Resequencing of sweetpotato germplasm resources reveals key loci associated with multiple agronomic traits

Shizhuo Xiao , Xibin Dai , Lingxiao Zhao , Zhilin Zhou , Lukuan Zhao , Pan Xu , Bingqian Gao , An Zhang , Donglan Zhao , Rui Yuan , Yao Wang , Jie Wang , Qinglian Li , Qinghe Cao

Horticulture Research ›› 2023, Vol. 10 ›› Issue (1) : 234

PDF (2246KB)
Horticulture Research ›› 2023, Vol. 10 ›› Issue (1) :234 DOI: 10.1093/hr/uhac234
Article
research-article
Resequencing of sweetpotato germplasm resources reveals key loci associated with multiple agronomic traits
Author information +
History +
PDF (2246KB)

Abstract

Sweetpotato is an important crop that exhibits hexaploidy and high heterozygosity, which limits gene mining for important agronomic traits. Here, 314 sweetpotato germplasm resources were deeply resequenced, and 4 599 509 SNPs and 846 654 InDels were generated, among which 196 124 SNPs were nonsynonymous and 9690 InDels were frameshifted. Based on the Indels, genome-wide marker primers were designed, and 3219 of 40 366 primer pairs were selected to construct the core InDel marker set. The molecular ID of 104 sweetpotato samples verified the availability of these primers. The sweetpotato population structures were then assessed through multiple approaches using SNPs, and diverse approaches demonstrated that population stratification was not obvious for most Chinese germplasm resources. As many as 20 important agronomic traits were evaluated, and a genome-wide association study was conducted on these traits. A total of 19 high-confidence loci were detected in both models. These loci included several candidate genes, such as IbMYB1, IbZEP1, and IbYABBY1, which might be involved in anthocyanin metabolism, carotenoid metabolism, and leaf morphogenesis, respectively. Among them, IbZEP1 and IbYABBY1 were first reported in sweetpotato. The variants in the promoter and the expression levels of IbZEP1 were significantly correlated with flesh color (orange or not orange) in sweetpotato. The expression levels of IbYABBY1 were also correlated with leaf shape. These results will assist in genetic and breeding studies in sweetpotato.

Cite this article

Download citation ▾
Shizhuo Xiao, Xibin Dai, Lingxiao Zhao, Zhilin Zhou, Lukuan Zhao, Pan Xu, Bingqian Gao, An Zhang, Donglan Zhao, Rui Yuan, Yao Wang, Jie Wang, Qinglian Li, Qinghe Cao. Resequencing of sweetpotato germplasm resources reveals key loci associated with multiple agronomic traits. Horticulture Research, 2023, 10 (1) : 234 DOI:10.1093/hr/uhac234

登录浏览全文

4963

注册一个新账户 忘记密码

Acknowledgements

This work was supported by the National Key Research & Development Program of China (2018YFD1000705/2018YFD1000700), the Natural Science Foundation of Jiangsu Province of China (BK20221213), and the China Agriculture Research System (CARS-10-GW01). We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

Author contributions

Q.C. and S.X. designed the study. S.X. conducted the data analysis and wrote the manuscript. X.D. prepared materials for genome resequencing and investigated aboveground agronomic traits. Li.Z. measured most physiological traits. Lu.Z. verified the molecular markers by electrophoresis. Z.Z., B.G., A.Z., D.Z., R.Y., J.W., Y.W., and Q.L. participated in the planting, phenotyping, reaping, storage, and transport of plant materials. P.X. assisted with data analysis. Q.C. supervised the research and the manuscript. All authors read and approved the manuscript.

Data availability

The sequence read archives of 314 samples were deposited in the NCBI database (Accession No. PRJNA857483). The SNP dataset and the phenotype data were deposited in a publicly available database (https://zenodo.org/) and can be accessed via the DOI number (10.5281/zenodo.7184909).

Conflict of interest

The authors declare that they have no conflicts of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

References

[1]

FAOSTAT. Vol. 2021 (2019).

[2]

Zierer W, Ruscher D, Sonnewald U, Sonnewald S . Tuber and tuberous root development. Annu Rev Plant Biol. 2021; 72: 551-80.

