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Interest in circulating RNAs for monitoring and diagnosing human health has grown significantly. There are few datasets describing baseline expression levels for total cell-free circulating RNA from healthy control subjects. In this study, total extracellular RNA (exRNA) was isolated and sequenced from 183 plasma samples, 204 urine samples and 46 saliva samples from 55 male college athletes ages 18–25 years. Many participants provided more than one sample, allowing us to investigate variability in an individual’s exRNA expression levels over time. Here we provide a systematic analysis of small exRNAs present in each biofluid, as well as an analysis of exogenous RNAs. The small RNA profile of each biofluid is distinct. We find that a large number of RNA fragments in plasma (63%) and urine (54%) have sequences that are assigned to YRNA and tRNA fragments respectively. Surprisingly, while many miRNAs can be detected, there are few miRNAs that are consistently detected in all samples from a single biofluid, and profiles of miRNA are different for each biofluid. Not unexpectedly, saliva samples have high levels of exogenous sequence that can be traced to bacteria. These data significantly contribute to the current number of sequenced exRNA samples from normal healthy individuals.

Background 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. Results 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). Conclusions 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.

Lizards, which are amniote vertebrates like humans, are able to lose and regenerate a functional tail. Understanding the molecular basis of this process would advance regenerative approaches in amniotes, including humans. We have carried out the first transcriptomic analysis of tail regeneration in a lizard, the green anole Anolis carolinensis, which revealed 326 differentially expressed genes activating multiple developmental and repair mechanisms. Specifically, genes involved in wound response, hormonal regulation, musculoskeletal development, and the Wnt and MAPK/FGF pathways were differentially expressed along the regenerating tail axis. Furthermore, we identified 2 microRNA precursor families, 22 unclassified non-coding RNAs, and 3 novel protein-coding genes significantly enriched in the regenerating tail. However, high levels of progenitor/stem cell markers were not observed in any region of the regenerating tail. Furthermore, we observed multiple tissue-type specific clusters of proliferating cells along the regenerating tail, not localized to the tail tip. These findings predict a different mechanism of regeneration in the lizard than the blastema model described in the salamander and the zebrafish, which are anamniote vertebrates. Thus, lizard tail regrowth involves the activation of conserved developmental and wound response pathways, which are potential targets for regenerative medical therapies.

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson’s disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug–gene interactions. We performed automated ML on multimodal data from the Parkinson’s progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson’s Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

Background The green anole lizard, Anolis carolinensis , is a key species for both laboratory and field-based studies of evolutionary genetics, development, neurobiology, physiology, behavior, and ecology. As the first non-avian reptilian genome sequenced, A. carolinesis is also a prime reptilian model for comparison with other vertebrate genomes. The public databases of Ensembl and NCBI have provided a first generation gene annotation of the anole genome that relies primarily on sequence conservation with related species. A second generation annotation based on tissue-specific transcriptomes would provide a valuable resource for molecular studies. Results Here we provide an annotation of the A. carolinensis genome based on de novo assembly of deep transcriptomes of 14 adult and embryonic tissues. This revised annotation describes 59,373 transcripts, compared to 16,533 and 18,939 currently for Ensembl and NCBI, and 22,962 predicted protein-coding genes. A key improvement in this revised annotation is coverage of untranslated region (UTR) sequences, with 79% and 59% of transcripts containing 5’ and 3’ UTRs, respectively. Gaps in genome sequence from the current A. carolinensis build (Anocar2.0) are highlighted by our identification of 16,542 unmapped transcripts, representing 6,695 orthologues, with less than 70% genomic coverage. Conclusions Incorporation of tissue-specific transcriptome sequence into the A. carolinensis genome annotation has markedly improved its utility for comparative and functional studies. Increased UTR coverage allows for more accurate predicted protein sequence and regulatory analysis. This revised annotation also provides an atlas of gene expression specific to adult and embryonic tissues.

