Quantitative trait locus mapping identifies candidate alleles involved in adaptive introgression and range expansion in a wild sunflower.

The wild North American sunflowers Helianthus annuus and H. debilis are participants in one of the earliest identified examples of adaptive trait introgression, and the exchange is hypothesized to have triggered a range expansion in H. annuus. However, the genetic basis of the adaptive exchange has not been examined. Here, we combine quantitative trait locus (QTL) mapping with field measurements of fitness to identify candidate H. debilis QTL alleles likely to have introgressed into H. annuus to form the natural hybrid lineage H. a. texanus. Two 500-individual BC1 mapping populations were grown in central Texas, genotyped for 384 single nucleotide polymorphism (SNP) markers and then phenotyped in the field for two fitness and 22 herbivore resistance, ecophysiological, phenological and architectural traits. We identified a total of 110 QTL, including at least one QTL for 22 of the 24 traits. Over 75% of traits exhibited at least one H. debilis QTL allele that would shift the trait in the direction of the wild hybrid H. a. texanus. We identified three chromosomal regions where H. debilis alleles increased both female and male components of fitness; these regions are expected to be strongly favoured in the wild. QTL for a number of other ecophysiological, phenological and architectural traits colocalized with these three regions and are candidates for the actual traits driving adaptive shifts. G × E interactions played a modest role, with 17% of the QTL showing potentially divergent phenotypic effects between the two field sites. The candidate adaptive chromosomal regions identified here serve as explicit hypotheses for how the genetic architecture of the hybrid lineage came into existence.

New insights into trait introgression with the look-ahead intercrossing strategy.

Trait introgression (TI) can be a time-consuming and costly task that typically requires multiple generations of backcrossing (BC). Usually, the aim is to introduce one or more alleles (e.g. QTLs) from a single donor into an elite recipient, both of which are fully inbred. This article studies the potential advantages of incorporating intercrossing (IC) into TI programs when compared with relying solely on the traditional BC framework. We simulate a TI breeding pipeline using 3 previously proposed selection strategies for the traditional BC scheme and 3 modified strategies that allow IC. Our proposed look-ahead intercrossing method (LAS-IC) combines look-ahead Monte Carlo simulations, intercrossing, and additional selection criteria to improve computational efficiency. We compared the efficiency of the 6 strategies across 5 levels of resource availability considering the generation when the major QTLs have been successfully introduced into the recipient and a desired background recovery rate reached. Simulations demonstrate that the inclusion of intercrossing in a TI program can substantially increase efficiency and the probability of success. The proposed LAS-IC provides the highest probability of success across the different scenarios using fewer resources compared with BC-only strategies.

Engineering drought and salinity tolerance traits in crops through CRISPR-mediated genome editing: Targets, tools, challenges, and perspectives.

Prolonged periods of drought triggered by climate change hamper plant growth and cause substantial agricultural yield losses every year. In addition to drought, salinity is one of the major abiotic stresses that severely affect crop health and agricultural production. Plant responses to drought and salinity involve multiple processes that operate in a spatiotemporal manner, such as stress sensing, perception, epigenetic modifications, transcription, post-transcriptional processing, translation, and post-translational changes. Consequently, drought and salinity stress tolerance are polygenic traits influenced by genome-environment interactions. One of the ideal solutions to these challenges is the development of high-yielding crop varieties with enhanced stress tolerance, together with improved agricultural practices. Recently, genome-editing technologies, especially clustered regularly interspaced short palindromic repeats (CRISPR) tools, have been effectively applied to elucidate how plants deal with drought and saline environments. In this work, we aim to portray that the combined use of CRISPR-based genome engineering tools and modern genomic-assisted breeding approaches are gaining momentum in identifying genetic determinants of complex traits for crop improvement. This review provides a synopsis of plant responses to drought and salinity stresses at the morphological, physiological, and molecular levels. We also highlight recent advances in CRISPR-based tools and their use in understanding the multi-level nature of plant adaptations to drought and salinity stress. Integrating CRISPR tools with modern breeding approaches is ideal for identifying genetic factors that regulate plant stress-response pathways and for the introgression of beneficial traits to develop stress-resilient crops.

