By sequencing post-mortem brain tissue from individuals with bipolar disorder, a team led by scientists from Johns Hopkins University has identified genes and pathways involved in the psychiatric disorder. Recent genome-wide association studies have linked certain genetic variants to bipolar disorder, but how brain gene expression is altered in the condition and how genetic risk for bipolar disorder may contribute to these alterations is unknown. To investigate, the scientists performed RNA sequencing on hundreds of subgenual anterior cingulate cortex and amygdala samples from nearly 300 bipolar disorder patients and neurotypical controls. As reported in this week's Nature Neuroscience, they tested for transcriptional differences between those with bipolar disorder and unaffected controls and further examined the transcriptional effects of bipolar disorder-associated genetic variants. Their findings include two coexpressed modules that were associated with transcriptional changes in bipolar disorder including one enriched for immune and inflammatory genes and one with genes related to the postsynaptic membrane. "The findings reported here should help guide follow-up functional work to further elucidate the mechanisms by which implicated transcriptional changes in these genes contribute to risk for [bipolar disorder]," the study's authors write. GenomeWeb has more on this, here.
A new technique for single-nuclei RNA sequencing is reported in Nature Biotechnology this week. Single-nuclei sequencing enables the characterization of cell types at the gene level and is commonly used with frozen tissue including human brain. Yet many single-nuclei cDNAs are purely intronic, lack barcodes, and hinder the study of isoforms. To address these shortcomings, a group led by researchers from Weill Cornell Medicine developed single-nuclei isoform RNA sequencing, or SnISOr-Seq, which uses microfluidics, PCR-based artifact removal, target enrichment, and long-read sequencing to increase barcoded, exon-spanning long reads 7.5-fold compared to traditional long-read single-nuclei sequencing. To demonstrate the method, the scientists applied it to adult human frontal cortex and find, among other things, that exons associated with distinct diseases including autism and schizophrenia exhibit distinct behavior in terms of inclusion variability across cell types and coordination.