Biology subjects

Zhu, Z.

Publications and source records attributed to Zhu, Z..

334 records · Page 19Linked to original sources

bioRxiv2017

Extracting active modules from multilayer PPI network: a continuous optimization approach

Active modules identification has received much attention due to its ability to reveal regulatory and signaling mechanisms of a given cellular response. Most existing algorithms identify active modules by extracting connected nodes with high activity scores from a graph. These algorithms do not consider other topological properties such as community structure, which may correspond to functional units. In this paper, we propose an active module identification algorithm based on a novel objective function, which considers both and network topology and nodes activity. This objective is formulated as a constrained quadratic programming problem, which is convex and can be solved by iterative methods. Furthermore, the framework is extended to the multilayer dynamic PPI networks. Empirical results on the single layer and multilayer PPI networks show the effectiveness of proposed algorithms.\n\nAvailability: The package and code for reproducing all results and figures are available at https://github.com/fairmiracle/ModuleExtraction.

bioinformatics↗

bioRxiv2017

Heritability of regional brain volumes in large-scale neuroimaging and genetic studies

Brain genetics is an active research area. The degree to which genetic variants impact variations in brain structure and function remains largely unknown. We examined the heritability of regional brain volumes (p ~ 100) captured by single-nucleotide polymorphisms (SNPs) in UK Biobank (n ~ 9000). We found that regional brain volumes are highly heritable in this study population. We observed omni-genic impact across the genome as well as enrichment of SNPs in active chromatin regions. Principal components derived from regional volume data are also highly heritable, but the amount of variance in brain volume explained by the component did not seem to be related to its heritability. Heritability estimates vary substantially across large-scale functional networks and brain regions. The variation in heritability across regions was not related to measurement reliability. Heritability estimates exhibit a symmetric pattern across left and right hemispheres and are consistent in females and males. Our main findings in UK Biobank are consistent with those in Alzheimers Disease Neuroimaging Initiative (n ~ 1100), Philadelphia Neurodevelopmental Cohort (n ~ 600), and Pediatric Imaging, Neurocognition, and Genetics (n ~ 500) datasets, with more stable estimates in UK Biobank.

genetics↗

bioRxiv2017

Causal associations between risk factors and common diseases inferred from GWAS summary data

Health risk factors such as body mass index (BMI), serum cholesterol and blood pressure are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. Genetic methods are useful to infer causality because genetic variants are present from birth and therefore unlikely to be confounded with environmental factors. We develop and apply a method (GSMR) that performs a multi-SNP Mendelian Randomization analysis using summary-level data from large genome-wide association studies (sample sizes of up to 405,072) to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height and years of schooling (EduYears) with a range of common diseases. We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimers disease, and bidirectional associations with opposite effects (e.g. higher BMI increases the risk of T2D but the effect T2D of BMI is negative). HDL-cholesterol has a significant risk effect on age-related macular degeneration, and the effect size remains significant accounting for the other risk factors. Our study develops powerful tools to integrate summary data from large studies to infer causality, and provides important candidates to be prioritized for further studies in medical research and for drug discovery.

genetics↗

bioRxiv2017

Shared Genetic Architecture Of Asthma With Allergic Diseases: A Genome-wide Cross Trait Analysis Of 112,000 Individuals From UK Biobank

Clinical and epidemiological data suggest that asthma and allergic diseases are associated. And may share a common genetic etiology. We analyzed genome-wide single-nucleotide polymorphism (SNP) data for asthma and allergic diseases in 35,783 cases and 76,768 controls of European ancestry from the UK Biobank. Two publicly available independent genome wide association studies (GWAS) were used for replication. We have found a strong genome-wide genetic correlation between asthma and allergic diseases (rg = 0.75, P = 6.84x10-62). Cross trait analysis identified 38 genome-wide significant loci, including novel loci such as D2HGDH and GAL2ST2. Computational analysis showed that shared genetic loci are enriched in immune/inflammatory systems and tissues with epithelium cells. Our work identifies common genetic architectures shared between asthma and allergy and will help to advance our understanding of the molecular mechanisms underlying co-morbid asthma and allergic diseases.

genetics↗

bioRxiv2017

Establishment In Culture Of Expanded Potential Stem Cells

Mouse embryonic stem cells are derived from in vitro explantation of blastocyst epiblasts1,2 and contribute to both the somatic lineage and germline when returned to the blastocyst3 but are normally excluded from the trophoblast lineage and primitive endoderm4-6. Here, we report that cultures of expanded potential stem cells (EPSCs) can be established from individual blastomeres, by direct conversion of mouse embryonic stem cells (ESCs) and by genetically reprogramming somatic cells. Remarkably, a single EPSC contributes to the embryo proper and placenta trophoblasts in chimeras. Critically, culturing EPSCs in a trophoblast stem cell (TSC) culture condition permits direct establishment of TSC lines without genetic modification. Molecular analyses including single cell RNA-seq reveal that EPSCs share cardinal pluripotency features with ESCs but have an enriched blastomere transcriptomic signature and a dynamic DNA methylome. These proof-of-concept results open up the possibility of establishing cultures of similar stem cells in other mammalian species.

