Biology subjects

Zhong, Y.

Publications and source records attributed to Zhong, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Chromosome-level de novo assembly of Coprinopsis cinerea A43mut B43mut pab1-1 #326 and genetic variant identification of mutants using Nanopore MinION sequencing

The homokaryotic Coprinopsis cinerea strain A43mut B43mut pab1-1 #326 is a widely used experimental model for developmental studies in mushroom-forming fungi. It can grow on defined artificial media and complete the whole lifecycle within two weeks. The mutations in mating type factors A and B result in the special feature of clamp formation and fruiting without mating. This feature allows investigations and manipulations with a homokaryotic genetic background. Current genome assembly of strain #326 was based on short-read sequencing data and was highly fragmented, leading to the bias in gene annotation and downstream analyses. Here, we report a chromosome-level genome assembly of strain #326. Oxford Nanopore Technology (ONT) MinION sequencing was used to get long reads. Illumina short reads was used to polish the sequences. A combined assembly yield 13 chromosomes and a mitochondrial genome as individual scaffolds. The assembly has 15,250 annotated genes with a high synteny with the C. cinerea strain Okayama-7 #130. This assembly has great improvement on contiguity and annotations. It is a suitable reference for further genomic studies, especially for the genetic, genomic and transcriptomic analyses in ONT long reads. Single nucleotide variants and structural variants in six mutagenized and cisplatin-screened mutants could be identified and validated. A 66 bp deletion in Ras GTPase-activating protein (RasGAP) was found in all mutants. To make a better use of ONT sequencing platform, we modified a high-molecular-weight genomic DNA isolation protocol based on magnetic beads for filamentous fungi. This study showed the use of MinION to construct a fungal reference genome and to perform downstream studies in an individual laboratory. An experimental workflow was proposed, from DNA isolation and whole genome sequencing, to genome assembly and variant calling. Our results provided solutions and parameters for fungal genomic analysis on MinION sequencing platform. HighlightO_LIA chromosome-level genome assembly of C. cinerea #326 C_LIO_LIA fast and efficient high-molecular-weight fungal genomic DNA isolation protocol C_LIO_LIStructural variant and single nucleotide variant calling using Nanopore reads C_LIO_LIA series of solutions and reference parameters for fungal genomic analysis on MinION C_LI

genetics↗

bioRxiv2020

MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data

Distinguishing cell types and cell states is one of the fundamental questions in single-cell studies. Meanwhile, exploring the lineage relations among cells and finding the path and critical points in the cell fate transition are also of great importance. Existing unsupervised clustering methods and lineage trajectory reconstruction methods often face several challenges such as clustering data of arbitrary shapes, tracking precise trajectories and identifying critical points. Certain adaptive landscape approach1-3, which constructs a pseudo-energy landscape of the dynamical system, may be used to explore such problems. Thus, we propose Markov hierarchical clustering algorithm (MarkovHC), which reconstructs multi-scale pseudo-energy landscape by exploiting underlying metastability structure in an exponentially perturbed Markov chain4. A Markov process describes the random walk of a hypothetically traveling cell in the corresponding pseudo-energy landscape over possible gene expression states. Technically, MarkovHC integrates the tasks of cell classification, trajectory reconstruction, and critical point identification in a single theoretical framework consistent with topological data analysis (TDA)5. In addition to the algorithm development and simulation tests, we also applied MarkovHC to diverse types of real biological data: single-cell RNA-Seq data, cytometry data, and single-cell ATAC-Seq data. Remarkably, when applying to single-cell RNA-Seq data of human ESC derived progenitor cells6, MarkovHC not only could successfully identify known cell types, but also discover new cell types and stages. In addition, when using MarkovHC to analyze single-cell RNA-Seq data of human preimplantation embryos in early development7, the hierarchical structure of the lineage trajectories was faithfully reconstituted. Furthermore, the critical points representing important stage transitions had also been identified by MarkovHC from early gastric cancer data8. In summary, these results demonstrate that MarkovHC is a powerful tool based on rigorous metastability theory to explore hierarchical structures of biological data, to identify a cell sub-population (basin) and a critical point (stage transition), and to track a lineage trajectory (differentiation path). HighlightsO_LIMarkovHC explores the topology hierarchy in high-dimensional data. C_LIO_LIMarkovHC can find clusters (basins) and cores (attractors) of clusters in different scales. C_LIO_LIThe trajectory of state transition (transition paths) and critical points in the process of state transition (critical points) among clusters can be tracked. C_LIO_LIMarkovHC can be applied on diverse types of single-cell omics data. C_LI

