The Duck 1000 Genomes Project: Achievements and perspectives

Abstract

The duck (Anas platyrhynchos) is not only a vital farm animal but also an excellent model for genetic dissection of economic traits. The integration of multiomics data provides a powerful approach to elucidate the genetic basis of domestication and phenotype variation. Since its inception in 2014, the Duck 1000 Genomes Project has aimed to uncover the genetic foundation of key economic traits in ducks by combining multiomics data including genomic, transcriptomic, and metabolomic from various natural and segregating populations. This paper summarizes the strategies and achievements of the Duck 1000 Genomes Project, highlighting the reference genome assembly, genome evolution analysis, and the identification of genes and causative mutations responsible for key economic traits in ducks. We also discuss perspectives and potential challenges in functional genomic studies that could further accelerate duck molecular breeding.

Keywords

domestication / duck / genetic dissection / multi-omics

References

[1] Zhou, Z., Li, M., Cheng, H., Fan, W., Yuan, Z., Gao, Q., Jiang, Y., Guo, Z., Zhang, Y., Hu, J., Liu, H., Liu, D., Chen, W., Zheng, Z., Wen, Z., Liu, Y., Chen, H., & Xie, M. (2018). An intercross population study reveals genes associated with body size and plumage color in ducks. Nature Communications, 9(1), 2648.

[2] Zhang, Z., Jia, Y., Almeida, P., Mank, J. E., van Tuinen, M., Wang, Q., Qu, L., Chen, Y., Zhan, K., Hou, S., Zhou, Z., Li, H., Yang, F., He, Y., Ning, Z., & Yang, N. (2018). Whole-genome resequencing reveals signatures of selection and timing of duck domestication. GigaScience, 7(4), giy027.

[3] Zhu, F., Yin, Z., Wang, Z., Smith, J., Zhang, F., Martin, F., Hou, Z., Hincke, M., Lin, F. B., Burt, D. W., Zhou, Z. K., Hou, S. S., Zhao, Q. S., Li, X. Q., Ding, S. R., Li, G. S., Yang, F. X., Hao, J. P., & Zhang, Z. (2021). Three chromosome-level duck genome assemblies provide insights into genomic variation during domestication. Nature Communications, 12(1), 5932.

[4] Jansen, R. C., & Jan-Peter, N. (2001). Genetical genomics: The added value from segregation. Trends in Genetics, 17(7), 388–391.

[5] Tan, X., He, Z., Fahey, A. G., Zhao, G., Liu, R., & Wen, J. (2023). Research progress and applications of genome-wide association study in farm animals. Animal Research and One Health, 1(1), 56–77.

[6] Zhang, H., Wang, Z., Wang, S., & Li, H. (2012). Progress of genome wide association study in domestic animals. Journal of Animal Science and Biotechnology, 3(1–10), 26.

[7] Clark, E. L., Archibald, A. L., Daetwyler, H. D., Groenen, M. A. M., Harrison, P. W., Houston, R. D., Giuffra, E., Lien, S., Macqueen, D. J., Reecy, J. M., Robledo, D., Watson, M., & Tuggle, C. K. (2020). From FAANG to fork: Application of highly annotated genomes to improve farmed animal production. Genome Biology, 21(1), 285.

[8] Li, J., Zhang, J., Liu, J., Zhou, Y., Cai, C., Xu, L., Zhou, Q., Feng, S., Guo, C., Rao, J., Wei, K., Jarvis, E. D., Jiang, Y., Zhou, Z., & Zhang, G. (2021). A new duck genome reveals conserved and convergently evolved chromosome architectures of birds and mammals. GigaScience, 10(1).

[9] Li, M., Sun, C., Xu, N., Bian, P., Tian, X., Wang, X., Yang, N., Jia, X., Heller, R., Wang, M., Wang, F., Dai, X., Luo, R., Guo, Y., Yang, P., Hu, D., Liu, Z., & Fu, W. (2022). De novo assembly of 20 chicken genomes reveals the undetectable phenomenon for thousands of core genes on micro-chromosomes and sub-telomeric regions. Molecular Biology and Evolution, 39(4), msac066.

