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Recent work from Bonvento and colleagues indicated that synaptic and memory deficits in early Alzheimer's disease (AD) are related to a shortage in L-serine production in astrocytes. Here, the authors, responding to correspondence from Chen and colleagues, discuss how this deficiency does not necessarily require a decrease in PHGDH expression and conclude that the primary event leading to lower serine production is more likely related to altered glycolytic flux in early AD than to PHGDH expression.

We report consistent increases in phosphoglycerate dehydrogenase (PHGDH) expression in mouse models of Alzheimer’s disease (AD) (3xTg-AD) and related tauopathy (PS19), particularly in hippocampal astrocytes. Human single-cell RNA-sequencing data reveal a sequential increase of PHGDH expression in people with no, early, and late AD pathology, which is corroborated by protein mass spectrometry and immunohistochemical analyses of three independent cohorts. A sequential increase of PHGDH expression also correlates with increasing clinical AD symptoms and worsening cognitive decline in patients. The consistent increase of PHGDH expression in six AD cohorts (Mayo, ROSMAP, Mount Sinai, Baltimore, Amsterdam, and UCSD/UCI) corroborates with the recent report of PHGDH extracellular RNA in blood plasma as a candidate biomarker for early diagnosis of AD and offers a caution to the suggested use of L-serine as a potential therapy of AD.

RNA–chromatin interactions represent an important aspect of the transcriptional regulation of genes and transposable elements. However, analyses of chromatin-associated RNAs (caRNAs) are often limited to one caRNA at a time. Here, we describe the iMARGI (in situ mapping of RNA–genome interactome) technique, which is used to discover caRNAs and reveal their respective genomic interaction loci. iMARGI starts with in situ crosslinking and genome fragmentation, followed by converting each proximal RNA–DNA pair into an RNA–linker–DNA chimeric sequence. These chimeric sequences are subsequently converted into a sequencing library suitable for paired-end sequencing. A standardized bioinformatic software package, iMARGI-Docker, is provided to decode the paired-end sequencing data into caRNA–DNA interactions. Compared to its predecessor MARGI (mapping RNA–genome interactions), the number of input cells for iMARGI is 3–5 million (a 100-fold reduction), experimental time is reduced, and clear checkpoints have been established. It takes a few hours a day and a total of 8 d to complete the construction of an iMARGI sequencing library and 1 d to carry out data processing with iMARGI-Docker. iMARGI (in situ mapping of RNA–genome interactome) is a proximity ligation method for global profiling of chromatin-associated RNAs. A linker sequence bridges DNA and RNA in physical proximity, permitting sequencing library preparation and mapping of DNA–RNA contacts.

Chromatin-associated RNA (caRNA) is a vital component of the interphase nucleus; yet its distribution and role in the three-dimensional (3D) genome organization and function remain poorly understood. Here, we map caRNA’s spatial distribution on the 3D genome in human embryonic stem cells, fibroblasts, and myelogenous leukemia cells. We find that the relative abundance of trans-acting caRNA reflects the functional nuclear compartmentalization of the 3D genome, and the caRNA’s sequence features are predictive of its spatial localization. We observe extensive caRNA-genome interactions that span several hundred kilobases to several megabases. These caRNA domains correlate with chromatin loops and enhancer-promoter interactions. We report a tradeoff of caRNA’s promotive and suppressive roles to chromatin interactions. As a result, caRNA promotes chromatin interactions outside the anchors of chromatin loops, whereas caRNA exhibits an overall suppressive impact to chromatin interactions between loop anchors. Furthermore, caRNA suppresses chromatin loops’ number and strengths genome-wide, and this suppression depends on electric charge-mediated RNA interactions. These results reveal caRNA’s multifaced role in regulating 3D chromatin organization and highlight caRNA’s ability to modulate chromatin looping.