bioinformatics↗

bioRxiv2020

Genomic selection to optimize doubled haploid-based hybrid breeding in maize

Crop improvement, as a long-term endeavor, requires continuous innovations in technique from multiple perspectives. Doubled haploid (DH) technology for pure inbred production, which shaves years off of the conventional selfing approach, has been widely used for breeding. However, the final success rate of in vivo maternal DH production is determined by four factors: haploids induction, haploids identification, chromosome doubling, and successful selfing of the fertile haploid plants to produce DH seeds. Traits in each of these steps, if they can be accurately predicted using genomic selection methods, will help adjust the DH production protocol and simplify the logistics and save costs. Here, a hybrid population (N=158) was generated based on an incomplete half diallel design using 27 elite inbred lines. These hybrids were induced to create F1-derived haploid families. The hybrid materials, as well as the 27 inbreds, the inbred-derived haploids (N=200), and the F1-derived haploids (N=5,000) were planted in the field to collect four DH-production traits, three yield-related traits, and three developmental traits. Quantitative genetics analysis suggested that in both diploids and haploid families, most of the developmental traits showed high heritability, while the DH-production and developmental traits exhibited intermediate levels of heritability. By employing different genomic selection models, our results showed that the prediction accuracy ranged from 0.52 to 0.59 for the DH-production traits, 0.50 to 0.68 for the yield-related traits, and 0.44 to 0.87 for the developmental traits. Further analysis using index selection achieved the highest prediction accuracy when considering both DH production efficiency and the agronomic trait performance. Furthermore, the long-term responses through simulation confirmed that index selection would increase the genetic gain for targeted agronomic traits while maintaining the DH production efficiency. Therefore, our study provides an optimization strategy to integrate GS technology for DH-based hybrid breeding.

genetics↗

bioRxiv2020

Incorporation of DNA methylation into eQTL mapping in African Americans.

Epigenetics is a reversible molecular mechanism that plays a critical role in many developmental, adaptive, and disease processes. DNA methylation has been shown to regulate gene expression and the advent of high throughput technologies has made genome-wide DNA methylation analysis possible. We investigated the effect of DNA methylation in eQTL mapping (methylation-adjusted eQTLs), by incorporating DNA methylation as a SNP-based covariate in eQTL mapping in African American derived hepatocytes. We found that the addition of DNA methylation uncovered new eQTLs and eGenes. Previously discovered eQTLs were significantly altered by the addition of DNA methylation data suggesting that methylation may modulate the association of SNPs to gene expression. We found that methylation-adjusted eQTLs which were less significant compared to PC-adjusted eQTLs were enriched in lipoprotein measurements (FDR = 0.0040), immune system disorders (FDR = 0.0042), and liver enzyme measurements (FDR = 0.047), suggesting a role of DNA methylation in regulating the genetic basis of these phenotypes. Our methylation-adjusted eQTL analysis also uncovered novel SNP-gene pairs. For example, our study found the SNP, rs11546996, was associated to PNKP. In a previous GWAS, this SNP was associated with primary biliary cirrhosis although the causal gene was thought to be SPIB. Our methylation-adjusted method potentially adds new understanding to the genetic basis of complex diseases that disproportionally affect African Americans.