[10] Georges, M., Charlier, C., & Hayes, B. (2019). Harnessing genomic information for livestock improvement. Nature Reviews Genetics, 20(3), 135–156.

[11] Huang, Z., Xu, Z., Bai, H., Huang, Y., Kang, N., Ding, X., Xu, L., Luo, H., Yang, C., Chen, W., Guo, Q., Xue, L., Zhang, X., Chen, M., Fu, H., Chen, Y., Yue, Z., & Fukagawa, T. (2023). Evolutionary analysis of a complete chicken genome. Proceedings of the National Academy of Sciences of the United States of America, 120(8), e2216641120.

[12] Li, H., & Durbin, R. (2024). Genome assembly in the telomere-to-telomere era. Nature Reviews Genetics, 25(9), 658–670.

[13] Nurk, S., Koren, S., Rhie, A., Rautiainen, M., Bzikadze, A. V., Mikheenko, A., Phillippy, A. M., Altemose, N., Uralsky, L., Gershman, A., Aganezov, S., Hoyt, S. J., Diekhans, M., Logsdon, G. A., Alonge, M., Antonarakis, S. E., Borchers, M., Bouffard, G. G., & Brooks, S. Y. (2022). The complete sequence of a human genome. Science, 376(6588), 44–53.

[14] Tam, V., Patel, N., Turcotte, M., Bosse, Y., Pare, G., & Meyre, D. (2019). Benefits and limitations of genome-wide association studies. Nature Reviews Genetics, 20(8), 467–484.

[15] Goddard, M. E., & Hayes, B. J. (2009). Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Reviews Genetics, 10(6), 381–391.

[16] Schaid, D. J., Chen, W., & Larson, N. B. (2018). From genome-wide associations to candidate causal variants by statistical fine-mapping. Nature Reviews Genetics, 19(8), 491–504.

[17] Tan, X., Liu, R., Zhao, D., He, Z., Li, W., Zheng, M., Wen, J., Wang, Q., Liu, D., Feng, F., Zhu, D., & Zhao, G. (2024). Large-scale genomic and transcriptomic analyses elucidate the genetic basis of high meat yield in chickens. Journal of Advanced Research, 55, 1–16.

[18] Li, X., Yang, J., Shen, M., Xie, X. L., Liu, G. J., Xu, Y. X., Li, M. H., Yang, H., Yang, Y. L., Liu, C. B., Zhou, P., Wan, P. C., Zhang, Y. S., Gao, L., Pi, W. H., Ren, Y. L., Shen, Z. Q., & Wang, F. (2020). Whole-genome resequencing of wild and domestic sheep identifies genes associated with morphological and agronomic traits. Nature Communications, 11(1), 2815.

[19] Wang, K., Hu, H., Tian, Y., Li, J., Scheben, A., Zhang, C., Kang, X., Wu, J., Yang, L., Fan, X., Sun, G., Zhang, Y., Han, R., Jiang, R., Huang, H., Yan, F., Wang, Y., & Li, Z. (2021). The chicken pan-genome reveals gene content variation and a promoter region deletion in IGF2BP1 affecting body size. Molecular Biology and Evolution, 38(11), 5066–5081.

[20] Zhang, Y., Zhang, J., Gong, H., Cui, L., Zhang, W., Ma, J., Yang, B., Ai, H., Xiao, S., & Huang, L. (2019). Genetic correlation of fatty acid composition with growth, carcass, fat deposition and meat quality traits based on GWAS data in six pig populations. Meat Science, 150, 47–55.

[21] Hasin, Y., Seldin, M., & Lusis, A. (2017). Multi-omics approaches to disease. Genome Biology, 18(1), 83.

[22] Kang, M., Ko, E., & Mersha, T. B. (2022). A roadmap for multi-omics data integration using deep learning. Briefings in Bioinformatics, 23(1), bbab454.