Background Lizards are evolutionarily the most closely related vertebrates to humans that can lose and regrow an entire appendage. Regeneration in lizards involves differential expression of hundreds of genes that regulate wound healing, musculoskeletal development, hormonal response, and embryonic morphogenesis. While microRNAs are able to regulate large groups of genes, their role in lizard regeneration has not been investigated. Results MicroRNA sequencing of green anole lizard ( Anolis carolinensis ) regenerating tail and associated tissues revealed 350 putative novel and 196 known microRNA precursors. Eleven microRNAs were differentially expressed between the regenerating tail tip and base during maximum outgrowth (25 days post autotomy), including miR-133a , miR-133b , and miR-206 , which have been reported to regulate regeneration and stem cell proliferation in other model systems. Three putative novel differentially expressed microRNAs were identified in the regenerating tail tip. Conclusions Differentially expressed microRNAs were identified in the regenerating lizard tail, including known regulators of stem cell proliferation. The identification of 3 putative novel microRNAs suggests that regulatory networks, either conserved in vertebrates and previously uncharacterized or specific to lizards, are involved in regeneration. These findings suggest that differential regulation of microRNAs may play a role in coordinating the timing and expression of hundreds of genes involved in regeneration.

While motor and cortical neurons are affected in C9orf72 amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD), it remains largely unknown if and how non-neuronal cells induce or exacerbate neuronal damage. We differentiated C9orf72 ALS/FTD patient-derived induced pluripotent stem cells 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 ALS/FTD iPSC-MG equally express microglial specific genes and perform microglial functions, including inflammatory cytokine release and phagocytosis of extracellular cargos, such as synthetic amyloid beta peptides and healthy human brain synaptoneurosomes. RNA sequencing analysis revealed select transcriptional changes of genes associated with neuroinflammation or neurodegeneration in diseased microglia yet no significant differentially expressed microglial-enriched genes. Moderate molecular and functional differences were observed in C9orf72 iPSC-MG mono-cultures despite the presence of C9orf72 pathological features suggesting that a diseased microenvironment may be required to induce phenotypic changes in microglial cells and the associated neuronal dysfunction seen in C9orf72 ALS/FTD neurodegeneration.

The growing utility and availability of genome-scale sequencing has led to increasingly broad incorporation across specialty disciplines of clinical research. However, classification of clinical relevance of genetic variation is an inherently clinical task, and the expertise to perform the necessary analysis, confirmation and reporting of these variants is not available in all research teams; consequently, disclosure of genomic variants to research participants remains challenging for many researchers. Advancing genomic medicine as a standard of care first requires institutional commitment and partnerships in supporting genomics in varied research studies that are inclusive of return of results to participants. The University of North Carolina at Chapel Hill has vast experience with genetics in both clinical and research realms. By utilizing historical experience and input from key players, the Clinical GENomic analYSIS (GENYSIS) core facility was created as a case study and aims to provide a roadmap for research organizations to implement their own genomic sequencing core facilities. The core has established a molecular sign-out conference, partnered with other core facilities on campus, and provides five main services: bioinformatics, variant analysis, clinical reporting, post-test services, and consultation with project advising. This paper presents case examples with discussion of continuous methodology improvements and embedded educational activities. This novel shared research resource enables clinical researchers with limited staff and genomics expertise to provide clinically relevant results to their study participants, expanding the reach of genomics research.

