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Biology subjects

Millet, E.

Publications and source records attributed to Millet, E..

2 recordsLinked to original sources

Genome sequences of Aegilops species of section Sitopsis reveal phylogenetic relationships and provide resources for wheat improvement

Aegilops is a close relative of wheat (Triticum spp.), and Aegilops species in the section Sitopsis represent a rich reservoir of genetic diversity for improvement of wheat. To understand their diversity and advance their utilization, we produced whole-genome assemblies of Ae. longissima and Ae. speltoides. Whole-genome comparative analysis, along with the recently sequenced Ae. sharonensis genome, showed that the Ae. longissima and Ae. sharonensis genomes are highly similar and most closely related to the wheat D subgenome. By contrast, the Ae. speltoides genome is more closely related to the B subgenome. Haplotype block analysis supported the idea that Ae. speltoides is the closest ancestor of the wheat B subgenome and highlighted variable and similar genomic regions between the three Aegilops species and wheat. Genome-wide analysis of nucleotide-binding site leucine-rich repeat (NLR) genes revealed species-specific and lineage-specific NLR genes and variants, demonstrating the potential of Aegilops genomes for wheat improvement. TeaserGenome sequences of Aegilops species provides a key for efficient exploitation of this rich genetic resource in wheat improvement.

plant biology↗

Genotyping-by-sequencing and microarrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies

BackgroundSingle Nucleotide Polymorphism (SNP) array and re-sequencing technologies have different properties (e.g. calling rate, minor allele frequency profile) and drawback (e.g. ascertainment bias), which lead us to study the complementarity and consequences of using them separately or combined in diversity analyses and Genome-Wide Association Studies (GWAS). We performed GWAS on three traits (grain yield, plant height and male flowering time) measured in 22 environments on a panel of 247 diverse dent maize inbred lines using three genotyping technologies (Genotyping-By-Sequencing, Illumina Infinium 50K and Affymetrix Axiom 600K arrays).\n\nResultsThe effects of ascertainment bias of both arrays were negligible for deciphering global genetic trends of diversity in this panel and for estimating relatedness. We developed an original approach based on linkage disequilibrium (LD) extent in order to determine whether SNPs significantly associated with a trait and that are physically linked should be considered as a single QTL or several independent QTLs. Using this approach, we showed that the combination of the three technologies, which have different SNP distribution and density, allowed us to detect more Quantitative Trait Loci (QTLs, gain in power) and potentially refine the localization of the causal polymorphisms (gain in position).\n\nConclusionsConceptually different technologies are complementary for detecting QTLs by tagging different haplotypes in association studies. Considering LD, marker density and the combination of different technologies (arrays and re-sequencing), the genotypic data presently available were most likely enough to well represent polymorphisms in the centromeric regions, whereas using more markers would be beneficial for telomeric regions.

genomics↗