Biology subjects

Qiu, Y.

Publications and source records attributed to Qiu, Y..

At least 163 records · Page 9Linked to original sources

bioRxiv2022

Comparative miRNA Transcriptomics of Mouse and Macaque Reveals Cytoskeleton is An Inhibitor for C. neoformans Invasion into Brain

Cryptococcal meningoencephalitis is an emerging infection shifted from primarily ART-naive to being ART-experienced HIV/AIDS patients, COVID-19 patients and also in immune competent individuals, mainly caused by the human opportunistic pathogen Cryptococcus neoformans, yet mechanisms of the brain or CNS dissemination remain to elucidate, which is the deadest process for the disease. Meanwhile, illustrations of clinically relevant responses in cryptococcosis were limited, as the low availabilities of clinical samples. In this study, macaque and mouse infection models were employed and miRNA-mRNA transcriptomes were performed and combined, which revealed cytoskeleton, a major feather in HIV/AIDS patients, was a centric pathway regulated in both two infection models. Notably, assays of clinical immune cells confirmed an enhanced "Trojan Horse" in HIV/AIDS patients, which can be shut down by cytoskeleton inhibitors. Furthermore, we identified a novel enhancer for macrophage "Trojan Horse", myocilin, and an enhanced fungal burden was achieved in brains of MYOC transgenic mice. Taking together, this study reveals fundamental roles of cytoskeleton and MYOC in blocking fungal CNS dissemination, which not only helps to understand the high prevalence of cryptococcal meningitis in HIV/AIDS, but also facilitates the development of novel drugs for therapies of meningoencephalitis caused by C. neoformans and other pathogenic microorganisms.

microbiology↗

bioRxiv2022

Novel plasma exosome biomarkers for prostate cancer progression in co-morbid metabolic disease

Comorbid Type 2 diabetes (T2D), a metabolic complication of obesity, associates with worse cancer outcomes for prostate, breast, head and neck, colorectal and several other solid tumors. However, the molecular mechanisms remain poorly understood. Emerging evidence shows that exosomes carry miRNAs in blood that encode the metabolic status of originating tissues and deliver their cargo to target tissues to modulate expression of critical genes. Exosomal communication potentially connects abnormal metabolism to cancer progression. Here, we hypothesized that T2D plasma exosomes induce epithelial-mesenchymal transition (EMT) and immune checkpoints in prostate cancer cells. We demonstrate that plasma exosomes from subjects with T2D induce EMT features in prostate cancer cells and upregulate the checkpoint genes CD274 and CD155. We demonstrate that specific exosomal miRNAs that are differentially abundant in plasma of T2D adults compared to nondiabetic controls (miR374a-5p, miR-93-5p and let-7b-3p) are delivered to cancer cells, thereby regulating critical target genes. We build on our previous reports showing BRD4 controls migration and dissemination of castration-resistant prostate cancer, and transcription of key EMT genes, to show that T2D exosomes require BRD4 to drive EMT and immune ligand expression. We validate our findings with gene set enrichment analysis of human prostate tumor tissue in TGCA genomic data. These results suggest novel, non-invasive approaches to evaluate and potentially block progression of prostate and other cancers in patients with comorbid T2D.

cancer biology↗

bioRxiv2022

Conserved Untranslated Regions of Multipartite Viruses: Natural Markers of Novel Viral Genomic Components and Tags of Viral Evolution

Viruses with split genomes are categorized as being either segmented or multipartite according to whether their genomic segments occur in single or different virions. Some complexity will exist, in that inherited "core" vital segments viruses may renew the others once host and environmental alterations keep driving viral evolution. Despite this uncertainty, empirical observations have been made across the split genomes in the untranslated regions (UTRs) on the short or long stretches of conserved or identical sequences. In this study, we describe a methodology that combines RNA and small RNA sequencing, conventional BLASTx, and iterative BLASTn of UTRs to detect viral genomic components even if they encode orphan genes (ORFans). Within the phylum Kitrinoviricota, novel putative multipartite viruses and viral genomic components were annotated using data obtained from our sampling or publicly available sources. The novel viruses, as extensions or intermediate nodes, enriched the information of the evolutionary networks. Furthermore, the diversity of novel genomic components emphasized the evolutionary roles of reassortment and recombination, as well as genetic deletion, strongly supporting the genomic complexity. These data also suggest insufficient knowledge of these genomic components for categorizing some extant viral taxa. The relative conservation of UTRs at the genome level may explain the relationships between monopartite and multipartite viruses and how the multipartite viruses can have a life strategy involving multiple host cells. Author summaryThe current workflows for virus identification are largely based on high-throughput sequencing and coupled protein sequence homology-dependent analysis methods and tools. However, for viruses with split genomes, the identification of genomic components whose deduced protein sequences are not homologous to known sequences is inadequate. Furthermore, many plant-infecting multipartite viruses contain conserved UTRs across their genomic components. Based on this, we propose a practical method of UTR-backed iterative BLASTn (UTR-iBLASTn) to explore the components with ORFans and study virus evolution using the UTRs as signals. These shed light on viral "dark matter"--unknown/omitted genomic components of segmented/multipartite viruses from different kingdoms and hosts, and the origins of these components.

