High-quality genome sequence of white lupin provides insight into soil exploration and seed quality.

Alkaloids / chemistry Centromere / genetics Ecotype Evolution, Molecular Gene Dosage Gene Duplication Genetic Variation Genome, Plant Genomic Structural Variation Lupinus / genetics Models, Genetic Molecular Sequence Annotation Plant Leaves / metabolism Plant Proteins / metabolism Plant Roots / genetics Polymorphism, Single Nucleotide / genetics Repetitive Sequences, Nucleic Acid / genetics Seeds / physiology Sequence Analysis, DNA Soil Synteny / genetics Transcriptome / genetics

Journal

Nature communications

ISSN: 2041-1723

Titre abrégé: Nat Commun

Pays: England

ID NLM: 101528555

Informations de publication

Date de publication:
24 01 2020

Historique:

received: 16 09 2019

accepted: 19 12 2019

entrez: 26 1 2020

pubmed: 26 1 2020

medline: 9 4 2020

Statut: epublish

Résumé

White lupin (Lupinus albus L.) is an annual crop cultivated for its protein-rich seeds. It is adapted to poor soils due to the production of cluster roots, which are made of dozens of determinate lateral roots that drastically improve soil exploration and nutrient acquisition (mostly phosphate). Using long-read sequencing technologies, we provide a high-quality genome sequence of a cultivated accession of white lupin (2n = 50, 451 Mb), as well as de novo assemblies of a landrace and a wild relative. We describe a modern accession displaying increased soil exploration capacity through early establishment of lateral and cluster roots. We also show how seed quality may have been impacted by domestication in term of protein profiles and alkaloid content. The availability of a high-quality genome assembly together with companion genomic and transcriptomic resources will enable the development of modern breeding strategies to increase and stabilize white lupin yield.

Identifiants

DOI: 10.1038/s41467-019-14197-9 PMID: 31980615 PMC: PMC6981116

pubmed: 31980615

doi: 10.1038/s41467-019-14197-9

pii: 10.1038/s41467-019-14197-9

pmc: PMC6981116

doi:

Substances chimiques

Alkaloids 0

Plant Proteins 0

Soil 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

Pagination

492

Références

Drummond, C. S., Eastwood, R. J., Miotto, S. T. S. & Hughes, C. E. Multiple continental radiations and correlates of diversification in Lupinus (Leguminosae): testing for key innovation with incomplete taxon sampling. Syst. Biol. 61, 443–460 (2012).

pubmed: 22228799 pmcid: 3329764 doi: 10.1093/sysbio/syr126

Hughes, C. & Eastwood, R. Island radiation on a continental scale: exceptional rates of plant diversification after uplift of the Andes. Proc. Natl Acad. Sci. USA 103, 10334–10339 (2006).

pubmed: 16801546 doi: 10.1073/pnas.0601928103

Ainouche, A.-K. & Bayer, R. J. Phylogenetic relationships in Lupinus (Fabaceae: Papilionoideae) based on internal transcribed spacer sequences (ITS) of nuclear ribosomal DNA. Am. J. Bot. 86, 590–607 (1999).

pubmed: 10205079 doi: 10.2307/2656820 pmcid: 10205079

Gladstones, J. S. Lupins as Crop Plants: Biology, Production and Utilization (eds Gladstones J. S., Atkins C, Hamblin J.) 1–39 (CAB International, Oxon, New York, 1998).

Bähr, M., Fechner, A., Hasenkopf, K., Mittermaier, S. & Jahreis, G. Chemical composition of dehulled seeds of selected lupin cultivars in comparison to pea and soya bean. LWT Food Sci. Technol. 59, 587–590 (2014).

doi: 10.1016/j.lwt.2014.05.026

Wolko, B., Clements, J. C., Naganowska, B., Nelson, M. N. & Yang, H. Lupinus. Wild Crop Relatives: Genomic and Breeding Resources. 153–206 (Springer Berlin Heidelberg, 2011). .

Boschin, G., D’Agostina, A., Annicchiarico, P. & Arnoldi, A. Effect of genotype and environment on fatty acid composition of Lupinus albus L. seed. Food Chem. 108, 600–606 (2008).

pubmed: 26059138 doi: 10.1016/j.foodchem.2007.11.016

Fontanari, G. G. et al. Cholesterol-lowering effect of whole lupin (Lupinus albus) seed and its protein isolate. Food Chem. 132, 1521–1526 (2012).

pubmed: 29243644 doi: 10.1016/j.foodchem.2011.11.145

Boschin, G. & Arnoldi, A. Legumes are valuable sources of tocopherols. Food Chem. 127, 1199–1203 (2011).

