Biology subjects

Lin, Z.

Publications and source records attributed to Lin, Z..

At least 235 records · Page 13Linked to original sources

bioRxiv2020

In-House Forecasting of Crop Latitude Adaptation through a Daylength-sensing-based Environment Adaptation Simulator (DEAS)

Global climate change necessitates the accelerated breeding of new crop varieties that can sustain yields in new environments. As a proxy for environmental adaptation, the selection of crops that can adapt to different latitudes is an appealing strategy. However, such selection currently involves a lengthy procedure that severely restricts the rapid breeding of varieties. Here, we aimed to combine molecular technologies with an in-house streamlined screening method to facilitate rapid selection for latitude adaptation. We established the Daylength-sensing-based Environment Adaptation Simulator (DEAS) to measure crop latitude adaptation via the transcriptional dynamics of florigen genes at different latitudes. We used different statistical approaches to demonstrate that DEAS predicts the florigen expression profiles in rice with high accuracy. Furthermore, we demonstrated the potential for application of DEAS in different crops. Incorporating DEAS into the breeding programs of conventional and underutilized crops could help meet the future needs for crop adaptation and promote sustainable agriculture.

plant biology↗

bioRxiv2020

Flexible and transparent silver nanowire structures for multifunctional electrical and optical biointerfacing

Transparent microelectrodes have recently emerged as a promising approach to combine electrophysiology with optophysiology for multifunctional biointerfacing. High-performance flexible platforms that allow seamless integration with soft tissue systems for such applications are urgently needed. Here, silver nanowires (Ag NWs)-based transparent microelectrodes and interconnects are designed to meet this demand. The Ag NWs percolating networks are patterned on flexible polymer substrates using an innovative photolithography-based solution-processing technique. The resulting nanowire networks exhibit a high average optical transparency of 76.1-90.0% over the visible spectrum, low normalized electrochemical impedance of 3.4-15 {Omega} cm2 at 1 kHz which is even better than those of opaque solid Ag films, superior sheet resistance of 11-25 {Omega} sq-1, excellent mechanical stability up to 10,000 bending cycles, good biocompatibility and chemical stability. Studies on Langendorff-perfused mouse and rat hearts demonstrate that the Ag NWs microelectrodes enable high-fidelity real-time monitoring of heart rhythm during co-localized optogenetic pacing and optical mapping with negligible light-induced electrical artifacts. This proof-of-concept work illustrates that the solution-processed, transparent, and flexible Ag NWs networks are a promising candidate for the next-generation of large-area multifunctional biointerfaces for interrogating complex biological systems in basic and translational research.

bioengineering↗

bioRxiv2020

DeepPSC (protein structure camera): computer vision-based reconstruction of proteins backbone structure from alpha carbon trace as a case study

Deep learning has been increasingly used in protein tertiary structure prediction, a major goal in life science. However, all the algorithms developed so far mostly use protein sequences as input, whereas the vast amount of protein tertiary structure information available in the Protein Data Bank (PDB) database remains largely unused, because of the inherent complexity of 3D data computation. In this study, we propose Protein Structure Camera (PSC) as an approach to convert protein structures into images. As a case study, we developed a deep learning method incorporating PSC (DeepPSC) to reconstruct protein backbone structures from alpha carbon traces. DeepPSC outperformed all the methods currently available for this task. This PSC approach provides a useful tool for protein structure representation, and for the application of deep learning in protein structure prediction and protein engineering.

bioinformatics↗

bioRxiv2020

A Comprehensive Classification of Coronaviruses and Inferred Cross-Host Transmissions

In this work, we present a unified and robust classification scheme for coronaviruses based on concatenated protein clusters. This subsequently allowed us to infer the apparent "horizontal gene transfer" events via reconciliation with the corresponding gene trees, which we argue can serve as a marker for cross-host transmissions. The cases of SARS-CoV, MERS-CoV, and SARS-CoV-2 are discussed. Our study provides a possible technical route to understand how coronaviruses evolve and are transmitted to humans.

bioinformatics↗

bioRxiv2020

Estimating SNP heritability in presence of population substructure in large biobank-scale data

