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Deleterious Alleles in maize, talk from PAGXXII

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Talk on deleterious alleles in maize. From PAGXXII

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Deleterious Alleles in maize, talk from PAGXXII

  1. 1. Deleterious Alleles in Maize Jeffrey Ross-Ibarra www.rilab.org @jrossibarra rossibarra January 11, 2014
  2. 2. Many new mutations, most deleterious ≈90 mutations per meiosis1 Maize HapMap2 : new mutations of large effect: 2Ne s > 100 1 2 Clark et al. 2005 MBE, Jiao et al. 2012 Nature Genetics Hufford et al. 2012 Nat. Genetics, Stoletzki & Eyre-Walker 2011 MBE
  3. 3. Many new mutations, most deleterious Nongenic Genic 15000 3000 10000 2000 maize teo 5000 Taxa count count Taxa maize teo 1000 0 0 −2 0 Tajima's D 2 4 −2 0 2 Tajima's D ≈90 mutations per meiosis1 Maize HapMap2 : new mutations of large effect: 2Ne s > 100 Purifying selection retards recovery of diversity in genic regions 1 2 Clark et al. 2005 MBE, Jiao et al. 2012 Nature Genetics Hufford et al. 2012 Nat. Genetics, Stoletzki & Eyre-Walker 2011 MBE
  4. 4. Inbreeding depression and segregating deleterious variants Likely cause of inbreeding depression in Zea3 Purging: fewer, lower frequency premature stops in maize4 ≈8% filtered genes ≥ 1 premature stop codon segregating Exponential growth since domestication increases number of weakly deleterious mutations 3 4 Jones 1924 Genetics; Hufford & Gepts Unpublished Chia et al. 2012 Nature Genetics
  5. 5. Residual heterozygosity suggests complementation Residual heterozygosity in RILs correlates negatively with recombination5,6 5 6 Gore et al. 2009 Science McMullen et al. 2009 Science
  6. 6. Residual heterozygosity suggests complementation 5 6 Gore et al. 2009 Science McMullen et al. 2009 Science
  7. 7. Deleterious alleles in the 282 association panel Explore patterns of deleterious alleles and associations with agronomic phenotypes (heterosis)7 GBS data8 for 282 inbreds Inbred and hybrid yield data9 from crosses to B73 and Mo17 A priori identify putatively deleterious alleles10 7 Mezmouk & Ross-Ibarra 2014 G3 Romay et al. 2013 Genome Biology 9 Flint-Garcia et al. 2009 PLoS ONE 10 Ng & Henikoff 2003 Nucl. Acids Res., Stone & Sidow 2005 Gen. Res. 8
  8. 8. Deleterious alleles in the 282 association panel Explore patterns of deleterious alleles and associations with agronomic phenotypes (heterosis)7 GBS data8 for 282 inbreds Inbred and hybrid yield data9 from crosses to B73 and Mo17 A priori identify putatively deleterious alleles10 Physicochemical properties of amino acids Amino acid conservation across plant genomes 7 Mezmouk & Ross-Ibarra 2014 G3 Romay et al. 2013 Genome Biology 9 Flint-Garcia et al. 2009 PLoS ONE 10 Ng & Henikoff 2003 Nucl. Acids Res., Stone & Sidow 2005 Gen. Res. 8
  9. 9. Deleterious alleles at lower frequencies
  10. 10. Constraint, not positive selection patterns deleterious SNPs 0.5 0.4 del KN KS 0.3 Deleterious None 0.2 0.1 NotC C 0.0 Not selected: 4% at high freq, 9% significant PHS11 No hitchhiking: <3% of these are in domestication features12 Genes with deleterious SNPs have higher mean 11 12 Toomajian et al. 2006 PLoS Biology Hufford et al. 2012 Nature Genetics KN KS
  11. 11. Deleterious alleles not correlated with recombination No relationship of abundance or frequency with recombination Low recombination is effective over long time scales13 13 Haddrill et al. 2007 Genome Biology
  12. 12. Low FST and few fixed deleterious variants among groups
  13. 13. Deleterious allele frequencies consistent with BPH BPH increases with distance from B73 tester Significant BPH even among stiff-stalk lines
  14. 14. GWA hits enriched for genes with deleterious alleles No enrichment for individual deleterious SNPs (too rare) All traits show enrichment at the gene level No gene enrichment for synonymous SNPs
  15. 15. Higher % VA and more causal SNPs under growth Number of causal variants A 250 ● ● ● 200 150 ● ● ● ● ● 100 ● 50 BN BN+growth Old growth Number of causal variants B 250 200 Exponential growth leads to more rare causal variants14 , and these explain a larger proportion of VA ● ● ● ● ● 150 ● ● ● ● ● 100 ● 50 14 Lohmueller 2013 arXivOld growth BN BN+growth
  16. 16. Allele frequency change in Iowa RRS Significant increase in yield over time15 15 16 Rouse, Hinze, Lamkey, Unpublished Gerke, Edwards, Guill, Ross-Ibarra, McMullen In Review
  17. 17. Allele frequency change in Iowa RRS Significant increase in yield over time15 Allele frequency change over time using 55K16 15 16 Rouse, Hinze, Lamkey, Unpublished Gerke, Edwards, Guill, Ross-Ibarra, McMullen In Review
  18. 18. No overlap in selected haplotypes: complementation
  19. 19. No overlap in selected haplotypes: complementation
  20. 20. Consistent with QTL for heterosis QTL for heterosis enriched in centromeric regions17 17 Lari`pe et al. 2012 Genetics e
  21. 21. Consistent with change in inbred and hybrid yield? GENETIC PROGRESS IN YIELD OF U.S. MAIZE 199 om 98 SSR loci distributed cal series of widely grown s of change in allele frer of alleles per group is t al. (2004a). Copyright © material is used by permis- FIGURE 7 - Yields of single crosses (SX) and their inbred parent Selection means (MP), and heterosis as SX – MP.regions pedigrees are inbreds? in high recombination Single-cross improve based on heterotic inbred combinations in the Era hybrids during Haplotype blocks in1930s through 1980s, 12 inbreds maintain heterosis?18 the six decades, low recombination and six single 18 crosses per decade. Means of trials grown in three locations in 1992 and two locations in 1993 at three densities (30, 54, and 79 thousand plants/ha) with one replication per density. From DUVICK et al. (2004b). Copyright © 2004 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc. Duvick 205 Advances in Agronomy
  22. 22. Conclusions Deleterious mutations common in maize. Large effect mutations likely removed by inbreeding. Weak-intermediate effect mutations abundant, but low frequency Deleterious mutations enriched in GWAS for heterosis Simple complementation consistent with patterns of evolution in Iowa RRS, QTL for heterosis, and perhaps inbred and hybrid yield trends
  23. 23. Acknowledgements People Sofiane Mezmouk Justin Gerke UC Davis U. Missouri Funding Jode Edwards (Iowa State) Mike McMullen (U. Missouri)

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