Plant height (PH) and ear height (EH) are two very important agronomic traits related to the population density and lodging in maize. In order to better understand of the genetic basis of nature variation in PH and EH, two bi-parental populations and one genome-wide association study (GWAS) population were used to map quantitative trait loci (QTL) for both traits. Phenotypic data analysis revealed a wide normal distribution and high heritability for PH and EH in the three populations, which indicated that maize height is a highly polygenic trait. A total of 21 QTL for PH and EH in three common genomic regions (bin 1.05, 5.04/05, and 6.04/05) were identified by QTL mapping in the two bi-parental populations under multiple environments. Additionally, 41 single nucleotide polymorphisms (SNPs) were identified for PH and EH by GWAS, of which 29 SNPs were located in 19 unique candidate gene regions. Most of the candidate genes were related to plant growth and development. One QTL on Chromosome 1 was further verified in a near-isogenic line (NIL) population, and GWAS identified a C2H2 zinc finger family protein that maybe the candidate gene for this QTL. These results revealed that nature variation of PH and EH are strongly controlled by multiple genes with low effect and facilitated a better understanding of the underlying mechanism of height in maize.
When chaotic systems are used in different practical applications, such as nonlinear control and cryptography, their complex chaos dynamics are strongly required. However, many existing chaotic systems have simple complexity, and this brings negative effects to chaos-based applications. To address this issue, this paper introduces a sine chaotification model (SCM) as a general framework to enhance the chaos complexity of existing one-dimensional (1-D) chaotic maps. The SCM uses a sine function as a nonlinear chaotification transform and applies it to the output of a 1-D chaotic map. The resulting enhanced chaotic map of the SCM has better chaos complexity and a much larger chaotic range than the seed map. Theoretical analysis verifies the efficiency of the SCM. To show the performance of the SCM, we apply SCM to three existing chaotic maps and analyze the dynamics properties of the obtained enhanced chaotic maps. Performance evaluations prove that the three enhanced chaotic maps have more complicated dynamics behaviors than their seed chaotic maps. To show the implementation simplicity of the SCM, we implement the three enhanced chaotic maps using the field-programmable gate array. To investigate the SCM in practical application, we design pseudorandom number generators using the enhanced chaotic maps.
Traditional transformation methods are complex and time consuming. It is generally difficult to transform indica rice varieties using traditional transformation methods due to their poor regeneration. In this contribution, a simple method was developed for the transformation of indica rice. In this method, the mature embryos of soaked seeds were pierced by a needle, and then soaked in the Agrobacterium inoculum under vacuum infiltration. The inoculated seeds germinated and grew to maturation (T (0)) under nonsterile conditions. The herbicide or antibiotic analysis and molecular analysis were conducted on T (0) plants. The results showed that although the efficiency of transformation was about 6.0%, it was easier to transform indica rice using the proposed method, and the transformation process was significantly shortened. The success of transformation was further confirmed by the genetic and molecular analyses of T (1) transformants.
The meta-QTL and candidate genes will facilitate the elucidation of molecular bases underlying agriculturally important traits and open new avenues for functional markers development and elite alleles introgression in maize breeding program. A large number of QTLs attributed to grain productivity and other agriculturally important traits have been identified and deposited in public repositories. The integration of fruitful QTL becomes a major issue in current plant genomics. To this end, we first collected QTL for six agriculturally important traits in maize, including yield, plant height, ear height, leaf angle, stay-green, and maize rough dwarf disease resistance. The meta-analysis method was then employed to retrieve 113 meta-QTL. Additionally, we also isolated candidate genes for target traits by the bioinformatic technique. Several candidates, including some well-characterized genes, GA3ox2 for plant height, lg1 and lg4 for leaf angle, zfl1 and zfl2 for flowering time, were co-localized with established meta-QTL intervals. Intriguingly, in a relatively narrow meta-QTL region, the maize ortholog of rice yield-related gene GW8/OsSPL16 was believed to be a candidate for yield. Leveraging results presented in this study will provide further insights into the genetic architecture of maize agronomic traits. Moreover, the meta-QTL and candidate genes reported here could be harnessed for the enhancement of stress tolerance and yield performance in maize and translation to other crops.
Increased availability of soil phosphorus (P) has recently been recognised as an underlying driving factor for the positive relationship between plant diversity and ecosystem function. The effects of plant diversity on the bioavailable forms of P involved in biologically mediated rhizospheric processes and how the link between plant and soil microbial diversity facilitates soil P bioavailability, however, remain poorly understood.
This study quantified four forms of bioavailable P (CaCl2‐P, citric‐P, enzyme‐P and HCl‐P) in mature subtropical forests using a novel biologically based approach, which emulates how rhizospheric processes influence the release and supply of available P. Soil microbial diversity was measured by Illumina high‐throughput sequencing.
Our results suggest that tree species richness significantly affects soil microbial diversity (p < 0.05), increases litter decomposition, fine‐root biomass and length and soil organic carbon and thus increases the four forms of bioavailable P. A structural equation model that links plants, soil microbes and P forms indicated that soil bacterial and fungal diversity play dominant roles in mediating the effects of tree species richness on soil P bioavailability.
An increase in the biodiversity of plants, soil bacteria and fungi could maintain soil P bioavailability and alleviate soil P limitations. Our results imply that biodiversity strengthens plant and soil feedback and increases P recycling.
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