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.

Modern crop breeding is in constant demand for new genetic diversity as part of the arms race with genetic gain. The elite gene pool has limited genetic variation and breeders are trying to introduce novelty from unadapted germplasm, landraces and wild relatives. For polygenic traits, currently available approaches to introgression are not ideal, as there is a demonstrable bias against exotic alleles during selection. Here, we propose a partitioned form of genomic selection, called Origin Specific Genomic Selection (OSGS), where we identify and target selection on favorable exotic alleles. Briefly, within a population derived from a bi-parental cross, we isolate alleles originating from the elite and exotic parents, which then allows us to separate out the predicted marker effects based on the allele origins. We validated the usefulness of OSGS using two nested association mapping (NAM) datasets: barley NAM (elite-exotic) and maize NAM (elite-elite), as well as by computer simulation. Our results suggest that OSGS works well in its goal to increase the contribution of favorable exotic alleles in bi-parental crosses, and it is possible to extend the approach to broader multi-parental populations.

The effects of an allelic substitution at a gene often depend critically on genetic background, i.e., the genotypes at other genes in the genome. During the domestication of maize from its wild ancestor (teosinte), an allelic substitution at teosinte branched (tb1) caused changes in both plant and ear architecture. The effects of tb1 on phenotype were shown to depend on multiple background loci, including one called enhancer of tb1.2 (etb1.2). We mapped etb1.2 to a YABBY class transcription factor (ZmYAB2.1) and showed that the maize alleles of ZmYAB2.1 are either expressed at a lower level than teosinte alleles or disrupted by insertions in the sequences. tb1 and etb1.2 interact epistatically to control the length of internodes within the maize ear, which affects how densely the kernels are packed on the ear. The interaction effect is also observed at the level of gene expression, with tb1 acting as a repressor of ZmYAB2.1 expression. Curiously, ZmYAB2.1 was previously identified as a candidate gene for another domestication trait in maize, nonshattering ears. Consistent with this proposed role, ZmYAB2.1 is expressed in a narrow band of cells in immature ears that appears to represent a vestigial abscission (shattering) zone. Expression in this band of cells may also underlie the effect on internode elongation. The identification of ZmYAB2.1 as a background factor interacting with tb1 is a first step toward a gene-level understanding of how tb1 and the background within which it works evolved in concert during maize domestication.

The appropriate use of molecular genetic approaches to reach impact in plant breeding is not straightforward. Here, we consider theory and realized application and explore key issues that early-career plant molecular genetic researchers especially should consider as they establish their careers, particularly in relation to opportunities in plant breeding that span academia and the private sector. Useful entry points for these researchers are an understanding of the plant breeding cycle and the breeder's equation. Becoming familiar with success and failure factors in the application of molecular genetics to practical plant breeding, including in relation to quantitative genetic principles, is also important. Other framing issues are scenario modeling for choosing between breeding scheme options, how agronomy and plant breeding interrelate, and the needs of future food production systems. We also recommend that early-career plant molecular genetic researchers look at whether pathways have been mapped out for how research will lead to impact at field level, whether stakeholders' perspectives have been accounted for, and whether the effectiveness of molecular genetic versus alternative interventions have been costed. Early-career researchers should also consider if effective systems are in place to monitor the values of molecular interventions and whether the necessary multidisciplinary teams are involved in crop development and deployment. We believe that through building a cadre of well-informed and well-connected early-career plant molecular genetic researchers, transformational change in the applications of molecular genetics to practical plant breeding will be enhanced.

Very little is known about how domestication was constrained by the quantitative genetic architecture of crop progenitors and how quantitative genetic architecture was altered by domestication. Yang et al. [C. J. Yang et al., Proc. Natl. Acad. Sci. U.S.A. 116, 5643–5652 (2019)] drew multiple conclusions about how genetic architecture influenced and was altered by maize domestication based on one sympatric pair of teosinte and maize populations. To test the generality of their conclusions, we assayed the structure of genetic variances, genetic correlations among traits, strength of selection during domestication, and diversity in genetic architecture within teosinte and maize. Our results confirm that additive genetic variance is decreased, while dominance genetic variance is increased, during maize domestication. The genetic correlations are moderately conserved among traits between teosinte and maize, while the genetic variance–covariance matrices (G-matrices) of teosinte and maize are quite different, primarily due to changes in the submatrix for reproductive traits. The inferred long-term selection intensities during domestication were weak, and the neutral hypothesis was rejected for reproductive and environmental response traits, suggesting that they were targets of selection during domestication. The G-matrix of teosinte imposed considerable constraint on selection during the early domestication process, and constraint increased further along the domestication trajectory. Finally, we assayed variation among populations and observed that genetic architecture is generally conserved among populations within teosinte and maize but is radically different between teosinte and maize. While selection drove changes in essentially all traits between teosinte and maize, selection explains little of the difference in domestication traits among populations within teosinte or maize. Significance We investigated the genetic architecture of maize domestication using a quantitative genetics approach. With multiple populations of teosinte and maize, we also compared the genetic architecture among populations within maize and teosinte. We showed that genetic architecture among populations within teosinte or maize is generally conserved, in contrast to the radical differences between teosinte and maize. Our results suggest that while selection drove changes in essentially all traits between teosinte and maize, selection is far less important for explaining domestication trait differences among populations within teosinte or maize.

Recommended List (RL) is the UK plant variety recommendation system introduced in 1944 for supporting growers in making decisions on variety choices. The current RL system is heavily focused on single-trial analyses developed in the 1980s without making full use of information across varieties and trial sites. Given the statistical advances that have been developed and adopted elsewhere, it is timely to review and update the methods for data analysis in RL. In addition, threats from climate change challenge the prediction of variety performance in future environments. Better variety recommendations, particularly for matching varieties to specific environments can be achieved through the improved modeling of effects from genetics, environments, and genetic-by-environment interactions. Here, we evaluate grain yield data from 153 spring barley varieties that were trialed for RL from 2002 to 2019. Our results show that the current RL system produces poor and inconsistent predictions on variety performance across environments. Improvement in RL can be achieved by using mixed models that account for genetic relationships among varieties, and additional improvement is possible if genetic-by-environment interaction can be modeled accurately. We highlight the relevance and importance of genomics in both variety registration and recommendation.