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BackgroundWith the advent of large-scale molecular profiling, an increasing number of oncogenic drivers contributing to precise medicine and reshaping classification of lung adenocarcinoma (LUAD) have been identified. However, only a minority of patients archived improved outcome under current standard therapies because of the dynamic mutational spectrum, which required expanding susceptible gene libraries. Accumulating evidence has witnessed that understanding gene regulatory networks as well as their changing processes was helpful in identifying core genes which acted as master regulators during carcinogenesis. The present study aimed at identifying key genes with differential correlations between normal and tumor status.MethodsWeighted gene co-expression network analysis (WGCNA) was employed to build a gene interaction network using the expression profile of LUAD from The Cancer Genome Atlas (TCGA). R package DiffCorr was implemented for the identification of differential correlations between tumor and adjacent normal tissues. STRING and Cytoscape were used for the construction and visualization of biological networks.ResultsA total of 176 modules were detected in the network, among which yellow and medium orchid modules showed the most significant associations with LUAD. Then genes in these two modules were further chosen to evaluate their differential correlations. Finally, dozens of novel genes with opposite correlations including ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 were identified. Further biological and survival analyses highlighted their potential values in the diagnosis and treatment of LUAD. Moreover, real-time qPCR confirmed the expression patterns of ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 in LUAD tissues and cell lines.ConclusionOur study provided new insights into the gene regulatory mechanisms during transition from normal to tumor, pioneering a network-based algorithm in the application of tumor etiology.

Acute myeloid leukemia (AML) is a type of blood cancer characterized by the rapid growth of immature white blood cells from the bone marrow. Therapy resistance resulting from the persistence of leukemia stem cells (LSCs) are found in numerous patients. Comparative transcriptome studies have been previously conducted to analyze differentially expressed genes between LSC+ and LSC- cells. However, these studies mainly focused on a limited number of genes with the most obvious expression differences between the two cell types. We developed a computational approach incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS), incremental feature selection (IFS), support vector machine (SVM), Repeated Incremental Pruning to Produce Error Reduction (RIPPER), to identify gene expression features specific to LSCs. One thousand 0ne hudred fifty-nine features (genes) were first identified, which can be used to build the optimal SVM classifier for distinguishing LSC+ and LSC- cells. Among these 1159 genes, the top 17 genes were identified as LSC-specific biomarkers. In addition, six classification rules were produced by RIPPER algorithm. The subsequent literature review on these features/genes and the classification rules and functional enrichment analyses of the 1159 features/genes confirmed the relevance of extracted genes and rules to the characteristics of LSCs.

Tumors are driven by a sequence of genetic and epigenetic alterations. Previous studies have mostly focused on the roles of somatic mutations in tumorigenesis, but how germline variants act is largely unknown. In this study, we hypothesized that allelic expression imbalance (AEI) participated in the process of germline variants on tumorigenesis. We screened single-nucleotide polymorphisms (SNPs) as representative germline variants. By using 127 patients’ RNA sequencing data from paired lung cancer and adjacent normal tissues from public databases, we analyzed the effects of the functional consequence of SNPs, function and conservativeness on genes with AEI. We found that natural selection can affect AEI. Functional adaptability of genes with a high frequency of AEI and a correlation of the incidence of AEI with conservativeness were observed in both adjacent tissues and tumor tissues. Moreover, we observed a higher incidence of AEI in genes with non-synonymous SNPs than in those with synonymous SNPs. However, we also found that AEI was affected by allele expression noise, especially in tumor tissues, which led to an increased proportion of AEI, weakened the effect of natural selection and eliminated the influence of the functional consequence of SNPs on AEI. We unveiled a previously unknown adaptive regulatory mechanism in which the effect of natural selection on SNPs can be reflected in allelic expression, which provides insight into a better understanding of cancer evolution.

Post-translational modifications play important roles in cell activities ranging from gene regulation to cytoplasmic mechanisms. Unfortunately, experimental methods investigating protein post-translational modifications such as high-resolution mass spectrometry are time consuming, labor-intensive and expensive. Therefore, there is a need to develop computational methods to facilitate fast and efficient identification. In this study, we developed a method to predict N-formylated methionines based on the Dagging method. Various features were incorporated, including PSSM conservation scores, amino acid factors, secondary structures, solvent accessibilities and disorder scores. An optimal feature set was selected containing 28 features using the mRMR (Maximum Relevance Minimum Redundancy) method and the IFS (Incremental Feature Selection) method. The prediction model constructed based on these features achieved an accuracy of 0.9074 and a MCC value of 0.7478. Analysis of these optimal features was performed, and several important factors and important sites were revealed to play important roles in N-formylation formation. We also compared N-formylation with N-acetylation, another type of important N-terminal modification of methionines. A total of top 34 MaxRel (most relevant) features were selected to discriminate between the two types of modifications, which may be candidates for studying the different mechanisms between N-formylation and N-acetylation. The results from our study further the understanding of these two types of modifications and provide guidance for related validation experiments.

Through linkage and candidate gene screening, many breast cancer (BC) predisposition genes have been identified in the past 20 years. However, the majority of genetic risks that contribute to familial BC remains undetermined. In this study, we revisited whole exome sequencing datasets from non-BRCA1/2 familial BC patients, to search for novel BC predisposition genes. Based on the infinite mutation model, we supposed that rare non-silent variants that cooccurred between familial and TCGA-germline datasets, might play a predisposition contributing role. In our analysis, we not only identified novel potential pathogenic variants from known cancer predisposition genes, such as MRE11, CTR9 but also identified novel candidate predisposition genes, such as NCK1. According to the TCGA mRNA expression dataset of BC, NCK1 was significantly upregulated in basal-like subtypes and downregulated in luminal subtypes. In vitro, NCK1 mutants (D73H and R42Q) transfected MCF7 cell lines, which attributed to the luminal subtype, were much more viable and invasive than the wild type. On the other side, our results also showed that overall survival and disease-free survival of patients with NCK1 variations might be dependent on the genomic context. In conclusion, genetic heterogeneity exists among non-BRCA1/2 BC pedigrees and NCK1 could be a novel BC predisposition gene.

