High‐Throughput and Low‐Cost Genotyping Method for Plant Genome Editing. Issue 4 (7th April 2021)

• Record Type: Journal Article
• Authors: Liu, Lei; Chen, Richelle; Fugina, Christopher John; Siegel, Ben; Jackson, David
• Is Part Of: Current protocols. Volume 1:Issue 4(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-04-07
• Subjects: barcode -- genome editing -- maize -- next‐generation sequencing; Life sciences -- Laboratory manuals -- Periodicals; Biology -- Laboratory manuals -- Periodicals; Life sciences -- Technique -- Periodicals; Biology -- Technique -- Periodicals; 570.028
• DOI: 10.1002/cpz1.100
• Languages: English
• ISSNs: 2691-1299

Abstract

Abstract: Genome editing technologies have revolutionized genetic studies in the life sciences community in recent years. The application of these technologies allows researchers to conveniently generate mutations in almost any gene of interest. This is very useful for species such as maize that have complex genomes and lack comprehensive mutant collections. With the improvement of genome editing tools and transformation methods, these technologies are also widely used to assist breeding research and implementation in maize. However, the detection and genotyping of genomic edits rely on low‐throughput, high‐cost methods, such as traditional agarose gel electrophoresis and Sanger sequencing. This article describes a method to barcode the target regions of genomic edits from many individuals by low‐cost polymerase chain reaction (PCR) amplification. It also employs next‐generation sequencing (NGS) to genotype the genome‐edited plants at high throughput and low cost. This protocol can be used for initial screening of genomic edits as well as derived population genotyping on a small or large scale, at high efficiency and low cost. © 2021 Wiley Periodicals LLC. Basic Protocol 1 : A fast genomic DNA preparation method from genome edited plants Basic Protocol 2 : Barcoding the amplicons of edited regions from each individual by two rounds of PCR Basic Protocol 3 : Bioinformatics analysis