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Carbohydrate microarrays and their use for the identification of molecular markers for plant cell wall composition.

Ian P WoodBruce M PearsonEnriqueta Garcia-GutierrezLenka HavlickovaZhesi HeAndrea L HarperIan BancroftKeith W Waldron
Published in: Proceedings of the National Academy of Sciences of the United States of America (2017)
Genetic improvement of the plant cell wall has enormous potential to increase the quality of food, fibers, and fuels. However, the identification and characterization of genes involved in plant cell wall synthesis is far from complete. Association mapping is one of the few techniques that can help identify candidate genes without relying on our currently incomplete knowledge of cell wall synthesis. However, few cell wall phenotyping methodologies have proven sufficiently precise, robust, or scalable for association mapping to be conducted for specific cell wall polymers. Here, we created high-density carbohydrate microarrays containing chemically extracted cell wall polysaccharides collected from 331 genetically diverse Brassica napus cultivars and used them to obtain detailed, quantitative information describing the relative abundance of selected noncellulosic polysaccharide linkages and primary structures. We undertook genome-wide association analysis of data collected from 57 carbohydrate microarrays and identified molecular markers reflecting a diversity of specific xylan, xyloglucan, pectin, and arabinogalactan moieties. These datasets provide a detailed insight into the natural variations in cell wall carbohydrate moieties between B. napus genotypes and identify associated markers that could be exploited by marker-assisted breeding. The identified markers also have value beyond B. napus for functional genomics, facilitated by the close genetic relatedness to the model plant Arabidopsis Together, our findings provide a unique dissection of the genetic architecture that underpins plant cell wall biosynthesis and restructuring.
Keyphrases
  • cell wall
  • high density
  • high resolution
  • healthcare
  • copy number
  • high throughput
  • dna methylation
  • risk assessment
  • single cell
  • quality improvement
  • big data
  • deep learning
  • wastewater treatment
  • rna seq