Lucas, M. M. et al. The future of lupin as a protein crop in Europe. Front. Plant Sci. 6, 705 (2015).

Lambers, H., Clements, J. C. & Nelson, M. N. How a phosphorus-acquisition strategy based on carboxylate exudation powers the success and agronomic potential of lupines (Lupinus, Fabaceae). Am. J. Bot. 100, 263–288 (2013).

pubmed: 23347972 doi: 10.3732/ajb.1200474 pmcid: 23347972

Giehl, R. F. H., Gruber, B. D. & von Wirén, N. It’s time to make changes: modulation of root system architecture by nutrient signals. J. Exp. Bot. 65, 769–778 (2014).

pubmed: 24353245 doi: 10.1093/jxb/ert421 pmcid: 24353245

Lynch, J. P. Root phenes for enhanced soil exploration and phosphorus acquisition: tools for future crops. Plant Physiol. 156, 1041–1049 (2011).

pubmed: 21610180 pmcid: 3135935 doi: 10.1104/pp.111.175414

Watt, M. & Evans, J. R. Phosphorus acquisition from soil by white lupin (Lupinus albus L.) and soybean (Glycine max L.), species with contrasting root development. Plant Soil 248, 271–283 (2003).

Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k -mer weighting and repeat separation. Genome Res. 27, 722–736 (2017).

pubmed: 28298431 pmcid: 5411767 doi: 10.1101/gr.215087.116

Chin, C. S. et al. Phased diploid genome assembly with single-molecule real-time sequencing. Nat. Methods 13, 1050–1054 (2016).

pubmed: 27749838 pmcid: 5503144 doi: 10.1038/nmeth.4035

Książkiewicz, M. et al. A high-density consensus linkage map of white lupin highlights synteny with narrow-leafed lupin and provides markers tagging key agronomic traits. Sci. Rep. 7, 15335 (2017).

pubmed: 29127429 pmcid: 5681670 doi: 10.1038/s41598-017-15625-w

Sallet, E., Gouzy, J. & Schiex, T. Gene Prediction (ed Kollmar, M.) 97–120 (Springer New York, 2019). https://doi.org/10.1007/978-1-4939-9173-0_6 .

Waterhouse, R. M. et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol. Biol. Evol. 35, 543–548 (2018).

pubmed: 29220515 doi: 10.1093/molbev/msx319 pmcid: 29220515

Macas, J. et al. In depth characterization of repetitive DNA in 23 plant genomes reveals sources of genome size variation in the legume tribe fabeae. PLoS ONE 10, 1–23 (2015).

doi: 10.1371/journal.pone.0143424

Hane, J. K. et al. A comprehensive draft genome sequence for lupin (Lupinus angustifolius), an emerging health food: insights into plant-microbe interactions and legume evolution. Plant Biotechnol. J. 15, 318–330 (2017).

pubmed: 27557478 doi: 10.1111/pbi.12615 pmcid: 27557478

Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).

pubmed: 10835412 pmcid: 10835412

Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14, 2611–2620 (2005).

pubmed: 15969739 doi: 10.1111/j.1365-294X.2005.02553.x pmcid: 15969739

Nattestad, M. & Schatz, M. C. Assemblytics: a web analytics tool for the detection of variants from an assembly. Bioinformatics 32, 3021–3023 (2016).

pubmed: 27318204 pmcid: 6191160 doi: 10.1093/bioinformatics/btw369

Kurtz, S. et al. Versatile and open software for comparing large genomes. Genome Biol. 5, R12 (2004).

pubmed: 14759262 pmcid: 14759262 doi: 10.1186/gb-2004-5-2-r12

Lee, C., Yu, D., Choi, H.-K. & Kim, R. W. Reconstruction of a composite comparative map composed of ten legume genomes. Genes Genomics 39, 111–119 (2017).

pubmed: 28090266 doi: 10.1007/s13258-016-0481-8 pmcid: 28090266

Wang, J. et al. Hierarchically aligning 10 legume genomes establishes a family-level genomics platform. Plant Physiol. 174, 284 LP–284300 (2017).

doi: 10.1104/pp.16.01981

Zhuang, W. et al. The genome of cultivated peanut provides insight into legume karyotypes, polyploid evolution and crop domestication. Nat. Genet. 51, 865–876 (2019).

