Genetic diversity of European maize landraces: Dataset on the molecular and phenotypic variation of derived doubled-haploid populations

Are cereal grasses a single genetic system?

In 1993, a passionate and provocative call to arms urged cereal researchers to consider the taxon they study as a single genetic system and collaborate with each other. Since then, that group of scientists has seen their discipline blossom. In an attempt to understand what unity of genetic systems means and how the notion was borne out by later research, we survey the progress and prospects of cereal genomics: sequence assemblies, population-scale sequencing, resistance gene cloning and domestication genetics. Gene order may not be as extraordinarily well conserved in the grasses as once thought. Still, several recurring themes have emerged. The same ancestral molecular pathways defining plant architecture have been co-opted in the evolution of different cereal crops. Such genetic convergence as much as cross-fertilization of ideas between cereal geneticists has led to a rich harvest of genes that, it is hoped, will lead to improved varieties.

Characterization and nutritional valorization of agricultural waste corncobs from Italian maize landraces through the growth of medicinal mushrooms

The research investigates the potential use of maize cobs (or corncobs) from five genotypes, including the B73 inbred line and four locally cultivated landraces from Northern Italy, as substrate for implementing Solid State fermentation processes with four Medicinal Mushrooms (MMs). The corncobs were characterized based on their proximate composition, lignin, phenolics content (both free and bound), and total antioxidant capacity. Among the MMs tested, Pleurotus ostreatus and Ganoderma annularis demonstrated the most robust performance. Their growth was parametrized using Image Analysis technique, and chemical composition of culture samples was characterized compared to that of corncobs alone. In all culture samples, the growth of MMs led to a significant reduction (averaging 40%) in the total phenolics contents compared to that measured in corncobs alone. However, the high content of free phenolics in the cobs negatively impacted the growth of P. ostreatus. The final MM-corncob matrix exhibited reduced levels of free sugars and starch (≤ 2.2% DW, as a sum) and increased levels of proteins (up to 5.9% DW) and soluble dietary fiber (up to 5.0% DW), with a notable trend toward higher levels of β-glucan compared to corncobs alone. This research paves the way for the use of this matrix as an active ingredient to enhance the nutritional value of food preparations.

Influence of the mating design on the additive genetic variance in plant breeding populations

KEY MESSAGE

Mating designs determine the realized additive genetic variance in a population sample. Deflated or inflated variances can lead to reduced or overly optimistic assessment of future selection gains. The additive genetic variance [Formula: see text] inherent to a breeding population is a major determinant of short- and long-term genetic gain. When estimated from experimental data, it is not only the additive variances at individual loci (QTL) but also covariances between QTL pairs that contribute to estimates of [Formula: see text]. Thus, estimates of [Formula: see text] depend on the genetic structure of the data source and vary between population samples. Here, we provide a theoretical framework for calculating the expectation and variance of [Formula: see text] from genotypic data of a given population sample. In addition, we simulated breeding populations derived from different numbers of parents (P = 2, 4, 8, 16) and crossed according to three different mating designs (disjoint, factorial and half-diallel crosses). We calculated the variance of [Formula: see text] and of the parameter b reflecting the covariance component in [Formula: see text] standardized by the genic variance. Our results show that mating designs resulting in large biparental families derived from few disjoint crosses carry a high risk of generating progenies exhibiting strong covariances between QTL pairs on different chromosomes. We discuss the consequences of the resulting deflated or inflated [Formula: see text] estimates for phenotypic and genome-based selection as well as for applying the usefulness criterion in selection. We show that already one round of recombination can effectively break negative and positive covariances between QTL pairs induced by the mating design. We suggest to obtain reliable estimates of [Formula: see text] and its components in a population sample by applying statistical methods differing in their treatment of QTL covariances.

Combining multiplex gene editing and doubled haploid technology in maize

A major advantage of using CRISPR/Cas9 for gene editing is multiplexing, that is, the simultaneous targeting of many genes. However, primary transformants typically contain hetero-allelic mutations or are genetic mosaic, while genetically stable lines that are homozygous are desired for functional analysis. Currently, a dedicated and labor-intensive effort is required to obtain such higher-order mutants through several generations of genetic crosses and genotyping. We describe the design and validation of a rapid and efficient strategy to produce lines of genetically identical plants carrying various combinations of homozygous edits, suitable for replicated analysis of phenotypical differences. This approach was achieved by combining highly multiplex gene editing in Zea mays (maize) with in vivo haploid induction and efficient in vitro generation of doubled haploid plants using embryo rescue doubling. By combining three CRISPR/Cas9 constructs that target in total 36 genes potentially involved in leaf growth, we generated an array of homozygous lines with various combinations of edits within three generations. Several genotypes show a reproducible 10% increase in leaf size, including a septuple mutant combination. We anticipate that our strategy will facilitate the study of gene families via multiplex CRISPR mutagenesis and the identification of allele combinations to improve quantitative crop traits.