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Drought stress is one of the key plant stresses reducing grain yield in cereal crops worldwide. Although it is not a breeding target in Northern Europe, the changing climate and the drought of 2018 have increased its significance in the region. A key challenge, therefore, is to identify novel germplasm with higher drought tolerance, a task that will require continuous characterization of a large number of genotypes. The aim of this work was to assess if phenotyping systems with low-cost consumer-grade digital cameras can be used to characterize germplasm for drought tolerance. To achieve this goal, we built a proximal phenotyping cart mounted with digital cameras and evaluated it by characterizing 142 winter wheat genotypes for drought tolerance under field conditions. The same genotypes were additionally characterized for seedling stage traits by imaging under controlled growth conditions. The analysis revealed that under field conditions, plant biomass, relative growth rates, and Normalized Difference Vegetation Index (NDVI) from different growth stages estimated by imaging were significantly correlated to drought tolerance. Under controlled growth conditions, root count at the seedling stage evaluated by imaging was significantly correlated to adult plant drought tolerance observed in the field. Random forest models were trained by integrating measurements from field and controlled conditions and revealed that plant biomass and relative growth rates at key plant growth stages are important predictors of drought tolerance. Thus, based on the results, it can be concluded that the consumer-grade cameras can be key components of affordable automated phenotyping systems to accelerate pre-breeding for drought tolerance.

Background In the Neolithic, domestic sheep migrated into Europe and subsequently spread in westerly and northwesterly directions. Reconstruction of these migrations and subsequent genetic events requires a more detailed characterization of the current phylogeographic differentiation. Results We collected 50 K single nucleotide polymorphism (SNP) profiles of Balkan sheep that are currently found near the major Neolithic point of entry into Europe, and combined these data with published genotypes from southwest-Asian, Mediterranean, central-European and north-European sheep and from Asian and European mouflons. We detected clines, ancestral components and admixture by using variants of common analysis tools: geography-informative supervised principal component analysis (PCA), breed-specific admixture analysis, across-breed \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f_{4}$$\end{document}f4 profiles and phylogenetic analysis of regional pools of breeds. The regional Balkan sheep populations exhibit considerable genetic overlap, but are clearly distinct from the breeds in surrounding regions. The Asian mouflon did not influence the differentiation of the European domestic sheep and is only distantly related to present-day sheep, including those from Iran where the mouflons were sampled. We demonstrate the occurrence, from southeast to northwest Europe, of a continuously increasing ancestral component of up to 20% contributed by the European mouflon, which is assumed to descend from the original Neolithic domesticates. The overall patterns indicate that the Balkan region and Italy served as post-domestication migration hubs, from which wool sheep reached Spain and north Italy with subsequent migrations northwards. The documented dispersal of Tarentine wool sheep during the Roman period may have been part of this process. Our results also reproduce the documented 18th century admixture of Spanish Merino sheep into several central-European breeds. Conclusions Our results contribute to a better understanding of the events that have created the present diversity pattern, which is relevant for the management of the genetic resources represented by the European sheep population.

Additional file 9: Figure S5. Supervised PCA of 546 animals as in Fig. 2b, showing svPC1 vs. svPC3 averaged per breed.

Additional file 7: Figure S3. FineStructure clustering of eastern and southeastern European sheep breeds. The color of each bin in the matrix indicates the number of “genomic chunks” copied from a donor (columns) to a recipient individual (rows).

Additional file 14: Figure S9. Neighbor-net graphs of 17 regional groups of breeds (Additional file 12 B) with (A) AMF, (B) EMF, (C, D) both AMF and EMF; (D, E) pattern obtained by increasing the AMF-EFM distance in order to suppress the EMF-AMF clustering and to show different affinities of EMF and AMF for European domestic sheep.

Additional file 8: Figure S4. Left panels: normal PCA plots of 525 sheep (≤ 6 per breed) including the inbred EFB, KCH, VBS. Right panels: supervised PCA of 546 sheep, including three mouflon populations, in which EFB, KCH and VBS as well as the mouflons have been excluded for calculation of the principal components (svPC1, svPC2 and svPC3).

