With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for managing huge sequence data, here we present Genome Sequence Archive (GSA; http://bigd.big.ac.cn/gsa or http://gsa.big.ac.cn), a data repository for archiving raw sequence data. In compliance with data standards and structures of the International Nucleotide Sequence Database Collaboration (INSDC), GSA adopts four data objects (BioProject, BioSample, Experiment, and Run) for data organization, accepts raw sequence reads produced by a variety of sequencing platforms, stores both sequence reads and metadata submitted from all over the world, and makes all these data publicly available to worldwide scientific communities. In the era of big data, GSA is not only an important complement to existing INSDC members by alleviating the increasing burdens of handling sequence data deluge, but also takes the significant responsibility for global big data archive and provides free unrestricted access to all publicly available data in support of research activities throughout the world.

Background Defining the RNA transcriptome in Alzheimer’s Disease (AD) will help understand disease mechanisms and provide biomarkers. Though the AD blood transcriptome has been studied, effects of white matter hyperintensities (WMH) were not considered. This study investigated the AD blood transcriptome and accounted for WMH. Methods RNA from whole blood was processed on whole-genome microarrays. Results 293 probe sets were differentially expressed in AD versus controls, 5 of which were significant for WMH status. The 288 AD-specific probe-sets classified subjects with 87.5% sensitivity and 90.5% specificity. They represented 188 genes of which 29 have been reported in prior AD blood and 89 in AD brain studies. Regulated blood genes included MMP9, MME (Neprilysin), TGFβ1, CA4, OCLN, ATM, TGM3, IGFR2, NOV, RNF213, BMX, LRRN1, CAMK2G, INSR, CTSD, SORCS1, SORL1 and TANC2. Conclusions RNA expression is altered in AD blood irrespective of WMH status. Some genes are shared with AD brain.

Meta-analysis of data from genome-wide association studies (GWAS) of Alzheimer's disease (AD) has confirmed the high risk of APOE and identified twenty other risk genes/loci with moderate effect size. However, many more risk genes/loci remain to be discovered to account for the missing heritability. The contributions from individual singe-nucleotide polymorphisms (SNPs) have been thoroughly examined in traditional GWAS data analysis, while SNP-SNP interactions can be explored by a variety of alternative approaches. Here we applied generalized multifactor dimensionality reduction to the re-analysis of four publicly available GWAS datasets for AD. When considering 4-order intragenic SNP interactions, we observed high consistency of discovered potential risk genes among the four independent GWAS datasets. Ten potential risk genes were observed across all four datasets, including PDE1A, RYR3, TEK, SLC25A21, LOC729852, KIRREL3, PTPN5, FSHR, PARK2, and NR3C2. These potential risk genes discovered by generalized multifactor dimensionality reduction are highly relevant to AD pathogenesis based on multiple layers of evidence. The genetic contributions of these genes warrant further confirmation in other independent GWAS datasets for AD.

Alzheimer’s disease (AD) remains to be a grand challenge for the international community despite over a century of exploration. A key factor likely accounting for such a situation is the vast heterogeneity in the disease etiology, which involves very complex and divergent pathways. Therefore, intervention strategies shall be tailored for subgroups of AD patients. Both demographic and in-depth information is needed for patient stratification. The demographic information includes primarily APOE genotype, age, gender, education, environmental exposure, life style, and medical history, whereas in-depth information stems from genome sequencing, brain imaging, peripheral biomarkers, and even functional assays on neurons derived from patient-specific induced pluripotent cells (iPSCs). Comprehensive information collection, better understanding of the disease mechanisms, and diversified strategies of drug development would help with more effective intervention in the foreseeable future.

Diabetic retinopathy (DR) is a common microvascular complication leading to a high blindness rate among patients with diabetes. Ferroptosis is a type of cell death caused by the accumulation of iron-dependent lipid peroxides. Studies have shown that ferroptosis plays an important role in DR. The rat model of DR was constructed and treated with Ferrostatin-1 (Ferr-1). Haematoxylin and eosin (HE) were used to detect the degree of retinopathy. Oxidative stress levels were detected by ELISA. Perl’s staining was used to detect iron deposition in retinal tissues. Ferritin levels were measured by ELISA. The expression of GPX4 was detected by immunohistochemistry (IHC). GSH/GSSG kit was used to detect the content and proportion of reduced/oxidized glutathione. Western blot was used to detect the expression of ferroptosis-related proteins. TUNEL assay was used to detect cell apoptosis. The expression of GSDMD was detected by fluorescence in situ hybridization (FISH). Western blot was used to detect the expression of apoptosis and pyroptosis-related proteins. Then, high glucose (HG)-induced retinal epithelial cell line ARPE-19 was treated by Erastin (ferroptosis activator) and Ferr-1. CCK-8, ELISA, western blot, flow cytometry, and immunofluorescence (IF) staining were used to detect oxidative stress levels, ferroptosis and cell damage. The mechanism was further explored by adding ferroptosis agonist Erastin. In vitro and in vivo results showed that oxidative stress was increased in DR model, resulting in ferroptosis and tissue or cell damage. After administration of Ferr-1, the antioxidant capacity was improved, ferroptosis levels were reduced and tissue or cell damage was alleviated. In vitro results showed that Ferr-1 reversed the impacts of Erastin on oxidative stress, ferroptosis, and cell damage in HG-induced ARPE-19 cells. Ferr-1 alleviated tissue and cell damage by improving the antioxidant capacity of the Xc--GPX4 system.

Alzheimer's disease (AD) affects a significant portion of elderly people worldwide. Although the amyloid-β (Aβ) cascade hypothesis has been the prevailing theory for the molecular mechanism of AD in the past few decades, treatment strategies targeting the Aβ cascade have not demonstrated effectiveness as yet. Thus, elucidating the spatial and temporal evolution of the molecular pathways in AD remains to be a daunting task. To facilitate novel discoveries in this filed, here, we have integrated information from multiple sources for the better understanding of gene functions in AD pathogenesis. Several categories of information have been collected, including (1) gene dysregulation in AD and closely related processes/diseases such as aging and neurological disorders, (2) correlation of gene dysregulation with AD severity, (3) a wealth of annotations on the functional and regulatory information, and (4) network connections for gene-gene relationship. In addition, we have also provided a comprehensive summary for the top ranked genes in AlzBase. By evaluating the information curated in AlzBase, researchers can prioritize genes from their own research and generate novel hypothesis regarding the molecular mechanism of AD. To demonstrate the utility of AlzBase, we examined the genes from the genetic studies of AD. It revealed links between the upstream genetic variations and downstream endo-phenotype and suggested several genes with higher priority. This integrative database is freely available on the web at http://alz.big.ac.cn/alzBase .

Neurological disorders comprise a variety of complex diseases in the central nervous system, which can be roughly classified as neurodegenerative diseases and psychiatric disorders. The basic and translational research of neurological disorders has been hindered by the difficulty in accessing the pathological center (i.e., the brain) in live patients. The rapid advancement of sequencing and array technologies has made it possible to investigate the disease mechanism and biomarkers from a systems perspective. In this review, recent progresses in the discovery of novel risk genes, treatment targets and peripheral biomarkers employing genomic technologies will be discussed. Our major focus will be on two of the most heavily investigated neurological disorders, namely Alzheimer’s disease and autism spectrum disorder.

No abstract