microbiology↗

bioRxiv2022

AAV11 permits efficient retrograde targeting of projection neurons

Viral tracers that permit efficient retrograde targeting of projection neurons are powerful vehicles for structural and functional dissections of the neural circuit and for the treatment of brain diseases. Recombinant adeno-associated viruses (rAAVs) are the most potential candidates because they are low-toxic with high-level transgene expression and minimal host immune responses. Currently, some rAAVs based on capsid engineering for retrograde tracing have been widely used in the analysis and manipulation of neural circuits, but suffer from brain area selectivity and inefficient retrograde transduction in certain neural connections. Here, we discovered that the recombinant adeno-associated virus 11 (rAAV11) exhibits potent retrograde labeling of projection neurons with enhanced efficiency to rAAV2-retro in some neural connections. Combined with calcium recording technology, rAAV11 can be used to monitor neuronal activities by expressing Cre recombinase or calcium-sensitive functional probe. In addition, we further showed the suitability of rAAV11 for astrocyte targeting. These properties make rAAV11 a promising tool for the mapping and manipulation of neural circuits and gene therapy of some neurological and neurodegenerative disorders. HighlightsO_LINaturally occurring AAV serotype capsid exhibits robust retrograde functionality C_LIO_LIImproved distribution properties and retrograde transport efficiency C_LIO_LICan express Cre recombinase or calcium-sensitive functional probe for neural circuits monitoring C_LIO_LICan specifically target astrocytes C_LI

neuroscience↗

bioRxiv2022

Efficient coding of natural scenes improves neural system identification

Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the "stand-alone" system identification model, it also produced more biologically-plausible filters. We found these results to be consistent for retinal responses to different stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. In summary, our results support the hypothesis that efficiently encoding environmental inputs can improve system identification models of early visual processing.

neuroscience↗

bioRxiv2022

Glutamine is required for M1-like polarization in response to Mycobacterium tuberculosis infection

In response to Mycobacterium tuberculosis infection, macrophages mount early proinflammatory and antimicrobial responses similar to those observed in M1 macrophages classically activated by LPS and IFN-{gamma}. A metabolic reprogramming to HIF-1-mediated uptake of glucose and its metabolism by glycolysis is required for M1-like polarization, but little is known about other metabolic programs driving M1-like polarization during M. tuberculosis infection. Identification and quantification of labeling patterns of U13C glutamine and U13C glucose-derived metabolites demonstrated that glutamine, rather than glucose, is catabolized in both the oxidative and reductive TCA cycle of M1-like macrophages, thereby generating signaling molecules that include succinate, biosynthetic precursors such as aspartate, and the antimicrobial metabolite itaconate. This conclusion is corroborated by diminished M1 polarization via chemical inhibition of glutaminase (GLS), the key enzyme of the glutaminolysis pathway, and by genetic deletion of GLS in infected macrophages. Furthermore, characterization of the labeling distribution pattern of U15N glutamine in M1-like macrophages indicates that glutamine serves as a nitrogen source for the synthesis of intermediates of purine and pyrimidine metabolism plus amino acids including aspartate. Thus, the catabolism of glutamine, as an integral component of metabolic reprogramming in activating macrophages, fulfills the cellular demand for bioenergetic and biosynthetic precursors of M1-like macrophages. Knowledge of these new immunometabolic features of M1-like macrophages is expected to advance the development of host-directed therapies that will enhance bacterial clearance and prevent immunopathology during tuberculosis. SummaryRecent advances in immunometabolism have stimulated increasing interest in understanding the specific cellular metabolic states of immune cells associated with the various disease states of tuberculosis. As the primary target of Mycobacterium tuberculosis (Mtb) infection, macrophages play essential roles in dictating the progression and final outcome of infection. Previous studies, including our own, show that the upregulation of hypoxia-inducible-factor 1 alpha (HIF-1) and a metabolic reprogramming to the Warburg effect-like state are general features of the host immune cell response to Mtb infection. They are also critical for macrophage polarization to the M1-like phenotype characterized by high-level expression of proinflammatory and antimicrobial molecules against Mtb infection. However, our knowledge about the immunometabolic features of M1-like macrophages is poor. Using widely targeted small metabolite (WTSM) screening (600+ small polar metabolites) and stable isotope tracing of U13 glutamine, U13 glucose, and N15 glutamine, as well as therapeutic and genetic approaches, we report that, in addition to elevated glucose catabolism by glycolysis, glutamine serves as an important carbon and nitrogen source for the generation of building blocks, signaling molecules, and antimicrobial metabolite during macrophage polarization to the M1-like phenotype. The study adds novel insights into the immunometabolic properties of Mtb-infected macrophages.