How complex interactions of genetic, environmental factors and aging jointly contribute to dopaminergic degeneration in Parkinson's disease (PD) is largely unclear. Here, we applied frequent gene co‐expression analysis on human patient substantia nigra‐specific microarray datasets to identify potential novel disease‐related genes. In vivo Drosophila studies validated two of 32 candidate genes, a chromatin‐remodeling factor SMARCA4 and a biliverdin reductase BLVRA. Inhibition of SMARCA4 was able to prevent aging‐dependent dopaminergic degeneration not only caused by overexpression of BLVRA but also in four most common Drosophila PD models. Furthermore, down‐regulation of SMARCA4 specifically in the dopaminergic neurons prevented shortening of life span caused by α‐synuclein and LRRK2. Mechanistically, aberrant SMARCA4 and BLVRA converged on elevated ERK‐ETS activity, attenuation of which by either genetic or pharmacological manipulation effectively suppressed dopaminergic degeneration in Drosophila in vivo. Down‐regulation of SMARCA4 or drug inhibition of MEK/ERK also mitigated mitochondrial defects in PINK1 (a PD‐associated gene)‐deficient human cells. Our findings underscore the important role of epigenetic regulators and implicate a common signaling axis for therapeutic intervention in normal aging and a broad range of age‐related disorders including PD., Using bioinformatics analysis of large‐scale human transcriptomic data and Drosophila disease models, Sun et al. identified novel Parkinson's disease (PD) genes and revealed a potential common pathogenic signaling pathway consisting of the chromatin‐remodeling factor SMARCA4 and the ERK‐ETS signaling axis in normal aging and age‐related disorders such as PD. The cancer drug Trametinib, previously shown to have lifespan extending capacity, was found to have therapeutic potency in multiple PD disease models.

Background Compared to proteins, glycans, and lipids, much less is known about RNAs on the cell surface. We develop a series of technologies to test for any nuclear-encoded RNAs that are stably attached to the cell surface and exposed to the extracellular space, hereafter called membrane-associated extracellular RNAs (maxRNAs). Results We develop a technique called Surface-seq to selectively sequence maxRNAs and validate two Surface-seq identified maxRNAs by RNA fluorescence in situ hybridization. To test for cell-type specificity of maxRNA, we use antisense oligos to hybridize to single-stranded transcripts exposed on the surface of human peripheral blood mononuclear cells (PBMCs). Combining this strategy with imaging flow cytometry, single-cell RNA sequencing, and maxRNA sequencing, we identify monocytes as the major type of maxRNA+ PBMCs and prioritize 11 candidate maxRNAs for functional tests. Extracellular application of antisense oligos of FNDC3B and CTSS transcripts inhibits monocyte adhesion to vascular endothelial cells. Conclusions Collectively, these data highlight maxRNAs as functional components of the cell surface, suggesting an expanded role for RNA in cell-cell and cell-environment interactions.

To evaluate any possible DNA contamination in Small Input Liquid Volume Extracellular RNA Sequencing (SILVER-seq), we carried out three types of tests. First, we tested the effectiveness of SILVER-seq’s DNase treatment step. Without DNase treatment, five of the five tested serum samples exhibited detectable cell-free DNA (cfDNA; Fig. 1 A ). After SILVER-seq’s DNase treatment step, none of the serum samples exhibited any detectable cfDNA (Fig. 1 A ), suggesting that SILVER-seq’s DNase treatment step thoroughly digested cfDNA in human serum samples. Fig. 1. DNA contamination tests. ( A ) Concentrations of cfDNA in five human serum samples (IDs: hS01 to hS05, columns) before and after SILVER-seq’s DNase treatment step. Each serum sample (column) was split into two 7-µL aliquots which were subjected to no treatment ( Upper ) or DNase treatment ( Lower ). ND, not detectable. The detection limit of Qubit’s high-sensitivity kit is 0.5 pg/µL. ( B ) Measured concentrations of cfDNA titers (columns) before ( Upper ) and after ( Lower ) SILVER-seq’s DNase treatment step. The detection limit of … [↵][1]2To whom correspondence may be addressed. Email: shuchien{at}ucsd.edu, hisu{at}ucsd.edu, or szhong{at}ucsd.edu. [1]: #xref-corresp-1-1

Additional file 1: Fig. S1. Size distribution of surface RNAs analyzed in Surface-seq. Fig. S2. Size distribution of the Surface-seq constructed sequencing libraries. Fig. S3. TTD microscopy of EL4 cells. Fig. S4. Images of healthy donor PBMCs from imaging flow cytometry. Fig. S5. tSNE plots of isFISH sorted single cells. Fig. S6. Summary of Surface-FISHseq datasets. Table S1. Summary of Surface-seq libraries. Table S2. Summary of Surface-FISHseq libraries. Table S3. Probe sequences for Surface-FISH.