Kreplak, J. et al. A reference genome for pea provides insight into legume genome evolution. Nat. Genet. 51, 1411–1422 (2019).

pubmed: 31477930 doi: 10.1038/s41588-019-0480-1 pmcid: 31477930

Bertioli, D. J. et al. The genome sequence of segmental allotetraploid peanut Arachis hypogaea. Nat. Genet. 51, 877–884 (2019).

Ren, L., Huang, W. & Cannon, S. B. Reconstruction of ancestral genome reveals chromosome evolution history for selected legume species. N. Phytol. 223, 2090–2103 (2019).

doi: 10.1111/nph.15770

Kroc, M., Koczyk, G., Święcicki, W., Kilian, A. & Nelson, M. N. New evidence of ancestral polyploidy in the Genistoid legume Lupinus angustifolius L. (narrow-leafed lupin). Theor. Appl. Genet. 127, 1237–1249 (2014).

pubmed: 24633641 doi: 10.1007/s00122-014-2294-y

Wang, Y., Coleman-Derr, D., Chen, G. & Gu, Y. Q. OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res. 43, W78–W84 (2015).

pubmed: 25964301 pmcid: 4489293 doi: 10.1093/nar/gkv487

Tang, H. et al. An improved genome release (version Mt4.0) for the model legume Medicago truncatula. BMC Genomics 15, 312 (2014).

pubmed: 24767513 pmcid: 4234490 doi: 10.1186/1471-2164-15-312

Finn, R. D. et al. InterPro in 2017-beyond protein family and domain annotations. Nucleic Acids Res. 45, D190–D199 (2016).

pubmed: 27899635 pmcid: 5210578 doi: 10.1093/nar/gkw1107

Skene, K. R. Pattern formation in cluster roots: some developmental and evolutionary considerations. Ann. Bot. 85, 901–908 (2000).

doi: 10.1006/anbo.2000.1140

Riechmann, J. L. & Meyerowitz, E. M. The AP2/EREBP family of plant transcription factors. Biol. Chem. 379, 633–646 (1998).

pubmed: 9687012

Hirota, A., Kato, T., Fukaki, H., Aida, M. & Tasaka, M. The auxin-regulated AP2/EREBP gene PUCHI is required for morphogenesis in the early lateral root primordium of Arabidopsis. Plant Cell 19, 2156–2168 (2007).

pubmed: 17630277 pmcid: 1955702 doi: 10.1105/tpc.107.050674

Hsieh, L.-C. et al. Uncovering small RNA-mediated responses to phosphate deficiency in Arabidopsis by deep sequencing. Plant Physiol. 151, 2120–2132 (2009).

pubmed: 19854858 pmcid: 2785986 doi: 10.1104/pp.109.147280

Bari, R., Datt Pant, B., Stitt, M. & Scheible, W.-R. PHO2, MicroRNA399, and PHR1 define a phosphate-signaling pathway in plants. Plant Physiol. 141, 988–999 (2006).

pubmed: 16679424 pmcid: 1489890 doi: 10.1104/pp.106.079707

Secco, D. et al. Spatio-temporal transcript profiling of rice roots and shoots in response to phosphate starvation and recovery. Plant Cell 25, 4285–4304 (2013).

pubmed: 24249833 pmcid: 3875719 doi: 10.1105/tpc.113.117325

Zhu, Y. Y. et al. microRNA expression profiles associated with phosphorus deficiency in white lupin (Lupinus albus L.). Plant Sci. 178, 23–29 (2010).

doi: 10.1016/j.plantsci.2009.09.011

Gamuyao, R. et al. The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency. Nature 488, 535–539 (2012).

pubmed: 22914168 doi: 10.1038/nature11346 pmcid: 22914168

Dobiesz, M. & Piotrowicz-Cieślak, A. I. Proteins in relation to vigor and viability of white lupin (Lupinus albus L.) seed stored for 26 years. Front. Plant Sci. 8, 1–11 (2017).

doi: 10.3389/fpls.2017.01392

Jimenez-Lopez, J. C. et al. Characterization of narrow-leaf lupin (Lupinus angustifolius L.) recombinant major allergen IgE-binding proteins and the natural β-conglutin counterparts in sweet lupin seed species. Food Chem. 244, 60–70 (2018).

pubmed: 29120805 doi: 10.1016/j.foodchem.2017.10.015 pmcid: 29120805

Lin, R. et al. Development of a sequence-specific PCR marker linked to the gene ‘pauper’ conferring low-alkaloids in white lupin (Lupinus albus L.) for marker assisted selection. Mol. Breed. 23, 153–161 (2009).

doi: 10.1007/s11032-008-9222-2

Lucas, M. M. et al. The future of lupin as a protein crop in Europe. Front. Plant Sci. 6, 705 (2015).

pubmed: 26442020 pmcid: 4561814

Berger, J. D., Shrestha, D. & Ludwig, C. Reproductive strategies in mediterranean legumes: trade-offs between phenology, seed size and vigor within and between wild and domesticated lupinus species collected along aridity gradients. Front. Plant Sci. 8, 548 (2017).

