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A causal relationship exists among the aging process, organ decay and dis-function, and the occurrence of various diseases including cancer. A genetically engineered mouse model, termedEklfK74R/K74RorEklf(K74R), carrying mutation on the well-conserved sumoylation site of the hematopoietic transcription factor KLF1/ EKLF has been generated that possesses extended lifespan and healthy characteristics including cancer resistance. We show that the high anti-cancer capability of theEklf(K74R) mice are gender-, age-and genetic background-independent. Significantly, the anti-cancer capability and extended lifespan characteristics ofEklf(K74R) mice could be transferred to wild-type mice via transplantation of their bone marrow mononuclear cells. Targeted/global gene expression profiling analysis has identified changes of the expression of specific proteins and cellular pathways in the leukocytes of theEklf(K74R) that are in the directions of anti-cancer and/or anti-aging. This study demonstrates the feasibility of developing a novel hematopoietic/ blood system for long-term anti-cancer and, potentially, for anti-aging.

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed by computational detection tools. During the last decade, a plethora of such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools were used and detected over 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were empirically validated using three orthogonal methods. Generally, tool-specific precision values are high and similar (median of 98.8%, 96.3%, and 95.5% for qPCR, RNase R, and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant tool differentiators. Furthermore, we demonstrate the complementarity of tools through the increase in detection sensitivity by considering the union of highly-precise tool combinations while keeping the number of false discoveries low. Finally, based on the benchmarking results, recommendations are put forward for circRNA detection and validation.

Circular RNAs (circRNAs) are non-polyadenylated RNAs with a continuous loop structure characterized by a non-co-linear back-splice junction (BSJ). While dozens of computational tools have been developed and identified millions of circRNA candidates in diverse species, it remains a major challenge for determining circRNA reliability due to various types of false positives. Here, we systematically assess the impacts of numerous factors related to identification, conservation, biogenesis, and function on circRNA reliability by comparisons of circRNA expression from mock (total RNAs) and the corresponding co-linear/polyadenylated RNA-depleted datasets based on three different RNA treatment approaches. Eight important indicators of circRNA reliability are determined. The relative contribution to variability explained analyses further reveal that the relative importance of these factors in affecting circRNA reliability is conservation level of circRNA > full-length circular sequences > supporting BSJ read count > both BSJ donor and acceptor splice sites at the same co-linear transcript isoforms > both BSJ donor and acceptor splice sites at the annotated exon boundaries > BSJs detected by multiple tools > supporting functional features > both BSJ donor and acceptor splice sites undergoing alternative splicing. By extracting RT-independent circRNAs, circRNAs passing multiple experimental validations, and database-specific circRNAs, we showed the additive effects of these important factors in determining circRNA reliability. This study thus provides a useful guideline and an important resource for selecting high-confidence circRNAs for further investigations.

Trans-splicing can generate non-co-linear (NCL) transcripts that consist of exons in an order topologically inconsistent with the corresponding DNA template. Detecting trans-spliced RNAs (ts-RNAs) may be interfered by false positives from experimental artifacts, circular RNAs (circRNAs), and genetic rearrangements. Particularly, intragenic ts-RNAs, which are derived from separate precursor mRNA molecules of the same genes, are often mistaken for circRNAs through analyses of high-throughput transcriptome sequencing (RNA-seq) data. In addition, the biogenesis and function of ts-RNAs remain elusive. Here we developed a bioinformatics pipeline, NCLscan-hybrid, with the integration of long and short RNA-seq reads to minimize false positives and identify intragenic ts-RNAs. We utilized two features of long reads, out-of-circle and rolling circle, to distinguish intragenic ts-RNAs from circRNAs. We also designed multiple experimental validation steps to examine each type of false positives and successfully confirmed an intragenic ts-RNA (ts-ARFGEF1) in breast cancer cells. On the basis of ectopic expression and CRISPR-based endogenous genome modification experiments, we confirmed that ts-ARFGEF1 formation was significantly dependent on the reverse complementary sequences in the flanking introns of the NCL junction. Subsequent in vitro and in vivo experiments demonstrated that ts-ARFGEF1 silencing can significantly inhibit tumor cell growth. We further showed the regulatory role of ts-ARFGEF1 in p53-mediated apoptosis through affecting the PERK/eIF2a/ATF4/CHOP signaling pathway in breast cancer cells. This study thus described both bioinformatics procedures and experimental validation steps for rigorous characterization of transcriptionally non-co-linear RNAs, expanding the discovery of this important but understudied class of RNAs.

Genetic risk variants and transcriptional expression changes in autism spectrum disorder (ASD) were widely investigated, but their causal relationship remains largely unknown. Circular RNAs (circRNAs) are abundant in brain and often serve as upstream regulators of mRNAs. By integrating RNA-sequencing with genotype data from autistic brains, we assessed expression quantitative trait loci of circRNAs (circQTLs) that cis-regulated expression of nearby circRNAs and trans-regulated expression of distant genes (trans-eGenes) simultaneously. We thus identified 3619 circQTLs that were also trans-eQTLs and constructed 19,804 circQTL-circRNA-trans-eGene regulatory axes. We conducted two different types of approaches, mediation and partial correlation tests (MPT), to determine the axes with mediation effects of circQTLs on trans-eGene expression through circRNA expression. We showed that the mediation effects of the circQTLs (trans-eQTLs) on circRNA expression were positively correlated with the magnitude of circRNA-trans-eGene correlation of expression profile. The positive correlation became more significant after adjustment for the circQTLs. Of the 19,804 axes, 8103 passed MPT. Meanwhile, we performed causal inference test (CIT) and identified 2070 circQTL-trans-eGene-ASD diagnosis propagation paths. We showed that the CIT-passing genes were significantly enriched for ASD risk genes, genes encoding postsynaptic density proteins, and other ASD-relevant genes, supporting the relevance of the CIT-passing genes to ASD pathophysiology. Integration of MPT- and CIT-passing axes further constructed 352 circQTL-circRNA-trans-eGene-ASD diagnosis propagation paths, wherein the circRNA-trans-eGene axes may act as causal mediators for the circQTL-ASD diagnosis associations. These analyses were also successfully applied to an independent dataset from schizophrenia brains. Collectively, this study provided the first framework for systematically investigating trans-genetic effects of circQTLs and inferring the corresponding causal relations in diseases. The identified circQTL-circRNA-trans-eGene regulatory interactions, particularly the internal modules that were previously implicated in the examined disorders, also provided a helpful dataset for further investigating causative biology and cryptic regulatory mechanisms underlying the neuropsychiatric diseases.

