- Record: found
- Abstract: found
- Article: found
One thousand plant transcriptomes and the phylogenomics of green plants
research-article
Publication date (Electronic):
23 October 2019
Journal:
Nature
Publisher:
Nature Publishing Group UK
Read this article at
There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
Green plants (Viridiplantae) include around 450,000–500,000 species 1, 2 of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life.
Abstract
The One Thousand Plant Transcriptomes Initiative provides a robust phylogenomic framework for examining green plant evolution that comprises the transcriptomes and genomes of diverse species of green plants.
Related collections
Most cited references84
- Record: found
- Abstract: found
- Article: not found
The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla.
Alberto Casagrande (2007)
The analysis of the first plant genomes provided unexpected evidence for genome duplication events in species that had previously been considered as true diploids on the basis of their genetics. These polyploidization events may have had important consequences in plant evolution, in particular for species radiation and adaptation and for the modulation of functional capacities. Here we report a high-quality draft of the genome sequence of grapevine (Vitis vinifera) obtained from a highly homozygous genotype. The draft sequence of the grapevine genome is the fourth one produced so far for flowering plants, the second for a woody species and the first for a fruit crop (cultivated for both fruit and beverage). Grapevine was selected because of its important place in the cultural heritage of humanity beginning during the Neolithic period. Several large expansions of gene families with roles in aromatic features are observed. The grapevine genome has not undergone recent genome duplication, thus enabling the discovery of ancestral traits and features of the genetic organization of flowering plants. This analysis reveals the contribution of three ancestral genomes to the grapevine haploid content. This ancestral arrangement is common to many dicotyledonous plants but is absent from the genome of rice, which is a monocotyledon. Furthermore, we explain the chronology of previously described whole-genome duplication events in the evolution of flowering plants.
- Record: found
- Abstract: found
- Article: found
The tomato genome sequence provides insights into fleshy fruit evolution
Introductory Paragraph Tomato (Solanum lycopersicum) is a major crop plant and a model system for fruit development. Solanum is one of the largest angiosperm genera 1 and includes annual and perennial plants from diverse habitats. We present a high quality genome sequence of domesticated tomato, a draft sequence of its closest wild relative, S. pimpinellifolium 2 , and compare them to each other and to potato (S. tuberosum). The two tomato genomes show only 0.6% nucleotide divergence and signs of recent admixture, but show >8% divergence from potato, with nine large and several smaller inversions. In contrast to Arabidopsis, but similar to soybean, tomato and potato, small RNAs map predominantly to gene-rich chromosomal regions, including gene promoters. The Solanum lineage has experienced two consecutive genome triplications: one that is ancient and shared with rosids, and a more recent one. These triplications set the stage for the neofunctionalization of genes controlling fruit characteristics, such as colour and fleshiness. Main Text The genome of the inbred tomato cultivar ‘Heinz 1706’ was sequenced and assembled using a combination of Sanger and “next generation” technologies (Supplementary Section 1). The predicted genome size is ~900 Mb, consistent with prior estimates 3 , of which 760 Mb were assembled in 91 scaffolds aligned to the 12 tomato chromosomes, with most gaps restricted to pericentromeric regions (Fig. 1A; Supplementary Fig. 1). Base accuracy is approximately one substitution error per 29.4 kb and one indel error per 6.4 kb. The scaffolds were linked with two BAC-based physical maps and anchored/oriented using a high-density genetic map, introgression line mapping and BAC fluorescence in situ hybridisation (FISH). The genome of S. pimpinellifolium (accession LA1589) was sequenced and assembled de novo using Illumina short reads, yielding a 739 Mb draft genome (Supplementary Section 3). Estimated divergence between the wild and domesticated genomes is 0.6% (5.4M SNPs distributed along the chromosomes (Fig. 1A, Supplementary Fig. 1)). Tomato