SYLLABUS INTRODUCTION TO PLANT QUANTITATIVE GENETICS Tucson, 8 – 10 Jan. 2018 INSTRUCTORS: Mike Gore, Cornell University, [email protected] Lucia Gutierrez, Department of Agronomy, University of Wisconsin, Madison [email protected] Bruce Walsh, Department of Ecology & Evolutionary Biology, University of Arizona [email protected] References B = Bernardo,Breeding for Quantitative Traits in Plants, 2nd ed. LW = Lynch & Walsh: Genetics and Analysis of Quantitative Traits (book) WL = Walsh & Lynch: Evolution and Selection of Quantitative Traits (website) http://nitro.biosci.arizona.edu/zbook/NewVolume_2/newvol2.html LECTURE SCHEDULE Monday, 8 Jan 8:30 10:00 am 1. Introd to Modern Plant Breeding (Gore, Gutierrez, Walsh) Background reading: B Chapter 1 10:00 10:30 am Break 10:30 12:00 am 2. Basic Genetics (Walsh, Gore) Background reading: LW Chapter 4 12:00 1:30 pm Lunch 1:30 3:00 pm 3. Basic Statistics (Walsh) Background reading: LW Chapters 2, 3 Additional reading: LW Appendix A4 3:00 3:30 pm Break 3:30 5:00 pm 4. Allelic Effects and Genetic Variances (Walsh) Background reading: B Chapters 3, 6 Additional reading: LW Chapters 4, 5 Tuesday, 9 Jan 8:30 10:00 am 5. Resemblance Between Relatives (Walsh) Background reading: B Chapter 6 Additional reading: LW Chapter 7 10:00 10:30 am Break 10:30 12:00 am 6. Heritability and Field Designs (Gutierrez) Background reading: B Chapters 6, 7 Additional reading: LW Chapters 17, 18, 20, 22 Holland, J., W.E. Nyquist, C.T. Cervantes-Martinez. 2010. Estimating and Interpreting Heritability for Plant Breeding: An Update. Plant Breeding Reviews 22: 9-112. 12:00 1:30 pm Lunch 1:30 3:00 pm 7. QTL Mapping (Gutierrez) Background reading: B Chapter 5 Additional reading: LW Chapters 12-15 3:00 3:30 pm Break 3:30 5:00 pm 8. Association Mapping (Gore) Background reading: B Chapter 5.4 Additional reading: LW Chapter 16 Wednesday, 10 Jan 8:30 10:00 am 9. Inbreeding, Heterosis (Gore) Background reading: B Chapter 12 Additional reading: LW Chapter 10, 10:00 10:30 am Break 10:30 12:00 am 10. Mass and Family Selection (Walsh) Background reading: B Chapters 9, 10 Additional reading: WL Chapters 12, 13, 19, 20, 35 ADDITIONAL BOOKS ON QUANTITATIVE GENETICS General Falconer, D. S. and T. F. C. Mackay. Introduction to Quantitative Genetics, 4th Edition Lynch, M. and B. Walsh. 1998. Genetics and Analysis of Quantitative Traits. Sinauer. Mather, K., and J. L. Jinks. 1982. Biometrical Genetics. (3rd Ed.) Chapman & Hall. Plant Breeding Wricke, G., and W. E. Weber. 1986. Quantitative Genetics and Selection in Plant Breeding. De Gruyter. Mayo, O. 1987. The Theory of Plant Breeding. Oxford. Stoskopf, N. C.. D. T. Tomes, and B. R. Christie. 1993. Plant breeding: Theory and practice. Westview, Boulder. Sleper, D. A., and J. M. Poehlman. 2006. Breeding Field Crops. 5th Edition. Blackwell Bernardo, R. 2010. Breeding for Quantitative Traits in Plants, 2nd Ed Stemma Press. Hallauer, A. R., M. J. Carena, and J. B. Miranda Filho. 2010. Quantitative Genetics in Maize Breeding. Iowa State Press. Statistical and Technical Issues Bulmer, M. 1980. The Mathematical Theory of Quantitative Genetics. Clarendon Press. Kempthorne, O. 1969. An Introduction to Genetic Statistics. Iowa State University Press. Sorensen, D., and D. Gianola. 2002. Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics. Springer. Saxton, A. M. (Ed). 2004. Genetic Analysis of Complex Traits Using SAS. SAS Press. Wu, R., C.-X. Ma, and G. Casella. 2007. Statistical Genetics of Quantitative Traits: Linkage, Maps. and QTL. Springer, N.Y Lecture 1 Introduction to Modern Plant Breeding Bruce Walsh Notes Introduction to Plant Quantitative Genetics Tucson. 8-10 Jan 2018 1 Importance of Plant breeding • Plant breeding is the most important technology developed by man. It allowed civilization to form and its continual success is critical to maintaining our way of life • Problem: Feeding 9 billion (+) people with the same (or fewer) inputs – Same or less acreage – Same or less fertilizer, pesticides, water – Adapting to climate and environmental change 2` Goals of Plant breeding • Increase the frequency of favorable alleles within a line – Additive effects • Increase the frequency of favorable genotypes within a line – Dominance and interaction effects • Better adapt crops to specific environments – Region-specific cultivars (high location G x E) – Stability across years within a region (low year-to- year G x E) 3 Objectives • Development of pure (i.e. highly inbred) lines with high per se performance • Development of pure lines with high hybrid performance (either with each other or with a testcross) • Less emphasis on developing outbred (random-mating) populations with improved performance • Development of lines with high regional G x E, low year G x E 4 Animal and tree breeding • Similar goals, but since mostly outcrossing, the goal is to create high-performing populations, not inbred lines • Generally speaking, inbreeding is bad in animals and many trees • Focus on finding those parents