HMG-CoA lyase (HMGCL), but it is located in peroxisomes. The last HMG-CoA lyase to be described is encoded by a different gene, HMGCLL1, and is located in the cytosolic side of the endoplasmic reticulum membrane. Some activity assays and tissue distribution of this enzyme have shown the brain and lung as key tissues for studying its function. Although the roles of the peroxisomal and cytosolic HMG-CoA lyases remain unknown, recent studies highlight the role of ketone bodies in metabolic remodeling, homeostasis, and signaling, providing new insights into the molecular and cellular function of these enzymes.