immunology↗

bioRxiv2021

Chemical-induced Gene Expression Ranking and its Application to Pancreatic Cancer Drug Repurposing

Chemical-induced gene expression profiles provide critical information on the mode of action, off-target effect, and cellar heterogeneity of chemical actions in a biological system, thus offer new opportunities for drug discovery, system pharmacology, and precision medicine. Despite their successful applications in drug repurposing, large-scale analysis that leverages these profiles is limited by sparseness and low throughput of the data. Several methods have been proposed to predict missing values in gene expression data. However, most of them focused on imputation and classification settings which have limited applications to real-world scenarios of drug discovery. Therefore, a new deep learning framework named chemical-induced gene expression ranking (CIGER) is proposed to target a more realistic but more challenging setting in which the model predicts the rankings of genes in the whole gene expression profiles induced by de novo chemicals. The experimental results show that CIGER significantly outperforms existing methods in both ranking and classification metrics for this prediction task. Furthermore, a new drug screening pipeline based on CIGER is proposed to select approved or investigational drugs for the potential treatments of pancreatic cancer. Our predictions have been validated by experiments, thereby showing the effectiveness of CIGER for phenotypic compound screening of precision drug discovery in practice.

bioinformatics↗

bioRxiv2021

The different brain areas occupied for integrating information of hierarchical linguistic units: a study based on EEG and TMS

Human linguistic units are hierarchical, and our brain responds differently when processing linguistic units during sentence comprehension, especially when the modality of the received signal is different (auditory, visual, or audio-visual). However, it is unclear how the brain processes and integrates language information at different linguistic units (words, phrases, and sentences) provided simultaneously in audio and visual modalities. To address the issue, we presented participants with sequences of short Chinese sentences through auditory or visual or combined audio- visual modalities, while electroencephalographic responses were recorded. With a frequency tagging approach, we analyzed the neural representations of basic linguistic units (i.e., characters/monosyllabic words) and higher-level linguistic structures (i.e., phrases and sentences) across the three modalities separately. We found that audio-visual integration occurs at all linguistic units, and the brain areas involved in the integration varied across different linguistic levels. In particular, the integration of sentences activated the local left prefrontal area. Therefore, we used continuous theta-burst stimulation (cTBS) to verify that the left prefrontal cortex plays a vital role in the audio-visual integration of sentence information. Our findings suggest the advantage of bimodal language comprehension at hierarchical stages in language-related information processing and provide evidence for the causal role of the left prefrontal regions in processing information of audio-visual sentences.

neuroscience↗

bioRxiv2021

An atlas of human viruses provides new insights into diversity and tissue tropism of human viruses

Viruses continue to threaten human health. Yet, the complete viral species carried by humans and their infection characteristics have not been fully revealed. This study curated an atlas of human viruses from public databases and literatures, and built the Human Virus Database (HVD) available at http://computationalbiology.cn/humanVirusBase/#/. The HVD contains 1,131 virus species of 54 viral families which were more than twice the number of the human-infecting virus species reported in previous studies. These viruses were identified in human samples including 68 human tissues, the excreta and body fluid. The viral diversity in humans was age-dependent with a peak in the infant and a valley in the teenager. The tissue range of viruses was found to be associated with several factors including the viral group (DNA, RNA or reverse-transcribing viruses), enveloped or not, viral genome length and GC content, viral receptors and the virus-interacting proteins. Finally, the tissue range of DNA viruses was predicted using a random-forest algorithm with a medium performance. Overall, the study not only provides a valuable resource for further studies of human viruses, but also deepens our understanding towards the diversity and tissue tropism of human viruses.

