Genomic insights into deleterious mutations and their impact on agronomic traits during pear domestication

Abstract

The pear (Pyrus spp.), a perennial fruit tree, is subjected to genetic alterations over decades or even centuries to adapt to complex climatic and cultivation conditions. Genome-wide studies of deleterious mutations remain limited in perennial fruit trees, particularly regarding the effects of domestication on deleterious mutations. In this study, 232 pear accessions were resequenced, and 9 909 773 single-nucleotide polymorphisms (SNPs), and 139 335 deleterious mutation sites, were identified genome wide. A higher proportion of deleterious mutations in coding regions (1.4%) were observed in the pear genome than annual crops. During domestication, a reduction in deleterious mutations in Pyrus pyrifolia/P. bretschneideri was found to be associated with their decreases in selective sweep regions. Conversely, an increase in the number of deleterious mutations in P. communis was observed, which may be related to a higher occurrence within selective sweep regions. In P. ussuriensis, an overall increasing trend in deleterious mutations was identified, which was determined to be unrelated to domestication or gene introgression but instead linked to its relatively high heterozygosity. Differential deleterious mutation genes were identified during the domestication process. Among these, the PyMYC2 gene, associated with stone cell synthesis, was identified through GWAS, overexpression of PyMYC2 in pear callus significantly promoter lignin biosynthesis, PyMYC2 contains three nonsynonymous deleterious mutations that were selected during the domestication of Asian pears. This research provides new insights into developing future breeding strategies aimed at improving agronomic traits and offers a framework for studying deleterious mutation patterns in the domestication of perennial fruit trees.

Acknowledgments

This work was supported by the National Science Foundation of China (nos 32230097 and 32172531), the National Key Research and Development Program of China (no. 2022YFD1200503), the Earmarked Fund for China Agriculture Research System (CARS-28), the Earmarked Fund for Jiangsu Agricultural Industry Technology System JATS [2023] 412, and the Natural Science Foundation of Jiangsu Province for Young Scholar (no. BK20221010).

Author Contributions

J.W. designed and managed the project. X.Z., S.D., and Y.R. collected the samples. X.Z., B.S., and S.C. performed the data analyses. X.Z., S.D. and S.Z. performed the experiments. S.X., P.Z., Z.Q., J.L., W.W., and C.X. provided valuable suggestions. X.Z. wrote the manuscript. J.W. revised the manuscript. All authors read and approved the final manuscript.

Data Availability

Data supporting the findings of this work are available within the paper and its Supplementary Information files. Raw genome re-sequencing reads have been deposited into the NCBI sequence read archive(SRA) (https://www.ncbi.nlm.nih.gov/sra/) under BioProject accession number of PRJNA1258372.

Conflict of interest statement:

The authors declare no competing interests.

Supplementary data

Supplementary data is available at Horticulture Research online.

References

[1] Quiroz D, Lensink M, Kliebenstein DJ. et al. Causes of mutation rate variability in plant genomes. Annu Rev Plant Biol. 2023; 74: 751-75

[2] Kono TJ, Fu F, Mohammadi M. et al. The role of deleterious substitutions in crop genomes. Mol Biol Evol. 2016; 33:2307-17

[3] Joseph SB, Hall DW. Spontaneous mutations in diploid Sac-charomyces cerevisiae: more beneficial than expected. Genetics. 2004; 168:1817-25

[4] Keightley PD, Lynch M. Toward a realistic model of mutations affecting fitness. Evolution. 2003;57:683-5 discussion 686-689

[5] Eyre-Walker A, Woolfit M, Phelps T. The distribution of fitness effects of new deleterious amino acid mutations in humans. Genetics. 2006; 173:891-900

[6] Lu J, Tang T, Tang H. et al. The accumulation of deleterious muta-tions in rice genomes: a hypothesis on the cost of domestication. Trends Genet. 2006; 22:126-31

[7] Gunther T, Schmid KJ. Deleterious amino acid polymorphisms in Arabidopsis thaliana and rice. Theor Appl Genet. 2010; 121:157-68

[8] Lozano R, Gazave E, Dos Santos JPR. et al. Comparative evolu-tionary genetics of deleterious load in sorghum and maize. Nat Plants. 2021; 7:17-24

