Biology subjects

Lv, R.

Publications and source records attributed to Lv, R..

7 recordsLinked to original sources

bioRxiv2022

The structural basis of itch receptor MRGPRX1 activation

Mas-related G-protein-coupled receptors X1-X4 (MRGPRX1-X4) are four primate-specific receptors that are recently reported to be responsible for many biological processes, including itch sensation, pain transmission, and inflammatory reactions. MRGPRX1 is the first identified human MRGPR, and its expression is restricted to primary sensory neurons. Due to its dual roles in itch and pain signaling pathways, MRGPRX1 has been regarded as a promising target for itch remission and pain inhibition. Here, we reported a cryo-electron microscopy (cryo-EM) structure of Gq-coupled MRGPRX1 in complex with a synthetic agonist compound 16 in an active conformation at an overall resolution of 3.0 angstrom via a NanoBiT tethering strategy. Compound 16 is a new pain-relieving compound with high potency and selectivity to MRGPRX1 over opioid receptor. According to the structure analysis, we revealed that MRGPRX1 shares common features of the Gq-mediated receptor activation mechanism of MRGPRX family members. However, the variable residues in orthosteric pocket of MRGPRX1 exhibits the unique agonist recognition pattern, which may facilitate to design MRGPRX1-specific modulators. Together with receptor activation and itch behavior evaluation assays, our study provides a structural snapshot to modify therapeutic molecules for itch relieving and analgesia targeting MRGPRX1.

biochemistry↗

bioRxiv2022

Novel Viroid-like RNAs Naturally Infect a Filamentous Fungus

Viroids have been found to naturally infect only plants, resulting in big losses for some crops, but whether viroids or viroid-like RNAs naturally infect non-plant hosts remains unknown. Here we report the existence of a set of exogenous, single-stranded circular RNAs, ranging in size between 157-450 nucleotides (nt), isolated from the fungus Botryosphaeria dothidea and nominated Botryosphaeria dothidea circular RNAs (BdcRNAs). BdcRNA(s) replicate autonomously in the nucleus via a rolling-circle replication mechanism following symmetric pathways with distribution patterns depending on strand polarity and species. BdcRNAs can modulate to different degrees specific biological traits (e.g., alter morphology, decrease growth rate, attenuate virulence, and increase or decrease tolerance to osmotic stress and oxidative stress) of the host fungus by regulating related metabolic pathways. Overall, BdcRNA(s) have genome characteristics similar to those of viroids and exhibit pathogenic effects on the fungal hosts. These novel viroid-like RNAs infecting fungi are proposed to be termed as mycoviroids. BdcRNA(s) may be regarded as additional inhabitants at the frontier of life in terms of genomic complexity, and represent a new class of acellular entities endowed with regulatory functions, and novel epigenomic carriers of biological information. Significance statementSeveral viroids have been transfected into unicellular and filamentous fungi to assess whether they can replicate, but no natural infections of fungi with viroid or viroid-like RNAs have been reported before. Here we describe a set of exogenous circular RNAs (cRNAs) in a phytopathogenic fungus. These cRNAs display molecular and biological features which might represent a new class of viroid-like cRNAs endowed with regulatory functions, and novel epigenomic carriers of biological information. This is the first report of infectious viroid-like RNAs (or exogenous small cRNAs) in a life kingdom (fungi) other than plants. We also present a subcellular analysis of cRNAs in a fungus for the first time and provide useful understanding in how cRNAs replicate, move, and are distributed in fungal cells.

microbiology↗

bioRxiv2021

Effects of homoeologous exchange on gene expression and alternative splicing in a newly formed allotetraploid wheat

Homoeologous exchange (HE) is a major mechanism generating post-polyploidization genetic variation with important evolutionary consequences. However, the direct impacts of HE without entangling with additional evolutionary forces on gene expression remains to be fully understood. Here, we analyzed high-throughput RNA-seq data of young leaves from individuals of a synthetic allotetraploid wheat (AADD), which contain variable numbers of HEs. We aimed to investigate if and to which extent HE directly impacts gene expression and alternative splicing (AS). We found that HE impacts expression of genes located within HE regions primarily via cis-acting dosage effect, which led to significant changes in the total expression of homoeolog pairs, especially for homoeologs whose original expression was biased. In parallel, HE influences expression of a large amount of genes residing in non-HE regions by trans-regulation leading to convergent expression of homoeolog pairs. Intriguingly, when taking into account of the original relative homoeolog expression states, homoeolog pairs under trans-effect are more prone to showing convergent response to HE whereas those under cis-effect trended to show subgenome-specific expression. Moreover, HE induced quantitative, largely individual-specific, changes of alternative splicing (AS) events. Like homoeologs expression, homoeo-AS events which related to trans effect were more responsive to HE. HE therefore exerts multifaceted immediate effects on gene expression and, to a less extent, also transcript diversity in nascent allopolyploidy.

plant biology↗

bioRxiv2021

Fast anther dehiscence state recognition system establishing by deep learning to screen heat tolerant cotton

