Carotenoid oxygenase is a key enzyme in carotenoid metabolism leading to the synthesis of two phytohormones, abscisic acid (ABA) and strigolactone, as well as norisoprenoids. Few studies have analyzed inter-relationship of the metabolic networks of these three substances. In this present paper, soybean carotenoid oxygenase genes were identified to reveal their phylogenetic relationships, and the transcriptional response of these genes to four abiotic stresses (NaCl, PEG, high and low temperature) and ABA treatment were investigated to characterize their potential roles in plant resistance. Positive selection was found in the branches of carotenoid cleavage dioxygenase (CCD1), CCD8 and NCED (9-cis-epoxycarotenoid oxygenase), indicating an adaptive evolution in these clades. In soybean eight carotenoid oxygenase genes were identified. The transcriptional responses of almost all of them under stress and ABA conditions were significantly altered when assessed by quantitative polymerase chain reaction. Notably, CCD1 and CCD4, previously known as the key genes in norisoprenoids metabolism, showed especially strong responses to the abiotic stresses and ABA treatment. Furthermore, transcription levels of CCD7 and CCD8, key genes for the strigolactone pathway, highly increased during ABA treatment providing further evidence that ABA is involved in regulating strigolactone metabolism. All of the carotenoid oxygenase genes in soybean are involved in plant abiotic stress physiology, and ABA is presumed to be a core regulatory substance. These findings provide some insights into the mechanisms that underlie the regulation of tolerance response to abiotic stresses in soybean.
Vine growth habit (VGH) is a beneficial phenotype in many wild plants, and is considered an important domesticated-related trait in soybean. However, its genetic basis remains largely unclear. Hence, in the present study we used an integrated strategy combining linkage mapping and population genome diversity analyses to reveal the genetics of VGH in soybean. In this regard, two recombinant inbred line (RIL) populations derived by crossing a common wild soybean genotype (PI342618B) with two cultivated lines
viz
., NN 86-4 and NN 493-1 were used to map quantitative trait loci (QTL) for VGH. Here, we identified seven and five QTLs at flowering stage (R1) and maturity stage (R8), respectively, and among them
qVGH-18-1
,
qVGH-18-2
,
qVGH-19-3
,
qVGH-19-4
were identified as major loci (
R
2
> 10% and detection time ≥2). However,
qVGH-18-2
was considered as a main QTL for VGH being consistently identified in both RIL populations as well as all growth stages and cropping years. Out of all the annotated genes within
qVGH-18-2
,
Glyma18g06870
was identified as the candidate gene and named as
VGH1
, which was a gibberellin oxidase (GAox) belongs to 2-oxoglutarate-dependent dioxygenase (2- ODD). Interestingly, there was one member of 2-ODD/GAox in
qVGH-18-1
and
qVGH-19-4
named as
VGH2
and
VGH3
, respectively. Moreover, from sequencing data analysis
VGH1
and three other
GAox
genes were found significantly divergent between vine and erect soybean with
F
ST
value larger than 0.25. Hence, GAox was assumed to play a major role in governing inheritance of VGH in soybean. Therefore, elucidating the genetic mechanism of GAox is very useful for exploring VGH and other stem traits, as well as genetic improvement of plant type in soybean.
An application of geometric reliability techniques on various pile types based on 67 load–displacement curves obtained from pertinent literature is presented in this paper. These static loading tests were performed at local scale (even building-specific sites) under essentially identical geotechnical conditions. A power-law function with two parameters was used to fit the measured load–settlement curves. For each site, the means and coefficients of variation for the power-law parameters were obtained. Since the number of tests conducted at each site is usually small, it is extremely difficult to identify a certain distribution type for these regression parameters. Thus, for simplicity, a bivariate normal distribution was assumed to represent the set of regression pairs. This joint distribution was incorporated into a geometric reliability method, which offers an estimation of the bearing capacity of piles at the serviceability limit state. Examples are provided to illustrate the application of the proposed reliability method to interpret the visually determined reliability index of the bearing capacity of piles. These case studies showed that the proposed method is a useful and comprehensive tool for capturing the load–displacement response and for evaluating the bearing capacity of piles by considering uncertainties in their load–displacement behaviour.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.