Biology subjects

Han, R.

Publications and source records attributed to Han, R..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

A hybrid PDE-ABM model for viral dynamics with application to SARS-CoV-2 and influenza

We propose a hybrid partial differential equation - agent-based (PDE-ABM) model to describe the spatio-temporal viral dynamics in a cell population. The virus concentration is considered as a continuous variable and virus movement is modelled by diffusion, while changes in the states of cells (i.e. healthy, infected, dead) are represented by a stochastic agent-based model. The two subsystems are intertwined: the probability of an agent getting infected in the ABM depends on the local viral concentration, and the source term of viral production in the PDE is determined by the cells that are infected. We develop a computational tool that allows us to study the hybrid system and the generated spatial patterns in detail. We systematically compare the outputs with a classical ODE system of viral dynamics, and find that the ODE model is a good approximation only if the diffusion coefficient is large. We demonstrate that the model is able to predict SARS-CoV-2 infection dynamics, and replicate the output of in vitro experiments. Applying the model to influenza as well, we can gain insight into why the outcomes of these two infections are different.

systems biology↗

bioRxiv2021

Multiple nucleotide polymorphism DNA markers for the accurate evaluation of genetic variations

DNA markers are an essential tool for the detection and evaluation of genetic variations, a central theme in genetics and biology. Effective markers must be highly reproducible, polymorphic, accurate and efficient to profile. We developed multiple dispersed nucleotide polymorphism (MNP) DNA marker and an efficient MNP genotyping method called MNP-Seq. The MNP marker was 17.48% more polymorphic than the highly polymorphic marker of microsatellites on a collection of hybrid rice plants. When applied to genotype more than 80,000 individual MNP markers of diploid rice and polyploidy hybrid cotton varieties which were notoriously difficult to genotype accurately, MNP-Seq finished in two days and achieved accuracies of 99.999% and 99.988%, respectively. We adopted MNP-Seq to reveal the ubiquitous, albeit subtle and neglected, genetic heterogeneities in homonyms of Nipponbare rice, a popular model organism for plant biology. This result raised a question on the consistency of the published results using the model plant. We also used MNP-Seq to accurately and efficiently determine the identities of plant varieties, a key but difficult problem for the protection of plant intellectual property rights. While being applied to plants in the current study, the MNP marker and MNP-Seq are general and readily applicable to similar problems in animals and micro-organisms.

molecular biology↗

bioRxiv2021

Hidden Transcriptome Signature in Autism Spectrum Disorder (ASD) is Attributed to the Interpatient Heterogeneity

Recent studies of ASD have mostly supported the existence of heterogeneity and genomic variation in ASD which have hindered and restrained development of any effective and targetable treatment for a long time. As numerous studies have shown, both genetic and phenotypic heterogeneity is presented in ASD, however, heterogeneity in genetic level is not fully understood which is the key challenges for the further research. Even dozens of ASD susceptibility genes have been discovered which is commonly accounting for 10 to 20 percent of ASD cases, the internal complex combination of mutated genes that determine the epigenetic factors of ASD is still not comprehensively recognized by the recent studies. First by discouraging the traditional method that have been applied in most of the current research of diseases, this research will then focus on dissecting the heterogeneity of polygenic diseases and analyzing with an unconventional approach for acquiring Differently Expressed Genes (DEGs) in Guptas Dataset that provided transcriptome of frontal cortex of ASD patients. Divide categories by using unsupervised learning strategy, the results yielded by analyzing within clusters of ASD have supported the feasibility of the attempts to use heterogeneity to reveal its underlying mechanism. This study puts forward the inference that the heterogeneity of polygenic diseases will obscure the molecular signals related to the disease, and at the same time attempts to use heterogeneity to reveal the underlying mechanism.

bioinformatics↗

bioRxiv2020

Genomic profiling of cancerous patients identifies FPR2 as an alternative immunotherapeutic target in glioblastoma multiforme