[3]

Liu Q . Improvement for agronomically important traits by gene engineering in sweetpotato. Breed Sci. 2017; 67: 15-26.

[4]

Srisuwan S, Sihachakr D, Siljak-Yakovlev S . The origin and evolution of sweet potato (Ipomoea batatas lam.) and its wild relatives through the cytogenetic approaches . Plant Sci. 2006; 171: 424-33.

[5]

Nishiyama I, Miyazaki T, Sakamoto S . Evolutionary autoploidy in the sweet potato (Ipomoea batatas (L.) lam.) and its progenitors . Euphytica. 1975; 24: 197-208.

[6]

Magoon ML, Krishnan R, Vijaya BK . Cytological evidence on the origin of sweet potato. Theor Appl Genet. 1970; 40: 360-6.

[7]

Wu S, Lau KH, Cao Q et al. Genome sequences of two diploid wild relatives of cultivated sweetpotato reveal targets for genetic improvement. Nat Commun. 2018; 9: 4580.

[8]

Yang J, Moeinzadeh MH, Kuhl H et al. Haplotype-resolved sweet potato genome traces back its hexaploidization history. Nature Plants. 2017; 3: 696-703.

[9]

Hoshino A, Jayakumar V, Nitasaka E et al. Genome sequence and analysis of the Japanese morning glory Ipomoea nil. Nat Commun. 2016; 7: 13295.

[10]

Isobe S, Shirasawa K, Hirakawa H . Current status in whole genome sequencing and analysis of ipomoea spp. Plant Cell Rep. 2019; 38: 1365-71.

[11]

Yoon U, Jeong JC, Kwak SS et al. Current status of sweetpotato genomics research. Journal of Plant Biotechnology. 2015; 42: 161-7.

[12]

Yan M, Nie H, Wang Y et al. Exploring and exploiting genetics and genomics for sweetpotato improvement: status and perspectives. Plant communications. 2022; 3: 100332.

[13]

Zhao N, Yu X, Jie Q et al. A genetic linkage map based on AFLP and SSR markers and mapping of QTL for dry-matter content in sweetpotato. Mol Breed. 2013; 32: 807-20.

[14]

Easton DF, Pooley KA, Dunning AM et al. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature. 2007; 447: 1087-93.

[15]

Li W, Zhu Z, Chern M et al. A natural allele of a transcription factor in rice confers broad-spectrum blast resistance. Cell. 2017; 170: 114-126.e15.

[16]

Johnston SE, McEwan JC, Pickering NK et al. Genome-wide association mapping identifies the genetic basis of discrete and quantitative variation in sexual weaponry in a wild sheep population. Mol Ecol. 2011; 20: 2555-66.

[17]

Meng Y, Zhao N, Li H et al. SSR fingerprinting of 203 sweetpotato (Ipomoea batatas (L.) lam.) varieties. J Integr Agric. 2018; 17: 86-93.

[18]

Yu J, Pressoir G, Briggs WH et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet. 2006; 38: 203-8.

[19]

Yan H, Pei X, Zhang H et al. MYB-mediated regulation of anthocyanin biosynthesis. Int J Mol Sci. 2021; 22: 3103.

[20]

Tanaka M, Takahata Y, Kurata R et al. Structural and functional characterization of IbMYB1 genes in recent Japanese purple-fleshed sweetpotato cultivars . Mol Breed. 2012; 29: 565-74.

[21]

Mano H, Ogasawara F, Sato K et al. Isolation of a regulatory gene of anthocyanin biosynthesis in tuberous roots of purple-fleshed sweet potato. Plant Physiol. 2007; 143: 1252-68.

[22]

Zhang L, Yu Y, Shi T et al. Genome-wide analysis of expression quantitative trait loci (eQTLs) reveals the regulatory architecture of gene expression variation in the storage roots of sweet potato. Hortic Res. 2020; 7: 90.

[23]

Haque E, Yamamoto E, Shirasawa K et al. Genetic analyses of anthocyanin content using polyploid GWAS followed by QTL detection in the sweetpotato (Ipomoea batatas L.) storage root . Plant Root. 2020; 14: 11-21.

