Gene disruption by structural mutations drives selection in US rice breeding over the last century

English version

Autoři: Justin N. Vaughn ^aff001; Walid Korani ^aff002; Joshua C. Stein ^aff003; Jeremy D. Edwards ^aff004; Daniel G. Peterson ^aff005; Sheron A. Simpson ^aff001; Ramey C. Youngblood ^aff005; Jane Grimwood ^aff006; Kapeel Chougule ^aff003; Doreen H. Ware ^aff003; Anna M. McClung ^aff004; Brian E. Scheffler ^aff001
Působiště autorů: USDA-ARS, Genomics and Bioinformatics Research Unit, Stoneville, Mississippi, United States of America ^aff001; University of Georgia, Athens, Institute of Plant Breeding, Genetics, and Genomics, Athens, Georgia, United States of America ^aff002; Cold Spring Harbor Laboratory, Cold Springs Harbor, New York, United States of America ^aff003; USDA-ARS, Dale Bumpers National Rice Research Center, Stuttgart, Arkansas, United States of America ^aff004; Mississippi State University, Institute for Genomics, Biocomputing & Biotechnology, Starkville, Mississippi, United States of America ^aff005; Hudson-Alpha Institute for Biotechnology, Huntsville, Alabama, United States of America ^aff006; USDA-ARS, Robert W. Holley Center for Agriculture and Health, Ithaca, New York, United States of America ^aff007
Vyšlo v časopise: Gene disruption by structural mutations drives selection in US rice breeding over the last century. PLoS Genet 17(3): e1009389. doi:10.1371/journal.pgen.1009389
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1009389

Souhrn

The genetic basis of general plant vigor is of major interest to food producers, yet the trait is recalcitrant to genetic mapping because of the number of loci involved, their small effects, and linkage. Observations of heterosis in many crops suggests that recessive, malfunctioning versions of genes are a major cause of poor performance, yet we have little information on the mutational spectrum underlying these disruptions. To address this question, we generated a long-read assembly of a tropical japonica rice (Oryza sativa) variety, Carolina Gold, which allowed us to identify structural mutations (>50 bp) and orient them with respect to their ancestral state using the outgroup, Oryza glaberrima. Supporting prior work, we find substantial genome expansion in the sativa branch. While transposable elements (TEs) account for the largest share of size variation, the majority of events are not directly TE-mediated. Tandem duplications are the most common source of insertions and are highly enriched among 50-200bp mutations. To explore the relative impact of various mutational classes on crop fitness, we then track these structural events over the last century of US rice improvement using 101 resequenced varieties. Within this material, a pattern of temporary hybridization between medium and long-grain varieties was followed by recent divergence. During this long-term selection, structural mutations that impact gene exons have been removed at a greater rate than intronic indels and single-nucleotide mutations. These results support the use of ab initio estimates of mutational burden, based on structural data, as an orthogonal predictor in genomic selection.

Klíčová slova:

Alleles – Genetic loci – Genomics – Haplotypes – Mutation – Rice – Sequence alignment – Single nucleotide polymorphisms

Zdroje

1. Gaut BS, Seymour DK, Liu Q, Zhou Y. Demography and its effects on genomic variation in crop domestication. Nat Plants. 2018;4 : 512. doi: 10.1038/s41477-018-0210-1 30061748

2. Moyers BT, Morrell PL, McKay JK. Genetic Costs of Domestication and Improvement. J Hered. 2018;109 : 103–116. doi: 10.1093/jhered/esx069 28992310

3. Lu J, Tang T, Tang H, Huang J, Shi S, Wu C-I. The accumulation of deleterious mutations in rice genomes: a hypothesis on the cost of domestication. Trends Genet TIG. 2006;22 : 126–131. doi: 10.1016/j.tig.2006.01.004 16443304

4. Wallace JG, Rodgers-Melnick E, Buckler ES. On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics. Annu Rev Genet. 2018;52 : 421–444. doi: 10.1146/annurev-genet-120116-024846 30285496

5. Yang J, Mezmouk S, Baumgarten A, Buckler ES, Guill KE, McMullen MD, et al. Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize. PLOS Genet. 2017;13:e1007019. doi: 10.1371/journal.pgen.1007019 28953891

6. Rodríguez-Leal D, Lemmon ZH, Man J, Bartlett ME, Lippman ZB. Engineering Quantitative Trait Variation for Crop Improvement by Genome Editing. Cell. 2017;171 : 470–480.e8. doi: 10.1016/j.cell.2017.08.030 28919077

7. Kremling KAG, Chen S-Y, Su M-H, Lepak NK, Romay MC, Swarts KL, et al. Dysregulation of expression correlates with rare-allele burden and fitness loss in maize. Nature. 2018;555 : 520–523. doi: 10.1038/nature25966 29539638

8. Fuentes RR, Chebotarov D, Duitama J, Smith S, Hoz JFD la, Mohiyuddin M, et al. Structural variants in 3000 rice genomes. Genome Res. 2019 [cited 1 May 2019]. doi: 10.1101/gr.241240.118 30992303