BackgroundGlioblastoma multiforme (GBM) is a type of high-grade brain tumor known for its proliferative, invasive property, and low survival rate. Recently, with the advancement in therapeutics for tumors such as targeted therapy, individual cancer-specific biomarkers could be recognized as targets for curative purposes. This study identified six differentially expressed genes that have shown significant implications in clinical field, including FPR2, VEGFA, SERPINA1, SOX2, PBK, and ITGB3. FPR2 was of the same protein family with FPR1, and the latter has been repeatedly reported to promote motility and invasiveness of multiple tumor forms. MethodsThe gene expression profiling of 40 GBM samples and five normal samples from the TCGA database were comprehensively analyzed. The differentially expressed genes (DEGs) were identified using R package and screened by enrichment analysis and examination of protein-protein interaction networks, in order to further explore the functions of DEGs with the highest association with clinical traits and to find hub genes. A qRT-PCR and Western blots were conducted to verify the results of this study. ResultsOur investigation showed that FPR2, VEGFA, SERPINA1, SOX2, PBK, and ITGB3 were significantly up-regulated in GBM primary tumor compared to the control group. Functional enrichment analysis of the DEGs demonstrated that biological functions related to immune systems, cell division and cell cycle were significantly increased, which were closely related to tumor progression and development. Downstream construction of PPI network analysis indicated that FPR2 was a hub gene involved in high level of interaction with CR3 and VEGFA, which played a key role in inflammatory pathways and cellular dysfunction. ConclusionFPR2, VEGFA, SERPINA1, SOX2, PBK, and ITGB3 were significantly over-expressed in primary tumor samples of GBM patients and were involved in cellular functions and pathways contributing to tumor progression. Out of these six pivotal genes, we intensively focused on FPR2, and our analysis and experimental data both suggested its efficacy as a potential biomarker, serving as an alternative immunotherapeutic target for glioblastoma multiforme.

bioinformatics↗

bioRxiv2020

Structural basis for the dimerization-dependent CRISPR-Cas12f nuclease

Cas12f, also known as Cas14, is an exceptionally small type V-F CRISPR-Cas nuclease that is roughly half the size of comparable nucleases of this type. To reveal the mechanisms underlying substrate recognition and cleavage, we determined the cryo-EM structures of the Cas12f-sgRNA-target DNA and Cas12f-sgRNA complexes at 3.1 [A] and 3.9 [A], respectively. An asymmetric Cas12f dimer is bound to one sgRNA for recognition and cleavage of dsDNA substrate with a T-rich PAM sequence. Despite its dimerization, Cas12f adopts a conserved activation mechanism among the type V nucleases which requires coordinated conformational changes induced by the formation of the crRNA-target DNA heteroduplex, including the close-to-open transition in the lid motif of the RuvC domain. Only one RuvC domain in the Cas12f dimer is activated by substrate recognition, and the substrate bound to the activated RuvC domain is captured in the structure. Structure-assisted truncated sgRNA, which is less than half the length of the original sgRNA, is still active for target DNA cleavage. Our results expand our understanding of the diverse type V CRISPR-Cas nucleases and facilitate potential genome editing applications using the miniature Cas12f.

biophysics↗

bioRxiv2020

Drone phenotyping and machine learning enable discovery of loci regulating daily floral opening in lettuce

Flower opening and closure are traits of reproductive importance in all angiosperms because they determine the success of self- and cross-pollination. The temporal nature of this phenotype rendered it a difficult target for genetic studies. Cultivated and wild lettuce, Lactuca spp., have composite inflorescences comprised of multiple florets that open only once. Different accessions were observed to flower at different times of day. An F6 recombinant inbred line population (RIL) had been derived from accessions of L. serriola x L. sativa that originated from different environments and differed markedly for daily floral opening time. This population was used to map the genetic determinants of this trait; the floral opening time of 236 RILs was scored over a seven-hour period using time-course image series obtained by drone-based remote phenotyping on two occasions, one week apart. Floral pixels were identified from the images using a support vector machine (SVM) machine learning algorithm with an accuracy above 99%. A Bayesian inference method was developed to extract the peak floral opening time for individual genotypes from the time-stamped image data. Two independent QTLs, qDFO2.1 (Daily Floral Opening 2.1) and qDFO8.1, were discovered. Together, they explained more than 30% of the phenotypic variation in floral opening time. Candidate genes with non-synonymous polymorphisms in coding sequences were identified within the QTLs. This study demonstrates the power of combining remote imaging, machine learning, Bayesian statistics, and genome-wide marker data for studying the genetics of recalcitrant phenotypes such as floral opening time. One sentence summaryMachine learning and Bayesian analyses of drone-mediated remote phenotyping data revealed two genetic loci regulating differential daily flowering time in lettuce (Lactuca spp.).

