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Development of Novel Wheat-Rye Chromosome 4R Translocations and Assignment of Their Powdery Mildew Resistance.

Pengtao MaGuohao HanQi ZhengShiyu LiuFangpu HanJing WangQiaoling LuoDiaoguo An
Published in: Plant disease (2019)
Rye (Secale cereale L.) is an important gene donor for wheat improvement because of its many valuable traits, especially disease resistance. Development of novel wheat-rye translocations with disease resistance can contribute to transferring resistance into common wheat. In a previous study, a wheat-rye T4BL·4RL and T7AS·4RS translocation line (WR41-1) was developed by distant hybridization, and it was speculated that its resistance to powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), was derived from rye based on pedigree analysis. To make accurate use of chromosome 4R in wheat improvement, a set of new 4R translocations involving different arm translocations (e.g., 4RS monosomic, 4RL monosomic, 4RL disomic, 4RS monosomic plus 4RL monosomic, 4RS monosomic plus 4RL disomic, and 4RS disomic plus 4RL disomic translocations) was developed from crosses with common wheat. Those translocations were characterized by genomic in situ hybridization and expressed sequence tag simple sequence repeat marker analysis. To confirm the source of powdery mildew resistance, the translocation plants were tested against Bgt isolate E09. The results indicated that all translocations with 4RL were resistant at all tested growth stages, whereas those with only 4RS translocation or no alien translocation were susceptible. This further indicated that the powdery mildew resistance of WR41-1 was derived from the alien chromosome arm 4RL. To effectively use 4RL resistance in wheat improvement, two competitive allele-specific PCR markers specific for chromosome arm 4RL were developed to detect the alien chromosome in the wheat genome. These new translocation lines with diagnostic markers can efficiently serve as important bridges for wheat improvement.
Keyphrases
  • genome wide
  • mass spectrometry
  • gene expression
  • data analysis