chromosomes consist of pericentric heterochromatin and distal euchromatin, with repeats concentrated within and around centromeres, in chromomeres and at telomeres (Fig. 1A, Supplementary Fig. 1). Substantially higher densities of recombination, genes and transcripts are observed in euchromatin, while chloroplast insertions (Supplementary Sections 1.22-1.23) and conserved miRNA genes (Supplementary Section 2.9) are more evenly distributed throughout the genome. The genome is highly syntenic with those of other economically important Solanaceae (Fig. 1B). Compared to the genomes of Arabidopsis 4 and sorghum 5 , tomato has fewer high-copy, full-length LTR retrotransposons with older average insertion ages (2.8 versus 0.8 mya) and fewer high-frequency k-mers (Supplementary Section 2.10). This supports previous findings that the tomato genome is unusual among angiosperms by being largely comprised of low-copy DNA 6,7 . The pipeline used to annotate the tomato and potato 8 genomes is described in Supplementary Section 2. It predicted 34,727 and 35,004 protein-coding genes, respectively. Of these, 30,855 and 32,988, respectively, are supported by RNA-Seq data, and 31,741 and 32,056, respectively, show high similarity to Arabidopsis genes (Supplementary section 2.1). Chromosomal organisation of genes, transcripts, repeats and sRNAs is very similar in the two species (Supplementary Figures 2-4). The protein coding genes of tomato, potato, Arabidopsis, rice and grape were clustered into 23,208 gene groups (≥2 members), of which 8,615 are common to all five genomes, 1,727 are confined to eudicots (tomato, potato, grape and Arabidopsis), and 727 are confined to plants with fleshy fruits (tomato, potato and grape) (Supplementary Section 5.1, Supplementary Fig. 5). Relative expression of all tomato genes was determined by replicated strand-specific Illumina RNA-Seq of root, leaf, flower (2 stages) and fruit (6 stages) in addition to leaf and fruit (3 stages) of S. pimpinellifolium (Supplementary Table 1). sRNA sequencing data supported the prediction of 96 conserved miRNA genes in tomato and 120 in potato, a number consistent with other plant species (Fig. 1A, Supplementary Figures 1 and 3, Supplementary Section 2.9). Among the 34 miRNA families identified, 10 are highly conserved in plants and similarly represented in the two species, whereas other, less conserved families are more abundant in potato. Several miRNAs, predicted to target TIR-NBS-LRR genes, appeared to be preferentially or exclusively expressed in potato (Supplementary Section 2.9). Supplementary section 4 deals with comparative genomic studies. Sequence alignment of 71 Mb of euchromatic tomato genomic DNA to their potato 8 counterparts revealed 8.7% nucleotide divergence (Supplementary Section 4.1). Intergenic and repeat-rich heterochromatic sequences showed more than 30% nucleotide divergence, consistent with the high sequence diversity in these regions among potato genotypes 8 . Alignment of tomato-potato orthologous regions confirmed 9 large inversions known from cytological or genetic studies and several smaller ones (Fig. 1C). The exact number of small inversions is difficult to determine due to the lack of orientation of most potato scaffolds. 18,320 clearly orthologous tomato-potato gene pairs were identified. Of these, 138 (0.75%) had significantly higher than average non-synonymous (Ka) versus synonymous (Ks) nucleotide substitution rate ratios (ω), suggesting diversifying selection, whereas 147 (0.80%) had significantly lower than average ω, suggesting purifying selection (Supplementary Table 2). The proportions of high and low ω between sorghum and maize (Zea mays) are 0.70% and 1.19%, respectively, after 11.9 Myr of divergence 9 , suggesting that diversifying selection may have been stronger in tomato-potato. The highest densities of low-ω genes are found in collinear blocks with average Ks >1.5, tracing to a genome triplication shared with grape (see below) (Fig. 1C, Supplementary Fig. 6, Supplementary Table 3). These genes, which have been preserved in paleo-duplicated locations for more than 100 Myr 10,11 are more constrained than ‘average’ genes and are enriched for transcription factors and genes otherwise related to gene regulation (Supplementary Tables 3-4). Sequence comparison of 32,955 annotated genes in tomato and S. pimpinellifolium revealed 6,659 identical genes and 3,730 with only synonymous changes. A total of 22,888 genes had non-synonymous changes, including gains and losses of