Fine mapping and characterization of stripe rust resistance gene YrAYH in near-isogenic lines derived from a cross involving wheat landrace Anyuehong

Stripe rust,caused by Puccinia striiformis f.sp.tritici(Pst),is a devastating disease in wheat worldwide.Discovering and characterizing new resistance genes/QTL is crucial for wheat breeding programs.In this study,we fine-mapped and characterized a stripe rust resistance gene,YRAYH,on chromosome arm 5BL in the Chinese wheat landrace Anyuehong(AYH).Evaluations of stripe rust response to prevalent Chinese Pst races in near-isogenic lines derived from a cross of Anyuehong and Taichung 29 showed that YrAYH conferred a high level of resistance at all growth stages.Fine mapping using a large segregating population of 9748 plants,narrowed the YRAYH locus to a 3.7 Mb interval on chromosome arm 5BL that included 61 annotated genes.Transcriptome analysis of two NIL pairs identified 64 upregulated differentially expressed genes(DEGs)in the resistant NILs(NILs-R).Annotations indicated that many of these genes have roles in plant disease resistance pathways.Through a combined approach of fine-mapping and transcriptome sequencing,we identified a serine/threonine-protein kinase SRPK as a candidate gene underlying YrAYH.A unique 25 bp insertion was identified in the NILs-R compared to the NILs-S and previously published wheat genomes.An InDel marker was developed and co-segregated with YrAYH.Agronomic trait evaluation of the NILs suggested that YrAYH not only reduces the impact of stripe rust but was also associated with a gene that increases plant height and spike length.

Joint Power Control and Scheduling for Two-Cell Energy Efficient Broadcasting with Network Coding

We consider the energy minimization problem for a two-cell broadcasting system, where the focus is devising energy efficient joint power control and scheduling algorithms. To improve the retransmission efficiency, linear network coding is applied to broadcast packets. Combined with network coding, an optimal algorithm is proposed, which is based on dynamic programming. To reduce computational complexity, two sub-optimal algorithms are also proposed for large networks. Simulation results show that the proposed schemes can reduce energy consumption up to 57% compared with the traditional Automatic Repeat-reQuest (ARQ).