Biology subjects

He, F.

Publications and source records attributed to He, F..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

Staphylococcus aureus nt5 gene contributes to bacterial infection ability to form kidney abscess

Staphylococcus aureus (S. aureus) is a commonly conditional infection pathogen, in which several key virulence genes are responsible for bacterial infection ability. The S. aureus nt5 gene, encoding 5-nucleotidase, mediates bacterial nucleic acid pathway, yet it is nearly unknown of nt5 function for staphylococcal infection ability. Herein we have constructed S. aureus mutant with the gene nt5C166T silence (S. aureus {Delta}nt5) by a CRISPR RNA-guided base editing system to investigate bacterial infection ability in vitro and in vivo. As expected, several nt5-related genes are disturbed in S. aureus {Delta}nt5, in which gene transcription level of py is decreased compared with the wild-type S. aureus. Bacterial gene nt5 is downregulated and py/adk are upregulated when S. aureus is exposed to antibiotics daptomycin, which indicates nt5-mediated nucleic acid pathway is interfered upon with daptomycin treatment. Furthermore, the mutant {Delta}nt5 displays about a 40-fold reduction of bacterial loading in mouse kidney on a mouse sepsis model, and the infection ability of {Delta}nt5 is reduced than the wild-type bacteria. The gene nt5 contributes to S. aureus-infected abscess formation in mouse kidney, and the silence of nt5 gene promotes phagocytosis of S. aureus by mouse and human immunocytes. In general, our findings reveal nt5 silence impedes bacterial loading in kidney to form abscess but enhances S. aureus to be phagocytosed by host cell immune system in vitro and in vivo, which indicates that nt5 gene plays an important role in bacterial infection and immune evasion.

immunology↗

bioRxiv2022

Data-driven dynamical modelling of a pathogen-infected plant gene regulatory network: a comparative analysis

Recent advances in synthetic biology have enabled the design of genetic feedback control circuits that could be implemented to build resilient plants against pathogen attacks. To facilitate the proper design of these genetic feedback control circuits, an accurate model that is able to capture the vital dynamical behaviour of the pathogen-infected plant is required. In this study, using a data-driven modelling approach, we develop and compare four dynamical models (i.e. linear, Michaelis-Menten, standard S-System and extended S-System) of a pathogen-infected plant gene regulatory network (GRN). These models are then assessed across several criteria, i.e. ease of identifying the type of gene regulation, the predictive capability, Akaike Information Criterion (AIC) and the robustness to parameter uncertainty to determine its viability of modelling the pathogen-infected plant GRN. Using our defined ranking score, our analyses show that while the extended S-System model ranks highest in the overall comparison, the performance of the linear model is more consistent throughout the comparison, making it the preferred model for this pathogen-infected plant GRN.

systems biology↗

bioRxiv2021

Progressive polysomal association of Upf1, Upf2, and Upf3 as ribosomes traverse mRNA coding regions

Upf1, Upf2, and Upf3 are the central regulators of nonsense-mediated mRNA decay (NMD), the eukaryotic mRNA quality control pathway generally triggered when a premature termination codon is recognized by the ribosome. The NMD-related functions of the Upf proteins likely commence while these factors are ribosome-associated, but little is known of the timing of their ribosome binding, their specificity for ribosomes translating NMD substrates, or the nature and role of any ribosome:Upf complexes. Here, we have elucidated details of the ribosome-associated steps of NMD. By combining yeast genetics with selective ribosome profiling and co-sedimentation analyses of polysomes with wild-type and mutant Upf proteins, our approaches have identified distinct states of ribosome:Upf association. All three Upf factors manifest progressive polysome association as mRNA translation proceeds, but these events appear to be preceded by formation of a Upf1:80S complex as mRNAs initiate translation. This complex is likely executing an early mRNA surveillance function.

molecular biology↗

bioRxiv2021

Molecular evolution of classic Hodgkin lymphoma revealed through whole genome sequencing of Hodgkin and Reed Sternberg cells