stop codons with potential consequences for gene function (Supplementary Tables 5-7). Several pericentric regions, predicted to contain genes, are absent or polymorphic in the broader S. pimpinellifolium germplasm (Supplementary Table 8, Supplementary Fig. 7). Within cultivated germplasm, particularly among the small-fruited cherry tomatoes, several chromosomal segments are more closely related to S. pimpinellifolium than to ‘Heinz 1706’ (Supplementary Figures 8-9), supporting previous observations on recent admixture of these gene pools due to breeding 12 . ‘Heinz 1706’ itself has been reported to carry introgressions from S. pimpinellifolium 13 , traces of which are detectable on chromosomes 4, 9, 11 and 12 (Supplementary Table 9). Comparison of the tomato and grape genomes supports the hypothesis that a whole-genome triplication affecting the rosid lineage occurred in a common eudicot ancestor 11 (Fig. 2B). The distribution of Ks between corresponding gene pairs in duplicated blocks suggests that one polyploidisation in the solanaceous lineage preceded the rosid-asterid (tomato-grape) divergence (Supplementary Fig. 10). Comparison to the grape genome also reveals a more recent triplication in tomato and potato. While few individual tomato/potato genes remain triplicated (Supplementary Tables 10-11), 73% of tomato gene models are in blocks that are orthologous to one grape region, collectively covering 84% of the grape gene space. Among these grape genomic regions, 22.5% have one orthologous region in tomato, 39.9% have two, and 21.6% have three, indicating that a whole genome triplication occurred in the Solanum lineage, followed by widespread gene loss. This triplication, also evident in potato (Supplementary Fig. 11) is estimated at 71 (+/-19.4) mya based on Ks of paralogous genes (Supplementary Fig. 10), and therefore predates the ~7.3 mya tomato-potato divergence. Based on alignments to single grape genome segments, the tomato genome can be partitioned into three non-overlapping ‘subgenomes’ (Fig. 2A). The number of euasterid lineages that have experienced the recent triplication remains unclear and awaits complete euasterid I and II genome sequences. Ks distributions show that euasterids I and II, and indeed the rosid-asterid lineages, all diverged from common ancestry at or near the pan-eudicot triplication (Fig. 2B), suggesting that this event may have contributed to formation of major eudicot lineages in a short period of several million years 14 , partially explaining the explosive radiation of angiosperm plants on earth 15 . Supplementary section 5 reports on the analysis of specific gene families. Fleshy fruits (Supplementary Fig. 12) are an important means of attracting vertebrate frugivores for seed dispersal 16 . Combined orthology and synteny analyses suggest that both genome triplications added new gene family members that mediate important fruit-specific functions (Fig. 3). These include transcription factors and enzymes necessary for ethylene biosynthesis (RIN, CNR, ACS) and perception (LeETR3/NR, LeETR4) 17 , red light photoreceptors influencing fruit quality (PHYB1/PHYB2) and ethylene- and light-regulated genes mediating lycopene biosynthesis (PSY1/PSY2). Several cytochrome P450 subfamilies associated with toxic alkaloid biosynthesis show contraction or complete loss in tomato and the extant genes show negligible expression in ripe fruits (Supplementary Section 5.4). Fruit texture has profound agronomic and sensory importance and is controlled in part by cell wall structure and composition 18 . More than 50 genes showing differential expression during fruit development and ripening encode proteins involved in modification of wall architecture (Fig. 4A and Supplementary Section 5.7). For example, a family of xyloglucan endotransglucosylase-/hydrolases (XTHs) has expanded both in the recent whole genome triplication and through tandem duplication. One of the triplicated members, SlXTH10, shows differential loss between tomato and potato (Fig. 4A, Supplementary Table 12), suggesting genetically driven specialisation in the remodelling of fruit cell walls. Similar to soybean and potato and in contrast to Arabidopsis, tomato sRNAs map preferentially to euchromatin (Supplementary Fig. 2). sRNAs from tomato flowers and fruits 19 map to 8,416 gene promoters. Differential expression of sRNAs during fruit development is apparent for 2,687 promoters, including those of cell wall-related genes (Fig. 4B) and occurs preferentially at key developmental