Clements, J. C., White, P. F. & Buirchell, B. J. The root morphology of Lupinus angustifolius in relation to other Lupinus species. Aust. J. Agric. Res. 44, 1367–1375 (1993).

doi: 10.1071/AR9931367

Skene, K. R. Cluster roots: some ecological considerations. J. Ecol. 86, 1060–1064 (1998).

doi: 10.1046/j.1365-2745.1998.00326.x

Cordell, D., Drangert, J.-O. & White, S. The story of phosphorus: global food security and food for thought. Glob. Environ. Change 19, 292–305 (2009).

doi: 10.1016/j.gloenvcha.2008.10.009

Raymond, O. et al. The Rosa genome provides new insights into the domestication of modern roses. Nat. Genet. 50, 772–777 (2018).

pubmed: 29713014 pmcid: 5984618 doi: 10.1038/s41588-018-0110-3

Walker, B. J., Abeel, T., Shea, T., Priest, M. & Abouelliel, A. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, 112963 (2014).

doi: 10.1371/journal.pone.0112963

Tang, H. et al. ALLMAPS: robust scaffold ordering based on multiple maps. Genome Biol. 16, 1–15 (2015).

doi: 10.1186/s13059-014-0573-1

Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17, 10 (2011).

doi: 10.14806/ej.17.1.200

Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010).

pubmed: 20080505 pmcid: 20080505 doi: 10.1093/bioinformatics/btp698

McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

pubmed: 2928508 pmcid: 2928508 doi: 10.1101/gr.107524.110

Dierckxsens, N., Mardulyn, P. & Smits, G. NOVOPlasty: de novo assembly of organelle genomes from whole genome data. Nucleic Acids Res. 45, e18 (2016).

pmcid: 5389512

Novak, P., Neumann, P., Pech, J., Steinhaisl, J. & Macas, J. RepeatExplorer: a Galaxy-based web server for genome-wide characterization of eukaryotic repetitive elements from next-generation sequence reads. Bioinformatics 29, 792–793 (2013).

pubmed: 23376349 doi: 10.1093/bioinformatics/btt054 pmcid: 23376349

Neumann, P., Novák, P., Hoštáková, N. & Macas, J. Systematic survey of plant LTR-retrotransposons elucidates phylogenetic relationships of their polyprotein domains and provides a reference for element classification. Mob. DNA 10, 1 (2019).

pubmed: 30622655 pmcid: 6317226 doi: 10.1186/s13100-018-0144-1

Marques, A. et al. Holocentromeres in Rhynchospora are associated with genome-wide centromere-specific repeat arrays interspersed among euchromatin. Proc. Natl Acad. Sci. USA 112, 13633–13638 (2015).

pubmed: 26489653 doi: 10.1073/pnas.1512255112 pmcid: 26489653

Kato, A. et al. Sensitive fluorescence in situ hybridization signal detection in maize using directly labeled probes produced by high concentration DNA polymerase nick translation. Biotech. Histochem. 81, 71–78 (2006).

pubmed: 16908431 doi: 10.1080/10520290600643677 pmcid: 16908431

Bradbury, P. J. et al. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23, 2633–2635 (2007).

pubmed: 17586829 doi: 10.1093/bioinformatics/btm308 pmcid: 17586829

Letunic, I. & Bork, P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 44, W242–W245 (2016).

pubmed: 27095192 pmcid: 27095192 doi: 10.1093/nar/gkw290

Earl, D. A. & vonHoldt, B. M. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361 (2012).

doi: 10.1007/s12686-011-9548-7

Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).

pubmed: 26059717 doi: 10.1093/bioinformatics/btv351 pmcid: 26059717

Pont, C. et al. Paleogenomics: reconstruction of plant evolutionary trajectories from modern and ancient DNA. Genome Biol. 20, 29 (2019).

pubmed: 30744646 pmcid: 6369560 doi: 10.1186/s13059-019-1627-1

Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357 (2015).

pubmed: 4655817 pmcid: 4655817 doi: 10.1038/nmeth.3317

Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 1–21 (2014).

doi: 10.1186/s13059-014-0550-8

Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25, 402–408 (2001).

doi: 10.1006/meth.2001.1262