Parkinson’s disease (PD) is a complex disease with high heterogeneity. How complex interactions of genetic, environmental factors and aging jointly contribute to dopaminergic degeneration in PD is largely unclear. Here, we applied frequent gene co-expression analysis on human patient substantia nigra-specific microarray datasets to identify potential novel disease-related genes. In vivo Drosophila studies validated two of 32 candidate genes, a chromatin remodeling factor SMARCA4 and a biliverdin reductase BLVRA. Inhibition of SMARCA4 was able to prevent dopaminergic degeneration not only caused by overexpression of BLVRA but also in four most common Drosophila PD models. Mechanistically, aberrant SMARCA4 and BLVRA converged on elevated ERK-ETS activity, attenuation of which by either genetic or pharmacological manipulation effectively suppressed dopaminergic degeneration in vivo. Drug inhibition of MEK/ERK also mitigated mitochondrial defects in PD gene-deficient human cells. Our findings underscore the important role of epigenetic regulators and implicate a common signaling axis for therapeutic intervention in a broad range of aging-related disorders including PD.

Significance The SILVER-seq technology enables sequencing extracellular RNAs (exRNAs) from a single droplet of liquid biopsy. This study revealed strong associations between serum exRNA expression levels and the donor’s sex and age. SILVER-seq detected serum exRNAs from the genes that are only expressed in brain, suggesting the possibility of monitoring brain gene expression from a blood test. Classifiers based on exRNA expression levels were able to separate breast cancer patients from control donors. The exRNA-based classifiers could also distinguish the patients with recurrent cancer from other breast cancer patients. The SILVER-seq technology can therefore lead the way to future in vitro diagnostics trials based on finger prick blood, which is more accessible for screening and frequent monitoring of human diseases., Extracellular RNAs (exRNAs) are present in human serum. It remains unclear to what extent these circulating exRNAs may reflect human physiologic and disease states. Here, we developed SILVER-seq (Small Input Liquid Volume Extracellular RNA Sequencing) to efficiently sequence both integral and fragmented exRNAs from a small droplet (5 μL to 7 μL) of liquid biopsy. We calibrated SILVER-seq in reference to other RNA sequencing methods based on milliliters of input serum and quantified droplet-to-droplet and donor-to-donor variations. We carried out SILVER-seq on more than 150 serum droplets from male and female donors ranging from 18 y to 48 y of age. SILVER-seq detected exRNAs from more than a quarter of the human genes, including small RNAs and fragments of mRNAs and long noncoding RNAs (lncRNAs). The detected exRNAs included those derived from genes with tissue (e.g., brain)-specific expression. The exRNA expression levels separated the male and female samples and were correlated with chronological age. Noncancer and breast cancer donors exhibited pronounced differences, whereas donors with or without cancer recurrence exhibited moderate differences in exRNA expression patterns. Even without using differentially expressed exRNAs as features, nearly all cancer and noncancer samples and a large portion of the recurrence and nonrecurrence samples could be correctly classified by exRNA expression values. These data suggest the potential of using exRNAs in a single droplet of serum for liquid biopsy-based diagnostics.

RNA-chromatin interactions represent an important aspect of transcriptional regulation of genes and transposable elements. However, analyses of chromatin-associated RNAs (caRNA) are often limited to one caRNA at a time. Here, we describe the iMARGI (in situ Mapping of RNA-Genome Interactome) technique used to discover caRNAs and reveal their respective genomic interaction loci. iMARGI starts with in situ crosslinking and genome fragmentation, followed by converting each proximal RNA-DNA pair into an RNA-linker-DNA chimeric sequence. These chimeric sequences are subsequently converted into a sequencing library suitable for paired-end sequencing. A standardized bioinformatic software package called iMARGI-Dockeris provided to decode the pairedend sequencing data into caRNA-DNA interactions. Compared to its predecessor MARGI, in iMARGI the number of input cells is 3-5 million, which is reduced by 100-fold, experimental time is reduced, clear checkpoints have been established. It takes a few hours a day and a total of 8 days to complete the construction of an iMARGI sequencing library and one day to carry out data processing with iMARGI-Docker.