Background Men are at higher risk of developing chronic lymphocytic leukemia (CLL) than women. DNA methylation has been shown to play important roles in a number of cancers. There are differences in the DNA methylation pattern between men and women. In this study, we investigated whether this contributes to the sex-related difference of B cell CLL risk. Methods Using the HumanMethylation450 BeadChip, we profiled the genome-wide DNA methylation pattern of CD19+ B cells from 48 CLL patients (29 female patients and 19 male patients) and 28 healthy people (19 women and 9 men). Results We identified 1043 sex-related differentially methylated positions (DMPs) related to CLL, 56 of which are located on autosomes and 987 on the X chromosome. Using published B cell RNA-sequencing data, we found 18 genes covered by the DMPs also have different expression levels in male and female CLL patients. Among them, TRIB1, an autosome gene, has been shown to promote tumor growth by suppressing apoptosis. Conclusions Our study represents the first epigenome-wide association study (EWAS) that investigates the sex-related differences in cancer, and indicated that DNA methylation differences might contribute to the sex-related difference in CLL risk. Electronic supplementary material The online version of this article (10.1186/s13293-018-0213-7) contains supplementary material, which is available to authorized users.

Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNAs can both participate in the regulation of methylation and pseudouridylation and regulate the expression pattern of their host genes. This research investigated the expression pattern of snoRNAs in eight major cancer types in TCGA via several machine learning algorithms. The expression levels of snoRNAs were first analyzed by a powerful feature selection method, Monte Carlo feature selection (MCFS). A feature list and some informative features were accessed. Then, the incremental feature selection (IFS) was applied to the feature list to extract optimal features/snoRNAs, which can make the support vector machine (SVM) yield best performance. The discriminative snoRNAs included HBII-52-14, HBII-336, SNORD123, HBII-85-29, HBII-420, U3, HBI-43, SNORD116, SNORA73B, SCARNA4, HBII-85-20, etc., on which the SVM can provide a Matthew&rsquo, s correlation coefficient (MCC) of 0.881 for predicting these eight cancer types. On the other hand, the informative features were fed into the Johnson reducer and repeated incremental pruning to produce error reduction (RIPPER) algorithms to generate classification rules, which can clearly show different snoRNAs expression patterns in different cancer types. The analysis results indicated that extracted discriminative snoRNAs can be important for identifying cancer samples in different types and the expression pattern of snoRNAs in different cancer types can be partly uncovered by quantitative recognition rules.

Tissue-specific gene expression has long been recognized as a crucial key for understanding tissue development and function. Efforts have been made in the past decade to identify tissue-specific expression profiles, such as the Human Proteome Atlas and FANTOM5. However, these studies mainly focused on &ldquo, qualitatively tissue-specific expressed genes&rdquo, which are highly enriched in one or a group of tissues but paid less attention to &ldquo, quantitatively tissue-specific expressed genes&rdquo, which are expressed in all or most tissues but with differential expression levels. In this study, we applied machine learning algorithms to build a computational method for identifying &ldquo, capable of distinguishing 25 human tissues from their expression patterns. Our results uncovered the expression of 432 genes as optimal features for tissue classification, which were obtained with a Matthews Correlation Coefficient (MCC) of more than 0.99 yielded by a support vector machine (SVM). This constructed model was superior to the SVM model using tissue enriched genes and yielded MCC of 0.985 on an independent test dataset, indicating its good generalization ability. These 432 genes were proven to be widely expressed in multiple tissues and a literature review of the top 23 genes found that most of them support their discriminating powers. As a complement to previous studies, our discovery of these quantitatively tissue-specific genes provides insights into the detailed understanding of tissue development and function.

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein–protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

Cancer is a significant public health problem worldwide. Complete identification of genes related to one type of cancer facilitates earlier diagnosis and effective treatments. In this study, two widely used algorithms, the random walk with restart algorithm and the shortest path algorithm, were adopted to construct two parameterized computational methods, namely, an RWR-based method and an SP-based method; based on these methods, an integrated method was constructed for identifying novel disease genes. To validate the utility of the integrated method, data for oral cancer were used, on which the RWR-based and SP-based methods were trained, thereby building two optimal methods. The integrated method combining these optimal methods was further adopted to identify the novel genes of oral cancer. As a result, 85 novel genes were inferred, among which eleven genes (e.g., MYD88, FGFR2, NF-κBIA) were identified by both the RWR-based and SP-based methods, 70 genes (e.g., BMP4, IFNG, KITLG) were discovered only by the RWR-based method and four genes (L1R1, MCM6, NOG and CXCR3) were predicted only by the SP-based method. Extensive analyses indicate that several novel genes have strong associations with cancers, indicating the effectiveness of the integrated method for identifying disease genes.

The human brain is one of the most mysterious tissues in the body. Our knowledge of the human brain is limited due to the complexity of its structure and the microscopic nature of connections between brain regions and other tissues in the body. In this study, we analyzed the gene expression profiles of three brain regions—the brain stem, cerebellum and cerebral cortex—to identify genes that are differentially expressed among these different brain regions in humans and to obtain a list of robust, region-specific, differentially expressed genes by comparing the expression signatures from different individuals. Feature selection methods, specifically minimum redundancy maximum relevance and incremental feature selection, were employed to analyze the gene expression profiles. Sequential minimal optimization, a machine-learning algorithm, was employed to examine the utility of selected genes. We also performed a literature search, and we discuss the experimental evidence for the important physiological functions of several highly ranked genes, including NR2E1, DAO, and LRRC7, and we give our analyses on a gene (TFAP2B) that have not been investigated or experimentally validated. As a whole, the results of our study will improve our ability to predict and understand genes related to brain regionalization and function.

