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Cytokinins and gibberellins (GAs) play antagonistic roles in regulating reproductive meristem activity. Cytokinins have positive effects on meristem activity and maintenance. During inflorescence meristem development, cytokinin biosynthesis is activated via a KNOX-mediated pathway. Increased cytokinin activity leads to higher grain number, whereas GAs negatively affect meristem activity. The GA biosynthesis genes GA20oxs are negatively regulated by KNOX proteins. KNOX proteins function as modulators, balancing cytokinin and GA activity in the meristem. However, little is known about the crosstalk among cytokinin and GA regulators together with KNOX proteins and how KNOX-mediated dynamic balancing of hormonal activity functions. Through map-based cloning of QTLs, we cloned a GA biosynthesis gene, Grain Number per Panicle1 (GNP1), which encodes rice GA20ox1. The grain number and yield of NIL-GNP1TQ were significantly higher than those of isogenic control (Lemont). Sequence variations in its promoter region increased the levels of GNP1 transcripts, which were enriched in the apical regions of inflorescence meristems in NIL-GNP1TQ. We propose that cytokinin activity increased due to a KNOX-mediated transcriptional feedback loop resulting from the higher GNP1 transcript levels, in turn leading to increased expression of the GA catabolism genes GA2oxs and reduced GA1 and GA3 accumulation. This rebalancing process increased cytokinin activity, thereby increasing grain number and grain yield in rice. These findings uncover important, novel roles of GAs in rice florescence meristem development and provide new insights into the crosstalk between cytokinin and GA underlying development process.

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We introduce a theoretical framework that predicts the optimum planting density and maximal yield for an annual crop plant. Two critical parameters determine the trajectory of plant growth and the optimal density, N opt , where canopies of growing plants just come into contact, and competition: (i) maximal size at maturity, M max , which differs among varieties due to artificial selection for different usable products; and (ii) intrinsic growth rate, g, which may vary with variety and environmental conditions. The model predicts (i) when planting density is less than N opt , all plants of a crop mature at the same maximal size, M max , and biomass yield per area increases linearly with density; and (ii) when planting density is greater than N opt , size at maturity and yield decrease with −4/3 and −1/3 powers of density, respectively. Field data from China show that most annual crops, regardless of variety and life form, exhibit similar scaling relations, with maximal size at maturity, M max , accounting for most of the variation in optimal density, maximal yield, and energy use per area. Crops provide elegantly simple empirical model systems to study basic processes that determine the performance of plants in agricultural and less managed ecosystems. E fficiency of agriculture will need to increase to feed the growing human population as arable land, water, and fertilizers become increasingly limited (1, 2). A relevant question is, What is the optimal density to plant seeds of an annual crop? The answer should be of interest to applied plant scientists who want to predict planting densities that maximize yields and to basic plant scientists who want to better understand the fundamental processes of growth and competition.Here we develop and test analytical models that predict the optimal seeding density that maximizes yield for annual crop plants. These models were inspired by theories and data on plant scaling relations (3-10). We modify the theories to model the growth and maturation of annual crops as a function of density and mature plant size. We evaluate the models using data from agricultural crops in controlled experiments in China. Empirical and Conceptual BackgroundThere is an intermediate seeding density for an annual crop that maximizes yield at harvest. When seeds are planted at lower density, yields are reduced because the plants grow to mature size without using all available resources. When seeds are planted at higher density, plants compete for resources and mature at smaller sizes; total yield declines because mature size per individual decreases faster than number of individuals per area increases.The dynamics of crop production can be modeled as the outcome of four interacting processes. First, the growth of an individual annual plant from germination to maturity traces a sigmoidal trajectory that reflects allocation of energy and biomass to new tissue as a function of plant size. Second, size at maturity depends on density: Initially all plants grow at nearmaximal rates, but if individuals ...

Effect of genetic background on detection of quantitative trait locus (QTL) governing salinity tolerance (ST) was studied using two sets of reciprocal introgression lines (ILs) derived from a cross between a moderately salinity tolerant japonica variety, Xiushui09 from China, and a drought tolerant but salinity susceptible indica breeding line, IR2061-520-6-9 from the Philippines. Salt toxicity symptoms (SST) on leaves, days to seedling survival (DSS), and sodium and potassium uptake by shoots were measured under salinity stress of 140 mmol/L of NaCl. A total of 47 QTLs, including 26 main-effect QTLs (M-QTLs) and 21 epistatic QTLs (E-QTLs), were identified from the two sets of reciprocal ILs. Among the 26 M-QTLs, only four (15.4%) were shared in the reciprocal backgrounds while no shared E-QTLs were detected, indicating that ST QTLs, especially E-QTLs, were very specific to the genetic background. Further, 78.6% of the M-QTLs for SST and DSS identified in the reciprocal ILs were also detected in the recombinant inbred lines (RILs) from the same cross, which clearly brings out the background effect on ST QTL detection and its utilization in ST breeding. The detection of ILs with various levels of pyramiding of nonallelic M-QTL alleles for ST from Xiushui09 into IR2061-520-6-9 allowed us to further improve the ST in rice.

We conclude that the change in floral orientation could enhance male and female fitness of A. luridus and is effectively adaptive to the alpine environments, indicating a strong selection by the combined pressure from various abiotic nonpollinator agents in shaping the floral traits of this alpine plant.

QTLs for salt-tolerance (ST) related traits at the seedling and tillering stages were identified using 99 BC(2)F(8) introgression lines (IL) derived from a cross between IR64 (indica) as a recurrent parent and Binam (japonica) from Iran as the donor parent. Thirteen QTLs affecting survival days of seedlings (SDS), score of salt toxicity of leaves (SST), shoot K(+) concentration (SKC) and shoot Na(+) concentration (SNC) at the seedling stage and 22 QTLs underlying fresh weight of shoots (FW), tiller number per plant (TN) and plant height (PH) at the tillering stage were identified. Most QTLs detected at the tillering stage showed obvious differential expression to salt stress and were classified into three types based on their differential behaviors. Type I included 11 QTLs which were expressed only under the non-stress condition. Type II included five QTLs expressed in the control and the salt stress conditions, and three of them (QPh5, QPh8 and QTn9) had similar quantity and the same direction of gene effect, suggesting their expression was less influenced by salt stress. Type III included six QTLs which were detectable only under salt stress, suggesting that these QTLs were apparently induced by the stress. Thirteen QTLs affecting trait difference or trait stability of ILs between the stress and non-stress conditions were identified and the Binam alleles at all loci except QPh4, QTn2 and QFw2a decreased trait difference. The three QTLs less influenced by the stress and 13 QTLs affecting trait stability were considered as ST QTLs which contributed to ST. Comparing the distribution of QTLs detected at the seedling and tillering stages, most (69%) of them were genetically independent. Only four were the same or adjacent regions on chromosomes 1, 2, 8 and 11 harboring ST QTLs detected at the two stages, suggesting that partial genetic overlap of ST across the two stages occurs. It is likely, therefore, to develop ST rice variety for both stages by pyramiding of ST QTLs of different stages or selection against the overlapping QTLs between the two stages via marker-assisted selection (MAS).