genetics↗

bioRxiv2020

Efficient precise in vivo base editing in adult dystrophic mice

ABSTRACTBackground Recent advances in the base editing technology have created an exciting opportunity to precisely correct disease-causing mutations. However, the large size of base editors and their inherited off-target activities pose challenges for in vivo base editing. Moreover, the requirement of a protospacer adjacent motif (PAM) sequence within a suitable window near the mutation site further limits the targeting feasibility. In this work, we rationally improved the adenine base editor (ABE) to overcome these challenges and demonstrated the exceptionally high efficiency to precisely edit the Duchenne muscular dystrophy (DMD) mutation in adult mice.Methods We employed a fluorescence reporter assay to assess the feasibility of ABE to correct the dystrophin mutation in mdx4cv mice. The intein protein trans-splicing (PTS) was used to split the oversized ABE into two halves for efficient packaging into adeno-associated virus 9 (AAV9). The ABE with broadened PAM recognition (ABE-NG) was rationally re-designed for improved off-target RNA editing activity and on-target DNA editing efficiency. The mdx4cv mice at the 5 weeks of age receiving intramuscular or intravenous injections of AAV9 carrying the improved ABE-NG were analyzed at 10 weeks or 10 months of age. The editing outcomes were analyzed by Sanger and deep sequencing of the amplicons, immunofluorescence staining, Western blot and contractile function measurements. The off-target activities, host immune response and long-term toxicity were analyzed by deep sequencing, ELISA and serological assays, respectively.Results We showed efficient in vitro base correction of the dystrophin mutation carried in mdx4cv mice using ABE-NG. The super-fast intein-splits of ABE-NG enabled the expression of full-length ABE-NG and efficient AAV9 packaging. We rationally improved ABE-NG with eliminated off-target RNA editing activity and minimal PAM requirement, and packaged into AAV9 (AAV9-iNG). Intramuscular and intravenous administration of AAV9-iNG resulted in dystrophin restoration and functional improvement. At 10 months after AAV9-iNG treatment, a near complete rescue of dystrophin was measured in mdx4cv mouse hearts. The off-target activities remained low and no obvious toxicity was detected.Conclusions This study highlights the promise of permanent base editing using iABE-NG for the treatment of monogenic diseases, in particular, the genetic cardiomyopathies.Competing Interest StatementThe authors have submitted a patent application based on the results reported in this paper.View Full Text

bioengineering↗

bioRxiv2020

Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders

BackgroundWith the reduce of cost and incomparable advantages, WGS is likely to change the way of clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated, especially for CNV detection. MethodsAll the samples underwent WGS using MGISEQ-2000. The performance of NA12878, YH cell line, and the Chinese trios were measured for sensitivity, PPV, depth and breadth of coverage. We also compared the performance of WES and WGS using NA12878. The sensitivity and PPV were tested using family-based trio design in the Chinese trios. We also developed a systematic WGS pipeline for the analysis of 8 clinical cases with known disease-causing variants. ResultsIn general, the sensitivity and PPV for SNV/indel detection increased with mean depth, and reached a plateau at a ~40X mean depth using down-sampling samples of NA12878. With a mean depth of 40X, the sensitivity of homozyous and heterozygous SNPs of NA12878 was >99.25% and >99.50% respectively, and PPVs were 99.97% and 98.96%. Homozygous and heterozygous indels showed lower sensitivity and PPV. The sensitivity and PPV is still not 100% even with a mean depth of ~150X. We also observed a substantial variation in the sensitivity of CNV detection across different tools, especially in CNVs with a size of less than 1kb. In general, the breadth of coverage for disease-associated genes and CNVs increased with mean depth. The sensitivity and coverage of WGS (~40X) is better than WES (~120X). Among the Chinese trios with ~40X mean depth, the sensitivity in the offspring was >99.48% and >96.36% for SNP and indel detection, and PPVs were 99.86% and 97.93%. All the 12 previously validated variants in the 8 clinical cases were successfully detected by our WGS pipeline. ConclusionsThe current standard of a mean depth of 40X may be sufficient for SNV/indel detection and identification of most CNVs. Clinical scientists should know the range of sensitivity and PPV for different classes of variants for a particular WGS pipeline, which would be useful when interpreting and delivering clinical reports.

genomics↗

bioRxiv2020

Angioplasty-induced epigenomic remodeling entails BRD4 and EZH2 hierarchical regulations

