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In pursuing our long-term goals of identifying causal genes for mutant phenotypes in maize, we have developed a new, phenotype-to-genotype approach for transposon-based resources, and used this to identify candidate genes that co-segregate with visible kernel mutants. The strategy incorporates a redesigned Mu-seq protocol (sequence-based, transposon mapping) for high-throughput identification of individual plants carrying Mu insertions. Forward-genetic Mu-seq also involves a genetic pipeline for generating families that segregate for mutants of interest, and grid designs for concurrent analysis of genotypes in multiple families. Critically, this approach not only eliminates gene-specific PCR genotyping, but also profiles all Mu-insertions in hundreds of individuals simultaneously. Here, we employ this scalable approach to study 12 families that showed Mendelian segregation of visible seed mutants. These families were analyzed in parallel, and 7 showed clear co-segregation between the selected phenotype and a Mu insertion in a specific gene. Results were confirmed by PCR. Mutant genes that associated with kernel phenotypes include those encoding: a new allele of Whirly1 (a transcription factor with high affinity for organellar and single-stranded DNA), a predicted splicing factor with a KH domain, a small protein with unknown function, a putative mitochondrial transcription-termination factor, and three proteins with pentatricopeptide repeat domains (predicted mitochondrial). Identification of such associations allows mutants to be prioritized for subsequent research based on their functional annotations. Forward-genetic Mu-seq also allows a systematic dissection of mutant classes with similar phenotypes. In the present work, a high proportion of kernel phenotypes were associated with mutations affecting organellar gene transcription and processing, highlighting the importance and non-redundance of genes controlling these aspects of seed development.

Phenotype to genotype using forward-genetic Mu-seq for identification and functional classification of maize mutants