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Optimizing selection of restriction enzymes for complexity-reduced genome sequencing in plants
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Abstract
Background
Reduced-representation sequencing, e.g., restriction-site-associated DNA sequencing and genotyping by sequencing, is a powerful and cost-effective method to detect polymorphism and to genotype pools of individuals. However, restriction enzymes employed to the analyses were often chosen in basis on intuition and precedents.
Results
We propose to apply an
in silico
analysis to predict gene concentrations in restriction fragments, which are templates of complexity-reduced genome libraries. It also predicts fragment lengths and physical positions in plant genomes. The
in silico
analysis was verified using actual amplified fragment length polymorphism patterns. The genome-scale differences in the distributions of restriction fragments from methylation-sensitive and resistant enzymes accounted for marker clusters on genetic maps, commonly reported in linkage maps of plants. The
in silico
analysis, using three combinations of enzymes across four model plants, indicated that the combination of MspI and PstI is remarkably informative for reduced-representation sequencing in terms of fragment length, distribution in euchromatic regions, and gene enrichment.
Conclusions
Application of our
in silico
restriction analysis provides useful information for optimizing the selection of restriction enzymes in empirical reduced-representation sequencing of genomes of several organisms including not only plants but also animals.
Title: Optimizing selection of restriction enzymes for complexity-reduced genome sequencing in plants
Description:
Abstract
Background
Reduced-representation sequencing, e.
g.
, restriction-site-associated DNA sequencing and genotyping by sequencing, is a powerful and cost-effective method to detect polymorphism and to genotype pools of individuals.
However, restriction enzymes employed to the analyses were often chosen in basis on intuition and precedents.
Results
We propose to apply an
in silico
analysis to predict gene concentrations in restriction fragments, which are templates of complexity-reduced genome libraries.
It also predicts fragment lengths and physical positions in plant genomes.
The
in silico
analysis was verified using actual amplified fragment length polymorphism patterns.
The genome-scale differences in the distributions of restriction fragments from methylation-sensitive and resistant enzymes accounted for marker clusters on genetic maps, commonly reported in linkage maps of plants.
The
in silico
analysis, using three combinations of enzymes across four model plants, indicated that the combination of MspI and PstI is remarkably informative for reduced-representation sequencing in terms of fragment length, distribution in euchromatic regions, and gene enrichment.
Conclusions
Application of our
in silico
restriction analysis provides useful information for optimizing the selection of restriction enzymes in empirical reduced-representation sequencing of genomes of several organisms including not only plants but also animals.
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