Atherosclerosis is commonly treated with angioplasty which, however, evokes neointimal hyperplasia (IH) and recurrent stenotic diseases. Epigenomic investigation was lacking on post-angioplasty IH. The histone acetylation reader BRD4 and H3K27me3 writer EZH2 are potent epigenetic factors; their relationship is little understood. Through genome-wide survey in the rat angioplasty model, we studied BRD4 and EZH2 functional regulations involved in IH. We performed chromatin immunoprecipitation sequencing (ChIPseq) using rat carotid arteries. While H3K27me3 ChIPseq signal prevalently intensified in balloon-injured (vs uninjured) arteries, BRD4 and H3K27ac became more enriched at Ezh2. Indeed, BRD4-siRNA or CRISPR-deletion of BRD4-associated enhancer abated the smooth muscle cell (SMC) expression of EZH2, and SMC-specific BRD4 knockout in BRD4fl/fl; Myh11CreERT2 mice reduced both H3K27me3 and IH in wire-injured femoral arteries. In accordance, post-angioplasty IH was exacerbated and mitigated, respectively, by lentiviral expression and pharmacological inhibition of EZH2/1; EZH2 (or EZH1) loss- and gain-of-function respectively attenuated and aggravated pro-IH SMC proliferative behaviors. Furthermore, while H3K27me3 ChIPseq signal magnified at P57 and ebbed at Ccnd1 and Uhrf1 after injury, silencing either EZH2 or EZH1 in SMCs up-regulated P57 and down-regulated Ccnd1 and Uhrf1. In summary, our results reveal an upsurge of EZH2/H3K27me3 after angioplasty, BRD4s control over EZH2 expression, and non-redundant EZH2/1 functions. As such, this study unravels angioplasty-induced loci-specific H3K27me3/ac redistribution in the epigenomic landscape rationalizing BRD4/EZH2-governed pro-IH regulations.

pathology↗

bioRxiv2019

Diffusion Histology Imaging Detects and Classifies Glioblastoma Pathology Missed by Conventional Magnetic Resonance Imaging

PurposeGlioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted for examining GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of GBMs. Experimental DesignWe employ a novel Diffusion Histology Imaging (DHI) approach, combining diffusion basis spectrum imaging (DBSI) and machine learning, to detect, differentiate, and quantify areas of high cellularity, tumor necrosis, and tumor infiltration in GBM. ResultsGd-enhanced T1W or hyper-intense FLAIR failed to reflect the morphological complexity underlying tumor in GBM patients. Contrary to the conventional wisdom that apparent diffusion coefficient (ADC) negatively correlates with increased tumor cellularity, we demonstrate disagreement between ADC and histologically confirmed tumor cellularity in glioblastoma specimens, whereas DBSI-derived restricted isotropic diffusion fraction positively correlated with tumor cellularity in the same specimens. By incorporating DBSI metrics as classifiers for a supervised machine learning algorithm, we accurately predicted high tumor cellularity, tumor necrosis, and tumor infiltration with 87.5%, 89.0% and 93.4% accuracy, respectively. ConclusionOur results suggest that DHI could serve as a favorable alternative to current neuroimaging techniques for guiding biopsy or surgery as well as monitoring therapeutic response in the treatment of glioblastoma. Translational RelevanceCurrent clinical diagnosis, surgical planning, and assessment of treatment response for GBM patients relies heavily on gadolinium-enhanced T1-weighted MRI, which is non-specific for tumor growth and merely reflects a disrupted blood-brain barrier. The complex tumor microenvironment and spatial heterogeneity make GBM difficult to characterize using current clinical imaging modalities. In this study, we developed a novel imaging technique to characterize and accurately predict key histological features of GBM - high tumor cellularity, tumor necrosis, and tumor infiltration. While further validation in a larger cohort of patients is needed, the current proof-of-concept approach could provide a solution to resolve important clinical questions such as the identification of true tumor progression vs. pseudoprogression or radiation necrosis.

neuroscience↗

bioRxiv2019

Coordination between stabilizing circuits and updating circuits in spatial orientation working memory

