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He, G.

Publications and source records attributed to He, G..

At least 55 records · Page 3Linked to original sources

A bi-kinase module sensitizes and potentiates plant immune signaling

Systemic signaling is an essential hallmark of multicellular life. Pathogen encounter occurs locally but triggers organ-scale and organismic immune responses. In plants, elicitor perception provokes systemically expanding Ca2+ and H2O2 signals conferring immunity. Here, we identify a Ca2+ sensing bi-kinase module as becoming super-activated through mutual trans-phosphorylation and imposing synergistically enhanced NADPH oxidase activation. A combined two-layer bi-kinase/substrate phospho-code allows for sensitized signaling initiation already by near-resting elevations of Ca2+ concentration at the infection site. Subsequently, it facilitates further signal wave proliferation with minimal amplitude requirement, triggering protective defense responses throughout the plant. Our study reveals how plants build and perpetuate trans-cellular immune signal proliferation while avoiding disturbance of ongoing cellular signaling along the path of response dissemination. One sentence summaryMutual trans-activation of a Ca2+ sensing bi-kinase module potentiates NADPH oxidase activation to facilitate systemic immunity.

plant biology↗

Seagrass genomes reveal a hexaploid ancestry facilitating adaptation to the marine environment

Seagrasses comprise the only submerged marine angiosperms, a feat of adaptation from three independent freshwater lineages within the Alismatales. These three parallel lineages offer the unique opportunity to study convergent versus lineage-specific adaptation to a fully marine lifestyle. Here, we present chromosome-level genome assemblies from a representative species of each of the seagrass lineages - Posidonia oceanica (Posidoniaceae), Cymodocea nodosa (Cymodoceaceae), and Thalassia testudinum (Hydrocharitaceae) - along with an improved assembly for Zostera marina (Zosteraceae). We also include a draft genome of Potamogeton acutifolius, a representative of Potamogetonaceae, the freshwater sister lineage to the Zosteraceae. Genome analysis reveals that all seagrasses share an ancient whole genome triplication (WGT) event, dating to the early evolution of the Alismatales. An additional whole genome duplication (WGD) event was uncovered for C. nodosa and P. acutifolius. Dating of ancient WGDs and more recent bursts of transposable elements correlate well with major geological and recent climatic events, supporting their role as rapid generators of genetic variation. Comparative analysis of selected gene families suggests that the transition from the submerged-freshwater to submerged-marine environment did not require revolutionary changes. Major gene losses related to, e.g., stomata, volatiles, defense, and lignification, are likely a consequence of the submerged lifestyle rather than the cause ( use it or lose it). Likewise, genes, often retained from the WGD and WGT, were co-opted for functions requiring the alignment of many small adaptations ( tweaking), e.g., osmoregulation, salinity, light capture, carbon acquisition, and temperature. Our ability to manage and conserve seagrass ecosystems depends on our understanding of the fundamental processes underpinning their resilience. These new genomes will accelerate functional studies and are expected to contribute to transformative solutions -- as continuing worldwide losses of the savannas of the sea are of major concern in times of climate change and loss of biodiversity.

evolutionary biology↗

Ketamine Effects on Energy Metabolism, Functional Connectivity and Working Memory in Healthy Humans

Working memory (WM) is a crucial resource for temporary memory storage and the guiding of ongoing behavior. N-methyl-D-aspartate glutamate receptors (NMDARs) are thought to support the neural underpinnings of WM. Ketamine is an NMDAR antagonist that has cognitive and behavioral effects at subanesthetic doses. To shed light on subanesthetic ketamine effects on brain function, we employed a multimodal imaging design, combining gas-free calibrated functional magnetic resonance imaging (fMRI) measurement of oxidative metabolism (CMRO2), resting-state cortical functional connectivity assessed with fMRI, and WM-related fMRI. Healthy subjects participated in two scan sessions in a randomized, double-blind, placebo-controlled design. Ketamine increased CMRO2 and cerebral blood flow (CBF) in prefrontal cortex (PFC) and other cortical regions. However, resting-state cortical functional connectivity was not affected. Ketamine did not alter CBF-CMRO2 coupling brain-wide. Higher levels of basal CMRO2 were associated with lower task-related PFC activation and WM accuracy impairment under both saline and ketamine conditions. These observations suggest that CMRO2 and resting-state functional connectivity index distinct dimensions of neural activity. Ketamines impairment of WM-related neural activity and performance appears to be related to its ability to produce cortical metabolic activation. This work illustrates the utility of direct measurement of CMRO2 via calibrated fMRI in studies of drugs that potentially affect neurovascular and neurometabolic coupling.

