Biology subjects

Tao, Y.

Publications and source records attributed to Tao, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

ErbB inhibition impairs cognition via disrupting myelination and aerobic glycolysis in oligodendrocytes

White matter abnormalities are an emerging feature of schizophrenia, yet the underlying pathophysiological mechanisms are largely unknown. Disruption of ErbB signaling that is essential for peripheral myelination has been genetically associated with schizophrenia and white matter lesions in schizophrenic patients. However, the roles of ErbB signaling in oligodendrocytes remain elusive. Here, we used a pan-ErbB inhibition strategy and demonstrated the synergistic functions of endogenous ErbB receptors in oligodendrocytes. Through analyses of the cellular, histological, biochemical, behavioral, and electrophysiological differences in mice with manipulation of ErbB activities in oligodendrocytes at different differentiation stages, we found that ErbB signaling regulates myelination and aerobic glycolysis in oligodendrocytes, and both functions are required for working memory. ErbB inhibition in oligodendrocytes at early differentiation stages induces hypomyelination by suppressing the differentiation of newly-formed oligodendrocytes. In contrast, ErbB inhibition in mature oligodendrocytes alters neither myelination nor oligodendrocyte numbers, but accelerates axonal conduction decline under energy stress. Mechanistically, mature oligodendrocytes with ErbB inhibition reduce the expression of lactate dehydrogenase A, failing to provide lactate to electrically active axons. Supplementation of L-lactate restores axonal conduction and working memory capacity that are suppressed by ErbB inhibition in mature oligodendrocytes. These findings reveal the indispensable roles of ErbB signaling in white matter integrity and function, and provide insights into the multifaceted contributions of white matter abnormalities to cognitive impairment.

neuroscience↗

bioRxiv2022

SARS-CoV-2 exposure in Norwegian rats (Rattus norvegicus) from New York City

Millions of Norway rats (Rattus norvegicus)inhabit New York City (NYC), presenting the potential for transmission of SARS-CoV-2 from humans to rats and other wildlife. We evaluated SARS-CoV-2 exposure among 79 rats captured from NYC during the fall of 2021. Results showed that 13 of 79 rats (16.5%) tested IgG or IgM positive, and partial genomes of SARS-CoV-2 were recovered from four rats that were qRT-PCR positive. Using a virus challenge study, we also showed that Alpha, Delta, and Omicron variants can cause robust infections in wild-type Sprague Dawley (SD) rats, including high level replications in the upper and lower respiratory tracts and induction of both innate and adaptive immune responses. Additionally, the Delta variant resulted in the highest infectivity. In summary, our results indicated that rats are susceptible to infection with Alpha, Delta, and Omicron variants, and rats in the NYC municipal sewer systems have been exposed to SARS-CoV-2. Our findings highlight the potential risk of secondary zoonotic transmission from urban rats and the need for further monitoring of SARS-CoV-2 in those populations. ImportanceSince its emergence causing the COVID-19 pandemic, the host tropism expansion of SARS-CoV-2 raises a potential risk for reverse-zoonotic transmission of emerging variants into rodent species, including wild rat species. In this study, we presented both genetic and serological evidence for SARS-CoV-2 exposure in wild rat population from New York City, and these viruses are potentially linked to the viruses during the early stages of the pandemic. We also demonstrated that rats are susceptible to additional variants (i.e., Alpha, Delta, and Omicron) predominant in humans and that the susceptibility to different variants vary. Our findings highlight the potential risk of secondary zoonotic transmission from urban rats and the need for further monitoring of SARS-CoV-2 in those populations.

