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.

Summary: 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.

Background: Selection has dramatically shaped genetic and phenotypic variation in bread wheat. We can assess the genomic basis of historical phenotypic changes, and the potential for future improvement, using experimental populations that attempt to undo selection through the randomizing effects of recombination. Results: We bred the NIAB Diverse MAGIC multi-parent population comprising over 500 recombinant inbred lines, descended from sixteen historical UK bread wheat varieties released between 1935 and 2004. We sequence the founders’ genes and promoters by capture, and the MAGIC population by low-coverage whole-genome sequencing. We impute 1.1 M high-quality SNPs that are over 99% concordant with array genotypes. Imputation accuracy only marginally improves when including the founders’ genomes as a haplotype reference panel. Despite capturing 73% of global wheat genetic polymorphism, 83% of genes cluster into no more than three haplotypes. We phenotype 47 agronomic traits over 2 years and map 136 genome-wide significant associations, concentrated at 42 genetic loci with large and often pleiotropic effects. Around half of these overlap known quantitative trait loci. Most traits exhibit extensive polygenicity, as revealed by multi-locus shrinkage modelling. Conclusions: Our results are consistent with a gene pool of low haplotypic diversity, containing few novel loci of large effect. Most past, and projected future, phenotypic changes arising from existing variation involve fine-scale shuffling of a few haplotypes to recombine dozens of polygenic alleles of small effect. Moreover, extensive pleiotropy means selection on one trait will have unintended consequences, exemplified by the negative trade-off between yield and protein content, unless selection and recombination can break unfavorable trait-trait associations.

Distinctness, Uniformity and Stability (DUS) is an intellectual property system introduced in 1961 by the International Union for the Protection of New Varieties of Plants (UPOV) for safeguarding the investment and rewarding innovation in developing new plant varieties. Despite the rapid advancement in our understanding of crop biology over the past 60 years, the DUS system has changed little and is still largely dependent upon a set of morphological traits for testing candidate varieties. As the demand for more plant varieties increases, the barriers to registration of new varieties become more acute and thus require urgent review to the system. To highlight the challenges and remedies in the current system, we evaluated a comprehensive panel of 805 UK barley varieties that span the entire history of DUS testing. Our findings reveal the system deficiencies such as inconsistencies in DUS traits across environments, limitations in DUS trait combinatorial space, and inadequacies in currently available DUS markers. We advocate the concept of genomic DUS and provide evidence for a shift towards a robust genomics-enabled registration system for new crop varieties.

Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome‐wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R²≥ .5 with the same QTL. Genome‐wide association studies identified marker‐trait associations for all four traits. For HFN (h² = .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h² = 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h² = 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement.

Two indica inbred rice lines, IR64, a drought-sensitive, and Apo, a moderately drought-tolerant genotype, were exposed to non- (control or unstressed) and water-stress treatments. Leaf samples collected at an early flowering stage were sequenced by RNA-seq. Reads generated were analyzed for differential expression (DE) implementing various models in baySeq to capture differences in genome-wide transcriptional response under contrasting water regimes. IR64, the drought-sensitive variety consistently exhibited a broader transcriptional response while Apo showed relatively modest transcriptional changes under water-stress conditions across all models implemented. Gene ontology (GO) and KEGG pathway analyses of genes revealed that IR64 showed enhancement of functions associated with signal transduction, protein binding and receptor activity. Apo uniquely showed significant enrichment of genes associated with an oxygen binding function and peroxisome pathway. In general, IR64 exhibited more extensive molecular re-programming, presumably, a highly energy-demanding route to deal with the abiotic stress. Several of these differentially expressed genes (DEGs) were found to co-localize with QTL marker regions previously identified to be associated with drought-yield response, thus, are the most promising candidate genes for further studies.