Epigenetic chromatin modifiers in barley: IV. The study of barley Polycomb group (PcG) genes during seed development and in response to external ABA

<p>Abstract</p> <p>Background</p> <p>Epigenetic phenomena have been associated with the regulation of active and silent chromatin states achieved by modifications of chromatin structure through DNA methylation, and histone post-translational modifications. The latter is accomplished, in part, through the action of PcG (Polycomb group) protein complexes which methylate nucleosomal histone tails at specific sites, ultimately leading to chromatin compaction and gene silencing. Different PcG complex variants operating during different developmental stages have been described in plants. In particular, the so-called FIE/MEA/FIS2 complex governs the expression of genes important in embryo and endosperm development in <it>Arabidopsis</it>. In our effort to understand the epigenetic mechanisms regulating seed development in barley (<it>Hordeum vulgare</it>), an agronomically important monocot plant cultivated for its endosperm, we set out to characterize the genes encoding barley PcG proteins.</p> <p>Results</p> <p>Four barley <it>PcG </it>gene homologues, named <it>HvFIE</it>, <it>HvE(Z), HvSu(z)12a</it>, and <it>HvSu(z)12b </it>were identified and structurally and phylogenetically characterized. The corresponding genes <it>HvFIE</it>, <it>HvE(Z), HvSu(z)12a</it>, and <it>HvSu(z)12b </it>were mapped onto barley chromosomes 7H, 4H, 2H and 5H, respectively. Expression analysis of the <it>PcG </it>genes revealed significant differences in gene expression among tissues and seed developmental stages and between barley cultivars with varying seed size. Furthermore, <it>HvFIE </it>and <it>HvE(Z) </it>gene expression was responsive to the abiotic stress-related hormone abscisic acid (ABA) known to be involved in seed maturation, dormancy and germination.</p> <p>Conclusion</p> <p>This study reports the first characterization of the <it>PcG </it>homologues, <it>HvFIE, HvE(Z)</it>, <it>HvSu(z)12a </it>and <it>HvSu(z)12b </it>in barley. All genes co-localized with known chromosomal regions responsible for malting quality related traits, suggesting that they might be used for developing molecular markers to be applied in marker assisted selection. The <it>PcG </it>differential expression pattern in different tissues and seed developmental stages as well as in two barley cultivars with different seed size is suggestive of a role for these genes in barley seed development. <it>HvFIE </it>and <it>HvE(Z) </it>were also found to be induced by the plant hormone ABA implying an association with ABA-mediated processes during seed development, germination and stress response.</p

Genome-wide association mapping in winter barley for grain yield and culm cell wall polymer content using the high-throughput CoMPP technique

<div><p>A collection of 112 winter barley varieties (<i>Hordeum vulgare</i> L.) was grown in the field for two years (2008/09 and 2009/10) in northern Italy and grain and straw yields recorded. In the first year of the trial, a severe attack of barley yellow mosaic virus (BaYMV) strongly influenced final performances with an average reduction of ~ 50% for grain and straw harvested in comparison to the second year. The genetic determination (GD) for grain yield was 0.49 and 0.70, for the two years respectively, and for straw yield GD was low in 2009 (0.09) and higher in 2010 (0.29). Cell wall polymers in culms were quantified by means of the monoclonal antibodies LM6, LM11, JIM13 and BS-400-3 and the carbohydrate-binding module CBM3a using the high-throughput CoMPP technique. Of these, LM6, which detects arabinan components, showed a relatively high GD in both years and a significantly negative correlation with grain yield (GYLD). Overall, heritability (<i>H</i>^<i>2</i>) was calculated for GYLD, LM6 and JIM and resulted to be 0.42, 0.32 and 0.20, respectively. A total of 4,976 SNPs from the 9K iSelect array were used in the study for the analysis of population structure, linkage disequilibrium (LD) and genome-wide association study (GWAS). Marker-trait associations (MTA) were analyzed for grain yield and cell wall determination by LM6 and JIM13 as these were the traits showing significant correlations between the years. A single QTL for GYLD containing three MTAs was found on chromosome 3H located close to the Hv-eIF4E gene, which is known to regulate resistance to BaYMV. Subsequently the QTL was shown to be tightly linked to rym4, a locus for resistance to the virus. GWAs on arabinans quantified by LM6 resulted in the identification of major QTLs closely located on 3H and hypotheses regarding putative candidate genes were formulated through the study of gene expression levels based on bioinformatics tools.</p></div