Summary RNA molecules can attach to chromatin. It remains difficult to know what RNAs are associated with chromatin and where the genomic target loci of these RNAs are. Here, we present MARGI (mapping RNA-genome interactions), a technology to massively reveal native RNA-chromatin interactions from unperturbed cells. The gist of this technology is to ligate chromatin-associated RNAs (caRNAs) with their target genomic sequences by proximity ligation, forming RNA-DNA chimeric sequences, which are converted to a sequencing library for paired-end sequencing. Using MARGI, we produced RNA-genome interaction maps for human embryonic stem cells (ESCs) and human embryonic kidney (HEK) cells. MARGI revealed hundreds of caRNAs, including previously known XIST , SNHG1 , NEAT1 , and MALAT1 , as well as each caRNA's genomic interaction loci. Using a cross-species experiment, we estimated that approximately 2.2% of MARGI-identified interactions were false positives. In ESCs and HEK cells, the RNA ends of more than 5% of MARGI read pairs were mapped to distal or inter-chromosomal locations as compared to the locations of their corresponding DNA ends. The majority of transcription start sites are associated with distal or inter-chromosomal caRNAs. Chromatin-immunoprecipitation-sequencing (ChIP-seq)-reported H3K27ac and H3K4me3 levels are positively correlated, while H3K9me3 is negatively correlated, with MARGI-reported RNA attachment levels. The MARGI technology should facilitate revealing novel RNA functions and their genomic target regions.

Significance It remains formidable to predict what unreported RNA pairs can form new fusion transcripts. By systematic mapping of chromatin-associated RNAs and their respective genomic interaction loci, we obtained genome-wide RNA–DNA interaction maps from two noncancerous cell types. The gene pairs involved in RNA–DNA interactions in these normal cells exhibited strong overlap with those with cancer-derived fusion transcripts. These data suggest an RNA-poise model, where the spatial proximity of one gene’s transcripts and the other gene’s genomic sequence poises for the creation of fusion transcripts. We validated this model with 96 additional lung cancer samples. One of these additional samples exhibited fusion transcripts without a corresponding fusion gene, suggesting that genome recombination is not a required step of the RNA-poise model., Fusion transcripts are used as biomarkers in companion diagnoses. Although more than 15,000 fusion RNAs have been identified from diverse cancer types, few common features have been reported. Here, we compared 16,410 fusion transcripts detected in cancer (from a published cohort of 9,966 tumor samples of 33 cancer types) with genome-wide RNA–DNA interactions mapped in two normal, noncancerous cell types [using iMARGI, an enhanced version of the mapping of RNA–genome interactions (MARGI) assay]. Among the top 10 most significant RNA–DNA interactions in normal cells, 5 colocalized with the gene pairs that formed fusion RNAs in cancer. Furthermore, throughout the genome, the frequency of a gene pair to exhibit RNA–DNA interactions is positively correlated with the probability of this gene pair to present documented fusion transcripts in cancer. To test whether RNA–DNA interactions in normal cells are predictive of fusion RNAs, we analyzed these in a validation cohort of 96 lung cancer samples using RNA sequencing (RNA-seq). Thirty-seven of 42 fusion transcripts in the validation cohort were found to exhibit RNA–DNA interactions in normal cells. Finally, by combining RNA-seq, single-molecule RNA FISH, and DNA FISH, we detected a cancer sample with EML4-ALK fusion RNA without forming the EML4-ALK fusion gene. Collectively, these data suggest an RNA-poise model, where spatial proximity of RNA and DNA could poise for the creation of fusion transcripts.

