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71 results for “plant architecture”
Data from: The genetic architecture of plant defense tradeoffs in a common monkeyflower
<p>Determining how adaptive combinations of traits arose requires understanding the prevalence and scope of genetic constraints. Frequently observed phenotypic correlations between plant growth, defenses, and/or reproductive timing have led researchers to suggest that pleiotropy or strong genetic linkage between variants affecting independent traits is pervasive. Alternatively, these correlations could arise via independent mutations in different genes for each trait and extensive correlational selection. Here we evaluate these alternatives by conducting a QTL mapping experiment involving a cross between two populations of common monkeyflower (<em>Mimulus guttatus</em>) that differ in growth rate as well as total concentration and arsenal composition of plant defense compounds, phenylpropanoid glycosides (PPGs). We find no evidence that pleiotropy underlies correlations between defense and growth rate. However, there is a strong genetic correlation between levels of total PPGs and flowering time that is largely attributable to a single shared QTL. While this result suggests a role for pleiotropy/close linkage, several other QTLs also contribute to variation in total PPGs. Additionally, divergent PPG arsenals are influenced by a number of smaller-effect QTLs that each underlie variation in one or two PPGs. This result indicates that chemical defense arsenals can be finely-adapted to biotic environments despite sharing a common biochemical precursor. Together, our results show correlations between defense and life history traits are influenced by pleiotropy or genetic linkage, but genetic constraints may have limited impact on future evolutionary responses, as a substantial proportion of variation in each trait is controlled by independent loci.</p>
FIG. 1. — L in Architectures de plantes de l'Île Robinson Crusoe, archipel Juan Fernández, Chili
FIG. 1. — L'archipel Juan Fernández, à 700 km à l'ouest de Valparaíso.
Analyzing defense-in-depth properties of nuclear power plant instrumentation and control system architectures using ontologies
<p>A proof-of-concept OWL ontology for representing knowledge over nuclear overall instrumentation & control (I&C) system architectures, and two case studies built around a proposed US variant of the European Pressurized Water Reactor and the NuScale Small Modular Reactor.</p>
The genetic architecture of repeated local adaptation to climate in distantly related plants
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Data from: The genetic architecture of plant defense tradeoffs in a common monkeyflower
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Data from: The NBS-LRR architectures of plant R-proteins and metazoan NLRs evolved in independent events
There are intriguing parallels between plants and animals, with respect to the structures of their innate immune receptors, that suggest universal principles of innate immunity. The cytosolic nucleotide binding site–leucine rich repeat (NBS-LRR) resistance proteins of plants (R-proteins) and the so-called NOD-like receptors of animals (NLRs) share a domain architecture that includes a STAND (signal transduction ATPases with numerous domains) family NTPase followed by a series of LRRs, suggesting inheritance from a common ancestor with that architecture. Focusing on the STAND NTPases of plant R-proteins, animal NLRs, and their homologs that represent the NB-ARC (nucleotide-binding adaptor shared by APAF-1, certain R gene products and CED-4) and NACHT (named for NAIP, CIIA, HET-E, and TEP1) subfamilies of the STAND NTPases, we analyzed the phylogenetic distribution of the NBS-LRR domain architecture, used maximum-likelihood methods to infer a phylogeny of the NTPase domains of R-proteins, and reconstructed the domain structure of the protein containing the common ancestor of the STAND NTPase domain of R-proteins and NLRs. Our analyses reject monophyly of plant R-proteins and NLRs and suggest that the protein containing the last common ancestor of the STAND NTPases of plant R-proteins and animal NLRs (and, by extension, all NB-ARC and NACHT domains) possessed a domain structure that included a STAND NTPase paired with a series of tetratricopeptide repeats. These analyses reject the hypothesis that the domain architecture of R-proteins and NLRs was inherited from a common ancestor and instead suggest the domain architecture evolved at least twice. It remains unclear whether the NBS-LRR architectures were innovations of plants and animals themselves or were acquired by one or both lineages through horizontal gene transfer.