Cotton is one of the most economically important crops in the world. The fertility of male reproductive organs is a key determinant of cotton yield. The anther dehiscence or indehiscence directly determine the probability of fertilization in cotton. Thus, the rapid and accurate identification of cotton anther dehiscence status is important for judging anther growth status and promoting genetic breeding research. The development of computer vision technology and the advent of big data have prompted the application of deep learning techniques to agricultural phenotype research. Therefore, two deep learning models (Faster R-CNN and YOLOv5) were proposed to detect the number and dehiscence status of anthers. The single-stage model based on YOLOv5 has higher recognition efficiency and the ability to deploy to the mobile end. Breeding researchers can apply this model to terminals to achieve a more intuitive understanding of cotton anther dehiscence status. Moreover, three improvement strategies of Faster R-CNN model were proposed, the improved model has higher detection accuracy than YOLOv5 model. In addition, the percentage of dehiscent anther of randomly selected 30 cotton varieties were observed from cotton population under normal temperature and high temperature (HT) conditions through the integrated Faster R-CNN model and manual observation. The result showed HT varying decreased the percentage of dehiscent anther in different cotton lines, consistent with the manual method. Thus, this system can help us to rapid and accurate identification of HT-tolerant cotton. One sentence summaryThe deep learning technique was applied to identify the anther dehiscence state for the first time to quickly screen heat tolerant cotton varieties and help to explore key genetic improvement genes.

bioengineering↗

bioRxiv2020

Microbiota in milk from healthy and mastitis cows varies greatly in diversity, species richness and composition, as revealed by PacBio sequencing

Mastitis is the most economically important disease of dairy cows. This study used PacBio single-molecule real-time sequencing technology to sequence the full-length of the l6S rRNA from the microbiota in 27 milk samples (18 from mastitis and 9 from healthy cows; the cows were at different stages of lactation). We observed that healthy or late stage milk microbiota had significantly higher microbial diversity and richness. The community composition of the microbiota from different groups also varied greatly. In milk from healthy cows the microbiota was predominantly comprised of Lactococcus lactis, Acinetobacter johnsonii and Bacteroides dorei, while from mastitis cows it was predominantly comprised of Bacillus cereus, Clostridium cadaveris and Streptococcus suis. The prevalence of La. lactis and B. cereus in milk from healthy and mastitis cows was confirmed by digital droplets PCR. Differences in milk microbiota composition could suggest an important role for these microbes in protecting the host from mastitis. Based on the milk microbiota profiles, the Udder Health Index was constructed to predict the risk of bovine mastitis. Application of this predictive model could aid early identification and prevention of mastitis in dairy cows, though the model requires further optimisation using a larger dataset.

microbiology↗

bioRxiv2019

PLANT NATRIURETIC PEPTIDE A antagonizes salicylic acid-primed cell death

Peptide hormones perceived in the cell surface via receptor proteins enable cell-to-cell communication and act in multiple biological processes through the activation of intracellular signaling. Even though Arabidopsis is predicted to have more than 1,000 secreted peptides, the biological relevance of the majority of these is yet to be established. Here, we demonstrate that PLANT NATRIURETIC PEPTIDE A (PNP-A), a functional analog to vertebrate atrial natriuretic peptides, antagonizes the salicylic acid (SA)-mediated cell death in the Arabidopsis lesion-stimulating disease 1 (lsd1) mutant. While loss of PNP-A potentiates SA signaling, exogenous application of the PNP-A synthetic peptide or overexpression of PNP-A significantly compromises the SA-mediated cell death. Moreover, we identified a plasma membrane-localized receptor-like protein, which we name PNPAR (for PNP-A receptor), that binds PNP-A and is required to counteract SA responses. Our work identifies a novel peptide-receptor pair which modulates SA responses in Arabidopsis.

plant biology↗

bioRxiv2018

The genome of the plague-resistant great gerbil reveals species-specific duplication of an MHCII gene

The great gerbil (Rhombomys opimus) is a social rodent living in permanent, complex burrow systems distributed throughout Central Asia, where it serves as the main host of several important vector-borne infectious diseases and is defined as a key reservoir species for plague (Yersinia pestis). Studies from the wild have shown that the great gerbil is largely resistant to plague but the genetic basis for resistance is yet to be determined. Here, we present a highly contiguous annotated genome assembly of great gerbil, covering over 96 % of the estimated 2.47 Gb genome. Comparative genomic analyses focusing on the immune gene repertoire, reveal shared gene losses within TLR gene families (i.e. TLR8, TLR10 and all members of TLR11-subfamily) for the Gerbillinae lineage, accompanied with signs of diversifying selection of TLR7 and TLR9. Most notably, we find a great gerbil-specific duplication of the MHCII DRB locus. In silico analyses suggest that the duplicated gene provides high peptide binding affinity for Yersiniae epitopes. The great gerbil genome provides new insights into the genomic landscape that confers immunological resistance towards plague. The high affinity for Yersinia epitopes could be key in our understanding of the high resistance in great gerbils, putatively conferring a faster initiation of the adaptive immune response leading to survival of the infection. Our study demonstrates the power of studying zoonosis in natural hosts through the generation of a genome resource for further comparative and experimental work on plague survival and evolution of host-pathogen interactions.

genomics↗