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Peter Morrell Ag Experimental Station Talk 2018

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Plant evolutionary genetics research in the Morrell Lab at the University of Minnesota

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Peter Morrell Ag Experimental Station Talk 2018

  1. 1. MAES Talk 2018 Peter L. Morrell Department of Agronomy & Plant Genetics https://morrelllab.github.io https://github.com/MorrellLab https://github.com/pmorrell
  2. 2. People Li Lei - Postdoc Fernanda Rodriguez - Postdoc Chaochih Liu - Grad Student Undergraduate students Abby Proulx Connor Depies Corey Carter Emily Vonderharr Erica Sun Malik Samuel Paul Hoffman Skylar Wyant
  3. 3. Alumni Ana Gonzales - Grad student Colin Pierce - Grad student Thomas Kono - Grad student Zhou Fang - Grad student Paul Hoffman - Research Associate
  4. 4. Objective 1 Assess the impact of deleterious variants on crop improvement and the potential of culling deleterious variants as a path to crop yield improvement 7 papers 146 exomes 17 genomes
  5. 5. Objective 2 Use environmental association to identify genetic variants contributing to adaptive phenotypes in crop plants Environmental association in barley landraces: identifying the genetic basis of low temperature and drought tolerance. Lei L, Poets AM, Liu C, Wyant SR, Hoffman PJ, Carter CK et al. (in preparation) 3 papers
  6. 6. Objective 3 Assess admixture-based approaches as a means of identifying loci underlying crop (barley) domestication and improvement 2 papers
  7. 7. Objective 4 Identify the population and genomic factors that contribute to linkage disequilibrium in crop plants 3 papers
  8. 8. Objective 5 Provide computational biology training and access to computational resources to other research programs and the broader community 4 papers 4 programs
  9. 9. Other publications 5 papers 2 chapters
  10. 10. New Objective 2 Assess the type and frequency of genetic changes in plants subject to biotechnology approaches including transgenesis, tissue culture, mutagenesis, and emerging targeted modifications 126 genomes 126 transcriptomes
  11. 11. New Objective 5 Improve the diversity of students participating in computational and plant biology research http://acampusdivided.umn.edu
  12. 12. New Objective 6 Provide computational biology training and access to computational resources to other research programs and the broader community
  13. 13. Alumni doing science
  14. 14. Alumni doing science
  15. 15. Alumni doing science
  16. 16. What is the “cost of domestication?” • Relaxation of selection and changing selective regimens will increase the proportion of deleterious variants in cultigens
  17. 17. • The proportion of deleterious variants will increase owing to genetic bottlenecks • Deleterious variants will be enriched near targets of selection • Selection for yield in elite cultivars could purge deleterious variants Justin Fay
  18. 18. Distribution of Fitness Effects Frequency Relative Fitness 0 1 Strongly Deleterious Approximately Neutral Weakly Deleterious Eyre-Walker et al. 2006 Eyre-Walker and Keightley, 2007
  19. 19. Genetic Effects of Human Demography • Human populations migrated from Africa, many expanded • Altered the number, dominance, and distribution of fitness effects of deleterious variants Henn et al. 2015
