QTL mapping for kernel-related traits in a durum wheat x T. dicoccum segregating population

Durum wheat breeding relies on grain yield improvement to meet its upcoming demand while coping with climate change. Kernel size and shape are the determinants of thousand kernel weight (TKW), which is a key component of grain yield, and the understanding of the genetic control behind these traits supports the progress in yield potential. The present study aimed to dissect the genetic network responsible for kernel size components (length, width, perimeter, and area) and kernel shape traits (width-to-length ratio and formcoefficient) as well as their relationships with kernel weight, plant height, and heading date in durum wheat. Quantitative Trait Locus (QTL) mapping was performed on a segregating population of 110 recombinant inbred lines, derived from a cross between the domesticated emmer wheat accession MG5323 and the durum wheat cv. Latino, evaluated in four different environments. A total of 24 QTLs stable across environments were found and further grouped in nine clusters on chromosomes 2A, 2B, 3A, 3B, 4B, 6B, and 7A. Among them, a QTL cluster on chromosome 4B was associated with kernel size traits and TKW, where the parental MG5323 contributed the favorable alleles, highlighting its potential to improve durum wheat germplasm. The physical positions of the clusters, defined by the projection on the T. durum reference genome, overlapped with already known genes (i.e., BIG GRAIN PROTEIN 1 on chromosome 4B). These results might provide genome-based guidance for the efficient exploitation of emmer wheat diversity in wheat breeding, possibly through yield-related molecular markers.

Genome-wide analysis of genetic diversity in a germplasm collection including wild relatives and interspecific clones of garden asparagus

The Asparagus genus includes approximately 240 species, the most important of which is garden asparagus (Asparagus officinalis L.), as this is a vegetable crop cultivated worldwide for its edible spear. Along with garden asparagus, other species are also cultivated (e.g., Asparagus maritimus L.) or have been proposed as untapped sources of variability in breeding programs (e.g., Asparagus acutifolius L.). In the present work, we applied reduced-representation sequencing to examine a panel of 378 diverse asparagus genotypes, including commercial hybrids, interspecific lines, wild relatives of garden asparagus, and doubled haploids currently used in breeding programs, which enabled the identification of more than 200K single-nucleotide polymorphisms (SNPs). These SNPs were used to assess the extent of linkage disequilibrium in the diploid gene pool of asparagus and combined with preliminary phenotypic information to conduct genome-wide association studies for sex and traits tied to spear quality and production. Moreover, using the same phenotypic and genotypic information, we fitted and cross-validated genome-enabled prediction models for the same set of traits. Overall, our analyses demonstrated that, unlike the diversity detected in wild species related to garden asparagus and in interspecific crosses, cultivated and wild genotypes of A. officinalis L. show a narrow genetic basis, which is a contributing factor hampering the genetic improvement of this crop. Estimating the extent of linkage disequilibrium and providing the first example of genome-wide association study and genome-enabled prediction in this species, we concluded that the asparagus panel examined in the present study can lay the foundation for determination of the genetic bases of agronomically important traits and for the implementation of predictive breeding tools to sustain breeding.

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.

Genetic diversity, distribution and domestication history of the neglected GGAtAt genepool of wheat

We present a comprehensive survey of cytogenetic and genomic diversity of the GGA^tA^t genepool of wheat, thereby unlocking these plant genetic resources for wheat improvement. Wheat yields are stagnating around the world and new sources of genes for resistance or tolerances to abiotic traits are required. In this context, the tetraploid wheat wild relatives are among the key candidates for wheat improvement. Despite its potential huge value for wheat breeding, the tetraploid GGA^tA^t genepool is largely neglected. Understanding the population structure, native distribution range, intraspecific variation of the entire tetraploid GGA^tA^t genepool and its domestication history would further its use for wheat improvement. The paper provides the first comprehensive survey of genomic and cytogenetic diversity sampling the full breadth and depth of the tetraploid GGA^tA^t genepool. According to the results obtained, the extant GGA^tA^t genepool consists of three distinct lineages. We provide detailed insights into the cytogenetic composition of GGA^tA^t wheats, revealed group- and population-specific markers and show that chromosomal rearrangements play an important role in intraspecific diversity of T. araraticum. The origin and domestication history of the GGA^tA^t lineages is discussed in the context of state-of-the-art archaeobotanical finds. We shed new light on the complex evolutionary history of the GGA^tA^t wheat genepool and provide the basis for an increased use of the GGA^tA^t wheat genepool for wheat improvement. The findings have implications for our understanding of the origins of agriculture in southwest Asia.

