Biology subjects

Cui, X.

Publications and source records attributed to Cui, X..

At least 127 records · Page 7Linked to original sources

bioRxiv2022

Genetic variation in BnGRP1 contributes to low phosphorus tolerance in Brassica napus

The lack of phosphorus (P) is a major environmental factor affecting rapeseed root growth and development. For breeding purposes, it is crucial to identify the molecular mechanisms of root system architecture (RSA) traits underlying low P tolerance in rapeseed. Using genome-wide association study (GWAS), transcriptome and re-sequencing analyses were done on 400 rapeseed cultivars, the natural variations of glycine-rich protein gene, BnGRP1, in response to low P tolerance. Based on 11 SNP mutations in the BnGRP1 sequence, ten types of haplotypes (Hap) were formed. Compared with the other types, the cultivar of the BnGRP1Hap1 type in the panel demonstrated the longest root length and heaviest root weight. Over-expression of BnGRP1Hap1 in rapeseed depicted the ability to enhance the resistance of rapeseed in its response to low P tolerance. CRISPR/Cas9-derived BnGRP1Hap1 knockout mutations in rapeseed could lead to sensitivity to low P stress. Furthermore, BnGRP1Hap1 influenced the expression of phosphate transporter 1 (PHT1) genes associated with P absorption. Overall, the findings of this study highlight the new mechanisms of GRP1 genes in enhancing the low P tolerance in rapeseed.

molecular biology↗

bioRxiv2022

Human iPSC-derived neuron of 16p11.2 deletion reveals haplotype-specific expression of MAPK3 and its contribution to variable NDD phenotypes

Recurrent proximal 16p11.2 deletion (16p11.2del) is risk factor of diverse neurodevelopmental disorders (NDDs) with variable penetrance. Although previous human induced pluripotent stem cell (hiPSC) models of 16p11.2del confirmed disrupted neuron development, it is not known which gene(s) at this interval are mainly responsible for the abnormal cellular phenotypes and how the NDD penetrance is regulated. After haplotype phasing of 16p11.2 region, we generated hiPSCs for two 16p11.2del families with distinct residual haplotypes and variable NDD phenotypes. We also differentiated the hiPSCs to cortical neural cells and demonstrated MAPK3 as a driver signal of 16p11.2 region contributing to the dysfunctions in multiple pathways related to neuron development, which leads to altered morphological or electrophysiological properties in neuron cells. Furthermore, residual haplotype-specific MAPK3 expression was identified in 16p11.2del neuron cells, associating MAPK3 down-expression with the minor allele of the residual haplotype. Ten SNPs of the residual haplotype are mapped as enhancer SNPs (enSNPs) of MAPK3, eight enSNPs were functionally validated by luciferase assays, implying enSNPs contribute to residual haplotype-specific MAPK3 expression via cis-regulation. Finally, the analyses of three different patient cohorts showed that the residual haplotype of 16p11.2del is associated with variable NDD phenotypes.

genetics↗

bioRxiv2022

TDP 2 modulates the expression of estrogen-responsive oncogenes

With its ligand estrogen, the estrogen receptor (ER) stimulates tumor cell growth by activating a global transcriptional program. This activation involves topoisomerase 2 (TOP2), which resolves topological problems by transiently creating and re-ligating DNA double-strand breaks (DSBs). Recent studies have uncovered the involvement of DNA repair proteins in the repair of TOP2-induced DSBs. These noncanonical repair pathways may serve as backup processes when TOP2 is halted and fails to re-ligate DSBs, but their impact on transcription remains elusive. In this study, we investigated the role of tyrosyl-DNA phosphodiesterase 2 (TDP2), an enzyme that acts for the removal of halted TOP2 from the 5-end of the DNA, in the estrogen-induced transcriptome. Using TDP2-deficient ER-positive cells and mice, we showed that TDP2 regulates the expression of oncogene MYC. MYC induction by estrogen was a very early event (1 hour) and TOP2-dependent. In TDP2-deficient cells, the induction of MYC by estrogen became prolonged and volatile. Bulk and single-cell RNA-seq identified the oncogenes MYC and CCND1 as genes whose estrogen response was regulated by TDP2. These results suggest that TDP2 may play a role in the repair of TOP2-induced DSBs in specific genomic loci and tightly regulates the expression of oncogenes.