[24]

Nisar N, Li L, Lu S et al. Carotenoid metabolism in plants. Mol Plant. 2015; 8: 68-82.

[25]

Giuliano G, Tavazza R, Diretto G et al. Metabolic engineering of carotenoid biosynthesis in plants. Trends Biotechnol. 2008; 26: 139-45.

[26]

Kumaran MK, Bowman JL, Sundaresan V . YABBY polarity genes mediate the repression of KNOX homeobox genes in Arabidopsis . Plant Cell. 2002; 14: 2761-70.

[27]

Sarojam R, Sappl PG, Goldshmidt A et al. Differentiating Arabidopsis shoots from leaves by combined YABBY activities. Plant Cell. 2010; 22: 2113-30.

[28]

Choi Y, Chan AP . PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics. 2015; 31: 2745-7.

[29]

Siegfried KR, Eshed Y, Baum SF et al. Members of the YABBY gene family specify abaxial cell fate in Arabidopsis . Development. 1999; 126: 4117-28.

[30]

Wu J, Wang L, Fu J et al. Resequencing of 683 common bean genotypes identifies yield component trait associations across a north-south cline. Nat Genet. 2020; 52: 118-25.

[31]

Zhang K, He M, Fan Y et al. Resequencing of global Tartary buckwheat accessions reveals multiple domestication events and key loci associated with agronomic traits. Genome Biol. 2021; 22: 23.

[32]

Monden Y, Tahara M . Genetic linkage analysis using DNA markers in sweetpotato. Breed Sci. 2017; 67: 41-51.

[33]

Su W, Wang L, Lei J et al. Genome-wide assessment of population structure and genetic diversity and development of a core germplasm set for sweet potato based on specific length amplified fragment (SLAF) sequencing. PLoS One. 2017; 12: e0172066.

[34]

Liu D, Zhao N, Zhai H et al. AFLP fingerprinting and genetic diversity of main sweetpotato varieties in China. J Integr Agric. 2012; 11: 1424-33.

[35]

Cervantes-Flores JC, Sosinski B, Pecota KV et al. Identification of quantitative trait loci for dry-matter, starch, and β-carotene content in sweetpotato. Mol Breed. 2011; 28: 201-16.

[36]

Haque E, Tabuchi H, Monden Y et al. QTL analysis and GWAS of agronomic traits in sweetpotato (Ipomoea batatas L.) using genome wide SNPs . Breed Sci. 2020; 70: 283-91.

[37]

Gemenet DC, da Silva Pereira G, de Boeck B et al. Quantitative trait loci and differential gene expression analyses reveal the genetic basis for negatively associated beta-carotene and starch content in hexaploid sweetpotato [ Ipomoea batatas (L.) lam.] . Theor Appl Genet. 2020; 133: 23-36.

[38]

Kim HS, Ji CY, Lee CJ et al. Orange: a target gene for regulating carotenoid homeostasis and increasing plant tolerance to environmental stress in marginal lands. J Exp Bot. 2018; 69: 3393-400.

[39]

Suematsu K, Tanaka M, Kurata R, Kai Y . Comparative transcriptome analysis implied a ZEP paralog was a key gene involved in carotenoid accumulation in yellow-fleshed sweetpotato . Sci Rep. 2020; 10: 20607.

[40]

Bouvier F, d’Harlingue A, Hugueney P et al. Xanthophyll biosynthesis. Cloning, expression, functional reconstitution, and regulation of beta-cyclohexenyl carotenoid epoxidase from pepper (Capsicum annuum). J Biol Chem. 1996; 271: 28861-7.

[41]

Gonzalez-Jorge S, Mehrshahi P, Magallanes-Lundback M et al. ZEAXANTHIN EPOXIDASE activity potentiates carotenoid degradation in maturing seed. Plant Physiol. 2016; 171: 1837-51.

[42]

Romer S, Lübeck J, Kauder F et al. Genetic engineering of a zeaxanthin-rich potato by antisense inactivation and cosuppression of carotenoid epoxidation. Metab Eng. 2002; 4: 263-72.

