Chromosome-scale genome assembly of bread wheat's wild relative Triticum timopheevii.


Journal

Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192

Informations de publication

Date de publication:
23 Apr 2024
Historique:
received: 16 01 2024
accepted: 15 04 2024
medline: 24 4 2024
pubmed: 24 4 2024
entrez: 23 4 2024
Statut: epublish

Résumé

Wheat (Triticum aestivum) is one of the most important food crops with an urgent need for increase in its production to feed the growing world. Triticum timopheevii (2n = 4x = 28) is an allotetraploid wheat wild relative species containing the A

Identifiants

pubmed: 38653999
doi: 10.1038/s41597-024-03260-w
pii: 10.1038/s41597-024-03260-w
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

420

Subventions

Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BB/P016855/1
Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BB/P016855/1
Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BB/P016855/1
Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BBS/E/ER/23NB0006
Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BBS/E/ER/23NB0006
Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BB/P016855/1
Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BB/P016855/1
Organisme : U.S. Department of Agriculture (United States Department of Agriculture)
ID : 2030-21000-056-00D
Organisme : U.S. Department of Agriculture (United States Department of Agriculture)
ID : 2030-21000-056-00D

Informations de copyright

© 2024. The Author(s).

Références

Dvořák, J., Terlizzi, P. D., Zhang, H.-B. & Resta, P. The evolution of polyploid wheats: identification of the A genome donor species. Genome 36, 21–31 (1993).
pubmed: 18469969 doi: 10.1139/g93-004
Dvorak, J. & Zhang, H.-B. Variation in repeated nucleotide sequences sheds light on the phylogeny of the wheat B and G genomes. Proceedings of the National Academy of Sciences 87, 9640–9644 (1990).
doi: 10.1073/pnas.87.24.9640
Ahmed, H. I. et al. Einkorn genomics sheds light on history of the oldest domesticated wheat. Nature 620, 830–838 (2023).
pubmed: 37532937 pmcid: 10447253 doi: 10.1038/s41586-023-06389-7
Rodriguez, S., Maestra, B., Perera, E., Diez, M. & Naranjo, T. Pairing affinities of the B-and G-genome chromosomes of polyploid wheats with those of Aegilops speltoides. Genome 43, 814–819 (2000).
pubmed: 11081971 doi: 10.1139/g00-055
Li, L. F. et al. Genome sequences of five Sitopsis species of Aegilops and the origin of polyploid wheat B subgenome. Molecular plant 15, 488–503 (2022).
pubmed: 34979290 doi: 10.1016/j.molp.2021.12.019
Dvořák, J. Triticum Species (Wheat). Encyclopedia of Genetics, 2060–2068 (2001).
Jiang, J. & Gill, B. S. Different species-specific chromosome translocations inTriticum timopheevii and T. turgidum support the diphyletic origin of polyploid wheats. Chromosome Research 2, 59–64 (1994).
pubmed: 8162322 doi: 10.1007/BF01539455
Maestra, B. & Naranjo, T. Structural chromosome differentiation between Triticum timopheevii and T. turgidum and T. aestivum. Theoretical and Applied Genetics 98, 744–750 (1999).
doi: 10.1007/s001220051130
Rodriguez, S., Perera, E., Maestra, B., Díez, M. & Naranjo, T. Chromosome structure of Triticum timopheevii relative to T. turgidum. Genome 43, 923–930 (2000).
pubmed: 11195344 doi: 10.1139/g00-062
Devi, U. et al. Development and characterisation of interspecific hybrid lines with genome-wide introgressions from Triticum timopheevii in a hexaploid wheat background. BMC Plant Biol 19, 183 (2019).
pubmed: 31060503 pmcid: 6501383 doi: 10.1186/s12870-019-1785-z