neuroscience↗

GraphGPSM: a global scoring model for protein structure using graph neural networks

The scoring models used for protein structure modeling and ranking are mainly divided into unified field and protein-specific scoring functions. Although protein structure prediction has made tremendous progress since CASP14, the modeling accuracy still cannot meet the requirements to a certain extent. Especially, accurate modeling of multi-domain and orphan proteins remains a challenge. Therefore, an accurate and efficient protein scoring model should be developed urgently to guide the protein structure folding or ranking through deep learning. In this work, we propose a protein structure global scoring model based on equivariant graph neural network (EGNN), named GraphGPSM, to guide protein structure modeling and ranking. We construct an EGNN architecture, and a message passing mechanism is designed to update and transmit information between nodes and edges of the graph. Finally, the global score of the protein model is output through a multilayer perceptron. Residue-level ultrafast shape recognition is used to describe the relationship between residues and the overall structure topology, and distance and direction encoded by Gaussian radial basis functions are designed to represent the overall topology of the protein backbone. These two features are combined with Rosetta energy terms, backbone dihedral angles, and inter-residue distance and orientations to represent the protein model and embedded into the nodes and edges of the graph neural network. The experimental results on the CASP13, CASP14, and CAMEO test sets show that the scores of our developed GraphGPSM have a strong correlation with the TM-score of the models, which are significantly better than those of the unified field score function REF2015 and the state-of-the-art local lDDT-based scoring models ModFOLD8, ProQ3D, and DeepAccNet etc. The modeling experimental results on 484 test proteins demonstrate that GraphGPSM can greatly improve the modeling accuracy. GraphGPSM is further used to model 35 orphan proteins and 57 multi-domain proteins. The results show that the average TM-score of the models predicted by GraphGPSM is 13.2% and 7.1% higher than that of the models predicted by AlphaFold2. GraphGPSM also participates in CASP15 and achieves competitive performance in global accuracy estimation.

bioinformatics↗

Differentiated genomic footprints and connections inferred from 440 Hmong-Mien genomes suggest their isolation and long-distance migration

BackgroundThe underrepresentation of Hmong-Mien (HM) people in Asian genomic studies has hindered our comprehensive understanding of population history and human health. South China is an ethnolinguistically diverse region and indigenously settled by ethnolinguistically diverse HM, Austroasiatic (AA), Tai-Kadai (TK), Austronesian (AN), and Sino-Tibetan (ST) people, which is regarded as East Asias initial cradle of biodiversity. However, previous fragmented genetic studies have only presented a fraction of the landscape of genetic diversity in this region, especially the lack of haplotype-based genomic resources. The deep characterization of demographic history and natural-selection-relevant architecture in HM people was necessary. ResultsWe comprehensively reported the population-specific genomic resources and explored the fine-scale genetic structure and adaptative features inferred from the high-density SNP data in 440 individuals from 34 ethnolinguistic populations, including previously unreported She. We identified solid genetic differentiation between inland (Miao/Yao) and coastal (She) southern Chinese HM people, and the latter obtained more gene flow from northern East Asians. Multiple admixture models further confirmed that extensive gene flow from surrounding ST, TK, and AN people entangled in forming the gene pool of coastal southeastern East Asian HM people. Population genetic findings of isolated shared unique ancestral components based on the sharing alleles and haplotypes deconstructed that HM people from Yungui Plateau carried the breadth of genomic diversity and previously unknown genetic features. We identified a direct and recent genetic connection between Chinese and Southeast Asian HM people as they shared the most extended IBD fragments, supporting the long-distance migration hypothesis. Uniparental phylogenetic topology and Network relationship reconstruction found ancient uniparental lineages in southwestern HM people. Finally, the population-specific biological adaptation study identified the shared and differentiated natural-selection signatures among inland and coastal HM people associated with physical features and immune function. The allele frequency spectrum (AFS) of clinical cancer susceptibility alleles and pharmacogenomic genes showed significant differences between HM and northern Chinese people. ConclusionsOur extensive genetic evidence combined with the historic documents supported the view that ancient HM people originated in Yungui regions associated with ancient Three-Miao tribes descended from the ancient Daxi-Qujialing-Shijiahe people. And then, some recently rapidly migrated to Southeast Asia, and some culturally dispersed eastward and mixed respectively with Southeast Asian indigenes, coastal Liangzhu-related ancient populations, and incoming southward Sino-Tibetan people. Generally, complex population migration, admixture, and adaptation history contributed to their specific patterns of non-coding or disease-related genetic variations.