microbiology↗

bioRxiv2022

An alternative malonyl-CoA producing pathway in nature

Malonyl-CoA is a key metabolic intermediate for biosynthesis of diverse cellular molecules and natural products. Carboxylation of acetyl-CoA is almost the unique pathway for malonly-CoA biosynthesis. Biotechnological production of numerous value-added malonyl-CoA-derived chemicals require high intracellular supply of malonyl-CoA. However, because of the central role of acetyl-CoA in primary metabolism, it is difficult to develop flexible strategies to balance malonyl-CoA supply with other cellular metabolism. Here we find that there is a natural alternative malonyl-CoA-producing pathway, in which the key reaction is catalyzed by an -keto acid dehydrogenase complex BkdFGH from Streptomyces avermitilis. This dehydrogenase complex could efficiently catalyze biosynthesis of malonyl-CoA from oxaloacetate in addition to recognizing its native substrate branched-chain -keto acid. Oxaloacetate dehydrogenase (OADH) was shown to play important physiological roles during the regulation of biosynthesis of native malonyl-CoA-derived polyketides in Streptomyces. Furthermore, the oxlaocetate dehydrogenation reaction is thermodynamically superior to acetyl-CoA carboxylation and enable efficient bioproduction of diverse malonyl-CoA-derived chemicals in engineering Escherichia coli. This novel malonyl-CoA source thus has great potential in the biotechnological field.

microbiology↗

bioRxiv2022

Leveraging PDE solver for predicting transient space-use dynamics in ecological and epidemiological systems

Model predictions of animal and human space-use patterns stemming from individual-level movement behaviors have not only contributed significantly to our understanding of population and community dynamics, but they could also inform the development of conservation, natural resource management, and disease control policies. The recent proliferation of high-resolution movement data has ushered in a paradigm shift in how space use is considered: instead of being defined narrowly as the stationary, long-term distribution of individual locations, there is a growing recognition of its transient dynamics, e.g.., how space-use pattern varies before it eventually stabilizes. However, movement models are slow to follow due to longstanding technical challenges in solving transient space-use dynamics. Here, we introduce a numerical framework that enables transient analysis of mechanistic movement models based on partial differential (Fokker-Planck) equations. We demonstrate its potential applications in the context of general research questions in movement ecology using classical and new case studies as illustrations. We demonstrate the frameworks applications and versatility in classical home range models, but also show how it may be extended to address new ecological questions.

ecology↗

bioRxiv2022

The Genome of the Wasp Anastatus disparis Reveals Energy Metabolism Adaptations for Extreme Aggression.

Extremely aggressive behavior is rare in most species, as contestants can be severely injured or killed. Such high level of aggression can evolve when critical resources are limited, as the benefits of winning outweigh the potential costs of conflict. Currently, studies of extreme aggression are mainly from the perspectives of behavioral ecology and evolutionary biology, displaying distinct results from common nonextreme aggression. Here, we provide a high-quality genome of the generalist endoparasitoid Anastatus disparis, the males of which exhibit extreme mate-competition aggression, to shed light on possible genomic adaptations for extreme aggressive behavior. We combined Nanopore PromethION sequencing with Hi-C technology to assemble a high-quality chromosome-level genome of A. disparis. The size of the genome of this species (939.58 Mb) is larger than that of most hymenopterans (ranging from 180 Mb to 340 Mb) due to the expansion of repeated sequences (612.90 Mb, 65.23% of the whole genome). With the aid of RNA sequencing, 19,246 protein-coding genes were identified, and a great expansion of genes involved in detoxification was detected, which could represent an adaptation of this species to exploit a diverse range of known hosts. The integrated multiomics analysis highlighted genes involved in energy metabolism (especially from lipids) and antibacterial activity, both of which are possibly major aspects of adaptation for extreme aggression in A. disparis. Our study provides insight into molecular and evolutionary studies of extreme aggression in A. disparis and provides a valuable genomic resource for further research into the molecular basis of trait evolution in Hymenoptera.

genomics↗

bioRxiv2022

Intestinal Epithelial Heat Shock Protein 25/27 integrates host and microbial drivers of mucosal restitution following inflammatory injury