The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells within a classic Hodgkin lymphoma (cHL) biopsy limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Here we leveraged this method to report the first whole genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events prior to the clinical diagnosis of cHL. We identified alterations in driver genes not previously described in cHL, a high activity of the APOBEC mutational signature, and the presence complex structural variants including chromothripsis. We found that the high ploidy observed in cHL is often acquired through multiple, independent large chromosomal gain events including whole genome duplication. The first of these likely occurs several years prior to the diagnosis of cHL, and the last gains typically occur very close to the time of diagnosis. Evolutionary timing analyses revealed that driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID driven mutagenesis usually preceded large chromosomal gains. The study provides the first temporal reconstruction of cHL pathogenesis and suggests a relatively long time course between the first pathogenic event and the clinical diagnosis.

cancer biology↗

bioRxiv2021

Structure Determination of Inactive-State GPCRs with a Universal Nanobody

Cryogenic electron microscopy (cryo-EM) has widened the field of structure-based drug discovery by allowing for routine determination of membrane protein structures previously intractable. However, despite representing one of the largest classes of therapeutic targets, most inactive-state G protein-coupled receptors (GPCRs) have remained inaccessible for cryo-EM because their small size and membrane-embedded nature impedes projection alignment for high-resolution map reconstructions. Here we demonstrate that the same single-chain camelid antibody (nanobody) recognizing a grafted intracellular loop can be used to obtain cryo-EM structures of different inactive-state GPCRs at resolutions comparable or better than those obtained by X-ray crystallography. Using this approach, we obtained the structure of human neurotensin 1 receptor (NTSR1) bound to antagonist SR48692, of {micro}-opioid receptor (MOR) bound to the clinical antagonist alvimopan, as well as the structures of the previously uncharacterized somatostatin receptor 2 (SSTR2) in the apo state and histamine receptor 2 (H2R) bound to the H2 blocker famotidine. Each of these structures yields novel insights into ligand binding and specificity. We expect this rapid, straightforward approach to facilitate the broad structural exploration of GPCR inactive states without the need for extensive engineering and crystallization.

biophysics↗

bioRxiv2021

A Kernel-based Nonlinear Manifold Learning for EEG Channel Selection with Application to Alzheimer's Disease

For the characterisation and diagnosis of neurological disorders, dynamical, causal and crossfrequency coupling analysis using the EEG has gained considerable attention. Due to high computational costs in implementing some of these methods, the selection of important EEG channels is crucial. The channel selection method should be able to accommodate non-linear and spatiotemporal interactions among EEG channels. In neuroscience, different measures of (dis)similarity are used to quantify functional connectivity between EEG channels. Brain regions functionally connected under one measure do not necessarily imply the same with another measure, as they could even be disconnected. Therefore, developing a generic measure of (dis)similarity is important in channel selection. In this paper, learning of spatial and temporal structures within the data is achieved by using kernel-based nonlinear manifold learning, where the positive semi-definite kernel is a generalisation of various (dis)similarity measures. We introduce a novel EEG channel selection method to determine which channel interrelationships are more important for the in-depth neural dynamical analysis, such as understanding the effect of neurodegeneration, e.g. Alzheimers disease (AD), on global and local brain dynamics. The proposed channel selection methodology uses kernel-based nonlinear manifold learning via Isomap and Gaussian Process Latent Variable Model (Isomap-GPLVM). The Isomap-GPLVM method is employed to learn the spatial and temporal local similarities and global dissimilarities present within the EEG data structures. The resulting kernel (dis)similarity matrix is used as a measure of synchrony, i.e. linear and nonlinear functional connectivity, between EEG channels. Based on this information, linear Support Vector Machine (SVM) classification with Monte-Carlo cross-validation is then used to determine the most important spatio-temporal channel inter-relationships that can well distinguish a group of patients from a cohort of age-matched healthy controls (HC). In this work, the analysis of EEG data from HC and patients with mild to moderate AD is presented as a case study. Considering all pairwise EEG channel combinations, our analysis shows that functional connectivity between bipolar channels within temporal, parietal and occipital regions can distinguish well between mild to moderate AD and HC groups. Furthermore, while only considering connectivity with respect to each EEG channel. Our results indicate that connectivity of EEG channels along the fronto-parietal with other channels are important in diagnosing mild to moderate AD.

neuroscience↗

bioRxiv2021

Dcp2 C-terminal Cis-Binding Elements Control Selective Targeting of the Decapping Enzyme by Forming Distinct Decapping Complexes