Genetic risk variants and transcriptional expression changes in autism spectrum disorder (ASD) have been widely identified, but their causal relationship is largely unknown. Circular RNAs (circRNAs) are abundant in brain and often serve as upstream regulators of mRNAs. By integrating RNA-sequencing with genotyping data from autistic brains, we accessed expression quantitative trait loci (eQTL) of circRNAs (circQTLs) that influenced expression of distant genes (trans-eGenes) and constructed 43,372 circQTL-trans-eGene pairs. Mediation test suggested that 19,393 pairs were significantly cis-mediated by expression of circRNAs near the circQTLs; meanwhile, causal inference test (CIT) suggested 1,000 pairs influencing 708 trans-eGenes, wherein trans-eGene expression mediated trans-eQTL effects on ASD diagnosis. The 708 trans-eGenes were enriched for ASD risk genes and overrepresented in neurons in the upper neocortical layer. Integration of mediation test- and CIT-passing pairs further constructed 257 circQTL-circRNA-trans-eGene-ASD propagation paths. These findings increase our understanding of causative biology and cryptic regulatory mechanisms underlying ASD.

Circular RNAs (circRNAs), a class of long noncoding RNAs, are known to be enriched in mammalian neural tissues. Although a wide range of dysregulation of gene expression in autism spectrum disorder (ASD) have been reported, the role of circRNAs in ASD remains largely unknown. Here, we performed genome-wide circRNA expression profiling in postmortem brains from individuals with ASD and controls and identified 60 circRNAs and three coregulated modules that were perturbed in ASD. By integrating circRNA, microRNA, and mRNA dysregulation data derived from the same cortex samples, we identified 8170 ASD-associated circRNA-microRNA-mRNA interactions. Putative targets of the axes were enriched for ASD risk genes and genes encoding inhibitory postsynaptic density (PSD) proteins, but not for genes implicated in monogenetic forms of other brain disorders or genes encoding excitatory PSD proteins. This reflects the previous observation that ASD-derived organoids show overproduction of inhibitory neurons. We further confirmed that some ASD risk genes (NLGN1, STAG1, HSD11B1, VIP, and UBA6) were regulated by an up-regulated circRNA (circARID1A) via sponging a down-regulated microRNA (miR-204-3p) in human neuronal cells. Particularly, alteration of NLGN1 expression is known to affect the dynamic processes of memory consolidation and strengthening. To the best of our knowledge, this is the first systems-level view of circRNA regulatory networks in ASD cortex samples. We provided a rich set of ASD-associated circRNA candidates and the corresponding circRNA-microRNA-mRNA axes, particularly those involving ASD risk genes. Our findings thus support a role for circRNA dysregulation and the corresponding circRNA-microRNA-mRNA axes in ASD pathophysiology.

Circular RNAs (circRNAs), a class of long non-coding RNAs, are known to be enriched in mammalian brain and neural tissues. While the effects of regulatory genetic variants on gene expression in autism spectrum disorder (ASD) have been widely reported, the role of circRNAs in ASD remains largely unknown. Here, we performed genome-wide circRNA expression profiling in post-mortem brains from individuals with ASD and controls and identified 60 circRNAs and three co-regulated modules that were perturbed in ASD. By integrating circRNA, microRNA, and mRNA dysregulation data derived from the same cortex samples, we identified 8,170 ASD-associated circRNA-microRNA-mRNA interactions. Putative targets of the axes were enriched for ASD risk genes and genes encoding inhibitory postsynaptic density (PSD) proteins, but not for genes implicated in monogenetic forms of other brain disorders or genes encoding excitatory PSD proteins. This result reflects the previous observation that ASD-derived organoids exhibit overproduction of inhibitory neurons. We further confirmed that some ASD risk genes (NLGN1, STAG1, HSD11B1, VIP, and UBA6) were indeed regulated by an upregulated circRNA (circARID1A) via sponging a downregulated microRNA (miR-204-3p) in human neuronal cells. We provided a systems-level view of landscape of circRNA regulatory networks in ASD cortex samples. We also provided multiple lines of evidence for the functional role of ASD for circRNA dysregulation and a rich set of ASD-associated circRNA candidates and the corresponding circRNA-miRNA-mRNA axes, particularly those involving ASD risk genes. Our findings thus support a role for circRNA dysregulation and the corresponding circRNA-microRNA-mRNA axes in ASD pathophysiology.