Background Hepatitis is a type of infectious disease that induces inflammation of the liver without pinpointing a particular pathogen or pathogenesis. Type C hepatitis, as a type of hepatitis, has been reported to induce cirrhosis and hepatocellular carcinoma within a very short amount of time. It is a great threat to human health. Some studies have revealed that trace elements are associated with infection with and immune rejection against hepatitis C virus (HCV). However, the mechanism underlying this phenomenon is still unclear. Methods In this study, we aimed to expand our knowledge of this phenomenon by designing a computational method to identify genes that may be related to both HCV and trace element metabolic processes. The searching procedure included three stages. First, a shortest path algorithm was applied to a large network, constructed by protein-protein interactions, to identify potential genes of interest. Second, a permutation test was executed to exclude false discoveries. Finally, some rules based on the betweenness and associations between candidate genes and HCV and trace elements were built to select core genes among the remaining genes. Results 12 lists of genes, corresponding to 12 types of trace elements, were obtained. These genes are deemed to be associated with HCV infection and trace elements metabolism. Conclusions The analyses indicate that some genes may be related to both HCV and trace element metabolic processes, further confirming the associations between HCV and trace elements. The method was further tested on another set of HCV genes, the results indicate that this method is quite robustness. General significance The newly found genes may partially reveal unknown mechanisms between HCV infection and trace element metabolism. This article is part of a Special Issue entitled “System Genetics” Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Longevity is one of the most basic and one of the most essential properties of all living organisms. Identification of genes that regulate longevity would increase understanding of the mechanisms of aging, so as to help facilitate anti-aging intervention and extend the life span. In this study, based on the network features and the biochemical/physicochemical features of the deletion network and deletion genes, as well as their functional features, a two-layer model was developed for predicting the deletion effects on yeast longevity. The first stage of our prediction approach was to identify whether the deletion of one gene would change the life span of yeast; if it did, the second stage of our procedure would automatically proceed to predict whether the deletion of one gene would increase or decrease the life span. It was observed by analyzing the predicted results that the functional features (such as mitochondrial function and chromatin silencing), the network features (such as the edge density and edge weight density of the deletion network), and the local centrality of deletion gene, would have important impact for predicting the deletion effects on longevity. It is anticipated that our model may become a useful tool for studying longevity from the angle of genes and networks. Moreover, it has not escaped our notice that, after some modification, the current model can also be used to study many other phenotype prediction problems from the angle of systems biology.

As a common brain cancer derived from glial cells, gliomas have three subtypes: glioblastoma, diffuse astrocytoma, and anaplastic astrocytoma. The subtypes have distinctive clinical features but are closely related to each other. A glioblastoma can be derived from the early stage of diffuse astrocytoma, which can be transformed into anaplastic astrocytoma. Due to the complexity of these dynamic processes, single-cell gene expression profiles are extremely helpful to understand what defines these subtypes. We analyzed the single-cell gene expression profiles of 5057 cells of anaplastic astrocytoma tissues, 261 cells of diffuse astrocytoma tissues, and 1023 cells of glioblastoma tissues with advanced machine learning methods. In detail, a powerful feature selection method, Monte Carlo feature selection (MCFS) method, was adopted to analyze the gene expression profiles of cells, resulting in a feature list. Then, the incremental feature selection (IFS) method was applied to the obtained feature list, with the help of support vector machine (SVM), to extract key features (genes) and construct an optimal SVM classifier. Several key biomarker genes, such as IGFBP2, IGF2BP3, PRDX1, NOV, NEFL, HOXA10, GNG12, SPRY4, and BCL11A, were identified. In addition, the underlying rules of classifying the three subtypes were produced by Johnson reducer algorithm. We found that in diffuse astrocytoma, PRDX1 is highly expressed, and in glioblastoma, the expression level of PRDX1 is low. These rules revealed the difference among the three subtypes, and how they are formed and transformed. These genes are not only biomarkers for glioma subtypes, but also drug targets that may switch the clinical features or even reverse the tumor progression.

We report a large Chinese family with X-linked postlingual nonsyndromic hearing impairment in which the critical linkage interval spans a genetic distance of 5.41 cM and a physical distance of 15.1 Mb that overlaps the DFN2 locus. Mutation screening of the PRPS1 gene in this family and in the three previously reported DFN2 families identified four different missense mutations in PRPS1. These mutations result in a loss of phosphoribosyl pyrophosphate (PRPP) synthetase 1 activity, as was shown in silico by structural analysis and was shown in vitro by enzymatic activity assays in erythrocytes and fibroblasts from patients. By in situ hybridization, we demonstrate expression of Prps1 in murine vestibular and cochlea hair cells, with continuous expression in hair cells and postnatal expression in the spiral ganglion. Being the second identified gene associated with X-linked nonsyndromic deafness, PRPS1 will be a good candidate gene for genetic testing for X-linked nonsyndromic hearing loss.

Although there is an accumulating appreciation of the key roles that long intergenic non-coding RNAs (lincRNAs) play in diverse cellular processes, our knowledge of how lincRNAs function in cancer remains sparse. Here, we present a comprehensive landscape of RNA-seq transcriptome profiles of lung adenocarcinomas and their paired normal counterparts to unravel gene regulation rules of lincRNAs. Consistent with previous findings of co-expression between neighboring protein-coding genes, lincRNAs were typically co-expressed with their neighboring genes, which was found in both cancerous and normal tissues. By building a mathematical model based on correlated gene expression, we distinguished an additional subset of lincRNAs termed "regulatory lincRNAs", representing their dominant roles in gene regulation. The number of regulatory lincRNAs was significantly higher in cancerous compared to normal tissues, and most of them positively regulated protein-coding genes in trans. Functional validation, using knockdown, determined that regulatory lincRNA, GAS5, affected its predicted protein-coding targets. Moreover, we discovered hundreds of differentially expressed regulatory lincRNAs with inclusion of some cancer-associated lincRNAs. Our integrated analysis reveals enhanced regulatory effects of lincRNAs and provides a resource for the study of regulatory lincRNAs that play critical roles in lung adenocarcinoma.