transitions (e.g. flower to fruit, fruit growth to fruit ripening, Supplementary Section 2.8). The genome sequences of tomato, S. pimpinellifolium and potato provide a starting point for comparing gene family evolution and sub-functionalization in the Solanaceae. A striking example is the SELF PRUNING (SP) gene family, which includes the homolog of Arabidopsis FT, encoding the mobile flowering hormone florigen 20 and its antagonist SP, encoding the ortholog of TFL1. Nearly a century ago, a spontaneous mutation in SP spawned the “determinate” varieties that now dominate the tomato mechanical harvesting industry 21 . The genome sequence has revealed that the SP family has expanded in the Solanum lineage compared to Arabidopsis, driven by the Solanum triplication and tandem duplication (Supplementary Fig. 13). In potato, SP3D and SP6A control flowering and tuberisation, respectively 22 , whereas SP3D in tomato, known as SINGLE FLOWER TRUSS, similarly controls flowering, but also drives heterosis for fruit yield in an epistatic relationship with SP 23,24,25 . Interestingly, SP6A in S. lycopersicum is inactivated by a premature stop codon, but remains functionally intact in S. pimpinellifolium. Thus, allelic variation in a subset of SP family genes has played a major role in the generation of both shared and species-specific variation in Solanaceous agricultural traits. The genome sequences of tomato and S. pimpinellifolium also provide a basis for understanding the bottlenecks that have narrowed tomato genetic diversity: the domestication of S. pimpinellifolium in the Americas, the export of a small number of accessions to Europe in the 16th Century, and the intensive breeding that followed. Charles Rick pioneered the use of trait introgression from wild tomato relatives to increase genetic diversity of cultivated tomatoes 26 . Introgression lines exist for seven wild tomato species, including S. pimpinellifolium, in the background of cultivated tomato. The genome sequences presented here and the availability of millions of SNPs will allow breeders to revisit this rich trait reservoir and identify domestication genes, providing biological knowledge and empowering biodiversity-based breeding. Methods Summary A total of 21 Gb of Roche/454 Titanium shotgun and matepair reads and 3.3 Gb of Sanger paired-end reads, including ~200,000 BAC and fosmid end sequence pairs, were generated from the ‘Heinz 1706’ inbred line (Supplementary Sections 1.1-1.7), assembled using both Newbler and CABOG and integrated into a single assembly (Supplementary Sections 1.17-1.18). The scaffolds were anchored using two BAC-based physical maps, one high density genetic map, overgo hybridization and genome-wide BAC FISH (Supplementary Sections 1.8-1.16 and 1.19). Over 99.9% of BAC/fosmid end pairs mapped consistently on the assembly and over 98% of EST sequences could be aligned to the assembly (Supplementary Section 1.20). Chloroplast genome insertions in the nuclear genome were validated using a matepair method and the flanking regions were identified (Supplementary Sections 1.22-1.24). Annotation was carried out using a pipeline based on EuGene that integrates de novo gene prediction, RNA-Seq alignment and rich function annotation (Supplementary Section 2). To facilitate interspecies comparison, the potato genome was re-annotated using the same pipeline. LTR retrotransposons were detected de novo with the LTR-STRUC program and dated by the sequence divergence between left and right solo LTR (Supplementary Section 2.10). The genome of S. pimpinellifolium was sequenced to 40x depth using Illumina paired end reads and assembled using ABySS (Supplementary Section 3). The tomato and potato genomes were aligned using LASTZ (Supplementary Section 4.1). Identification of triplicated regions was done using BLASTP, in-house generated scripts and three way comparisons between tomato, potato and S. pimpinellifolium using MCscan (Supplementary Sections 4.2-4.4). Specific gene families/groups (genes for ascorbate, carotenoid and jasmonate biosynthesis, cytochrome P450s, genes controlling cell wall architecture, hormonal and transcriptional regulators, resistance genes) were subjected to expert curation/analysis, (Supplementary Section 5). PHYML and MEGA were used to reconstruct phylogenetic trees and MCSCAN was used to infer gene collinearity (Supplementary Section 5.2). Supplementary Material 1 2 3 4
- Record: found
- Abstract: found
- Article: found
ASTRAL-II: coalescent-based species tree estimation with many hundreds of taxa and thousands of genes
