First interspecific multi-parent advanced generation inter-cross (MAGIC) population in Capsicum peppers: development, phenotypic evaluation, genomic analysis, and prospects

Abstract

This work presents the first eight-way multi-parental advanced generation inter-cross (MAGIC) population in pepper. This interspecific MAGIC population was built with six Capsicum annuum accessions and two C. chinense accessions, selected for encompassing a representative and wide genetic diversity, and being complementary for morphological, agronomic, and fruit quality traits. The population in its third selfing generation has been phenotyped with reliable descriptors and genotyped using genotyping-by-sequencing to assess its overall diversity, homozygosity, parental contributions, and genetic structure. A great variability was found in the phenotyping study, showing many forms of recombination of all the founder lines. Moreover, new phenotypic combinations were found, as well as transgressive inheritance in quantitative traits. The S3 generation contained a balanced distribution of the parental genomes and each S3 individual seemed to contain a unique genomic combination of the founder lines, reaching high homozygosity. In this regard, a preliminary genome-wide association study (GWAS) was performed for highly heritable traits to evaluate the potential of this population for future breeding prospects. Strong associations were found for most traits analysed, like stem pubescence and fruit colour at maturity stage, with associated genes related to response to stress and defence functions; or fruit wall consistency, with associated genes related to lipid metabolism. Our results show that this first Capsicum MAGIC population is a valuable genetic resource for research and breeding purposes in peppers, by identifying genomic regions associated with traits of interest and its potential for future GWAS in more complex agronomical and fruit quality traits.

Acknowledgements

This work was supported by grant CIPROM/2021/020 funded by Conselleria de Innovación, Universidades, Investigación y Sociedad Digital (Generalitat Valenciana) and grant PID2022-137735OR-C33 funded by Ministerio de Ciencia e Innovación (Agencia Estatal de Investigación, Spanish Government). N.O.A. also wants to thank Ministerio de Educación, Cultura y Deporte (Spanish Government) for grant number FPU19/04080.

Author contributions

Conceptualization, A.R.B.; data curation, L.B.; formal analysis, L.G. and L.B.; funding acquisition, A.F. and A.R.B.; investigation, N.O.A. and M.D.R.; methodology, N.O.A. and M.D.R.; project administration, A.F. and A.R.B.; resources, A.R.B.; software, L.B.; supervision, A.F. and A.R.B.; validation, N.O.A., A.F., and A.R.B.; visualization, N.O.A. and A.R.B.; writing - original draft, N.O.A., M.D.R; writing - review and editing, A.R.B. All authors have read and agreed to the published version of the manuscript.

Data availability

The genomic raw data underlying this article are available in the Sequence Read Archive (SRA) of the National Institutes of Health (NIH).

Conflict of interest

The authors declare no conflict of interest for publishing this article.

Supplementary Data

Supplementary data are available at Horticulture Research online.

References

[1] Jarret RL, Barboza GE, Batista FR. et al. Capsicum-an abbreviated compendium. J Am Soc Hortic Sci. 2019; 144:3-22

[2] Manzur JP, Fita A, Prohens J. et al. Successful wide hybridization and introgression breeding in a diverse set of common peppers (Capsicum annuum) using different cultivated Ají (C. baccatum) accessions as donor parents. PLoS One. 2015; 10:1-18

[3] Jeong HS, Jang S, Han K. et al. Marker-assisted backcross breeding for development of pepper varieties (Capsicum annuum)contain-ing capsinoids. Mol Breed. 2015; 35:1-10

[4] Wei J, Zheng J, Yu J. et al. Production and identification of inter-specific hybrids between pepper (Capsicum annuum L.) and the wild relative (Capsicum frutescens L.). J Agric Sci Technol. 2019; 21: 761-9

[5] Hulse-Kemp AM, Maheshwari S, Stoffel K. et al. Reference quality assembly of the 3.5-Gb genome of Capsicum annuum from a single linked-read library. Hortic Res. 2018; 5:4

[6] Barchi L, Pietrella M, Venturini L. et al. A chromosome-anchored eggplant genome sequence reveals key events in Solanaceae evolution. Sci Rep. 2019; 9:1-13

[7] Hosmani PS, Flores-Gonzalez M, van de Geest H. et al. An improved de novo assembly and annotation of the tomato ref-erence genome using single-molecule sequencing, Hi-C prox-imity ligation and optical maps. bioRxiv. 2019. https://doi.org/10.1101/767764

[8] Kim S, Park M, Yeom SI. et al. Genome sequence of the hot pepper provides insights into the evolution of pungency in Capsicum species. Nat Genet. 2014; 46:270-8

[9] Qin C, Yu C, Shen Y. et al. Whole-genome sequencing of culti-vated and wild peppers provides insights into Capsicum domes-tication and specialization. Proc Natl Acad Sci USA. 2014; 111: 5135-40