developmental biology↗

bioRxiv2017

Secretogranin-II Plays A Critical Role In Zebrafish Neurovascular Modeling

Summary statementNeurons expressing sgIIb align with central arteries in hindbrain. We show that sgIIb is critical for neurovascular modeling the larval zebrafish mediated by MAPK and PI3K/AKT signaling in vivo.\n\nAbstractSecretoneurin (SN) is a neuropeptide derived from specific proteolytic processing of the precursor secretogranin II (SgII). In zebrafish and other teleosts there are 2 paralogs we previously named sgIIa and sgIIb. Our results showed that neurons expressing sgIIb were aligned with central arteries in hindbrain, demonstrating a close neurovascular association. Both sgIIb-/- and sgIIa-/- /sgIIb-/- mutant embryos were defective in hindbrain central artery development, while artery development in sgIIa-/- mutant embryos was not affected. Hindbrain arterial and venous network identities were not affected in sgIIb-/- mutant embryos, and the mRNA levels of Notch and VEGF pathway-related genes were not altered. However, the activation of MAPK and PI3K/AKT pathways were inhibited in sgIIb-/- mutant embryos. Injection of a synthetic SNb mRNA or delivery of the protein kinase activator N-arachidonoyl-L-serine could partially rescue the central artery developmental defects in the sgIIb mutants. This study provides the first in vivo evidence that sgIIb plays a critical role in neurovascular modeling the hindbrain.

developmental biology↗

bioRxiv2017

Accumulation of Minor Alleles of Common SNPs in Schizophrenia

Schizophrenia is a common neuropsychiatric disorder with a lifetime risk of 1%. A number of large scale genome wide association studies have identified numerous individual risk single nucleotide polymorphisms (SNPs) whose precise roles in schizophrenia remain unknown. Accumulation of many of these risk alleles has been found to be a more important risk factor. Consistently, recent studies showed a role for enrichment of minor alleles (MAs) in complex diseases. Here we studied the role of MAs in general in schizophrenia using public datasets. Relative to matched controls, schizophrenia cases showed higher minor allele content (MAC), especially for the sporadic cases. By linkage analysis, we identified 82 419 SNPs that could be used to predict 2.2% schizophrenia cases with 100% certainty. Pathway enrichment analysis of these SNPs identified 17 pathways, 15 of which are known to be linked with Schizophrenia with the remaining 2 associated with other mental disorders. These results suggest a role for a collective effect of MAs in schizophrenia and provide a method to genetically screen for schizophrenia.\n\nAbbreviations

pathology↗

bioRxiv2017

Collective effects of common SNPs and improved risk prediction in lung cancer

Lung cancer is the leading cause of cancer deaths in both men and women in the US. While most sporadic lung cancer cases are related to environmental factors such as smoking, genetic susceptibility may also play an important role and a number of lung cancer associated single nucleotide polymorphisms (SNPs) have been identified although many remain to be found. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have been linked with quantitative variations of complex traits and diseases. Here we studied MAC in lung cancer using previously published SNP datasets and found higher MAC in cases relative to matched controls. A set of 25883 SNPs with MA (MAF < 0.5) more common in cases (P < 0.1) was found to have the best predictive accuracy. A weighted risk score calculated by using this set can predict 2.6% of lung cancer cases (100% specificity). These results identify a novel genetic risk element or higher MAC in lung cancer susceptibility and provide a useful genetic method to identify a small fraction of lung cancer cases.

cancer biology↗

bioRxiv2017

Rapid Automated Large Structural Variation Detection in a Diploid Genome by NanoChannel Based Next-Generation Mapping

The human genome is diploid with one haploid genome inherited from the maternal and one from the paternal lineage. Within each haploid genome, large structural variants such as deletions, duplications, inversions, and translocations are extensively present and many are known to affect biological functions and cause disease. The ultimate goal is to resolve these large complex structural variants (SVs) and place them in the correct haploid genome with correct location, orientation, and copy number. Current methods such as karyotyping, chromosomal microarray (CMA), PCR-based tests, and next-generation sequencing fail to reach this goal either due to limited resolution, low throughput, or short read length.\n\nBionano Genomics next-generation mapping (NGM) offers a high-throughput, genome-wide method able to detect SVs of one kilobase pairs (kbp) and up. By imaging extremely long genomic molecules of up to megabases in size, the structure and copy number of complex regions of the g ...

genomics↗

bioRxiv2017

Modern human origins: multiregional evolution of autosomes and East Asia origin of Y and mtDNA

The neutral theory has been used as a null model for interpreting nature and produced the Recent Out of Africa model of anatomically modern humans. Recent studies, however, have established that genetic diversities are mostly at maximum saturation levels maintained by selection, therefore challenging the explanatory power of the neutral theory and rendering the present molecular model of human origins untenable. Using improved methods and public data, we have revisited human evolution and found sharing of genetic variations among racial groups to be largely a result of parallel mutations rather than recent common ancestry and admixture as commonly assumed. We derived an age of 1.86-1.92 million years for the first split in modern human populations based on autosomal diversity data. We found evidence of modern Y and mtDNA originating in East Asia and dispersing via hybridization with archaic humans. Analyses of autosomes, Y and mtDNA all suggest that Denisovan and Neanderthal were archaic Africans with Eurasian admixtures and ancestors of South Asia Negritos and Aboriginal Australians. Verifying our model, we found more ancestry of Southern Chinese from Hunan in Africans relative to other East Asian groups examined. These results suggest multiregional evolution of autosomes and replacements of archaic Y and mtDNA by modern ones originating in East Asia, thereby leading to a coherent account of modern human origins.

evolutionary biology↗