  20. 20. How are deleterious variants identified? A•••••••T••A••T ... Banana ••T••••A•••A••A ... Switchgrass ••••••••••••••C ... Purple False Brome ••T•••••••••••A ... Foxtail Millet •••••••••••A••A ... Maize •••••C•••••T••C ... Wild Red Einkorn ••••••••••••••T ... Cutgrass •••••C••••••••C ... Goatgrass ••••••••••••••T ... Asian Rice •••••••••••A••A ... Milo Barley GTCCCTTTCCCGCTM ... Consensus •••••••C••••••C ... N D DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD H Y CCCCYY--YYYCCCCCCCCCCCCCCCCCCCCCCCCCCC C F FFFFFFF-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFF R T TTTMTTTTTTTTTTTTTTTDTTTTTTTTTTTTTTTTTT A T VVAAVVVAVAAAVSVVVTVVVVIVAAAALATTTVVVVV A V VVVVVIVVVIIIIIVVVV-VVV-VVVVVVVVVVVVVVV D E EDDEEEEEEEE-EEEEEEEEEEEEEEEVVEEEEEEEEE Q L LLLLLLL-LMLLLLLLLLLLLL-LLLLLLLLLLLLLLL D N NDDDNNNNNDDDDNDNNNNDDDDDDDDDDNNNNNNDNN V I VVLVVVMMVVVVVVVSVIIIIVMVVVVVIVVVVVIVVV A V AAAAAAAAAAAAAAAAAA-AVT-TA-SAAATTTTTAAT D E DDDDDDDN-DDDDDDDDDNEDD-EEEEEEEDDDDDDDD A P EKSKEEEKEENAENEEEEDAAPAAAEKKEEGGEEEEEE E D RNKKKRK-KKKKKNSSKDPESSPS-KS-SN---KKHHN E D EEEEEEQDDEEEEEEEDEEEDEEDDDDEEEEEEEEEED E A TATTMTTSTTTTATSSCA-SPPMASREECGSSSMTAAT Deleterious Tolerated Kono et al. 2016 https://github.com/MorrellLAB/BAD_Mutations Predict! All Variants SNPs Coding SNPs Nonsynonymous SNPs Length Polymorphisms Noncoding SNPs Synonymous SNPs
  21. 21. Measuring the Cost of Domestication Measure Individuals Populations Absolute number of derived variants at conserved sites Ratio of deleterious to synonymous variants Average frequency of deleterious variants
  22. 22. Assumptions • Gene (codon) function is conserved across the phylogeny • Includes no selection for new function along branches of phylogeny • Epistasis (and compensatory mutations) are ignored • Degree of deleteriousness more readily inferred from frequency than phylogenetic conservation
  23. 23. A cost of domestication in rice? Measure Individuals Populations Absolute number of derived variants at conserved sites Ratio of deleterious to synonymous variants Average frequency of deleterious variants Measure Individuals Populations Absolute number of derived variants at conserved sites Ratio of deleterious to synonymous variants Average frequency of deleterious variants Liu et al. 2017
  24. 24. Summary • Deleterious variants are abundant in the genomes of cultivated plants (and domesticated animals) • More abundant in regions of reduced recombination and near targets of selection (will vary by species) • In very deep resequencing panels, conservation can be inferred based on constrained sites • SNPs annotated as deleterious could be selected against using genomic prediction
  25. 25. Read More About It!
  26. 26. dSNPs in Genomic Prediction Experiment
  27. 27. Questions • How common are dSNPs in elite barley lines and what is their fate through rounds of selection? • Are dSNPs uniformly distributed or concentrated in regions of low recombination?
  28. 28. Fate of dSNPs ● ● ● ● ● ● ● ● ● ● DAF in Parents ProportionofVariantsFixedforAncestralAllele ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00.10.20.30.40.5 [0,0.1] (0.2,0.3] (0.4,0.5] (0.6,0.7] (0.8,0.9] ● ● ● ● Noncoding Synonymous Nonsynonymous Deleterious
  29. 29. SNP Density & dSNPs • Pericentromeres - 19% of sequence, 12% of dSNPs chr1H Position (Mb) DSNPsperCodon ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.000.060.12 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 chr2H Position (Mb) DSNPsperCodon ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.000.060.12 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 chr3H Position (Mb) DSNPsperCodon ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.000.060.12 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 chr4H Position (Mb) DSNPsperCodon ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.000.060.12 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 chr5H Position (Mb) DSNPsperCodon ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.000.060.12 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 chr6H Position (Mb) DSNPsperCodon ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.000.060.12 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 chr7H Position (Mb) DSNPsperCodon ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.000.060.12 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