The extracellular RNAs (exRNAs) from human biofluid have recently been systematically characterized. However, the correlations of biofluid exRNA levels and human diseases remain largely untested. Here, considering the unmet need for presymptomatic biomarkers of sporadic Alzheimer's disease (AD), we leveraged the recently developed SILVER-seq (small-input liquid volume extracellular RNA sequencing) technology to generate exRNA profiles from a longitudinal collection of human plasma samples. These 164 plasma samples were collected from research subjects 70 years or older with up to 15 years of clinical follow-up prior to death and whose clinical diagnoses were confirmed by pathological analysis of their post mortem brains. The exRNAs of AD-activated genes and transposons in the brain exhibited a concordant trend of increase in AD plasma in comparison with age-matched control plasma. However, when we required statistical significance with multiple testing adjustments, phosphoglycerate dehydrogenase (PHGDH) was the only gene that exhibited consistent upregulation in AD brain transcriptomes from 3 independent cohorts and an increase in AD plasma as compared to controls. We validated PHGDH's serum exRNA and brain protein expression increases in AD by using 5 additional published cohorts. Finally, we compared the time-course exRNA trajectories between "converters" and controls. Plasma PHGDH exRNA exhibited presymptomatic increases in each of the 11 converters during their transitions from normal to cognitive impairment but remained stable over the entire follow-up period in 8 out of the 9 control elderly subjects. These data suggest the potential utilities of plasma exRNA levels for screening and longitudinal exRNA changes as a presymptomatic indication of sporadic AD.

In situ mapping of RNA-Genome Interactome (iMARGI) is a technique that globally maps native RNA-genome interactions from unperturbed cells. It is an improved version of traditional MARGI published in 2017. Compared to traditional MARGI, this technique performs RNA-DNA proximity ligation in situ inside intact nucleus instead of in solution to reduce random ligation. It also reduces the number of cell input by 100-fold and shortens experimental processing time. In this protocol, cells are crosslinked with formaldehyde. Intact nuclei are collected from fixed cells and permeabilized with SDS. A restriction enzyme AluI is used to digest chromatin into DNA fragments and RNase I is used to fragment RNA. A specially designed biotinylated linker is introduced to ligate to 3´-end of RNA first and then this RNA-ligated linker is ligated to DNA. These ligation steps are controlled by the configuration of the linker and by sequential applications of different end modifications and ligation enzymes. Nuclei are lysed, and successfully ligated products, in the form of RNA-linker-DNA are selected with streptavidin beads, followed by converting the RNA part of chimera into cDNA on beads. cDNA-linker-DNA is circularized and then cut in the middle, producing DNAs with the configuration left.half.Linker-RNA-DNA-right.half.Linker, which are subjected to library amplification and paired-end sequencing.

We thank Drs. Hartl and Gao for pointing out the difference in read lengths between the cancer and normal samples (1). Indeed, Illumina discontinued their 50-base pair (bp) sequencing kits after we finished sequencing the cancer samples, forcing us to switch to 75-bp sequencing kits on the normal samples. The different sequencing kits did incur small changes of sequence alignment metrics. While acknowledging the possibility that this may bias the assessment of cancer vs. normal discrimination performance of our method, we believe such a possibility is substantially ameliorated by the following considerations. First, a recent study reported that “with the exception of 25 bp reads, there is little difference for the detection of … [↵][1]1To whom correspondence may be addressed. Email: shuchien{at}ucsd.edu, hisu{at}ucsd.edu, or szhong{at}ucsd.edu. [1]: #xref-corresp-1-1

Fusion transcripts are used as biomarkers in companion diagnoses. Although more than 15,000 fusion RNAs have been identified from diverse cancer types, few common features have been reported. Here, we compared 16,410 fusion transcripts detected in cancer (from a published cohort of 9,966 tumor samples of 33 cancer types) with genome-wide RNA-DNA interactions mapped in two normal, non-cancerous cell types (using iMARGI, an enhanced version of the MARGI [Mapping RNA-Genome Interactions assay]). Among the top 10 most significant RNA-DNA interactions in normal cells, 5 co-localized with the gene pairs that formed fusion RNAs in cancer. Furthermore, throughout the genome, the frequency of a gene pair to exhibit RNA-DNA interactions is positively correlated with the probability of this gene pair to present documented fusion transcripts in cancer. To test whether RNA-DNA interactions in normal cells are predictive of fusion RNAs, we analyzed these in a validation cohort of 96 lung cancer samples using RNA-seq. 37 out of 42 fusion transcripts in the validation cohort were found to exhibit RNA-DNA interactions in normal cells. Finally, by combining RNA-seq, single-molecule RNA FISH, and DNA FISH, we detected a cancer sample with EML4-ALK fusion RNA without forming the EML4-ALK fusion gene. Collectively, these data suggest a novel RNA-poise model, where spatial proximity of RNA and DNA could poise for the creation of fusion transcripts.

