Quantitative analysis reveals genotype- and domain- specific differences between mRNA and protein expression of segmentation genes in Drosophila.

In many biological systems gene expression at mRNA and protein levels is not identical. Rigorous comparison of such differences on a spatio-temporal scale is still not feasible by high-throughput transcriptomic and proteomic analyses of early embryo development. Here, we characterize differences between mRNA and protein expression of Drosophila segmentation genes at the level of individual gene expression domains. We obtained quantitative imaging data on expression of gap genes gt and hb and pair-rule gene eve for Drosophila wild type embryos, Kr null mutants and Kr+/Kr- heterozygotes. To compare mRNA and protein expression we use several criteria including difference in amplitude and positions of expression domains, pattern shape and positional variability. For a number of gene expression domains we show examples where protein expression does not repeat mRNA expression even after a temporal delay. We calculated time delays between eve pattern formation at the level of mRNA and protein for wild type embryos, Kr mutants and Kr+/Kr- heterozygotes. We detect that in wild type embryos, the amplitudes of eve stripes 3 and 7 do not differ significantly at the level of mRNA, however, stripe 3 is higher than stripe 7 at the protein level. We further show that hb mRNA and protein expression in both anterior and posterior domains significantly differs at specific time points. The formation of hb PS4 stripe at the mRNA level proceeds five times faster than at the level of protein. With regard to spatial expression, we show that the offset between posterior gt mRNA and protein domains is much larger in Kr mutants than in wild type embryos and heterozygotes. Finally, we analyze differences in positional variability of eve stripe 7 expression in Kr mutants and Kr+/Kr- heterozygotes at the level of mRNA and protein. These results enable further perspectives to uncover mechanisms underlying discrepancies between mRNA and protein expression in early embryo.

Dynamical climatic model for time to flowering in Vigna radiata.

BACKGROUND: Phenology data collected recently for about 300 accessions of Vigna radiata (mungbean) is an invaluable resource for investigation of impacts of climatic factors on plant development. RESULTS: We developed a new mathematical model that describes the dynamic control of time to flowering by daily values of maximal and minimal temperature, precipitation, day length and solar radiation. We obtained model parameters by adaptation to the available experimental data. The models were validated by cross-validation and used to demonstrate that the phenology of adaptive traits, like flowering time, is strongly predicted not only by local environmental factors but also by plant geographic origin and genotype. CONCLUSIONS: Of local environmental factors maximal temperature appeared to be the most critical factor determining how faithfully the model describes the data. The models were applied to forecast time to flowering of accessions grown in Taiwan in future years 2020-2030.

Genome-wide association study in accessions of the mini-core collection of mungbean (Vigna radiata) from the World Vegetable Gene Bank (Taiwan).

BACKGROUND: Mungbean (Vigna radiata (L.) R. Wilczek, or green gram) is important tropical and sub-tropical legume and a rich source of dietary protein and micronutrients. In this study we employ GWAS to examine the genetic basis of variation in several important traits in mungbean, using the mini-core collection established by the World Vegetable Center, which includes 296 accessions that represent the major market classes. This collection has been grown in a common field plot in southern European part of Russia in 2018. RESULTS: We used 5041 SNPs in 293 accessions that passed strict filtering for genetic diversity, linkage disequilibrium, population structure and GWAS analysis. Polymorphisms were distributed among all chromosomes, but with variable density. Linkage disequilibrium decayed in approximately 105 kb. Four distinct subgroups were identified within 293 accessions with 70% of accessions attributed to one of the four populations. By performing GWAS on the mini-core collection we have found several loci significantly associated with two important agronomical traits. Four SNPs associated with possibility of maturation in Kuban territory of Southern Russia in 2018 were identified within a region of strong linkage which contains genes encoding zinc finger A20 and an AN1 domain stress-associated protein. CONCLUSIONS: The core collection of mungbean established by the World Vegetable Center is a valuable resource for mungbean breeding. The collection has been grown in southern European part of Russia in 2018 under incidental stresses caused by abnormally hot weather and different photoperiod. We have found several loci significantly associated with color of hypocotyl and possibility of maturation under these stressful conditions. SNPs associated with possibility of maturation localize to a region on chromosome 2 with strong linkage, in which genes encoding zinc finger A20 and AN1 domain stress associated protein (SAP) are located. Phenotyping of WorldVeg collection for maturation traits in temperate climatic locations is important as phenology remains a critical breeding target for mungbean. As demand rises for mungbean, production in temperate regions with shorter growing seasons becomes crucial to keep up with needs. Uncovering SNPs for phenology traits will speed breeding efforts.

Genomic Analysis of Vavilov's Historic Chickpea Landraces Reveals Footprints of Environmental and Human Selection.

A defining challenge of the 21st century is meeting the nutritional demands of the growing human population, under a scenario of limited land and water resources and under the specter of climate change. The Vavilov seed bank contains numerous landraces collected nearly a hundred years ago, and thus may contain 'genetic gems' with the potential to enhance modern breeding efforts. Here, we analyze 407 landraces, sampled from major historic centers of chickpea cultivation and secondary diversification. Genome-Wide Association Studies (GWAS) conducted on both phenotypic traits and bioclimatic variables at landraces sampling sites as extended phenotypes resulted in 84 GWAS hits associated to various regions. The novel haploblock-based test identified haploblocks enriched for single nucleotide polymorphisms (SNPs) associated with phenotypes and bioclimatic variables. Subsequent bi-clustering of traits sharing enriched haploblocks underscored both non-random distribution of SNPs among several haploblocks and their association with multiple traits. We hypothesize that these clusters of pleiotropic SNPs represent co-adapted genetic complexes to a range of environmental conditions that chickpea experienced during domestication and subsequent geographic radiation. Linking genetic variation to phenotypic data and a wealth of historic information preserved in historic seed banks are the keys for genome-based and environment-informed breeding intensification.

Quantitative analysis of the heterogeneous population of endocytic vesicles.

The quantitative characterization of endocytic vesicles in images acquired with microscope is critically important for deciphering of endocytosis mechanisms. Image segmentation is the most important step of quantitative image analysis. In spite of availability of many segmentation methods, the accurate segmentation is challenging when the images are heterogeneous with respect to object shapes and signal intensities what is typical for images of endocytic vesicles. We present a Morphological reconstruction and Contrast mapping segmentation method (MrComas) for the segmentation of the endocytic vesicle population that copes with the heterogeneity in their shape and intensity. The method uses morphological opening and closing by reconstruction in the vicinity of local minima and maxima respectively thus creating the strong contrast between their basins of attraction. As a consequence, the intensity is flattened within the objects and their edges are enhanced. The method accurately recovered quantitative characteristics of synthetic images that preserve characteristic features of the endocytic vesicle population. In benchmarks and quantitative comparisons with two other popular segmentation methods, namely manual thresholding and Squash plugin, MrComas shows the best segmentation results on real biological images of EGFR (Epidermal Growth Factor Receptor) endocytosis. As a proof of feasibility, the method was applied to quantify the dynamical behavior of Early Endosomal Autoantigen 1 (EEA1)-positive endosome subpopulations during EGF-stimulated endocytosis.