Rapid identification and recovery of ENU-induced mutations with next-generation sequencing and Paired-End Low-Error analysis
- Pan, L., Shah, A.N., Phelps, I.G., Doherty, D., Johnson, E.A., Moens, C.B.
- BMC Genomics 16: 83 (Journal)
- Registered Authors
- Johnson, Eric, Moens, Cecilia, Pan, Luyuan, Phelps, Ian
- MeSH Terms
- Codon, Nonsense/drug effects
- DNA/isolation & purification
- Gene Library
- Genome/drug effects*
- High-Throughput Nucleotide Sequencing*/standards
- Mutation/drug effects
- RNA Splice Sites/genetics
- Sequence Analysis, DNA
- 25886285 Full text @ BMC Genomics
Pan, L., Shah, A.N., Phelps, I.G., Doherty, D., Johnson, E.A., Moens, C.B. (2015) Rapid identification and recovery of ENU-induced mutations with next-generation sequencing and Paired-End Low-Error analysis. BMC Genomics. 16:83.
Background Targeting Induced Local Lesions IN Genomes (TILLING) is a reverse genetics approach to directly identify point mutations in specific genes of interest in genomic DNA from a large chemically mutagenized population. Classical TILLING processes, based on enzymatic detection of mutations in heteroduplex PCR amplicons, are slow and labor intensive.
Results Here we describe a new TILLING strategy in zebrafish using direct next generation sequencing (NGS) of 250bp amplicons followed by Paired-End Low-Error (PELE) sequence analysis. By pooling a genomic DNA library made from over 9,000 N-ethyl-N-nitrosourea (ENU) mutagenized F1 fish into 32 equal pools of 288 fish, each with a unique Illumina barcode, we reduce the complexity of the template to a level at which we can detect mutations that occur in a single heterozygous fish in the entire library. MiSeq sequencing generates 250 base-pair overlapping paired-end reads, and PELE analysis aligns the overlapping sequences to each other and filters out any imperfect matches, thereby eliminating variants introduced during the sequencing process. We find that this filtering step reduces the number of false positive calls 50-fold without loss of true variant calls. After PELE we were able to validate 61.5% of the mutant calls that occurred at a frequency between 1 mutant call:100 wildtype calls and 1 mutant call:1000 wildtype calls in a pool of 288 fish. We then use high-resolution melt analysis to identify the single heterozygous mutation carrier in the 288-fish pool in which the mutation was identified.
Conclusions Using this NGS-TILLING protocol we validated 28 nonsense or splice site mutations in 20 genes, at a two-fold higher efficiency than using traditional Cel1 screening. We conclude that this approach significantly increases screening efficiency and accuracy at reduced cost and can be applied in a wide range of organisms.
Genes / Markers
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Engineered Foreign Genes