[43]

Lee SY, Jang SJ, Jeong HB et al. A mutation in zeaxanthin epoxidase contributes to orange coloration and alters carotenoid contents in pepper fruit (Capsicum annuum). Plant J. 2021; 106: 1692-707.

[44]

Liu Y, Ye S, Yuan G et al. Gene silencing of BnaA09.ZEP and BnaC09.ZEP confers orange color in Brassica napus flowers . Plant J. 2020; 104: 932-49.

[45]

Karniel U, Koch A, Zamir D, Hirschberg J . Development of zeaxanthin-rich tomato fruit through genetic manipulations of carotenoid biosynthesis. Plant Biotechnol J. 2020; 18: 2292-303.

[46]

Gupta S, Rosenthal DM, Stinchcombe JR, Baucom RS . The remarkable morphological diversity of leaf shape in sweet potato (Ipomoea batatas): the influence of genetics, environment, and GxE . New Phytol. 2020; 225: 2183-95.

[47]

Chen M, Fan W, Ji F et al. Genome-wide identification of agronomically important genes in outcrossing crops using OutcrossSeq. Mol Plant. 2021; 14: 556-70.

[48]

Juliana P, Poland J, Huerta-Espino J et al. Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics. Nat Genet. 2019; 51: 1530-9.

[49]

Ma Z, He S, Wang X et al. Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield. Nat Genet. 2018; 50: 803-13.

[50]

Sasai R, Tabuchi H, Shirasawa K et al. Development of molecular markers associated with resistance to Meloidogyne incognita by performing quantitative trait locus analysis and genome-wide association study in sweetpotato. DNA Res. 2019; 26: 399-409.

[51]

Okada Y, Monden Y, Nokihara K et al. Genome-wide association studies (GWAS) for yield and weevil resistance in sweet potato (Ipomoea batatas (L.) lam). Plant Cell Rep. 2019; 38: 1383-92.

[52]

Bararyenya A, Olukolu BA, Tukamuhabwa P et al. Genome-wide association study identified candidate genes controlling continuous storage root formation and bulking in hexaploid sweetpotato. BMC Plant Biol. 2020; 20: 3.

[53]

Liu Y, Pan R, Zhang W et al. Integrating genome-wide association study with transcriptomic analysis to predict candidate genes controlling storage root flesh color in sweet potato. Agronomy. 2022; 12: 991.

[54]

Langmead B, Salzberg SL . Fast gapped-read alignment with bowtie 2. Nat Methods. 2012; 9: 357-9.

[55]

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

[56]

McKenna A, Hanna M, Banks E et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010; 20: 1297-303.

[57]

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

[58]

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

[59]

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

[60]

Chow CN, Lee TY, Hung YC et al. PlantPAN3.0: a new and updated resource for reconstructing transcriptional regulatory networks from ChIP-seq experiments in plants. Nucleic Acids Res. 2019; 47: D1155-63.

[61]

Koressaar T, Remm M . Enhancements and modifications of primer design program Primer3. Bioinformatics. 2007; 23: 1289-91.

[62]

Price MN, Dehal PS, Arkin AP . FastTree 2-approximately maximum-likelihood trees for large alignments. PLoS One. 2010; 5: e9490.

[63]

Alexander DH, Lange K . Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics. 2011; 12: 246.

[64]

Francis RM . Pophelper: an R package and web app to analyse and visualize population structure. Mol Ecol Resour. 2017; 17: 27-32.

[65]

Yin L, Zhang H, Tang Z et al. rMVP: a memory-efficient, visualization-enhanced, and parallel-accelerated tool for genome-wide association study. Genomics Proteomics Bioinformatics. 2021; 19: 619-28.

[66]

Saitou N, Nei M . The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol. 1987; 4: 406-25.

[67]

Park SC, Kim YH, Ji CY et al. Stable internal reference genes for the normalization of real-time PCR in different sweet-potato cultivars subjected to abiotic stress conditions. PLoS One. 2012; 7: e51502.

PDF (2246KB)

68

Accesses

0

Citation

Detail

Sections
Recommended

/