SNP heritability of a trait is measured by the proportion of total variance explained by the additive effects of genome-wide single nucleotide polymorphisms (SNPs). Linear mixed models are routinely used to estimate SNP heritability for many complex traits. The basic concept behind this approach is to model genetic contribution as a random effect, where the variance of this genetic contribution attributes to the heritability of the trait. This linear mixed model approach requires estimation of relatedness among individuals in the sample, which is usually captured by estimating a genetic relationship matrix (GRM). Heritability is estimated by the restricted maximum likelihood (REML) or method of moments (MOM) approaches, and this estimation relies heavily on the GRM computed from the genetic data on individuals. Presence of population substructure in the data could significantly impact the GRM estimation and may introduce bias in heritability estimation. The common practice of accounting for such population substructure is to adjust for the top few principal components of the GRM as covariates in the linear mixed model. Here we propose an alternative way of estimating heritability in multi-ethnic studies. Our proposed approach is a MOM estimator derived from the Haseman-Elston regression and gives an asymptotically unbiased estimate of heritability in presence of population stratification. It introduces adjustments for the population stratification in a second-order estimating equation and allows for the total phenotypic variance vary by ethnicity. We study the performance of different MOM and REML approaches in presence of population stratification through extensive simulation studies. We estimate the heritability of height, weight and other anthropometric traits in the UK Biobank cohort to investigate the impact of subtle population substructure on SNP heritability estimation.

genetics↗

bioRxiv2020

VirPreNet: A weighted ensemble convolutional neural network for the virulence prediction of influenza A virus using all 8 segments

MotivationInfluenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics. The evolution of influenza viruses remains to be the main obstacle in the effectiveness of antiviral treatments due to rapid mutations. Previous work has been investigated to reveal the determinants of virulence of the influenza A virus. To further facilitate flu surveillance, explicit detection of influenza virulence is crucial to protect public health from potential future pandemics. ResultsIn this paper, we propose a weighted ensemble convolutional neural network for the virulence prediction of influenza A viruses named VirPreNet that uses all 8 segments. Firstly, mouse lethal dose 50 is exerted to label the virulence of infections into two classes, namely avirulent and virulent. A numerical representation of amino acids named ProtVec is applied to the 8-segments in a distributed manner to encode the biological sequences. After splittings and embeddings of influenza strains, the ensemble convolutional neural network is constructed as the base model on the influenza dataset of each segment, which serves as the VirPreNets main part. Followed by a linear layer, the initial predictive outcomes are integrated and assigned with different weights for the final prediction. The experimental results on the collected influenza dataset indicate that VirPreNet achieves state-of-the-art performance combining ProtVec with our proposed architecture. It outperforms baseline methods on the independent testing data. Moreover, our proposed model reveals the importance of PB2 and HA segments on the virulence prediction. We believe that our model may provide new insights into the investigation of influenza virulence. Contactyinr0002@e.ntu.edu.sg Availability and ImplementationCodes and data to generate the VirPreNet are publicly available at https://github.com/Rayin-saber/VirPreNet

bioinformatics↗

bioRxiv2020

IAV-CNN: a 2D convolutional neural network model to predict antigenic variants of influenza A virus

The rapid evolution of influenza viruses constantly leads to the emergence of novel influenza strains that are capable of escaping from population immunity. The timely determination of antigenic variants is critical to vaccine design. Empirical experimental methods like hemagglutination inhibition (HI) assays are time-consuming and labor-intensive, requiring live viruses. Recently, many computational models have been developed to predict the antigenic variants without considerations of explicitly modeling the interdependencies between the channels of feature maps. Moreover, the influenza sequences consisting of similar distribution of residues will have high degrees of similarity and will affect the prediction outcome. Consequently, it is challenging but vital to determine the importance of different residue sites and enhance the predictive performance of influenza antigenicity. We have proposed a 2D convolutional neural network (CNN) model to infer influenza antigenic variants (IAV-CNN). Specifically, we introduce a new distributed representation of amino acids, named ProtVec that can be applied to a variety of downstream proteomic machine learning tasks. After splittings and embeddings of influenza strains, a 2D squeeze-and-excitation CNN architecture is constructed that enables networks to focus on informative residue features by fusing both spatial and channel-wise information with local receptive fields at each layer. Experimental results on three influenza datasets show IAV-CNN achieves state-of-the-art performance combing the new distributed representation with our proposed architecture. It outperforms both traditional machine algorithms with the same feature representations and the majority of existing models in the independent test data. Therefore we believe that our model can be served as a reliable and robust tool for the prediction of antigenic variants.

