Four-Generation Pedigree of Monozygotic Female Twins Reveals Genetic Factors in Twinning Process by Whole-Genome Sequencing.

Familial monozygotic (MZ) twinning reports are rare around the world, and we report a four-generation pedigree with seven recorded pairs of female MZ twins. Whole-genome sequencing of seven family members was performed to explore the featured genetic factors in MZ twins. For variations specific to MZ twins, five novel variants were observed in the X chromosome. These candidates were used to explain the seemingly X-linked dominant inheritance pattern, and only one variant was exonic, located at the 5'UTR region of ZCCHC12 (chrX: 117958597, G > A). Besides, consistent mitochondrial DNA composition in the maternal linage precluded roles of mitochondria for this trait. In this pedigree, autosomes also contain diverse variations specific to MZ twins. Pathway analysis revealed a significant enrichment of genes carrying novel SNVs in the epithelial adherens junction-signaling pathway (p = .011), contributed by FGFR1, TUBB6, and MYH7B. Meanwhile, TBC1D22A, TRIOBP, and TUBB6, also carrying similar SNVs, were involved in the GTPase family-mediated signal pathway. Furthermore, gene-set enrichment analysis for 533 genes covered by copy number variations specific to MZ twins illustrated that the tight junction-signaling pathway was significantly enriched (p < .001). Therefore, the novel changes in the X chromosome and the provided candidate variants across autosomes may be responsible for MZ twinning, giving clues to increase our understanding about the underlying mechanism.

Integrating epigenetic marks for identification of transcriptionally active miRNAs.

MicroRNAs have been identified as important regulators involved in biological processes and human diseases. We proposed a computational approach to systematic identification of active promoters of miRNAs by active models using epigenetic characteristics at active promoters of protein-coding genes together with a genomic context-based filtering step in nine human cell types, which were validated to exhibit greater conservation, more overlap with CAGE-identified TSSs, more conserved TFBSs and higher transcription factor binding signal intensities. Furthermore, expression analysis showed discordance between transcriptional activation of miRNAs and expression of their precursor and mature forms, indicating that precursor and mature miRNA expression is insufficient to account for transcriptional activation of miRNAs. Compared to other methods, our approach identified higher percentages of active miRNAs with CAGE-detected TSS activity and primary transcript expression, further supporting the validity of our approach, which will be valuable to understand the biological roles of miRNAs in specific cell contexts.

Prioritizing cancer-related key miRNA-target interactions by integrative genomics.

Accumulating evidence indicates that microRNAs (miRNAs) can function as oncogenes or tumor suppressor genes by controlling few key targets, which in turn contribute to the pathogenesis of cancer. The identification of cancer-related key miRNA-target interactions remains a challenge. We performed a systematic analysis of known cancer-related key interactions manually curated from published papers based on different aspects including sequence, expression and function. Known cancer-related key interactions show more miRNA binding sites (especially for 8mer binding sites), more reliable binding of miRNA to the target region, higher expression associations and broader functional coverage when compared to non-disease-related interactions. Through integrating these sequence, expression and function features, we proposed a bioinformatics approach termed PCmtI to prioritize cancer-related key interactions. Ten-fold cross-validation of our approach revealed that it can achieve an area under the receiver operating characteristic curve of 93.9%. Subsequent leave-one-miRNA-out cross-validation also demonstrated the performance of our approach. Using miR-155 as a case, we found that the top ranked interactions can account for most functions of miR-155. In addition, we further demonstrated the power of our approach by 23 recently identified cancer-related key interactions. The approach described here offers a new way for the discovery of novel cancer-related key miRNA-target interactions.

Differential expression pattern-based prioritization of candidate genes through integrating disease-specific expression data.

Expression data can reveal subtle transcriptional changes that mediate the clinical phenotype of the disease resulting from interaction between genetic and environmental factors, which offers us a new perspective to prioritize candidate genes. Here, we proposed a novel differential expression pattern (DEP)-based approach integrating numerous disease-specific expression data sets for prioritizing candidate genes. Using breast cancer as a case study, we validated the efficiency of our approach through integrating 12 breast cancer-related expression data sets based on the leave-one-out cross-validation. Particularly, prioritization based on subtype-specific expression data sets could generate significantly higher performance. The performance could be continually improved with the increasing expression data sets regardless of platform heterogeneity. We further validated the robustness of this approach by application to prostate cancer. Additionally, our approach showed higher performance in comparison with other expression-based approaches and better capability of identification of less well-studied disease genes in comparison with other integration-based approaches.

SUV39H1 regulates the progression of MLL-AF9-induced acute myeloid leukemia.