Mucosal healing following inflammatory injury is poorly understood and often neglected, despite being the best indicator of long-term outcomes in inflammatory bowel diseases. We report here that the enigmatic small molecular weight heat shock protein, Hsp25 (the human form is Hsp27), plays a vital role in converging microbial and host factors to promote pSTAT3-mediated mucosal healing. In wild type mice, the proximal-to-distal gradient of intestinal epithelial cell (IEC) Hsp25 expression is dependent on microbial cues. Patients with left-sided ulcerative colitis, however, show reduced levels of Hsp27 expression in both uninvolved and involved areas compared to normal colons of non-IBD patients. In mice with global or IEC-specific Hsp25 gene-targeted deletion, impaired mucosal healing with development of hallmarks of chronic disease are observed following DSS-induced or TNBS-induced colitis, whereas mucosal restitution is accelerated in IEC-specific overexpressing Hsp25 transgenic mice. In colonic IECs derived from these murine lines, Hsp25 binds and stabilizes a phospho-STAT3/YAP nuclear complex stimulated by IL-22 to sustain its wound healing gene programming. Thus, our findings provide insight into the mechanism of action of IEC Hsp25/27 in integrating host and microbial drivers of mucosal restitution, which can be leveraged to develop novel approaches for achieving and maintaining remission in complex immune disorders like IBD.

pathology↗

bioRxiv2022

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↗

bioRxiv2022

CircEML1 facilitates the steroid synthesis in follicular granulosa cells of chicken through sponging gga-miR-449a to release IGF2BP3 expression

Non-coding RNAs (ncRNAs) induced competing endogenous RNAs (ceRNA) play crucial roles in various biological process by regulating target gene expression. However, the studies of ceRNA networks in the regulation of ovarian ovulation process of chicken remains deficient compared to that in mammals. In the present study, it was revealed that circEML1 was differential expressed in hens ovarian tissue at different ages (15W, 20W, 30W and 68W) and identified as a loop structure from EML1 pre-mRNA, which promoted the expressions of CYP19A1 and StAR and the production of E2 and P4 in follicular granulosa cells (GCs) using qRT-PCR and ELISA. Furthermore, circEML1 was proved to serve as a sponge of gga-miR-449a to participate in the steroidogenesis using the dual luciferase reporter, RNA FISH assays, qRT-PCR and ELISA assays. In addition, we evaluated several potential target genes of gga-miR-449a and found that IGF2BP3 was targeted by gga-miR-449a and promoted steroidogenesis and E2/P4 secretions in GCs, which may act the regulatory role via mTOR/p38MAPK pathways. Meanwhile, we implemented a rescue experiment and demonstrated that gga-miR-449a reversed the promoting role of circEML1 on IGF2BP3 expression and steroidogenesis. Eventually, this study suggested that circEML1/gga-miR-449a/IGF2BP3 axis exerted an important role in the regulation of steroidogenesis and steroid hormones production possibly through mTOR/p38MAPK pathways in follicular GCs of chicken and may contribute a better understanding of ceRNA network in the modulatory mechanism of hens ovarian development and ovulation cycle.

molecular biology↗

bioRxiv2022

A high potent synthetic nanobody with broad-spectrum activity neutralizes SARS-Cov-2 virus and Omicron variant through a unique binding mode

The major challenge to control COVID pandemic is the rapid mutation rate of the SARS-Cov-2 virus, leading to the escape of the protection of vaccines and most of the neutralizing antibodies to date. Thus, it is essential to develop neutralizing antibodies with broad-spectrum activity targeting multiple SARS-Cov-2 variants. Here, we reported a synthetic nanobody (named C5G2) obtianed by phage display and subsequent antibody engineering. C5G2 has a single digit nanomolar binding affinity to RBD domain and inhibits its binding to ACE2 with an IC50 of 3.7 nM. Pseudovirus assay indicated that the monovalent C5G2 could protect the cells from the infection of SARS-Cov-2 wild type virus and most of the virus of concern, i.e. Alpha, Beta, Gamma and Omicron variants. Strikingly, C5G2 has the highest potency against Omicron among all the variants with the IC50 of 4.9ng/mL. The Cryo-EM structure of C5G2 in complex with the Spike trimer showed that C5G2 bind to RBD mainly through its CDR3 at a conserved region that not overlapping with the ACE2 binding surface. Additionally, C5G2 bind simultaneously to the neighboring NTD domain of spike trimer through the same CDR3 loop, which may further increase its potency against the virus infection. Third, the steric hindrance caused by FR2 of C5G2 could inhibit the binding of ACE2 to RBD as well. Thus, this triple-function nanobody may be served as an effective drug for the prophylaxis and therapy against Omicron as well as future variants.

