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Molecular characterization of a wheat -Thinopyrum ponticum partial amphiploid and its derived substitution line for resistance to stripe rust

100%

Hu L.-J. , Li G.-R. , Zeng Z.-X. , Chang Z.-J. , Liu C. , Yang Z.-J.

tom 52

nr 3

Stripe rust (caused by Puccinia striiformis) occurs annually in most wheat-growing areas of the world. Thinopyrum ponticum has provided novel rust resistance genes to protect wheat from this fungal disease. Wheat – Th. ponticum partial amphiploid line 7430 and a substitution line X005 developed from crosses between wheat and 7430 were resistant to stripe rust isolates from China. Genomic in situ hybridization (GISH) analysis using Pseudoroegneria spicata genomic DNA as a probe demonstrated that the partial amphiploid line 7430 contained ten Js and six J genome chromosomes, and line X005 had a pair of Js-chromosomes. Giemsa-C banding further revealed that both lines 7430 and X005 were absent of wheat chromosomes 6B. The EST based PCR confirmed that the introduced Js chromosomes belonging to linkage group 6, indicating that line X005 was a 6Js/6B substitution line. Both resistance observation and sequence characterized amplified region (SCAR) markers displayed that the introduced chromosomes 6Js were responsible for the stripe rust resistances. Therefore, lines 7430 and X005 can be used as a donor in wheat breeding for stripe rust resistance.

Comparative study of models for predicting permeability from nuclear magnetic Rresonance (NMR) logs in two Chinese tight sandstone reservoirs

84%

Xiao L. , Liu X.-P. , Zou C.-C. , Hu X.-X. , Mao Z. Q. , Shi Y.-J. , Guo H.-P. , Li G.-R.

tom Vol. 62, no. 1

116--141

Based on the analysis of mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) experimental data for core plugs, which were drilled from two Chinese tight sandstone reservoirs, permeability prediction models, such as the classical SDR, Timur– Coates, the Swanson parameter, the Capillary Parachor, the R10 and R35 models, are calibrated to estimating permeabilities from field NMR logs, and the applicabilities of these permeability prediction models are compared. The processing results of several field examples show that the SDR model is unavailable in tight sandstone reservoirs. The Timur– Coates model is effective once the optimal T2cutoff can be acquired to accurately calculate FFI and BVI from field NMR logs. The Swanson parameter model and the Capillary Parachor model are not always available in tight sandstone reservoirs. The R35 based model cannot effectively work in tight sandstone reservoirs, while the R10 based model is optimal in permeability prediction.