[23] Verardo, L. L., Brito, L. F., Carolino, N., & Magalhães, A. F. B. (2023). Editorial: Omics applied to livestock genetics. Frontiers in Genetics, 14.

[24] Civelek, M., & Lusis, A. J. (2014). Systems genetics approaches to understand complex traits. Nature Reviews Genetics, 15(1), 34–48.

[25] Wang, D., Tan, L., Zhi, Y., Bu, L., Wang, Y., Wang, Z., Liu, X., Tian, W., Xu, C., Jiang, R., Han, R., Xia, D., Tian, Y., Dunn, I. C., & Hu, X. (2024). Genome-wide variation study and inter-tissue communication analysis unveil regulatory mechanisms of egg-laying performance in chickens. Nature Communications, 15(1), 7069.

[26] Liang, S., Zhang, J., Wang, X., Xing, G., Guo, Z., Zhang, Q., Hou, S., & Xie, M. (2023). Selective analysis of resistance and susceptibility to duck hepatitis A virus genotype 3 in Pekin duck. Animal Research and One Health, 1(2), 146–155.

[27] Zhu, G., Wang, S., Huang, Z., Zhang, S., Liao, Q., Zhang, C., Huang, S., Qin, M., Peng, M., Yang, C., Cao, X., Han, X., Wang, X., van der Knaap, E., Cui, X., Klee, H., Fernie, A. R., & Luo, J. (2018). Rewiring of the fruit metabolome in tomato breeding. Cell, 172(1–2), 249–261.e212.

[28] Fu, Y., Liu, H., Dou, J., Wang, Y., Liao, Y., Huang, X., Zhao, S., Xu, J., Yin, D., Zhu, S., Shen, X., Liu, J., Yang, X., Zhang, Y., Xiang, Y., Li, J., & Zheng, Z. (2023). IAnimal: A cross-species omics knowledgebase for animals. Nucleic Acids Research, 51(D1), D1312–D1324.

[29] Scott, M. F., Ladejobi, O., Amer, S., Bentley, A. R., Biernaskie, J., Boden, S. A., Mott, R., Dell’Acqua, M., Dixon, L. E., Filippi, C. V., Fradgley, N., Gardner, K. A., Mackay, I. J., O’Sullivan, D., Percival-Alwyn, L., Roorkiwal, M., Singh, R. K., Thudi, M., & Varshney, R. K. (2020). Multi-parent populations in crops: A toolbox integrating genomics and genetic mapping with breeding. Heredity, 125(6), 396–416.

[30] Li, Z., & Xu, Y. (2022). Bulk segregation analysis in the NGS era: A review of its teenage years. The Plant Journal, 109(6), 1355–1374.

[31] Zou, C., Wang, P., & Xu, Y. (2016). Bulked sample analysis in genetics, genomics and crop improvement. Plant Biotechnology Journal, 14(10), 1941–1955.

[32] Dong, J., He, C., Wang, Z., Li, Y., Li, S., Tao, L., Du, B., Yang, F., Zhang, Q., Zhang, L., Wang, G., Akinyemi, F., & Meng, H. (2018). A novel deletion in KRT75L4 mediates the frizzle trait in a Chinese indigenous chicken. Genetics Selection Evolution, 50(1), 68.

[33] Wang, Z., Qu, L., Yao, J., Yang, X., Li, G., Zhang, Y., Wu, C., Wang, X., Bai, J., Xu, G., Deng, X., & Yang, N. (2013). An EAV-HP insertion in 5’ flanking region of SLCO1B3 causes blue eggshell in the chicken. PLoS Genetics, 9(1), e1003183.

[34] Guo, Y., Tian, J., Song, C., Han, W., Zhu, C., Li, H., Hu, X., Chen, K., & Carlborg, Ö. (2023). Mapping and functional dissection of the rumpless trait in Piao chicken identifies a causal loss of function mutation in the novel gene rum. Molecular Biology and Evolution, 40(12), msad273.

