BrainEXP: a database featuring with spatiotemporal expression variations and co-expression organizations in human brains

Deciphering Distinct Genetic Risk Factors for FTLD-TDP Pathological Subtypes via Whole-Genome Sequencing

Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) is a fatal neurodegenerative disorder with only a limited number of risk loci identified. We report our comprehensive genome-wide association study as part of the International FTLD-TDP Whole-Genome Sequencing Consortium, including 985 cases and 3,153 controls, and meta-analysis with the Dementia-seq cohort, compiled from 26 institutions/brain banks in the United States, Europe and Australia. We confirm UNC13A as the strongest overall FTLD-TDP risk factor and identify TNIP1 as a novel FTLD-TDP risk factor. In subgroup analyses, we further identify for the first time genome-wide significant loci specific to each of the three main FTLD-TDP pathological subtypes (A, B and C), as well as enrichment of risk loci in distinct tissues, brain regions, and neuronal subtypes, suggesting distinct disease aetiologies in each of the subtypes. Rare variant analysis confirmed TBK1 and identified VIPR1 , RBPJL , and L3MBTL1 as novel subtype specific FTLD-TDP risk genes, further highlighting the role of innate and adaptive immunity and notch signalling pathway in FTLD-TDP, with potential diagnostic and novel therapeutic implications.

STW-MD: a novel spatio-temporal weighting and multi-step decision tree method for considering spatial heterogeneity in brain gene expression data

Gene expression during brain development or abnormal development is a biological process that is highly dynamic in spatio and temporal. Previous studies have mainly focused on individual brain regions or a certain developmental stage. Our motivation is to address this gap by incorporating spatio-temporal information to gain a more complete understanding of brain development or abnormal brain development, such as Alzheimer's disease (AD), and to identify potential determinants of response. In this study, we propose a novel two-step framework based on spatial-temporal information weighting and multi-step decision trees. This framework can effectively exploit the spatial similarity and temporal dependence between different stages and different brain regions, and facilitate differential gene analysis in brain regions with high heterogeneity. We focus on two datasets: the AD dataset, which includes gene expression data from early, middle and late stages, and the brain development dataset, spanning fetal development to adulthood. Our findings highlight the advantages of the proposed framework in discovering gene classes and elucidating their impact on brain development and AD progression across diverse brain regions and stages. These findings align with existing studies and provide insights into the processes of normal and abnormal brain development.

Insertion of 643bp Retrotransposon Upstream of PPARγ CDS Is Associated with Backfat of Large White Pigs

PPARs are essential regulators of mammalian fatty acid and lipid metabolism. Although the effects of genetic variations, including single nucleotide polymorphisms (SNPs) in PPARs genes on the phenotype of domestic animals have been investigated, there is limited information on the impact of retrotransposon insertion polymorphisms (RIPs). In this study, a combined comparative genome and polymerase chain reaction (PCR) was used to excavate the RIPs in porcine PPARs. We also investigated the potential effects of retrotransposon insertion on phenotype and expression patterns. This study identified the two RIPs in PPARs genes, namely an ERV in intron 1 of PPARα and a combined retrotransposon in intron 2 of PPARγ, designated as PPARα-ERV-RIP and PPARγ-COM-RIP, respectively. These RIPs exhibited different distribution patterns among Chinese indigenous breeds and Western commercial breeds. Individuals with the PPARα-ERV-RIP^+/+ genotype (+/+ indicated homozygous with insertion) among Large White pigs had significantly higher (p < 0.05) corrected backfat thickness compared to those with the other two genotypes. Similarly, those with the PPARγ-COM-RIP^-/- genotype had significantly higher (p < 0.05) corrected backfat thickness than those with the other two genotypes in Large White pigs. Moreover, in 30-day-old Sujiang piglets, the PPARγ gene expression in the backfat of those with the PPARγ-COM-RIP^-/- genotype (-/- indicated homozygous without insertion) was significantly greater (p < 0.01) than those with other genotypes. The dual luciferase reporter gene assay demonstrated that the combined retrotransposon insertion significantly reduced the activity of the MYC promoter in both C2C12 and 3T3-L1 cells (p < 0.01). Therefore, the combined retrotransposon insertion could function as a repressor to decrease the expression of PPARγ, making PPARγ-COM-RIP a valuable molecular marker for assisted selection of backfat thickness in pig breeding.

Network-based identification of miRNAs and transcription factors and in silico drug screening targeting δ-secretase involved in Alzheimer's disease

BACKGROUND

System medicine approaches have played a pivotal role in identifying novel disease networks especially in miRNA research. It is no wonder that miRNAs are implicated in multiple clinical conditions, allowing us to establish the hubs and nodes for network models of Alzheimer's Disease (AD). AD is an age-related, progressive, irreversible, and multifactorial neurodegenerative disorder characterized by cognitive and memory impairment and is the most common cause of dementia in older adults. Worldwide, around 50 million people have dementia, and there are nearly 10 million new cases every year. δ-secretase, also known as asparagine endopeptidase (AEP) or legumain (LGMN), is a lysosomal cysteine protease that cleaves peptide bonds C-terminally to asparagine residues in both amyloid precursor protein (APP) and tau, mediating the amyloid-β and tau pathology in AD. The patient's miRNA expression was found to be deregulated in the brain, extracellular fluid, blood plasma, and serum.