Spatial orientation memory plays a crucial role in animal navigation. Recent studies of tethered Drosophila melanogaster (fruit fly) in a virtual reality setting showed that the head direction is encoded in the form of an activity bump, i.e. localized neural activity, in the torus-shaped ellipsoid body (EB). However, how this system is involved in orientation working memory is not well understood. We investigated this question using free moving flies (Drosophila melanogaster) in a spatial orientation memory task by manipulating two EB subsystems, C and P circuits, which are hypothesized for stabilizing and updating the activity bump, respectively. To this end, we suppressed or activated two types of inhibitory ring neurons (EIP and P) which innervate EB, and we discovered that manipulating the two inhibitory neuron types produced distinct behavioral deficits, suggesting specific roles of the inhibitory neurons in coordinating the stabilization and updating functions of the EB circuits. We further elucidate the neural mechanisms underlying such control circuits using a connectome-constrained spiking neural network model. Significance statementHead-direction (HD) system has been discovered in rodents for decades. But the detailed neural circuit mechanisms underlying the HD system were only described recently by studies of fruit flies on the similar HD system. However, how this fruit fly HD system involves in orientation memory was not well investigated. The present study addresses this question by investigating free moving flies in a spatial orientation working memory task. By combining neural functional experiments and neural circuit modelling, the study shows how disrupting either of the two subcircuits, one stabilizing and the other updating the neural activity, in the HD system leads to different behavioral impairments. The result suggests specific roles of the HD subcircuits in the spatial orientation working memory. Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/819185v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@101cb04org.highwire.dtl.DTLVardef@b7ac8borg.highwire.dtl.DTLVardef@a10a41org.highwire.dtl.DTLVardef@a8691e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2019

Variations of gut microbiome profile under different storage conditions and preservation periods: A multi-dimensional evaluation

Gut dysbiosis contributes to the development of various human diseases. There are thousands of publications per year for investigating the role of gut microbiota in development of various diseases. However, emerging evidence has indicated data inconsistency between different studies frequently, but gained very little attention by scientists. There are many factors that can cause data variation and inconsistency during the process of microbiota study, in particular, sample storage conditions and subsequent sequencing process. Here, we systemically evaluated the impacts of six fecal sample storage conditions (including -80 {degrees}C, -80 {degrees}C with 70% ethanol (ET_-80 {degrees}C), 4{degrees}C with 70% ethanol (ET_4{degrees}C), and three commercial storage reagents including OMNIgene*GUT OMR-200 (GT), MGIEasy (MGIE), and Longsee (LS)), storage periods (1, 2 weeks or 6 months), and sequencing platform on gut microbiome profile using 16S rRNA gene sequencing. Our results suggested that -80{degrees}C is acceptable for fecal sample storage, and the addition of 70% ethanol offers some benefits. Meanwhile, we found that samples in ET_4 {degrees}Cand GT reagents are comparable, both introduced multi-dimensional variations. The use of MGIE resulted in the least alteration, while the greatest changes were observed in samples stored in LS reagents during the whole experiment. Finally, we also confirmed that variations caused by storage condition were larger than that of storage time and sequencing platform.\n\nIMPORTANCEIn the current study, we performed a multi-dimensional evaluation on the variations introduced by types of storage conditions, preservation period and sequencing platform on the basis of data acquired from 16S rRNA gene sequencing. The efficacy of preservation methods was comprehensively evaluated by DNA yield and quality, and {beta} diversity, relative abundance of the dominant bacteria and functional bacteria associated with SCFAs producing and BAs metabolism. Our results confirmed that variations introduced by storage condition were larger than that of storage periods and sequencing platform. Collectively, our study provided a comprehensive view to the impacts of storage conditions, storage times, and sequencing platform on gut microbial profile.

microbiology↗

bioRxiv2019

Identification of porcine RUNX1 as an LPS-dependent gene expression regulator in PBMCs by Super deepSAGE sequencing of multiple tissues

Genome-wide identification of gene expression regulators may facilitate our understanding of the transcriptome constructed by gene expression profiling experiment. These regulators may be selected as targets for genetic manipulations in farm animals. In this study, we developed a gene expression profile of 76,000+ unique transcripts for 224 porcine samples from 28 normal tissues collected from 32 animals using Super deepSAGE (serial analysis of gene expression by deep sequencing) technology. Excellent sequencing depth has been achieved for each multiplexed library, and principal component analysis showed that duplicated samples from the same tissues cluster together, demonstrating the high quality of the Super deepSAGE data. Comparison with previous research indicated that our results not only have excellent reproducibility but also have greatly extended the coverage of the sample types as well as the number of genes. Clustering analysis discovered ten groups of genes showing distinct expression patterns among those samples. Binding motif over representative analysis identified 41 regulators responsible for the regulation of these gene clusters. Finally, we demonstrate a potential application of this dataset to infectious and immune research by identifying an LPS-dependent transcription factor, runt-related transcription factor 1 (RUNX1), in peripheral blood mononuclear cells (PBMCs). The selected genes are specifically responsible for the transcription of toll-like receptor 2 (TLR2), lymphocyte-specific protein tyrosine kinase (LCK), vav1 oncogene (VAV1), and other 32 genes. These genes belong to the T and B cell signaling pathways, making them potential novel targets for the diagnostic and therapy of bacterial infections and other immune disorders.