Summary It remains challenging to identify all parts of the nuclear genome that are in proximity to nuclear speckles, due to physical separation between the nuclear speckle cores and chromatin. We hypothesized that noncoding RNAs including small nuclear RNA (snRNAs) and Malat1, which accumulate at the periphery of nuclear speckles (nsaRNA [nuclear speckle-associated RNA]), may extend to sufficient proximity to the genome. Leveraging a transcriptome-genome interaction assay (mapping of RNA-genome interactions [MARGI]), we identified clusters of nsaRNA-interacting genomic sequences (nsaPeaks). Posttranscriptional pre-mRNAs, which also accumulate to nuclear speckles, exhibited proximity to nsaPeaks but rarely to other genomic regions. Our combined DNA fluorescence in situ hybridization and immunofluorescence analysis in 182 single cells revealed a 3-fold increase in odds for nuclear speckles to localize near an nsaPeak than its neighboring genomic sequence. These data suggest a model that nsaRNAs are located in sufficient proximity to the nuclear genome and leave identifiable genomic footprints, thus revealing the parts of genome proximal to nuclear speckles., Graphical Abstract, Highlights • MARGI captures interactions of nuclear speckle-associated RNAs (nsaRNA) and DNA • nsaRNA-interacting genomic sequences were clustered (nsaPeaks) in the genome • Posttranscriptional pre-mRNAs and CDK9 proteins exhibited proximity to nsaPeaks • Single-cell images confirmed proximity of nuclear speckles to an nsaPeak, Genetics; Molecular Genetics; Data Analysis in Structural Biology

Nuclear speckles are interchromatin structures enriched in RNA splicing factors. Determining their relative positions with respect to the folded nuclear genome could provide critical information on co-and post-transcriptional regulation of gene expression. However, it remains challenging to identify which parts of the nuclear genome are in proximity to nuclear speckles, due to physical separation between nuclear speckle cores and chromatin. We hypothesized that noncoding RNAs including small nuclear RNAs, 7SK and Malat1, which accumulate at the periphery of nuclear speckles (nsaRNA,nuclearspeckleassociated RNA), may extend to sufficient proximity to the nuclear genome. Leveraging a transcriptome-genome interaction assay (MARGI), we identified nsaRNA-interacting genomic sequences, which exhibited clustering patterns (nsaPeaks) in the genome, suggesting existence of relatively stable interaction sites for nsaRNAs in nuclear genome. Posttranscriptional pre-mRNAs, which are known to be clustered to nuclear speckles, exhibited proximity to nsaPeaks but rarely to other genomic regions. Furthermore, CDK9 proteins that localize to the vicinity of nuclear speckles produced ChIP-seq peaks that overlapped with nsaPeaks. Our combined DNA FISH and immunofluorescence analysis in 182 single cells revealed a 3-fold increase in odds for nuclear speckles to localize near an nsaPeak than its neighboring genomic sequence. These data suggest a model that nsaRNAs locate in sufficient proximity to nuclear genome and leave identifiable genomic footprints, thus revealing the parts of genome proximal to nuclear speckles.

N 6-Methyladenosine (m6A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m6A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m6A functions in plants. Therefore, computational prediction of mRNA m6A sites becomes emergently important. Here, we present a method to predict the m6A sites for A. thaliana mRNA sequence(s). To predict the m6A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m6A sites. The server also provides a comprehensive database of predicted transcriptome-wide m6A sites and curated m6A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m6A sites, which is freely accessible for public use at http://bioinfo.tsinghua.edu.cn/AthMethPre/index.html.