Data from: The genetic architecture of ecological adaptation: intraspecific variation in host plant use by the lepidopteran crop pest Chloridea virescens
Intraspecific variation in ecologically important traits is a cornerstone of Darwin's theory of evolution by natural selection. The evolution and maintenance of this variation depends on genetic architecture, which in turn determines responses to natural selection. Some models suggest that traits with complex architectures are less likely to respond to selection than those with simple architectures, yet rapid divergence has been observed in such traits. The simultaneous evolutionary lability and genetic complexity of host plant use in the Lepidopteran subfamily Heliothinae suggest that architecture may not constrain ecological adaptation in this group. Here we investigate the response of Chloridea virescens, a generalist that feeds on diverse plant species, to selection for performance on a novel host, Physalis angulata (Solanaceae). P. angulata is the preferred host of Chloridea subflexa, a narrow specialist on the genus Physalis. In previous experiments, we found that the performance of C. subflexa on P. angulata depends on many loci of small effect distributed throughout the genome, but whether the same architecture would be involved in the generalist's adoption of P. angulata was unknown. Here we report a rapid response to selection in C. virescens for performance on P. angulata, and establish that the genetic architecture of intraspecific variation is quite similar to that of the interspecific differences in terms of the number, distribution, and effect sizes of the QTL involved. We discuss the impact of genetic architecture on the ability of Heliothine moths to respond to varying ecological selection pressures.
Data from: Genetic architecture of adaptation to novel environmental conditions in a predominantly selfing allopolyploid plant
Genetic architecture of adaptation is traditionally studied in the context of local adaptation, viz. spatially varying conditions experienced by the species. However, human made changes in the natural environment pose a new context to this issue, i.e. adaptation to an environment that is new for the species. In this study, we used crossbreeding to analyze genetic architecture of adaptation to conditions not currently experienced by the species but with high probability of encounter in the near future due to the global climate change. We performed targeted inter-population crossing using genotypes from two core and two peripheral Triticum dicoccoides populations and grew up the parents and three generations of hybrids in a greenhouse under simulated desert conditions to analyze the genetic architecture of adaptation to these conditions and an effect of gene flow from plants having different origin. The observed in allopolyploid T. dicoccoides low importance of epistatic gene interactions and low probability of hybrid breakdown appear to be the result of permanent fixation of heterozygosity and lack of inter-genomic recombination in this species. At the same time, predominant but not complete selfing combined with an advantage of bivalent pairing of homologous chromosomes appear to maintain high genetic variability in T. dicoccoides, greatly enhancing its adaptive ability.
Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen
<p>Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus <i>Pseudocercospora fijiensis,</i> was recently identified in the northern Caribbean region<i>. </i>Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of <i>P. fijiensis </i>were identified in genomic regions by combining annotation analysis with available biological data.</p>
Supplementary Tables for the genome architecture of the fungal plant pathogens Cladosporium fulvum and Erysiphe necator and its relevance to pathogenicity
<p>This repository contains supplementary tables for the PhD disseration titled "The genome architecture of the fungal plant pathogens <em>Cladosporium fulvum</em> and <em>Erysiphe necator</em> and its relevance to pathogenicity".</p> <p> </p> <p> </p>
Data from: Effects of apical meristem mining on plant fitness, architecture and flowering phenology in Cirsium altissimum (Asteracaeae)
Premise of the study: Interactions that limit lifetime seed production have the potential to limit plant population sizes and drive adaptation through natural selection. Effects of insect herbivory to apical meristems (apical meristem mining) on lifetime seed production rarely have been quantified experimentally. We studied Cirsium altissimum (tall thistle), whose meristems are mined by Platyptilia carduidactyla (artichoke plume moth), to determine how apical damage affects plant maternal fitness and evaluate both direct and indirect mechanisms underlying these effects. Methods: In restored prairie, apical mining was manipulated on tall thistles by applying insecticide, water, or no spray to apical meristems. We quantified effects on lifetime seed production, plant architecture, and flowering phenology. Seed germinability and seedling mass were evaluated in a greenhouse. Key results: Apical meristem miners decreased lifetime seed production of C. altissimum, but not seed quality. Higher mortality rates of damaged plants contributed to reduced seed production. Apical damage reduced plant height and increased the proportion of blooming flower heads in axial positions on branches. Apical damage delayed flowering and shortened flowering duration. Conclusions: Apical meristem mining reduced plant maternal fitness. The shift in the identity of blooming flower heads from terminal to axial positions contributed to this reduction because axial heads are less fecund. Shorter, meristem-mined plants may have been more susceptible to competition, and this susceptibility may explain their higher mortality rates. The kinds of changes in architecture and phenology that resulted from apical damage to C. altissimum have been shown to affect floral visitation in other plant species.
