Impact of genome build on RNA-seq interpretation and diagnostics.

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network and Genomics Research to Elucidate the Genetics of Rare Disease Consortium.

Loss of function of FAM177A1, a Golgi complex localized protein, causes a novel neurodevelopmental disorder.

Purpose: The function of FAM177A1 and its relationship to human disease is largely unknown. Recent studies have demonstrated FAM177A1 to be a critical immune-associated gene. One previous case study has linked FAM177A1 to a neurodevelopmental disorder in 4 siblings.

Integration of transcriptomics and long-read genomics prioritizes structural variants in rare disease.

Rare structural variants (SVs) - insertions, deletions, and complex rearrangements - can cause Mendelian disease, yet they remain difficult to accurately detect and interpret. We sequenced and analyzed Oxford Nanopore long-read genomes of 68 individuals from the Undiagnosed Disease Network (UDN) with no previously identified diagnostic mutations from short-read sequencing. Using our optimized SV detection pipelines and 571 control long-read genomes, we detected 716 long-read rare (MAF < 0.

APOE loss-of-function variants: Compatible with longevity and associated with resistance to Alzheimer's disease pathology.

The ε4 allele of apolipoprotein E (APOE) is the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Knockdown of ε4 may provide a therapeutic strategy for AD, but the effect of APOE loss of function (LoF) on AD pathogenesis is unknown. We searched for APOE LoF variants in a large cohort of controls and patients with AD and identified seven heterozygote carriers of APOE LoF variants.

A 3'UTR Insertion Is a Candidate Causal Variant at the Locus Associated with Increased Risk for FTLD-TDP.

Background And Objectives: Single nucleotide variants near associate with risk of frontotemporal lobar dementia with TDP-43 inclusions (FTLD-TDP) and Alzheimer's disease (AD) in genome-wide association studies (GWAS), but the causal variant at this locus remains unclear. Here we asked whether a novel structural variant on is the causal variant.

Methods: An exploratory analysis identified structural variants on neurodegeneration-related genes.

The effect of sudden-onset distractors on reading efficiency and comprehension.

Reading is an essential skill that requires focused attention. However, much reading is done in non-optimal environments. These days, reading is often done on digital devices or with a digital device nearby.

Accelerated identification of disease-causing variants with ultra-rapid nanopore genome sequencing.

Whole-genome sequencing (WGS) can identify variants that cause genetic disease, but the time required for sequencing and analysis has been a barrier to its use in acutely ill patients. In the present study, we develop an approach for ultra-rapid nanopore WGS that combines an optimized sample preparation protocol, distributing sequencing over 48 flow cells, near real-time base calling and alignment, accelerated variant calling and fast variant filtration for efficient manual review. Application to two example clinical cases identified a candidate variant in <8 h from sample preparation to variant identification.

Culture shock: microglial heterogeneity, activation, and disrupted single-cell microglial networks in vitro.

Background: Microglia, the resident immune cells of the brain, play a critical role in numerous diseases, but are a minority cell type and difficult to genetically manipulate in vivo with viral vectors and other approaches. Primary cultures allow a more controlled setting to investigate these cells, but morphological and transcriptional changes upon removal from their normal brain environment raise many caveats from in vitro studies.

Methods: To investigate whether cultured microglia recapitulate in vivo microglial signatures, we used single-cell RNA sequencing (scRNAseq) to compare microglia freshly isolated from the brain to primary microglial cultures.

Widespread choroid plexus contamination in sampling and profiling of brain tissue.

The choroid plexus, a tissue responsible for producing cerebrospinal fluid, is found predominantly in the lateral and fourth ventricles of the brain. This highly vascularized and ciliated tissue is made up of specialized epithelial cells and capillary networks surrounded by connective tissue. Given the complex structure of the choroid plexus, this can potentially result in contamination during routine tissue dissection.

Clusterin ameliorates tau pathology in vivo by inhibiting fibril formation.

The molecular chaperone Clusterin (CLU) impacts the amyloid pathway in Alzheimer's disease (AD) but its role in tau pathology is unknown. We observed CLU co-localization with tau aggregates in AD and primary tauopathies and CLU levels were upregulated in response to tau accumulation. To further elucidate the effect of CLU on tau pathology, we utilized a gene delivery approach in CLU knock-out (CLU KO) mice to drive expression of tau bearing the P301L mutation.

Analysis of Identification Method for Bacterial Species and Antibiotic Resistance Genes Using Optical Data From DNA Oligomers.

Bacterial antibiotic resistance is becoming a significant health threat, and rapid identification of antibiotic-resistant bacteria is essential to save lives and reduce the spread of antibiotic resistance. This paper analyzes the ability of machine learning algorithms (MLAs) to process data from a novel spectroscopic diagnostic device to identify antibiotic-resistant genes and bacterial species by comparison to available bacterial DNA sequences. Simulation results show that the algorithms attain from 92% accuracy (for genes) up to 99% accuracy (for species).