Understanding the classics: the unifying concepts of transgressive segregation,inbreeding depression and heterosis and their central relevance for crop breeding

Transgressive segregation and heterosis are the reasons that plant breeding works. Molecular explanations for both phenomena have been suggested and play a contributing role. However, it is often overlooked by molecular genetic researchers that transgressive segregation and heterosis are most simply explained by dispersion of favorable alleles. Therefore, advances in molecular biology will deliver the most impact on plant breeding when integrated with sources of heritable trait variation – and this will be best achieved within a quantitative genetics framework. An example of the power of quantitative approaches is the implementation of genomic selection, which has recently revolutionized animal breeding. Genomic selection is now being applied to both hybrid and inbred crops and is likely to be the major source of improvement in plant breeding practice over the next decade. Breeders’ ability to efficiently apply genomic selection methodologies is due to recent technology advances in genotyping and sequencing. Furthermore, targeted integration of additional molecular data (such as gene expression, gene copy number and methylation status) into genomic prediction models may increase their performance. In this review, we discuss and contextualize a suite of established quantitative genetics themes relating to hybrid vigour, transgressive segregation and their central relevance to plant breeding, with the aim of informing crop researchers outside of the quantitative genetics discipline of their relevance and importance to crop improvement. Better understanding between molecular and quantitative disciplines will increase the potential for further improvements in plant breeding methodologies and so help underpin future food security.     

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm ‘package’ that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.Subject terms: Plant genetics, Plant breeding, Agricultural genetics, Quantitative trait

Over recent years, numerous multi-parent populations (MPPs) have been successfully developed in crops (Huang et al. 2015; Cockram and Mackay 2018). MPPs bring together key genomic, phenotypic and germplasm resources to form a platform for research and development. In this review, we examine three themes covering new developments in crop MPP research: (1) we survey the rapidly expanding variety of crop MPPs, explaining how differences in their design and construction affect their power and precision in mapping quantitative trait loci (QTL), on which we provide a brief primer. (2) We review the use of genomic technologies in MPPs, which have proven particularly suitable for gathering dense genomic information across large populations. We make general recommendations for collecting genotypic resources in MPPs. (3) We discuss successful applications of MPPs, particularly where they have been used for breeding and pre-breeding. This includes the identification of QTL, the application of genomic prediction to MPPs, and the direct use of MPP lines as germplasm for varietal release or pre-breeding. These recent developments have shown the potential of MPPs for crop improvement.     

TGB: the tobacco genetics and breeding database

The germplasm of the genus Nicotiana contains more than 5,000 accessions and plays an important role in modern biological research. Tobacco can be used as a model system to develop methodologies for plant transformation and for investigating gene function. In order to develop the study of Nicotiana, a large quantity of data on germplasm, sequences, molecular markers and genetically modified tobacco was required for in-depth and systematic collation and research. It became necessary to establish a special database for tobacco genetics and breeding. The tobacco genetics and breeding (TGB, http://yancao.sdau.edu.cn/tgb) database was developed with the aim of bringing together tobacco genetics and breeding. The database has three main features: (1) a materials database with information on 1,472 Nicotiana germplasm accessions, as well as updated genomic and expressed sequence tag (EST) data available from the public database; (2) a molecular markers database containing a total of 12,388 potential intron polymorphisms 10,551 EST-simple sequence repeat (EST-SSR) and 66,297 genomic-SSR markers; and (3) an applications database with genetic maps and some genetically modified studies in tobacco. The TGB database also makes Basic Local Alignment Search Tool and primer designing tools publicly available. As far as can be ascertained, the TGB database is the first tobacco genetics and breeding database to be created, and all this comprehensive information will aid basic research into Nicotiana and other related plants. It will serve as an excellent resource for the online tobacco research community.     