Pancreatic cancer (PC) is a highly malignant tumor derived from pancreas tissue and is one of the leading causes of death from cancer. Its molecular mechanism has been partially revealed by validating its oncogenes and tumor suppressor genes; however, the available data remain insufficient for medical workers to design effective treatments. Large-scale identification of PC-related genes can promote studies on PC. In this study, we propose a computational method for mining new candidate PC-related genes. A large network was constructed using protein-protein interaction information, and a shortest path approach was applied to mine new candidate genes based on validated PC-related genes. In addition, a permutation test was adopted to further select key candidate genes. Finally, for all discovered candidate genes, the likelihood that the genes are novel PC-related genes is discussed based on their currently known functions.

Human brain development is a dramatic process composed of a series of complex and fine-tuned spatiotemporal gene expressions. A good comprehension of this process can assist us in developing the potential of our brain. However, we have only limited knowledge about the genes and gene functions that are involved in this biological process. Therefore, a substantial demand remains to discover new brain development-related genes and identify their biological functions. In this study, we aimed to discover new brain-development related genes by building a computational method. We referred to a series of computational methods used to discover new disease-related genes and developed a similar method. In this method, the shortest path algorithm was executed on a weighted graph that was constructed using protein-protein interactions. New candidate genes fell on at least one of the shortest paths connecting two known genes that are related to brain development. A randomization test was then adopted to filter positive discoveries. Of the final identified genes, several have been reported to be associated with brain development, indicating the effectiveness of the method, whereas several of the others may have potential roles in brain development.

Apoptosis is the process of programmed cell death (PCD) that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature.

Numerous eukaryotic genes are alternatively spliced. Recently, deep transcriptome sequencing has skyrocketed proportion of alternatively spliced genes; over 95% human multi-exon genes are alternatively spliced. One fundamental question is: are all these alternative splicing (AS) events functional? To look into this issue, we studied the most common form of alternative 5' splice sites-GYNNGYs (Y = C/T), where both GYs can function as splice sites. Global analyses suggest that splicing noise (due to stochasticity of splicing process) can cause AS at GYNNGYs, evidenced by higher AS frequency in non-coding than in coding regions, in non-conserved than in conserved genes and in lowly expressed than in highly expressed genes. However, ∼20% AS GYNNGYs in humans and ∼3% in mice exhibit tissue-dependent regulation. Consistent with being functional, regulated GYNNGYs are more conserved than unregulated ones. And regulated GYNNGYs have distinctive sequence features which may confer regulation. Particularly, each regulated GYNNGY comprises two splice sites more resembling each other than unregulated GYNNGYs, and has more conserved downstream flanking intron. Intriguingly, most regulated GYNNGYs may tune gene expression through coupling with nonsense-mediated mRNA decay, rather than encode different proteins. In summary, AS at GYNNGY 5' splice sites is primarily splicing noise, and secondarily a way of regulation.

Although the study of imprinted genes in human development is very important, little is known about their expression and regulation in the early differentiation of human tissues due to lack of an appropriate model. In this study, a Chinese human embryonic stem (hES) cell line, SHhES1, was derived and fully characterized. Expression profiles of human imprinted genes were determined by Affymetrix Oligo micro-array in undifferentiated SHhES1 cells and SHhES1-derived embryoid bodies (EBs) at day 3, 8, 13 and 18. Thirty-two known human imprinted genes were detected in undifferentiated ES cells. Significantly, differential expression was found in nine genes at different stages of EB formation. Expression profile changes were confirmed by quantitative real-time reverse transcriptase-polymerase chain reaction in SHhES1 cells as well as in another independently derived hES cell line, HUES-7. In addition, the monoallelic expressions of four imprinted genes were examined in three different passages of undifferentiated ES cells and EBs of both hES cell lines. The monoallelic expressions of imprinted genes, H19, PEG10, NDNL1 and KCNQ1 were maintained in both undifferentiated hES cells and derived EBs. More importantly, with the availability of maternal peripheral blood lymphocyte sample, we demonstrated that the maternal expression of KCNQ1 and the paternal expression of NDNL1 and PEG10 were maintained in SHhES1 cells. These data provide the first demonstration that the parental-specific expression of imprinted genes is stable in EBs after extensive differentiation, also indicating that in vitro fertilization protocol does not disrupt the parental monoallelic expression of the imprinted genes examined.

Our group has previously demonstrated a high frequency of allelic loss on the short arm of chromosome 8 and identified a region of homozygous deletion of 1.41 Mb, flanked by D8S520 and D8S1130, on 8p23.1 in medulloblastomas, suggesting the presence of a tumor suppressor gene in this critical deletion region. The aim of our study was to investigate whether PinX1, a newly identified gene whose product is a potent inhibitor of telomerase, is the target gene in the homozygous deletion region identified in medulloblastomas. We assessed for alterations in gene sequence and transcript expression of PinX1, as well as the correlation between PinX1 expression and telomerase activity in a series of 52 medulloblastomas, 3 medulloblastoma cell lines (D283, D341 and Daoy) and 4 primitive neuroectodermal tumors (PNETs). Direct sequence analysis of all 7 exons and splice junctions of the PinX1 gene revealed no somatic mutations but 11 genetic polymorphisms. Transcript expression of PinX1, as evaluated by reverse transcription-polymerase chain reaction, in microdissected tumors and normal cerebellum showed 2 transcript variants, corresponding to the full-length form and an alternative spliced variant lacking exon 6, in all samples. This result indicated that PinX1 expression was not suppressed in medulloblastomas. Using the telomeric repeat amplification protocol (TRAP) assay, 13 of 19 (68%) medulloblastomas, 1 of 2 PNETs and all 3 cell lines showed telomerase activity. There is no significant correlation between PinX1 transcript expression and telomerase activity, but our results showed that telomerase activation is involved in medulloblastomas. Taken together, our results suggest that PinX1 does not play a major role in the oncogenesis of medulloblastomas. © 2003 Wiley-Liss, Inc.