genetics↗

Multifaceted roles of a light-responsive factor LhWRKY44 in promoting anthocyanin accumulation in Asiatic hybrid lilies (Lilium spp.)

The coloration of Asiatic hybrid lily results mostly from anthocyanin accumulation in flowers. Although anthocyanin accumulation-related genes and MBW complexes are well studied, the transcriptional regulation of WRKY transcription factors involved in anthocyanin accumulation remains poorly understood.Here, we identified a lily WRKY protein, LhWRKY44, whose expression is highly expressed downstream of LhHY5 by light and positively correlated with anthocyanin accumulation. LhWRKY44 overexpression enhanced anthocyanin accumulation and silencing decreased anthocyanin accumulation in flowers. As a trans-acting regulator, LhWRKY44 activited the anthocyanin biosynthesis pathway-related genes PAL and F3H by binding to the their promoters. And the encoded TF also participates in anthocyanin transport and targets the intracellular anthocyanin transport protein GST promoters. Additionally, a novel dual activity of LhWRKY44 and LhMYBSPLATTER regulatory module, with LhWRKY44 binds to the promoter of LhMYBSPLATTER and interacts with LhMYBSPLATTER, strongly enhanced the interaction of LhMYBSPLATTER and LhbHLH2, indirectly enhancing DFR, UFGT and GST expression targeted by LhMYBSPLATTER. These results show a regulatory mode for light-induced anthocyanin accumulation enhancement by LhWRKY44 in lily, expanding our understanding of the complex transcriptional regulatory hierarchy modulating anthocyanin accumulation.

molecular biology↗

Multiple founding paternal lineages inferred from the newly-developed SNPSeqTyper 639 Y-SNP panel suggested the complex admixture and migration history of Chinese people

Non-recombining regions of the Y-chromosome are inherited male-specifically and recorded the evolutionary traces of male human populations. Recent whole Y-chromosome sequencing studies have identified previously unrecognized population divergence, expansion and admixture processes, which promotes a better understanding and application of the observed patterns of Y-chromosome genetic diversity. Here, we developed one highest-resolution Y-SNP panel for forensic pedigree search and paternal biogeographical ancestry inference, which included 639 phylogenetically informative SNPs (Y-SNPs). We genotyped these loci in 1033 Chinese male individuals from 33 ethnolinguistically diverse populations and identified 257 terminal Y-chromosomal lineages with frequency ranging from 0.010 (singleton) to 0.0687. We identified six dominant common founding lineages associated with different ethnolinguistic backgrounds, which included O2a2b1a1a1a1a1a1a1-M6539, O2a1b1a1a1a1a1a1-F17, O2a2b1a1a1a1a1b1a1b-MF15397, O2a2b2a1b1-A16609, O1b1a1a1a1b2a1a1-F2517 and O2a2b1a1a1a1a1a1-F155. The AMOVA and nucleotide diversity estimates revealed considerable differences and high genetic diversity among ethnolinguistically different populations. We constructed one representative phylogenetic tree among 33 studied populations based on the haplogroup frequency spectrum and sequence variations. Clustering patterns in principal component analysis and multidimensional scaling results showed a genetic differentiation between Tai-Kadai-speaking Li, Mongolic-speaking Mongolian and other Sinitic-speaking Han Chinese populations. Phylogenetic topology inferred from the BEAST and Network relationships reconstructed from the popART further showed the founding lineages from culturally/linguistically diverse populations, such as C2a/C2b was dominant in Mongolian people and O1a/O1b was dominant in island Li people. We also identified many lineages shared by more than two ethnolinguistically different populations with a high proportion, suggesting their extensive admixture and migration history. Our findings indicated that our developed high-resolution Y-SNP panel included major dominant Y-lineages of Chinese populations from different ethnic groups and geographical regions, which can be used as the primary and powerful tool for forensic practice. We should emphasize the necessity and importance of whole-sequencing of more ethnolinguistically different populations, which can help identify more unrecognized population-specific variations for the final promotion of Y-chromosome-based forensic applications.