TAR DNA-binding protein (TDP-43) is a ubiquitously expressed nuclear protein, which participates in a number of cellular processes and has been identified as the major pathological factor in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). Here we constructed a conditional TDP-43 mouse with depletion of TDP-43 in the mouse forebrain and find that the mice exhibit a whole spectrum of age-dependent frontotemporal dementia-like behaviour abnormalities including perturbation of social behaviour, development of dementia-like behaviour, changes of activities of daily living, and memory loss at a later stage of life. These variations are accompanied with inflammation, neurodegeneration, and abnormal synaptic plasticity of the mouse CA1 neurons. Importantly, analysis of the cortical RNA transcripts of the conditional knockout mice at the pre−/post-symptomatic stages and the corresponding wild type mice reveals age-dependent alterations in the expression levels and RNA processing patterns of a set of genes closely associated with inflammation, social behaviour, synaptic plasticity, and neuron survival. This study not only supports the scenario that loss-of-function of TDP-43 in mice may recapitulate key behaviour features of the FTLD diseases, but also provides a list of TDP-43 target genes/transcript isoforms useful for future therapeutic research. Electronic supplementary material The online version of this article (10.1186/s40478-019-0674-x) contains supplementary material, which is available to authorized users.

Figure S1. Altered activity of daily living (ADL) of TDP-43 cKO mice. Figure S2. Immunohistochemistry staining of brain slices. Figure S3. Persisting reactive astrocytosis in TDP-43 cKO mouse forebrain. Figure S4. Electrophysiology measurements. Figure S5. Mis-regulated genes in TDP-43 cKO mice. Figure S6. Alternations of the processing events of cortical RNAs in TDP-43 cKO mice. Figure S7. The alternative uses of poly(A) sites in the cortical RNAs of TDP-43 cKO mice. Figure S8. qRT-PCR validation of RNA splicing events altered in 3- and 12-month-old TDP-43 cKO mice. Figure S9. Validation of altered splicing events in TDP-43 cKO mice. Figure S10. Calcium signaling and synaptic long term potentiation pathway analysis using Ingenuity Pathway Analysis (IPA). (PDF 2990 kb)

Table S2. Changes of the mRNA levels of social behaviour-related genes in the neocortex of TDP-43 cKO mice relative to Ctrl mice. (PDF 72 kb)

Table S1. Parameter settings of intragenic/intergenic NCL detectors tested in this study. (DOCX 34 kb)

Table S1. List of the chromosome numbers, donor positions, acceptors positions and gene names of the transcripts from which the individual circularRNAs change in the neocortex of 3- and 12-month-old TDP-43 cKO mice, but not Ctrl mice are listed. (PDF 141 kb)

ABSTARCTAdenosine-to-inosine (A-to-I) RNA editing is a very common post-transcriptional modification that can lead to A-to-G changes at the RNA level and compensate for G-to-A genomic changes to a certain extent. It has been shown that each healthy individual can carry dozens of missense variants predicted to be severely deleterious. Why strongly detrimental variants are preserved in a population and not eliminated by negative natural selection remains mostly unclear. Here we ask if RNA editing correlates with the burden of deleterious A/G polymorphisms in a population. Integrating genome and transcriptome sequencing data from 447 human lymphoblastoid cell lines, we show that nonsynonymous editing activities (prevalence/level) are negatively correlated with the deleteriousness of A-to-G genomic changes and positively correlated with that of G-to-A genomic changes within the population. We find a significantly negative correlation between nonsynonymous editing activities and allele frequency of A within the population. This negative editing-allele frequency correlation is particularly strong when editing sites are located in highly important genes/loci. Examinations of deleterious missense variants from the 1000 genomes project further show a significantly higher mutational burden in G-to-A changes than in other types of changes. The level of the mutational burden in G-to-A changes increases with increasing deleterious effects of the changes. Moreover, the deleteriousness of G-to-A changes is significantly positively correlated with the percentage of binding motif of editing enzymes at the variants. Overall, we show that nonsynonymous editing contributes to the increased burden of G-to-A missense mutations in healthy individuals, expanding RNA editing in pathogenomics studies.

Adenosine-to-inosine (A-to-I) RNA editing is a very common co-/posttranscriptional modification that can lead to A-to-G changes at the RNA level and compensate for G-to-A genomic changes to a certain extent. It has been shown that each healthy individual can carry dozens of missense variants predicted to be severely deleterious. Why strongly detrimental variants are preserved in a population and not eliminated by negative natural selection remains mostly unclear. Here, we ask if RNA editing correlates with the burden of deleterious A/G polymorphisms in a population. Integrating genome and transcriptome sequencing data from 447 human lymphoblastoid cell lines, we show that nonsynonymous editing activities (prevalence/level) are negatively correlated with the deleteriousness of A-to-G genomic changes and positively correlated with that of G-to-A genomic changes within the population. We find a significantly negative correlation between nonsynonymous editing activities and allele frequency of A within the population. This negative editing-allele frequency correlation is particularly strong when editing sites are located in highly important genes/loci. Examinations of deleterious missense variants from the 1000 Genomes Project further show a significantly higher proportion of rare missense mutations for G-to-A changes than for other types of changes. The proportion for G-to-A changes increases with increasing deleterious effects of the changes. Moreover, the deleteriousness of G-to-A changes is significantly positively correlated with the percentage of editing enzyme binding motifs at the variants. Overall, we show that nonsynonymous editing is associated with the increased burden of G-to-A missense mutations in healthy individuals, expanding RNA editing in pathogenomics studies.

Adenosine-to-inosine (A-to-I) editing is widespread across the kingdom Metazoa. However, for the lack of comprehensive analysis in nonmodel animals, the evolutionary history of A-to-I editing remains largely unexplored. Here, we detect high-confidence editing sites using clustering and conservation strategies based on RNA sequencing data alone, without using single-nucleotide polymorphism information or genome sequencing data from the same sample. We thereby unveil the first evolutionary landscape of A-to-I editing maps across 20 metazoan species (from worm to human), providing unprecedented evidence on how the editing mechanism gradually expands its territory and increases its influence along the history of evolution. Our result revealed that highly clustered and conserved editing sites tended to have a higher editing level and a higher magnitude of the ADAR motif. The ratio of the frequencies of nonsynonymous editing to that of synonymous editing remarkably increased with increasing the conservation level of A-to-I editing. These results thus suggest potentially functional benefit of highly clustered and conserved editing sites. In addition, spatiotemporal dynamics analyses reveal a conserved enrichment of editing and ADAR expression in the central nervous system throughout more than 300 Myr of divergent evolution in complex animals and the comparability of editing patterns between invertebrates and between vertebrates during development. This study provides evolutionary and dynamic aspects of A-to-I editome across metazoan species, expanding this important but understudied class of nongenomically encoded events for comprehensive characterization.

