Assessing the leaf shape dynamic through marker–trait association under drought stress in a rice germplasm panel

The flag leaf acts as a functional leaf in rice, Oryza sativa L., primarily supplying photosynthate to the developing grains and influencing yields to a certain extent. Drought stress damages the leaf physiology, severely affecting grain fertility. Autumn rice of northeast India is called locally as ‘ahu’ rice, and is known for its drought tolerance. Exploring diverse germplasm resources at the morphological level using an association mapping approach can aid in identifying the genomic regions influencing leaf shape dynamics. A marker–trait association (MTA) study was carried out using 95 polymorphic SSR markers and a panel of 273 ahu rice germplasm accessions in drought stress and irrigated conditions. The trials suggest that at the vegetative stage, drought stress significantly affects leaf morphology. The leaf physiology of some tolerant accessions was relatively little affected by stress and these can be considered as ideal varieties for drought conditions. The phenotypic coefficient of variance and genotypic coefficient of variance values implied moderate to high variability for the leaf traits studied. Analysis of molecular variance inferred that 11% of variation in the germplasm panel was due to differences between populations, while the remaining 89% may be attributed to a difference within subgroups formed through STRUCTURE analysis. Using the mixed linear model approach revealed 11 MTAs explaining between 4.5 and 20.0% of phenotypic variance at P > 0.001 for all the leaf traits. The study concludes that ahu rice germplasm is extremely diverse and can serve as a valuable resource for mining desirable alleles for drought tolerance.

Leaf trait differences between 97 pairs of invasive and native plants across China: effects of identities of both the invasive and native species

Many studies have attempted to test whether certain leaf traits are associated with invasive plants, resulting in discrepant conclusions that may be due to species-specificity. However, no effort has been made to test for effects of species identity on invasive-native comparisons. Here, we compared 20 leaf traits between 97 pairs of invasive and native plant species in seven disturbed sites along a southwest-to-northeast transect in China using phylogenetically controlled within-study meta-analyses. The invasive relative to the native species on average had significantly higher leaf nutrients concentrations, photosynthetic rates, photosynthetic nutrients- and energy-use efficiencies, leaf litter decomposition rates, and lower payback time and carbon-to-nitrogen ratios. However, these differences disappeared when comparing weakly invasive species with co-occurring natives and when comparing invasives with co-occurring widespread dominant natives. Furthermore, the magnitudes of the differences in some traits decreased or even reversed when a random subset of strongly to moderately invasive species was excluded from the species pool. Removing rare to common natives produced the same effect, while exclusion of weakly to moderately invasives and dominant to common natives enhanced the differences. Our study indicates that the results of invasive-native comparisons are species-specific, providing a possible explanation for discrepant results in previous studies, such that we may be unable to detect general patterns regarding traits promoting exotic plant invasions through multi-species comparisons.

Leaf Traits and Water-Use Characteristics of Impatiens hainanensis, a Limestone-Endemic Plant under Different Altitudes in Dry and Foggy Seasons

The southwestern mountains of Hainan Island are distributed in the southernmost tropical karst landscape of China, and the unique hydrological structure and frequent solifluction droughts lead to double water stress for local plants. Highly heterogeneous water environments affect the water–use characteristics of plants. Plants develop local adaptative mechanisms in response to changes in the external environment. In this paper, hydrogen–oxygen and carbon stable isotope technology, and physiological index measurements were applied to determine the leaf traits, water–use efficiency, and photosynthetic characteristics of Impatiens hainanensis leaves in dry and foggy seasons, hoping to expound the adaptation mechanism of I. hainanensis leaves to the water dynamics in dry and foggy seasons. In dry and foggy seasons (November 2018 to April 2019), the leaves of I. hainanensis at low and medium altitudes have the following combination of traits: larger leaf dry weights, leaf areas, and specific leaf areas; smaller leaf thicknesses and leaf dry matter contents; and higher chlorophyll contents. In comparison, the leaves of I. hainanensis at high altitudes have the following combination of traits: smaller leaf dry weights, leaf areas, and specific leaf areas; larger leaf thicknesses and leaf dry matter contents; and lower chlorophyll contents. The leaves of I. hainanensis can absorb fog water through their leaves. When the leaves are sprayed with distilled water, the water potential is low, the water potential value gradually increases, and the leaves have a higher rate of water absorption. The leaves of I. hainanensis at low and medium altitudes have the following water–use characteristics: high photosynthesis, high transpiration, and low water–use efficiency. At high altitudes, the Pn of I. hainanensis decreases by 8.43% relative to at low altitudes and by 7.84% relative to at middle altitudes; the Tr decreased by 4.21% relative to at low altitudes and by 3.38% relative to at middle altitude; the WUE increased by 16.61% relative to at low altitudes and increased by 40.79% relative to at middle altitudes. The leaves of I. hainanensis at high altitudes have the following water–use characteristics: low photosynthesis, low transpiration, and high water–use efficiency. I. hainanensis develop different physiological mechanisms of water adaptation by weighing the traits of the leaves and their use of light and water to obtain resources during dry and foggy seasons.

