Evolving interest in comprehensively profiling the full range of small RNAs present in small tissue biopsies and in circulating biofluids, and how the profile differs with disease, has launched small RNA sequencing (RNASeq) into more frequent use. However, known biases associated with small RNASeq, compounded by low RNA inputs, have been both a significant concern and a hurdle to widespread adoption. As RNASeq is becoming a viable choice for the discovery of small RNAs in low input samples and more labs are employing it, there should be benchmark datasets to test and evaluate the performance of new sequencing protocols and operators. In a recent publication from the National Institute of Standards and Technology, Pine et al., 2018, the investigators used a commercially available set of three tissues and tested performance across labs and platforms. In this paper, we further tested the performance of low RNA input in three commonly used and commercially available RNASeq library preparation kits; NEB Next, NEXTFlex, and TruSeq small RNA library preparation. We evaluated the performance of the kits at two different sites, using three different tissues (brain, liver, and placenta) with high (1 μg) and low RNA (10 ng) input from tissue samples, or 5.0, 3.0, 2.0, 1.0, 0.5, and 0.2 ml starting volumes of plasma. As there has been a lack of robust validation platforms for differentially expressed miRNAs, we also compared low input RNASeq data with their expression profiles on three different platforms (Abcam Fireplex, HTG EdgeSeq, and Qiagen miRNome). The concordance of RNASeq results on these three platforms was dependent on the RNA expression level; the higher the expression, the better the reproducibility. The results provide an extensive analysis of small RNASeq kit performance using low RNA input, and replication of these data on three downstream technologies.

Amyotrophic lateral sclerosis (ALS) is a genetically heterogeneous neurodegenerative disease in which 97% of patients exhibit cytoplasmic aggregates containing the RNA binding protein TDP-43. Using tagged ribosome affinity purifications in Drosophila models of TDP-43 proteinopathy, we identified TDP-43 dependent translational alterations in motor neurons impacting the spliceosome, pentose phosphate and oxidative phosphorylation pathways. A subset of the mRNAs with altered ribosome association are also enriched in TDP-43 complexes suggesting that they may be direct targets. Among these, dlp mRNA, which encodes the glypican Dally like protein (Dlp)/GPC6, a wingless (Wg/Wnt) signaling regulator is insolubilized both in flies and patient tissues with TDP-43 pathology. While Dlp/GPC6 forms puncta in the Drosophila neuropil and ALS spinal cords, it is reduced at the neuromuscular synapse in flies suggesting compartment specific effects of TDP-43 proteinopathy. These findings together with genetic interaction data show that Dlp/GPC6 is a novel, physiologically relevant target of TDP-43 proteinopathy.

Alzheimer’s disease (AD), due to its multifactorial nature and complex etiology, poses challenges for research, diagnosis, and treatment, and impacts millions worldwide. To address the need for minimally invasive, repeatable measures that aid in AD diagnosis and progression monitoring, studies leveraging RNAs associated with extracellular vesicles (EVs) in human biofluids have revealed AD-associated changes. However, the validation of AD biomarkers has suffered from the collection of samples from differing points in the disease time course or a lack of confirmed AD diagnoses. Here, we integrate clinical diagnosis and postmortem pathology data to form more accurate experimental groups and use small RNA sequencing to show that EVs from plasma can serve as a potential source of RNAs that reflect disease-related changes. Importantly, we demonstrated that these changes are identifiable in the EVs of preclinical patients, years before symptom manifestation, and that machine learning models based on differentially expressed RNAs can help predict disease conversion or progression. This research offers critical insight into early disease biomarkers and underscores the significance of accounting for disease progression and pathology in human AD studies.

Summary: While motor and cortical neurons are affected in C9orf72 ALS/FTD, it remains still largely unknown if and how non-neuronal cells induce or exacerbate neuronal damage. We generated C9orf72 ALS/FTD patient-derived induced pluripotent stem cells differentiated into microglia (iPSC-MG) and examined their intrinsic phenotypes. Similar to iPSC motor neurons, C9orf72 ALS/FTD iPSC-MG mono-cultures form G ₄ C ₂ repeat RNA foci, exhibit reduced C9orf72 protein levels and generate dipeptide repeat proteins. Healthy control and C9orf72 iPSC-MG equivalently express microglial specific genes and display microglial functions including inflammatory cytokine release and phagocytosis of extracellular toxic cargos such as synthetic amyloid beta peptides and healthy human brain synaptoneurosomes. Select C9orf72 iPSC-MG patient lines show inability to efficiently remove phagocytosed contents, suggesting dysfunction of the endosomal-lysosomal pathways. Finally, RNA sequencing revealed overall transcriptional changes in diseased microglia yet no significant differentially expressed microglial-enriched genes. These minimal differences in cellular, molecular and functional characteristics of microglial mono-cultures suggest that a diseased microenvironment is associated with microglial activation and subsequent regulation of neuronal dysfunction.

Coding and non-coding RNAs have diagnostic and prognostic importance in Parkinson’s diseases (PD). We studied circulating small non-coding RNAs (sncRNAs) in 7, 003 samples from two longitudinal PD cohorts (Parkinson’s Progression Marker Initiative (PPMI) and Luxembourg Parkinson’s Study (NCER-PD)) and modelled their influence on the transcriptome. First, we sequenced sncRNAs in 5, 450 blood samples of 1, 614 individuals in PPMI. The majority of 323 billion reads (59 million reads per sample) mapped to miRNAs. Other covered RNA classes include piRNAs, rRNAs, snoRNAs, tRNAs, scaRNAs, and snRNAs. De-regulated miRNAs were associated with the disease and disease progression and occur in two distinct waves in the third and seventh decade of live. Originating mostly from a characteristic set of immune cells they resemble a systemic inflammation response and mitochondrial dysfunction, two hallmarks of PD. By profiling 1, 553 samples from 1, 024 individuals in the NCER-PD cohort using an independent technology, we validate relevant findings from the sequencing study. Finally, network analysis of sncRNAs and transcriptome sequencing of the original cohort identified regulatory modules emerging in progressing PD patients.