Nonsyndromic inherited hearing impairment is genetically heterogeneous. Up to now, approximately 51 autosomal dominant loci implicated in nonsyndromic forms of hearing impairment have been reported in humans and 17 causative genes have been identified. Skipping of exon 8 in the DFNA5 gene has been shown to cause hearing impairment in a Dutch family. To our knowledge, no other DFNA5 mutation has been reported in familial or sporadic hearing impairment. Here, we report another mutation in DFNA5, a CTT deletion in the polypyrimidine tract of intron 7. This mutation, just like the previously reported mutation in the Dutch family, leads to skipping of exon 8 of DFNA5. In addition, we prove the existence of a recently identified short isoform of DFNA5, but the 3-nucleotide deletion reported here seems not to affect the function of this short isoform. Because no other mutation in any other part of DFNA5 has ever been described, this finding might indicate that exon 8 of DFNA5 is indispensable for the development of hearing impairment.

As a chronic illness derived from hair cells of the inner ear, Menière's disease (MD) negatively influences the quality of life of individuals and leads to a number of symptoms, such as dizziness, temporary hearing loss, and tinnitus. The complete identification of novel genes related to MD would help elucidate its underlying pathological mechanisms and improve its diagnosis and treatment. In this study, a network-based method was developed to identify novel MD-related genes based on known MD-related genes. A human protein-protein interaction (PPI) network was constructed using the PPI information reported in the STRING database. A classic ranking algorithm, the random walk with restart (RWR) algorithm, was employed to search for novel genes using known genes as seed nodes. To make the identified genes more reliable, a series of screening tests, including a permutation test, an interaction test and an enrichment test, were designed to select essential genes from those obtained by the RWR algorithm. As a result, several inferred genes, such as CD4, NOTCH2 and IL6, were discovered. Finally, a detailed biological analysis was performed on fifteen of the important inferred genes, which indicated their strong associations with MD.

Lung cancer is the most common cause of cancer mortality worldwide, with an estimated 1.4 million deaths each year. Here we report whole-exome sequencing of nine tumor/normal tissue pairs from Chinese patients with non-small cell lung carcinoma (NSCLC). This allows us to identify a number of significantly mutated genes in NSCLC, which were highly enriched in DNA damage repair, NF-κB pathway, JAK/STAT signaling and chromatin modification. Notably, we identify a histone-lysine methyltransferase gene, namely, MLL2, as one of the most significantly mutated genes in our screen. In a following validation study, we identify deleterious mutations of MLL2 in 12 out of 105 (11.4%) NSCLC patients. Additionally, reduced or lost expression of MLL2 was commonly observed in tumor tissues as compared with paired adjacent non-tumor tissues regardless of mutation status. Together, our study defines the landscape of somatic mutations in Chinese NSCLC and supports the role of MLL2 mutation in the pathogenesis of the disease.

Congenital heart disease (CHD) is the most common birth defect affecting the structure and function of fetal hearts. Despite decades of extensive studies, the genetic mechanism of sporadic CHD remains obscure. Deleted in liver cancer 1 (DLC1) gene, encoding a GTPase-activating protein, is highly expressed in heart and essential for heart development according to the knowledge of Dlc1-deficient mice. To determine whether DLC1 is a susceptibility gene for sporadic CHD, we sequenced the coding region of DLC1 isoform 1 in 151 sporadic CHD patients and identified 13 non-synonymous rare variants (including 6 private variants) in the case cohort. Importantly, these rare variants (8/13) were enriched in the N-terminal region of the DLC1 isoform 1 protein. Seven of eight amino acids at the N-terminal variant positions were conserved among the primates. Among the 9 rare variants that were predicted as "damaging", five were located at the N-terminal region. Ensuing in vitro functional assays showed that three private variants (Met360Lys, Glu418Lys and Asp554Val) impaired the ability of DLC1 to inhibit cell migration or altered the subcellular location of the protein compared to wild-type DLC1 isoform 1. These data suggest that DLC1 might act as a CHD-associated gene in addition to its role as a tumor suppressor in cancer.

Gingival fibromatosis ( GINGF ) is an oral disorder characterized by enlargement of the gingiva. It occurs either as the sole phenotype or combined with other symptoms. Thus far, one GINGF locus has been mapped on chromosome 2, at 2p21, and a second possible locus has been mapped to 2p13. However, the genes responsible for this disorder have not been elucidated. We identified a four-generation Chinese GINGF family in which the disease manifests within 1 year after birth. After exclusion of the two known GINGF loci in this family, we performed a genome-wide search to map the chromosome location of the responsible gene. We identified a new locus, GINGF2, on chromosome 5q13–q22 with a maximum two-point lod score of 4.31 at D5S1721 (θ = 0.00). Haplotype analysis placed the critical region in the interval defined by D5S1491 and D5S1453. Within this region, calcium/calmodulin-dependent protein kinase IV ( CAMK4 ) is a strong candidate.

In female mammals most X-linked genes are subject to X-inactivation. However, in humans some X-linked genes escape silencing, these escapees being candidates for the phenotypic aberrations seen in polyX karyotypes. These escape genes have been reported to be under stronger purifying selection than other X-linked genes. Although it is known that escape from X-inactivation is much more common in humans than in mice, systematic assays of escape in humans have to date employed only interspecies somatic cell hybrids. Here we provide the first systematic next-generation sequencing analysis of escape in a human cell line. We analyzed RNA and genotype sequencing data obtained from B lymphocyte cell lines derived from Europeans (CEU) and Yorubans (YRI). By replicated detection of heterozygosis in the transcriptome, we identified 114 escaping genes, including 76 not previously known to be escapees. The newly described escape genes cluster on the X chromosome in the same chromosomal regions as the previously known escapees. There is an excess of escaping genes associated with mental retardation, consistent with this being a common phenotype of polyX phenotypes. We find both differences between populations and between individuals in the propensity to escape. Indeed, we provide the first evidence for there being both hyper- and hypo-escapee females in the human population, consistent with the highly variable phenotypic presentation of polyX karyotypes. Considering also prior data, we reclassify genes as being always, never, and sometimes escape genes. We fail to replicate the prior claim that genes that escape X-inactivation are under stronger purifying selection than others.