Circular RNAs (circRNAs) arise during post-transcriptional processes, in which a single-stranded RNA molecule forms a circle through covalent binding. Previously, circRNA products were often regarded to be splicing intermediates, by-products, or products of aberrant splicing. But recently, rapid advances in high-throughput RNA sequencing (RNA-seq) for global investigation of nonco-linear (NCL) RNAs, which comprised sequence segments that are topologically inconsistent with the reference genome, leads to renewed interest in this type of NCL RNA (i.e., circRNA), especially exonic circRNAs (ecircRNAs). Although the biogenesis and function of ecircRNAs are mostly unknown, some ecircRNAs are abundant, highly expressed, or evolutionarily conserved. Some ecircRNAs have been shown to affect microRNA regulation, and probably play roles in regulating parental gene transcription, cell proliferation, and RNA-binding proteins, indicating their functional potential for development as diagnostic tools. To date, thousands of ecircRNAs have been identified in multiple tissues/cell types from diverse species, through analyses of RNA-seq data. However, the detection of ecircRNA candidates involves several major challenges, including discrimination between ecircRNAs and other types of NCL RNAs (e.g., trans-spliced RNAs and genetic rearrangements); removal of sequencing errors, alignment errors, and in vitro artifacts; and the reconciliation of heterogeneous results arising from the use of different bioinformatics methods or sequencing data generated under different treatments. Such challenges may severely hamper the understanding of ecircRNAs. Herein, we review the biogenesis, identification, properties, and function of ecircRNAs, and discuss some unanswered questions regarding ecircRNAs. We also evaluate the accuracy (in terms of sensitivity and precision) of some well-known circRNA-detecting methods.

Genomic imprinting is an important epigenetic process that silences one of the parentally-inherited alleles of a gene and thereby exhibits allelic-specific expression (ASE). Detection of human imprinting events is hampered by the infeasibility of the reciprocal mating system in humans and the removal of ASE events arising from non-imprinting factors. Here, we describe a pipeline with the pattern of reciprocal allele descendants (RADs) through genotyping and transcriptome sequencing data across independent parent-offspring trios to discriminate between varied types of ASE (e.g., imprinting, genetic variation-dependent ASE, and random monoallelic expression (RME)). We show that the vast majority of ASE events are due to sequence-dependent genetic variant, which are evolutionarily conserved and may themselves play a cis-regulatory role. Particularly, 74% of non-RAD ASE events, even though they exhibit ASE biases toward the same parentally-inherited allele across different individuals, are derived from genetic variation but not imprinting. We further show that the RME effect may affect the effectiveness of the population-based method for detecting imprinting events and our pipeline can help to distinguish between these two ASE types. Taken together, this study provides a good indicator for categorization of different types of ASE, opening up this widespread and complex mechanism for comprehensive characterization.

Global transcriptome investigations often result in the detection of an enormous number of transcripts composed of non-co-linear sequence fragments. Such ‘aberrant’ transcript products may arise from post-transcriptional events or genetic rearrangements, or may otherwise be false positives (sequencing/alignment errors or in vitro artifacts). Moreover, post-transcriptionally non-co-linear (‘PtNcl’) transcripts can arise from trans-splicing or back-splicing in cis (to generate so-called ‘circular RNA’). Here, we collected previously-predicted human non-co-linear RNA candidates, and designed a validation procedure integrating in silico filters with multiple experimental validation steps to examine their authenticity. We showed that >50% of the tested candidates were in vitro artifacts, even though some had been previously validated by RT-PCR. After excluding the possibility of genetic rearrangements, we distinguished between trans-spliced and circular RNAs, and confirmed that these two splicing forms can share the same non-co-linear junction. Importantly, the experimentally-confirmed PtNcl RNA events and their corresponding PtNcl splicing types (i.e. trans-splicing, circular RNA, or both sharing the same junction) were all expressed in rhesus macaque, and some were even expressed in mouse. Our study thus describes an essential procedure for confirming PtNcl transcripts, and provides further insight into the evolutionary role of PtNcl RNA events, opening up this important, but understudied, class of post-transcriptional events for comprehensive characterization.

Gene expression is largely regulated by DNA methylation, transcription factor (TF), and microRNA (miRNA) before, during, and after transcription, respectively. Although the evolutionary effects of TF/miRNA regulations have been widely studied, evolutionary analysis of simultaneously accounting for DNA methylation, TF, and miRNA regulations and whether promoter methylation and gene body (coding regions) methylation have different effects on the rate of gene evolution remain uninvestigated. Here, we compared human-macaque and human-mouse protein evolutionary rates against experimentally determined single base-resolution DNA methylation data, revealing that promoter methylation level is positively correlated with protein evolutionary rates but negatively correlated with TF/miRNA regulations, whereas the opposite was observed for gene body methylation level. Our results showed that the relative importance of these regulatory factors in determining the rate of mammalian protein evolution is as follows: Promoter methylation ≈ miRNA regulation > gene body methylation > TF regulation, and further indicated that promoter methylation and miRNA regulation have a significant dependent effect on protein evolutionary rates. Although the mechanisms underlying cooperation between DNA methylation and TFs/miRNAs in gene regulation remain unclear, our study helps to not only illuminate the impact of these regulatory factors on mammalian protein evolution but also their intricate interaction within gene regulatory networks.