Dataset: Bridging Time-series Image Phenotyping and Functional-Structural Plant Modeling to Predict Adventitious Root System Architecture
<p>Dataset for Bridging Time-series Image Phenotyping and Functional-Structural Plant Modeling to Predict Adventitious Root System Architecture manuscript submitted to Plant Phenomics. The dataset contains raw and processed root architecture images, RhizoVision trait outputs, and the associated R scripts for statistical analysis and model parameterization.</p>
Fig. 4 in Phylogeny and domain architecture of plant ribosome inactivating proteins
Fig. 4. - Circular gene tree of RIPs. Our dataset comprised a curated selection from all the proteins available within NCBI's Conserved Domain Database containing a RIP domain. The phylogenetic tree was constructed using the maximum-likelihood method with the amino acid substitution model WAG + R9, ultrafast bootstrapping approximation (UFBoot) with 1000 iterations and the SH-like approximate likelihood ratio test with 1000 iterations. The legend titled 'Order (outer ring)' outlines the coloured dots around the perimeter of the tree and represents the phylogenetic order from which each protein sequence originated. Proteins without a coloured dot belong to orders with less than ten proteins. The legend titled 'RIP domains (inner lines)' defines colours in the branches of the tree, each representing a RIP group, based on presence/absence of a signal peptide and domains listed in both NCBI's Conserved Domain and Protein databases. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Phylogeny and domain architecture of plant ribosome inactivating proteins
Fig. 2. - The number and type of RIPs within each plant order. Our dataset comprised a curated selection from all the proteins available within NCBI's Conserved Domain Database containing a RIP domain. The groups were sorted based on presence/absence of a signal peptide and domains listed in both NCBI's Conserved Domain and Protein databases. Colours represent different RIP groups. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 6 in Phylogeny and domain architecture of plant ribosome inactivating proteins
Fig. 6. Tile plot of the most conserved amino acids within RIP domains of each protein group. The Y axis depicts the amino acid and corresponding position within the pokeweed antiviral protein (protein databank: 1QCI), the X axis depicts the proteins groups. For the two pink-highlighted amino acids on the Y axis, different amino acids were present in 70% of sequences at that position but were not present in the amino acid sequence of the crystal structure. The solid blue cells represent amino acids conserved at least 70% within each RIP group and with shared identity to the reference sequence 1QCI. Patterned blue cells represent amino acids conserved at least 70% within RIP groups but without identity to 1QCI. Any amino acid positions with 70% consensus in less than three protein groups were collapsed and shaded black.
Fig. 3 in Phylogeny and domain architecture of plant ribosome inactivating proteins
Fig. 3. - The number of RIPs within each plant species. Our dataset comprised a curated selection from all the proteins available within NCBI's Conserved Domain Database containing a RIP domain. The groups were sorted based on presence/absence of a signal peptide and domains listed in both NCBI's Conserved Domain and Protein databases. Colours represent different RIP groups. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Phylogeny and domain architecture of plant ribosome inactivating proteins
Fig. 1. - Physicochemical characteristics of different RIP groups. Values were calculated from the amino acid coding sequence of each protein in our dataset with the R package 'peptides' and presented on boxplot format. Our dataset comprised a curated selection from all the proteins available within NCBI's Conserved Domain Database containing a RIP domain. The groups were sorted based on presence/absence of a signal peptide and domains listed in both NCBI's Conserved Domain and Protein databases. (A) molecular weight prediction; (B) theoretical net charge prediction; (C) Boman potential protein interaction index prediction; (D) aliphatic index prediction.
Fig. 5. - The most highly conserved RIP amino acids. Our dataset comprised a in Phylogeny and domain architecture of plant ribosome inactivating proteins
Fig. 5. - The most highly conserved RIP amino acids. Our dataset comprised a curated selection from all the proteins available within NCBI's Conserved Domain Database containing a RIP domain. Colours indicate amino acids conserved in at least 70% of sequences. For the two pink-highlighted proteins, the black bolded amino acids were present in 70% of sequences at that position but were not present in the amino acid sequence of the crystal structure. (A) Sequence alignment. RIP domain consensus: the consensus sequence generated from the multiple sequence alignment in Jalview excluding gaps; 1QCI: the amino acid sequence of pokeweed antiviral protein (protein databank: 1QCI). The third line denotes the similarity in the two sequences as determined by Clustal Omega. (B) The crystal structure of 1QCI visualized in UCSF ChimeraX in surface representation; (C) mesh representation; and (D) cartoon representation. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Data from: The NBS-LRR architectures of plant R-proteins and metazoan NLRs evolved in independent events
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Data from: Genetic architecture of adaptation to novel environmental conditions in a predominantly selfing allopolyploid plant
Open the record for dataset details and reuse information.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.