with the best transmitting abilities (highest breeding values) • Less of a G x E focus with animals, less of a focus on line and hybrid breeding 5 Special features exploited by plant breeders • Selfing allows for the capture of specific genotypes, and hence the capture of interactions between alleles and loci (dominance and epistasis) – Homozygous for selfed lines – Heterozygous for crossed lines • Often high reproductive output (relative to animal breeding) • Seeds allow for multigeneration progeny testing, wherein individuals are chosen on the performance of their progeny, or of their sibs – Allows for better control over G x E by testing over multiple sites/years 6 Historical plant breeding • Early origins – Creation of new lines through species crosses (allopolyploids) – Visual selection – Early domestication (selection for specific traits for ease of harvesting) • Biometrical school – Using crosses to predict average performance under inbreeding or crossing or response to selection – Better management of G x E 7 Modern tools • Molecular markers – Initially low density for QTL mapping, introgression of major genes into elite germplasm – With high-density markers, association mapping and MAS/ genomic selection • New statistical tools – Mixed model methods – Bayesian approaches to handle high-dimensional data sets – New methods to deal with G x E • Other technologies – Better standardization of field sites (laser-tilled fields, GPS, better micro- and macro-environmental measurements) – High throughput phenotypic scoring – DH lines 8 Diversity • Plant breeders face the conundrum of using inbred lines to concentrate elite genotypes, but requiring a very large collection of such lines to store variation for further selection • Landraces or local cultivars may be highly adapted to specific environments, but otherwise not elite • Issue with keeping germplasm elite while introgressing genes/regions of interest. 9 Integrated Approaches • How do we best combine the rich history of quantitative genetics and classical plant breeding with the new tools from genomics and other advances? • Key: Quantitative genetics has all of the machinery needed to fully incorporate these new sources of information • The goal of this course is to show how this is done. 10 Lecture 2 Basic Plant Genetics Bruce Walsh Notes Introduction to Plant Quantitative Genetics Tucson. 8-10 Jan 2018 1 Overview • Ploidy • Linkage • Linkage disequilibrium (LD) • Genetic markers • Mapping functions • Organelle inheritance • Mating systems and types of crosses • Gene actions – Dominance and Epistasis – Pleiotropy 2 Ploidy • Most animals are diploid (2n), with their gametes (eggs, sperm) containing a haploid set of n chromosomes • Polyploids are much more common in plants. • Allopolyploids consist of haploid sets from two (or more) species – e.g., an allotetraploid is AABB, – One allohexaploid is AABBCC – Generally speaking, allopolyploids largely behave as diploids, i.e., each pollen/egg gets a haploid set from each of the founding species • Autopolyploids have multiple haploid sets from the same species – Autoteraploids (4n) and autohexaploids (6n) – these give pollen and eggs with two (2n) and three (3n) (respectively) copies of each homologous chromosome 3 4 Linkage • Independent assortment for unlinked genes • Linkage • Computing expected genotypic frequencies from linkage 5 Dealing with two (or more) genes For his 7 traits, Mendel observed Independent Assortment The genotype at one locus is independent of the second RR, Rr - round seeds, rr - wrinkled seeds Pure round, green (RRgg) x pure wrinkled yellow (rrYY) F1 --> RrYg = round, yellow What about the F2? 6 Let R- denote RR and Rr. R- are round. Note in F2, Pr(R-) = 1/2 + 1/4 = 3/4 Likewise, Y- are YY or Yg, and are yellow Phenotype Genotype Frequency Yellow, round Y-R- (3/4)*(3/4) = 9/16 Yellow, wrinkled Y-rr (3/4)*(1/4) = 3/16 Green, round ggR- (1/4)*(3/4) = 3/16 Green, wrinkled ggrr (1/4)*(1/4) = 1/16 Or a 9:3:3:1 ratio 7 Mendel was wrong: Linkage Bateson and Punnet looked at flower color: P (purple) dominant over p (red ) pollen shape: L (long) dominant over l (round) Phenotype Genotype Observed Expected Purple long P-L- 284 215 Purple round P-ll 21 71 Red long ppL- 21 71 Red round ppll 55 24 Excess of PL, pl gametes over Pl, pL Departure from independent assortment 8 Linkage If genes are located on different chromosomes they (with very few exceptions) show independent assortment. Indeed, peas have only 7 chromosomes, so was Mendel luckyin choosing seven traits at random that happen to all be on different chromosomes? However, genes on the same chromosome, especially if they are close to each other, tend to be passed onto their offspring in the same configuration as on the parental chromosomes. 9 Consider the Bateson-Punnet pea data Let PL / pl denote that in the parent, one chromosome carries the P and L alleles (at the flower color and pollen shape loci, respectively), while the other chromosome carries the p and l alleles.