Polyploidy is an important feature of plant genomes, but the nature of many polyploidization events remains to be elucidated. Here, we demonstrate that the evolutionary fates of the subgenomes in maize () and soybean () have followed different trajectories. One subgenome has been subject to relaxed selection, lower levels of gene expression, higher rates of transposable element accumulation, more small interfering RNAs and DNA methylation around genes, and higher rates of gene loss in maize, whereas none of these features were observed in soybean. Nevertheless, individual gene pairs exhibit differentiation with respect to these features in both species. In addition, we observed a higher number of chromosomal rearrangements and higher frequency of retention of duplicated genes in soybean than in maize. Furthermore, soybean "singletons" were found to be more frequently tandemly duplicated than "duplicates" in soybean, which may, to some extent, counteract the genome imbalance caused by gene loss. We propose that unlike in maize, in which two subgenomes were distinct prior to the allotetraploidization event and thus experienced global differences in selective constraints, in soybean, the two subgenomes were far less distinct prior to polyploidization, such that individual gene pairs, rather than subgenomes, experienced stochastic differences over longer periods of time, resulting in retention of the majority of duplicates.

Phytophthora root and stem rot (PRR), caused by the soil-borne oomycete pathogen Phytophthora sojae, is one of the most destructive diseases of soybean. PRR can be effectively controlled by race-specific genes conferring resistance to P. sojae (Rps). However, the Rps genes are usually non-durable, as populations of P. sojae are highly diverse and quick to adapt, and can be overcome 8-15 years after deployment. Thus, it is important to identify novel Rps genes for development of resistant soybean cultivars. PI 567139B is a soybean landrace carrying excellent resistance to nearly all predominant P. sojae races in Indiana. A mapping population consisting of 245 F2 individuals and 403 F2:3 families was developed from a cross between PI 567139B and the susceptible cultivar 'Williams', and used to dissect the resistance carried by PI 567139B. We found that the resistance in PI 567139B was conferred by two independent Rps genes, designated RpsUN1 and RpsUN2. The former was mapped to a 6.5 cM region between SSR markers Satt159 and BARCSOYSSR_03_0250 that spans the Rps1 locus on chromosome 3, while the latter was mapped to a 3.0 cM region between BARCSOYSSR_16_1275 and Sat_144, approximately 3.0-3.4 cM upstream of Rps2 on chromosome 16. According to the 'Williams 82' reference genome sequence, both regions are highly enriched with NBS-LRR genes. Marker assisted resistance spectrum analyses of these genes with 16 isolates of P. sojae, in combination with the mapping results, suggested that RpsUN1 was likely to be a novel allele at the Rps1 locus, while RpsUN2 was more likely to be a novel Rps gene.

BackgroundPhytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is controlled by Rps genes. However, little is known regarding the Rps-induced molecular responses to P. sojae and how they actually overlap. We thus sequenced, analyzed, and compared the transcriptomes of 10 near isogenic lines (NILs), each with a unique Rps gene/allele, and the susceptible parent Williams, pre- and post-inoculation with the pathogen.ResultsA total of 4,330 differentially expressed genes (DEGs) were identified in Williams versus 2,014 to 5,499 DEGs in individual NILs upon inoculation with the pathogen. Comparisons of the DEGs between the NILs and Williams identified incompatible interaction genes (IIGs) and compatible interaction genes (CIGs). Hierarchical cluster and heatmap analyses consistently grouped the NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6), suggesting an overlap in Rps-induced defense signaling among certain NILs. Gene ontology (GO) analysis revealed associations between members of the WRKY family and incompatible reactions and between a number of phytohormone signaling pathways and incompatible/compatible interactions. These associations appear to be distinguished according to the NIL clusters.ConclusionsThis study characterized genes and multiple branches of putative regulatory networks associated with resistance to P. sojae in ten soybean NILs, and depicted functional “fingerprints” of individual Rps-mediated resistance responses through comparative transcriptomic analysis. Of particular interest are dramatic variations of detected DEGs, putatively involved in ethylene (ET)-, jasmonic acid (JA)-, (reactive oxygen species) ROS-, and (MAP-kinase) MAPK- signaling, among these soybean NILs, implicating their important roles of these signaling in differentiating molecular defense responses. We hypothesize that different timing and robustness in defense signaling to the same pathogen may be largely responsible for such variations.

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Human error has been statistically proven to be the primary cause of road accidents. This undoubtedly is a contributory cause of the rising popularity of autonomous vehicles as they are presumably able to maneuver appropriately/optimally on the roads while diminishing the likelihood of human error and its repercussion. However, autonomous vehicles are not ready for widespread adoption because their safety and security issues are yet to be thoroughly investigated/addressed. Little literature could be found on collaborative analysis of safety and security of autonomous vehicles. This paper proposes a framework for analyzing both safety and security issues, which includes an integrated safety and security method (S&S) with international vehicle safety and security standards ISO 26262 and SAE J3061. The applicability of the proposed framework is demonstrated using an example of typical autonomous vehicle model. Using this framework, one can clearly understand the vehicle functions, structure, the associated failures and attacks, and also see the vulnerabilities that are not yet addressed by countermeasures, which helps to improve the in-vehicle safety and security from researching and engineering perspectives.