Standard chow diets influence reproducibility in animal model experiments because chows have different nutrient compositions, which can independently influence phenotypes. However, there is little evidence of the role of timing in the extent of variability caused by chow exposure. Here we measured the impact of different diets (5V5M, 5V0G, 2920X and 5058) and timing of exposure (adult exposure (AE), lifetime exposure (LE) and developmental exposure (DE)) on growth and development, metabolic health indicators and gut bacterial microbiota profiles across genetically identical C57BL/6J mice. Diet drove differences in macro- and micronutrient intake for all exposure models. AE had no effect on phenotypic outcomes. However, LE mice exhibited significant sex-dependent diet effects on growth, body weight and body composition. LE effects were mostly absent in the DE model, where mice were exposed to chow differences only from conception to weaning. Both AE and LE models exhibited similar diet-driven beta diversity profiles for the gut bacterial microbiota, with 5058 diet driving the most distinct profile. However, compared with AE, LE effects on beta diversity were sex dependent, and LE mice exhibited nine times more differentially abundant bacterial genera, the majority of which were inversely affected by 2920X and 5058 diets. Our findings demonstrate that LE to different chow diets has the greatest impact on the reproducibility of several experimental measures commonly used in preclinical mouse model studies. Importantly, weaning mice from different diets onto the same diet for maturation may be an effective way to reduce unwanted phenotypic variability among experimental models. Differences in standard chow diets can influence mouse model phenotypes and impact experimental reproducibility. Here Knuth et al. show that the timing during which mice are exposed to standard chow can also affect phenotypic outcomes.

As amniote vertebrates, lizards are the most closely related organisms to humans capable of appendage regeneration. Lizards can autotomize, or release their tails as a means of predator evasion, and subsequently regenerate a functional replacement. Green anoles (Anolis carolinensis) can regenerate their tails through a process that involves differential expression of hundreds of genes, which has previously been analyzed by transcriptomic and microRNA analysis. To investigate protein expression in regenerating tissue, we performed a whole proteomic analysis of regenerating tail tip and base. This is the first proteomic data set available for any anole lizard. We identified a total of 2646 proteins—976 proteins only in the regenerating tail base, 796 only in the tail tip, and 874 in both tip and base. For over 90% of these proteins in these tissues, we were able to assign a clear orthology to gene models in either the Ensembl or NCBI databases. For 13 proteins in the tail base, 9 proteins in the tail tip, and 10 proteins in both regions, the gene model in Ensembl and NCBI matched an uncharacterized protein, confirming that these predictions are present in the proteome. Ontology and pathways analysis of proteins expressed in the regenerating tail base identified categories, including actin filament‐based process, ncRNA metabolism, regulation of phosphatase activity, small GTPase‐mediated signal transduction, and cellular component organization or biogenesis. Analysis of proteins expressed in the tail tip identified categories, including regulation of organelle organization, regulation of protein localization, ubiquitin‐dependent protein catabolism, small GTPase‐mediated signal transduction, morphogenesis of epithelium, and regulation of biological quality. These proteomic findings confirm pathways and gene families activated in tail regeneration in the green anole as well as identify uncharacterized proteins whose role in regrowth remains to be revealed. This study demonstrates the insights that are possible from the integration of proteomic and transcriptomic data in tail regrowth in the green anole, with potentially broader application to studies in other regenerative models. KEY POINTS This research is highly interdisciplinary, combining our previous analyses with these most recent findings: Appendage regeneration is a conserved trait among vertebrates and has been characterized in animals ranging from teleost fish (zebrafish), urodele amphibians (axolotl), anuran amphibians (Xenopus frog), squamate reptiles (various species of lizards), and even crocodilians (American alligator). Comparative genomic and proteomic analysis of this process allows us to identify the genetic pathways and cellular processes under evolutionary selection for this regrowth capacity. Activating these conserved genetic pathways and cellular processes will be critical to developing regenerative medical therapies in humans. The identification of proteins expressed in regeneration extends analyses based only on predicted proteins from transcriptomic analysis, and permits integration with protein‐expression studies of regrowing nervous and musculoskeletal structures. Lizards are capable of multi‐tissue appendage regeneration, and anole lizards have been examined by transcriptomic and microRNA sequencing during tail regrowth. The first proteome for the green anole identified a total of 2,646 proteins in the regenerating tail, permitting integration of proteomic and transcriptomic data in this model. This proteomic analysis confirm pathways and gene families transcriptionally activated in tail regeneration in the green anole as well as identify uncharacterized proteins whose role in regrowth remains to be revealed.