  30. 30. Code and Data Sharing • https://github.com/MorrellLab/ BAD_Mutations • https://github.com/MorrellLab/ sequence_handling • Sequences - NCBI Sequence Read Archive
  31. 31. Cold Tolerance in Barley
  32. 32. Questions • Can we identify genetic variants that contribute to environmental adaptation in barley? • In particular, are their detectable variants that could contribute to cold temperature adaptation? Poets et al. 2015
  33. 33. Allele Frequency Divergence
  34. 34. LD around “hits”
  35. 35. ● ● ● ●●●● ●● ● ● ● ● ●●● ● ● ●●● ● ● ● ● ● ●●● ● ●●● ● ● ●● ● ● ● ●● ● ●●●●●●● ● ●● ● ●● ●● ● ● ●● ●● ● ● ● ●●● ● ●● ●●●● ● ●● ● ● Original significant SNP: 11_10085 LD decay for SNPs around SNP: 11_10085 ( chr2H : 758851026 bp ) Physical Distance (Kb) LDestimate(r2 ) −100 −80 −60 −40 −20 0 20 40 60 80 100 0.00.20.40.60.81.0 Candidate SNP: 11_20742 (Chr3H:17409756 bp) ● ●● ● ●●●●● ● ● ● ●● ● ● ● ● ● ●●●●●●●● ● ●●● ● ● ●●● ● ● ● ● ● ● ● ● ●●●●●●●●● ● ● ● ●●●● ●●● ● ● ●● ● ●●●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●●●●●● ●● ●●● ● ●●●●● ● ●●●●●●●●● ●●●●●●●●●●●●●●●● ● ● ● ●●● ● ●●●●●● ● ● ●● ●●● ● ●●● ● ●●● ● ●● ● ● ● ●●● ● ●●● ● ● ● ● ● ● ● ● ●●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ●●●● ●●●●●●●●●●●●●●●●●● ● ● ●● ● ● ●● ● ( chr3H : 17409756 bp ) Physical Distance (Kb) LDestimate(r2 ) −100 −80 −60 −40 −20 0 20 40 60 80 100 0.00.20.40.60.81.0 Candidate SNP: 11_10085 (Chr2H: 758851026 bp) ●●● ● ● ● ● ● ● ● ● ● ● ●● ●●● ● ●●●● ● ● ● ● ● ● ●●● ● ●● ● ● ● ●● ● ● ● ●● ● ● ● ● ●●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ●●● Original significant SNP: 11_10143 LD decay for SNPs around SNP: 11_10143 ( chr7H : 537951457 bp ) Physical Distance (Kb) LDestimate(r2 ) −100 −80 −60 −40 −20 0 20 40 60 80 100 0.00.20.40.60.81.0 Candidate SNP: 11_10143 (Chr7H: 537951457 bp) ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ●●● ● ●● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ●● ● Original significant SNP: 11_20784 LD decay for SNPs around SNP: 11_20784 ( chr6H : 507569812 bp ) Physical Distance (Kb) LDestimate(r2 ) −100 −80 −60 −40 −20 0 20 40 60 80 100 0.00.20.40.60.81.0 Candidate SNP: 11_10143 (Chr6H: 507569812 bp) A B C D
  36. 36. HvPrr1/HvTOC1 SCRI_RS_137464 - chr6H:374867096
  37. 37. ●●●● ● ●●●●●●●●●●●●●●●●●●●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ●● ● ● ● ● ● ● ●● ● LD decay for SNPs around SNP: SCRI_RS_137464 ( chr6H : 374867096 bp ) Physical Distance (Kb) LDestimate(r2 ) −100 −80 −60 −40 −20 0 20 40 60 80 1000.00.20.40.60.81.0 LD decay for SNPs around SNP: SCRI_RS_137464 ( chr6H : 374867096 bp ) Physical Distance (Kb) LDestimate(r2 ) HvPRR1/HvTOC1 HORVU6Hr1G057640 11_10513 556 A/C 535 T/C 580 T/C 592 C/T 608 T/C 609 G/T 618 T/C 621 C/T 632 A/T 644 T/G 645 A/C 647 T/C 658 A/C 669 C/T 670 G/A 673 G/A 710 T/C 714 G/T 716 A/C 717 T/C 726 C/T 728 G/C 734 G/C 745 A/G 754 T/A 856 C/A 1003 G/A 1056 C/G 1169 G/A 1172 G/A 1180 T/C 1188 A/G 1336 C/T 2003 C/T 2011 C/T 2081 T/C 2117 G/T 2318 G/A 2332 C/T 2421 T/C 2579 G/A 2664 G/A 2724 C/T 2737 C/T 2739 T/G 2751 C/G 2767 C/T 2865 C/T 0 2995 Red: Nonsynonymous SNP Blue: Significant associated SNP LD with significant associated SNP (r2>0.4) HvPRR1/HvTOC1 556 A/C 535 T/C 580 T/C 592 C/T 608 T/C 609 G/T 618 T/C 621 C/T 632 A/T 644 T/G 645 A/C 647 T/C 658 A/C 669 C/T 670 G/A 673 G/A 710 T/C 714 G/T 716 A/C 717 T/C 726 C/T 728 G/C 734 G/C 745 A/G 754 T/A 856 C/A 1003 G/A 1056 C/G 1169 G/A 1172 G/A 1180 T/C 1188 A/G 1336 C/T 2003 C/T 2011 C/T 2081 T/C 2117 G/T 2318 G/A 2332 C/T 2421 T/C 2579 G/A 2664 G/A 2724 C/T 2737 C/T 2739 T/G 2751 C/G 2767 C/T 2865 C/T 0 2995 Li et al. - in prep.
