DNA markers have enormous potential to improve the efficiency and precision of conventional plant breeding via marker-assisted selection (MAS). The large number of quantitative trait loci (QTLs) mapping studies for diverse crops species have provided an abundance of DNA marker-trait associations. In this review, we present an overview of the advantages of MAS and its most widely used applications in plant breeding, providing examples from cereal crops. We also consider reasons why MAS has had only a small impact on plant breeding so far and suggest ways in which the potential of MAS can be realized. Finally, we discuss reasons why the greater adoption of MAS in the future is inevitable, although the extent of its use will depend on available resources, especially for orphan crops, and may be delayed in less-developed countries. Achieving a substantial impact on crop improvement by MAS represents the great challenge for agricultural scientists in the next few decades.

Recognizing the enormous potential of DNA markers in plant breeding, many agricultural research centers and plant breeding institutes have adopted the capacity for marker development and marker-assisted selection (MAS). However, due to rapid developments in marker technology, statistical methodology for identifying quantitative trait loci (QTLs) and the jargon used by molecular biologists, the utility of DNA markers in plant breeding may not be clearly understood by non-molecular biologists. This review provides an introduction to DNA markers and the concept of polymorphism, linkage analysis and map construction, the principles of QTL analysis and how markers may be applied in breeding programs using MAS. This review has been specifically written for readers who have only a basic knowledge of molecular biology and/or plant genetics. Its format is therefore ideal for conventional plant breeders, physiologists, pathologists, other plant scientists and students.

Random amplified polymorphic DNA (RAPD) markers have been used for numerous applications in plant molecular genetics research despite having disadvantages of poor reproducibility and not generally being associated with gene regions. A novel method for generating plant DNA markers was developed based on the short conserved region flanking the ATG start codon in plant genes. This method uses single 18-mer primers in single primer polymerase chain reaction (PCR) and an annealing temperature of 50°C. PCR amplicons are resolved using standard agarose gel electrophoresis. This method was validated in rice using a genetically diverse set of genotypes and a backcross population. Reproducibility was evaluated by using duplicate samples and conducting PCR on different days. Start codon targeted (SCoT) markers were generally reproducible but exceptions indicated that primer length and annealing temperature are not the sole factors determining reproducibility. SCoT marker PCR amplification profiles indicated dominant marker like RAPD markers. We propose that this method could be used in conjunction with these markers for applications such as genetic analysis, bulked segregant analysis, and quantitative trait loci mapping, especially in laboratories with a preference for agarose gel electrophoresis.

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Submergence stress regularly affects 15 million hectares or more of rainfed lowland rice areas in South and Southeast Asia. A major QTL on chromosome 9, Sub1, has provided the opportunity to apply marker assisted backcrossing (MAB) to develop submergence tolerant versions of rice cultivars that are widely grown in the region. In the present study, molecular markers that were tightly linked with Sub1, flanking Sub1, and unlinked to Sub1 were used to apply foreground, recombinant, and background selection, respectively, in backcrosses between a submergence-tolerant donor and the widely grown recurrent parent Swarna. By the BC(2)F(2) generation a submergence tolerant plant was identified that possessed Swarna type simple sequence repeat (SSR) alleles on all fragments analyzed except the tip segment of rice chromosome 9 that possessed the Sub1 locus. A BC(3)F(2) double recombinant plant was identified that was homozygous for all Swarna type alleles except for an approximately 2.3-3.4 Mb region surrounding the Sub1 locus. The results showed that the mega variety Swarna could be efficiently converted to a submergence tolerant variety in three backcross generations, involving a time of two to three years. Polymorphic markers for foreground and recombinant selection were identified for four other mega varieties to develop a wider range of submergence tolerant varieties to meet the needs of farmers in the flood-prone regions. This approach demonstrates the effective use of marker assisted selection for a major QTL in a molecular breeding program.

To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable to keep pace with demand. Genomic selection (GS) is a new technique that helps accelerate the rate of genetic gain in breeding by using whole-genome data to predict the breeding value of offspring. Here, we describe a new GS model that combines RR-BLUP with markers fit as fixed effects selected from the results of a genome-wide-association study (GWAS) on the RR-BLUP training data. We term this model GS + de novo GWAS. In a breeding population of tropical rice, GS + de novo GWAS outperformed six other models for a variety of traits and in multiple environments. On the basis of these results, we propose an extended, two-part breeding design that can be used to efficiently integrate novel variation into elite breeding populations, thus expanding genetic diversity and enhancing the potential for sustainable productivity gains.

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.

HighlightsA shift in breeding mentality is needed to realise improved varieties’ potential to increase food security.Information on markets, environment and climate, pre-breeding research and effective dissemination methods are needed too.Rapid generation advance has the highest adoption potential of all the accelerated breeding methods in the public sector.Foregone benefits from earlier adoption could have mitigated the long-term negative impact of hunger on human development.Postponing accelerated breeding technologies makes no economic sense and immediate adoption is economically optimal.