MicroRNA (miRNA)-mediated RNA silencing and nonsense-mediated decay (NMD) are two conserved RNA-level regulatory pathways. Although they are mechanically different, both can regulate target genes by RNA degradation and translational repression. Moreover, studies of individual target genes indicated that these two pathways can be involved in the same processes (e.g., development and stress responses). These facts raise an important question that whether these two systems are cooperative, interchangeable or optimal for regulation of different sorts of genes. We addressed this by comparing miRNA and NMD targets in Arabidopsis thaliana at the genome-wide scale. We find no more overlap in the genes targeted by both systems than expected by chance. Moreover, the sorts of genes or pathways regulated by these systems are categorically different on several cross-correlating fronts. While miRNA targets show enrichment in the process of development, metabolism and transcription, NMD targets are associated with stress responses but otherwise poorly annotated. Validated miRNA targets are more highly expressed, less variably expressed and slower evolving. These differences suggest that the modes of regulation need not be interchangeable. Instead, we suggest that miRNA genes are commonly dose-sensitive and require fine control of levels through weak pull-down by miRNAs. This is consistent with miRNA-regulated genes being more likely to be involved in protein–protein interactions. Many NMD-regulated genes, by contrast, have properties consistent with them being rapid emergency response “fire-fighter” genes. If true, the lack of annotation of NMD targets suggests that we poorly understand the emergencies plants face in the wild.

Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC) and nonsmall cell lung cancer (NSCLC). In this work, a computational method was proposed for identifying lung-cancer-related genes with a shortest path approach in a protein-protein interaction (PPI) network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra’s algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutationPvalue less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results.

Ichthyosis vulgaris (IV) is an inherited scaling skin disorder with a prevalence estimated at 2.29% in China. The gene responsible for this disorder has not been elucidated. To find the disease gene, we ascertained two Chinese IV families. Linkage analysis identified an IV locus on chromosome 1q22 with a maximum two-point Lod score of 2.47 at D1S1653 (theta=0.00). Haplotype analysis placed the critical region in a 7-cM interval defined by D1S1653 and D1S2675. These results provide the basis for further identifying the gene responsible for IV disorder.

Congenital cataracts cause 10–30% of all blindness in children, with one-third of cases estimated to have a genetic cause1. Lamellar cataract is the most common type of infantile cataract2. We carried out whole-genome linkage analysis of Chinese individuals with lamellar cataract, and found that the disorder is associated with inheritance of a 5.11-cM locus on chromosome 16. This locus coincides with one previously described for Marner cataract3. We screened individuals of three Chinese families for mutations in HSF4 (a gene at this locus that encodes heat-shock transcription factor 4) and discovered that in each family, a distinct missense mutation, predicted to affect the DNA-binding domain of the protein, segregates with the disorder. We also discovered an association between a missense mutation and Marner cataract in an extensive Danish family. We suggest that HSF4 is critical to lens development.

A very small proportion of people remain negative for HIV infection after repeated HIV-1 viral exposure, which is called HIV-1 resistance. Understanding the mechanism of HIV-1 resistance is important for the development of HIV-1 vaccines and Acquired Immune Deficiency Syndrome (AIDS) therapies. In this study, we analyzed the gene expression profiles of CD4+ T cells from HIV-1-resistant individuals and HIV-susceptible individuals. One hundred eighty-five discriminative HIV-1 resistance genes were identified using the Minimum Redundancy-Maximum Relevance (mRMR) and Incremental Feature Selection (IFS) methods. The virus protein target enrichment analysis of the 185 HIV-1 resistance genes suggested that the HIV-1 protein nef might play an important role in HIV-1 infection. Moreover, we identified 29 infection information exchanger genes from the 185 HIV-1 resistance genes based on a virus-host interaction network analysis. The infection information exchanger genes are located on the shortest paths between virus-targeted proteins and are important for the coordination of virus infection. These proteins may be useful targets for AIDS prevention or therapy, as intervention in these pathways could disrupt communication with virus-targeted proteins and HIV-1 infection.

Background Copy number variations (CNV) are important causal genetic variations for human disease; however, the lack of a statistical model has impeded the systematic testing of CNVs associated with disease in large-scale cohort. Methodology/Principal Findings Here, we developed a novel integrated strategy to test CNV-association in genome-wide case-control studies. We converted the single-nucleotide polymorphism (SNP) signal to copy number states using a well-trained hidden Markov model. We mapped the susceptible CNV-loci through SNP site-specific testing to cope with the physiological complexity of CNVs. We also ensured the credibility of the associated CNVs through further window-based CNV-pattern clustering. Genome-wide data with seven diseases were used to test our strategy and, in total, we identified 36 new susceptible loci that are associated with CNVs for the seven diseases: 5 with bipolar disorder, 4 with coronary artery disease, 1 with Crohn's disease, 7 with hypertension, 9 with rheumatoid arthritis, 7 with type 1 diabetes and 3 with type 2 diabetes. Fifteen of these identified loci were validated through genotype-association and physiological function from previous studies, which provide further confidence for our results. Notably, the genes associated with bipolar disorder converged in the phosphoinositide/calcium signaling, a well-known affected pathway in bipolar disorder, which further supports that CNVs have impact on bipolar disorder. Conclusions/Significance Our results demonstrated the effectiveness and robustness of our CNV-association analysis and provided an alternative avenue for discovering new associated loci of human diseases.