A single Dcp1-Dcp2 decapping enzyme targets diverse classes of yeast mRNAs for decapping-dependent 5 to 3 decay, but the molecular mechanisms controlling selective mRNA targeting by the enzyme remain elusive. Through extensive genetic analyses we uncover cis-regulatory elements in the Dcp2 C-terminal domain that control selective targeting of the decapping enzyme by forming distinct decapping complexes. Two Upf1-binding motifs target the decapping enzyme to NMD substrates, and a single Edc3-binding motif targets both Edc3 and Dhh1 substrates. Pat1-binding leucine-rich motifs target Edc3 and Dhh1 substrates under selective conditions. Although it functions as a unique targeting component of specific complexes, Edc3 is a common component of multiple complexes. Xrn1 also has a specific Dcp2 binding site, allowing it to be directly recruited to decapping complexes. Collectively, our results demonstrate that Upf1, Edc3, and Pat1 function as regulatory subunits of the holo-decapping enzyme, controlling both its targeting specificity and enzymatic activation. HighlightsLoss of Dcp2 cis-binding elements causes selective stabilization of distinct decapping substrates Dcp2 cis-binding elements promote the assembly of target-specific decapping complexes in vivo Xrn1 binds to Dcp2, and both Edc3 and Xrn1 are common components of multiple decapping complexes Upf1, Edc3, and Pat1 function as unique targeting subunits of the yeast holo-decapping enzyme

molecular biology↗

bioRxiv2021

Genome sequencing of white-blotched river stingray (Potamotrygon leopoldi) provides novel clues for niche-adaptation and skeleton formation

The white-blotched river stingray (Potamotrygon leopoldi) is a cartilaginous fish native to the Xingu River, a tributary of the Amazon River system. It possesses a lot of unique biological features such as disc-like body shape, bizarre color pattern and living in freshwater habitat while most stingrays and their close relatives are sea dwellers. As a member of the Potamotrygonidae family, P. leopoldi bears evolutionary signification in fish phylogeny, niche adaptation and skeleton formation. In this study, we present its draft genome of 4.11 Gb comprised of 16,227 contigs and 13,238 scaffolds, which has contig N50 of 3,937 kilobases and scaffold N50 of 5,675 kilobases in size. Our analysis shows that P. leopoldi is a slow-evolving fish, diverged from elephant shark about 96 million years ago. We find that two gene families related to immune system, immunoglobulin heavy constant delta genes, and T-cell receptor alpha/delta variable genes, stand out expanded in P. leopoldi only, suggesting robustness in response to freshwater pathogens in adapting novel environments. We also identified the Hox gene clusters in P. leopoldi and discovered that seven Hox genes shared by five representative fishes are missing in P. leopoldi. The RNA-seq data from P. leopoldi and other three fish species demonstrate that fishes have a more diversified tissue expression spectrum as compared to the corresponding mammalian data. Our functional studies suggest that the lack of genes encoding vitamin D-binding protein in cartilaginous (both P. leopoldi and Callorhinchus milii) fishes could partly explain the absence of hard bone in their endoskeleton. Overall, this genome resource provides new insights into the niche-adaptation, body plan and skeleton formation of P. leopoldi as well as the genome evolution in cartilaginous fish.

genomics↗

bioRxiv2021

Bispectrum-based Cross-frequency Functional Connectivity: A Study of Alzheimer's Disease

Alzheimers disease (AD) is a neurodegenerative disorder known to affect functional connectivity (FC) across many brain regions. Linear FC measures have been applied to study the differences in AD by splitting neurophysiological signals, such as electroencephalography (EEG) recordings, into discrete frequency bands and analysing them in isolation from each other. We address this limitation by quantifying cross-frequency FC in addition to the traditional within-band approach. Cross-bispectrum, a higher-order spectral analysis approach, is used to measure the nonlinear FC and is compared with the cross-spectrum, which only measures the linear FC within bands. This work reports the reconstruction of a cross-frequency FC network where each frequency band is treated as a layer in a multilayer network with both inter- and intra-layer edges. Cross-bispectrum detects cross-frequency differences, mainly increased FC in AD cases in{delta} -{theta} coupling. Overall, increased strength of low-frequency coupling and decreased level of high-frequency coupling is observed in AD cases in comparison to healthy controls (HC). We demonstrate that a graph-theoretic analysis of cross-frequency brain networks is crucial to obtain a more detailed insight into their structure and function. Vulnerability analysis reveals that the integration and segregation properties of networks are enabled by different frequency couplings in AD networks compared to HCs. Finally, we use the reconstructed networks for classification. The extra cross-frequency coupling information can improve the classification performance significantly, suggesting an important role of cross-frequency FC. The results highlight the importance of studying nonlinearity and including cross-frequency FC in characterising AD.