genetics↗

Phase-separating pyrenoid proteins form complexes in the dilute phase

While most studies of biomolecular phase separation have focused on the condensed phase, relatively little is known about the dilute phase. Theory suggests that stable complexes form in the dilute phase of two-component phase-separating systems, impacting phase separation; however, these complexes have not been interrogated experimentally. We show that such complexes indeed exist, using an in vitro reconstitution system of a phase-separated organelle, the algal pyrenoid, consisting of purified proteins Rubisco and EPYC1. Applying fluorescence correlation spectroscopy (FCS) to measure diffusion coefficients, we found that complexes form in the dilute phase with or without condensates present. The majority of these complexes contain exactly one Rubisco molecule. Additionally, we developed a simple analytical model which recapitulates experimental findings and provides molecular insights into the dilute phase organization. Thus, our results demonstrate the existence of protein complexes in the dilute phase, which could play a significant role in the stability, dynamics, and regulation of condensates.

biophysics↗

Linking Choroid Plexus Enlargement with Plasma Analyte and Structural Phenotypes in Clinical High Risk for Psychosis: A Multisite Neuroimaging Study

BackgroundChoroid plexus (ChP) enlargement exists in first-episode and chronic psychosis, but whether enlargement occurs before psychosis onset is unknown. This study investigated whether ChP volume is enlarged in individuals with clinical high-risk (CHR) for psychosis and whether these changes are related to clinical, neuroanatomical, and plasma analytes. MethodsClinical and neuroimaging data from the North American Prodrome Longitudinal Study 2 (NAPLS2) was used for analysis. 509 participants (169 controls, 340 CHR) were recruited. Conversion status was determined after 2-years of follow-up, with 36 psychosis converters. The lateral ventricle ChP was manually segmented from baseline scans. A subsample of 31 controls and 53 CHR had plasma analyte and neuroimaging data. ResultsCompared to controls, CHR (d=0.23, p=0.017) and non-converters (d=0.22, p=0.03) demonstrated higher ChP volumes, but not in converters. In CHR, greater ChP volume correlated with lower cortical (r=-0.22, p<0.001), subcortical gray matter (r=-0.21, p<0.001), and total white matter volume (r=-0.28,p<0.001), as well as larger lateral ventricle volume (r=0.63,p<0.001). Greater ChP volume correlated with makers functionally associated with the lateral ventricle ChP in CHR [CCL1 (r=-0.30, p=0.035), ICAM1 (r=0.33, p=0.02)], converters [IL1{beta} (r=0.66, p=0.004)], and non-converters [BMP6 (r=-0.96, p<0.001), CALB1 (r=-0.98, p<0.001), ICAM1 (r=0.80, p=0.003), SELE (r=0.59, p=0.026), SHBG (r=0.99, p<0.001), TNFRSF10C (r=0.78, p=0.001)]. ConclusionsCHR and non-converters demonstrated significantly larger ChP volumes compared to controls. Enlarged ChP was associated with neuroanatomical alterations and analyte markers functionally associated with the ChP. These findings suggest that the ChP may be a key explanatory biomarker in CHR for psychosis.