Determinants of barley grain yield in drought-prone Mediterranean environments

The determinants of barley grain yield in drought-prone Mediterranean environments have been studied in the Nure x Tremois (NT) population. A large set of yield and other morpho-physiological data were recorded in 118 doubled haploid (DH) lines of the population, in multi-environment field trials (18 site-year combination). Agrometeorological variables have been recorded and calculated at each site too. Four main periods of barley development were considered, vegetative, reproductive early and late grain filling phases, to dissect the effect on yield traits of the growth phases. Relationships between agrometeorological variables, grain yield (GY) and its main components (GN and GW) were also investigated by correlation. Results firstly gave a clear indication of the involvement of water consumption in determining GY and GW (r2=0.616, P=0.007 and r2=0.703, P=0.005, respectively) calculated from sowing to the early grain filling period, while GN showed its highest correlation with the total photothermal quotient (PQ) calculated for the same period (r2=0.646, P=0.013). With the only exception of total PQ calculated during the vegetative period, all significant correlations with GY were associated to water-dependent agrometeorological parameters. As a second result, the NT segregating population allowed us to weight the amount of interaction due to genotypes over environments or to environments in relation to genotypes by a GGE analysis; 47.67% of G+GE sum of squares was explained by the first two principal components. Then, the introduction of genomic information at major barley genes regulating the length of growth cycle allowed us to explain patterns of adaptation of different groups of NT lines according to the variants (alleles) harbored at venalization (Vrn-H1) in combination with earliness (Eam6) genes. The superiority of the lines carrying the Nure allele at Eam6 was confirmed by factorial ANOVA testing the four possible haplotypes obtained combining alternative alleles at Eam6 and Vrn-H1. Maximum yield potential and differentials among the NT genotypes was finally explored through Finlay-Wilkinson model to interpret grain yield of NT genotypes together with yield adaptability (Ya), as the regression coefficient bi; Ya ranged from 0.71 for NT77 to 1.20 for NT19. Lines simply harboring the Nure variants at the two genes behaved as highest yielding (3.04 t ha\u20131), and showed the highest yield adaptability (bi=1.05). The present study constitutes a starting point towards the introduction of genomic variables in agronomic models for barley grain yield in Mediterranean environments

THE COMPLEX OF SANTA CROCE IN RAVENNA AS A CASE STUDY: INTEGRATION OF 3D TECHNIQUES FOR SURVEYING AND MONITORING OF A HISTORICAL SITE

Over the last decades, climate change has brought more and more challenges to managers of cultural heritage and researchers. The increasing effects of natural hazards on assets have required the development of a new protocol of techniques and methodologies for the monitoring of Cultural Heritage and the adoption of management plans adapted to the new challenges at every stage of risk management. The work here presented aims at providing an insight of the work undertaken under the framework of the H2020 SHELTER project, to showcase the first steps of the multi-disciplinary research conducted in one of the project’s case studies, the complex of Santa Croce in Ravenna, Italy. The paper provides the presentation of the case study and the description of the surveying activities with some first results, to provide a preliminary assessment of the site criticalities to be addressed in the future activities in the area, in line with the EU project expected outcomes

Multi-environment genome -wide association mapping of culm morphology traits in barley

In cereals with hollow internodes, lodging resistance is influenced by morphological characteristics such as internode diameter and culm wall thickness. Despite their relevance, knowledge of the genetic control of these traits and their relationship with lodging is lacking in temperate cereals such as barley. To fill this gap, we developed an image analysis-based protocol to accurately phenotype culm diameters and culm wall thickness across 261 barley accessions. Analysis of culm trait data collected from field trials in seven different environments revealed high heritability values (>50%) for most traits except thickness and stiffness, as well as genotype-by-environment interactions. The collection was structured mainly according to row-type, which had a confounding effect on culm traits as evidenced by phenotypic correlations. Within both row-type subsets, outer diameter and section modulus showed significant negative correlations with lodging (Peer reviewe