neuroscience↗

bioRxiv2021

RESEPT: tissue architecture inference and visualization from spatially resolved transcriptomics

Spatially resolved transcriptomics provides a new way to define spatial contexts and understand biological functions in complex diseases. Although some computational frameworks can characterize spatial context via various clustering methods, the detailed spatial architectures and functional zonation often cannot be revealed and localized due to the limited capacities of associating spatial information. We present RESEPT, a deep-learning framework for characterizing and visualizing tissue architecture from spatially resolved transcriptomics. Given inputs as gene expression or RNA velocity, RESEPT learns a three-dimensional embedding with a spatial retained graph neural network from the spatial transcriptomics. The embedding is then visualized by mapping as color channels in an RGB image and segmented with a supervised convolutional neural network model. Based on a benchmark of sixteen 10x Genomics Visium spatial transcriptomics datasets on the human cortex, RESEPT infers and visualizes the tissue architecture accurately. It is noteworthy that, for the in-house AD samples, RESEPT can localize cortex layers and cell types based on a pre-defined region-or cell-type-specific genes and furthermore provide critical insights into the identification of amyloid-beta plaques in Alzheimers disease. Interestingly, in a glioblastoma sample analysis, RESEPT distinguishes tumor-enriched, non-tumor, and regions of neuropil with infiltrating tumor cells in support of clinical and prognostic cancer applications.

bioinformatics↗

bioRxiv2021

Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

genomics↗

bioRxiv2021

The haplotype-based analysis of Aegilops tauschii introgression into hard red winter wheat and its impact on productivity traits

Introgression from wild relatives have a great potential to broaden beneficial allelic diversity available for crop improvement in breeding programs. Here, we assessed the impact of introgression from 21 diverse accessions of Aegilops tauschii, the diploid ancestor of the wheat D genome, into six hard red winter wheat cultivars on yield and yield component traits. We used 5.2 million imputed D genome SNPs identified by whole-genome sequencing of parental lines and the sequence-based genotyping of introgression population including 351 BC1F3:5 lines. Phenotyping data collected from the irrigated and non-irrigated field trials revealed that up to 23% of the introgression lines produce more grain than the parents and check cultivars. Based on sixteen yield stability statistics, the yield of twelve introgression lines (3.4%) was stable across treatments, years and locations; five of these lines were also high yielding, producing 9.8% more grain than the average yield of check cultivars. The most significant SNP-trait and haplotype-trait associations were identified on chromosome arms 2DS and 6DL for spikelet number per spike (SNS), on chromosome arms 2DS, 3DS, 5DS and 7DS for grain length and on chromosome arms 1DL, 2DS, 6DL and 7DS for grain width. Introgression of haplotypes from Ae. tauschii parents was associated with increase in SNS, which positively correlated with heading date, whereas haplotypes from hexaploid wheat parents were associated with increased grain width. We show that haplotypes on 2DS associated with increased spikelet number and heading date are linked with multiple introgressed alleles of Ppd-D1 identified by the whole-genome sequencing of the Ae. tauschii parents. While some introgressed haplotypes exhibited significant pleiotropic effects with the direction of effects on the yield component traits being largely consistent with the previously reported trade-offs, there were haplotype combinations associated with the positive trends in yield. The characterized repertoire of the introgressed haplotypes derived from Ae. tauschii accessions with the combined positive effects on yield and yield components traits in elite germplasm provides a valuable source of alleles for improving the productivity of winter wheat by optimizing the contribution of component traits to yield.

genetics↗

bioRxiv2021

TMPs Interaction Domain: A Discovery of Structural Universality Among TMPs Interaction Sites Using Deep Learning Method

Transmembrane proteins (TMPs) serve as important drug targets and accounts for nearly half of the drugs currently available in the market. Research into TMPs interactions and their structural basis will provide key information for drug research and new drug development. Based on previous works like a binding pocket or binding site, our main purpose in this study is to find whether the structural universality (Interaction Domain) exists in all kinds of TMPs interaction regions through a computational approach. After implementing the experiments using our 3D deep learning model and achieve the Matthews correlation coefficient (MCC) of 0.36, we found strong evidence for the existence of the structural basis among TMPs interaction regions. That means those regions, or we call them interaction domains, are structural specific distinguishing to the domains without any interaction. According to this, this work provides a new theoretical basis for TMPs interaction research and can greatly boost the development of the drug industry.