Multiple lines of evidence indicate that aberrant activation of Hedgehog (Hh) signaling plays an important role in tumorigenesis in human glioma. However, the underlying molecular mechanism and crucial downstream targets of glioma-associated oncogene (Gli), a primary transcriptional regulator of Hh signaling, are not fully understood. Here, we report the identification of miR-124 as a novel downstream target of the transcriptional factor Gli2, which is important for proliferation and tumor growth in human glioma cells. Blockade of Hh signaling leads to a remarkable increase in miR-124 expression in glioma cells, whereas overexpression of Gli2 suppresses miR-124 expression by increasing the direct binding of Gli2 to the upstream region of the transcriptional start site for miR-124. Furthermore, we found that miR-124 potentially interacts with the 3'-UTR region of AURKA. Overexpression of miR-124 significantly decreased the expression of AURKA in glioma cells. In contrast, the loss of miR-124 led to the increased expression of AURKA mRNA and protein. In addition, cell proliferation and colony formation ability were significantly decreased following Gli2 knockdown in human glioma cells, while transfection with a miR-124 inhibitor rescued the proliferative ability of cells. These results demonstrate that miR-124 is an important downstream target gene of Hh signaling, and the Gli2/miR-124/AURKA axis is essential for the proliferation and growth of human glioma cells.

Human and several nonhuman species share the rare ability of modifying acoustic and/or syntactic features of sounds produced, i.e. vocal learning, which is the important neurobiological and behavioral substrate of human speech/language. This convergent trait was suggested to be associated with significant genomic convergence and best manifested at the ROBO-SLIT axon guidance pathway. Here we verified the significance of such genomic convergence and assessed its functional relevance to human speech/language using human genetic variation data. In normal human populations, we found the affected amino acid sites were well fixed and accompanied with significantly more associated protein-coding SNPs in the same genes than the rest genes. Diseased individuals with speech/language disorders have significant more low frequency protein coding SNPs but they preferentially occurred outside the affected genes. Such patients' SNPs were enriched in several functional categories including two axon guidance pathways (mediated by netrin and semaphorin) that interact with ROBO-SLITs. Four of the six patients have homozygous missense SNPs on PRAME gene family, one youngest gene family in human lineage, which possibly acts upon retinoic acid receptor signaling, similarly as FOXP2, to modulate axon guidance. Taken together, we suggest the axon guidance pathways (e.g. ROBO-SLIT, PRAME gene family) served as common targets for human speech/language evolution and related disorders.

Summary: Large numbers of long intergenic non-coding RNA (lincRNA) have been detected through high-throughput sequencing technology. However, currently we still know very little about their functions. Therefore, a lincRNA function annotation database is needed to facilitate the study in this field. In this article, we present Linc2GO, a web resource that aims to provide comprehensive functional annotations for human lincRNA. MicroRNA-mRNA and microRNA-lincRNA interaction data were integrated to generate lincRNA functional annotations based on the ‘competing endogenous RNA hypothesis’. To the best of our knowledge, Linc2GO is the first database that makes use of the ‘competing endogenous RNA hypothesis’ to predict lincRNA functions. Availability: Freely available at http://www.bioinfo.tsinghua.edu.cn/~liuke/Linc2GO/index.html Contact: sunzhr@mail.tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

BackgroundImmunoglobulin A nephropathy (IgAN) is the most common form of glomerulonephritis in China. An accurate diagnosis of IgAN is dependent on renal biopsies, and there is lack of non-invasive and practical classification methods for discriminating IgAN from other primary kidney diseases. The objective of this study was to develop a classification model for the auxiliary diagnosis of IgAN using multiparameter analysis with various biological parameters.MethodsTo establish an optimal classification model, 121 cases (58 IgAN vs. 63 non-IgAN) were recruited and statistically analyzed. The model was then validated in another 180 cases.ResultsOf the 57 biological parameters, there were 16 parameters that were significantly different (P ConclusionsThese models possess potential clinical applications in distinguishing IgAN from other primary kidney diseases.