Brown-Guedira, G. L., Singh, S. & Fritz, A. K. Performance and Mapping of Leaf Rust Resistance Transferred to Wheat from Triticum timopheevii subsp. armeniacum. Phytopathology 93, 784–789 (2003).
pubmed: 18943158 doi: 10.1094/PHYTO.2003.93.7.784
Singh, A. K. et al. Genetics and mapping of a new leaf rust resistance gene in Triticum aestivum L. × Triticum timopheevii Zhuk. derivative ‘Selection G12. J Genet 96, 291–297 (2017).
pubmed: 28674228 doi: 10.1007/s12041-017-0760-4
Leonova, I. N. et al. Microsatellite mapping of a leaf rust resistance gene transferred to common wheat from Triticum timopheevii. Cereal Research Communications 38, 211–219 (2010).
doi: 10.1556/CRC.38.2010.2.7
McIntosh, R. & Gyarfas, J. Triticum timopheevii as a source of resistance to wheat stem rust. Zeitschrift fur Pflanzenzuchtung 66, 240–248 (1971).
Wu, S., Pumphrey, M. & Bai, G. Molecular Mapping of Stem-Rust-Resistance Gene Sr40 in Wheat. Crop Science 49, 1681–1686 (2009).
doi: 10.2135/cropsci2008.11.0666
Allard, R. & Shands, R. Inheritance of resistance to stem rust and powdery mildew in cytologically stable spring wheats derived from Triticum timopheevii. Phytopathology 44, 266–274 (1954).
Perugini, L. D., Murphy, J. P., Marshall, D. & Brown-Guedira, G. Pm37, a new broadly effective powdery mildew resistance gene from Triticum timopheevii. Theoretical and Applied Genetics 116, 417–425 (2008).
pubmed: 18092148 doi: 10.1007/s00122-007-0679-x
Qin, B. et al. Collinearity-based marker mining for the fine mapping of Pm6, a powdery mildew resistance gene in wheat. Theoretical and Applied Genetics 123, 207–218 (2011).
pubmed: 21468676 doi: 10.1007/s00122-011-1577-9
Steed, A. et al. Identification of Fusarium Head Blight Resistance in Triticum timopheevii Accessions and Characterization of Wheat-T. timopheevii Introgression Lines for Enhanced Resistance. Frontiers in Plant Science 13 (2022).
Malihipour, A., Gilbert, J., Fedak, G., Brûlé-Babel, A. & Cao, W. Characterization of agronomic traits in a population of wheat derived from Triticum timopheevii and their association with Fusarium head blight. European Journal of Plant Pathology 144, 31–43 (2016).
doi: 10.1007/s10658-015-0744-2
Brown-Guedira, G. et al. Evaluation of a collection of wild timopheevi wheat for resistance to disease and arthropod pests. Plant disease 80, 928–933 (1996).
doi: 10.1094/PD-80-0928
Badridze, G., Weidner, A., Asch, F. & Börner, A. Variation in salt tolerance within a Georgian wheat germplasm collection. Genetic resources and crop evolution 56, 1125–1130 (2009).
doi: 10.1007/s10722-009-9436-0
Yudina, R., Leonova, I., Salina, E. & Khlestkina, E. Change in salt tolerance of bread wheat as a result of the introgression of the genetic material of Aegilops speltoides and Triticum timopheevii. Russian Journal of Genetics: Applied Research 6, 244–248 (2016).
Lehmensiek, A., Bovill, W., Banks, P., Sutherland, M. Molecular characterization of a Triticum timopheevii introgression in a Wentworth/Lang population. (2008).
Hu, X. et al. Zn and Fe concentration variations of grain and flag leaf and the relationship with NAM-G1 gene in Triticum timopheevii (Zhuk.) Zhuk. ssp. timopheevii. Cereal Research Communications 45, 421–431 (2017).
doi: 10.1556/0806.45.2017.022
Walkowiak, S. et al. Multiple wheat genomes reveal global variation in modern breeding. Nature 588, 277–283 (2020).
pubmed: 33239791 pmcid: 7759465 doi: 10.1038/s41586-020-2961-x
Keilwagen, J. et al. Detecting major introgressions in wheat and their putative origins using coverage analysis. Scientific Reports 12, 1908 (2022).