molecular biology↗

bioRxiv2022

The molecular consequences of androgen activity in the human breast

The mammary gland has been extensively studied for estrogen and progesterone reactivity, but the molecular effects of androgen in the breast remain largely unexplored. Transgender men are recorded female at birth but identify as male and may undergo gender-affirming androgen therapy to align their physical characteristics and gender identity. Here we perform single cell resolution transcriptome, chromatin, and spatial profiling of androgen treated breasts from transgender men. We find male-biased androgen receptor gene targets are upregulated in cells expressing androgen receptor, and that paracrine signaling drives sex-relevant changes in other cell types. We observe an altered epithelium, shifts in immune populations, and a reduction of capillary vasculature. Finally, we find evidence of the metabolic impact of androgen and identify a gene regulatory network driving androgen-directed fat loss. This work elucidates the molecular consequences of androgen in the human breast at single cell resolution.

genomics↗

bioRxiv2022

The multi-BRCT domain protein DDRM2 is required for homologous recombination in plants

DNA double-strand breaks (DSBs) are the most toxic DNA damage for cells. Homologous recombination (HR) is a precise DSB repair mechanism as well as a basis for gene targeting using genome-editing techniques. Despite the importance of HR, the HR mechanism in plants is poorly understood. In a genetic screen for DNA Damage Response Mutants (DDRMs), we find that the Arabidopsis ddrm2 mutant is hypersensitive to DSB-inducing reagents. DDRM2 encodes a protein with four BRCA1 C-terminal (BRCT) domains and is highly conserved in plants including the earliest land plant linage, bryophytes. The plant-specific transcription factor SOG1 binds to the promoter of DDRM2 and activates its expression, suggesting that DDRM2 is a direct target of SOG1. In consistence, the expression of DDRM2 is induced by DSBs in a SOG1-dependent manner. Epistasis analysis indicates that DDRM2 functions downstream of SOG1. Similar to the sog1 mutant, the ddrm2 mutant shows dramatically reduced HR efficiency. Our study suggests that the SOG1-DDRM2 module is required for HR, providing new insights into the HR mechanisms in plants and a potential target for improving the efficiency of gene targeting. One Sentence SummaryA genetic screen in Arabidopsis reveals that the multi-BRCT domain protein DDRM2 is required for homologous recombination and is targeted by the master DNA damage response regulator SOG1.

plant biology↗

bioRxiv2022

Oropouche orthobunyavirus infection is mediated by the cellular host factor Lrp1

Oropouche orthobunyavirus (OROV; Peribunyaviridae) is a mosquito-transmitted virus that causes widespread cases of human febrile illness in South America, with occasional progression to neurologic effects. Host entry factors mediating cellular entry of OROV are undefined. Here, we show that OROV requires the host protein low density lipoprotein-related protein 1 (Lrp1) for cellular infection. Cells from evolutionarily distinct species lacking Lrp1 were less permissive to OROV infection than cells with Lrp1. Treatment of cells with either the high-affinity Lrp1 ligand receptor-associated protein (RAP) or recombinant ectodomain truncations of Lrp1 significantly reduced OROV infection. Thus, Lrp1 is an important host factor required for infection of cells by OROV. Taken together with our results showing that Lrp1 is a newly identified receptor for Rift Valley fever virus (RVFV), Lrp1 may play a broader role in cellular infection by bunyaviruses than previously appreciated.

microbiology↗

bioRxiv2021

Atypical relationships between neurofunctional features of print-sound integration and reading abilities in Chinese children with dyslexia

