RFMix-reader: Accelerated reading and processing for local ancestry studies.

Motivation: Local ancestry inference is a powerful technique in genetics, revealing population history and the genetic basis of diseases. It is particularly valuable for improving eQTL discovery and fine-mapping in admixed populations. Despite the widespread use of the RFMix software for local ancestry inference, large-scale genomic studies face challenges of high memory consumption and processing times when handling RFMix output files.

Sex affects transcriptional associations with schizophrenia across the dorsolateral prefrontal cortex, hippocampus, and caudate nucleus.

Schizophrenia is a complex neuropsychiatric disorder with sexually dimorphic features, including differential symptomatology, drug responsiveness, and male incidence rate. Prior large-scale transcriptome analyses for sex differences in schizophrenia have focused on the prefrontal cortex. Analyzing BrainSeq Consortium data (caudate nucleus: n = 399, dorsolateral prefrontal cortex: n = 377, and hippocampus: n = 394), we identified 831 unique genes that exhibit sex differences across brain regions, enriched for immune-related pathways.

Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donors' Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia.

Objective: Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs).

dRFEtools: dynamic recursive feature elimination for omics.

Motivation: Advances in technology have generated larger omics datasets with potential applications for machine learning. In many datasets, however, cost and limited sample availability result in an excessively higher number of features as compared to observations. Moreover, biological processes are associated with networks of core and peripheral genes, while traditional feature selection approaches capture only core genes.

Analysis of the caudate nucleus transcriptome in individuals with schizophrenia highlights effects of antipsychotics and new risk genes.

Most studies of gene expression in the brains of individuals with schizophrenia have focused on cortical regions, but subcortical nuclei such as the striatum are prominently implicated in the disease, and current antipsychotic drugs target the striatum's dense dopaminergic innervation. Here, we performed a comprehensive analysis of the genetic and transcriptional landscape of schizophrenia in the postmortem caudate nucleus of the striatum of 443 individuals (245 neurotypical individuals, 154 individuals with schizophrenia and 44 individuals with bipolar disorder), 210 from African and 233 from European ancestries. Integrating expression quantitative trait loci analysis, Mendelian randomization with the latest schizophrenia genome-wide association study, transcriptome-wide association study and differential expression analysis, we identified many genes associated with schizophrenia risk, including potentially the dopamine D2 receptor short isoform.

Variation in TAF1 expression in female carrier induced pluripotent stem cells and human brain ontogeny has implications for adult neostriatum vulnerability in X-linked Dystonia Parkinsonism.

X-linked Dystonia-Parkinsonism (XDP) is an inherited, X-linked, adult-onset movement disorder characterized by degeneration in the neostriatum. No therapeutics alter disease progression. The mechanisms underlying regional differences in degeneration and adult onset are unknown.

Developmental excitation-inhibition imbalance underlying psychoses revealed by single-cell analyses of discordant twins-derived cerebral organoids.

Despite extensive genetic and neuroimaging studies, detailed cellular mechanisms underlying schizophrenia and bipolar disorder remain poorly understood. Recent progress in single-cell RNA sequencing (scRNA-seq) technologies enables identification of cell-type-specific pathophysiology. However, its application to psychiatric disorders is challenging because of methodological difficulties in analyzing human brains and the confounds due to a lifetime of illness.