Age-Correlated Gene Expression in Normal and Neurodegenerative Human Brain Tissues

Human brain aging has received special attention in part because of the elevated risks of neurodegenerative disorders such as Alzheimer's disease in seniors. Recent technological advances enable us to investigate whether similar mechanisms underlie aging and neurodegeneration, by quantifying the similarities and differences in their genome-wide gene expression profiles.We have developed a computational method for assessing an individual's "physiological brain age" by comparing global mRNA expression datasets across a range of normal human brain samples. Application of this method to brains samples from select regions in two diseases--Alzheimer's disease (AD, superior frontal gyrus), frontotemporal lobar degeneration (FTLD, in rostral aspect of frontal cortex ∼BA10)--showed that while control cohorts exhibited no significant difference between physiological and chronological ages, FTLD and AD exhibited prematurely aged expression profiles.This study establishes a quantitative scale for measuring premature aging in neurodegenerative disease cohorts, and it identifies specific physiological mechanisms common to aging and some forms of neurodegeneration. In addition, accelerated expression profiles associated with AD and FTLD suggest some common mechanisms underlying the risk of developing these diseases

Genome-Wide Double-Stranded RNA Sequencing Reveals the Functional Significance of Base-Paired RNAs in \u3cem\u3eArabidopsis\u3c/em\u3e

The functional structure of all biologically active molecules is dependent on intra- and inter-molecular interactions. This is especially evident for RNA molecules whose functionality, maturation, and regulation require formation of correct secondary structure through encoded base-pairing interactions. Unfortunately, intra- and inter-molecular base-pairing information is lacking for most RNAs. Here, we marry classical nuclease-based structure mapping techniques with high-throughput sequencing technology to interrogate all base-paired RNA in Arabidopsis thaliana and identify ∼200 new small (sm)RNA–producing substrates of RNA–DEPENDENT RNA POLYMERASE6. Our comprehensive analysis of paired RNAs reveals conserved functionality within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs, as well as a novel population of functional RNAs, many of which are the precursors of smRNAs. Finally, we identify intra-molecular base-pairing interactions to produce a genome-wide collection of RNA secondary structure models. Although our methodology reveals the pairing status of RNA molecules in the absence of cellular proteins, previous studies have demonstrated that structural information obtained for RNAs in solution accurately reflects their structure in ribonucleoprotein complexes. Furthermore, our identification of RNA–DEPENDENT RNA POLYMERASE6 substrates and conserved functional RNA domains within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs using this approach strongly suggests that RNA molecules are correctly folded into their secondary structure in solution. Overall, our findings highlight the importance of base-paired RNAs in eukaryotes and present an approach that should be widely applicable for the analysis of this key structural feature of RNA

Lamin B1 Depletion in Senescent Cells Triggers Large-Scale Changes in Gene Expression and the Chromatin Landscape

Senescence is a stable proliferation arrest, associated with an altered secretory pathway, thought to promote tumor suppression and tissue aging. While chromatin regulation and lamin B1 down-regulation have been implicated as senescence effectors, functional interactions between them are poorly understood. We compared genome-wide Lys4 trimethylation on histone H3 (H3K4me3) and H3K27me3 distributions between proliferating and senescent human cells and found dramatic differences in senescence, including large-scale domains of H3K4me3- and H3K27me3-enriched “mesas” and H3K27me3-depleted “canyons.” Mesas form at lamin B1-associated domains (LADs) in replicative senescence and oncogene-induced senescence and overlap DNA hypomethylation regions in cancer, suggesting that pre-malignant senescent chromatin changes foreshadow epigenetic cancer changes. Hutchinson-Gilford progeria syndrome fibroblasts (mutant lamin A) also show evidence of H3K4me3 mesas, suggesting a link between premature chromatin changes and accelerated cell senescence. Canyons mostly form between LADs and are enriched in genes and enhancers. H3K27me3 loss is correlated with up-regulation of key senescence genes, indicating a link between global chromatin changes and local gene expression regulation. Lamin B1 reduction in proliferating cells triggers senescence and formation of mesas and canyons. Our data illustrate profound chromatin reorganization during senescence and suggest that lamin B1 down-regulation in senescence is a key trigger of global and local chromatin changes that impact gene expression, aging, and cancer

H3K36 Methylation Promotes Longevity by Enhancing Transcriptional Fidelity

Epigenetic mechanisms, including histone post-translational modifications, control longevity in diverse organisms. Relatedly, loss of proper transcriptional regulation on a global scale is an emerging phenomenon of shortened life span, but the specific mechanisms linking these observations remain to be uncovered. Here, we describe a life span screen in Saccharomyces cerevisiae that is designed to identify amino acid residues of histones that regulate yeast replicative aging. Our results reveal that lack of sustained histone H3K36 methylation is commensurate with increased cryptic transcription in a subset of genes in old cells and with shorter life span. In contrast, deletion of the K36me2/3 demethylase Rph1 increases H3K36me3 within these genes, suppresses cryptic transcript initiation, and extends life span. We show that this aging phenomenon is conserved, as cryptic transcription also increases in old worms. We propose that epigenetic misregulation in aging cells leads to loss of transcriptional precision that is detrimental to life span, and, importantly, this acceleration in aging can be reversed by restoring transcriptional fidelity