bioinformatics↗

bioRxiv2020

Hydrazines as versatile chemical biology probes and drug-discovery tools for cofactor-dependent enzymes

Known chemoproteomic probes generally use warheads that tag a single type of amino acid or modified form thereof to identify cases in which its hyper-reactivity underpins function. Much important biochemistry derives from electron-poor enzyme cofactors, transient intermediates and chemically-labile regulatory modifications, but probes for such species are underdeveloped. Here, we have innovated a versatile class of chemoproteomic probes for this less charted hemisphere of the proteome by using hydrazine as the common chemical warhead. Its electron-rich nature allows it to react by both polar and radicaloid mechanisms and to target multiple, pharmacologically important functional classes of enzymes bearing diverse organic and inorganic cofactors. Probe attachment can be blocked by active-site-directed inhibitors, and elaboration of the warhead supports connection of a target to a lead compound. The capacity of substituted hydrazines to profile, discover and inhibit diverse cofactor-dependent enzymes enables cell and tissue imaging and makes this platform useful for enzyme and drug discovery. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/154864v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1e1a54forg.highwire.dtl.DTLVardef@12be680org.highwire.dtl.DTLVardef@129e027org.highwire.dtl.DTLVardef@3b2317_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2020

A reference-guided approach for epigenetic characterization of single cells

The recent advancements in single-cell technologies, including single-cell chromatin accessibility sequencing (scCAS), have enabled profiling the epigenetic landscapes for thousands of individual cells. However, the characteristics of scCAS data, including high dimensionality, high degree of sparsity and high technical variation, make the computational analysis challenging. Reference-guided approach, which utilizes the information in existing datasets, may facilitate the analysis of scCAS data. We present RA3 (Reference-guided Approach for the Analysis of single-cell chromatin Acessibility data), which utilizes the information in massive existing bulk chromatin accessibility and annotated scCAS data. RA3 simultaneously models 1) the shared biological variation among scCAS data and the reference data, and 2) the unique biological variation in scCAS data that identifies distinct subpopulations. We show that RA3 achieves superior performance in many scCAS datasets. We also present several approaches to construct the reference data to demonstrate the wide applicability of RA3.

bioinformatics↗

bioRxiv2020

Genome-wide identification of long non-coding RNAs in the gravid ectoparasite Varroa destructor

Long non-coding RNAs (lncRNAs) emerge as critical regulators with various biological functions in living organisms. However, to date, no systematic characterization of lncRNAs has been investigated in the ectoparasitic mite Varroa destructor, the most severe biotic threat to honey bees worldwide. Here, we performed an initial genome-wide identification of lncRNAs in V. destructor via high-throughput sequencing technology and reported, for the first time, the transcriptomic landscape of lncRNAs in the devastating parasite. By means of a lncRNA identification pipeline, 6,645 novel lncRNA transcripts, encoded by 3,897 gene loci, were identified, including 2,066 sense lncRNAs, 2,772 lincRNAs, and 1,807 lncNATs. Compared with protein-coding mRNAs, V. destructor lncRNAs are shorter in terms of full length, as well as of the ORF length, contain less exons, and express at lower level. GO term and KEGG pathway enrichment analyses of the lncRNA target genes demonstrated that these predicted lncRNAs are likely to play key roles in cellular processes, genetic information processing and environmental responses. To our knowledge, this is the first catalog of lncRNA profile in the parasitiformes species, providing a valuable resource for genetic and genomic studies. Understanding the characteristics and features of lncRNAs in V. destructor would promote sustainable pest control.

genomics↗

bioRxiv2020

The Profiling of Bisecting N-acetylglucosamine (GlcNAc) Modification in Human Amniotic Membrane by Glycomic and Glycoproteomic Analyses