Siavash Mirarab, Tandy Warnow (2015)
Motivation: The estimation of species phylogenies requires multiple loci, since different loci can have different trees due to incomplete lineage sorting, modeled by the multi-species coalescent model. We recently developed a coalescent-based method, ASTRAL, which is statistically consistent under the multi-species coalescent model and which is more accurate than other coalescent-based methods on the datasets we examined. ASTRAL runs in polynomial time, by constraining the search space using a set of allowed ‘bipartitions’. Despite the limitation to allowed bipartitions, ASTRAL is statistically consistent. Results: We present a new version of ASTRAL, which we call ASTRAL-II. We show that ASTRAL-II has substantial advantages over ASTRAL: it is faster, can analyze much larger datasets (up to 1000 species and 1000 genes) and has substantially better accuracy under some conditions. ASTRAL’s running time is O ( n 2 k | X | 2 ) , and ASTRAL-II’s running time is O ( n k | X | 2 ) , where n is the number of species, k is the number of loci and X is the set of allowed bipartitions for the search space. Availability and implementation: ASTRAL-II is available in open source at https://github.com/smirarab/ASTRAL and datasets used are available at http://www.cs.utexas.edu/~phylo/datasets/astral2/. Contact: smirarab@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
Author and article information
Journal
Journal ID (nlm-ta): Nature
Journal ID (iso-abbrev): Nature
Title:
Nature
Publisher:
Nature Publishing Group UK
(London
)
ISSN
(Print):
0028-0836
ISSN
(Electronic):
1476-4687
Publication date
(Electronic):
23
October
2019
Publication date PMC-release: 23
October
2019
Publication date
(Print):
2019
Volume: 574
Issue: 7780
Pages: 679-685
Affiliations
[1
]ISNI 0000 0004 1936 738X, GRID grid.213876.9, Department of Plant Biology, , University of Georgia, ; Athens, GA USA
[2
]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Department of Ecology and Evolutionary Biology, , University of Arizona, ; Tucson, AZ USA
[3
]GRID grid.17089.37, Department of Biological Sciences, , University of Alberta, ; Edmonton, Alberta Canada
[4
]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Department of Biology, , The University of British Columbia Okanagan, ; Kelowna, British Columbia Canada
[5
]ISNI 0000 0004 1936 8091, GRID grid.15276.37, Department of Biology, , University of Florida, ; Gainesville, FL USA
[6
]ISNI 0000 0004 1936 8091, GRID grid.15276.37, Florida Museum of Natural History, , University of Florida, ; Gainesville, FL USA
[7
]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Department of Botany, , University of British Columbia, ; Vancouver, British Columbia Canada
[8
]ISNI 0000 0001 2230 9752, GRID grid.9647.c, German Centre for Integrative Biodiversity Research (iDiv), ; Halle-Jena-Leipzig, Germany
[9
]ISNI 0000 0000 8580 3777, GRID grid.6190.e, Botanical Institute, , University of Cologne, ; Cologne, Germany
[10
]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Department of Electrical and Computer Engineering, , University of California, San Diego, ; San Diego, CA USA
[11
]ISNI 0000 0001 0679 2801, GRID grid.9018.0, Institute of Computer Science, , Martin Luther University Halle-Wittenberg, ; Halle (Saale), Germany
[12
]ISNI 0000 0001 0679 2801, GRID grid.9018.0, Institute of Agricultural and Nutritional Sciences, , Martin Luther University Halle-Wittenberg, ; Halle (Saale), Germany
[13
]GRID grid.5963.9, BIOSS Centre for Biological Signalling Studies, , University of Freiburg, ; Freiburg, Germany
[14
]ISNI 0000 0004 1936 9756, GRID grid.10253.35, Plant Cell Biology, Faculty of Biology, , University of Marburg, ; Marburg, Germany
[15
]ISNI 0000 0004 1936 8091, GRID grid.15276.37, UF Biodiversity Institute, and UF Genetics Institute, , University of Florida, ; Gainesville, FL USA
[17
]ISNI 0000 0001 2222 4708, GRID grid.419520.b, Department of Evolutionary Genetics, , Max Planck Institute for Evolutionary Biology, ; Plön, Germany
[18
]ISNI 0000 0001 0664 5801, GRID grid.421134.1, Negaunee Institute for Plant Conservation Science and Action, , Chicago Botanic Garden, ; Glencoe, IL USA
[19
]ISNI 0000 0001 2299 3507, GRID grid.16753.36, Program in Plant Biology and Conservation, , Northwestern University, ; Evanston, IL USA
[20
]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Department of Horticulture, , Michigan State University, ; East Lansing, MI USA
[21