A High-Density Genetic Map Enables Genome Synteny and QTL Mapping of Vegetative Growth and Leaf Traits in Gardenia

The gardenia is a traditional medicinal horticultural plant in China, but its molecular genetic research has been largely hysteretic. Here, we constructed an F1 population with 200 true hybrid individuals. Using the genotyping-by-sequencing method, a high-density sex-average genetic map was generated that contained 4,249 SNPs with a total length of 1956.28 cM and an average genetic distance of 0.46 cM. We developed 17 SNP-based Kompetitive Allele-Specific PCR markers and found that 15 SNPs were successfully genotyped, of which 13 single-nucleotide polymorphism genotypings of 96 F1 individuals showed genotypes consistent with GBS-mined genotypes. A genomic collinearity analysis between gardenia and the Rubiaceae species Coffea arabica, Coffea canephora and Ophiorrhiza pumila showed the relativity strong conservation of LG11 with NC_039,919.1, HG974438.1 and Bliw01000011.1, respectively. Lastly, a quantitative trait loci analysis at three phenotyping time points (2019, 2020, and 2021) yielded 18 QTLs for growth-related traits and 31 QTLs for leaf-related traits, of which qBSBN7-1, qCD8 and qLNP2-1 could be repeatably detected. Five QTL regions (qCD8 and qSBD8, qBSBN7 and qSI7, qCD4-1 and qLLLS4, qLNP10 and qSLWS10-2, qSBD10 and qLLLS10) with potential pleiotropic effects were also observed. This study provides novel insight into molecular genetic research and could be helpful for further gene cloning and marker-assisted selection for early growth and development traits in the gardenia.

Vertical profiles of leaf photosynthesis and leaf traits and soil nutrients in two tropical rainforests in French Guiana before and after a 3-year nitrogen and phosphorus addition experiment

Terrestrial biosphere models typically use the biochemical model of Farquhar, von Caemmerer, and Berry (1980) to simulate photosynthesis, which requires accurate values of photosynthetic capacity of different biomes. However, data on tropical forests are sparse and highly variable due to the high species diversity, and it is still highly uncertain how these tropical forests respond to nutrient limitation in terms of C uptake. Tropical forests often grow on soils low in phosphorus (P) and are, in general, assumed to be P rather than nitrogen (N) limited. However, the relevance of P as a control of photosynthetic capacity is still debated. Here, we provide a comprehensive dataset of vertical profiles of photosynthetic capacity and important leaf traits, including leaf N and P concentrations, from two 3-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N, P, and other leaf nutrients in photosynthesis in tropical forests. To further facilitate the use of our data in syntheses and model studies, we provide an elaborate list of ancillary data, including important soil properties and nutrients, along with the leaf data. As environmental drivers are key to improve our understanding of carbon (C) and nutrient cycle interactions, this comprehensive dataset will aid to further enhance our understanding of how nutrient availability interacts with C uptake in tropical forests. The data are available at https://doi.org/10.5281/zenodo.5638236 (Verryckt, 2021).