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1,715 results for “Arabidopsis thaliana; Arabidopsis”

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zenodo40/100

Historical Arabidopsis thaliana genomes from Germany

We report short-read Illumina sequencing of 35 Arabidopsis thaliana herbarium specimens collected in Southern Germany from 1817 to 1957. The historical genomes were sequenced to an average depth of ~7X. The herbarium-derived sequences showed patterns of degradation typical of ancient DNA with average read lengths of 78 bp, endogenous DNA content between 26%-93% (mean 72%; median 74%) and enrichment of cytosine to thymine substitutions at the read’s termini. We provide the sequences to the public with open access.

opencc-by-4.0Oct 2022View details →

zenodo40/100

Raster Image Correlation Spectroscopy and Brightness Measurements of AtLEA proteins from Arabidopsis thaliana

Temporal sequences of various fluorescent leaves were captured using a confocal scanning microscope (Olympus FV1000 inverted microscope), equipped with a 1.3 NA oil immersion 60X objective and the photon counting detection mode. Utilizing a 488 nm laser at 0.1% power and GFP filters/cubes, each temporal sequence involved the acquisition of 100 frames of 64x64 pixels, with a dwell time of 10 μs (1.76 ms per line, 130.24 ms per frame) and a pixel size of 66 nm (50X digital zoom). The interval between frames was set at 131.6 ms. Five plants were analyzed, each expressing one of four distinct genetic constructs fused to complementary fragments of Yellow Fluorescent Protein: pYFN-4-/5pYFC-4-5 (representing the complete AtLEA4-5 protein), pYFN-4-51-77/pYFC-4-51-77 (associated with the N-terminal region of AtLEA4-5), pYFN-4-578-158/pYFC-4-578-158 (relating to the C-terminal region of AtLEA4-5), and pYFN-pYFC (serving as the control). The raw data (*.oib files) were collected during three imaging sessions within a one-week period: - 220618 raw oib dataset.zip - 220622 raw oib dataset.zip - 220623 raw oib dataset.zip Images were converted to *.tif format using FIJI/ImageJ for further analysis and were archived in "tif dataset RICS NB LEAs.zip," excluding files with excessive movement of biological specimens. These images were then subjected to "Raster Image Correlation Spectroscopy" and "Number and Brightness" techniques for analysis. Notation: - h1, h2, h3, h4, h5: Replicates (plants) expressing one of four specific genetic constructs fused to complementary fragments of Yellow Fluorescent Protein. - 45: Fused to the full-length AtLEA4-5 protein (pYFN-4-/5pYFC-4-5). - 4h: Fused to the N-terminal region of AtLEA4-5 (pYFN-4-51-77/pYFC-4-51-77). - rc: Fused to the C-terminal region of AtLEA4-5 (pYFN-4-578-158/pYFC-4-578-158). - ct: The control condition (pYFN-pYFC).

opencc-by-4.0Apr 2024View details →

zenodo40/100

Indirect genetic effects are shaped by demographic history and ecology in Arabidopsis thaliana