METHODS

Protein-Protein Interaction (PPI) networks of LGMN or δ-secretase were constructed using the Genemania database. Network Analyzer, a Cytoscape plugin, analyzed the network topological properties of LGMN. miRNAs related to Alzheimer's were extracted from the HMDD (Human microRNA Disease Database) and experimentally verified miRNA-gene interaction was obtained by searching miRWalk. Starbase v2.0 and miRanda were used for screening miRNA of LGMN genes. Moreover, to understand the regulatory mechanism in AD, we have screened major transcription factors of LGMN targeted genes using the Network Analyst 3.0, TRRUST (v2.0) server, and ENCODE. The Genotype-Tissue Expression (GTEx) and BEST tool were used to investigate the expression pattern of the LGMN gene. In parallel, we performed in-silico drug designing of the novel inhibitor scaffold of δ-secretase as powerful therapeutic targets by using the concept of scaffolds and frameworks. In this context, this study also aimed at identifying effective small molecule inhibitors targeting δ-secretase.

RESULTS

Among the 16 experimentally verified miRNAs, Network analysis of the LGMN and its associated miRNA identify novel hsa-miRNA-106a-5p and hsa-miRNA-34a-5p being more expressed in the brain. Our in silico high throughput screening, followed by XP docking revealed Oprea1 as the lead. Molecular dynamic simulations of the δ-secretase-docked complex have been carried out for a time period of 200 ns and revealed that Root Mean Square Deviation (RMSD) of the protein Cα-backbone with respect to its starting position increased to 1.20 Å for the first 25 ns of the trajectory and then became stable around 0.6 Å in the last 170 ns course of the simulation. The radius of gyration (RGYR) reveals that compactness was maintained till the end of simulations.

CONCLUSION

Network analysis of LGMN associated miRNAs lead to the identification of two novel miRNAs, being highly expressed in the brain. This study also lead to the identification and expression of 10 Transcription factors associated with LGMN. Expression Heatmap results show high and continuous expression of LGMN in most of the regions of the brain, especially in the frontal cortex. Further, in silico drug analysis led us to the identification of Oprea1 which could be taken for further investigation to explore its potential for AD therapy.

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

Agonal Factors Distort Gene-Expression Patterns in Human Postmortem Brains

Agonal factors, the conditions that occur just prior to death, can impact the molecular quality of postmortem brains, influencing gene expression results. Our study used gene expression data of 262 samples from ROSMAP with the detailed terminal state recorded for each donor, such as fever, infection, and unconsciousness. Fever and infection were the primary contributors to brain gene expression changes, brain cell-type-specific gene expression, and cell proportion changes. Furthermore, we also found that previous studies of gene expression in postmortem brains were confounded by agonal factors. Therefore, correction for agonal factors is important in the step of data preprocessing. Our analyses revealed fever and infection contributing to gene expression changes in postmortem brains and emphasized the necessity of study designs that document and account for agonal factors.

C21orf91 Regulates Oligodendroglial Precursor Cell Fate-A Switch in the Glial Lineage?

Neuropathological diseases of the central nervous system (CNS) are frequently associated with impaired differentiation of the oligodendroglial cell lineage and subsequent alterations in white matter structure and dynamics. Down syndrome (DS), or trisomy 21, is the most common genetic cause for cognitive impairments and intellectual disability (ID) and is associated with a reduction in the number of neurons and oligodendrocytes, as well as with hypomyelination and astrogliosis. Recent studies mainly focused on neuronal development in DS and underestimated the role of glial cells as pathogenic players. This also relates to C21ORF91, a protein considered a key modulator of aberrant CNS development in DS. We investigated the role of C21orf91 ortholog in terms of oligodendrogenesis and myelination using database information as well as through cultured primary oligodendroglial precursor cells (OPCs). Upon modulation of C21orf91 gene expression, we found this factor to be important for accurate oligodendroglial differentiation, influencing their capacity to mature and to myelinate axons. Interestingly, C21orf91 overexpression initiates a cell population coexpressing astroglial- and oligodendroglial markers indicating that elevated C21orf91 expression levels induce a gliogenic shift towards the astrocytic lineage reflecting non-equilibrated glial cell populations in DS brains.

Brain Banks Spur New Frontiers in Neuropsychiatric Research and Strategies for Analysis and Validation

Neuropsychiatric disorders affect hundreds of millions of patients and families worldwide. To decode the molecular framework of these diseases, many studies use human postmortem brain samples. These studies reveal brain-specific genetic and epigenetic patterns via high-throughput sequencing technologies. Identifying best practices for the collection of postmortem brain samples, analyzing such large amounts of sequencing data, and interpreting these results are critical to advance neuropsychiatry. We provide an overview of human brain banks worldwide, including progress in China, highlighting some well-known projects using human postmortem brain samples to understand molecular regulation in both normal brains and those with neuropsychiatric disorders. Finally, we discuss future research strategies, as well as state-of-the-art statistical and experimental methods that are drawn upon brain bank resources to improve our understanding of the agents of neuropsychiatric disorders.