It is acknowledged that the bisecting N-acetylglucosamine (GlcNAc) structure, a GlcNAc linked to the core {beta}-mannose residue via a {beta}1,4 linkage, represents a special type of N-glycosylated modification and has been reported to be involved in various biological processes, such as cell adhesion and fetal development. Clark et al. has found that the majority of N-glycans in human trophoblasts bearing a bisecting GlcNAc. This type of glycan has been reported to help trophoblasts get resistant to natural killer (NK) cell-mediated cytotoxicity, and this would provide a possible explanation for the question how could the mother nourish a fetus within herself without rejection. Herein, we hypothesized that human amniotic membrane which is the last barrier for the fetus may also express bisecting type glycans to protect the fetus. To test this hypothesis, glycomic analysis of human amniotic membrane was performed, and the bisecting N-glycans with high abundance were detected. In addition, we re-analyzed our proteomic data with high fractionation and amino acid sequence coverage from human amniotic membrane, which had been released for the exploration of human missing proteins. The presence of bisecting GlcNAc peptides was revealed and confirmed. A total of 41 glycoproteins with 43 glycopeptides were found to possess a bisecting GlcNAc, 25 of which are for the first time to be reported to have this type of modification. These results provide the profiling of bisecting GlcNAc modification in human amniotic membrane and benefit to the function studies of glycoproteins with bisecting GlcNAc modification and the function studies in immune suppression of human placenta. The mass spectrometry placenta data are available via ProteomeXchange (PXD010630).

cell biology↗

bioRxiv2020

FIRM: Fast Integration of single-cell RNA-sequencing data across Multiple platforms

Single-cell RNA-sequencing (scRNA-seq) is being used extensively to measure the mRNA expression of individual cells from deconstructed tissues, organs, and even entire organisms to generate cell atlas references, leading to discoveries of novel cell types and deeper insight into biological trajectories. These massive datasets are usually collected from many samples using different scRNA-seq technology platforms, including the popular SMART-Seq2 (SS2) and 10X platforms. Inherent heterogeneities between platforms, tissues, and other batch effects makes scRNA-seq data difficult to compare and integrate, especially in large-scale cell atlas efforts; yet, accurate integration is essential for gaining deeper insights into cell biology. Through comprehensive data exploration, we found that accurate integration is often hampered by differences in cell-type compositions. Herein we describe FIRM, an algorithm that addresses this problem and achieves efficient and accurate integration of heterogeneous scRNA-seq datasets across multiple tissue types, platforms, and experimental batches. We applied FIRM to numerous large-scale scRNA-seq datasets from mouse, mouse lemur, and human, comparing its performance in dataset integration with other state-of-the-art methods. FIRM-integrated datasets show accurate mixing of shared cell type identities and superior preservation of original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis. It is also a facile way to transfer cell type labels and annotations from one dataset to another, making it a reliable and versatile tool for scRNA-seq analysis, especially for cell atlas data integration.

bioinformatics↗

bioRxiv2020

Integrate Heterogeneous NGS and TGS Data to Boost Genome-free Transcriptome Research

It is a long-term challenge to undertake reliable transcriptomic research under different circumstances of genome availability. Here, we newly developed a genome-free computational method to aid accurate transcriptome assembly, using the amphioxus as the example. Via integrating ten next generation sequencing (NGS) transcriptome datasets and one third-generation sequencing (TGS) dataset, we built a sequence library of non-redundant expressed transcripts for the amphioxus. The library consisted of overall 91,915 distinct transcripts, 51,549 protein-coding transcripts, and 16,923 novel extragenic transcripts. This substantially improved current amphioxus genome annotation by expanding the distinct gene number from 21,954 to 38,777. We consolidated the library significantly outperformed the genome, as well as de novo method, in transcriptome assembly from multiple aspects. For convenience, we curated the Integrative Transcript Library database of the amphioxus (http://www.bio-add.org/InTrans/). In summary, this work provides a practical solution for most organisms to alleviate the heavy dependence on good quality genome in transcriptome research. It also ensures the amphioxus transcriptome research grounding on reliable data.

bioinformatics↗

bioRxiv2020

MRI-guided histology of TDP-43 knock-in mice implicates parvalbumin interneuron loss, impaired neurogenesis and aberrant neurodevelopment in ALS-FTD

