DeepTetrad: high-throughput image analysis of meiotic tetrads by deep learning in Arabidopsis thaliana
- DeepTetrad: high-throughput image analysis of meiotic tetrads by deep learning in Arabidopsis thaliana
- LIM, EUNCHEON; KIM, JAE IL; KIM, JAE IL; KIM, EUNJUNG; KIM, JUHYUN; PARK, YEONGMI; CHO, HYUN SEOB; BYUN, DOHWAN; HENDERSON, IAN R; COPENHAVER, GREGORY P; HWANG, IL DOO; CHOI, KYUHA
- Date Issued
- Cold Spring Harbor Conferences Asia
- Meiotic crossovers facilitate chromosome segregation and create new combinations of alleles in gametes. Crossover frequency varies along chromosomes and crossover interference limits the coincidence of closely spaced crossovers. Crossovers can be measured by observing the inheritance of linked transgenes expressing different colors of fluorescent protein in Arabidopsis pollen tetrads. Here we establish DeepTetrad, a deep learning-based image recognition package for pollen tetrad analysis that enables high-throughput measurements of crossover frequency and interference in individual plants. DeepTetrad will accelerate genetic dissection of mechanisms that control meiotic recombination.
- Article Type
- 2019 Cold Spring Harbor Asia Conference: PLANT CELL & DEVELOPMENTAL BIOLOGY, 2019-11-04
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