]ISNI 0000 0001 2167 3675, GRID grid.14003.36, Department of Botany, , University of Wisconsin-Madison, ; Madison, WI USA
[23
]ISNI 0000 0001 1008 957X, GRID grid.266869.5, Department of Biological Sciences, , University of North Texas, ; Denton, TX USA
[24
]GRID grid.466567.0, Centre for Plant Biotechnology and Genomics (CBGP, UPM-INIA), ; Madrid, Spain
[26
]ISNI 0000 0001 2097 4353, GRID grid.4903.e, Jodrell Laboratory, , Royal Botanic Gardens, Kew, ; London, UK
[27
]ISNI 0000000121820794, GRID grid.21106.34, School of Marine Sciences, , University of Maine, ; Orono, ME USA
[29
]ISNI 0000 0004 1936 8390, GRID grid.23856.3a, Department of Plant Biology, , Laval University, Quebec, ; Quebec, Canada
[30
]ISNI 0000 0004 0466 6352, GRID grid.34424.35, Donald Danforth Plant Science Center, ; St Louis, MO USA
[31
]ISNI 0000 0004 1936 7910, GRID grid.1012.2, School of Biological Sciences, , The University of Western Australia, ; Perth, Western Australia Australia
[32
]Kings Park and Botanic Garden, Department of Biodiversity, Conservation and Attractions,
Perth, Western Australia Australia
[33
]ISNI 0000 0004 0474 1797, GRID grid.1011.1, Australian Tropical Herbarium, , James Cook University, ; Cairns, Queensland Australia
[34
]ISNI 0000000086837370, GRID grid.214458.e, Department of Ecology and Evolutionary Biology, , University of Michigan, ; Ann Arbor, MI USA
[35
]ISNI 0000 0004 1936 9262, GRID grid.11835.3e, Department of Animal and Plant Sciences, , University of Sheffield, ; Sheffield, UK
[36
]ISNI 0000 0004 0613 9724, GRID grid.467081.c, Umeå Plant Science Centre, Umeå Universitet, ; Umeå, Sweden
[37
]ISNI 0000 0004 1936 7304, GRID grid.1010.0, Australian Centre for Evolutionary Biology and Biodiversity, Environment Institute,
School of Earth and Environmental Science, , University of Adelaide, ; Adelaide, South Australia Australia
[38
]ISNI 0000000121885934, GRID grid.5335.0, Department of Plant Sciences, , University of Cambridge, ; Cambridge, UK
[40
]ISNI 0000 0001 2315 1184, GRID grid.411461.7, Department of Plant Sciences, , University of Tennessee, ; Knoxville, TN USA
[41
]ISNI 0000 0001 2315 1184, GRID grid.411461.7, Center for Agricultural Synthetic Biology, , University of Tennessee, ; Knoxville, TN USA
[42
]ISNI 0000 0001 2315 1184, GRID grid.411461.7, Department of Food Science, , University of Tennessee, ; Knoxville, TN USA
[43
]ISNI 0000 0001 2173 6074, GRID grid.40803.3f, Department of Food, Bioprocessing and Nutrition Sciences, , North Carolina State University, ; Raleigh, NC USA
[44
]ISNI 0000 0004 0647 1452, GRID grid.449988.0, Institute for Exact and Applied Sciences, , University of New Caledonia, ; Noumea, New Caledonia
[46
]ISNI 0000 0004 0404 0958, GRID grid.463419.d, USDA-Agricultural Research Service, , Corn Insects and Crop Genetics Research Unit, ; Ames, IA USA
[47
]ISNI 0000 0001 2112 1969, GRID grid.4391.f, Department of Botany and Plant Pathology, , Oregon State University, ; Corvallis, OR USA
[48
]ISNI 0000 0004 1936 9262, GRID grid.11835.3e, Department of Molecular Biology and Biotechnology, , University of Sheffield, ; Sheffield, UK
[49
]ISNI 0000 0004 1936 9991, GRID grid.35403.31, Department of Plant Biology, , University of Illinois, Urbana-Champaign, ; Urbana, IL USA
[50
]ISNI 0000000119573309, GRID grid.9227.e, Fairy Lake Botanical Garden, , Chinese Academy of Sciences, ; Shenzhen, China
[51
]ISNI 0000 0004 4651 0380, GRID grid.463064.3, Yale-NUS College, ; Singapore, Republic of Singapore
[52
]ISNI 0000 0004 1936 7910, GRID grid.1012.2, School of Molecular Sciences, , The University of Western Australia, ; Perth, Western Australia Australia
[53
]ISNI 0000 0001 1090 2313, GRID grid.411026.0, Department of Plant Biology, , Southern Illinois University, ; Carbondale, IL USA
[54
]ISNI 0000 0004 1936 7830, GRID grid.29980.3a, Department of Anatomy, , University of Otago, ; Dunedin, New Zealand
[55
]ISNI 0000 0001 2097 4281, GRID grid.29857.31, Biology Department, , Pennsylvania State University, ; University Park, PA USA
[56
]ISNI 0000 0001 2292 8158, GRID grid.253559.d, Department of Biological Science, , California State University Fullerton, ; Fullerton, CA USA
[58
]ISNI 0000 0001 0696 9806, GRID grid.148374.d, Massey University, School of Fundamental Sciences, ; Palmerston North, New Zealand
[59
]ISNI 0000000122986657, GRID grid.34477.33, Department of Biology, , University of Washington, ; Seattle, WA USA
[60
]ISNI 0000 0004 1936 8403, GRID grid.9909.9, Centre for Plant Sciences, Faculty of Biological Sciences, , University of Leeds, ; Leeds, UK
[61