9. Mahmoud M, Gobet N, Cruz-Dávalos DI, Mounier N, Dessimoz C, Sedlazeck FJ. Structural variant calling: the long and the short of it. Genome Biol. 2019;20 : 246. doi: 10.1186/s13059-019-1828-7 31747936

10. Tabien RE, Samonte SOP, McClung AM. Forty-eight Years of Rice Improvement in Texas since the Release of Cultivar Bluebonnet in 1944. Crop Sci. 2008;48 : 2097–2106. https://doi.org/10.2135/cropsci2007.12.0680

11. Williams VR, Wu W-T, Tsai HY, Bates HG. Rice Starch, Varietal Differences in Amylose Content of Rice Starch. J Agric Food Chem. 1958;6 : 47–48. doi: 10.1021/jf60083a009

12. Wang X, Jia Y, Wamishe Y, Jia MH, Valent B. Dynamic Changes in the Rice Blast Population in the United States Over Six Decades. Mol Plant-Microbe Interactions®. 2017;30 : 803–812. doi: 10.1094/MPMI-04-17-0101-R 28677493

13. Ma J, Bennetzen JL. Rapid recent growth and divergence of rice nuclear genomes. Proc Natl Acad Sci U S A. 2004;101 : 12404–12410. doi: 10.1073/pnas.0403715101 15240870

14. Carpentier M-C, Manfroi E, Wei F-J, Wu H-P, Lasserre E, Llauro C, et al. Retrotranspositional landscape of Asian rice revealed by 3000 genomes. Nat Commun. 2019;10 : 24. doi: 10.1038/s41467-018-07974-5 30604755

15. Read AC, Moscou MJ, Zimin AV, Pertea G, Meyer RS, Purugganan MD, et al. Genome assembly and characterization of a complex zfBED-NLR gene-containing disease resistance locus in Carolina Gold Select rice with Nanopore sequencing. PLOS Genet. 2020;16:e1008571. doi: 10.1371/journal.pgen.1008571 31986137

16. Wang M, Yu Y, Haberer G, Marri PR, Fan C, Goicoechea JL, et al. The genome sequence of African rice (Oryza glaberrima) and evidence for independent domestication. Nat Genet. 2014;46 : 982–988. doi: 10.1038/ng.3044 25064006

17. Vaughn JN, Bennetzen JL. Natural insertions in rice commonly form tandem duplications indicative of patch-mediated double-strand break induction and repair. Proc Natl Acad Sci. 2014;111 : 6684–6689. doi: 10.1073/pnas.1321854111 24760826

18. Kosugi S, Momozawa Y, Liu X, Terao C, Kubo M, Kamatani Y. Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing. Genome Biol. 2019;20 : 117. doi: 10.1186/s13059-019-1720-5 31159850

19. Puchta H. The repair of double-strand breaks in plants: mechanisms and consequences for genome evolution. J Exp Bot. 2005;56 : 1–14. doi: 10.1093/jxb/eri025 15557293

20. Schiml S, Fauser F, Puchta H. Repair of adjacent single-strand breaks is often accompanied by the formation of tandem sequence duplications in plant genomes. Proc Natl Acad Sci. 2016; 201603823. doi: 10.1073/pnas.1603823113 27307441

21. Messer PW, Arndt PF. The majority of recent short DNA insertions in the human genome are tandem duplications. Mol Biol Evol. 2007;24 : 1190–1197. doi: 10.1093/molbev/msm035 17322553

22. Wang W, Mauleon R, Hu Z, Chebotarov D, Tai S, Wu Z, et al. Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature. 2018;557 : 43. doi: 10.1038/s41586-018-0063-9 29695866

23. Alexander DH, Lange K. Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics. 2011;12 : 246. doi: 10.1186/1471-2105-12-246 21682921

24. Vaughn JN, Li Z. Genomic Signatures of North American Soybean Improvement Inform Diversity Enrichment Strategies and Clarify the Impact of Hybridization. G3 Genes Genomes Genet. 2016;6 : 2693–2705. doi: 10.1534/g3.116.029215 27402364

25. van Heerwaarden J, Hufford MB, Ross-Ibarra J. Historical genomics of North American maize. Proc Natl Acad Sci. 2012;109 : 12420–12425. doi: 10.1073/pnas.1209275109 22802642

26. Gan X, Stegle O, Behr J, Steffen JG, Drewe P, Hildebrand KL, et al. Multiple reference genomes and transcriptomes for Arabidopsis thaliana. Nature. 2011;477 : 419–423. doi: 10.1038/nature10414 21874022

27. Hill WG, Robertson A. The effect of linkage on limits to artificial selection. Genet Res. 1966;8 : 269–294. 5980116

28. Lin Z, Qin P, Zhang X, Fu C, Deng H, Fu X, et al. Divergent selection and genetic introgression shape the genome landscape of heterosis in hybrid rice. Proc Natl Acad Sci. 2020;117 : 4623–4631. doi: 10.1073/pnas.1919086117 32071222