[35] Dell’Acqua, M., Gatti, D. M., Pea, G., Cattonaro, F., Coppens, F., Magris, G., Pè M. E., Aung, H. H., Nelissen, H., Baute, J., Frascaroli, E., Churchill, G. A., Inzé D., & Morgante, M. (2015). Genetic properties of the MAGIC maize population: A new platform for high definition QTL mapping in Zea mays. Genome Biology, 16(1), 167.

[36] Houle, D., Govindaraju, D. R., & Omholt, S. (2010). Phenomics: The next challenge. Nature Reviews Genetics, 11(12), 855–866.

[37] Rhie, A., McCarthy, S. A., Fedrigo, O., Damas, J., Formenti, G., Koren, S., Uliano-Silva, M., Chow, W., Fungtammasan, A., Kim, J., Lee, C., Ko, B. J., Chaisson, M., Gedman, G. L., Cantin, L. J., Thibaud-Nissen, F., Haggerty, L., Bista, I., Smith, M., …, & Jarvis, E. D. (2021). Towards complete and error-free genome assemblies of all vertebrate species. Nature, 592(7856), 737–746.

[38] Hotaling, S., Kelley, J. L., & Frandsen, P. B. (2021). Toward a genome sequence for every animal: Where are we now? Proceedings of the National Academy of Sciences of the United States of America, 118(52), e2109019118.

[39] Huang, Y., Li, Y., Burt, D. W., Chen, H., Zhang, Y., Qian, W., Li, N., Gan, S., Zhao, Y., Li, J., Yi, K., Feng, H., Zhu, P., Li, B., Liu, Q., Fairley, S., Magor, K. E., Du, Z., & Hu, X. (2013). The duck genome and transcriptome provide insight into an avian influenza virus reservoir species. Nature Genetics, 45(7), 776–783.

[40] Rao, M., Morisson, M., Faraut, T., Bardes, S., Feve, K., Labarthe, E., Vignal, A., Huang, Y., & Vignal, A. (2012). A duck RH panel and its potential for assisting NGS genome assembly. BMC Genomics, 13(1), 513.

[41] Yu, S., Liu, Z., Li, M., Zhou, D., Hua, P., Cheng, H., Fan, W., Xu, Y., Liu, D., Liang, S., Zhang, Y., Xie, M., Tang, J., Jiang, Y., Hou, S., & Zhou, Z. (2023). Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection. GigaScience, 12, giad016.

[42] Chang, G., Yuan, X., Guo, Q., Bai, H., Cao, X., Liu, M., Chen, G., Li, B., Wang, S., Jiang, Y., Wang, Z., Zhang, Y., Xu, Q., Song, Q., Pan, R., Qiu, L., Gu, T., Wu, X., & Bi, Y. (2023). The first Crested duck genome reveals clues to genetic compensation and crest cushion formation. Genomics, Proteomics & Bioinformatics, 21(3), 483–500.

[43] Peona, V., Weissensteiner, M. H., & Suh, A. (2018). How complete are “complete” genome assemblies? An avian perspective. Molecular Ecology Resources, 18(6), 1188–1195.

[44] Chen, L., Qiu, Q., Jiang, Y., Wang, K., Lin, Z., Li, Z., Wang, W., Yang, Y., Wang, J., Nie, W., Su, W., Liu, G., Li, Q., Fu, W., Pan, X., Liu, C., Yang, J., Zhang, C., & Yin, Y. (2019). Large-scale ruminant genome sequencing provides insights into their evolution and distinct traits. Science, 364(6446), eaav6202.

[45] Pan, Z., Li, S., Liu, Q., Wang, Z., Zhou, Z., Di, R., Li, Y., Hu, W., Wang, X., Hu, X., Xu, Z., Wei, D., He, X., Yuan, L., Guo, X., Liang, B., Wang, R., Li, X., & Cao, X. (2018). Whole-genome sequences of 89 Chinese sheep suggest role of RXFP2 in the development of unique horn phenotype as response to semi-feralization. GigaScience, 7(4), giy019.