Trans-splicing is a post-transcriptional event that joins exons from separate pre-mRNAs. Detection of trans-splicing is usually severely hampered by experimental artifacts and genetic rearrangements. Here, we develop a new computational pipeline, TSscan, which integrates different types of high-throughput long-/short-read transcriptome sequencing of different human embryonic stem cell (hESC) lines to effectively minimize false positives while detecting trans-splicing. Combining TSscan screening with multiple experimental validation steps revealed that most chimeric RNA products were platform-dependent experimental artifacts of RNA sequencing. We successfully identified and confirmed four trans-spliced RNAs, including the first reported trans-spliced large intergenic noncoding RNA (“tsRMST”). We showed that these trans-spliced RNAs were all highly expressed in human pluripotent stem cells and differentially expressed during hESC differentiation. Our results further indicated that tsRMST can contribute to pluripotency maintenance of hESCs by suppressing lineage-specific gene expression through the recruitment of NANOG and the PRC2 complex factor, SUZ12. Taken together, our findings provide important insights into the role of trans-splicing in pluripotency maintenance of hESCs and help to facilitate future studies into trans-splicing, opening up this important but understudied class of post-transcriptional events for comprehensive characterization.

Human and other primate genomes consist of many segmental duplications (SDs) due to fixation of copy number variations (CNVs). Structure of these duplications within the human genome has been shown to be a complex mosaic composed of juxtaposed subunits (called duplicons). These duplicons are difficult to be uncovered from the mosaic repeat structure. In addition, the distribution and evolution of duplicons among primates are still poorly investigated. In this paper, we develop a statistical framework for discovering duplicons via integration of a Hidden Markov Model (HMM) and a permutation test. Our comparative analysis indicates that the mosaic structure of duplicons is common in CNV/SD regions of both human and chimpanzee genomes, and a subset of core duplicons is shared by the majority of CNVs/SDs. Phylogenetic analyses using duplicons suggested that most CNVs/SDs share common duplication ancestry. Many human/chimpanzee duplicons flank both ends of CNVs, which may be hotspots of nonallelic homologous recombination.

Transcriptionally non-co-linear (NCL) transcripts can originate from trans-splicing (trans-spliced RNA; ‘tsRNA’) or cis-backsplicing (circular RNA; ‘circRNA’). While numerous circRNAs have been detected in various species, tsRNAs remain largely uninvestigated. Here, we utilize integrative transcriptome sequencing of poly(A)- and non-poly(A)-selected RNA-seq data from diverse human cell lines to distinguish between tsRNAs and circRNAs. We identified 24,498 NCL events and found that a considerable proportion (20–35%) of them arise from both tsRNAs and circRNAs, representing extensive alternative trans-splicing and cis-backsplicing in human cells. We show that sequence generalities of exon circularization are also observed in tsRNAs. Recapitulation of NCL RNAs further shows that inverted Alu repeats can simultaneously promote the formation of tsRNAs and circRNAs. However, tsRNAs and circRNAs exhibit quite different, or even opposite, expression patterns, in terms of correlation with the expression of their co-linear counterparts, expression breadth/abundance, transcript stability, and subcellular localization preference. These results indicate that tsRNAs and circRNAs may play different regulatory roles and analysis of NCL events should take the joint effects of different NCL-splicing types and joint effects of multiple NCL events into consideration. This study describes the first transcriptome-wide analysis of trans-splicing and cis-backsplicing, expanding our understanding of the complexity of the human transcriptome.

Genome-wide analysis has observed an excess of coincident single nucleotide polymorphisms (coSNPs) at human-chimpanzee orthologous positions and suggested that this is due to cryptic variation in the mutation rate. While this phenomenon primarily corresponds with non-coding coSNPs, the situation in coding sequences remains unclear. Here we calculate the observed-to-expected ratio of coSNPs (coSNPO/E) to estimate the prevalence of human-chimpanzee coSNPs and show that the excess of coSNPs is also present in coding regions. Intriguingly, coSNPO/E is much higher at zero-fold than at nonzero-fold degenerate sites; such a difference is due to an elevation of coSNPO/E at zero-fold degenerate sites, rather than a reduction at nonzero-fold degenerate ones. These trends are independent of chimpanzee subpopulation, population size, or sequencing techniques; and hold in broad generality across primates. We find that this discrepancy cannot fully explained by sequence contexts, shared ancestral polymorphisms, SNP density and recombination rate and that coSNPO/E in coding sequences is significantly influenced by purifying selection. We also show that selection and mutation rate affect coSNPO/E independently and coSNPs tend to be less damaging and more correlated with human diseases than non-coSNPs. These suggest that coSNPs may represent a “signature” during primate protein evolution.

DNA cytosine methylation is a central epigenetic marker that is usually mutagenic and may increase the level of sequence divergence. However, methylated genes have been reported to evolve more slowly than unmethylated genes. Hence, there is a controversy on whether DNA methylation is correlated with increased or decreased protein evolutionary rates. We hypothesize that this controversy has resulted from the differential correlations between DNA methylation and the evolutionary rates of coding exons in different genic positions. To test this hypothesis, we compare human–mouse and human–macaque exonic evolutionary rates against experimentally determined single-base resolution DNA methylation data derived from multiple human cell types. We show that DNA methylation is significantly related to within-gene variations in evolutionary rates. First, DNA methylation level is more strongly correlated with C-to-T mutations at CpG dinucleotides in the first coding exons than in the internal and last exons, although it is positively correlated with the synonymous substitution rate in all exon positions. Second, for the first exons, DNA methylation level is negatively correlated with exonic expression level, but positively correlated with both nonsynonymous substitution rate and the sample specificity of DNA methylation level. For the internal and last exons, however, we observe the opposite correlations. Our results imply that DNA methylation level is differentially correlated with the biological (and evolutionary) features of coding exons in different genic positions. The first exons appear more prone to the mutagenic effects, whereas the other exons are more influenced by the regulatory effects of DNA methylation.