[9] Kim MS, Lozano R, Kim JH. et al. The patterns of deleterious mutations during the domestication of soybean. Nat Commun. 2021; 12:97

[10] Zhang C, Wang P, Tang D. et al. The genetic basis of inbreeding depression in potato. Nat Genet. 2019; 51:374-8

[11] Stokstad E. The new potato. Science. 2019; 363:574-7

[12] Wu Y, Li D, Hu Y. et al. Phylogenomic discovery of dele-terious mutations facilitates hybrid potato breeding. Cell. 2023; 186:2313-2328.e15

[13] Bell RL. Pears (PYRUS). Leuven, Belgium: International Society for Horticultural Science (ISHS); 1991:657-700

[14] Rom RC, Carlson RF.Rootstocks for Fruit Crops. Wiley, 1987

[15] Wu J, Wang Y, Xu J. et al. Diversification and independent domes-tication of Asian and European pears. Genome Biol. 2018; 19:77

[16] Zhang MY, Xue C, Xu L. et al. Distinct transcriptome profiles reveal gene expression patterns during fruit development and maturation in five main cultivated species of pear (Pyrus L.). Sci Rep. 2016; 6:28130

[17] Li XL, Liu L, Ming ML. et al. Comparative transcriptomic analysis provides insight into the domestication and improvement of pear (P. Pyrifolia). Fruit Plant Physiology. 2019; 180:435-52

[18] Zhang L, Kamitakahara H, Murayama H. et al. Analysis of fruit lignin content, composition, and linkage types in pear cultivars and related species. J Agric Food Chem. 2020; 68:2493-505

[19] Wu J, Wang Z, Shi Z. et al. The genome of the pear (Pyrus bretschneideri Rehd.). Genome Res. 2013; 23:396-408

[20] Wu J, Li LT, Li M. et al. High-density genetic linkage map con-struction and identification of fruit-related QTLs in pear using SNP and SSR markers. JExp Bot. 2014; 65:5771-81

[21] Li J, Zhang M, Li X. et al. Pear genetics: recent advances, new prospects, and a roadmap for the future. Hortic Res. 2022;9:uhab040

[22] Gao Y, Yang Q, Yan X. et al. High-quality genome assembly of ’Cuiguan’ pear (Pyrus pyrifolia) as a reference genome for identi-fying regulatory genes and epigenetic modifications responsible for bud dormancy. Hortic Res. 2021; 8:197

[23] Boulnois L, Loveday H. Silk Road: Monks, Warriors & Merchants on the Silk Road. New York: WW Norton & Co Inc, 2004

[24] Prevas J. Envy of the gods:Alexander the Great’s ill-fated journey across Asia. Boston: Da Capo Press, 2005

[25] Huang X, Kurata N, Wei X. et al. A map of rice genome variation reveals the origin of cultivated rice. Nature. 2012; 490:497-501

[26] Huang X, Wei X, Sang T. et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet. 2010; 42:961-7

[27] Chen L, Luo J, Jin M. et al. Genome sequencing reveals evidence of adaptive variation in the genus Zea. Nat Genet. 2022; 54:1736-45

[28] Jia G, Huang X, Zhi H. et al. A haplotype map of genomic varia-tions and genome-wide association studies of agronomic traits in foxtail millet (Setaria italica). Nat Genet. 2013; 45:957-61

[29] Dong Y, Duan S, Xia Q. et al. Dual domestications and origin of traits in grapevine evolution. Science. 2023; 379:892-901

[30] Lu Q, Zhao H, Zhang Z. et al. Genomic variation in weedy and cultivated broomcorn millet accessions uncovers the genetic architecture of agronomic traits. Nat Genet. 2024; 56:1006-17

[31] Ji FY, Ma QG, Zhang WT. et al. A genome variation map provides insights into the genetics of walnut adaptation and agronomic traits. Genome Biol. 2021; 22:300

[32] Frary A, Nesbitt TC, Grandillo S. et al. Tanksley SD: fw2.2: a quantitative trait locus key to the evolution of tomato fruit size. Science. 2000; 289:85-8

[33] Wang RZ, Xue YS, Fan J. et al. A systems genetics approach reveals PbrNSC as a regulator of lignin and cellulose biosynthe-sis in stone cells of pear fruit. Genome Biol. 2021; 22:313