The Kozak motif, which is located near the translational start codon, often regulates the protein translation. Moreover, it is believed that the conserved positions -3 and +4 contribute the most. Since changes that occur in this motif have a great impact on protein yield and in some cases are associated with disease, we screened the human SNP database for all Kozak-motif-located SNPs (kSNPs) and focused on the strong-changed kSNPs (sckSNPs). Many intron-located and synonymous SNPs are reported to be associated with disease, though the mechanisms underlying these associations are poorly understood. Here, we performed haplotype analysis on sckSNP-containing genes and found that there are some sckSNPs that exist in the same haplotype blocks of reported intron-located and synonymous disease-associated SNPs, indicating that those kSNPs could be a true risk factor for disease-association by affecting the efficiency of protein expression. Our findings provide a candidate explanation for how diseases are associated with intron-located and synonymous SNPs.

Current models of X chromosome dosage compensation are usually framed by reference to how regulation in transcriptional level elevates the gene expression of the active X chromosome. This framework, however, might be oversimplified because regulation of gene expression can also act at the post-transcriptional level. Here, after a genome-wide survey, we find that autosomal genes are more likely subject to nonsense-mediated mRNA decay (NMD) than X-linked genes. Furthermore, we demonstrate that after NMD inhibition, balanced gene expression between X chromosome and autosomes is corrupted such that the global mean X/autosome gene expression ratio is decreased by 10-15%. Our results identify NMD as a post-transcription-level regulatory mechanism that contributes to the observed fine-tuning of X chromosome dosage compensation in mammals.

Comparison of gene expression variation in autosomal and X-linked genes reveals that high transcriptional noise is not a necessary consequence of haploid expression., Background Theory predicts that haploid-expressed genes should have noisier expression than comparable diploid-expressed ones with the same expression level. However, in mammals there are several classes of gene that are monoallelically expressed, including X-linked genes, imprinted genes and some other autosomal genes. Does it follow that the evolution of X chromosomes in eukaryotes comes at the cost of increased transcriptional noise in the heterogametic sex? Moreover, is escaping X-inactivation in mammalian females associated with an increase in transcriptional variation? To address these questions, we analyze gene expression variation between replicate samples of diverse mammalian cell lines in steady-state using microarray data. Results We observe that transcriptional variation of X-linked genes is no different to that of autosomal genes both before and after control for transcript abundance. By contrast, autosomal genes subject to allelic exclusion do have unusually high noise levels even allowing for their low transcript abundance. The prior theory we suggest was insufficient, at least as regards X-chromosomes, as it failed to appreciate the regulatory complexity of gene expression, not least the effects of genomic neighborhood. Conclusions These results suggest that high noise is not a necessary consequence of haploid expression and emphasize the primacy of expression level as a determinant of noise. The latter has consequences for understanding the etiology of haplo-insufficiency and the evolution of gene expression levels. Given the coupling between expression level and noise on the X-chromosome, we suggest that part of the selective advantage of dosage compensation is noise abatement of X-linked genes.

Background More and more experiments have shown that transcription and mRNA processing are not two independent events but are tightly coupled to each other. Both promoter and transcription rate were found to influence alternative splicing. More than half of human genes have alternative promoters, but it is still not clear why there are so many alternative promoters and what their biological roles are. Methodology/Principal Findings In this study, we explored whether there is a functional correlation between alternative promoters and alternative splicing by a genome-wide analysis of human and mouse genes. We constructed a large data set of genes with alternative promoter and alternative splicing annotations. By analyzing these genes, we showed that genes with alternative promoters tended to demonstrate alternative splicing compare to genes with single promoter, and, genes with more alternative promoters tend to have more alternative splicing variants. Furthermore, transcripts from different alternative promoters tended to splice differently. Conclusions/Significance Thus at the genomic level, alternative promoters are positively correlated with alternative splicing.

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

We describe here a spontaneous, autosomal recessive mutant mouse suffering from skin and hair defects, which arose in the outbred Kunming strain. By haplotype analysis and direct sequencing of PCR products, we show that this mutation is a new allele of the asebia locus with a naturally occurring mutation in the Scd1 gene (a CCC insertion at nucleotide position 835 in exon 5), which codes for stearoyl-CoA desaturase 1. This mutation introduces an extra proline residue at position 279 in the Scd1 protein. The mutant mice, originally designated km/km but now assigned the name Scd1 ab-Xyk (hereafter abbreviated as ab Xyk / ab Xyk ), have a similar gross and histological phenotype to that reported for previously characterized allelic asebia mutations ( Scd1 ab , Scd1 abJ , Scd1 ab2J , and Scd1 tm1Ntam ). Histological analysis showed they were also characterized by hypoplasic sebaceous glands and abnormal hair follicles. In a cross between Kunming- ab Xyk / ab Xyk and ABJ/Le- ab J / ab J mice, all the progeny showed the same phenotype, indicating that the two mutations were non-complementing and therefore allelic. Comparisons with the other four allelic mutants indicate that the Scd1 ab-Xyk mutation causes the mildest change in Scd1 function. This new mouse mutant is a good model not only for the study of scarring alopecias in humans, which are characterized by hypoplasic sebaceous glands, but also for studying the structure and function of the Scd1 protein.

Cytokines, having central functions in immunological and inflammatory processes, are expected to play important roles in the pathogenesis of various diseases, such as asthma. Genetic polymorphisms of those cytokine and cytokine receptor genes are the focus of genetic association studies. In an effort to identify gene(s) whose variant(s) are associated with asthma, we screened all exons and their flanking regions, as well as the promoter region (1.5kb) of eight genes, including IL4, IL13, IL12B, IL5, IL3, IL9, CD14 and IL4R. We identified 42 single nucleotide polymorphisms, 15 of which were novel. Then, we examined the genetic effects of 30 single nucleotide polymorphisms in eight cytokine and cytokine receptor genes on asthma in a Chinese asthma cohort (n = 537). Genetic association analysis of polymorphisms revealed that six polymorphisms (c.899-2C>A, c.1199A>C, c.1242G>T, c.1291T>C, c.1299T>C, c.1507T>C) in the IL4R gene, three of which resulted in an amino-acid change, showed significant association with the risk of asthma (P = 0.00023). Further analysis indicates that these six polymorphisms segregated in strong linkage disequilibrium. The genetic association of IL4R with asthma might provide valuable insights into the pathogenesis of asthma. © 2007 Wiley-Liss, Inc.