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are overlapping neurodegenerative diseases that are increasingly understood to have long prodromal periods. Investigation of these early stages promises to yield valuable biomarkers of disease and will be key to understanding mechanisms underlying the genesis of ALS-FTD. Here, we use in vivo magnetic resonance imaging (MRI), histology and computed tomography to identify structural and cellular readouts of early stage disease in the TDP-43Q331K knock-in mouse model of ALS-FTD. Adult mutant mice demonstrated parenchymal volume reductions affecting the frontal lobe and entorhinal cortex in a manner reminiscent of ALS-FTD. Subcortical, cerebellar and brain stem regions were also affected in line with observations in presymptomatic carriers of mutations in C9orf72, the commonest genetic cause of both ALS and FTD. Volume loss, as measured by MRI, was also observed in the dentate gyrus (DG) of the hippocampus, along with ventricular enlargement. Guided by these imaging findings, detailed post-mortem brain tissue analysis revealed reduced parvalbumin-positive (PV+) interneurons as a potential cellular correlate of MRI changes in mutant mice. By contrast, microglia were in a disease activated state even in the absence of brain volume loss. A reduction in immature neurons was found in the DG, indicative of impaired adult neurogenesis, while a paucity of PV+ interneurons in juvenile mutant mice (P14) suggests that TDP-43Q331K disrupts neurodevelopment. Computerised tomography imaging also showed altered skull morphology in mutants, further suggesting a role for TDP-43Q331K in development. Finally, analysis of human post-mortem prefrontal cortices confirmed a paucity of PV+ interneurons in the prefrontal cortex in cases with both sporadic ALS and ALS linked to C9orf72 mutations. This study suggests an important role for PV+ interneurons in regional brain vulnerability associated with ALS-FTD, and identifies novel MRI and histological biomarkers that will be of value in assessing the efficacy of putative therapeutics in TDP-43Q331K knock-in mice.

neuroscience↗

bioRxiv2020

YTHDF2 is essential for spermatogenesis and fertility through mediating a wave of transcript transition during spermatogonial differentiation

The dynamic and reversible regulation roles of m6A modification, and the characterization of m6A readers have provided new insights into spermatogenesis at post-transcriptional level. YTHDF2 has been reported to recognize and mediate the m6A-containing transcripts decay during the mouse oocyte mature, embryonic stem cell differentiation, neural development, and zebrafish maternal-to-zygotic transition. However, the roles of YTHDF2 in mammalian spermatogenesis are uncertain. Here, we generated germ cell-specific Ythdf2 mutants (Ythdf2-vKO) at a C57BL/6J background, and demonstrated that YTHDF2 was essential for mouse spermatogenesis and fertility. Ythdf2-vKO provided oligoasthenoteratozoospermia (OAT) phenotype with increased apoptosis in germ cells. High-throughput RNA-seq of the testis tissue showed the failure of the degradation of a wave of YTHDF2 target mRNA. Interestingly, RNA-seq analysis combined with our previous single-cell transcriptomics data of mouse spermatogenesis pointed out the failure of a wave of transcript transition during the spermatogenesis of Ythdf2-vKO, which was confirmed by gene expression analysis of diplotene spermatocytes and round spermatids obtained through fluorescence-activated cell sorting using qPCR. Our study demonstrates the fundamental role of YTHDF2 during mouse spermatogenesis and provides a potential candidate for the diagnosis of male infertility with OAT syndrome. Author summaryMale infertility is becoming a worldwide health problem. Male gamete is generated through spermatogenesis, which is a complicated developmental process with dynamic transcriptome changes. RNA m6A modification has been reported as the most prominently internal mRNA modification, which control the tune of gene expression through mRNA splicing, export, translation and decay. RNA m6A modification is catalyzed by "writers", and could be removed by "erasers". The m6A modification enzymes are reported to play important roles during spermatogenesis. Given that the biological function of m6A modification are mediated through its "readers", its readers might be proposed to be involved in the regulation of spermatogenesis. YTHDF2, as a reader of m6A modification, has been reported to mediate the m6A-containing transcripts decay. To explore the roles of YTHDF2 in spermatogenesis, we used germ cell-specific mutation strategy to knock out the mouse Ythdf2. The mutants provided oligoasthenoteratozoospermia phenotype. Our study demonstrate that YTHDF2 is essential for mouse spermatogenesis. YTHDF2 could be a potential candidate for the diagnosis of oligoasthenoteratozoospermia syndrome.

genetics↗

bioRxiv2020

TRPM7 kinase-mediated immunomodulation in macrophage plays a central role in magnesium ion-induced bone regeneration