microbiology↗

bioRxiv2021

Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines

Beta cells intrinsically contribute to the pathogenesis of type 1 diabetes (T1D), but the genes and molecular processes that mediate beta cell survival in T1D remain largely unknown. We combined high throughput functional genomics and human genetics to identify T1D risk loci regulating genes affecting beta cell survival in response to the proinflammatory cytokines IL-1{beta}, IFN{gamma}, and TNF. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) active in beta cells using ATAC-seq and single nuclear ATAC-seq (snATAC-seq), and linked cytokine-responsive beta cell cCREs to putative target genes using single cell co-accessibility and HiChIP. We performed a genome-wide pooled CRISPR loss-of-function screen in EndoC-{beta}H1 cells, which identified 867 genes affecting cytokine-induced beta cell loss. Genes that promoted beta cell survival and had up-regulated expression in cytokine exposure were specifically enriched at T1D loci, and these genes were preferentially involved in inhibiting inflammatory response, ubiquitin-mediated proteolysis, mitophagy and autophagy. We identified 2,229 variants in cytokine-responsive beta cell cCREs altering transcription factor (TF) binding using high-throughput SNP-SELEX, and variants altering binding of TF families regulating stress, inflammation and apoptosis were broadly enriched for T1D association. Finally, through integration with genetic fine mapping, we annotated T1D loci regulating beta cell survival in cytokine exposure. At the 16p13 locus, a T1D variant affected TF binding in a cytokine-induced beta cell cCRE that physically interacted with the SOCS1 promoter, and increased SOCS1 activity promoted beta cell survival in cytokine exposure. Together our findings reveal processes and genes acting in beta cells during cytokine exposure that intrinsically modulate risk of T1D.

genomics↗

bioRxiv2021

REViewer: Haplotype-resolved visualization of read alignments in and around tandem repeats

BackgroundExpansions of short tandem repeats are the cause of many neurogenetic disorders including familial amyotrophic lateral sclerosis, Huntington disease, and many others. Multiple methods have been recently developed that can identify repeat expansions in whole genome or exome sequencing data. Despite the widely-recognized need for visual assessment of variant calls in clinical settings, current computational tools lack the ability to produce such visualizations for repeat expansions. Expanded repeats are difficult to visualize because they correspond to large insertions relative to the reference genome and involve many misaligning and ambiguously aligning reads. ResultsWe implemented REViewer, a computational method for visualization of sequencing data in genomic regions containing long repeat expansions. To generate a read pileup, REViewer reconstructs local haplotype sequences and distributes reads to these haplotypes in a way that is most consistent with the fragment lengths and evenness of read coverage. To create appropriate training materials for onboarding new users, we performed a concordance study involving 12 scientists involved in STR research. We used the results of this study to create a user guide that describes the basic principles of using REViewer as well as a guide to the typical features of read pileups that correspond to low confidence repeat genotype calls. Additionally, we demonstrated that REViewer can be used to annotate clinically-relevant repeat interruptions by comparing visual assessment results of 44 FMR1 repeat alleles with the results of triplet repeat primed PCR. For 38 of these alleles, the results of visual assessment were consistent with triplet repeat primed PCR. ConclusionsRead pileup plots generated by REViewer offer an intuitive way to visualize sequencing data in regions containing long repeat expansions. Laboratories can use REViewer to assess the quality of repeat genotype calls as well as to visually detect interruptions or other imperfections in the repeat sequence and the surrounding flanking regions.

bioinformatics↗

bioRxiv2021

Neuronal glucose metabolism sets cholinergic tone and controls thermo-regulated signaling at the neuromuscular junction

