Decrypting the sugarcane genome architecture for pre-breeding applications
By Piperidis
Advances in sugarcane DNA sequence analysis and assembly have been major assets for the development of new methods in cytogenetics. An Oligo-FISH technique using whole-chromosome probes was developed to decrypt the genome architecture of pure species and cultivars of sugarcane. Results are described from whole-chromosome painting (WCP) combined with the use of three new oligo probes designed to test our capacity to detect and track probes of different sizes and frequencies. The goal is to improve the efficiency and outcomes from cytogenetics research that support the SRA introgression breeding program. A set of retrotransposons (RT) repetitive-sequences that generate S. spontaneum-specific signals were converted into an oligo S. spontaneum-specific probe (RT-oligo) to characterise the species composition of SRA cultivars more accurately than with the previously used GISH method. Two gene-specific oligo probes for the alcohol dehydrogenase gene (ADH) and the gene responsible for brown rust resistance (Bru1) in sugarcane were designed. Whole-chromosome mapping, oligo-gene mapping and RT-oligo mapping were used to characterise the genomes of SRA elite/current varieties as well as introgression derivatives to establish a baseline database classifying chromosomal structure variations/chromosome patterns/genes inheritance across SRA cultivar germplasm. The next step is to characterise elite introgression clones and successive generations of introgression clones derived from the nematode-resistance research program. The characterisation of the genome structure of clones of multiple generations allows the study of chromosome transmission behaviour, to follow introgression regions/traits of interest, and to study transmission patterns. The aim is to improve fundamental understanding of trait transmission through generations which would maximise the chance to introgress required traits in preferred parents and make targeting breeding a closer reality.
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2023_Decrypting the sugarcane genome architecture for pre-breeding applications.pdf