genomics↗

bioRxiv2020

A unified atlas of CD8 T cell dysfunctional states in cancer and infection

CD8 T cells play an essential role in defense against viral and bacterial infections and in tumor immunity. Deciphering T cell loss of functionality is complicated by the conspicuous heterogeneity of CD8 T cell states described across different experimental and clinical settings. By carrying out a unified analysis of over 300 ATAC-seq and RNA-seq experiments from twelve independent studies of CD8 T cell dysfunction in cancer and infection we defined a shared differentiation trajectory towards terminal dysfunction and its underlying transcriptional drivers and revealed a universal early bifurcation of functional and dysfunctional T cell activation states across models. Experimental dissection of acute and chronic viral infection using scATAC-seq and allele-specific scRNA-seq identified state-specific transcription factors and captured the early emergence of highly similar TCF1+ progenitor-like populations at an early branch point, at which epigenetic features of functional and dysfunctional T cells diverge. Our atlas of CD8 T cell states will facilitate mechanistic studies of T cell immunity and translational efforts.

genomics↗

bioRxiv2020

Adult newborn granule cells confer emotional-state-dependent plasticity in memory retrieval

Achieving optimal behavior requires animals to flexibly retrieve prior knowledge. Here we show that adult newborn granule cells (anbGCs) mediate emotional-state-dependent plasticity of memory retrieval. We find that acute social reward (aSR) enhances memory retrieval by increasing the reactivation of engram cells, while acute social stress (aSS) weakens retrieval and reduces the reactivation. Such bidirectional regulation relies on the activation of distinct populations of anbGCs by aSR and aSS, triggering opposing modifications of dDG activity, which is sufficient to regulate and predict the performance of memory retrieval. Concordantly, in emotional disorder models, aSR-dependent memory plasticity is impaired, while the effect of aSS remains intact. Together, our data revealed that anbGCs mediate plasticity of memory retrieval, allowing animals to flexibly retrieve memory according to the current emotional state, and suggested the essential roles of anbGCs in translating emotional information to the regulation of memory expression.

neuroscience↗

bioRxiv2020

Site-specific N-glycosylation Characterization of Recombinant SARS-CoV-2 Spike Proteins using High-Resolution Mass Spectrometry

SummaryThe glycoprotein spike (S) on the surface of SARS-CoV-2 is a determinant for viral invasion and host immune response. Herein, we characterized the site-specific N-glycosylation of S protein at the level of intact glycopeptides. All 22 potential N-glycosites were identified in the S-protein protomer and were found to be preserved among the 753 SARS-CoV-2 genome sequences. The glycosites exhibited glycoform heterogeneity as expected for a human cell-expressed protein subunits. We identified masses that correspond to 157 N-glycans, primarily of the complex type. In contrast, the insect cell-expressed S protein contained 38 N-glycans, primarily of the high-mannose type. Our results revealed that the glycan types were highly determined by the differential processing of N-glycans among human and insect cells. This N-glycosylation landscape and the differential N-glycan patterns among distinct host cells are expected to shed light on the infection mechanism and present a positive view for the development of vaccines and targeted drugs.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsACE2angiotensin-converting enzyme IICryo-EMcryoelectron microscopyEenvelope proteinHCoV-NL63human coronavirus NL63Mmembrane proteinMSmass spectrometryMERS-CoVMiddle East respiratory syndrome coronavirusNnucleocapsid proteinRBDreceptor-binding domainSspike proteinSARS-CoV-2severe acute respiratory syndrome coronavirusSCEstepped collision energyZic-HILICzwitterionic hydrophilic interaction liquid chromatographyView Full Text

biochemistry↗

bioRxiv2020

A Novel Non-hypermucoviscous ST11 Hypervirulent Carbapenem-resistant Klebsiella pneumoniae Lacking Classical Virulence Factors