Cholinergic and sympathetic counter-regulatory networks control numerous physiologic functions including learning/memory/cognition, stress responsiveness, blood pressure, heart rate and energy balance. As neurons primarily utilize glucose as their primary metabolic energy source, we generated mice with increased glycolysis in cholinergic neurons by specific deletion of the fructose-2,6-phosphatase protein TIGAR. Steady-state and stable isotope flux analyses demonstrated increased rates of glycolysis, acetyl-CoA production, acetylcholine levels and density of neuromuscular synaptic junction clusters with enhanced acetylcholine release. The increase in cholinergic signaling reduced blood pressure and heart rate with a remarkable resistance to cold-induced hypothermia. These data directly demonstrate that increased cholinergic signaling through the modulation of glycolysis has several metabolic benefits particularly to increase energy expenditure and heat production upon cold exposure. HighlightsO_LIDeficiency of a negative regulator of glycolysis (TIGAR) in cholinergic neurons increases the biosynthesis and content of the neurotransmitter acetylcholine. C_LIO_LIIncreased cholinergic tone reduces blood pressure and heart rate while enhancing signaling at neuromuscular junction. C_LIO_LIUpregulation of neuromuscular junction activation provides protection against the paralytic curare and cold-induced hypothermia. C_LIO_LIModulation of cholinergic neuron glycolysis may provide a novel therapeutic approach for treatment of diseases stemming from reduced acetylcholine signaling such as myasthenia gravis and sarcopenic pre-synaptic dysfunction. C_LI

cell biology↗

bioRxiv2021

A screen for mutants deficient in coronatine-mediated suppression of root immunity identifies Arabidopsis SDA1 as a novel integrator of immunity and phytohormone signaling

Despite the importance of the root immune system in the interaction with rhizosphere microbes, the majority of genetic screens for immunity regulators have been performed in leaves. A previous screen identified 27 hsm (hormone-mediated suppression of MAMP-triggered immunity) mutants that are impaired in jasmonic acid (JA)-mediated suppression of pattern-triggered immunity (PTI) in roots. Here we characterized 16 of the hsm mutants that retain JA sensitivity and are potential negative regulators of root immunity. We found that the majority of hsm mutants show enhanced resistance to Fusarium, a root fungal pathogen; however, only a subset are more resistant to a foliar pathogen. Surprisingly, 12 of 16 hsm mutants are also impaired in abscisic acid (ABA)-mediated suppression of PTI, suggesting a largely shared pathway between JA- and ABA-mediated immune suppression in roots. Although all hsm mutants are insensitive to JA-mediated suppression of root immunity, hsm4 shows hypersensitivity to JA-mediated root growth inhibition and JA-induced gene expression. Consistently, hsm4 is more resistant to leaf pathogens, suggesting that HSM4 is a negative regulator of both root and leaf immunity. Hsm4 was mapped to a mutation in a conserved ARM-repeat protein homologous to yeast SDA1, which has been reported to regulate 60S ribosome biogenesis. As translational reprogramming is a critical layer of immune regulation, this work suggests that AtSDA1 is a novel negative translational regulator of immunity. Additionally, a comprehensive characterization of all 16 hsm mutants provides a genetic toolkit to identify novel mechanisms that regulate root immunity.

plant biology↗

bioRxiv2021

Prediction of coronavirus 3C-like protease cleavage sites using machine-learning algorithms

The coronavirus 3C-like (3CL) protease is a Cysteine protease. It plays an important role in viral infection and immune escape by not only cleaving the viral polyprotein ORF1ab at 11 sites, but also cleaving the host proteins. However, there is still a lack of effective tools for determining the cleavage sites of the 3CL protease. This study systematically investigated the diversity of the cleavage sites of the coronavirus 3CL protease on the viral polyprotein, and found that the cleavage motif were highly conserved for viruses in the genera of Alphacoronavirus, Betacoronavirus and Gammacoronavirus. Strong residue preferences were observed at the neighboring positions of the cleavage sites. A random forest (RF) model was built to predict the cleavage sites of the coronavirus 3CL protease based on the representation of residues at cleavage site and neighboring positions by amino acid indexes, and the model achieved an AUC of 0.96 in cross-validations. The RF model was further tested on an independent test dataset composed of cleavage sites on host proteins, and achieved an AUC of 0.88 and a prediction precision of 0.80 when considering the accessibility of the cleavage site. Then, 1,079 human proteins were predicted to be cleaved by the 3CL protease by the RF model. These proteins were enriched in pathways related to neurodegenerative diseases and pathogen infection. Finally, a user-friendly online server named 3CLP was built to predict the cleavage sites of the coronavirus 3CL protease based on the RF model. Overall, the study not only provides an effective tool for identifying the cleavage sites of the 3CL protease, but also provides insights into the molecular mechanism underlying the pathogenicity of coronaviruses.

bioinformatics↗

bioRxiv2021

Predictive Modeling of Multiplex Chemical Phenomics for Novel Cells and Patients: Applied to Personalized Alzheimer's Disease Drug Repurposing