[10] Mohammadi M, Xavier A, Beckett T. et al. Identification, deploy-ment, and transferability of quantitative trait loci from genome-wide association studies in plants. Curr Plant Biol. 2020; 24:100145

[11] Mackay I, Powell W. Methods for linkage disequilibrium mapping in crops. Trends Plant Sci. 2007; 12:57-63

[12] Arrones A, Vilanova S, Plazas M. et al. The dawn of the age of multi-parent MAGIC populations in plant breeding: novel powerful next-generation resources for genetic analysis and selection of recombinant elite material. Biology (Basel). 2020; 9: 1-25

[13] Bandillo N, Raghavan C, Muyco PA. et al. Multi-parent advanced generation inter-cross (MAGIC) populations in rice: progress and potential for genetics research and breeding. Rice. 2013; 6: 1-15

[14] Mangino G, Arrones A, Plazas M. et al. Newly developed MAGIC population allows identification of strong associations and can-didate genes for anthocyanin pigmentation in eggplant. Front Plant Sci. 2022; 13:1-15

[15] Pascual L, Desplat N, Huang BE. et al. Potential of a tomato MAGIC population to decipher the genetic control of quantita-tive traits and detect causal variants in the resequencing era. Plant Biotechnol J. 2015; 13:565-77

[16] Arrones A, Mangino G, Alonso D. et al. Mutations in the SmAPRR2 transcription factor suppressing chlorophyll pigmentation in the eggplant fruit peel are key drivers of a diversified colour palette. Front Plant Sci. 2022; 13:1-14

[17] Dell’Acqua M, Gatti DM, Pea G. et al. Genetic properties of the MAGIC maize population: a new platform for high definition QTL mapping in Zea mays. Genome Biol. 2015; 16:167-23

[18] Mackay IJ, Bansept-Basler P, Bentley AR. et al. An eight-parent multiparent advanced generation inter-cross population for winter-sown wheat: creation, properties, and validation. G3 (Bethesda). 2014; 4:1603-10

[19] Huynh BL, Ehlers JD, Huang BE. et al. A multi-parent advanced generation inter-cross (MAGIC) population for genetic analysis and improvement of cowpea (Vigna unguiculata L. Walp.). Plant J. 2018; 93:1129-42

[20] ThudiM, SamineniS, LiW. et al. Whole genome resequencing and phenotyping of MAGIC population for high resolution map-ping of drought tolerance in chickpea. Plant Genome. 2024; 17: 1-16

[21] Leprévost T, Boutet G, Lesné A. et al. Advanced backcross QTL analysis and comparative mapping with RIL QTL studies and GWAS provide an overview of QTL and marker haplotype diver-sity for resistance to Aphanomyces root rot in pea (Pisum sativum). Front Plant Sci. 2023; 14:1189289

[22] Navara S, Smith KP. Using near-isogenic barley lines to validate deoxynivalenol (DON) QTL previously identified through associ-ation analysis. Theor Appl Genet. 2014; 127:633-45

[23] Jeong HB, Jang SJ, Kang MY. et al. Candidate gene analysis reveals that the fruit color locus C1 corresponds to PRR2 in pepper (Capsicum frutescens). Front Plant Sci. 2020; 11:1-14

[24] Zhou H, Li P, Xie W. et al. Genome-wide association analyses reveal the genetic basis of stigma exsertion in rice. Mol Plant. 2017; 10:634-44

[25] Rodionov AV, Amosova AV, Belyakov EA. et al. Genetic con-sequences of interspecific hybridization, its role in specia-tion and phenotypic diversity of plants. Russ J Genet. 2019; 55: 278-94

[26] Kumar D, Sharma S, Sharma R. et al. Genome-wide associa-tion study in hexaploid wheat identifies novel genomic regions associated with resistance to root lesion nematode (Pratylenchus thornei). Sci Rep. 2021; 11:1-14

[27] Sui YH, Hu NB. Acquisition, identification and analysis of an interspecific capsicum hybrid (C. annuum × C. chinense). JHortic Sci Biotechnol. 2015; 90:31-8

[28] Naves ER, Scossa F, Araújo WL. et al. Heterosis and reciprocal effects for agronomic and fruit traits in Capsicum pepper hybrids. Sci Hortic. 2022; 295:110821

[29] Naves ER, Scossa F, Araújo WL. et al. Heterosis for capsacinoids accumulation in chili pepper hybrids is dependent on parent-of-origin effect. Sci Rep. 2022; 12:14450

[30] Hayano-Kanashiro C, Gámez-Meza N, Medina-Juárez LÁ. Wild pepper Capsicum annuum L. var. glabriusculum: taxonomy, plant morphology, distribution, genetic diversity, genome sequencing, and phytochemical compounds. Crop Sci. 2016; 56:1-11