Evolutionary expansion of a gene family may occur at both the DNA and RNA levels. The rat testis-specific Rtdpoz-T2 and -T1 (rT2 and rT1) retrogenes are members of the TD/POZ gene family which also includes the well-characterized SPOP gene. In this study, rT2/rT1 transcriptional activation in cancer cells is demonstrated; the cancer rT2/rT1 transcripts are structurally similar to the embryonic transcripts reported previously in frequent exonization of transposed elements. On database interrogation, we have identified an uncharacterized rT2/rT1-like SPOP paralog, designated as SPOP-like (SPOPL), in the human and rodent genomes. Ka/Ks analysis indicates that the SPOPL genes are under functional constraints implicating biological functions. Phylogenetic analyses further suggest that segmental duplication and retrotransposition events had occurred giving rise to new gene members or retrogenes in the human-rodent ancestors during the evolution of the TD/POZ gene family. Based on this and previous works, a model is proposed to map the routes of evolutionary expansion of the TD/POZ gene family. More importantly, different gene expression patterns of members of the family are depicted: intron-harboring members are ubiquitously expressed whereas retrogenes are expressed in tissue-specific and developmentally regulated manner, and are fortuitously re-activated in cancer cells involving exonization of transposed elements.

Human-specific small insertions and deletions (HS indels, with lengths

The completion of the rice (Oryza sativa) genome draft has brought unprecedented opportunities for genomic studies of the world's most important food crop. Previous rice gene annotations have relied mainly on ab initio methods, which usually yield a high rate of false-positive predictions and give only limited information regarding alternative splicing in rice genes. Comparative approaches based on expressed sequence tags (ESTs) can compensate for the drawbacks of ab initio methods because they can simultaneously identify experimental data-supported genes and alternatively spliced transcripts. Furthermore, cross-species EST information can be used to not only offset the insufficiency of same-species ESTs but also derive evolutionary implications. In this study, we used ESTs from seven plant species, rice, wheat (Triticum aestivum), maize (Zea mays), barley (Hordeum vulgare), sorghum (Sorghum bicolor), soybean (Glycine max), and Arabidopsis (Arabidopsis thaliana), to annotate the rice genome. We developed a plant genome annotation pipeline, Plant Gene and Alternatively Spliced Variant Annotator (PGAA). Using this approach, we identified 852 genes (931 isoforms) not annotated in other widely used databases (i.e. the Institute for Genomic Research, National Center for Biotechnology Information, and Rice Annotation Project) and found 87% of them supported by both rice and nonrice EST evidence. PGAA also identified more than 44,000 alternatively spliced events, of which approximately 20% are not observed in the other three annotations. These novel annotations represent rich opportunities for rice genome research, because the functions of most of our annotated genes are currently unknown. Also, in the PGAA annotation, the isoforms with non-rice-EST-supported exons are significantly enriched in transporter activity but significantly underrepresented in transcription regulator activity. We have also identified potential lineage-specific and conserved isoforms, which are important markers in evolutionary studies. The data and the Web-based interface, RiceViewer, are available for public access at http://RiceViewer.genomics.sinica.edu.tw/.

Circular RNAs (circRNAs) arise during post‐transcriptional processes, in which a single‐stranded RNA molecule forms a circle through covalent binding. Previously, circRNA products were often regarded to be splicing intermediates, by‐products, or products of aberrant splicing. But recently, rapid advances in high‐throughput RNA sequencing (RNA‐seq) for global investigation of nonco‐linear (NCL) RNAs, which comprised sequence segments that are topologically inconsistent with the reference genome, leads to renewed interest in this type of NCL RNA (i.e., circRNA), especially exonic circRNAs (ecircRNAs). Although the biogenesis and function of ecircRNAs are mostly unknown, some ecircRNAs are abundant, highly expressed, or evolutionarily conserved. Some ecircRNAs have been shown to affect microRNA regulation, and probably play roles in regulating parental gene transcription, cell proliferation, and RNA‐binding proteins, indicating their functional potential for development as diagnostic tools. To date, thousands of ecircRNAs have been identified in multiple tissues/cell types from diverse species, through analyses of RNA‐seq data. However, the detection of ecircRNA candidates involves several major challenges, including discrimination between ecircRNAs and other types of NCL RNAs (e.g., trans‐spliced RNAs and genetic rearrangements); removal of sequencing errors, alignment errors, and in vitro artifacts; and the reconciliation of heterogeneous results arising from the use of different bioinformatics methods or sequencing data generated under different treatments. Such challenges may severely hamper the understanding of ecircRNAs. Herein, we review the biogenesis, identification, properties, and function of ecircRNAs, and discuss some unanswered questions regarding ecircRNAs. We also evaluate the accuracy (in terms of sensitivity and precision) of some well‐known circRNA‐detecting methods. WIREs RNA 2015, 6:563–579. doi: 10.1002/wrna.1294 For further resources related to this article, please visit the WIREs website.