Conquering print-sound mappings (e.g., grapheme-phoneme correspondence rules) is vital for developing fluent reading skills. In neuroimaging research, this ability can be indexed by activation differences between audiovisual congruent against incongruent conditions in brain areas such as the left superior temporal cortex. In line with it, individuals with dyslexia have difficulty in tasks requiring print-sound processing, accompanied by a reduced neural integration. However, existing evidence is almost restricted to alphabetic languages. Whether and how multisensory processing of print and sound is impaired in Chinese dyslexia remains underexplored. In this study, we applied a passive audiovisual integration paradigm with functional magnetic resonance imaging to investigate the possible dysfunctions in processing character-sound (opaque; semantics can be automatically accessed) and pinyin-sound associations (transparent; no particular meaning can be confirmed) in Chinese dyslexic children. Unexpectedly, the dyslexic group did not show reduced neural integration compared with typically developing readers in either character or pinyin experiment. However, the results revealed atypical correlations between neural integration and different reading abilities in dyslexia. Specifically, while the neural integration in the left inferior frontal cortex in processing character-sound pairs correlated with silent reading comprehension in both children with and without dyslexia, it was associated with morphological awareness (semantic-related) in controls but with rapid naming (phonological-related) in dyslexics. This result indicates Chinese dyslexic children may not use the same grapho-semantic processing strategy as their typical peers do. As for pinyin-sound processing, while a stronger neural integration in the direction of "congruent > incongruent" in the left occipito-temporal cortex and bilateral superior temporal cortices was associated with better oral reading fluency in the control group, an opposite pattern was found in dyslexia. This finding may reflect dyslexias dysfunctional recruitment of the regions in grapho-phonological processing, which further impedes character learning. HighlightsO_LINeurofunctional correlates of print-sound integration in Chinese children with and without dyslexia are investigated. C_LIO_LIDyslexic children show atypical relationships between neural audiovisual integration and reading abilities. C_LIO_LIChinese children with dyslexia are likely to use inefficient strategies to process characters and pinyin. C_LI

neuroscience↗

bioRxiv2021

Targeted Reactivation of X-linked Endogenous FOXP3 Gene from X-chromosome Inactivation in Human Female Breast Cancer Cells

Unlike autosomal tumor suppressors, which must be inactivated by a two-hit Knudson mechanism, X-linked tumor suppressors can be inactivated by a single hit due to X-chromosome inactivation (XCI). Here, we argue that targeted reactivation of the non-mutated allele from XCI offers a potential therapy for female breast cancers. Towards this goal, we developed a dual CRISPR interference and activation (CRISPRi/a) approach for simultaneously silencing and reactivating multiple X-linked genes using two orthogonal, nuclease-deficient CRISPR/Cas9 (dCas9) proteins. We verified the efficacy for use of Streptococcus pyogenes (Sp) dCas9-KRAB for silencing XIST and Staphylococcus aureus (Sa) dCas9-VPR for activating FOXP3 in various cell lines of human female breast cancers. We confirmed CRISPR reactivation of the non-mutated copy of FOXP3 from XCI in human breast cancer CRL2316 cells, which express a synonymous heterozygous mutation (p.L266L; c.798G>C) in the coding region of FOXP3. Further, simultaneous silencing of XIST from XCI led to enhanced and prolonged FOXP3 reactivation. We optimized CRISPRa by fusing SadCas9 to the demethylase TET1 and observed enhanced FOXP3 activation. Analysis of the conserved CpG-rich region of FOXP3 intron 1 confirmed that CRISPRi/a-mediated simultaneous FOXP3 activation and XIST silencing were accompanied by elevated H4 acetylation, including H4K5ac, H4K8ac, and H4K16ac, and H3K4me3 and lower DNA methylation. This indicates that CRISPRi/a targeting to XIST and FOXP3 loci alters their transcription and their nearby epigenetic modifications. The simultaneous activation and repression of the X-linked, endogenous FOXP3 and XIST from XCI offers a useful research tool and a potential therapeutic for female breast cancers. This approach also provides new routes of targeted therapy for other X-chromosome-linked genetic disorders.

cancer biology↗

bioRxiv2021

Ontology-Aware Deep Learning Enables Novel Antibiotic Resistance Gene Discovery Towards Comprehensive Profiling of ARGs