This folder contains data & code used for the study "Indirect genetic effects are shaped by demographic history and ecology in Arabidopsis thaliana" All data analyzed in the study are stored in the folder "data": <ul> <li>"pheno_file.csv": the main phenotypic file corresponding to the experiment with paired plants used to estimate Indirect Genetic Effects.</li> <li>"pheno_file_single_plants.csv": phenotypic file with measurements of plant biomasses in the absence of competition (single plants)</li> <li>"call_method_75_TAIR9.csv": genomic data (SNPs) for each accession from the RegMap panel (ref [1])</li> <li>"Data_geo_RegMap_accessions.csv": geographic localization of each accession from the RegMap panel (ref [2])</li> <li>"igeGWAS_scores.csv": Genome-Wide Association Study (GWAS) results reporting for each SNP from the RegMap panel the p-value and estimated effect sizes of their direct and indirect genetic effects</li> <li>"1001_accessions_info.csv": geographic localization and admixture group for each accession from the 1001 genomes project (ref [3])</li> <li>"snp_data_all_samples.txt": allelic value of each accession from the 1001 genomes project at the eleven top SNPs associated with IGE</li> <li>"sample_names.txt": names of  accessions listed in the file "snp_data_all_samples.txt"</li> <li>"climatic_data.csv": climatic data for each accessions from the 1001 genomes project (ref [4])</li> <li>"candidate_genes_all.csv":  list of all genes (and associated GO terms) with a non-synonymous, nonsense, or frameshift mutation in close proximity (distance < half LD decay distance) and high linkage (r2>0.5) with a SNP significantly associated with IGE</li> <li>"genes.coord.bed": list of all genes in a +- 500 kb around top IGE SNPs and their coordinates</li> <li>"AllGenes_fst.GeneID.txt": pairwise Fst computed between each pair of admixture groups, for all genes annotated in the genome of A. thaliana</li> </ul> "ABBA_BABA" subfolder contains ABBA_BABA statistics computed for each individual chromosome (Chr1-Chr5) using genomic windows of 20 kb with at least 250 SNPs per windows. ABBA-BABA statistics were computed using custom python scripts from https://github.com/simonhmartin/genomics_general "GEA" subfolder contains Genome-Environment Association results, with one file per chromosome x climatic variable. Climatique variable are indexed, following the order listed in the file "Climatic_variables.txt" within the subfolder "GEA". GEA analysis were run with the gemma program: https://github.com/genetics-statistics/GEMMA. "LD_IGE_SNPs" subfolders contains the list of SNPs located at +- 2Mb of a significant IGE SNP (one file per IGE SNP, named "SNPalias_LDSimplified.csv") and their linkage (r2) with the IGE SNP. It also contains the file "LD_windows_sizes.csv" with the half LD decay distances for all significant IGE SNP. All analysis performed to produce the tables and figures presented in the study (main manuscript & supplementary information) were done with the R script "Arabidopsis_IGE_analysis.R", which uses "manhattan_custom.R" as a source function to produce custom manhattan plots.   REFERENCES: [1] Horton MW, Hancock AM, Huang YS, Toomajian C, Atwell S, Auton A, Muliyati NW, Platt A, Sperone FG, Vilhjálmsson BJ, et al. 2012. Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel. Nature Genetics 44: 212–216. [2] Anastasio AE, Platt A, Horton M, Grotewold E, Scholl R, Borevitz JO, Nordborg M, Bergelson J. 2011. Source verification of mis-identified Arabidopsis thaliana accessions. The Plant Journal 67: 554–566. [3] 1001 Genomes Consortium. 2016. 1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell 166: 481–491. [4] Ferrero-Serrano Á, Assmann SM. 2019. Phenotypic and genome-wide association with the local environment of Arabidopsis. Nature Ecology & Evolution 3: 274–285.

opencc-by-4.0Jan 2023View details →

dryad40/100

Data from: Genome-wide association mapping within a local Arabidopsis thaliana population more fully reveals the genetic architecture for defensive metabolite diversity

A paradoxical finding from genome-wide association studies (GWAS) in plants is that variation in metabolite profiles typically maps to a small number of loci, despite the complexity of underlying biosynthetic pathways. This discrepancy may partially arise from limitations presented by geographically diverse mapping panels. Properties of metabolic pathways that impede GWAS by diluting the additive effect of a causal variant, such as allelic and genic heterogeneity and epistasis, would be expected to increase in severity with the geographic range of the mapping panel. We hypothesized that a population from a single locality would reveal an expanded set of associated loci. We tested this in a French Arabidopsis thaliana population (< 1 km transect) by profiling and conducting GWAS for glucosinolates, a suite of defensive metabolites that have been studied in depth through functional and genetic mapping approaches. For two distinct classes of glucosinolates, we discovered more associations at biosynthetic loci than previous GWAS with continental-scale mapping panels. Candidate genes underlying novel associations were supported by concordance between their observed effects in the TOU-A population and previous functional genetic and biochemical characterization. Local populations complement geographically diverse mapping panels to reveal a more complete genetic architecture for metabolic traits.

opencc-zeroMay 2024View details →

zenodo40/100