Summary: ESTviewer is a web application for interactively visualizing human gene structures, with emphasis on mammalian and avian expressed sequence tags (ESTs) that are conserved in the human genome and alternatively spliced (AS) variants. AS variants from the UCSC, Vega and PSEP annotations are presented in this application for comparison. EST data from six species, human, mouse, rat, cattle, pig and chicken, are mapped to the human genome to show cross-species EST conservation in annotated exonic and intronic regions. Cross-species EST conservation is evolutionarily and functionally important because it represents the effects of selection pressure on genic regions and transcriptome over evolutionary time. Emphatically, ESTviewer provides a convenient tool to compare highly conserved non-human ESTs and human AS variants. The application takes human gene accession Ids or coordinates of genomic sequences as inputs and presents annotated gene structures and their AS variants. In addition, the lengths and percentages of human genic regions covered by ESTs are displayed to show the level of EST coverage of different species. The percentages of the UCSC, Vega and PSEP annotated exons covered by ESTs of the six studied species are also displayed in the interface. Availability: The ESTviewer web interface is publicly accessible at http://www.gate.sinica.edu.tw/~trees/ESTviewer/ESTviewer.htm Contact: trees@gate.sinica.edu.tw Supplementary information: Detailed documentation and the data sets, including the whole human genome annotation of PSEP and 6-species ESTs conserved in the human genome, can be found on the ESTviewer home page.

The entire human genome has been sequenced and annotated separately by Lander et al. (2001) and Venter et al. (2001). Altogether, 30,000 to 40,000 protein-coding genes were annotated from the genomic sequence. This number, roughly twice as many as in the worm or fly, deviates greatly from the earlier high estimates (Ewing and Green 2000; Liang et al. 2000; Roest Crollius et al. 2000). The exact gene number in the human genome remains to be determined by accurate annotation of the sequence data. Genome annotation is based primarily on the ab initio and homology methods. The ab initio approach predicts genes directly from the genomic sequence using the computational properties of exons, introns, and other signature features without referencing the experimental data. Numerous ab initio prediction programs have been used extensively in genome annotation, including FGENESH (Solovyev et al. 1995; Salamov and Solovyev 2000), GeneID (Parra et al. 2000), GeneMark.hmm (Lukashin and Borodovsky 1998), GeneView (Milanesi et al. 1993), GENSCAN (Burge and Karlin 1997, 1998), Genie (Kulp et al. 1996; Reese et al. 2000), Grail (Xu et al. 1994), GrailEXP_Perceval (Hyatt et al. 2000), HMMgene (Krogh 1998, 2000), and MZEF (Zhang 1997). The homology approach identifies genes with the aid of experimental data. This approach exploits sequence alignment between the genomic data and known cDNA or protein databases. Successful implementation of this method includes AAT (Huang et al. 1997), FGENESH+ and FGENESH++ (Salamov and Solovyev 2000), GAIA (Bailey et al. 1998), GeneBuilder (Milanesi et al. 1999), GenomeScan (Yeh et al. 2001), GrailEXP_Gawain (Hyatt et al. 2000), GeneWise (Birney and Durbin 2000), ICE (Pachter et al. 1999), and Procrustes (Gelfand et al. 1996; Sze and Pevzner 1997; Mironov et al. 1998). Among these programs FGENESH+ (and FGENESH++), GenomeScan, GeneWise, and Procrustes are combined tools of sequence homology and ab initio annotation. Generally speaking, the ab initio approach tends to have a higher rate of false-positive predictions (overprediction) in annotating long genomic sequences with multiple genes (Dunham et al. 1999). The homology-based approaches demand high-performance computing and large storage space. Furthermore, these methods require extensive manual interventions to curate true gene prediction from large sets of matched data. The combination tools for sequence alignment and ab initio annotation, although highly accurate, are not robust in routine applications. In this paper, we propose a new method, the Complexity Reduction Algorithm for Sequence Analysis (CRASA), for global alignment and annotation of the genomic sequence. The method finds the exact match between the cDNA data and genomic sequence; thus mapping the expressed genes directly to it. By using a set of filters, the enormous data complexity is reduced substantially. Thus, it provides an annotated framework of expressed genes in the genome. The CRASA system restructures the cDNA data progressively into a pattern-based pyramidal data structure in hierarchical orders. The algorithm offers an automatic search of the entire database efficiently and is amicable to the implementation of parallel processing (see Methods). In this paper, CRASA was tested with two benchmark data sets, the SemiArtificial Genomic (SAG) sequences provided by Guigo et al. (2000) and the Real Genomic (RG) sequences generated ad hoc from GeneBank of NCBI (National Center of Biotechnolgy Information). In general, CRASA was capable of delivering annotation accuracy better than the other 15 programs tested in this study (see Results and Discussion). The annotated human Chromosomes 21 (Hattori et al. 2000) and 22 (Dunham et al. 1999), although incomplete, are considered as standard benchmarks for genome annotation. In the benchmark test of human Chromosomes 21 and 22, CRASA's filters were able to remove the massive noise from matched hits, thus reducing the complexity of genome analysis. More significantly, our method identified 83 additional EST matches that were not annotated previously. These 83 matches were extracted and categorized into five classes. Our results indicate that CRASA, with its capabilities of complexity reduction, progressive data transmission, and direct pattern match, is a robust and effective new method for genome annotation. The simplicity of program implementation allows for unlimited query size and parallel processing on multiple processors. It is well suited for annotating large genomic sequences.