29. Beissinger TM, Hirsch CN, Vaillancourt B, Deshpande S, Barry K, Buell CR, et al. A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number. Genetics. 2014;196 : 829–840. doi: 10.1534/genetics.113.160655 24381334

30. Pritchard JK, Pickrell JK, Coop G. The Genetics of Human Adaptation: Hard Sweeps, Soft Sweeps, and Polygenic Adaptation. Curr Biol CB. 2010;20:R208–R215. doi: 10.1016/j.cub.2009.11.055 20178769

31. Bersaglieri T, Sabeti PC, Patterson N, Vanderploeg T, Schaffner SF, Drake JA, et al. Genetic Signatures of Strong Recent Positive Selection at the Lactase Gene. Am J Hum Genet. 2004;74 : 1111–1120. doi: 10.1086/421051 15114531

32. Athwal DS. Semidwarf Rice and Wheat in Global Food Needs. Q Rev Biol. 1971;46 : 1–34. doi: 10.1086/406754 4927378

33. Angira B, Addison CK, Cerioli T, Rebong DB, Wang DR, Pumplin N, et al. Haplotype Characterization of the sd1 Semidwarf Gene in United States Rice. Plant Genome. 2019;12. doi: 10.3835/plantgenome2019.02.0010 33016579

34. Rybka K, Miyamoto M, Ando I, Saito A, Kawasaki S. High Resolution Mapping of the Indica-Derived Rice Blast Resistance Genes II. Pi-ta2 and Pi-ta and a Consideration of Their Origin. Mol Plant Microbe Interact. 1997;10 : 517–524. doi: 10.1094/MPMI.1997.10.4.517

35. Messer PW, Petrov DA. Population genomics of rapid adaptation by soft selective sweeps. Trends Ecol Evol. 2013;28 : 659–669. doi: 10.1016/j.tree.2013.08.003 24075201

36. Lorenz AJ, Chao S, Asoro FG, Heffner EL, Hayashi T, Iwata H, et al. Chapter Two—Genomic Selection in Plant Breeding: Knowledge and Prospects. In: Sparks DL, editor. Advances in Agronomy. Academic Press; 2011. pp. 77–123. doi: 10.1016/B978-0-12-385531-2.00002–5

37. Stewart-Brown BB, Song Q, Vaughn JN, Li Z. Genomic Selection for Yield and Seed Composition Traits Within an Applied Soybean Breeding Program. G3 Genes Genomes Genet. 2019;9 : 2253–2265. doi: 10.1534/g3.118.200917 31088906

38. Doyle J, Doyle JL, Doyle JJ, Doyle J, Doyle JL, Doyle JJ, et al. A rapid DNA isolation procedure from small quantities of fresh leaf tissues. 1987 [cited 7 Apr 2020]. Available from: https://www.scienceopen.com/document?vid=1cd6f3da-bc63-466b-9990-270af0960e2a.

39. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH, Phillippy AM. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 2017; gr.215087.116. doi: 10.1101/gr.215087.116 28298431

40. Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, et al. Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement. PLOS ONE. 2014;9:e112963. doi: 10.1371/journal.pone.0112963 25409509

41. Cantarel BL, Korf I, Robb SMC, Parra G, Ross E, Moore B, et al. MAKER: An easy-to-use annotation pipeline designed for emerging model organism genomes. Genome Res. 2008;18 : 188–196. doi: 10.1101/gr.6743907 18025269

42. Stein JC, Yu Y, Copetti D, Zwickl DJ, Zhang L, Zhang C, et al. Genomes of 13 domesticated and wild rice relatives highlight genetic conservation, turnover and innovation across the genus Oryza. Nat Genet. 2018;50 : 285–296. doi: 10.1038/s41588-018-0040-0 29358651

43. Copetti D, Zhang J, El Baidouri M, Gao D, Wang J, Barghini E, et al. RiTE database: a resource database for genus-wide rice genomics and evolutionary biology. BMC Genomics. 2015;16 : 538. doi: 10.1186/s12864-015-1762-3 26194356

44. Darling AE, Mau B, Perna NT. progressiveMauve: multiple genome alignment with gene gain, loss and rearrangement. PloS One. 2010;5:e11147. doi: 10.1371/journal.pone.0011147 20593022

45. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10 : 421. doi: 10.1186/1471-2105-10-421 20003500

46. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30 : 2114–2120. doi: 10.1093/bioinformatics/btu170 24695404

47. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinforma Oxf Engl. 2009;25 : 1754–1760. doi: 10.1093/bioinformatics/btp324 19451168

48. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43 : 491–498. doi: 10.1038/ng.806 21478889

49. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics. 2007;23 : 2633–2635. doi: 10.1093/bioinformatics/btm308 17586829

50. Endelman JB, Jannink J-L. Shrinkage estimation of the realized relationship matrix. G3 Bethesda Md. 2012;2 : 1405–1413. doi: 10.1534/g3.112.004259 23173092

51. He J, Meng S, Zhao T, Xing G, Yang S, Li Y, et al. An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding. Theor Appl Genet. 2017;130 : 2327–2343. doi: 10.1007/s00122-017-2962-9 28828506

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