Leveraging natural diversity: back through the bottleneck

Plant breeders have long recognized the existence of useful genetic variation in the wild ancestors of our domesticated crop species. In cultivated rice (Oryza sativa), crosses between high-yielding elite cultivars and low-yielding wild accessions often give rise to superior offspring, with wild alleles conferring increased performance in the context of the elite cultivar genetic background. Because the breeding value of wild germplasm cannot be determined by examining the performance of wild accessions, a phylogenetic approach is recommended to determine which interspecific combinations are most likely to be useful in a breeding program. As we deepen our understanding of how genetic diversity is partitioned within and between cultivated and wild gene pools of Oryza, breeders will have increased power to make predictions about the most efficient strategies for utilizing wild germplasm for rice improvement.     

QTL mapping and breeding value estimation through pedigree-based analysis of fruit size and weight in four diverse peach breeding programs

The narrow genetic base of peach (Prunus persica L. Batsch) challenges efforts to accurately dissect the genetic architecture of complex traits. Standardized phenotypic assessment of pedigree-linked breeding germplasm and new molecular strategies and analytical approaches developed and conducted during the RosBREED project for enabling marker-assisted breeding (MAB) in Rosaceae crops has overcome several aspects of this challenge. The genetic underpinnings of fruit size (fruit equatorial diameter (FD)) and weight (fresh weight (FW)), two most important components of yield, were investigated using the pedigree-based analysis (PBA) approach under a Bayesian framework which has emerged as an alternative strategy to study the genetics of quantitative traits within diverse breeding germplasm across breeding programs. In this study, a complex pedigree with the common founder “Orange Cling” was identified and FD and FW data from 2011 and 2012 analyzed. A genetic model including genetic additive and dominance effects was considered, and its robustness was evaluated by using various prior and initial values in the Markov chain Monte Carlo procedure. Five QTLs were identified which accounted for up to 29 and 17 % of the phenotypic variation for FD and FW, respectively. Additionally, genomic breeding values were obtained for both traits, with accuracies >85 %. This approach serves as a model study for performing PBA across diverse pedigrees. By incorporating multiple breeding programs, the method and results presented support and highlight the ability of this strategy to identify genomic resources as targets for DNA marker development and subsequent MAB within each program.     

From mutations to MAGIC: resources for gene discovery, validation and delivery in crop plants

The dissection of gene-trait associations and its translation into practice through plant breeding is a central aspect of modern plant biology. The identification of genes underlying simply inherited traits has been very successful. However, the identification of gene-trait associations for complex (multi-genic) traits in crop plants with large, often polyploid genomes has been limited by the absence of appropriate genetic resources that allow quantitative trait loci (QTL) and causal genes to be identified and localised. There has also been a tendency for genetic resources to be developed in germplasm not directly relevant to the breeding community limiting effective implementation. In this review, we discuss approaches to mapping genes and the development of Multi-parent Advanced Generation Inter-cross (MAGIC) populations derived from breeder-relevant germplasm as a platform for a new generation of gene-trait analysis in crop species.     

Improving salinity tolerance in crop plants: a biotechnological view

Salinity limits the production capabilities of agricultural soils in large areas of the world. Both breeding and screening germplasm for salt tolerance encounter the following limitations: (a) different phenotypic responses of plants at different growth stages, (b) different physiological mechanisms, (c) complicated genotype × environment interactions, and (d) variability of the salt-affected field in its chemical and physical soil composition. Plant molecular and physiological traits provide the bases for efficient germplasm screening procedures through traditional breeding, molecular breeding, and transgenic approaches. However, the quantitative nature of salinity stress tolerance and the problems associated with developing appropriate and replicable testing environments make it difficult to distinguish salt-tolerant lines from sensitive lines. In order to develop more efficient screening procedures for germplasm evaluation and improvement of salt tolerance, implementation of a rapid and reliable screening procedure is essential. Field selection for salinity tolerance is a laborious task; therefore, plant breeders are seeking reliable ways to assess the salt tolerance of plant germplasm. Salt tolerance in several plant species may operate at the cellular level, and glycophytes are believed to have special cellular mechanisms for salt tolerance. Ion exclusion, ion sequestration, osmotic adjustment, macromolecule protection, and membrane transport system adaptation to saline environments are important strategies that may confer salt tolerance to plants. Cell and tissue culture techniques have been used to obtain salt tolerant plants employing two in vitro culture approaches. The first approach is selection of mutant cell lines from cultured cells and plant regeneration from such cells (somaclones). In vitro screening of plant germplasm for salt tolerance is the second approach, and a successful employment of this method in durum wheat is presented here. Doubled haploid lines derived from pollen culture of F₁ hybrids of salt-tolerant parents are promising tools to further improve salt tolerance of plant cultivars. Enhancement of resistance against both hyper-osmotic stress and ion toxicity may also be achieved via molecular breeding of salt-tolerant plants using either molecular markers or genetic engineering.     

Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding: a challenge for plant biotechnological breeding under soil water deficit conditions

In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations, and substantial time needed to develop such populations. To overcome these limitations, and as an alternative to planned populations, molecular marker–trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, the authors (1) survey the successful applications of germplasm–regression–combined (GRC) molecular marker–trait association identification in plants; (2) describe how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; (3) consider the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and (4) finally discuss the future prospects of GRC marker–trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and QTL are available.     

Mapping QTL for agronomic traits in breeding populations

Detection of quantitative trait loci (QTL) in breeding populations offers the advantage that these QTL are of direct relevance for the improvement of crops via knowledge-based breeding. As phenotypic data are routinely generated in breeding programs and the costs for genotyping are constantly decreasing, it is tempting to exploit this information to unravel the genetic architecture underlying important agronomic traits in crops. This review characterizes the germplasm from breeding populations available for QTL detection, provides a classification of the different QTL mapping approaches that are available, and highlights important considerations concerning study design and biometrical models suitable for QTL analysis.     

Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High‐throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis‐related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio‐engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype‐to‐gene identification pipeline.     

Will genomic selection be a practical method for plant breeding?

Background

Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use.

Scope

In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed.

Conclusions

Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.Key words: Genomic selection, plant breeding, marker assisted selection, genetic model, linkage disequilibrium     

Unraveling Additive from Nonadditive Effects Using Genomic Relationship Matrices

The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies.     

Family-based mapping of quantitative trait loci in plant breeding populations with resistance to Fusarium head blight in wheat as an illustration

Traditional quantitative trait loci (QTL) mapping approaches are typically based on early or advanced generation analysis of bi-parental populations. A limitation associated with this methodology is the fact that mapping populations rarely give rise to new cultivars. Additionally, markers linked to the QTL of interest are often not immediately available for use in breeding and they may not be useful within diverse genetic backgrounds. Use of breeding populations for simultaneous QTL mapping, marker validation, marker assisted selection (MAS), and cultivar release has recently caught the attention of plant breeders to circumvent the weaknesses of conventional QTL mapping. The first objective of this study was to test the feasibility of using family-pedigree based QTL mapping techniques generally used with humans and animals within plant breeding populations (PBPs). The second objective was to evaluate two methods (linkage and association) to detect marker-QTL associations. The techniques described in this study were applied to map the well characterized QTL, Fhb1 for Fusarium head blight resistance in wheat (Triticum aestivum L.). The experimental populations consisted of 82 families and 793 individuals. The QTL was mapped using both linkage (variance component and pedigree-wide regression) and association (using quantitative transmission disequilibrium test, QTDT) approaches developed for extended family-pedigrees. Each approach successfully identified the known QTL location with a high probability value. Markers linked to the QTL explained 40–50% of the phenotypic variation. These results show the usefulness of a human genetics approach to detect QTL in PBPs and subsequent use in MAS.     

What is genetic quality?

Mate choice is favored by indirect selection if choosy females mate with males of high genetic quality. We believe, however, that testing hypotheses about indirect selection has been constrained by how we conceptualize and therefore empirically measure male genetic quality. Here, we argue that genetic quality is the breeding value of an individual for total fitness. We can therefore learn little about genetic quality from measures of only a few fitness components. We explain breeding value for total fitness, drawing on concepts from life-history theory and quantitative genetics, and suggest how approaches incorporating these insights might result in empirical progress.