BackgroundHypervirulent Klebsiella pneumoniae lacking classical virulence factors is uncommon, and the virulence mechanisms of this organism are not understood. MethodsFollowing a retrospective study of carbapenem-resistant K. pneumoniae based on core genome multilocus sequence typing (cgMLST), isolates that caused high mortality were investigated with a genome-wide association study (GWAS), proteome analysis and an animal model. ResultsThe sublineage of sequence type 11 (ST11) K. pneumoniae, which belongs to complex type 3176 (CT3176) and K-locus 47 (KL47), was highlighted due to the high mortality of infected patients. GWAS analysis showed that ampR was associated with the CT3176 isolates. In a mouse model, the mortality of ampR-carrying isolates was comparable to that of the typical hypervirulent isolate GM2. Even during the first 24 hours of infection, the bacterial load and pathological changes of the ampR-carrying isolates in the lungs were more severe than those of GM2. The ampR complement mutant was able to enhance the virulence of the KL47 isolate but not the virulence of KL1. Proteome analysis showed that the expression of WcaJ in the ampR+ isolates was significantly higher than that in the ampR- isolates, and this result was also confirmed by transcription tests and capsule staining. It is suggested that the enhancement of the initial stage of capsule synthesis may be the cause of the high virulence of these non-hypermucoviscous ST11 carbapenem-resistant K. pneumoniae isolates. ConclusionsNon-hypermucoviscous ST11 hypervirulent carbapenem-resistant K. pneumoniae warrants continued surveillance and investigation.

microbiology↗

bioRxiv2020

Single-cell Analysis of ACE2 Expression in Human Kidneys and Bladders Reveals a Potential Route of 2019-nCoV Infection

Since December 2019, a novel coronavirus named 2019 coronavirus (2019-nCoV) has emerged in Wuhan of China and spread to several countries worldwide within just one month. Apart from fever and respiratory complications, acute kidney injury has been observed in some patients with 2019-nCoV. In a short period of time, angiotensin converting enzyme II (ACE2), have been proposed to serve as the receptor for the entry of 2019-nCoV, which is the same for severe acute respiratory syndrome coronavirus (SARS). To investigate the possible cause of kidney damage in 2019-nCoV patients, we used both published kidney and bladder cell atlas data and an independent unpublished kidney single cell RNA-Seq data generated in-house to evaluate ACE2 gene expressions in all cell types in healthy kidneys and bladders. Our results showed the enriched expression of all subtypes of proximal tubule cells of kidney and low but detectable levels of expression in bladder epithelial cells. These results indicated the urinary system is a potential route for 2019-nCoV infection, along with the respiratory system and digestion system. Our findings suggested the kidney abnormalities of SARS and 2019-nCoV patients may be due to proximal tubule cells damage and subsequent systematic inflammatory response induced kidney injury. Beyond that, laboratory tests of viruses and related indicators in urine may be needed in some special patients of 2019-nCoV.

genomics↗

bioRxiv2020

scTenifoldNet: a machine learning workflow for constructing and comparing transcriptome-wide gene regulatory networks from single-cell data

Constructing and comparing gene regulatory networks (GRNs) from single-cell RNA sequencing (scRNAseq) data has the potential to reveal critical components in the underlying regulatory networks regulating different cellular transcriptional activities. Here, we present a robust and powerful machine learning workflow--scTenifoldNet--for comparative GRN analysis of single cells. The scTenifoldNet workflow, consisting of principal component regression, low-rank tensor approximation, and manifold alignment, constructs and compares transcriptome-wide single-cell GRNs (scGRNs) from different samples to identify gene expression signatures shifting with cellular activity changes such as those associated with pathophysiological processes and responses to environmental perturbations. We used simulated data to benchmark scTenifoldNets performance, and then applied scTenifoldNet to several real data sets. In real-data applications, scTenifoldNet identified highly specific changes in gene regulation in response to acute morphine treatment, an antibody anticancer drug, gene knockout, double-stranded RNA stimulus, and amyloid-beta plaques in various types of mouse and human cells. We anticipate that scTenifoldNet can help achieve breakthroughs through constructing and comparing scGRNs in poorly characterized biological systems, by deciphering the full cellular and molecular complexity of the data. HighlightsO_LIscTenifoldNet is a machine learning workflow built upon principal component regression, low-rank tensor approximation, and manifold alignment C_LIO_LIscTenifoldNet uses single-cell RNA sequencing (scRNAseq) data to construct single-cell gene regulatory networks (scGRNs) C_LIO_LIscTenifoldNet compares scGRNs of different samples to identify differentially regulated genes C_LIO_LIReal-data applications demonstrate that scTenifoldNet accurately detects specific signatures of gene expression relevant to the cellular systems tested. C_LI Short abstractWe present scTenifoldNet--a machine learning workflow built upon principal component regression, low-rank tensor approximation, and manifold alignment--for constructing and comparing single-cell gene regulatory networks (scGRNs) using data from single-cell RNA sequencing (scRNAseq). scTenifoldNet reveals regulatory changes in gene expression between samples by comparing the constructed scGRNs. With real data, scTenifoldNet identifies specific gene expression programs associated with different biological processes, providing critical insights into the underlying mechanism of regulatory networks governing cellular transcriptional activities.