Additional file 5: Figure S1. Inverse linear relationship of observed heterozygosity and the total ROH coverage FROH, showing relatively low heterozygosity values for AMF, SMF and fat-tailed sheep.

Additional file 6: Figure S2. Neighbour-joining tree visualizing the allele-sharing distances of the Balkan sheep (see Fig. 1) or (see Additional file 1: Table S1) for the breed codes). Breeds that are dispersed over different branches of the tree are indicated by colored lines.

Pea (Pisum sativum L. subsp. sativum) is one of the oldest domesticated species and a widely cultivated legume. In this study, we combined next generation sequencing (NGS) data referring to two genotyping-by-sequencing (GBS) libraries, each one prepared from a different Pisum germplasm collection. The selection of single nucleotide polymorphism (SNP) loci called in both germplasm collections caused some loss of information; however, this did not prevent the obtainment of one of the largest datasets ever used to explore pea biodiversity, consisting of 652 accessions and 22 127 markers. The analysis of population structure reflected genetic variation based on geographic patterns and allowed the definition of a model for the expansion of pea cultivation from the domestication centre to other regions of the world. In genetically distinct populations, the average decay of linkage disequilibrium (LD) ranged from a few bases to hundreds of kilobases, thus indicating different evolutionary histories leading to their diversification. Genome-wide scans resulted in the identification of putative selective sweeps associated with domestication and breeding, including genes known to regulate shoot branching, cotyledon colour and resistance to lodging, and the correct mapping of two Mendelian genes. In addition to providing information of major interest for fundamental and applied research on pea, our work describes the first successful example of integration of different GBS datasets generated from ex situ collections – a process of potential interest for a variety of purposes, including conservation genetics, genome-wide association studies, and breeding.

Almond [Prunus dulcisMiller (D.A. Webb)] is the main tree nut species worldwide. Here, genotyping-by-sequencing (GBS) was applied to 149 almond cultivars from the ex situ collections of the Italian Council for Agricultural Research (CREA) and the Spanish National Research Council (CSIC), leading to the detection of 93,119 single-nucleotide polymorphisms (SNPs). The study of population structure outlined four distinct genetic groups and highlighted diversification between the Mediterranean and Californian gene pools. Data on SNP diversity and runs of homozygosity (ROHs) allowed the definition of kinship, inbreeding, and linkage disequilibrium (LD) decay in almond cultivated germplasm. Four-year phenotypic observations, gathered on 98 cultivars of the CREA collection, were used to perform a genome-wide association study (GWAS) and, for the first time in a crop species, homozygosity mapping (HM), resulting in the identification of genomic associations with nut, shell, and seed weight. Both GWAS and HM suggested that loci controlling nut and seed weight are mostly independent. Overall, this study provides insights on the almond cultivation history and delivers information of major interest for almond genetics and breeding. In a broader perspective, our results encourage the use of ROHs in crop science to estimate inbreeding, choose parental combinations minimizing the risk of inbreeding depression, and identify genomic footprints of selection for specific traits.

High-throughput genotyping is boosting genome-wide association studies (GWAS) in crop species, ultimately leading to the identification of single nucleotide polymorphisms (SNPs) and genes associated with economically important traits. Choosing a cost-effective genotyping method for crop GWAS requires careful examination of several aspects, namely the purpose and the scale of the study, crop-specific genomic features, and technical and economic matters associated with each genotyping option. Once genotypic data have been obtained, quality control (QC) procedures must be applied to avoid bias and false signals in genotype-phenotype association tests. QC for human GWAS has been extensively reviewed, however QC for crop GWAS may require different actions, depending on the mating system and breeding activities. Here we review most popular genotyping methods based on next generation sequencing (NGS) and array hybridization, and provide observations that should guide the investigator in the choice of the genotyping method for crop GWAS. We define best practises to perform QC, including actions that are specific for crop species. Finally, we provide an overview of bioinformatics tools that can be used to accomplish all needed tasks. Overall, this work aims to provide guidelines to harmonize those procedures leading to SNP datasets ready for crop GWAS.