PLoS ONEGenomicsPeer-reviewed journal article
Bulked segregant analysis RNA-seq (BSR-Seq) validated a stem resistance locus in Aegilops umbellulata, a wild relative of wheat
Abstract
Many disease resistance genes that have been transferred from wild relatives to cultivated wheat have played a significant role in wheat production worldwide. Ae. umbellulata is one of the species within the genus Aegilops that have been successfully used as sources of resistance genes to leaf rust, stem rust and powdery mildew. The objectives of the current work was to validate the map position of a major QTL that confers resistance to the stem rust pathogen races Ug99 (TTKSK) and TTTTF with an independent bi-parental mapping population and to refine the QTL region with a bulk segregant analysis approach. Two F2 bi-parental mapping populations were developed from stem rust resistant Ae. umbellulata accessions (PI 298905 and PI 5422375) and stem rust susceptible accessions (PI 542369 and PI 554395). Firstly, one of the two populations was used to map the chromosome location of the resistance gene. Later on, the 2nd population was used to validate the chromosome location in combination with a bulk segregant analysis approach. For the bulk segregant analysis, RNA was extracted from a bulk of leaf tissues of 12 homozygous resistant F3 families, and a separate bulk of 11 susceptible homozygous F3 families derived from the PI 5422375 and PI 554395 cross. The RNA samples of the two bulks and the two parents were sequenced for SNPs identification. Stem rust resistance QTL was validated on chromosome 2U of Ae. umbellulata in the same region in both populations. With bulk segregant analysis, the QTL position was delimited within 3.2 Mbp. Although there were a large number of genes in the orthologous region of the detected QTL on chromosome 2D of Ae. tauschii, we detected only two Ae. umbellulata NLR genes which can be considered as a potential candidate genes.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 35
- FWCI
- 2.58
- Field percentile
- top 11%
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