The use of magnesium ion (Mg2+)-modified biomaterials in bone regeneration is a promising and cost-effective therapeutic. Despite the widespread observation on the osteogenic effects of Mg2+, the diverse roles played by Mg2+ in the complex biological process of bone healing have not been systematically dissected. Here, we reveal a previously unknown biphasic mode of action of Mg2+ in bone repair. In the early inflammation phase, Mg2+ primarily targets the monocyte-macrophage lineage to promote their recruitment, activation, and polarization. We showed that an increase in extracellular Mg2+ contributes to an upregulated expression of transient receptor potential cation channel member 7 (TRPM7) and a TRPM7-dependent influx of Mg2+ in the monocyte-macrophage lineage, resulting in the cleavage and nuclear accumulation of TRPM7-cleaved kinase fragments (M7CKs). This then triggers the phosphorylation of Histone H3 at serine 10, in a TRPM7-dependent manner at the promoters of inflammatory cytokines like IL-8, leading to the formation of a pro-osteogenic immune microenvironment. In the later active repair/remodeling phase of bone healing, however, continued exposure of Mg2+ and IL-8 leads to over activation of NF-{kappa}B signaling in macrophages, turning the immune microenvironment into pro-osteoclastogenesis. Moreover, the presence of Mg2+ at this stage also decelerates bone maturation through the suppression of hydroxyapatite precipitation. The negative effects of Mg2+ on osteogenesis can override the initial pro-osteogenic benefits of Mg2+, as we found prolonged delivery of Mg2+ compromises overall bone formation. Taken together, this study establishes a paradigm shift in understanding the diverse and multifaceted roles of Mg2+ in bone healing.

cell biology↗

bioRxiv2020

RbAp46/48LIN-53 and HAT-1 are required for initial CENP-AHCP-3 deposition and de novo centromere formation in Caenorhabditis elegans embryos

Foreign DNA microinjected into the Caenorhabditis elegans germline forms episomal extra-chromosomal arrays, or artificial chromosomes (ACs), in embryos. Injected linear, short DNA fragments concatemerize into high molecular weight (HMW)-DNA arrays that are visible as punctate DAPI-stained foci in oocytes, which undergo chromatinization and centromerization in embryos. The inner centromere, inner and outer kinetochore components, including AIR-2, CENP-AHCP-3, Mis18BP1KNL-2 and BUB-1, assemble onto the nascent ACs during the first mitosis. Yet, due to incomplete DNA replication of the nascent ACs, centromeric proteins are not oriented at the poleward faces of the nascent ACs in mitosis, resulting in lagging ACs. The DNA replication efficiency of ACs improves over several cell cycles. We found that a condensin subunit, SMC-4, but not the replicative helicase component, MCM-2, facilitates de novo CENP-AHCP-3 deposition on nascent ACs. Furthermore, H3K9ac, H4K5ac, and H4K12ac are highly enriched on newly chromatinized ACs. HAT-1 and RbAp46/48LIN-53, which are essential for de novo centromere formation and segregation competency of nascent ACs, also hyperacetylate histone H3 and H4. Different from centromere maintenance on endogenous chromosomes, where Mis18BP1KNL-2 functions upstream of RbAp46/48LIN-53, RbAp46/48LIN-53 depletion causes the loss of both CENP-AHCP-3 and Mis18BP1KNL-2 initial deposition at de novo centromeres on ACs.

cell biology↗

bioRxiv2020

DNA Sequence Preference for De Novo Centromere Formation on a Caenorhabditis elegans Artificial Chromosome

Centromeric DNA sequences vary in different species, but share common characteristics, like high AT-content, repetitiveness, and low, but not no, transcriptional activity. Yet, neocentromeres can be found on non-centromeric, ectopic sequences, suggesting that centromeres can be established and maintained epigenetically. In contrast, canonical centromeric DNA sequences are more competent in de novo centromere formation on artificial chromosomes (ACs). To determine if specific DNA sequence features are preferred for new centromere formation, we injected different DNA sequences into the gonad of a holocentric model organism, Caenorhabditis elegans, to form ACs in embryos, and monitored mitotic AC segregation. We demonstrated that AT-rich sequences, but not repetitive sequences, accelerated de novo centromere formation on ACs. We also injected fragmented Saccharomyces cerevisiae genomic DNA to construct a less repetitive, more complex AC that can propagate through generations. By whole-genome sequencing and de novo assembly of AC sequences, we deduced that this AC was formed through non-homologous end joining. By CENP-AHCP-3 chromatin immunoprecipitation followed by sequencing (ChIP-seq), we found that CENP-AHCP-3 domain width on both the AC and endogenous chromosomes is positively correlated with AT-content. Besides, CENP-AHCP-3 binds to unexpressed gene loci or non-genic regions on the AC, consistent with the organization of endogenous holocentromeres.

cell biology↗