Background Crop plants such as rice, maize and sorghum play economically-important roles as main sources of food, fuel, and animal feed. However, current genome annotations of crop plants still suffer false-positive predictions; a more comprehensive registry of alternative splicing (AS) events is also in demand. Comparative genomics of crop plants is largely unexplored. Results We performed a large-scale comparative analysis (ExonFinder) of the expressed sequence tag (EST) library from nine grass plants against three crop genomes (rice, maize, and sorghum) and identified 2,879 previously-unannotated exons (i.e., novel exons) in the three crops. We validated 81% of the tested exons by RT-PCR-sequencing, supporting the effectiveness of our in silico strategy. Evolutionary analysis reveals that the novel exons, comparing with their flanking annotated ones, are generally under weaker selection pressure at the protein level, but under stronger pressure at the RNA level, suggesting that most of the novel exons also represent novel alternatively spliced variants (ASVs). However, we also observed the consistency of evolutionary rates between certain novel exons and their flanking exons, which provided further evidence of their co-occurrence in the transcripts, suggesting that previously-annotated isoforms might be subject to erroneous predictions. Our validation showed that 54% of the tested genes expressed the newly-identified isoforms that contained the novel exons, rather than the previously-annotated isoforms that excluded them. The consistent results were steadily observed across cultivated (Oryza sativa and O. glaberrima) and wild (O. rufipogon and O. nivara) rice species, asserting the necessity of our curation of the crop genome annotations. Our comparative analyses also inferred the common ancestral transcriptome of grass plants and gain- and loss-of-ASV events. Conclusions We have reannotated the rice, maize, and sorghum genomes, and showed that evolutionary rates might serve as an indicator for determining whether the identified exons were alternatively spliced. This study not only presents an effective in silico strategy for the improvement of plant annotations, but also provides further insights into the role of AS events in the evolution and domestication of crop plants. ExonFinder and the novel exons/ASVs identified are publicly accessible at http://exonfinder.sourceforge.net/. Electronic supplementary material The online version of this article (doi:10.1186/s12870-015-0431-7) contains supplementary material, which is available to authorized users.

Summary: CNVVdb is a web interface for identification of putative copy number variations (CNVs) among 16 vertebrate species using the-same-species self-alignments and cross-species pairwise alignments. By querying genomic coordinates in the target species, all the potential paralogous/orthologous regions that overlap ≥80–100% (adjustable) of the query sequences with user-specified sequence identity (≥60%∼≥90%) are returned. Additional information is also given for the genes that are included in the returned regions, including gene description, alternatively spliced transcripts, gene ontology descriptions and other biologically important information. CNVVdb also provides information of pseudogenes and single nucleotide polymorphisms (SNPs) for the CNV-related genomic regions. Moreover, multiple sequence alignments of shared CNVs across species are also provided. With the combination of CNV, SNP, pseudogene and functional information, CNVVdb can be very useful for comparative and functional studies in vertebrates. Availability: CNVVdb is freely accessible at http://CNVVdb.genomics.sinica.edu.tw. Contact: trees@gate.sinica.edu.tw

This paper presents a spatial domain method for lossless still image compression using a new scheme: base switching (BS). The given image is partitioned into non-overlapping fixed-size subimages. Di⁄erent subimages then get di⁄erent compression ratios according to the base values of the subimages. In order to increase the compression ratio, a hierarchical technique is also used. It is found that the compression ratio of the proposed algorithm can compete with that of the VBSS and the international standard algorithms known as JBIG and Lossless JPEG. In addition, when the BS method is compared with the S#P method, which is an excellent frequency domain method that used EZW, although S#P method gains about 9% increase in the compression ratio, its encoding time (excluding I/O) is about three times longer than ours. The math theory needed to build up the proposed compression scheme is also provided. ( 1998 Published by Elsevier Science Ltd on behalf of the Pattern Recognition Society. All rights reserved

Background Complex human diseases may be associated with many gene interactions. Gene interactions take several different forms and it is difficult to identify all of the interactions that are potentially associated with human diseases. One approach that may fill this knowledge gap is to infer previously unknown gene interactions via identification of non-physical linkages between different mutations (or single nucleotide polymorphisms, SNPs) to avoid hitchhiking effect or lack of recombination. Strong non-physical SNP linkages are considered to be an indication of biological (gene) interactions. These interactions can be physical protein interactions, regulatory interactions, functional compensation/antagonization or many other forms of interactions. Previous studies have shown that mutations in different genes can be linked to the same disorders. Therefore, non-physical SNP linkages, coupled with knowledge of SNP-disease associations may shed more light on the role of gene interactions in human disorders. A user-friendly web resource that integrates information about non-physical SNP linkages, gene annotations, SNP information, and SNP-disease associations may thus be a good reference for biomedical research. Findings Here we extracted the SNPs located within the promoter or exonic regions of protein-coding genes from the HapMap database to construct a database named the L inkage-D isequilibrium-based G ene I nteraction d atab ase (LDGIdb). The database stores 646,203 potential human gene interactions, which are potential interactions inferred from SNP pairs that are subject to long-range strong linkage disequilibrium (LD), or non-physical linkages. To minimize the possibility of hitchhiking, SNP pairs inferred to be non-physically linked were required to be located in different chromosomes or in different LD blocks of the same chromosomes. According to the genomic locations of the involved SNPs (i.e., promoter, untranslated region (UTR) and coding region (CDS)), the SNP linkages inferred were categorized into promoter-promoter, promoter-UTR, promoter-CDS, CDS-CDS, CDS-UTR and UTR-UTR linkages. For the CDS-related linkages, the coding SNPs were further classified into nonsynonymous and synonymous variations, which represent potential gene interactions at the protein and RNA level, respectively. The LDGIdb also incorporates human disease-association databases such as Genome-Wide Association Studies (GWAS) and Online Mendelian Inheritance in Man (OMIM), so that the user can search for potential disease-associated SNP linkages. The inferred SNP linkages are also classified in the context of population stratification to provide a resource for investigating potential population-specific gene interactions. Conclusion The LDGIdb is a user-friendly resource that integrates non-physical SNP linkages and SNP-disease associations for studies of gene interactions in human diseases. With the help of the LDGIdb, it is plausible to infer population-specific SNP linkages for more focused studies, an avenue that is potentially important for pharmacogenetics. Moreover, by referring to disease-association information such as the GWAS data, the LDGIdb may help identify previously uncharacterized disease-associated gene interactions and potentially lead to new discoveries in studies of human diseases. Keywords Gene interaction, SNP, Linkage disequilibrium, Systems biology, Bioinformatics