biochemistry↗

bioRxiv2022

Enhanced photosynthetic efficiency for increased carbon assimilation and woody biomass production in hybrid poplar INRA 717-1B4

Increasing CO2 levels in the atmosphere and the resulting negative impacts on climate change have compelled global efforts to achieve carbon neutrality or negativity. Most such efforts focus on carbon sequestration through chemical or physical approaches. We aim to harness the power of synthetic biology to enhance plants natural ability to draw down and sequester carbon, thereby positively affecting climate change. Past decades of scientific progress have shed light on strategies to overcome the intrinsic limitations of carbon drawdown and fixation through photosynthesis, particularly in row crops in hopes of improving agricultural productivity for food security. Incorporating a photorespiration bypass in C3 plants has shown promising results of increased biomass and grain yield. Despite their globally dominant role in atmospheric carbon flux, the drawdown rates of most trees are currently limited by their C3 photosynthetic metabolism, and efforts to improve the photosynthetic capacity of trees, such as by reducing energy loss in photorespiration, are currently lacking. Here, we selected a photorespiration bypass pathway and tested its effectiveness on photosynthetic enhancement in hybrid poplar INRA717-IB4. The design includes a RNAi strategy to reduce the transportation of the photorespiration byproduct, glycolate, out of chloroplast and a shunt pathway to metabolize the retained glycolate back to CO2 for fixation through the Calvin-Benson cycle. Molecular and physiological data collected from two repeated growth experiments indicates that transgenic plants expressing genes in the photorespiration bypass pathway have increased photosynthetic efficiency, leading to faster plant growth and elevated biomass production. One lead transgenic event accumulated 53% more above-ground dry biomass over a five month growth period in a controlled environment. Pilot projects with photosynthesis-enhanced trees in the field are in progress. Our results provide a proof-of-concept for engineering trees to help combat climate change.

plant biology↗

bioRxiv2021

RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes

A hallmark of type 2 diabetes (T2D), a major cause of world-wide morbidity and mortality, is dysfunction of insulin-producing pancreatic islet {beta} cells1-3. T2D genome-wide association studies (GWAS) have identified hundreds of signals, mostly in the non-coding genome and overlapping {beta} cell regulatory elements, but translating these into biological mechanisms has been challenging4-6. To identify early disease-driving events, we performed single cell spatial proteomics, sorted cell transcriptomics, and assessed islet physiology on pancreatic tissue from short-duration T2D and control donors. Here, through integrative analyses of these diverse modalities, we show that multiple gene regulatory modules are associated with early-stage T2D {beta} cell-intrinsic defects. One notable example is the transcription factor RFX6, which we show is a highly connected {beta} cell hub gene that is reduced in T2D and governs a gene regulatory network associated with insulin secretion defects and T2D GWAS variants. We validated the critical role of RFX6 in {beta} cells through direct perturbation in primary human islets followed by physiological and single nucleus multiome profiling, which showed reduced dynamic insulin secretion and large-scale changes in the {beta} cell transcriptome and chromatin accessibility landscape. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs, and individuals and thus we anticipate this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits with GWAS data.

cell biology↗

bioRxiv2021

Differential neutralization and inhibition of SARS-CoV-2 variants by antibodies elicited by COVID-19 mRNA vaccines

IntroductoryThe evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the emergence of many new variant lineages that have exacerbated the COVID-19 pandemic. Some of those variants were designated as variants of concern/interest (VOC/VOI) by national or international authorities based on many factors including their potential impact on vaccines. To ascertain and rank the risk of VOCs and VOIs, we analyzed their ability to escape from vaccine-induced antibodies. The variants showed differential reductions in neutralization and replication titers by post-vaccination sera. Although the Omicron variant showed the most escape from neutralization, sera collected after a third dose of vaccine (booster sera) retained moderate neutralizing activity against that variant. Therefore, vaccination remains the most effective strategy to combat the COVID-19 pandemic.

microbiology↗

bioRxiv2021

CyanoHABs: inevitable evolutionary ecological consequence for low nutrient-requiring cyanobacteria in water eutrophication