[31] Pereira-Dias L, Vilanova S, Fita A. et al. Genetic diversity, pop-ulation structure, and relationships in a collection of pepper (Capsicum spp.) landraces from the Spanish centre of diver-sity revealed by genotyping-by-sequencing (GBS). Hortic Res. 2019; 6:54

[32] Middleton R, Sinnott-Armstrong M, Ogawa Y. et al. Viburnum tinus fruits use lipids to produce metallic blue structural color. Curr Biol. 2020; 30:3804-3810.e2

[33] Rey P, Gillet B, Römer S. et al. Over-expression of a pepper plastid lipid-associated protein in tobacco leads to changes in plastid ultrastructure and plant development upon stress. Plant J. 2000; 21:483-94

[34] Fu H, Chao H, Zhao X. et al. Anthocyanins identification and transcriptional regulation of anthocyanin biosynthesis in purple Brassica napus. Plant Mol Biol. 2022; 110:53-68

[35] Wang R, Lu N, Liu C. et al. MtGSTF7, a TT19-like GST gene, is essential for accumulation of anthocyanins, but not proantho-cyanins in Medicago truncatula. JExp Bot. 2022; 73:4129-46

[36] Lopez-Moreno H, Basurto-Garduño AC, Torres-Meraz MA. et al. Genetic analysis and QTL mapping of domestication-related traits in chili pepper (Capsicum annuum L.). Front Genet. 2023; 14: 1-13

[37] Chunthawodtiporn J, Hill T, Stoffel K. et al. Quantitative trait loci controlling fruit size and other horticultural traits in bell pepper (Capsicum annuum). Plant Genome. 2018; 11:1-11

[38] Moles AT, Laffan SW, Keighery M. et al. A hairy situa-tion: Plant species in warm, sunny places are more likely to have pubescent leaves. Am J Bot. 2017; 104:174-86

[39] Guo G, Wang S, Liu J. et al. Rapid identification of QTLs under-lying resistance to cucumber mosaic virus in pepper (Capsicum frutescens). Theor Appl Genet. 2017; 130:41-52

[40] Aruna TS, Srivastava A, Tomar BS. et al. Genetic analysis of heat tolerance in hot pepper: insights from comprehensive pheno-typing and QTL mapping. Front Plant Sci. 2023; 14:1-18

[41] Sudheeran PK, Feygenberg O, Maurer D. et al. Improved cold tolerance of mango fruit with enhanced anthocyanin and flavonoid contents. Molecules. 2018; 23:2

[42] Eggink PM, Tikunov Y, Maliepaard C. et al. Capturing flavors from Capsicum baccatum by introgression in sweet pepper. Theor Appl Genet. 2014; 127:373-90

[43] Wu Y, Popovsky-Sarid S, Tikunov Y. et al. CaMYB12-like underlies a major QTL for flavonoid content in pepper (Capsicum annuum) fruit. New Phytol. 2023; 237:2255-67

[44] Zhang RX, Cheng GX, Liu GT. et al. Assessing the functional role of color-related CaMYB gene under cold stress using virus-induced gene silencing in the fruit of pepper (Capsicum annuum L.). Sci Hortic. 2020; 272:109504

[45] Liu J, Ai X, Wang Y. et al. Fine mapping of the Ca3GT gene controlling anthocyanin biosynthesis in mature unripe fruit of Capsicum annuum L. Theor Appl Genet. 2020; 133:2729-42

[46] Brand A, Borovsky Y, Meir S. et al. pc8.1, a major QTL for pigment content in pepper fruit, is associated with variation in plastid compartment size. Planta. 2012; 235:579-88

[47] Wei X, Meng C, Yuan Y. et al. CaPSY1 gene plays likely the key role in carotenoid metabolism of pepper (Capsicum annuum) at ripening. Funct Plant Biol. 2020; 48:141-55.

[48] ZhaiZ, FengC, WangY. et al. Genome-wide identification of the xyloglucan endotransglucosylase/hydrolase (Xth) and polygalacturonase (pg) genes and characterization of their role in fruit softening of sweet cherry. Int J Mol Sci. 2021; 22: 12331

[49] Chaim AB, Paran I, Grube RC. et al. QTL mapping of fruit-related traits in pepper (Capsicum annuum). Theor Appl Genet. 2001; 102: 1016-28

[50] Islam K, Momo J, Rawoof A. et al. Integrated use of molecular and omics approaches for breeding high yield and stress resistance chili peppers. In: Singh S, Sharma D, Kumar S, Rajender S,eds. Smart plant breeding for vegetable crops in post-genomics era. Springer: Singapore, 2023,279-335

[51] Pereira-Dias L, Gil-Villar D, Castell-Zeising V. et al. Main root adaptations in pepper germplasm (Capsicum spp.) to phosphorus low-input conditions. Agronomy. 2020; 10:637