bioinformatics↗

bioRxiv2020

KALRN Mutations Promote Anti-tumor Immunity and Immunotherapy Response in Cancer

BackgroundKALRN (kalirin RhoGEF kinase) is mutated in a wide range of cancers. Nevertheless, the association between KALRN mutations and the pathogenesis of cancer remains unexplored. The identification of biomarkers for cancer immunotherapy response is important considering that immunotherapies show beneficial effects only in a subset of cancer patients. MethodsWe explored the correlation between KALRN mutations and anti-tumor immunity in 10 cancer cohorts from The Cancer Genome Atlas (TCGA) program by the bioinformatics approach. Moreover, we verified the findings from bioinformatics analysis by in vitro experiments. Furthermore, we explored the correlation between KALRN mutations and immunotherapy response in four cancer cohorts receiving immune checkpoint blockade therapy. ResultsWe found that anti-tumor immune signatures were stronger in KALRN-mutated than in KALRN-wildtype cancers. Moreover, KALRN mutations correlated with increased tumor mutation burden and the microsatellite instability or DNA damage repair deficiency genomic properties which may explain the elevated anti-tumor immunity in KALRN-mutated cancers. Furthermore, we found that PD-L1 expression was significantly upregulated in KALRN-mutated versus KALRN-wildtype cancers. The enhanced anti-tumor immune signatures and PD-L1 expression in KALRN-mutated cancers may favor the response to immune checkpoint blockade therapy in this cancer subtype, as evidenced in four cancer cohorts receiving anti-PD-1/PD-L1/CTLA-4 immunotherapy. We further revealed that the significant association between KALRN mutations and increased anti-tumor immunity was attributed to that KALRN mutations compromised the function of KALRN target Rho GTPases on regulating DNA damage repair pathways. ConclusionsThe KALRN mutation is a useful biomarker for predicting the response to immunotherapy in cancer patients.

immunology↗

bioRxiv2019

Lyb-2-4, a unique genomic region of hypervirulent carbapenem-resistant Acinetobacter baumannii

Acinetobacter baumannii is an important human pathogen due to its multi-drug resistance, but is usually with low-grade virulence. Although a mouse model revealed different virulence grades of clinical carbapenem-resistant A. baumannii (CRAB) strains, the genetic basis remains unknown. We collected 61 CRAB isolates from intensive care unit of Shenzhen Peoples Hospital (Shenzhen, China), and analyzed them used whole genome sequencing (WGS), multilocus sequence typing (MLST) and core genome MLST (cgMLST), transmission chain reconstruction and Comparative genomic tools. A mouse pneumonia model was used to confirm the hypervirulent phenotype. Eleven complex types (CT) were identified based on core genome multilocus sequence typing scheme. CT512 showed higher transmissibility and bloodstream infection rates than other CTs. A genomic region Lyb-2-4 was shared by CT512 and CT2092 but not CT2085. The mortality rates of patient infected with CRAB harboring Lyb-2-4 was significantly higher than those infected with CRAB isolates without Lyb-2-4 (77.8% vs 24.5%, p < 0.01). In the mouse model, the survival rates of strains containing the Lyb-2-4 region (LAC-4, 5122 and 2092) were significantly lower than for strains without Lyb-2-4 (7152, 71517, 20859 and ATCC17978). One open reading frame (ORF) was a marker for the presence of Lyb-2-4, and PCR of a segment of this ORF, designated as hvcT, served as a tag for hypervirulent CRAB. Our study should be very useful in advising the clinician to implement medical intervention earlier, and also making the worldwide surveillance of these hypervirulent CRAB strains easier.\n\nIMPORTANCEHypervirulent CRAB strains are expected to pose a threat to human health because infection of these strains is associated with high mortality and multidrug resistance. The rapid hypervirulent CRAB identification assay will facilitate prompt medical intervention. Our findings should provoke surveillance for hypervirulent CRAB strains harboring Lyb-2-4 in other countries. Further research should focus on the mechanism of hypervirulence, the acquisition of this genomic region and the development of control measures to prevent further dissemination.