genomics↗

bioRxiv2019

Inhibition of ADORA1 attenuates hepatic steatosis by gut microbiota-derived acetic acid from Astragalus polysaccharides

The authors have withdrawn this manuscript, because some data could not be replicated. During the process of subsequent revision of the manuscript, we separated the data into two parts. The majority data of the preprint draft, the anti-NAFLD effect of Astragalus polysaccharides (APS) in mice and the contribution of gut microbiota, were independently published in 2021 after substantial revision (doi: https://doi.org/10.1080/19490976.2021.1930874). However, the data on figure 6 (about ARs inhibitors DPCPX orally ameliorating NAFLD in mice, and Adora1 si-RNA data in vitro) could not be fully replicated in subsequent experiments. The most probable reason might be due to the batch differences of mice / cells, or other undetermined factors during experiment. Moreover, we have carried out in-depth studies on the exact role of hepatic A1R on NAFLD formation, which is opposite to our prior assumption. Therefore, we do not wish this work to be cited as reference for the project. We apologize for any inconvenience caused to our readers. Any questions can be addressed to first/corresponding author.

physiology↗

bioRxiv2019

Efficient and accurate prediction of transmembrane topology from amino acid sequence only

MotivationRapid and accurate identification of transmembrane (TM) topology is well suited for the annotation of the entire membrane proteome. It is the initial step of predicting the structure and function of membrane proteins. However, existing methods that utilize only amino acid sequence information suffer from low prediction accuracy, whereas methods that exploit sequence profile or consensus need too much computational time.\n\nMethodHere we propose a deep learning framework DeepCNF that predicts TM topology from amino acid sequence only. Compared to previous sequence-based approaches that use hidden Markov models or dynamic Bayesian networks, DeepCNF is able to incorporate much more contextual information by a hierarchical deep neural network, while simultaneously modeling the interdependency between adjacent topology labels.\n\nResultExperimental results show that PureseqTM not only outperforms existing sequence-based methods, but also reaches or even surpasses the profile/consensus methods. On the 39 newly released membrane proteins, our approach successfully identifies the correct TM segments and boundaries for at least 3 cases while all existing methods fail to do so. When applied to the entire human proteome, our method can identify the incorrect annotations of TM regions by UniProt and discover the membrane-related proteins that are not manually curated as membrane proteins.\n\nAvailabilityhttp://pureseqtm.predmp.com/

bioinformatics↗

bioRxiv2019

Combined Transcriptomics and Proteomics Forecast Analysis for Potential Genes Regulating the Columbian Plumage Color in Chickens