Altered gene expression in the Werner and Bloom syndromes is associated with sequences having G-quadruplex forming potential

The human Werner and Bloom syndromes (WS and BS) are caused by deficiencies in the WRN and BLM RecQ helicases, respectively. WRN, BLM and their Saccharomyces cerevisiae homologue Sgs1, are particularly active in vitro in unwinding G-quadruplex DNA (G4-DNA), a family of non-canonical nucleic acid structures formed by certain G-rich sequences. Recently, mRNA levels from loci containing potential G-quadruplex-forming sequences (PQS) were found to be preferentially altered in sgs1Δ mutants, suggesting that G4-DNA targeting by Sgs1 directly affects gene expression. Here, we extend these findings to human cells. Using microarrays to measure mRNAs obtained from human fibroblasts deficient for various RecQ family helicases, we observe significant associations between loci that are upregulated in WS or BS cells and loci that have PQS. No such PQS associations were observed for control expression datasets, however. Furthermore, upregulated genes in WS and BS showed no or dramatically reduced associations with sequences similar to PQS but that have considerably reduced potential to form intramolecular G4-DNA. These findings indicate that, like Sgs1, WRN and BLM can regulate transcription globally by targeting G4-DNA

Model performance and interpretability of semi-supervised generative adversarial networks to predict oncogenic variants with unlabeled data

Abstract Background It remains an important challenge to predict the functional consequences or clinical impacts of genetic variants in human diseases, such as cancer. An increasing number of genetic variants in cancer have been discovered and documented in public databases such as COSMIC, but the vast majority of them have no functional or clinical annotations. Some databases, such as CiVIC are available with manual annotation of functional mutations, but the size of the database is small due to the use of human annotation. Since the unlabeled data (millions of variants) typically outnumber labeled data (thousands of variants), computational tools that take advantage of unlabeled data may improve prediction accuracy. Result To leverage unlabeled data to predict functional importance of genetic variants, we introduced a method using semi-supervised generative adversarial networks (SGAN), incorporating features from both labeled and unlabeled data. Our SGAN model incorporated features from clinical guidelines and predictive scores from other computational tools. We also performed comparative analysis to study factors that influence prediction accuracy, such as using different algorithms, types of features, and training sample size, to provide more insights into variant prioritization. We found that SGAN can achieve competitive performances with small labeled training samples by incorporating unlabeled samples, which is a unique advantage compared to traditional machine learning methods. We also found that manually curated samples can achieve a more stable predictive performance than publicly available datasets. Conclusions By incorporating much larger samples of unlabeled data, the SGAN method can improve the ability to detect novel oncogenic variants, compared to other machine-learning algorithms that use only labeled datasets. SGAN can be potentially used to predict the pathogenicity of more complex variants such as structural variants or non-coding variants, with the availability of more training samples and informative features

Mung bean nuclease treatment significantly increases on-target efficiency for DNA enriched through RainDance microdroplet-PCR.

<p>Aliquots of RainDance enriched DNA for the same sample were either treated or not treated with mung bean nuclease, processed into TruSeq libraries, and sequenced on MiSeq as illustrated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103491#pone-0103491-g001" target="_blank">Figure 1A</a>. Plotted is the mean value of on-target efficiency of 3 samples that went through parallel treatments (also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103491#pone-0103491-t002" target="_blank">Table 2</a>). Nuclease treatment leads to significantly higher on-target efficiency (*<i>p</i> = 0.018, one-tail paired <i>t</i> test; error bar, SEM).</p

Mung Bean Nuclease Treatment Increases Capture Specificity of Microdroplet-PCR Based Targeted DNA Enrichment

<div><p>Targeted DNA enrichment coupled with next generation sequencing has been increasingly used for interrogation of select sub-genomic regions at high depth of coverage in a cost effective manner. Specificity measured by on-target efficiency is a key performance metric for target enrichment. Non-specific capture leads to off-target reads, resulting in waste of sequencing throughput on irrelevant regions. Microdroplet-PCR allows simultaneous amplification of up to thousands of regions in the genome and is among the most commonly used strategies for target enrichment. Here we show that carryover of single-stranded template genomic DNA from microdroplet-PCR constitutes a major contributing factor for off-target reads in the resultant libraries. Moreover, treatment of microdroplet-PCR enrichment products with a nuclease specific to single-stranded DNA alleviates off-target load and improves enrichment specificity. We propose that nuclease treatment of enrichment products should be incorporated in the workflow of targeted sequencing using microdroplet-PCR for target capture. These findings may have a broad impact on other PCR based applications for which removal of template DNA is beneficial.</p></div

Comparison of variants detected for the same sample either treated or not treated with mung bean nuclease.

<p>*: Variants detected only when samples were treated with mung bean nuclease.</p