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Abstract Cardamine enshiensis is a well-known selenium (Se)-hyperaccumulating plant. Se is an essential trace element associated with many health benefits. Despite its critical importance, genomic information of this species is limited. Here, we report a chromosome-level genome assembly of C. enshiensis, which consists of 443.4 Mb in 16 chromosomes with a scaffold N50 of 24 Mb. To elucidate the mechanism of Se tolerance and hyperaccumulation in C. enshiensis, we generated and analyzed a dataset encompassing genomes, transcriptomes, and metabolomes. The results reveal that flavonoid, glutathione, and lignin biosynthetic pathways may play important roles in protecting C. enshiensis from stress induced by Se. Hi-C analysis of chromatin interaction patterns showed that the chromatin of C. enshiensis is partitioned into A and B compartments, and strong interactions between the two telomeres of each chromosome were correlated with histone modifications, epigenetic markers, DNA methylation, and RNA abundance. Se supplementation could affect the 3D chromatin architecture of C. enshiensis at the compartment level. Genes with compartment changes after Se treatment were involved in selenocompound metabolism, and genes in regions with topologically associated domain insulation participated in cellular responses to Se, Se binding, and flavonoid biosynthesis. This multiomics research provides molecular insight into the mechanism underlying Se tolerance and hyperaccumulation in C. enshiensis.

Abstract Tourette syndrome (TS) is a neurobehavioral disorder for which the neurological mechanism has not been elucidated. Voxel-based morphometry (VBM) studies have revealed abnormalities in gray matter volume (GMV) in patients with TS; however, consistent results have not been obtained. The current study attempted to provide a voxel wise meta-analysis of gray matter changes using seed-based d mapping (SDM). We identified ten relevant studies that investigated gray matter alterations in TS patients and performed a meta-analysis using the SDM method to quantitatively estimate regional gray matter abnormalities. Next, we examined the relationships between GMV abnormalities and demographic and clinical characteristics. Our results demonstrated that TS patients had smaller GMV in the bilateral inferior frontal gyri and greater GMV in the cerebellum, right striatum (putamen), and bilateral thalami (pulvinar nucleus) than healthy controls. A meta-regression analysis did not identify correlations between GMV changes and demographic or clinical variables. This meta-analysis confirmed significant and consistent GMV changes in several brain regions of TS patients, primarily in the cortico-striato-thalamo-cortical network.