BackgroundColoration is one of the most recognizable characteristics in chickens, and clarifying the coloration mechanisms will help us understand feather color formation. \"Yufen I\" is an commercial egg-laying chicken breed in China, that was developed by a three-line cross using lines H, N and D. Columbian plumage is a typical feather character of the \"Yufen I\" H line. To elucidate the molecular mechanism underlying pigmentation of Columbian plumage, this study utilizes the technology of high-throughput sequencing to compare the transcriptome and proteome differences in different feather follicular tissue, including the dorsal neck with black and white striped feather follicles (Group A) and the ventral neck with white feather follicles (Group B) in the \"Yufen I\" H line.\n\nResultsIn this study, we identified a total of 21,306 genes and 5203 proteins in chicken feather follicles. Among these, 209 genes and 382 proteins were differentially expressed in two different locations, Group A and Group B, respectively. A total of 8 differentially expressed genes (DEGs) and 9 differentially expressed proteins (DEPs) were found to be involved in the melanogenesis pathway. Besides, a specifically expressed MED23 gene and a differential expressed GNAQ protein were involved in melanin synthesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis mapped 190 DEGs and 322 DEPs, to 175 and 242 pathways, respectively, and there were 166 pathways correlated with both DEGs and DEPs. 49 DEPs/DEGs overlapped and were enriched for 12 pathways. Transcriptomic and proteomic analyses revealed that the following pathways were activated: melanogenesis, cardiomycete adrenergic, calcium and the cGMP-PKG. The expression of DEGs was validated by real-time quantitative polymerase chain reaction (qRT-PCR) that was similar to that of RNA-seq. In addition, we found that MED23, FZD10, WNT7B and WNT11 genes expression peaked at approximately 8 weeks in the \"Yufen I\" H line, which is consistent with the molting cycle. As both the groups showed significant differences in terms of expression of the genes studied, this study opens up avenues for study in the future to assess their exact function in color of plumage.\n\nConclusionThese common DEGs and DEPs were enriched in the melanogenesis pathway. The MED23 and GNAQ were also reported to have a crucial part synthesis of melanin. In addition, this study is the first to reveal variations in gene and protein in the \"Yufen I\" H line during Columbian feather color development, and discover principal genes and proteins that would aid in the functional genomics studies in future. The results of the present study provide a significant conceptual basis for the \"Yufen I\" H line future breeding schemes and provide a basis for research on the mechanisms of feather pigmentation.

molecular biology↗

bioRxiv2018

Searching and mapping genomic subsequences in nanopore raw signals through novel dynamic time warping algorithms

Genome diagnostics have gradually become a prevailing routine for human healthcare. With the advances in understanding the causal genes for many human diseases, targeted sequencing provides a rapid, cost-efficient and focused option for clinical applications, such as SNP detection and haplotype classification, in a specific genomic region. Although nanopore sequencing offers a perfect tool for targeted sequencing because of its mobility, PCR-freeness, and long read properties, it poses a challenging computational problem of how to efficiently and accurately search and map genomic subsequences of interest in a pool of nanopore reads (or raw signals). Due to its relatively low sequencing accuracy, there is no reliable solution to this problem, especially at low sequencing coverage.\n\nHere, we propose a brand new signal-based subsequence inquiry pipeline as well as two novel algorithms to tackle this problem. The proposed algorithms follow the principle of subsequence dynamic time warping and directly operate on the electrical current signals, without loss of information in base-calling. Therefore, the proposed algorithms can serve as a tool for sequence inquiry in targeted sequencing. Two novel criteria are offered for the consequent signal quality analysis and data classification. Comprehensive experiments on real-world nanopore datasets show the efficiency and effectiveness of the proposed algorithms. We further demonstrate the potential applications of the proposed algorithms in two typical tasks in nanopore-based targeted sequencing: SNP detection under low sequencing coverage, and haplotype classification under low sequencing accuracy.

bioinformatics↗

bioRxiv2018

SCDT: Detecting CNVs of low chimeric ratio in cf-DNA

MotivationSequencing of cell-free DNA (cf-DNA) has enabled Noninvasive Prenatal Testing (NIPT) and\"liquid biopsy\" of cancers. However, while the aneuploidy and point mutations were focused on by most of NITP and liquid biopsy studies, detecting sub-chromosome CNVs that affect a few to dozens of megabases was rarely reported, likely attributable to the difficulty in accurately identifying them, especially for those present in a small fraction of cf-DNA.\n\nResultsWe developed a somatic CNV detection tool (SCDT), for detecting sub-chromosome CNVs in cf-DNA using whole genome sequencing (WGS) data or off-target reads in target sequencing data. Additional to using control samples for correcting genome position specific bias, two GC correction steps were performed, which regressed GC content of DNA fragments and that of genome bins, respectively. After GC correction, the coefficients of variation of copy ratios approximated the lower boundary of theoretical values, suggesting removing of almost all systematic errors. Finally, CNVs were detected by a piecewise least squares fitting based segmentation algorithm, which outperformed other segmentation methods. We applied SCDT on simulated and real maternal plasma samples, and target cf-DNA sequencing of 118 normal individuals and 240 cancer patients, and demonstrated high sensitivity and specificity.\n\nAvailabilitySCDT is available at https://github.com/Martiantian/Somatic_cnv_detect_tool.\n\nContactzhuhongmei@genomics.cn\n\nSupplementary InformationSupplementary data are available at Bioinformatics online

bioinformatics↗