]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Department of Plant Sciences, , University of Oxford, ; Oxford, UK
[62
]ISNI 0000 0004 1936 7857, GRID grid.1002.3, School of Biological Sciences, , Monash University, Melbourne, ; Victoria, Australia
[64
]ISNI 0000 0004 0385 4466, GRID grid.443909.3, Facultad de Ciencias Forestales y de la Conservación de la Naturaleza, , Universidad de Chile, ; Santiago, Chile
[65
]ISNI 0000 0004 0620 715X, GRID grid.418377.e, Genome Institute of Singapore, ; Singapore, Singapore
[66
]ISNI 0000 0004 0491 976X, GRID grid.418390.7, Max Planck Institute of Molecular Plant Physiology, ; Potsdam-Golm, Germany
[67
]ISNI 0000 0004 1936 8024, GRID grid.8391.3, Biosciences, College of Life and Environmental Sciences, , University of Exeter, ; Exeter, UK
[69
]ISNI 0000000419368710, GRID grid.47100.32, Department of Ecology and Evolutionary Biology, , Yale University, ; New Haven, CT USA
[70
]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Biology, , University of Toronto Mississauga, ; Mississauga, Ontario Canada
[71
]ISNI 0000 0001 2342 0938, GRID grid.1018.8, School of Life Sciences, , La Trobe University, ; Bundoora, Victoria Australia
[72
]ISNI 0000 0001 2168 186X, GRID grid.134563.6, CyVerse, BIO5 Institute, , University of Arizona, ; Tucson, AZ USA
[73
]ISNI 0000 0001 0462 7212, GRID grid.1006.7, School of Natural and Environmental Sciences, , Newcastle University, ; Newcastle upon Tyne, UK
[74
]ISNI 0000000114809378, GRID grid.266757.7, University of Missouri, St Louis, ; St Louis, MO USA
[75
]ISNI 0000 0001 2190 4373, GRID grid.7700.0, Centre for Organismal Studies Heidelberg, Department of Biodiversity and Plant Systematics,
Botanic Garden and Herbarium Heidelberg, , University of Heidelberg, ; Heidelberg, Germany
[77
]ISNI 0000 0004 0514 8477, GRID grid.499494.d, Royal Horticultural Society Garden Wisley, ; Woking, UK
[78
]ISNI 0000 0004 0457 9566, GRID grid.9435.b, University of Reading Herbarium, School of Biological Sciences, University of Reading,
; Reading, UK
[79
]ISNI 0000 0004 1936 9457, GRID grid.8993.b, Department of Pharmaceutical Biosciences, , Uppsala University, ; Uppsala, Sweden
[80
]ISNI 0000 0001 2171 1133, GRID grid.4868.2, School of Biological and Chemical Sciences, , Queen Mary University of London, ; London, UK
[81
]ISNI 000000041936877X, GRID grid.5386.8, Boyce Thompson Institute, , Cornell University, ; Ithaca, NY USA
[82
]ISNI 0000 0004 1936 7304, GRID grid.1010.0, Environment Institute, School of Biological Science, , University of Adelaide, ; Adelaide, South Australia Australia
[83
]ISNI 0000 0004 1936 7961, GRID grid.26009.3d, Department of Biology, , Duke University, ; Durham, NC USA
[84
]ISNI 0000 0000 8612 0361, GRID grid.419533.9, Smithsonian Environmental Research Center, ; Edgewater, MD USA
[85
]ISNI 0000 0001 0727 7545, GRID grid.411015.0, Department of Biological Sciences, , University of Alabama, ; Tuscaloosa, AL USA
[86
]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, School of Molecular and Cell Biology, , University of the Witwatersrand, ; Johannesburg, South Africa
[87
]ISNI 0000 0000 9620 8332, GRID grid.258509.3, Department of Ecology, Evolution and Organismal Biology, , Kennesaw State University, ; Kennesaw, GA USA
[90
]ISNI 0000 0001 2097 4353, GRID grid.4903.e, Millennium Seed Bank, Wakehurst, , Royal Botanic Gardens, ; Kew, Ardingly UK
[91
]ISNI 0000 0004 1936 7910, GRID grid.1012.2, The UWA Institute of Agriculture, , The University of Western Australia, ; Perth, Western Australia Australia
[92
]ISNI 0000 0001 2163 0069, GRID grid.416738.f, Centers for Disease Control and Prevention, ; Atlanta, GA USA
[93
]GRID grid.493004.a, Department of Primary Industries and Regional Development, ; Perth, Western Australia Australia
[94
]ISNI 0000 0004 1936 9991, GRID grid.35403.31, Department of Crop Sciences, , University of Illinois at Urbana-Champaign, ; Urbana, IL USA
[95
]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Ecology and Evolutionary Biology, , The University of Toronto, ; Ontario, Canada
[96
]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Department of Ecology and Evolutionary Biology, , University of California, Irvine, ; Irvine, CA USA
[97
]ISNI 0000 0001 2315 1184, GRID grid.411461.7, Department of Ecology and Evolutionary Biology, , University of Tennessee, ; Knoxville, TN USA
[98
]ISNI 0000 0001 2173 6074, GRID grid.40803.3f, Department of Plant and Microbial Biology, , North Carolina State University, ; Raleigh, NC USA
[100