Epigenetic regulations play crucial roles in leukemogenesis and leukemia progression. SUV39H1 is the dominant H3K9 methyltransferase in the hematopoietic system, and its expression declines with aging. However, the role of SUV39H1 via its-mediated repressive modification H3K9me3 in leukemogenesis/leukemia progression remains to be explored. We found that SUV39H1 was down-regulated in a variety of leukemias, including MLL-r AML, as compared with normal individuals. Decreased levels of Suv39h1 expression and genomic H3K9me3 occupancy were observed in LSCs from MLL-r-induced AML mouse models in comparison with that of hematopoietic stem/progenitor cells. Suv39h1 overexpression increased leukemia latency and decreased the frequency of LSCs in MLL-r AML mouse models, while Suv39h1 knockdown accelerated disease progression with increased number of LSCs. Increased Suv39h1 expression led to the inactivation of Hoxb13 and Six1, as well as reversion of Hoxa9/Meis1 downstream target genes, which in turn decelerated leukemia progression. Interestingly, Hoxb13 expression is up-regulated in MLL-AF9-induced AML cells, while knockdown of Hoxb13 in MLL-AF9 leukemic cells significantly prolonged the survival of leukemic mice with reduced LSC frequencies. Our data revealed that SUV39H1 functions as a tumor suppressor in MLL-AF9-induced AML progression. These findings provide the direct link of SUV39H1 to AML development and progression.

The fusion landscape of hepatocellular carcinoma.

Most cases of hepatocellular carcinoma (HCC) are already advanced at the time of diagnosis, which limits treatment options. Challenges in early-stage diagnosis may be due to the genetic complexity of HCC. Gene fusion plays a critical function in tumorigenesis and cancer progression in multiple cancers, yet the identities of fusion genes as potential diagnostic markers in HCC have not been investigated. Here, we employed STAR-Fusion and identified 43 recurrent fusion events in our own and four public RNA-seq datasets. We identified 2354 different gene fusions in two hepatitis B virus (HBV)-HCC patients. Validation analysis against the four RNA-seq datasets revealed that only 1.8% (43/2354) were recurrent fusions. Comparison with the four fusion databases demonstrated that 19 recurrent fusions were not previously annotated to diseases and three were annotated as disease-related fusion events. Finally, we validated six of the novel fusion events, including RP11-476K15.1-CTD-2015H3.2, by RT-PCR and Sanger sequencing of 14 pairs of HBV-related HCC samples. In summary, our study provides new insights into gene fusions in HCC and may contribute to the development of anti-HCC therapy.

[Research on the protein C-activating property and influencial factors of protein C activator isolated from the venom of Agkistrodon halys].

OBJECTIVE: To investigate the protein C-activating property and experimental conditions that may affect the activities of protein C activator (PCA-SV). METHODS: PCA-SV's functional characteristic, possible anticoagulant and amidase activities were measured by method of APTT and that of specific chromogenic substrate respectively in various experimental conditions. RESULTS: PCA-SV can specifically act on protein C. The pH-optimum and temperature-optimum for the action of PCA-SV were 6.0 - 7.0 and 37 - 40 degrees C respectively. The anticoagulants (heparin, sodium citrate) had no effect on the activities. CONCLUSION: PCA-SV is a new protein C-activating reagent that has high potency and specificity.

[The pharmacological studies of yifuzhixue pill].

OBJECTIVE: To investigate the pharmacological effect of Yifuzhixue Pill (YFZXP). METHODS: PPT, RT, PT, platelet counts and platelet adhesive rate were examined after administration of YFZXP. In other hand, the functions of isolated rabbit's uteri were also examined to determine whether they were responsible to the administration of YFZXP. RESULTS: YFZXP could enhance the intrinsic blood coagulating function and stimulate the contraction of smooth muscles of uterus including increasing the rhythms and strength. The stimulation effect of YFZXP on smooth muscles of uterus exhibited no selections between the uteri treated with or without estradiol. It was speculated that the increased intrinsic blood coagulating and uterus' contraction induced by YFZXP were contributed to its anti-bleeding effect in uterus.

[Effect of fractions isolated from Naja naja atra venom on antioxidation in animals].

OBJECTIVE: To study the antioxidation of fraction F and H isolated from Naja naja atra venom on homogenate and RBC autoxidation. And to explore the effect of two fractions on the activities of antioxidation enzymes in mice. METHOD: Samples of tissues homogenates and RBC suspension were pretreated with fraction F/H, and then their generation of malondialdehyde(MDA) was examined. The effects of fraction F/H on O2-* produced by pyrogallol autoxidation and *OH produced by Cu2+ -VitC were checked. After being administrated i.p. with fraction F/H for 15 days, superoxide dismutase and hydroperoxidase in mice were measured for their activities. RESULT: Fraction F/H inhibited RBC autohemolysis and the generation of MDA decreased. The production of lipid peroxides in normal brain, liver and heart homogenate of rat and the elevation of lipid peroxides induced by cysteine and FeSO4 in homogenate were inhibited by addition of fraction F/H. The O2-* produced by autoxidation of pyrogallol and the *OH produced by Cu2+ -VitC system could be scavenged by fraction F/H (the potency of scavenging oxygen free radical is that fraction H > fraction F). Fraction F/H all increased the activities of several antioxidation enzymes in mice to different extents. CONCLUSION: Fraction F/H have the effect of antilipid peroxidation,may scavenge active oxygen free radical and increase the activity of SOD.