[46] Axelsson, E., Ratnakumar, A., Arendt, M. L., Maqbool, K., Webster, M. T., Perloski, M., Lindblad-Toh, K., Arnemo, J. M., & Hedhammar, Å. (2013). The genomic signature of dog domestication reveals adaptation to a starch-rich diet. Nature, 495(7441), 360–364.

[47] Lillie, M., Sheng, Z. Y., Honaker, C. F., Andersson, L., Siegel, P. B., & Carlborg, O. (2017). Genomic signatures of 60 years of bidirectional selection for 8-week body weight in chickens. Poultry Science, 97(3), 781–790.

[48] Zhang, H., Liang, Q., Wang, N., Wang, Q., Leng, L., Mao, J., Li, H., Wang, S., Zhang, J., Zhou, X., Li, Y., Cao, Z., Luan, P., Wang, Z., Yuan, H., Wang, Z., Zhou, X., & Lamont, S. J. (2020). Microevolutionary dynamics of chicken genomes under divergent selection for adiposity. iScience, 23(6), 101193.

[49] Wang, K., Hua, G., Li, J., Yang, Y., Zhang, C., Yang, L., Li, W., Scheben, A., Wu, Y., Gong, P., Zhang, S., Fan, Y., Zeng, T., Lu, L., Gong, Y., Jiang, R., Sun, G., Tian, Y., & Kang, X. (2023). Duck pan-genome reveals two transposon insertions caused bodyweight enlarging and white plumage phenotype formation during evolution. iMeta, 3(1), e154.

[50] Price-Waldman, R., & Stoddard, M. C. (2021). Avian coloration genetics: Recent advances and emerging questions. Journal of Heredity, 112(5), 395–416.

[51] Cuthill, I. C., Allen, W. L., Arbuckle, K., Caspers, B., Chaplin, G., Hauber, M. E., Caro, T., Jablonski, N. G., Jiggins, C. D., Kelber, A., Mappes, J., Marshall, J., Merrill, R., Osorio, D., Prum, R., Roberts, N. W., Roulin, A., Rowland, H. M., & Sherratt, T. N. (2017). The biology of color. Science, 357(6350), eaan0221.

[52] Cooke, T. F., Fischer, C. R., Wu, P., Jiang, T. X., Xie, K. T., Kuo, J., Bustamante, C. D., Zehnder, A., Khosla, C., & Chuong, C. M. (2017). Genetic mapping and biochemical basis of yellow feather pigmentation in budgerigars. Cell, 171(2), 427–439.e421.

[53] Barsh, G. S., Bruders, R., Van Hollebeke, H., Osborne, E. J., Kronenberg, Z., Maclary, E., & Shapiro, M. D. (2020). A copy number variant is associated with a spectrum of pigmentation patterns in the rock pigeon (Columba livia). PLoS Genetics, 16(5), e1008274.

[54] Gao, G., Xu, M., Bai, C., Yang, Y., Li, G., Xu, J., & Zuo, Y. (2018). Comparative genomics and transcriptomics of Chrysolophus provide insights into the evolution of complex plumage coloration. GigaScience, 7(10), giy113.

[55] Liu, H., Xi, Y., Tang, Q., Qi, J., Zhou, Z., Guo, Z., Hou, S., Hu, J., Xu, Y., Liang, S., Xie, M., Tang, J., & Zhang, Y. (2023). Genetic fine-mapping reveals single nucleotide polymorphism mutations in the MC1R regulatory region associated with duck melanism. Molecular Ecology, 32(12), 3076–3088.

[56] Campagna, L., & Toews, D. P. L. (2022). The genomics of adaptation in birds. Current Biology, 32(20), R1173–R1186.

[57] Desuzinges-Mandon, E., Arnaud, O., Martinez, L., Huche, F., Di Pietro, A., & Falson, P. (2010). ABCG2 transports and transfers heme to albumin through its large extracellular loop. Journal of Biological Chemistry, 285(43), 33123–33133.