Antibiotic resistance genes (ARGs) have emerged in pathogens and arousing a worldwide concern, which is estimated to cause millions of deaths each year globally. Accurately identifying and classifying ARGs is a formidable challenge in studying the generation and spread of antibiotic resistance. Current methods could identify close homologous ARGs, have limited utility for discovery of novel ARGs, thus rendering the profiling of ARGs incomprehensive. Here, an ontology-aware neural network (ONN) approach, ONN4ARG, is proposed for comprehensive ARG discovery. Systematic evaluation shows ONN4ARG is advanced than previous methods such as DeepARG in efficiency, accuracy, and comprehensiveness. Experiments using 200 million candidate microbial genes collected from 815 microbial community samples from diverse environments or hosts have resulted in 120,726 candidate ARGs, out of which more than 20% are not yet present in public databases. These comprehensive set of ARGs have clarified the environment-specific and host-specific patterns. The wet-experimental functional validation, together with structural investigation of docking sites, have also validated a novel streptomycin resistance gene from oral microbiome samples, confirming ONN4ARGs ability for novel ARGs identification. In summary, ONN4ARG is superior to existing methods in efficiency, accuracy, and comprehensiveness. It enables comprehensive ARG discovery, which is helpful towards a grand view of ARGs worldwide. ONN4ARG is available at https://github.com/HUST-NingKang-Lab/ONN4ARG, and online web service is available at http://onn4arg.xfcui.com/.

bioinformatics↗

bioRxiv2021

VP-Detector: A 3D convolutional neural network for automated macromolecule localization and classification in cryo-electron tomograms

MotivationCryo-electron tomography (Cryo-ET) with sub-tomogram averaging (STA) is indispensable when studying macromolecule structures and functions in their native environments. However, current tomographic reconstructions suffer the low signal-to-noise (SNR) ratio and the missing wedge artifacts. Hence, automatic and accurate macromolecule localization and classification become the bottleneck problem for structural determination by STA. Here, we propose a 3D multi-scale dense convolutional neural network (MSDNet) for voxel-wise annotations of tomograms. Weighted focal loss is adopted as a loss function to solve the class imbalance. The proposed network combines 3D hybrid dilated convolutions (HDC) and dense connectivity to ensure an accurate performance with relatively few trainable parameters. 3D HDC expands the receptive field without losing resolution or learning extra parameters. Dense connectivity facilitates the re-use of feature maps to generate fewer intermediate feature maps and trainable parameters. Then, we design a 3D MSDNet based approach for fully automatic macromolecule localization and classification, called VP-Detector (Voxel-wise Particle Detector). VP-Detector is efficient because classification performs on the pre-calculated coordinates instead of a sliding window. ResultsWe evaluated the VP-Detector on simulated tomograms. Compared to the state-of-the-art methods, our method achieved a competitive performance on localization with the highest F1-score. We also demonstrated that the weighted focal loss improves the classification of hard classes. We trained the network on a part of training sets to prove the availability of training on relatively small datasets. Moreover, the experiment shows that VP-Detector has a fast particle detection speed, which costs less than 14 minutes on a test tomogram. Contactzsh@amss.ac.cn, xfcui@email.sdu.edu.cn, zhangfa@ict.ac.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2021

The First High-Quality Reference Genome of Sika Deer Provides Insights for High-Tannin Adaptation

Sika deer are known to prefer oak leaves, which are rich in tannins and toxic to most mammals; however, the genetic mechanisms underlying their unique ability to adapt to living in the jungle are still unclear. In identifying the mechanism responsible for the tolerance of a highly toxic diet, we have made a major advancement in the elucidation of the genomics of sika deer. We generated the first high-quality, chromosome-level genome assembly of sika deer and measured the correlation between tannin intake and RNA expression in 15 tissues through 180 experiments. Comparative genome analyses showed that the UGT and CYP gene families are functionally involved in the adaptation of sika deer to high-tannin food, especially the expansion of UGT genes in a subfamily. The first chromosome-level assembly and genetic characterization of the tolerance toa highly toxic diet suggest that the sika deer genome will serve as an essential resource for understanding evolutionary events and tannin adaptation. Our study provides a paradigm of comparative expressive genomics that can be applied to the study of unique biological features in non-model animals.