[34] Zhou MQ, Shen C, Wu LH. et al. CBF-dependent signaling path-way: a key responder to low temperature stress in plants. Crit Rev Biotechnol. 2011; 31:186-92

[35] Chen M, Wang QY, Cheng XG. et al. GmDREB2, a soybean DRE-binding transcription factor, conferred drought and high-salt tolerance in transgenic plants. Biochem Biophys Res Commun. 2007; 353:299-305

[36] Hsieh TH, Lee JT, Charng YY. et al. Tomato plants ectopically expressing Arabidopsis CBF1 show enhanced resistance to water deficit stress. Plant Physiol. 2002; 130:618-26

[37] Cao B, Zhu R, Sun M. et al. PcPME63 is involved in fruit softening during post-cold storage process of European pear (Pyrus com-munis L.). Postharvest Biol Technol. 2024; 211:112811

[38] Li X, Wang Y, Cai C. et al. Large-scale gene expression alterations introduced by structural variation drive morphotype diversifi-cation in Brassica oleracea. Nat Genet. 2024; 56:517-29

[39] Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc. 2009; 4:1073-81

[40] Han C, Zhang F, Qiao X. et al. Multi-omics analysis reveals the dynamic changes of RNA N (6) -methyladenosine in pear (Pyrus bretschneideri) defense responses to Erwinia amylovora pathogen infection. Front Microbiol. 2021; 12:803512

[41] Yan CC, Yin M, Zhang N. et al. Stone cell distribution and lignin structure in various pear varieties. Sci Hortic-Amsterdam. 2014; 174:142-50

[42] Xue C, Yao JL, Xue YS. et al. PbrMYB169 positively regulates lignification of stone cells in pear fruit. JExp Bot. 2019; 70:1801-14

[43] Xu S, Sun M, Yao JL. et al. Auxin inhibits lignin and cellulose biosynthesis in stone cells of pear fruit via the PbrARF13-PbrNSC-PbrMYB132 transcriptional regulatory cascade. Plant Biotechnol J. 2023; 21:1408-25

[44] Zhang Q, Xie Z, Zhang R. et al. Blue light regulates sec-ondary Cell Wall thickening via MYC2/MYC4 activation of the NST1-directed transcriptional network in Arabidopsis. Plant Cell. 2018; 30:2512-28

[45] Zhang MY, Xue C, Hu H. et al. Genome-wide association studies provide insights into the genetic determination of fruit traits of pear. Nat Commun. 2021; 12:1144

[46] Song B, Yu J, Li X. et al. Increased DNA methylation contributes to the early ripening of pear fruits during domestication and improvement. Genome Biol. 2024; 25:87

[47] Xiao H, Liu Z, Wang N. et al. Adaptive and maladaptive intro-gression in grapevine domestication. Proc Natl Acad Sci USA. 2023; 120:e2222041120

[48] He F, Pasam R, Shi F. et al. Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome. Nat Genet. 2019; 51:896-904

[49] Liu Q, Zhou Y, Morrell PL. et al. Deleterious variants in Asian Rice and the potential cost of domestication. MolBiolEvol. 2017; 34: 908-24

[50] Zhou Z, Jiang Y, Wang Z. et al. Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean. Nat Biotechnol. 2015; 33:408-14

[51] Cheng F, Sun R, Hou X. et al. Subgenome parallel selection is associated with morphotype diversification and convergent crop domestication in Brassica rapa and Brassica oleracea. Nat Genet. 2016; 48:1218-24

[52] Yano K, Yamamoto E, Aya K. et al. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nat Genet. 2016; 48: 927-34

[53] Peleman JD, van der Voort JR. Breeding by design. Trends Plant Sci. 2003; 8:330-4

[54] Davierwala AP, Reddy AP, Lagu MD. et al. Marker assisted selec-tion of bacterial blight resistance genes in rice. Biochem Genet. 2001; 39:261-78

[55] Das A, Soubam D, Singh PK. et al. A novel blast resistance gene, Pi54rh cloned from wild species of rice, Oryza rhizomatis confers broad spectrum resistance to Magnaporthe oryzae. Funct Integr Genomics. 2012; 12:215-28