High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings

In plants, the study of belowground traits is gaining momentum due to their importance on yield formation and the uptake of water and nutrients. In several cereal crops, seminal root number and seminal root angle are proxy traits of the root system architecture at the mature stages, which in turn contributes to modulating the uptake of water and nutrients. Along with seminal root number and seminal root angle, experimental evidence indicates that the transpiration rate response to evaporative demand or vapor pressure deficit is a key physiological trait that might be targeted to cope with drought tolerance as the reduction of the water flux to leaves for limiting transpiration rate at high levels of vapor pressure deficit allows to better manage soil moisture. In the present study, we examined the phenotypic diversity of seminal root number, seminal root angle, and transpiration rate at the seedling stage in a panel of 8-way Multiparent Advanced Generation Inter-Crosses lines of winter barley and correlated these traits with grain yield measured in different site-by-season combinations. Second, phenotypic and genotypic data of the Multiparent Advanced Generation Inter-Crosses population were combined to fit and cross-validate different genomic prediction models for these belowground and physiological traits. Genomic prediction models for seminal root number were fitted using threshold and log-normal models, considering these data as ordinal discrete variable and as count data, respectively, while for seminal root angle and transpiration rate, genomic prediction was implemented using models based on extended genomic best linear unbiased predictors. The results presented in this study show that genome-enabled prediction models of seminal root number, seminal root angle, and transpiration rate data have high predictive ability and that the best models investigated in the present study include first-order additive × additive epistatic interaction effects. Our analyses indicate that beyond grain yield, genomic prediction models might be used to predict belowground and physiological traits and pave the way to practical applications for barley improvement

Genomic Prediction of Grain Yield in a Barley MAGIC Population Modeling Genotype per Environment Interaction

18 Pags.- 7 Figs.- 4 Tabls. © 2021 Puglisi, Delbono, Visioni, Ozkan, Kara, Casas, Igartua, Valè, Piero, Cattivelli, Tondelli and Fricano. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).Multi-parent Advanced Generation Inter-crosses (MAGIC) lines have mosaic genomes that are generated shuffling the genetic material of the founder parents following pre-defined crossing schemes. In cereal crops, these experimental populations have been extensively used to investigate the genetic bases of several traits and dissect the genetic bases of epistasis. In plants, genomic prediction models are usually fitted using either diverse panels of mostly unrelated accessions or individuals of biparental families and several empirical analyses have been conducted to evaluate the predictive ability of models fitted to these populations using different traits. In this paper, we constructed, genotyped and evaluated a barley MAGIC population of 352 individuals developed with a diverse set of eight founder parents showing contrasting phenotypes for grain yield. We combined phenotypic and genotypic information of this MAGIC population to fit several genomic prediction models which were cross-validated to conduct empirical analyses aimed at examining the predictive ability of these models varying the sizes of training populations. Moreover, several methods to optimize the composition of the training population were also applied to this MAGIC population and cross-validated to estimate the resulting predictive ability. Finally, extensive phenotypic data generated in field trials organized across an ample range of water regimes and climatic conditions in the Mediterranean were used to fit and cross-validate multi-environment genomic prediction models including G×E interaction, using both genomic best linear unbiased prediction and reproducing kernel Hilbert space along with a non-linear Gaussian Kernel. Overall, our empirical analyses showed that genomic prediction models trained with a limited number of MAGIC lines can be used to predict grain yield with values of predictive ability that vary from 0.25 to 0.60 and that beyond QTL mapping and analysis of epistatic effects, MAGIC population might be used to successfully fit genomic prediction models. We concluded that for grain yield, the single-environment genomic prediction models examined in this study are equivalent in terms of predictive ability while, in general, multi-environment models that explicitly split marker effects in main and environmental-specific effects outperform simpler multi-environment models.This research was carried out in the framework of the iBarMed project, which has been funded through the ARIMNet2 initiative and the Italian “Ministry of Agricultural, Food and Forestry Policies” under grant agreement “DM n. 20120.” ARIMNet2 has received funding from the EU 7th Framework Programme for research, technological development and demonstration under grant agreement no. 618127. The work was also supported by YSTEMIC_1063 (An integrated approach to the challenge of sustainable food systems: adaptive and mitigatory strategies to address climate change and malnutrition: From cereal diversity to plant breeding), a research project funded by Italian “Ministry of Agricultural, Food and Forestry Policies” in the frame of the Knowledge Hub on Food and Nutrition Security.Peer reviewe

Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley

Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop of barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi-environment common garden trials. Then we applied refined statistical methods, including based on exomic haplotype states, for genotype-by-environment (G 7E) modelling. Sub-populations defined from exomic profiles were coincident with barley's biology, geography and history, and explained a high proportion of trial phenotypic variance. Clear G 7E interactions indicated adaptation profiles that varied for landraces and cultivars. Exploration of circadian clock-related genes, associated with the environmentally-adaptive days to heading trait (crucial for the crop's spread from the Fertile Crescent), illustrated complexities in G 7E effect directions, and the importance of latitudinally-based genic context in the expression of large effect alleles. Our analysis supports a gene-level scientific understanding of crop adaption and leads to practical opportunities for crop improvement, allowing the prioritisation of genomic regions and particular sets of lines for breeding efforts seeking to cope with climate change and other stresses