Multiple familial trichoepithelioma (MFT) and familial cylindromatosis are two clinically distinct cancer syndromes. MFT patients developed mostly trichoepithelioma in the face while cylindromatosis patients developed cylindromas predominantly (approximately 90%) on the head and neck. However, multiple familial trichoepithelioma is occasionally associated with familial cylindromatosis while cylindromatosis patients can also develop trichoepithelioma. This has led to the speculation that the 2 types of dermatoses may be caused by dysfunction of a common pathway. Previously, a candidate MTF locus has been mapped to 9p21 while disease gene for familial cylindromatosis, the CYLD gene located on 16q21-13 has been identified. Here, we show that mutations in the CYLD gene are also the genetic basis for three different Chinese families with MFT. Sequence analysis reveal a single nucleotide deletion, c.1462delA (P.Ile488fsX9) in exon 9, a nonsense mutation, c.2128C>T (p. Gln710X) in exon 17, and a missense mutation, c.2822A>T (p. Asp941Val) in exon 21 in each of the three families respectively. This provides direct evidence that the mutations in CYLD can cause two clinically distinct cancer syndromes. © 2004 Wiley-Liss, Inc.

A computational prediction of human coding RNA trans short sense-antisense pairs suggests that mRNA regulation by other coding transcripts might be a common occurrence., Background There is increasing realization that regulation of genes is done partly at the RNA level by sense-antisense binding. Studies typically concentrate on the role of non-coding RNAs in regulating coding RNA. But the majority of transcripts in a cell are likely to be coding. Is it possible that coding RNA might regulate other coding RNA by short perfect sense-antisense binding? Here we compare all well-described human protein coding mRNAs against all others to identify sites 15-25 bp long that could potentially perfectly match sense-antisense. Results From 24,968 protein coding mRNA RefSeq sequences, none failed to find at least one match in the transcriptome. By randomizations generating artificial transcripts matched for G+C content and length, we found that there are more such trans short sense-antisense pairs than expected. Several further features are consistent with functionality of some of the putative matches. First, transcripts with more potential partners have lower expression levels, and the pair density of tissue specific genes is significantly higher than that of housekeeping genes. Further, the single nucleotide polymorphism density is lower in short pairing regions than it is in flanking regions. We found no evidence that the sense-antisense pairing regions are associated with small RNAs derived from the protein coding genes. Conclusions Our results are consistent with the possibility of common short perfect sense-antisense pairing between transcripts of protein coding genes.

An analysis of human exonic splicing elements in duplicated genes reveals their important role in the generation of new gene structures., Background The origin of new genes and their contribution to functional novelty has been the subject of considerable interest. There has been much progress in understanding the mechanisms by which new genes originate. Here we examine a novel way that new gene structures could originate, namely through the evolution of new alternative splicing isoforms after gene duplication. Results We studied the divergence of exonic splicing enhancers and silencers after gene duplication and the contributions of such divergence to the generation of new splicing isoforms. We found that exonic splicing enhancers and exonic splicing silencers diverge especially fast shortly after gene duplication. About 10% and 5% of paralogous exons undergo significantly asymmetric evolution of exonic splicing enhancers and silencers, respectively. When compared to pre-duplication ancestors, we found that there is a significant overall loss of exonic splicing enhancers and the magnitude increases with duplication age. Detailed examination reveals net gains and losses of exonic splicing enhancers and silencers in different copies and paralog clusters after gene duplication. Furthermore, we found that exonic splicing enhancer and silencer changes are mainly caused by synonymous mutations, though nonsynonymous changes also contribute. Finally, we found that exonic splicing enhancer and silencer divergence results in exon splicing state transitions (from constitutive to alternative or vice versa), and that the proportion of paralogous exon pairs with different splicing states also increases over time, consistent with previous predictions. Conclusions Our results suggest that exonic splicing enhancer and silencer changes after gene duplication have important roles in alternative splicing divergence and that these changes contribute to the generation of new gene structures.

Background Nonsense-mediated decay is a mechanism that degrades mRNAs with a premature termination codon. That some exons have premature termination codons at fixation is paradoxical: why make a transcript if it is only to be destroyed? One model supposes that splicing is inherently noisy and spurious transcripts are common. The evolution of a premature termination codon in a regularly made unwanted transcript can be a means to prevent costly translation. Alternatively, nonsense-mediated decay can be regulated under certain conditions so the presence of a premature termination codon can be a means to up-regulate transcripts needed when nonsense-mediated decay is suppressed. Results To resolve this issue we examined the properties of putative nonsense-mediated decay targets in humans and mice. We started with a well-annotated set of protein coding genes and found that 2 to 4% of genes are probably subject to nonsense-mediated decay, and that the premature termination codon reflects neither rare mutations nor sequencing artefacts. Several lines of evidence suggested that the noisy splicing model has considerable relevance: 1) exons that are uniquely found in nonsense-mediated decay transcripts (nonsense-mediated decay-specific exons) tend to be newly created; 2) have low-inclusion level; 3) tend not to be a multiple of three long; 4) belong to genes with multiple splice isoforms more often than expected; and 5) these genes are not obviously enriched for any functional class nor conserved as nonsense-mediated decay candidates in other species. However, nonsense-mediated decay-specific exons for which distant orthologous exons can be found tend to have been under purifying selection, consistent with the regulation model. Conclusion We conclude that for recently evolved exons the noisy splicing model is the better explanation of their properties, while for ancient exons the nonsense-mediated decay regulated gene expression is a viable explanation.