Cyanobacterial harmful algal blooms (CyanoHABs) arise as cyanobacteria dominate phytoplankton communities when nutrient levels increase from oligotrophic state. From a wholistic perspective, this longstanding altered phytoplankton structure results from two conditions: one sufficient condition that cyanobacteria can grow maximally with elevated nutrients; one necessary condition that co-living algae cannot grow fast or dominate at the same levels. The sufficient condition, the special mechanism of CyanoHABs at the population level, has been established as the synergistic interaction between superior cyanobacterial ecophysiology and elevated nutrients. But it is unknown how these functions arise or whether they are under directed evolution to water eutrophication. The necessary condition, the general mechanism of CyanoHABs at the community level, is little understood: why co-living algae cannot form blooms as cyanobacteria? Literature and bioinformatics analyses show that the superior ecophysiology undergoes no directed positive evolution to worldwide eutrophication in general or any local eutrophic waters in particular; instead, these functions are under strong purifying selection and likely acquired through early adaptive radiation in nutrient-deficient conditions, as functions enabling extant cyanobacteria to occupy other niches. The general mechanism turns out to be quite straightforward: cyanobacteria are simple life forms and thus have lower per capita nutrient demand for growth, compared to co-existing eukaryotic algae in cell size and structure, genome size, size of genome-scale metabolic networks, cell content, nutrient requirement. Lower nutrient demand is proved by existing field nutrient supplementation. Both the special and general mechanisms of CyanoHABs are tentative frameworks awaiting further theoretic improvement and empirical assessment.

evolutionary biology↗

bioRxiv2021

Different structures and pathologies of alpha-synuclein fibrils derived from preclinical and postmortem patients of Parkinson's disease

-Synuclein (-syn) fibrillar aggregates are the major component of Lewy bodies and Lewy neurites presenting as the pathology hallmark of Parkinsons disease (PD). Studies have shown that -syn is potential to form different conformational fibrils associated with different synucleinopathies, but whether the conformation of -syn fibrils changes in different phases of related diseases is to be explored. Here, we amplified -syn aggregates from the cerebrospinal fluid (CSF) of preclinical (pre-PD) and late-stage postmortem PD (post-PD) patients. Our results show that compared to the CSF of pre-PD, that of post-PD is markedly stronger in seeding in vitro -syn aggregation, and the amplified fibrils are more potent in inducing endogenous -syn aggregation in neurons. Cryo-electron microscopic structures further reveal that the difference between the pre-PD- and post-PD-derived fibrils lies on a minor polymorph which in the pre-PD fibrils is morphologically straight, while in the post-PD fibrils represents a single protofilament assembled by a distinctive conformation of -syn. Our work demonstrates structural and pathological differences between pre-PD and post-PD -syn aggregation and suggests potential alteration of -syn fibrils during the progression of PD clinical phases. Significance StatementIncreasing evidence support different conformational -syn fibrils in patients with different -synucleinopathies, but whether the conformation of -syn fibrils changes in different phases of related diseases is unknown. Here, we show that -syn fibrils amplified from the cerebrospinal fluid (CSF) of the late-stage postmortem PD (post-PD) patient are more potent in inducing endogenous -syn aggregation in neurons than that amplified from the preclinical (pre-PD) patient. Cryo-EM structures further reveal that the post-PD fibrils contain a novel conformation that is distinct from either the pre-PD fibrils or those previously reported. Our work suggests conformational evolution of -syn fibrils along with PD progression.

biophysics↗

bioRxiv2021

Developing a More Accurate Biomedical Literature Retrieval Method using Deep Learning and Citations in PubMed Central Full-text Articles

Most queries submitted to a literature search engine can be more precisely written as sentences to give the search engine more specific information. Sentence queries should be more effective, in principle, than short queries with small numbers of keywords. Querying with full sentences is also a key step in question-answering and citation recommendation systems. Despite the considerable progress in natural language processing (NLP) in recent years, using sentence queries on current search engines does not yield satisfactory results. In this study, we developed a deep learning-based method for sentence queries, called DeepSenSe, using citation data available in full-text articles obtained from PubMed Central (PMC). A large amount of labeled data was generated from millions of matched citing sentences and cited articles, making it possible to train quality predictive models using modern deep learning techniques. A two-stage approach was designed: in the first stage we used a modified BM25 algorithm to obtain the top 1000 relevant articles; the second stage involved re-ranking the relevant articles using DeepSenSe. We tested our method using a large number of sentences extracted from real scientific articles in PMC. Our method performed substantially better than PubMed and Google Scholar for sentence queries.