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

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.

Segmental duplications are hot spots of copy number variants affecting barley gene content

Copy number variants (CNVs) are pervasive in several animal and plant genomes and contribute to shaping genetic diversity. In barley, there is evidence that changes in gene copy number underlie important agronomic traits. The recently released reference sequence of barley represents a valuable genomic resource for unveiling the incidence of CNVs that affect gene content and for identifying sequence features associated with CNV formation. Using exome sequencing and read count data, we detected 16 605 deletions and duplications that affect barley gene content by surveying a diverse panel of 172 cultivars, 171 landraces, 22 wild relatives and other 32 uncategorized domesticated accessions. The quest for segmental duplications (SDs) in the reference sequence revealed many low-copy repeats, most of which overlap predicted coding sequences. Statistical analyses revealed that the incidence of CNVs increases significantly in SD-rich regions, indicating that these sequence elements act as hot spots for the formation of CNVs. The present study delivers a comprehensive genome-wide study of CNVs affecting barley gene content and implicates SDs in the molecular mechanisms that lead to the formation of this class of CNVs.

Genome-Wide Analysis of japonica Rice Performance under Limited Water and Permanent Flooding Conditions

A rice GWAS panel of 281 accessions of japonica rice was phenotypically characterized for 26 traits related to phenology, plant and seed morphology, physiology and yield for 2 years in field conditions under permanent flooding (PF) and limited water (LW). A genome-wide analysis uncovered a total of 160 significant marker-trait associations (MTAs), of which 32 were LW-specific, 59 were PF-specific, and 69 were in common between the two water management systems. LW-specific associations were identified for several agronomic traits including days to maturation, days from flowering to maturation, leaf traits, plant height, panicle and seed traits, hundred grain weight, yield and tillering. Significant MTAs were detected across all the 12 rice chromosomes, while clusters of effects influencing different traits under LW or in both watering conditions were, respectively, observed on chromosomes 4, 8, and 12 and on chromosomes 1, 3, 4, 5, and 8. The analysis of genes annotated in the Nipponbare reference sequence and included in the regions associated to traits related to plant morphology, grain yield, and physiological parameters allowed the identification of genes that were demonstrated to affect the respective traits. Among these, three (OsOFP2, Dlf1, OsMADS56) and seven (SUI1, Sd1, OsCOL4, Nal1, OsphyB, GW5, Ehd1) candidate genes were, respectively, identified to co-localize with LW-specific associations and associations in common between the two water treatments. For several LW-specific MTAs, or in common among the two treatments, positional co-localizations with previously identified QTLs for rice adaptation to water shortages were observed, a result that further supports the role of the loci identified in this work in conferring adaptation to LW. The most robust associations identified here could represent suitable targets for genomic selection approaches to improve yield-related traits under LW.