Dynamic Programming for Resource Allocation in Multi-Allelic Trait Introgression.

Trait introgression is a complex process that plant breeders use to introduce desirable alleles from one variety or species to another. Two of the major types of decisions that must be made during this sophisticated and uncertain workflow are: parental selection and resource allocation. We formulated the trait introgression problem as an engineering process and proposed a Markov Decision Processes (MDP) model to optimize the resource allocation procedure. The efficiency of the MDP model was compared with static resource allocation strategies and their trade-offs among budget, deadline, and probability of success are demonstrated. Simulation results suggest that dynamic resource allocation strategies from the MDP model significantly improve the efficiency of the trait introgression by allocating the right amount of resources according to the genetic outcome of previous generations.

Quantitative Trait Locus Mapping of Resistance to Turnip Yellows Virus in Brassica rapa and Brassica oleracea and Introgression of These Resistances by Resynthesis Into Allotetraploid Plants for Deployment in Brassica napus.

Turnip yellows virus (TuYV) is aphid-transmitted and causes considerable yield losses in oilseed rape (OSR, Brassica napus, genome: AACC) and vegetable brassicas. Insecticide control of the aphid vector is limited due to insecticide resistance and the banning of the most effective active ingredients in the EU. There is only one source of TuYV resistance in current commercial OSR varieties, which has been mapped to a single dominant quantitative trait locus (QTL) on chromosome A04. We report the identification, characterisation, and mapping of TuYV resistance in the diploid progenitor species of OSR, Brassica rapa (genome: AA), and Brassica oleracea (genome: CC). Phenotyping of F1 populations, produced from within-species crosses between resistant and susceptible individuals, revealed the resistances were quantitative and partially dominant. QTL mapping of segregating backcross populations showed that the B. rapa resistance was controlled by at least two additive QTLs, one on chromosome A02 and the other on chromosome A06. Together, they explained 40.3% of the phenotypic variation. In B. oleracea, a single QTL on chromosome C05 explained 22.1% of the phenotypic variation. The TuYV resistance QTLs detected in this study are different from those in the extant commercial resistant varieties. To exploit these resistances, an allotetraploid (genome: AACC) plant line was resynthesised from the interspecific cross between the TuYV-resistant B. rapa and B. oleracea lines. Flow cytometry confirmed that plantlets regenerated from the interspecific cross had both A and C genomes and were mixoploid. To stabilise ploidy, a fertile plantlet was self-pollinated to produce seed that had the desired resynthesised, allotetraploid genome AACC. Phenotyping of the resynthesised plants confirmed their resistance to TuYV. Genotyping with resistance-linked markers identified during the mapping in the progenitors confirmed the presence of all TuYV resistance QTLs from B. rapa and B. oleracea. This is the first report of TuYV resistance mapped in the Brassica C genome and of an allotetraploid AACC line possessing dual resistance to TuYV originating from both of its progenitors. The introgression into OSR can now be accelerated, utilising marker-assisted selection, and this may reduce selection pressure for TuYV isolates that are able to overcome existing sources of resistance to TuYV.

The Predicted Cross Value for Genetic Introgression of Multiple Alleles.

We consider the plant genetic improvement challenge of introgressing multiple alleles from a homozygous donor to a recipient. First, we frame the project as an algorithmic process that can be mathematically formulated. We then introduce a novel metric for selecting breeding parents that we refer to as the predicted cross value (PCV). Unlike estimated breeding values, which represent predictions of general combining ability, the PCV predicts specific combining ability. The PCV takes estimates of recombination frequencies as an input vector and calculates the probability that a pair of parents will produce a gamete with desirable alleles at all specified loci. We compared the PCV approach with existing estimated-breeding-value approaches in two simulation experiments, in which 7 and 20 desirable alleles were to be introgressed from a donor line into a recipient line. Results suggest that the PCV is more efficient and effective for multi-allelic trait introgression. We also discuss how operations research can be used for other crop genetic improvement projects and suggest several future research directions.