neuroscience↗

Predicting individualized tissue gene expression profiles with multi-task learning

Predicting tissue expression profiles from peripheral surrogate samples, especially blood transcriptome, has become an effective alternative when invasive procedures are not ideal. However, existing approaches ignore tissue-shared intrinsic relevance, inevitably limiting predictive performance. Here, we propose a unified deep learning-based multi-task learning framework, Multi-tissue Transcriptome Mapping (MTM), enabling the prediction of individualized expression profiles from any available tissue of an individual. By jointly leveraging individualized cross-tissue information through multi-task learning, MTM achieves superior sample-level and gene-level performance. With the high prediction accuracy and the ability to preserve individualized biological variations, MTM could facilitate both fundamental and clinical biomedical research.

bioinformatics↗

The western redcedar genome reveals low genetic diversity in a self-compatible conifer

We assembled the 9.8 Gbp genome of western redcedar (WRC, Thuja plicata), an ecologically and economically important conifer species of the Cupressaceae. The genome assembly, derived from a uniquely inbred tree produced through five generations of self-fertilization (selfing), was determined to be 86% complete by BUSCO analysis - one of the most complete genome assemblies for a conifer. Population genomic analysis revealed WRC to be one of the most genetically depauperate wild plant species, with an effective population size of approximately 300 and no significant genetic differentiation across its geographic range. Nucleotide diversity, {pi}, is low for a continuous tree species, with many loci exhibiting zero diversity, and the ratio of {pi} at zero-to four-fold degenerate sites is relatively high ([~] 0.33), suggestive of weak purifying selection. Using an array of genetic lines derived from up to five generations of selfing, we explored the relationship between genetic diversity and mating system. While overall heterozygosity was found to decline faster than expected during selfing, heterozygosity persisted at many loci, and nearly 100 loci were found to deviate from expectations of genetic drift, suggestive of associative overdominance. Non-reference alleles at such loci often harbor deleterious mutations and are rare in natural populations, implying that balanced polymorphisms are maintained by linkage to dominant beneficial alleles. This may account for how WRC remains responsive to natural and artificial selection, despite low genetic diversity.

plant biology↗

A GPU-based computational framework that bridges Neuron simulation and Artificial Intelligence

Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive computational cost severely limits the applications in both the neuroscience and AI fields. The major bottleneck during simulating detailed compartment models is the ability of a simulator to solve large systems of linear equations. Here, we present a novel Dendritic Hierarchical Scheduling (DHS) method to markedly accelerate such process. We theoretically prove that the DHS implementation is computationally optimal and accurate. This GPU-based method performs at 2-3 orders of magnitude higher speed than that of the classic serial Hines method in the conventional CPU platform. We build a DeepDendrite framework, which integrates the DHS method and the GPU computing engine of the NEURON simulator and demonstrate applications of DeepDendrite in neuroscience and AI tasks. We investigated how spatial patterns of spine inputs affect neuronal excitability in a detailed human pyramidal neuron model with 25,000 spines; and examined how dendrites protect morphologically detailed neural networks against adversarial attacks in typical image classification tasks.

neuroscience↗

Triangulation fails when neither linguistic, genetic, nor archaeological data support the Transeurasian narrative

Robbeets et al.1 argue that the dispersal of the so-called "Transeurasian" languages, a highly disputed language superfamily comprising the Turkic, Mongolian, Tungusic, Koreanic, and Japonic language families, was driven by Neolithic farmers in the West Liao River region of China. They adduce evidence from linguistics, archaeology, and genetics to support their claim. An admirable feature of the Robbeets et al.s paper is that all their datasets can be accessed. However, a closer investigation of all three types of evidence reveals fundamental problems with each of them. Robbeets et al.s analysis of the linguistic data does not conform to the minimal standards required by traditional scholarship in historical linguistics and contradicts their own stated sound correspondence principles. A reanalysis of the genetic data finds that they do not conclusively support the farming-driven dispersal of Turkic, Mongolian, and Tungusic, nor the two-wave spread of farming to Korea. Their archaeological data contain little phylogenetic signal, and we failed to reproduce the results supporting their core hypotheses about migrations. Given the severe problems we identify in all three parts of the "triangulation" process, we conclude that there is neither conclusive evidence for a Transeurasian language family nor for associating the five different language families with the spread of Neolithic farmers from the West Liao River region.