Physical Mapping of Bread Wheat Chromosome 5A: An Integrated Approach

The huge size, redundancy, and highly repetitive nature of the bread wheat [Triticum aestivum (L.)] genome, makes it among the most difficult species to be sequenced. To overcome these limitations, a strategy based on the separation of individual chromosomes or chromosome arms and the subsequent production of physical maps was established within the frame of the International Wheat Genome Sequence Consortium (IWGSC). A total of 95,812 bacterial artificial chromosome (BAC) clones of short-arm chromosome 5A (5AS) and long-arm chromosome 5A (5AL) arm-specific BAC libraries were fingerprinted and assembled into contigs by complementary analytical approaches based on the FingerPrinted Contig (FPC) and Linear Topological Contig (LTC) tools. Combined anchoring approaches based on polymerase chain reaction (PCR) marker screening, microarray, and sequence homology searches applied to several genomic tools (i.e., genetic maps, deletion bin map, neighbor maps, BAC end sequences (BESs), genome zipper, and chromosome survey sequences) allowed the development of a high-quality physical map with an anchored physical coverage of 75% for 5AS and 53% for 5AL with high portions (64 and 48%, respectively) of contigs ordered along the chromosome. In the genome of grasses, Brachypodium [Brachypodium distachyon (L.) Beauv.], rice (Oryza sativa L.), and sorghum [Sorghum bicolor (L.) Moench] homologs of genes on wheat chromosome 5A were separated into syntenic blocks on different chromosomes as a result of translocations and inversions during evolution. The physical map presented represents an essential resource for fine genetic mapping and map-based cloning of agronomically relevant traits and a reference for the 5A sequencing projects.

Molecular diversity, population structure, and linkage disequilibrium in a worldwide collection of tobacco (Nicotiana tabacum L.) germplasm

BACKGROUND

The goals of our study were to assess the phylogeny and the population structure of tobacco accessions representing a wide range of genetic diversity; identify a subset of accessions as a core collection capturing most of the existing genetic diversity; and estimate, in the tobacco core collection, the extent of linkage disequilibrium (LD) in seven genomic regions using simple sequence repeat (SSR) markers. To this end, a collection of accessions were genotyped with SSR markers. Molecular diversity was evaluated and LD was analyzed across seven regions of the genome.

RESULTS

A genotyping database for 312 tobacco accessions was profiled with 49 SSR markers. Principal Coordinate Analysis (PCoA) and Bayesian cluster analysis revealed structuring of the tobacco population with regard to commercial classes and six main clades were identified, which correspond to "Oriental", Flue-Cured", "Burley", "Dark", "Primitive", and "Other" classes. Pairwise kinship was calculated between accessions, and an overall low level of co-ancestry was observed. A set of 89 genotypes was identified that captured the whole genetic diversity detected at the 49 loci. LD was evaluated on these genotypes, using 422 SSR markers mapping on seven linkage groups. LD was estimated as squared correlation of allele frequencies (r2). The pattern of intrachromosomal LD revealed that in tobacco LD extended up to distances as great as 75 cM with r2 > 0.05 or up to 1 cM with r2 > 0.2. The pattern of LD was clearly dependent on the population structure.

CONCLUSIONS

A global population of tobacco is highly structured. Clustering highlights the accessions with the same market class. LD in tobacco extends up to 75 cM and is strongly dependent on the population structure.

Genetic variants of HvCbf14 are statistically associated with frost tolerance in a European germplasm collection of Hordeum vulgare

Two quantitative trait loci (Fr-H1 and Fr-H2) for frost tolerance (FT) have been discovered on the long arm of chromosome 5H in barley. Two tightly linked groups of CBF genes, known to play a key role in the FT regulatory network in A. thaliana, have been found to co- segregate with Fr-H2. Here, we investigate the allelic variations of four barley CBF genes (HvCbf3, HvCbf6, HvCbf9 and HvCbf14) in a panel of European cultivars, landraces and H. spontaneum accessions. In the cultivars a reduction of nucleotide and haplotype diversities in CBFs compared with the landraces and the wild ancestor H. spontaneum, was evident. In particular, in cultivars the loss of HvCbf9 genetic variants was higher compared to other sequences. In order to verify if the pattern of CBF genetic variants correlated with the level of FT, an association procedure was adopted. The pairwise analysis of linkage disequilibrium (LD) among the genetic variants in four CBF genes was computed to evaluate the resolution of the association procedure. The pairwise plotting revealed a low level of LD in cultivated varieties, despite the tight physical linkage of CBF genes analysed. A structured association procedure based on a general liner model was implemented, including the variants in CBFs,of Vrn-H1, and of two reference genes not involved in FT (alpha-Amy1 and Gapdh) and considering the phenotypic data for FT. Association analysis recovered two nucleotide variants of HvCbf14 and one nucleotide variant of Vrn-H1 as statistically associated to FT.