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High-depth resequencing of 312 accessions reveals the local adaptation of foxtail millet

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Abstract

Key message

Based on the high-density variation map, we identified genome-level evidence for local adaptation and demonstrated that Siprr37 with transposon insertion contributes to the fitness of foxtail millet in the northeastern ecoregion.

Abstract

Adaptation is a robust way through which plants are able to overcome environmental constraints. The mechanisms of adaptation in heterogeneous natural environments are largely unknown. Deciphering the genomic basis of local adaptation will contribute to further improvement in domesticated plants. To this end, we describe a high-depth (19.4 ×) haplotype map of 3.02 million single nucleotide polymorphisms in foxtail millet (Setaria italica) from whole-genome resequencing of 312 accessions. In the genome-wide scan, we identified a set of improvement signals (including the homologous gene of OsIPA1, a key gene controlling ideal plant architecture) related to the geographical adaptation to four ecoregions in China. In particular, based on the genome-wide association analysis results, we identified the contribution of a pseudo-response regulator gene, SiPRR37, to heading date adaptation in foxtail millet. We observed the expression changes of SiPRR37 resulted from a key Tc1–Mariner transposon insertion in the first intron. Positive selection analyses revealed that SiPRR37 mainly contributed to the adaptation of northeastern ecoregions. Taken together, foxtail millet adapted to the northeastern region by regulating the function of SiPRR37, which sheds lights on genome-level evidence for adaptive geographical divergence. Besides, our data provide a nearly complete catalog of genomic variation aiding the identification of functionally important variants.

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Acknowledgements

This work was supported by Grants from the National Key R&D Program of China (2018YFD1000706/2018YFD1000700), the Beijing Municipal Natural Science Foundation (6202011), the China Postdoctoral Science Foundation (Grant No. 2019M650555), the Beijing Postdoctoral Research Foundation (Agreement No. 2018–ZZ–054), Key Research & Development Plan of Hebei Province (19226378D) and HAAFS Agriculture Science and Technology Innovation Project (2019-4-2).

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  1. Congcong Li and Genping Wang have contributed equally to this work.

Authors and Affiliations

  1. Beijing Agro-Biotechnology Research Center, Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China

    Congcong Li, Guoliang Wang, Xin Zhao, Linhe Huo, Liquan Zhang, Jiewei Zhang, Guiming Liu, Jianhua Wei & Lei Yao

  2. Institute of Millet Crops, Key Laboratory of Minor Crops in Hebei Province, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, 050035, China

    Genping Wang, Haiquan Li, Yanmiao Jiang, Guoqing Liu & Ruhong Cheng

  3. Beijing Vegetable Research Center, Beijing Key Laboratory of Vegetable Germplasms Improvement, National Engineering Research Center for Vegetables, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China

    Jian Ma

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  1. Congcong Li
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Contributions

JW and LY designed the research. CL, GW, JW and LY wrote the paper. XZ, YJ and LZ provided DNAs and collected the phenotype data. JM, CL, GW, HL, GW, LH, JZ, G-ML, G-QL and RC performed the population analysis and were involved in many discussion.

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Correspondence to Jianhua Wei or Lei Yao.

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Communicated by Hai-Chun Jing.

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Supplementary file1 (DOC 58 kb)

Supplementary Fig. S1

The geographic distribution of the 299 accessions by province of origin in China and the eight worldwide germplasm samples by country of origin. Bubble sizes are proportional to the number of accessions.

Supplementary Fig. S2

Sequencing depth of the 312 accessions.

Supplementary Fig. S3

Population structure analysis of all accessions using the program Admixture. (a) The cross-validation error estimate plotted for the population structure shows the optimal number of subpopulations at K = 8. (b) Different numbers of landraces and cultivars in the eight clades. (c) Genetic structure analysis based on different numbers of clusters. Different colors represent different ancestral populations. Each accession is represented by a vertical bar, and the length of each colored segment in each vertical bar represents the proportion contributed by ancestral populations.

Supplementary Fig. S4

Decay of LD in all accessions, landraces and improved cultivars.

Supplementary Fig. S5

Manhattan and quantile–quantile plots resulting from GWAS of two bioclimatic variables based on whole-genomic SNPs. (a) Annual mean temperature; (b) annual precipitation. Gray horizontal dashed lines indicate 1% Bonferroni-corrected genome-wide significance thresholds.

Supplementary Fig. S6

Manhattan and quantile–quantile plots resulting from GWAS of heading date based on whole-genomic SNPs. Gray horizontal dashed lines indicate 1% Bonferroni-corrected genome-wide significance thresholds.

Supplementary Fig. S7

Structural representation of the Tc1–Mariner transposon insertion and SiPRR37 haplotypes. (a) Structural representation of the Tc1–Mariner transposon at SiPRR37 locus. Picture is scaled except for the terminal inverted repeats and target site duplication. (b) Two haplotypes of SiPRR37 with or without Tc1–Mariner transposon.

Supplementary Fig. S8

The relationship of SiPRR37 and homologous genes in crops by unrooted phylogenetic tree analysis. Numbers at the branches indicate percentage of 1000 bootstrap replicates. The scale bar at the bottom represents genetic distance. The protein sequences were downloaded from Phytozome (https://phytozome.jgi.doe.gov/pz/portal.html#). The accession numbers: OsPRR37 (LOC_Os07g49460), Ppd-H1 (HORVU2Hr1G013400), Ppd-D1a (Traes_2DS_2A961F39D), AtPRR7 (AT5G02810), SbPRR37 (Sobic.006G057866) and GmPRR37 (Glyma.12G073900).

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Li, C., Wang, G., Li, H. et al. High-depth resequencing of 312 accessions reveals the local adaptation of foxtail millet. Theor Appl Genet 134, 1303–1317 (2021). https://doi.org/10.1007/s00122-020-03760-4

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