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The Pattern and Distribution of Induced Mutations in Using Reduced Representation Sequencing. | LitMetric

The Pattern and Distribution of Induced Mutations in Using Reduced Representation Sequencing.

Front Plant Sci

Plant Biotechnology Unit, Department of Biotechnology, Vienna Institute of BioTechnology, University of Natural Resources and Life Sciences, Vienna, Austria.

Published: April 2018

AI Article Synopsis

Article Abstract

Mutagenesis in combination with Genotyping by Sequencing (GBS) is a powerful tool for introducing variation, studying gene function and identifying causal mutations underlying phenotypes of interest in crop plant genomes. About 400 million paired-end reads were obtained from 82 ethylmethane sulfonate (EMS) induced mutants and 14 wild-type accessions of for the detection of Single Nucleotide Polymorphisms (SNPs) and Insertion/Deletions (InDels) by two different approaches (nGBS and ddGBS) on an Illumina HiSeq 2000 sequencer. Using bioinformatics analyses, 1,452 induced SNPs and InDels were identified in coding regions, which were distributed across 995 genes. The predominantly observed mutations were G/C to A/T transitions (64%), while transversions were observed at a lower frequency (36%). Regarding the effect of mutations on gene function, 18% of the mutations were located in intergenic regions. In fact, mutants with the highest number of heterozygous SNPs were found in samples treated with 0.8% EMS for 3 h. Reconstruction of the metabolic pathways showed that in total 16 SNPs were located in six KEGG pathways by nGBS and two pathways by ddGBS. The most highly represented pathways were ether-lipid metabolism and glycerophospholipid metabolism, followed by starch and sucrose metabolism by nGBS and triterpenoid biosynthesis as well as steroid biosynthesis by ddGBS. Furthermore, high genome methylation was observed in , which might help to understand the plasticity of the genome in response to environmental factors. At last, the results showed that continuously vegetatively propagated tissue is a fast, efficient and accurate method to dissolve chimeras, especially for long-lived plants like . Obtained data showed that allelic variations and analyses of gene functions (gene function prediction), which control important traits, could be identified in mutant populations using nGBS and ddGBS. However, the handling of GBS data is more difficult and more challenging than the traditional TILLING strategy in mutated plants, since the genome sequence is incomplete, which makes alignment and variant analysis of target sequence reads challenging to perform and interpret. Therefore, providing a complete reference genome sequence with high quality should be a priority for any breeding program.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944264PMC
http://dx.doi.org/10.3389/fpls.2018.00524DOI Listing

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