genetics↗

Retina Gap Junction Networks Facilitate Blind Denoising in Visual Hierarchy

Gap junctions in the retina are electrical synapses, which strength is regulated byambient light conditions. Such tunable synapses are crucial for the denoising function of the early visual system. However, it is unclear that how the plastic gap junction network processes unknown noise, specifically how this process works synergistically with the brains higher visual centers. Inspired by the electrically coupled photoreceptors, we develop a computational model of the gap junction filter (G-filter). We show that G-filter is an effective blind denoiser that converts different noise distributions into a similar form. Next, since deep convolutional neural networks (DCNNs) functionally reflect some intrinsic features of the visual cortex, we combine G-filter with DCNNs as retina and ventral visual pathways to investigate the relationship between retinal denoising processing and the brains high-level functions. In the image denoising and reconstruction task, G-filter dramatically improve the classic deep denoising convolutional neural network (DnCNN)s ability to process blind noise. Further, we find that the gap junction strength of the G-filter modulates the receptive field of DnCNNs output neurons by the Integrated Gradients method. At last, in the image classification task, G-filter strengthens the defense of state-of-the-arts DCNNs (ResNet50, VGG19 and InceptionV3) against blind noise attacks, far exceeding human performance when noise is large. Our results indicate G-filter significantly enhance DCNNs ability on various blind denoising tasks, implying an essential role for retina gap junction networks in high-level visual processing.

neuroscience↗

Genetic admixture history and forensic characteristics of Tibeto-Burman-speaking Qiang people explored via the newly developed Y-STR panel and genome-wide SNP data

Fine-scale patterns of population genetic structure and diversity of ethnolinguistically diverse populations are important for biogeographical ancestry inference, kinship testing and also for the development and validation of new kits focused on forensic personal identification. Analyses focused on forensic markers and genome-wide SNP data can provide new insights into the origin, admixture processes and forensic characteristics of targeted populations. Qiang people with a large sample size among Tibeto-Burman-speaking populations widely reside in the middle latitude of the Tibetan Plateau. However, their genetic structure and forensic features have remained uncharacterized due to the paucity of comprehensive genetic analyses. Here, we first developed and validated the AGCU-Y30 Y-STR panel, which contains slowly and moderately mutating Y-STRs, and then we conducted comprehensive population genetic analyses based on Y-STRs and genome-wide SNPs to explore the admixture history of Qiang people and their neighbours. The validated results of this panel showed that the new Y-STR kit was sensitive and robust enough for forensic applications. Haplotype diversity (HD) ranging from 0.9932 to 0.9996 and allelic frequencies ranging from 0.001946 to 0.8326 in 514 Qiang people demonstrated that all included markers were highly polymorphic in Tibeto-Burman people. Population genetic analyses based on Y-STRs (RST, FST, MDS, NJ, PCA and MJNs) revealed that the Qiang people harboured a paternally close relationship with lowland Tibetan-Yi corridor populations. Furthermore, we made a comprehensive population admixture analysis among Eurasian modern and ancient populations based on the shared alleles. We determined that the Qiang people were a genetically admixed population and showed the closest relationship with Tibetan and Neolithic Yellow River farmers. Admixture modelling showed that Qiang people shared the primary ancestry with Tibetan and was derived from North China, supporting the hypothesis of common origin between Tibetan and Qiang people.

genetics↗

The infiltration pattern of microenvironmental cells and different immune escape mechanisms in colorectal cancer