]ISNI 0000 0000 9831 5270, GRID grid.266621.7, Department of Biology, , University of Louisiana at Lafayette, ; Lafayette, LA USA
[101
]ISNI 0000 0004 1936 8972, GRID grid.25879.31, Morris Arboretum of the University of Pennsylvania, ; Philadelphia, PA USA
[102
]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Koffler Scientific Reserve, , University of Toronto, ; King City, Ontario Canada
[103
]ISNI 0000 0004 1937 0650, GRID grid.7400.3, Department of Systematic and Evolutionary Botany, , University of Zurich, ; Zurich, Switzerland
[104
]ISNI 0000 0004 0546 0241, GRID grid.19188.39, National Taiwan University, Institute of Ecology and Evolutionary Biology, Department
of Life Science, ; Taipei, Taiwan
[105
]ISNI 0000 0004 1936 9457, GRID grid.8993.b, Systematic Biology, Department of Organismal Biology, Evolutionary Biology Centre,
, Uppsala University, ; Uppsala, Sweden
[106
]ISNI 0000 0001 0694 4940, GRID grid.438526.e, Department of Plant Pathology, , Physiology and Weed Science, Virginia Tech, ; Blacksburg, VA USA
[107
]ISNI 0000000119573309, GRID grid.9227.e, CAS Key Laboratory of Genome Sciences and Information, Beijing Key Laboratory of Genome
and Precision Medicine Technologies, Beijing Institute of Genomics, , Chinese Academy of Sciences, ; Beijing, China
[108
]ISNI 0000 0004 1760 1136, GRID grid.412243.2, Key Laboratory of Agricultural Biological Functional Genes, , Northeast Agricultural University, ; Harbin, China
[109
]ISNI 0000 0000 9526 6338, GRID grid.412608.9, College of Life Science, , Qingdao Agricultural University, ; Qingdao, China
[110
]ISNI 0000 0001 1302 4958, GRID grid.55614.33, Agriculture and Agri-Food Canada, ; Lacombe, Alberta Canada
[111
]ISNI 0000 0004 0375 4078, GRID grid.1032.0, Department of Environment and Agriculture, , Curtin University, ; Bentley, Western Australia Australia
[112
]ISNI 0000 0001 2162 3504, GRID grid.134936.a, Bond Life Sciences Center, Division of Biological Sciences, , University of Missouri, ; Columbia, MO USA
[113
]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Department of Zoology, , University of British Columbia, ; Vancouver, British Columbia Canada
[114
]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, University Herbarium and Department of Integrative Biology, , University of California, Berkeley, ; Berkeley, CA USA
[117
]ISNI 0000 0001 0526 1937, GRID grid.410727.7, Agricultural Genome Institute at Shenzhen, , Chinese Academy of Agricultural Sciences, ; Shenzhen, China
[122
]ISNI 0000 0004 1936 738X, GRID grid.213876.9, Georgia Advanced Computing Resource Center, , University of Georgia, ; Athens, GA USA
[123
]ISNI 0000 0001 0672 1122, GRID grid.268187.2, Department of Biological Sciences, , Western Michigan University, ; Kalamazoo, MI USA
[124
]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Department of Computer Science and Engineering, , University of California, San Diego, ; San Diego, CA USA
[125
]ISNI 0000 0001 2156 6853, GRID grid.42505.36, Lawrence J. Ellison Institute for Transformative Medicine, , University of Southern California, ; Los Angeles, CA USA
[126
]ISNI 0000 0004 0386 9246, GRID grid.267301.1, Microbiology, Immunology and Biochemistry, , The University of Tennessee Health Science Center, ; Memphis, TN USA
[127
]ISNI 0000 0004 1936 9991, GRID grid.35403.31, Department of Computer Science, , University of Illinois, Urbana-Champaign, ; Urbana, IL USA
[128
]ISNI 0000 0001 2162 3504, GRID grid.134936.a, Division of Biological Sciences, , University of Missouri, ; Columbia, MO USA
[129
]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Arizona Research Laboratories, , University of Arizona, ; Tucson, AZ USA
[130
]ISNI 0000 0001 1014 7864, GRID grid.458495.1, Key Laboratory of Plant Resources Conservation and Sustainable Utilization, , South China Botanical Garden, Chinese Academy of Sciences, ; Guangzhou, China
[131
]ISNI 0000 0004 1799 1111, GRID grid.410732.3, Flower Research Institute, , Yunnan Academy of Agricultural Sciences, ; Kunming, China
Article
Publisher ID: 1693DOI: 10.1038/s41586-019-1693-2
PMC ID: 6872490
PubMed ID: 31645766
SO-VID: 52c32687-948e-4704-b9f4-8525082bcc2c
Copyright © © The Author(s) 2019
License:
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
History
Date
received
: 17
November
2017
Date
accepted
: 12
September
2019
Categories
Subject:
Article
Custom metadata
issue-copyright-statement © The Author(s), under exclusive licence to Springer Nature Limited 2019
ScienceOpen disciplines: Uncategorized
Data availability:
ScienceOpen disciplines: Uncategorized