microbiology↗

bioRxiv2019

Impact of peripheral mutations on the access channels of human cytochrome P450 1A2

As an important member of cytochrome P450 (CYP) enzymes, human CYP1A2 is associated with the metabolism of caffeine and melatonin and the activation of precarcinogens. Besides, this CYP protein also involves in metabolizing 5-10% of clinical medicines. Some peripheral mutations in CYP1A2 (P42R, I386F, R431W, and R456H) significantly decrease the enzyme activities, resulting in a vital reduction in substrate metabolisms. To explore the effects of these peripheral mutations, we constructed a membrane-binding model for the full-length human CYP1A2 and studied their dynamic behaviors on lipid membranes. Free energy calculations indicate that the peripheral mutations donot influence substrate binding. P42R is located in the N-terminal anchor, and its positive charged sidechain is adverse to membrane binding. I386F enhances the van der Waals contacts of the water channel bottleneck and R456H breaks the hydrogen bonding interactions that function to position the BC loop, both of which result in a significant inhibition on the water channel. R431W causes a sidechain conformational rearrangement for aromatic residues around the substrate channel, making it in a closed state in most cases. Our computational simulations demonstrate that pi-pi stacking interactions are essential for substrate binding and channel opening. We hope that these findings may be of general relevance to the mutation-induced activity changes for CYP proteins, providing useful information for understanding the CYP-mediated drug metabolism.

biophysics↗

bioRxiv2019

Mining the human tonsillar microbiota as autoimmune modulator

Palatine tonsils are important lymphoid organs featuring constant cross-talks between the commensal microorganisms and immune system, and have been implicated as critical autoimmunity origins for immune-related diseases, including rheumatoid arthritis (RA), a common autoimmune disorder. However, there was no evidence to show link between tonsillar microbiota and RA. Here, we identified a significant dysbiosis of RA tonsillar microbiota, with loss of Streptococcus salivarius and its functional molecules salivaricins (a type of antibacterial peptides). Consistent with the niche-preference, S. salivarius and salivaricins administrated intranasally or intraorally conferred prophylactic and therapeutic efficacies against experimental arthritis. Moreover, we demonstrated, for the first time, that S. salivarius and salivaricins exerted immunosuppressive capacities via inhibiting CD4+effector T cell subsets and autoantibody production in mice and human. These results uncover a communication between tonsillar microbiota and host autoimmunity, and identify the active components from tonsillar microbes in modulating immune homeostasis.\n\nOne sentence summaryTonsillar microbiota regulate host autoimmunity via antibacterial peptides

microbiology↗

bioRxiv2019

Characterizing the Emergence of Liver and Gallbladder from the Embryonic Endoderm through Single-Cell RNA-Seq

The liver and gallbladder are among the most important internal organs derived from the endoderm. Several inductive signals regulate liver development, yet the pure nascent hepatic and gallbladder cells are unable to be isolated due to limited cell markers and cell numbers. The transcriptome networks of the hepatic lineage in the endoderm, and how the gallbladder differentiates from the adjacent endoderm population, are not fully understood. Using a transgenic Foxa2eGFP reporter mouse line, we performed deep single-cell RNA sequencing on 1,966 individual cells, including nascent hepatic and gallbladder cells, isolated from the endoderm and hepatic regions from ten embryonic stages, ranging from day E7.5 to E15.5. We identified the embryonic liver developmental trajectory from primitive streak to hepatoblasts and characterized the transcriptome of the hepatic lineage. During pre-hepatogenesis (5-6 somite stage), we have identified two groups of foregut endoderm cells, one derived from visceral endoderm and the second derived from primitive streak via a mesenchymal-epithelial transition (MET). During the liver specification stages, liver primordium was identified to share both foregut and liver features. We also documented dynamic gene expression during the epithelial-hepatic transition (EHT). Six gene groups were found to switch on or off at different stages during liver specification. Importantly, we found that RXR complex signaling and newly identified transcription factors associated with liver specification. Moreover, we revealed the gallbladder primordium cells at E9.5 and found genes that transcriptionally distinguish them from the liver primordium. The present data provides a high-resolution resource and critical insights for understanding the emergence of the endoderm, liver and gallbladder development.

