Multiple reference genomes and transcriptomes for Arabidopsis thaliana

By Xiangchao Gan, Oliver Stegle, Jonas Behr, Joshua G. Steffen, Philipp Drewe, Katie L. Hildebrand, R. Lyngsoe, Sebastian J. Schultheiss, E. Osborne, Vipin T. Sreedharan and 13 more. Nature, 2011

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Genetic differences between Arabidopsis thaliana accessions underlie the plant’s extensive phenotypic variation, and until now these have been interpreted largely in the context of the annotated reference accession Col-0. Here we report the sequencing, assembly and annotation of the genomes of 18 natural A. thaliana accessions, and their transcriptomes. When assessed on the basis of the reference annotation, one-third of protein-coding genes are predicted to be disrupted in at least one accession. However, re-annotation of each genome revealed that alternative gene models often restore coding potential. Gene expression in seedlings differed for nearly half of expressed genes and was frequently associated with cis variants within 5 kilobases, as were intron retention alternative splicing events. Sequence and expression variation is most pronounced in genes that respond to the biotic environment. Our data further promote evolutionary and functional studies in A. thaliana, especially the MAGIC genetic reference population descended from these accessions.

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/50f0c7b0ce3a5277e27b73a3a98adc8b2d9463ef

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Citations in the corpus

Phased Diploid Genome Assembly with Single Molecule Real-Time Sequencing (2016, background): “The contig N50 sizes of the assemblies were 7.4 Mb (Col-0) and 6.0 Mb (Cvi-0), about 10 to 100 times more contiguous than other recently published Arabidopsis assemblies produced from short-read shotgun sequencing 33 .”
Pure polyploidy: Closing the gaps in autopolyploid research (2017, background): “Systems with published genomes enable a wide variety of sophisticated genetic experiments (Arabidopsis Genome Initiative, 2000; Gan et al., 2011; Young et al., 2011; Tang et al., 2014).”
Comprehending crystalline β-carotene accumulation by comparing engineered cell models and the natural carotenoid-rich system of citrus (2011, neutral): “, 2011) and the Ler-0 genome (Gan et al., 2011), using the Blastx algorithm (Altschul et al.”
Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity (2014, positive): “As our data greatly expand the motif collection in the model plant Arabidopsis, we examined a data set of expression quantitative trait loci (eQTLs) defined from Arabidopsis genomic sequences and matched seedling RNA sequencing (RNA-seq) taken from 19 strains (Gan et al., 2011).”
The advantages and limitations of trait analysis with GWAS: a review (2013, background): “In Arabidopsis, LD generally decays 50% within 5 Kb [45]; hence, the 250 K SNPs (on average one SNP every 600 bp) tag almost all of the non-repetitive genome, and thus enable GWAS [14,47].”
Natural variations and genome-wide association studies in crop plants. (2014, background): “To capture a full catalog of sequence variants in a crop, it is best to deep sequence several representative varieties and then perform whole-genome de novo assembly and comparative genome analysis (25).”
Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines (2014, background): “Next, we identified closely linked co-segregating variants that might ameliorate these potentially damaging variants (Gan et al., 2010).”
SNPhylo: a pipeline to construct a phylogenetic tree from huge SNP data (2014, background): “Because of the relatively high LD level [20], the phylogenetic tree was constructed with relatively higher LD threshold (−l 0.”
Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression (2016, background): “By correlating genetic variants with gene expression profiles of individual genes, it has been possible to establish genome-wide maps of genetic effects on gene expression, both in model systems [1 – 3] and in human [4 – 9].”