Mapping Complex Agronomic Traits in Autotetraploid Potato

The world is facing an unprecedented challenge to provide a sustainable food supply, caused by a rapid population increase and shrinkage of land for growing traditional food crops such as wheat, rice etc., largely due to urbanization and climate change. The FAO has ranked potato as the world's third most important food crop based on its high yield, nutritional value and less stringent requirements for irrigation and arable land to grow compared with many crops. However, there is an urgent need for the development of new varieties with genetically improved agronomic performance, particularly adaptability to harsh cultivation environments such as low rainfall and temperature, resistance to disease, and high tuber yield and quality. A major challenge is posed by the polyploid nature of the potato genome. Polyploid organisms have multiple sets of chromosomes per cell. When polyploid cells divide, they show much more complicated chromosome pairing behaviour compared to diploid cells with two sets of chromosomes, creating a wider range of outcomes for recombination (gene shuffling) and gene segregation (partitioning). Polyploidy has played a key role in the evolution of plants and animals, particularly flowering plants, many of which are currently polyploid, while the rest have experienced polyploidy in their evolutionary history. Potato is an autotetraploid with four copies of the same genome and shows tetrasomic inheritance, a characteristic shared by many other important crops including leek, sugarcane, alfalfa and some economically important aquaculture species, including Atlantic salmon and trout.

To develop new potato varieties with genetically improved performance requires knowledge of the number and location of genes that affect the target traits. Most observable traits in nature are quantitative or complex, including key agronomic traits, such as yield and resistance to disease, as well as most traits relevant to health and disease, in humans and other animals. Therefore understanding how phenotypic variation in quantitative traits is genetically controlled provides an essential and rational basis for plant breeding. Discovery of abundant DNA sequence variants in the genome of most species provides a source of information for locating genes that underlie quantitative trait phenotypes, the so called mapping of Quantitative Trait Loci (QTL). QTL mapping provides estimates of genome locations, the number and effects of the genes controlling a quantitative trait. Theory and methods for QTL mapping have been well established and QTL mapping is routinely practiced in diploid species. However, the same type of study lags far behind in autotetraploid species, primarily due to the lack of appropriate methods for these analyses. Since inheritance in autotetraploids differs markedly from that in diploids, it is inappropriate to use the methods developed for diploids to conduct the same analysis in autotetraploids.

This project will deliver the scientific basis and novel analytical tools for DNA-marker assisted mapping of QTL and other quantitative genetic analyses in autotetraploid species. The methods to be developed will take proper account of the essential yet complex features of autotetraploid inheritance. We will carry out experiments to sequence an outbred segregating population of cultivated potato for evenly distributed DNA sequence variants in the potato genome. The sequence data will be integrated with phenotype data of several agronomically important quantitative traits from the same population to enable mapping of QTL for these traits using the analytical methods to be developed. This will provide the first example of QTL mapping practice on a rigorous tetrasomic basis. Accomplishment of this project will open unprecedented opportunities for basic genetics and genomics research in autotetraploid species, and facilitate genetic breeding for elite autotetraploid crop cultivars and aquaculture animal varieties.

Dissecting the genetic variation of quantitative traits into chromosomal regions (Quantitative Trait Loci, QTL) is an effective first step for unveiling the molecular architecture governing quantitative genetic variation and the mechanisms maintaining such variation in nature. In one of many potential applications, QTL mapping provides breeders with map information of agronomic quantitative traits for performing marker assisted selection and thereby significantly enhancing breeding efficiency. Theory and methods for QTL mapping have been well established for diploid species and QTL mapping is now routinely practised in almost all diploid species, including plants, animals, and humans. However, the same kind of study is rare, if not non-existent, in autotetraploid species, primarily due to the lack of appropriate methods for conducting the relevant quantitative genetic analyses. Although efforts have recently been made to develop such methods, none of them can be used to model and analyse data from QTL mapping experiments with autotetraploid species on a rigorous scientific basis.

In the proposed project, we will develop novel theoretical models on a strict tetrasomic basis and statistically appropriate methods for marker assisted mapping of QTL in outbred segregating populations of autotetraploid species. These methods will take full account of all essential features of tetrasomic inheritance in gene segregation and recombination. We will apply these methods to map the genetic basis of a series of 29 agronomic traits, including flowering time, tuber yield and quality etc., in a potato segregating population. The population consists of 351 individuals created by crossing two autotetraploid cultivars divergent for a series of agronomic and morphological quantitative traits. We will carry out optimized RAD-sequencing in this population to identify genome-wide genetic markers and integrate this data with phenotype data we have collected for QTL mapping analysis.

To feed the rapidly expanding human population, we are currently facing a serious need to boost agricultural production. This challenge urges the development of a multifaceted approach to developing new crop varieties with enhanced characteristics. Genetic modification will undoubtedly have its role to play, but for the most part, this will depend on traditional, genomically informed plant breeding. To develop new cultivars with enhanced performance for complex agronomic traits such as yield or disease resistance requires knowledge of the number of genes affecting the trait, their actions and interactions, and their genome locations.

Our work will benefit geneticists and breeders by delivering new methods and analytical tools to enable the genes underlying complex quantitative traits (QTL) to be appropriately dissected in autotetraploid species. This group includes many of the most important crops including cultivated potato, the world's third most important food crop, leek, sugarcane, alfalfa and some economically important aquaculture species, including Atlantic salmon and trout. Application of these new methods and tools will facilitate the marker assisted selection of agronomic traits in such species, thereby improving the efficiency of breeding for elite autotetraploid varieties. It also opens unprecedented opportunities for basic genetics and genomics research in autotetraploid species. This project is therefore perfectly aligned to the first BBSRC strategic priority of agriculture and food security.

The global food security challenge is further intensified by climate change and urbanization. For example, yields of our most important food crops decline seriously because of climate driven shrinkage of their cultivation area. There is therefore an urgent need to develop a new generation of crops tolerant of diverse biotic and abiotic stresses. Potato may be grown with less stringent requirements for environmental conditions than other food crops such as rice or wheat, and thus it is an increasingly important crop for coping with climate change. The experimental data, materials and analytical methods to be generated in this project will contribute an informative guide for crop, particularly potato, breeding. This makes a valuable contribution to the BBSRC strategic priority of "generating crops adapted to the challenges of future environments."

The proposed work will help to fulfill the BBSRC aim of providing skilled researchers for academic research in quantitative biology, specifically statistical genetics, by generating an opportunity for PhD projects and training the RA with both experimental skills (e.g. NGS) and analytical skills for handling sophisticated biological datasets. Skills in computer programming and algorithm development are becoming increasingly important in bioscience, which has experienced huge increases in the scale of data produced in genome projects. These skills will therefore provide a solid basis for future research success in almost any field of modern biology. Moreover, support to the project will benefit the UK scientists' international leading role in the field of autotetraploid genetics and genomics, and thus contribute to the wider economy and to society.

We will continue our active involvement with the potato industry and breeding institutes, including PepsiCo (USA) and the Qinghai Academy of Agricultural and Forestry Sciences (China). We are also committed to reaching the wider community of plant breeders and businesses, e.g. through various outreach activities at NIAB Innovation Farm. We will also incorporate our work into teaching of the Masters courses (e.g. MSc Molecular Biotechnology) at the University of Birmingham, to attract the interest of UK and overseas students. The public will also be engaged through various activities, including science days at the Birmingham "Think Tank" museum.