  38. 38. Primary Results • 12 associations to “cloned” flowering time or cold- tolerance genes • 5 associations to loci relate to cold tolerance • 14 Fst outliers, primarily involved flowering time and cold tolerance T A T V P Y STOP A C T G C C A C G G T G C C C T A C T G A T A T V P Y STOP A C T G C C A C G G T A C C C T A C T G A Reference Alternative … … SNP: 11_20784 Known cold tolerance gene: MLOC_15214.4 0 50 100 150 0 20 40 60 BIO17 Precipitation of Driest Quarter X11_20784, Chro: 6H, 75.16cM, P−value: 2.563e−04 0 200 400 600 800 1000 1200 1400 ● ●●● ● ● ●● ● ● ● ●● ● ● ●● ●●●● ●● ●●●●●● ● ●●●● ● ● ● ● ● ●● ● ●● ● ● ● ●●● ● ● ●●● ● ●● ●● ● ● ●●●●●●●● ● ● ● ● ● ● ● ●●●●●●●●●●●● ● ●●● ● ●● ●●●● ●●●●●●●●●●●● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ●●● ● ● ● ●●●●● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ●●●●●●● ● ● ● ● ●●●●●●● ● ●●●●●●●●● ● ● ●● ● ● ●● ● ●●●●●●●● ●● ●●● ● ●●●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●●●●●● ● ●●●●●● ● ● ● ● ● ●● ● ●● ● ● ● ●●●● ●● ● ●● ● ●● ●● ●●● ● ● ● ●●● ● ● ● ●● ●●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ●● ●● ●●● ●● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●●● ● ●● ● ●● ● ● ●●●●● ● ● ● ●●● ● ● ● ● ● ●●●● ●● ● ●● ● ●●●● ● ●●● ●●●●● ● ●●●●●● ● ● ● ● ● ● ●●● ● ● ● ●● ● ● ●● ● ● ● ●● ●● ●● ● ● ● ● ● ● ●●●●●●●●● ● ● ●● ●● ● ● ●●●●●●●●●●●●● ● ● ●●●● ●●●●● ●●●●●●●●●●●●●●●●● ● ●● ● ● ●● ● ● ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● ● ● ●●●●●● ● ●● ●● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●●●●●●●●● ● ● ●●●●●●●●●●●●●●● ●●●●●●●●●●●●● ● ● ● ● ●●● ●● ●● ● ●●●●●●● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ●●● ●● ● ● ● ●● ●●● ● ● ●● ●●●● ●● ● ●●●● ●●●●●●●●● ● ● ● ●●●●●●● ●●●● ●●●● ● ● ●● ●●●●●● ●●● ● ●●●●● ●●● ● ● ●● ●● ● ● ● ● ● ● ●● ●● ●●●● BIO17 Precipitation of Driest Quarter 100150 tionofDriestQuarter 75.16cM,P−value:2.563e−04 0 200 400 600 800 1000 1200 1400 ● ●●●● ●●●●●●●● ●●●● ●●●● ●●●●●●●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ●● ● ●●●●●●●● ●● ●●● ● ●●●●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ●●●●●●● ● ●●●●●● ● ●● ●●●● ● ● ●●● ● ● ●●●● ● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ●●● ● ●●● ●●● ●● ● ● ● ●●●●●●●●●●●●●●● ●●●●●●● ● ● ● ●●● ●● ● ● ● ●● ●●●● ● ●●●●●●●●● ●●●● ●● ●● ●●●●●● ●●● ● ●●●●●● ● ●● ●● ● ● ● ●● ●●●● 100150 tionofDriestQuarter tionunavailable,P−value:2.597e−04 0 200 400 600 800 1000 1200 1400 ● ●●●● ●●●●●●●● ●●●● ●●●● ●●●●●●●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ●● ● ●●●●●●●● ●● ●●● ● ●●●●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ●●●●●● ● ●●●●●● ● ●● ●●●● ● ● ●●● ● ● ●●●● ● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ●●● ● ●●● ●●● ●● ● ● ● ●●●●●●●●●●●●●●● ●●●●●●● ● ● ● ●●● ●● ● ● ● ●● ●●●● ● ●●●●●●●●● ●●●● ●● ●● ●●●●●● ●●● ● ●●●●●● ● ●● ●● ● ● ● ●● ●●●● Bio17 Precipitation of Driest Quarter Li et al. - in prep.
  39. 39. Summary • Recover previously characterized loci: Cbf3, PhyC, Ppd-H1, Vrn1 • At least one locus directly associated with freezing tolerance • Environmental association in barley landraces will benefit greatly from resequencing, increased SNP density
  40. 40. Code and Data Sharing • https://github.com/MorrellLab/ Env_Assoc • https://github.com/MorrellLab/ sequence_handling • Sequences - NCBI Sequence Read Archive
  41. 41. Acknowledgements • NSF Plant Genome Research • USDA Biotech Risk Assessment • MN Ag Experiment Station • USDA National Needs • MnDrive • UMN Doctoral Dissertation Fellowships
  42. 42. Evolution of Crop Plants Evolution of Crop Plants AGRO 8023 Fall 2018 Evolution of Crop Plants is a multidisciplinary examination of crop domestication and improvement for graduate students in the life sciences. The four units of the course include: 1) Origins of Agriculture, 2) Methods for Understanding Domestication and Improvement, 3) The Genetic Basis of Agronomic Adaptations, 4) Twenty-first Century Plant Domestication. Monday & Wednesday, 10:15 - 11:30 am Instructor: Peter L. Morrell http://z.umn.edu/ecp
  43. 43. barleyworld.org

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