bioinformatics↗

bioRxiv2021

Insights into the susceptibility of rice to a floral disease

Crop floral diseases are economically important as they reduce grain yield and quality and even introduce food toxins. Rice false smut has emerged as a serious floral disease producing mycotoxins. However, very little is known on the interaction mechanisms between rice flower and the causal fungus Ustilaginoidea virens. Here we show that a conserved anti-fungal immunity in rice flower is disarmed by U. virens via a secreted protein UvChi1. UvChi1 functioned as an essential virulence factor and directly interacted with the chitin receptor CEBiP and co-receptor CERK1 in rice to disrupt their oligomerizations and subsequent immune responses. Moreover, intraspecific-conserved UvChi1 could target OsCEBiP/OsCERK1 receptor complex in at least 98.5% of 5232 surveyed rice accessions. These results demonstrate that U. virens utilizes a crucial virulence factor to subvert chitin-triggered flower immunity in most rice varieties, providing new insights into the susceptibility of rice to false smut disease. One Sentence SummaryThe fungal pathogen Ustilaginoidea virens disarms chitin-triggered immunity in rice flower via a secreted chitinase.

plant biology↗

bioRxiv2021

Assembly of chromosome-scale and allele-aware autotetraploid genome of the Chinese alfalfa cultivar Zhongmu-4 and identification of SNP loci associated with 27 agronomic traits

Alfalfa (Medicago sativa L.), the most valuable perennial legume crop, referred to as "Queen of the Forages" for its high nutritional value and yield production among forage crops. Comprehensive genomic information of germplasm resources from different ecological regions and modern breeding strategies, such as molecular-marker assisted breeding are of great importance to breed new alfalfa varieties with environmental resilience. Here, we report assembly of the genome sequence of Zhongmu-4 (ZM-4), one of the most planted cultivars in China, and identification of SNPs associated with alfalfa agronomic traits by Genome-wide Association Studies (GWAS). Sequence of 32 allelic chromosomes was assembled successfully by single molecule real time sequencing and Hi-C technique with ALLHiC algorithm. About 2.74 Gbp contigs, accounting for 88.39% of the estimated genome, were assembled with 2.56 Gbp contigs anchored to 32 pseudo-chromosomes. In comparison with M. truncatula A17, distinctive inversion and translocation on chromosome 1, and between chromosome 4 and 8, respectively, were detected. Moreover, we conducted resequencing of 220 alfalfa accessions collected globally and performed GWAS analysis based on our assembled genome. Population structure analysis demonstrated that alfalfa has a complex genetic relationship among germplasm with different geographic origins. GWAS identified 101 SNPs associated with 27 out of 93 agronomic traits. The updated chromosome-scale and allele-aware genome sequence, coupled with the resequencing data of most global alfalfa germplasm, provides valuable information for alfalfa genetic research, and further analysis of major SNP loci will accelerate unravelling the molecular basis of important agronomic traits and facilitate genetic improvement of alfalfa.

plant biology↗

bioRxiv2020

Transcriptome-wide investigation of stop codon readthrough in Saccharomyces cerevisiae