[56] Collard BC, Mackill DJ. Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc Lond Ser B Biol Sci. 2008; 363:557-72

[57] Gaut BS, Seymour DK, Liu Q. et al. Demography and its effects on genomic variation in crop domestication. Nat Plants. 2018; 4: 512-20

[58] Moyers BT, Morrell PL, McKay JK. Genetic costs of domestication and improvement. J Hered. 2018; 109:103-16

[59] Charlesworth D, Willis JH. The genetics of inbreeding depression. Nat Rev Genet. 2009; 10:783-96

[60] Li P, Xiao L, Du Q. et al. Genomic insights into selection for heterozygous alleles and woody traits in Populus tomentosa. Plant Biotechnol J. 2023; 21:2002-18

[61] Sun S, Wang B, Li C. et al. Unraveling prevalence and effects of deleterious mutations in maize elite lines across decades of modern breeding. Mol Biol Evol. 2023;40:msad170

[62] Yang G, Sun M, Brewer L. et al. Allelic variation of BBX24 is a dominant determinant controlling red coloration and dwarfism in pear. Plant Biotechnol J. 2024; 22:1468-90

[63] Wingett SW, Andrews S. FastQ screen: a tool for multi-genome mapping and quality control. F1000Res. 2018; 7:1338

[64] Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014; 30: 2114-20

[65] Li H, Handsaker B, Wysoker A. et al. Genome project data pro-cessing S: the sequence alignment/map format and SAMtools. Bioinformatics. 2009; 25:2078-9

[66] Wang K, Li M, Hakonarson H. ANNOVAR: functional annota-tion of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010; 38:e164

[67] He W, Zhao S, Liu X. et al. ReSeqTools: an integrated toolkit for large-scale next-generation sequencing based resequencing analysis. Genet Mol Res. 2013; 12:6275-83

[68] Price MN, Dehal PS, Arkin AP. FastTree: computing large mini-mum evolution trees with profiles instead of a distance matrix. Mol Biol Evol. 2009; 26:1641-50

[69] Letunic I, Bork P. Interactive tree of life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res. 2024;52:W78-82

[70] Alexander DH, Novembre J, Lange K. Fast model-based estima-tion of ancestry in unrelated individuals. Genome Res. 2009; 19: 1655-64

[71] Danecek P, Auton A, Abecasis G. et al. The variant call format and VCFtools. Bioinformatics. 2011; 27:2156-8

[72] Chen H, Patterson N, Reich D. Population differentiation as a test for selective sweeps. Genome Res. 2010; 20:393-402

[73] Chen C, Chen H, Zhang Y. et al. TBtools: an integrative toolkit developed for interactive analyses of big biological data. Mol Plant. 2020; 13:1194-202

[74] Vaser R, Adusumalli S, Leng SN. et al. SIFT missense predictions for genomes. Nat Protoc. 2016; 11:1-9

[75] Davydov EV, Goode DL, Sirota M. et al. Identifying a high fraction of the human genome to be under selective constraint using GERP++. PLoS Comput Biol. 2010; 6:e1001025

[76] Flynn JM, Hubley R, Goubert C. et al. RepeatModeler2 for auto-mated genomic discovery of transposable element families. Proc Natl Acad Sci USA. 2020; 117:9451-7

[77] Tarailo-Graovac M, Chen N.Using RepeatMasker to identify repetitive elements in genomic sequences. Curr Protoc Bioinfor-matics. 2009; Chapter 4:4.10.1-4.10.14.

[78] Purcell S, Neale B, Todd-Brown K. et al. PLINK: a tool set for whole-genome association and population-based linkage anal-yses. Am J Hum Genet. 2007; 81:559-75

[79] Yamagishi Y, Yoshimoto J, Uchiyama H. et al. In vitro induction of secondary xylem-like tracheary elements in calli of hybrid poplar (Populus sieboldii x P. Grandidentata). Planta. 2013; 237: 1179-85

[80] Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 2001; 25:402-8

[81] Xue Y, Shan Y, Yao JL. et al. The transcription factor PbrMYB24 regulates lignin and cellulose biosynthesis in stone cells of pear fruits. Plant Physiol. 2023; 192:1997-2014