genomics↗

bioRxiv2021

Homogeneous environmental selection overturns distance-decay relationship of soil prokaryotic community

Though being fundamental to global diversity distribution, little is known about the geographic pattern of soil microorganisms across different biomes on a large scale. Here, we investigated soil prokaryotic communities from Chinese northern grasslands on a scale up to 4,000 km in both alpine and temperate biomes. Surprisingly, prokaryotic similarities increased with geographic distance after tipping points of 1,760 - 1,920 km, overturning the well-accepted distance-decay relationship and generating a significant U-shape pattern. Such U-shape pattern was likely due to decreased disparities in environmental heterogeneity along with geographic distance when across biomes, as homogeneous environmental selection dominated prokaryotic assembly based on {beta}NTI analysis. Consistently, short-term environmental heterogeneity also followed the U-shape pattern spatially, mainly attributed to dissolved nutrients. In sum, these results demonstrate that homogeneous environmental selection via dissolved nutrients overwhelmed the "distance" effect when across biomes, subverting the previously well-accepted geographic pattern for microbes on a large scale.

ecology↗

bioRxiv2021

PRMT5 regulates ovarian follicle development by facilitating Wt1 translation

Protein arginine methyltransferase 5 (Prmt5) is the major type II enzyme responsible for symmetric dimethylation of arginine. Here, we found PRMT5 was expressed at high level in ovarian granulosa cells of growing follicles. Inactivation of Prmt5 in granulosa cells resulted in aberrant follicle development and female infertility. In Prmt5-knockout mice, follicle development was arrested with disorganized granulosa cells in which WT1 expression was dramatically reduced and the expression of steroidogenesis-related genes was significantly increased. The premature differentiated granulosa cells were detached from oocytes and follicle structure was disrupted. Mechanism studies revealed that Wt1 expression was regulated by PRMT5 at the protein level. PRMT5 facilitated IRES-dependent translation of Wt1 mRNA by methylating HnRNPA1. Moreover, the upregulation of steroidogenic genes in Prmt5-deficient granulosa cells was repressed by Wt1 overexpression. These results demonstrate PRMT5 participates in granulosa cell lineage maintenance by inducing Wt1 expression. Our study uncovers a new role of post-translational arginine methylation in granulosa cell differentiation and follicle development.

developmental biology↗

bioRxiv2021

Attention is all you need for general-purpose protein structure embedding

General-purpose protein structure embedding can be used for many important protein biology tasks, such as protein design, drug design and binding affinity prediction. Recent researches have shown that attention-based encoder layers are more suitable to learn high-level features. Based on this key observation, we treat low-level representation learning and high-level representation learning separately, and propose a two-level general-purpose protein structure embedding neural network, called ContactLib-ATT. On the local embedding level, a simple yet meaningful hydrogen-bond representation is learned. On the global embedding level, attention-based encoder layers are employed for global representation learning. In our experiments, ContactLib-ATT achieves a SCOP superfamily classification accuracy of 82.4% (i.e., 6.7% higher than state-of-the-art method) on the SCOP40 2.07 dataset. Moreover, ContactLib-ATT is demonstrated to successfully simulate a structure-based search engine for remote homologous proteins, and our top-10 candidate list contains at least one remote homolog with a probability of 91.9%. Source codes: https://github.com/xfcui/contactlib.

bioinformatics↗

bioRxiv2021

A Facile and Rapid Route to Self-Digitization of Samples into a High Density Microwell Array for Digital Bioassays