Translation of mRNA into a polypeptide is terminated when the release factor eRF1 recognizes a UAA, UAG, or UGA stop codon in the ribosomal A site and stimulates nascent peptide release. However, stop codon readthrough can occur when a near-cognate tRNA outcompetes eRF1 in decoding the stop codon, resulting in the continuation of the elongation phase of protein synthesis. At the end of a conventional mRNA coding region, readthrough allows translation into the mRNA 3-UTR. Previous studies with reporter systems have shown that the efficiency of termination or readthrough is modulated by cis-acting elements other than stop codon identity, including two nucleotides 5 of the stop codon, six nucleotides 3 of the stop codon in the ribosomal mRNA channel, and stem-loop structures in the mRNA 3-UTR. It is unknown whether these elements are important at a genome-wide level and whether other mRNA features proximal to the stop codon significantly affect termination and readthrough efficiencies in vivo. Accordingly, we carried out ribosome profiling analyses of yeast cells expressing wild-type or temperature-sensitive eRF1 and developed bioinformatics strategies to calculate readthrough efficiency, and to identify mRNA and peptide features which influence that efficiency. We found that the stop codon (nt +1 to +3), the nucleotide after it (nt +4), the codon in the P site (nt -3 to -1), and 3-UTR length are the most influential features in the control of readthrough efficiency, while nts +5 to +9 and mRNA secondary structure in the 3-UTR had milder effects. Additionally, we found low readthrough genes to have shorter 3-UTRs compared to high readthrough genes in cells with thermally inactivated eRF1, while this trend was reversed in wild-type cells. Together, our results demonstrated the general roles of known regulatory elements in genome-wide regulation and identified several new mRNA or peptide features affecting the efficiency of translation termination and readthrough. AUTHOR SUMMARYOf the 64 codons that exist for translation of the genetic code into a polypeptide chain, only UAA, UAG, and UGA signify termination of continued protein synthesis. However, the efficiency of termination is not the same for different mRNAs and is likely influenced by mRNA sequences proximal to these "stop" codons. Here, we sought to expand current understanding of termination efficiency to a genome-wide scale. Our analysis identifies novel mRNA features that may regulate the efficiency of translation termination, including the identities of the stop codon, the penultimate codon, the proximal nucleotides, and the length of mRNA 3-untranslated region. As [~]11% of human diseases are caused by mutations that introduce premature stop codons, resulting in both accelerated mRNA decay and truncated protein product, our findings are valuable for understanding and developing therapeutics targeting the termination step of mRNA translation.

genetics↗

bioRxiv2020

Expanding the range of editable targets in the wheat genome using the variants of the Cas12a and Cas9 nucleases

The development of CRISPR-based editors having different protospacer adjacent motif (PAM) recognition specificities, or guide RNA length/structure requirements broadens the range of possible genome editing applications. Here, we evaluated the natural and engineered variants of Cas12a (FnCas12a from Francisella novicida and LbCas12a from Lachnospiraceae bacterium) and Cas9 for wheat genome editing efficiency and ability to induce heritable mutations in endogenous genes controlling important agronomic traits in wheat. Unlike FnCas12a, LbCas12a was able to induce mutations in the wheat genome in the current study, even though with a lower rate than that reported for SpCas9. The eight-fold improvement in the gene editing efficiency was achieved for LbCas12a by using the guide RNAs flanked by ribozymes and driven by the RNA polymerase II promoter from switchgrass. The efficiency of multiplexed genome editing (MGE) using LbCas12a was mostly similar to that obtained using the simplex RNA guides. A LbCas12a-MGE construct was successfully applied for generating heritable mutations in a gene controlling grain size and weight in wheat. We show that the range of editable loci in the wheat genome could be expanded by using the engineered variants of Cas12a (LbCas12a-RVR) and Cas9 (Cas9-NG and xCas9) that recognize the TATV and NG PAMs, respectively, with the Cas9-NG showing higher editing efficiency on the targets with atypical PAMs compared to xCas9. In conclusion, our study reports the set of validated natural and engineered variants of Cas12a and Cas9 editors for targeting loci in the wheat genome not amenable to Cas9-based modification.

genetics↗

bioRxiv2020

Nonlinear System Identification of Neural Systems from Neurophysiological Signals

The human nervous system is one of the most complicated systems in nature. Complex nonlinear behaviours have been shown from the single neuron level to the system level. For decades, linear connectivity analysis methods, such as correlation, coherence and Granger causality, have been extensively used to assess the neural connectivities and input-output interconnections in neural systems. Recent studies indicate that these linear methods can only capture a small amount of neural activities and functional relationships, and therefore cannot describe neural behaviours in a precise or complete way. In this review, we highlight recent advances in nonlinear system identification of neural systems, corresponding time and frequency domain analysis, and novel neural connectivity measures based on nonlinear system identification techniques. We argue that nonlinear modelling and analysis are necessary to study neuronal processing and signal transfer in neural systems quantitatively. These approaches can hopefully provide new insights to advance our understanding of neurophysiological mechanisms underlying neural functions. These nonlinear approaches also have the potential to produce sensitive biomarkers to facilitate the development of precision diagnostic tools for evaluating neurological disorders and the effects of targeted intervention.

neuroscience↗