bioinformatics↗

bioRxiv2021

De novo Prediction of Cell-Drug Sensitivities Using Deep Learning-based Graph Regularized Matrix Factorization

Application of artificial intelligence (AI) in precision oncology typically involves predicting whether the cancer cells of a patient (previously unseen by AI models) will respond to any of a set of existing anticancer drugs, based on responses of previous training cell samples to those drugs. To expand the repertoire of anticancer drugs, AI has also been used to repurpose drugs that have not been tested in an anticancer setting, i.e., predicting the anticancer effects of a new drug on previously unseen cancer cells de novo. Here, we report a computational model that addresses both of the above tasks in a unified AI framework. Our model, referred to as deep learning-based graph regularized matrix factorization (DeepGRMF), integrates neural networks, graph models, and matrix-factorization techniques to utilize diverse information from drug chemical structures, their impact on cellular signaling systems, and cancer cell cellular states to predict cell response to drugs. DeepGRMF learns embeddings of drugs so that drugs sharing similar structures and mechanisms of action (MOAs) are closely related in the embedding space. Similarly, DeepGRMF also learns representation embeddings of cells such that cells sharing similar cellular states and drug responses are closely related. Evaluation of DeepGRMF and competing models on Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets show its superiority in prediction performance. Finally, we show that the model is capable of predicting effectiveness of a chemotherapy regimen on patient outcomes for the lung cancer patients in The Cancer Genome Atlas (TCGA) dataset.*

bioinformatics↗

bioRxiv2021

Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers

Cancer is a disease of gene dysregulation, where cells acquire somatic and epigenetic alterations that drive aberrant cellular signaling. These alterations adversely impact transcriptional programs and cause profound changes in gene expression. Interpreting somatic alterations within context-specific transcriptional programs will facilitate personalized therapeutic decisions but is a monumental task. Toward this goal, we develop a partially interpretable neural network model called Chromatin-informed Inference of Transcriptional Regulators Using Self-attention mechanism (CITRUS). CITRUS models the impact of somatic alterations on transcription factors and downstream transcriptional programs. Our approach employs a self-attention mechanism to model the contextual impact of somatic alterations. Furthermore, CITRUS uses a layer of hidden nodes to explicitly represent the state of transcription factors (TFs) to learn the relationships between TFs and their target genes based on TF binding motifs in the open chromatin regions of tumor samples. We apply CITRUS to genomic, transcriptomic, and epigenomic data from 17 cancer types profiled by The Cancer Genome Atlas. CITRUS predicts patient-specific TF activities and reveals transcriptional program variations between and within tumor types. We show that CITRUS yields biological insights into delineating TFs associated with somatic alterations in individual tumors. Thus, CITRUS is a promising tool for precision oncology.

bioinformatics↗

bioRxiv2021

Miniature inverted-repeat transposable elements drive rapid microRNA diversification in angiosperms

MicroRNAs (miRNAs) are rapidly evolving endogenous small RNAs programing organism function and behavior. Although models for miRNA origination have been proposed based on sporadic cases, the genomic mechanisms driving swift diversification of the miRNA repertoires in plants remain elusive. Here, by comprehensively analyzing 20 phylogenetically representative plant species, we identified miniature inverted-repeat transposable elements (MITEs) as the predominant genomic sources for de novo miRNAs in angiosperms. Our data illustrated a transposition-transcription process whereby properly sized MITEs transposed into active genic regions could be converted into new miRNAs, termed MITE-miRNAs, in as few as 20 generations. We showed that this molecular domestication mechanism leads to a possible evolutionary arms race between the MITEs and the host genomes that rapidly and continuously changes the miRNA repertoires. We found that the MITE-miRNAs are selected for targeting genes associated with plant adaptation and habitat expansion, thereby constituting a genomic innovation potentially underlying angiosperm megadiversity.

plant biology↗