BackgroundThe tumour microenvironment (TME) plays a crucial role in tumour progression and metastasis. However, the infiltration pattern of TME cells in CRC samples and the immune escape mechanism underneath have not been studied sufficiently. MethodsTranscriptomic data from public datasets were retrieved online. In total, 1802 samples from the microarray dataset and 619 samples from the TCGA dataset were enrolled. The ssGSEA algorithm and unsupervised clustering were used for TME cells infiltration speculation and infiltration pattern recognition. ResultsCRC samples can be classified into three distinct TME cell subtypes. Subtype 1, the immune-active subtype, was characterised by high infiltration of activated adaptive immune cells. Subtype 2, the immune-desert subtype, featured high tumour purity and low infiltration of immune and stromal cells. And subtype 3, stroma-rich subtype, had high infiltration of stromal cells. The stroma-rich subtype conferred a significantly worse prognosis. Three subtypes had different immune escape mechanisms. The immune-active subtype has the highest immune checkpoint expression level. In comparison, the immune-desert subtype had the lowest immunogenicity and the defective antigen presentation. And the stroma-rich subtype lacked activated immune cells. ConclusionsDistinct TME cell subtypes and immune escape mechanisms may provide inspiration and direction for further researches on CRC immunotherapy.

cancer biology↗

De novo protein structure prediction by incremental inter-residue geometries prediction and model quality assessment using deep learning

MotivationThe successful application of deep learning has promoted progress in protein model quality assessment. How to use model quality assessment to further improve the accuracy of protein structure prediction, especially not reliant on the existing templates, is helpful for unraveling the folding mechanism. Here, we investigate whether model quality assessment can be introduced into structure prediction to form a closed-loop feedback, and iteratively improve the accuracy of de novo protein structure prediction. ResultsIn this study, we propose a de novo protein structure prediction method called RocketX. In RocketX, a feedback mechanism is constructed through the geometric constraint prediction network GeomNet, the structural simulation module, and the model quality evaluation network EmaNet. In GeomNet, the co-evolutionary features extracted from MSA that search from the sequence databases are sent to an improved residual neural network to predict the inter-residue geometric constraints. The structure model is folded based on the predicted geometric constraints. In EmaNet, the 1D and 2D features are extracted from the folded model and sent to the deep residual neural network to estimate the inter-residue distance deviation and per-residue lDDT of the model, which will be fed back to GeomNet as dynamic features to correct the geometries prediction and progressively improve model accuracy. RocketX is tested on 483 benchmark proteins and 20 FM targets of CASP14. Experimental results show that the closed-loop feedback mechanism significantly contributes to the performance of RocketX, and the prediction accuracy of RocketX outperforms that of the state-of-the-art methods trRosetta (without templates) and RaptorX. In addition, the blind test results on CAMEO show that although no template is used, the prediction accuracy of RocketX on medium and hard targets is comparable to the advanced methods that integrate templates. AvailabilityThe RocketX web server are freely available at http://zhanglab-bioinf.com/RocketX. Contactzgj@zjut.edu.cn

bioinformatics↗

Control of Leaf Width by the APC/CTAD1-WL1-NAL1 Pathway in Rice

Leaf morphology is one of the most important features of the ideal plant architecture. However, the genetic and molecular mechanisms controlling leaf morphology in crops remain largely unknown, despite their central importance. Here we demonstrate that the APC/CTAD1-WL1-NAL1 pathway regulates leaf width in rice, and mutation of WL1 leads to width leaf variation. WL1 interacts with TAD1 and is degraded by APC/CTAD1, with the loss of TAD1 function resulting in narrow leaves. The WL1 protein directly binds to the regulatory region of NAL1 and recruits the corepressor TOPLESS-RELATED PROTEIN to inhibit NAL1 expression by down-regulating the level of histone acetylation of chromatin. Furthermore, biochemical and genetic analyses revealed that TAD1, WL1, and NAL1 function in a common pathway to control leaf width. Our study establishes an important framework for the APC/CTAD1-WL1-NAL1 pathway-mediated control of leaf width in rice and introduces novel perspectives for using this regulatory pathway for improving crop plant architecture.

plant biology↗