Ebbert, Mark

AbstractBackgroundRNA‐seq experiments have traditionally been done with short‐read sequencing technologies that, by nature, collapse all RNA isoforms for a given gene into a single expression measurement—a major oversimplification of the underlying biology. Collapsing all RNA isoforms for a single gene severely limits our ability to characterize all RNA isoforms and determine their individual downstream functions. While computational approaches for assembling short reads into full transcripts exist, these methods are inherently structurally inaccurate, especially when compared to full‐length sequencing possible with long‐read sequencing technologies. In contrast, long‐read sequencing technologies can sequence entire RNA molecules, allowing researchers to accurately quantify expression for the complete set of RNA isoform species, including de novo RNA isoforms. Long‐read sequencing is especially well suited for discovering novel isoforms in the recently released telomere‐to‐telomere (T2T) human reference genome (CHM13). The new CHM13 genome assembly resolved highly homologous regions that are challenging to study with short‐reads. Here we sequenced post‐mortem human brain tissue with long‐reads and aligned them to CHM13 to explore novel gene bodies and transcript isoforms.MethodsWe sequenced pre‐frontal cortex tissue from four post‐mortem human brain samples using Oxford Nanopore Technologies long‐read sequencing for PCR amplified cDNA. Data were basecalled using Guppy, reads were aligned to the CHM13 human reference genome using minimap2, and transcripts were assembled and quantified with the Bambu package in R.ResultsAmong other findings, we discovered 84 new, high‐confidence gene bodies expressed in all four samples with at least 5 reads in each sample. We also found 223 novel RNA isoforms in previously annotated gene bodies. Of these 223 novel isoforms, 29 aligned to medically relevant genes such as MAOB, HLA‐DRB1, and ABO.ConclusionsOur results suggest long‐reads aligned to the CHM13 reference genome have the potential to reveal novel gene bodies and transcript isoforms that were missed in previous studies. These methods can provide a more complete picture of the transcriptomic landscape of diseases, including Alzheimer’s disease—hopefully generating information with potential to help inform future treatment and/or early diagnostic efforts.

AbstractTo examine the length of a hexanucleotide expansion in C9orf72, which represents the most frequent genetic cause of frontotemporal lobar degeneration and motor neuron disease, we employed a targeted amplification-free long-read sequencing technology: No-Amp sequencing. In our cross-sectional study, we assessed cerebellar tissue from 28 well-characterized C9orf72 expansion carriers. We obtained 3507 on-target circular consensus sequencing reads, of which 814 bridged the C9orf72 repeat expansion (23%). Importantly, we observed a significant correlation between expansion sizes obtained using No-Amp sequencing and Southern blotting (P = 5.0 × 10−4). Interestingly, we also detected a significant survival advantage for individuals with smaller expansions (P = 0.004). Additionally, we uncovered that smaller expansions were significantly associated with higher levels of C9orf72 transcripts containing intron 1b (P = 0.003), poly(GP) proteins (P = 1.3 × 10− 5), and poly(GA) proteins (P = 0.005). Thorough examination of the composition of the expansion revealed that its GC content was extremely high (median: 100%) and that it was mainly composed of GGGGCC repeats (median: 96%), suggesting that expanded C9orf72 repeats are quite pure. Taken together, our findings demonstrate that No-Amp sequencing is a powerful tool that enables the discovery of relevant clinicopathological associations, highlighting the important role played by the cerebellar size of the expanded repeat in C9orf72-linked diseases.

Polygenic scores (or genetic risk scores) quantify the aggregate of small effects from many common genetic loci that have been associated with a trait through genome-wide association. Polygenic scores were first used successfully in schizophrenia and have since been applied to multiple phenotypes including multiple sclerosis, rheumatoid arthritis, and height. Because human height is an easily-measured and complex polygenic trait, polygenic height scores provide exciting insights into the predictability of aggregate common variant effect on the phenotype. Shawn Bradley is an extremely tall former professional basketball player from Brigham Young University and the National Basketball Association (NBA), measuring 2.29 meters (7 ′ 6 ″ , 99.99999th percentile for height) tall, with no known medical conditions. Here, we present a case where a rare combination of common SNPs in one individual results in an extremely high polygenic height score that is correlated with an extreme phenotype. While polygenic scores are not clinically significant in the average case, our findings suggest that for extreme phenotypes, polygenic scores may be more successful for the prediction of individuals.

Alzheimer’s disease (AD) is an age-associated neurodegenerative disease characterized by amyloidosis, tauopathy, and activation of microglia, the brain resident innate immune cells. We show that a RiboTag translational profiling approach can bypass biases due to cellular enrichment/cell sorting. Using this approach in models of amyloidosis, tauopathy, and aging, we revealed a common set of alterations and identified a central APOE-driven network that converged on CCL3 and CCL4 across all conditions. Notably, aged females demonstrated a significant exacerbation of many of these shared transcripts in this APOE network, revealing a potential mechanism for increased AD susceptibility in females. This study has broad implications for microglial transcriptomic approaches and provides new insights into microglial pathways associated with different pathological aspects of aging and AD.