developmental biology↗

bioRxiv2019

CHD4 slides nucleosomes by decoupling entry- and exit-side DNA translocation

Chromatin remodellers hydrolyse ATP to move nucleosomal DNA against histone octamers. The mechanism, however, is only partially resolved, and unclear if it is conserved among the four remodeller families. Here we use single-molecule assays to examine the mechanism of action of CHD4, which is part of the least well understood family of remodellers. We demonstrate that the binding energy for CHD4-nucleosome complex formation - even in the absence of nucleotide - triggers significant conformational changes in DNA at the entry side, effectively priming the system for remodelling. During remodelling, flanking DNA enters the nucleosome in a continuous, gradual manner but exits in concerted 4-6 base-pair steps. This decoupling of entry- and exit-side translocation suggests that ATP-driven movement of entry-side DNA builds up strain inside the nucleosome that is subsequently released at the exit side by DNA expulsion. We propose a mechanism for nucleosome sliding based on these and published data.

biochemistry↗

bioRxiv2019

CNOT1 mediates phosphorylation via Protein kinase A on the circadian clock

At the core of the mammalian circadian feedback loop, CLOCK (NPAS2)-BMAL1 is the positive element to activate transcription of downstream genes encoding the negative elements PERs and CRYs. Here we show that CNOT1 associates with both CLOCK and BMAL1, promotes their phosphorylation and increases their protein stability, and in turn inhibits the transcriptional activity of CLOCK-BMAL1. Expression of either CLOCK, BMAL1 or CNOT1 could interact with endogenous Protein Kinase A (PKA) as assessed by co-immunoprecipitation (Co-IP) and kinase assays. PKA could phosphorylate CLOCK and BMAL1 and this was promoted by CNOT1. Genetic deletion of PKA-C by CRISPR-Cas9 results in a longer period of the circadian rhythm; while overexpression of PKA-C induces a shorter period. Furthermore, we demonstrate that CNOT1 associates with CLOCK and BMAL1 in the mouse liver and promotes their phosphorylation. PER2, but not CRY2, is also a PKA target. Our results suggest that CNOT1 and PKA play a critical role in the mammalian circadian clock, revealing a conserved function in eukaryotic circadian regulations.

developmental biology↗

bioRxiv2019

Extension of the in vivo haploid induction system from diploid maize to hexaploid wheat

Doubled haploid breeding technology has been one of the most important techniques for accelerating crop breeding. In compare to in vivo haploid induction in maize, which is efficient and background independent, wheat haploid production by interspecific hybridization pollinated with maize is influenced by genetic background and requires rescue of young embryos. Here, we analyzed the homologues of maize haploid induction gene MTL/ZmPLA1/NLD in several crop species systematically, the homologues are highly conserved in sorghum, millet and wheat etc. Since wheat is a very important polyploidy crop, as a proof of concept, we demonstrated that the in vivo haploid induction method could be extended from diploid maize to hexaploid wheat by knocking out the wheat homologues (TaPLAs). Result showed that double knock-out mutation could trigger wheat haploid induction at ~ 2%-3%, accompanied by 30% - 60% seed setting rate. The performance of haploid wheat individual showed shorter plant, narrower leaves and male sterile. Our results also revealed that knockout of TaPLA-A and TaPLA-D do not affect pollen viability. This study not only confirmed the function of the induction gene and explored a new approach for haploid production in wheat, but also provided an example that the in vivo haploid induction could be applied in more crop species with different ploidy levels. Furthermore, by combining with gene editing, it would be a fast and powerful platform for traits improvement in polyploidy crops breeding.

plant biology↗