Chemical phenomics which measures multiplex chemical-induced phenotypic response of cells or patients, particularly dose-dependent transcriptomics and drug-response curves, provides new opportunities for in silico mechanism-driven phenotype-based drug discovery. However, state-of-the-art computational methods only focus on predicting a single phenotypic readout and are less successful in screening compounds for novel cells or individual patients. We designed a new deep learning model, MultiDCP, to enable high-throughput compound screening based on multiplex chemical phenomics for the first time, and further expand the scope of chemical phenomics to unexplored cells and patients. The novelties of MultiDCP lie in a multi-task learning framework with a novel knowledge-driven autoencoder to integrate incoherent labeled and unlabeled omics data, and a teacher-student training strategy to exploit unreliable data. MultiDCP significantly outperforms the state-of-the-art for novel cell lines. The predicted chemical transcriptomics demonstrate a stronger predictive power than noisy experimental data for downstream tasks. We applied MultiDCP to repurpose individualized drugs for Alzheimers disease, suggesting that MultiDCP is a potentially powerful tool for personalized medicine.

bioinformatics↗

bioRxiv2021

TGF--dependent Lymphoid Tissue Residency of Stem-like T cells Limits the Response to Tumor Vaccine

Stem-like CD8+ T cells represent the key subset responding to multiple tumor immunotherapies, including tumor vaccination. However, the signals that control the differentiation of stem-like T cells are not entirely known. Most previous investigations on stem-like T cells are focused on tumor infiltrating T cells (TIL). The behavior of stem-like T cells in other tissues remains to be elucidated. Tissue-resident memory T cells (TRM) are often defined as a non-circulating T cell population residing in non-lymphoid tissues. TILs carrying TRM features are associated with better tumor control. Here, we found that stem-like CD8+ T cells differentiated into TRMs in a TGF-{beta} and tumor antigen dependent manner almost exclusively in tumor draining lymph node (TDLN). TDLN-resident stemlike T cells were negatively associated with the response to tumor vaccine. In other words, after tumor vaccine, TDLN stem-like T cells transiently lost TRM features, differentiated into migratory effectors and exerted tumor control.

immunology↗

bioRxiv2021

Multi-environment QTL analysis delineates a major locus associated with homoeologous exchanges for water-use efficiency and seed yield in allopolyploid Brassica napus

O_LICanola varieties exhibit discernible variation in drought avoidance and drought escape traits, suggesting its adaptation to water-deficit environments. However, the underlying mechanisms are poorly understood. C_LIO_LIA doubled haploid (DH) population was analysed to identify QTL associated with water use efficiency (WUE) related traits. Based on the resequenced parental genome data, we developed sequence-capture based markers for fine mapping. mRNA-Seq was performed to determine the expression of candidate genes underlying QTL for carbon isotope discrimination ({Delta}13C). C_LIO_LIQTL contributing to main and QTL x Environment interaction effects for {Delta}13C and for agronomic WUE were identified. One multi-trait QTL for {Delta}13C, days to flower, plant height and seed yield was identified on chromosome A09, in the vicinity of ERECTA. Interestingly, this QTL region was overlapped with a homoeologous exchange event (HE), suggesting its association with the major QTL. Transcriptome analysis revealed several differentially expressed genes between parental lines, including in HE regions. C_LIO_LIThis study provides insights into the complexity of WUE related genes in the context of canola adaptation to water-deficit conditions. Our results suggest that alleles for high {Delta}13C contribute positively to canola yield. Genetic and genomic resources developed herein could be utilised to make genetic gains for improving canola WUE. C_LI

plant biology↗

bioRxiv2021

Endosperm evolution by duplicated and neofunctionalized Type I MADS-box transcription factors

MADS-box transcription factors (TFs) are present in nearly all major eukaryotic groups. They are divided into Type I and Type II that differ in domain structure, functional roles, and rates of evolution. In flowering plants, major evolutionary innovations like flowers, ovules and fruits have been closely connected to Type II MADS-box TFs. The role of Type I MADS-box TFs in angiosperm evolution remains to be identified. Here, we show that the formation of angiosperm-specific Type I MADS-box clades of M{gamma} and M{gamma}-interacting M genes (M*) can be tracked back to the ancestor of all angiosperms. Angiosperm-specific M{gamma} and M* genes were preferentially expressed in the endosperm, consistent with their proposed function as heterodimers in the angiosperm-specific embryo-nourishing endosperm tissue. We propose that duplication and diversification of Type I MADS-genes underpins the evolution of the endosperm, a developmental innovation closely connected to the origin and success of angiosperms.

plant biology↗