[52] Ribes-Moya AM, Raigón MD, Moreno-Peris E. et al. Response to organic cultivation of heirloom Capsicum peppers: variation in the level of bioactive compounds and effect of ripening. PLoS One. 2018; 13:e0207888

[53] Rodríguez-Burruezo A, Prohens J, Raigón MD. et al. Variation for bioactive compounds in ají (Capsicum baccatum L.) and rocoto (C. pubescens R. & P.) and implications for breeding. Euphytica. 2009; 170:169-81

[54] Moreno-Peris E, Cortés-Olmos C, Díez-Díaz M. et al. Hybridization in peppers (Capsicum spp.) to improve the volatile composition in fully ripe fruits: the effects of parent combinations and fruit tissues. Agronomy. 2020; 10:751

[55] Rodríguez-Burruezo A, Kollmannsberger H, González-Mas MC. et al. HS-SPME comparative analysis of genotypic diversity in the volatile fraction and aroma-contributing compounds of Cap-sicum fruits from the annuum-chinense-frutescens complex. J Agric Food Chem. 2010; 58:4388-400

[56] Devi J, Sagar V, Kaswan V. et al. Advances in breeding strategies of bell pepper (Capsicum annuum L. var. grossum Sendt.). In: Al-Khayri JM, Jain SM, Johnson DV, eds. Advances in plant breeding strategies:vegetable crops. Cham: Springer, 2021,3-58

[57] Tanksley SD, Iglesias-Olivas J. Inheritance and transfer of multiple-flower character from Capsicum chinense into Capsicum annuum. Euphytica. 1984; 33:769-77

[58] Uncu AT. Genome-wide identification of simple sequence repeat (SSR) markers in Capsicum chinense Jacq. with high potential for use in pepper introgression breeding. Biologia (Bratisl). 2019; 74: 119-26

[59] International Plant Genetic Resources Institute (IPGRI). Descrip-tors for Capsicum (Capsicum spp.). Rome, Italy: Internation Plant Genetics Resources Institute, 1995

[60] Rodriguez-riano T, Dafni A. New procedure assess pollen viabil-ity. Sex Plant Reprod. 2000; 12:241-4

[61] Díez MJ, Andrés C, Terrab A. Physicochemical parameters and pollen analysis of Moroccan honeydew honeys. Int J Food Sci Technol. 2004; 39:167-76

[62] RCoreTeam. R: a language and environment for statistical computing. Vienna, Austria: R Found Stat Comput, 2015

[63] Wickham H. ggplot2: elegant graphics for data analysis. Cham: Springer, 2016

[64] Vilanova S, Alonso D, Gramazio P. et al. SILEX: a fast and inexpensive high-quality DNA extraction method suitable for multiple sequencing platforms and recalcitrant plant species. Plant Methods. 2020; 16:110

[65] Elshire RJ, Glaubitz JC, Sun Q. et al.A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One. 2011; 6:e19379

[66] Murray KD, Borevitz JO. Axe: rapid, competitive sequence read demultiplexing using a trie. Bioinformatics. 2018; 34: 3924-5

[67] Li H. Aligning sequence reads, clone sequences and assem-bly contigs with BWA-MEM. Genomics. 2013. https://arxiv.org/abs/1303.3997

[68] Depristo MA, Banks E, Poplin R. et al. A framework for variation discovery and genotyping using next-generation DNA sequenc-ing data. Nat Genet. 2011; 43:491-8

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

[70] Pook T, Schlather M, De Los Campos G. et al. Haploblocker: creation of subgroup-specific haplotype blocks and libraries. Genetics. 2019; 212:1045-61

[71] Li H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter esti-mation from sequencing data. Bioinformatics. 2011; 27:2987-93

[72] Chang CC, Chow CC, Tellier LCAM. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:s13742-015-0047-8

[73] Zheng X, Levine D, Shen J. et al. A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics. 2012; 28:3326-8

[74] Minh BQ, Schmidt HA, Chernomor O. et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020; 37:1530-4

[75] Mussmann SM, Douglas MR, Chafin TK. et al. AdmixPipe: pop-ulation analyses in admixture for non-model organisms. BMC Bioinformatics. 2020; 21:337

[76] Behr AA, Liu KZ, Liu-Fang G. et al. pong: fast analysis and visualization of latent clusters in population genetic data. Bioin-formatics. 2016; 32:2817-23

[77] Wang J, Zhang Z. GAPIT version 3: boosting power and accu-racy for genomic association and prediction. Genomics, Proteomics Bioinformatics. 2021; 19:629-40

[78] Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B. 1995; 57:289-300

[79] Zhang C, Dong SS, Xu JY. et al. PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics. 2019; 35:1786-8

[80] Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010; 26:841-2