Identifying dysfunctional miRNA-mRNA regulatory modules by inverse activation, cofunction, and high interconnection of target genes: a case study of glioblastoma.

BACKGROUND: Accumulating evidence demonstrates that complex diseases may arise from cooperative effects of multiple dysfunctional miRNAs. Thus, identifying abnormal functions cooperatively regulated by multiple miRNAs is useful for understanding the pathogenesis of complex diseases. METHODS: In this study, we proposed a multistep method to identify dysfunctional miRNA-mRNA regulatory modules (dMiMRMs) in a specific disease, in which a group of miRNAs cooperatively regulate a group of target genes involved in a specific function. We identified dysfunctional miRNAs, which were differentially expressed and inversely regulated most of their target genes, by integrating paired miRNA and mRNA expression profiles and miRNA target information. Then, we identified cooperative functional units, in each of which a pair of miRNAs cooperatively repressed function-enriched and highly interconnected target genes. Finally, the cooperative functional units were assembled into dMiMRMs. RESULTS: We applied our method to glioblastoma (GBM) and identified GBM-associated dMiMRMs at the population, subtype, and individual levels. We identified 5 common dMiMRMs using all GBM samples, 3 of which were associated with the prognosis in patients with GBM and were better predictors of prognosis than were miRNAs or mRNAs alone. By applying our approach to GBM subtypes, we found consistent dMiMRMs across GBM subtypes, and some subtype-specific dMiMRMs were observed. Furthermore, personalized dMiMRMs were identified, suggesting significant individual differences in different patients with GBM. CONCLUSIONS: Our method provides the capability to identify miRNA-mediated dysfunctional mechanisms underlying complex diseases.

Discovering dysfunction of multiple microRNAs cooperation in disease by a conserved microRNA co-expression network.

MicroRNAs, a new class of key regulators of gene expression, have been shown to be involved in diverse biological processes and linked to many human diseases. To elucidate miRNA function from a global perspective, we constructed a conserved miRNA co-expression network by integrating multiple human and mouse miRNA expression data. We found that these conserved co-expressed miRNA pairs tend to reside in close genomic proximity, belong to common families, share common transcription factors, and regulate common biological processes by targeting common components of those processes based on miRNA targets and miRNA knockout/transfection expression data, suggesting their strong functional associations. We also identified several co-expressed miRNA sub-networks. Our analysis reveals that many miRNAs in the same sub-network are associated with the same diseases. By mapping known disease miRNAs to the network, we identified three cancer-related miRNA sub-networks. Functional analyses based on targets and miRNA knockout/transfection data consistently show that these sub-networks are significantly involved in cancer-related biological processes, such as apoptosis and cell cycle. Our results imply that multiple co-expressed miRNAs can cooperatively regulate a given biological process by targeting common components of that process, and the pathogenesis of disease may be associated with the abnormality of multiple functionally cooperative miRNAs rather than individual miRNAs. In addition, many of these co-expression relationships provide strong evidence for the involvement of new miRNAs in important biological processes, such as apoptosis, differentiation and cell cycle, indicating their potential disease links.

Systematic identification of common functional modules related to heart failure with different etiologies.

The development of heart failure (HF) is a complex process that can be initiated by multiple etiologies. Identifying common functional modules associated with HF is a challenging task. Here, we developed a systems method to identify these common functional modules by integrating multiple expression profiles, protein interactions from four species, gene function annotations, and text information. We identified 1439 consistently differentially expressed genes (CDEGs) across HF with different etiologies by applying three meta-analysis methods to multiple HF-related expression profiles. Using a weighted human interaction network constructed by combining interaction data from multiple species, we extracted 60 candidate CDEG modules. We further evaluated the functional relevance of each module by using expression, interaction network, functional annotations, and text information together. Finally, five functional modules with significant biological relevance were identified. We found that almost half of the genes in these modules are hubs in the weighted network, and that these modules can accurately classify HF patients from healthy subjects. We also identified many significantly enriched biological processes that contribute to the pathophysiology of HF, including two new ones, RNA splicing and vesicle-mediated protein transport. In summary, we proposed a novel framework to analyze common functional modules related to HF with different etiologies. Our findings provide important insights into the complex mechanism of HF. Further biological experimentations should be required to validate these novel biological processes.