Digital bioassays are powerful methods to detect rare analytes from complex mixtures and study the temporal processes of individual entities within biological systems. In digital bioassays, a crucial first step is the discretization of samples into a large number of identical independent partitions. Here, we developed a rapid and facile sample partitioning method for versatile digital bioassays. This method is based on a detachable self-digitization (DSD) chip which couples a reversible assembly configuration and a predegassing-based self-pumping mechanism to achieve an easy, fast and large-scale sample partitioning. The DSD chip consists of a channel layer used for loading sample and a microwell layer used for holding the sample partitions. Benefitting from its detachability, the chip avoids a lengthy oil flushing process used to remove the excess sample in loading channels and can compartmentalize a sample into more than 100,000 wells of picoliter volume with densities up to 14,000 wells/cm2 in less than 30 s. We also demonstrated the utility of the proposed method by applying it to digital PCR and digital microbial assays.

bioengineering↗

bioRxiv2021

Microtubule-associated ROP interactors both delimit and transduce ROP signaling and regulate microtubule dynamics

Evidence suggests that ICR proteins function as adaptors that mediate ROP signaling. Here, we studied the functions of ICR2 and its homologs ICR5 and ICR3. We showed that ICR2 is a microtubule-associated protein that regulates microtubule dynamics. ICR2 can retrieve activated ROPs from the plasma membrane, and it is recruited to a subset of ROP domains. Secondary cell wall pits in the metaxylem of icr2 and icr5 Arabidopsis single mutants and icr2/icr5 double and icr2/icr5/icr3 triple mutants were denser and larger than those in wild-type Col-0 seedlings, implicating these three ICRs in restriction of ROP function. The icr2 but not the icr5 mutants developed split root hairs further implicating ICR2 in restriction of ROP signaling. Taken together, our results show that ICR2, and likely also ICR5 and ICR3, have multiple functions as ROP effectors and as regulators of microtubule dynamics.

cell biology↗

bioRxiv2021

Single-cell and single-variant resolution analysis of clonal evolution in human liver cancer

Genetic heterogeneity of tumor is closely related to clonal evolution, phenotypic diversity and treatment resistance. Such heterogeneity has been characterized in liver cancer at single-cell sub-chromosomal scale, and a more precise single-variant resolution analysis is lacking. Here we employed a strategy to analyze both the single-cell genomic mutations and transcriptomic changes in 5 patients with liver cancer. Target sequencing was done for a total of 480 single cells in a patient-specific manner. DNA copy number status of point mutations was obtained from single-cell mutational profiling. The clonal structures of liver cancers were then uncovered at single-variant resolution, and mutation combinations in single cells enabled reconstruction of their evolutionary history. A common origin but independent evolutionary fate was revealed for primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. The mutational signature suggested early evolutionary process may be related to specific etiology like aristolochic acids. By parallel single-cell RNA-Seq, the transcriptomic phenotype was found to be related with genetic heterogeneity in liver cancer. We reconstructed the single-cell and single-variant resolution clonal evolutionary history of liver cancer, and dissection of both genetic and phenotypic heterogeneity provides knowledge for mechanistic understanding of liver cancer initiation and progression.

genomics↗

bioRxiv2020

Ontology-Aware Deep Learning Enables Ultrafast, Accurate and Interpretable Source Tracking among Sub-Million Microbial Community Samples from Hundreds of Niches

The taxonomical structure of microbial community sample is highly habitat-specific, making it possible for source tracking niches where samples are originated. Current methods face challenges when the number of samples and niches are magnitudes more than current in use, under which circumstances they are unable to accurately source track samples in a timely manner, rendering them difficult in knowledge discovery from sub-million heterogeneous samples. Here, we introduce a deep learning method based on Ontology-aware Neural Network approach, ONN4MST (https://github.com/HUST-NingKang-Lab/ONN4MST), which takes into consideration the ontology structure of niches and the relationship of samples from these ontologically-organized niches. ONN4MSTs superiority in accuracy, speed and robustness have been proven, for example with an accuracy of 0.99 and AUC of 0.97 in a microbial source tracking experiment that 125,823 samples and 114 niches were involved. Moreover, ONN4MST has been utilized on several source tracking applications, showing that it could provide highly-interpretable results from samples with previously less-studied niches, detect microbial contaminants, and identify similar samples from ontologically-remote niches, with high fidelity.

bioinformatics↗