[58] Kobuchi, H., Moriya, K., Ogino, T., Fujita, H., Inoue, K., Shuin, T., Utsumi, T., & Utsumi, K. (2012). Mitochondrial localization of ABC transporter ABCG2 and its function in 5-aminolevulinic acid-mediated protoporphyrin IX accumulation. PLoS One, 7(11), e50082.

[59] Liu, H., Hu, J., Guo, Z., Fan, W., Xu, Y., Liang, S., & Hou, S. (2021). A SNP variant located in the cis-regulatory region of the ABCG2 gene is associated with mallard egg color. Molecular Ecology, 1–15.

[60] Chen, L., Gu, X., Huang, X., Liu, R., Li, J., Hu, Y., Li, N., Zeng, T., Tian, Y., & Lu, L. (2020). Two cis-regulatory SNPs upstream of ABCG2 synergistically cause the blue eggshell phenotype in the duck. PLoS Genetics, 16(11), e1009119.

[61] Henchion, M. M., McCarthy, M., & Resconi, V. C. (2017). Beef quality attributes: A systematic review of consumer perspectives. Meat Science, 128, 1–7.

[62] Liu, D., Fan, W., Xu, Y., Yu, S., Liu, W., Guo, Z., Hou, S., & Zhou, Z. (2021). Genome-wide association studies demonstrate that TASP1 contributes to increased muscle fiber diameter. Heredity, 126(6), 991–999.

[63] Tang, H., Liu, D., Zhang, H., Fan, W., Hu, J., Xu, Y., Zhou, Z., Huang, W., & Hou, S. (2023). Genome-wide association studies demonstrate the genes associated with perimysial thickness in ducks. Animal Genetics, 54(3), 363–374.

[64] Calkins, C. R., & Hodgen, J. M. (2007). A fresh look at meat flavor. Meat Science, 77(1), 63–80.

[65] Su, X. Q., Wang, J., & Sinclair, A. J. (2019). Plasmalogens and Alzheimer’s disease: A review. Lipids in Health and Disease, 18(1), 100.

[66] Boldyrev, A. A., Aldini, G., & Derave, W. (2013). Physiology and pathophysiology of carnosine. Physiological Reviews, 93(4), 1803–1845.

[67] Liu, D., Zhang, H., Yang, Y., Liu, T., Guo, Z., Fan, W., Zhou, Z., Yang, X., Zhang, B., Liu, H., Tang, H., Yu, D., Yu, S., Gai, K., Mou, Q., Cao, J., Hu, J., Tang, J., & Hou, S. (2023). Metabolome-Based genome-wide association study of duck meat leads to novel genetic and biochemical insights. Advanced Science, 10(18), 2300148.

[68] Jones, H. E., & Wilson, P. B. (2022). Progress and opportunities through use of genomics in animal production. Trends in Genetics, 38(12), 1228–1252.

[69] Misztal, I., Lourenco, D., & Legarra, A. (2020). Current status of genomic evaluation. Journal of Animal Science, 98(4), skaa101.

[70] VanRaden, P. M. (2020). Symposium review: How to implement genomic selection. Journal of Dairy Science, 103(6), 5291–5301.

[71] Cai, W., Hu, J., Fan, W., Xu, Y., Tang, J., Xie, M., Hou, S., Guo, Z., & Zhou, Z. (2024). Genetic parameters and genomic prediction of growth and breast morphological traits in a crossbreed duck population. Evolutionary Applications, 17(2), e13638.

[72] Cai, W., Hu, J., Fan, W., Xu, Y., Tang, J., Xie, M., Hou, S., Guo, Z., & Zhou, Z. (2023). Strategies to improve genomic predictions for 35 duck carcass traits in an F2 population. Journal of Animal Science and Biotechnology, 14(1), 74.

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2024 The Author(s). Animal Research and One Health published by John Wiley & Sons Australia, Ltd on behalf of Institute of Animal Science, Chinese Academy of Agricultural Sciences.