pubmed: 35115645 pmcid: 8813953 doi: 10.1038/s41598-022-05865-w
Keilwagen, J. et al. Finding needles in a haystack: identification of inter-specific introgressions in wheat genebank collections using low-coverage sequencing data. Frontiers in Plant Science 14 (2023).
King, J. et al. Introgression of the Triticum timopheevii Genome Into Wheat Detected by Chromosome-Specific Kompetitive Allele Specific PCR Markers. Frontiers in Plant Science 13 (2022).
Grewal, S. et al. Rapid identification of homozygosity and site of wild relative introgressions in wheat through chromosome-specific KASP genotyping assays. Plant Biotechnol J 18, 743–755 (2020).
pubmed: 31465620 doi: 10.1111/pbi.13241
Belton, J. M. et al. Hi-C: a comprehensive technique to capture the conformation of genomes. Methods 58, 268–276 (2012).
pubmed: 22652625 doi: 10.1016/j.ymeth.2012.05.001
Wenger, A. M. et al. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nature Biotechnology 37, 1155–1162 (2019).
pubmed: 31406327 pmcid: 6776680 doi: 10.1038/s41587-019-0217-9
Driguez, P. et al. LeafGo: Leaf to Genome, a quick workflow to produce high-quality de novo plant genomes using long-read sequencing technology. Genome biology 22, 256 (2021).
pubmed: 34479618 pmcid: 8414726 doi: 10.1186/s13059-021-02475-z
Dong, L. et al. Single-molecule real-time transcript sequencing facilitates common wheat genome annotation and grain transcriptome research. BMC Genomics 16, 1039 (2015).
pubmed: 26645802 pmcid: 4673716 doi: 10.1186/s12864-015-2257-y
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. 2011 17, 3 (2011).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
pubmed: 24695404 pmcid: 4103590 doi: 10.1093/bioinformatics/btu170
Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).
pubmed: 21217122 pmcid: 3051319 doi: 10.1093/bioinformatics/btr011
Wang, H. et al. Estimation of genome size using k-mer frequencies from corrected long reads. arXiv:200311817 [q-bioGN] (2020).
Ranallo-Benavidez, T. R., Jaron, K. S. & Schatz, M. C. GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. Nature Communications 11, 1432 (2020).
pubmed: 32188846 pmcid: 7080791 doi: 10.1038/s41467-020-14998-3
Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nature Methods 18, 170–175 (2021).
pubmed: 33526886 pmcid: 7961889 doi: 10.1038/s41592-020-01056-5
Formenti, G. et al. Gfastats: conversion, evaluation and manipulation of genome sequences using assembly graphs. Bioinformatics 38, 4214–4216 (2022).
pubmed: 35799367 pmcid: 9438950 doi: 10.1093/bioinformatics/btac460
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
Laetsch, D., Blaxter, M. BlobTools: Interrogation of genome assemblies. F1000Research 6 (2017).
Korbel, J. O. & Lee, C. Genome assembly and haplotyping with Hi-C. Nature Biotechnology 31, 1099–1101 (2013).
pubmed: 24316648 doi: 10.1038/nbt.2764
Ghurye, J. et al. Integrating Hi-C links with assembly graphs for chromosome-scale assembly. PLOS Computational Biology 15, e1007273 (2019).
pubmed: 31433799 pmcid: 6719893 doi: 10.1371/journal.pcbi.1007273
Howe, K. et al. Significantly improving the quality of genome assemblies through curation. GigaScience 10 (2021).
Zhu, T. et al. Optical maps refine the bread wheat Triticum aestivum cv. Chinese Spring genome assembly. The Plant Journal 107, 303–314 (2021).
pubmed: 33893684 pmcid: 8360199 doi: 10.1111/tpj.15289
Kurtz, S. et al. Versatile and open software for comparing large genomes. Genome biology 5, R12 (2004).
pubmed: 14759262 pmcid: 395750 doi: 10.1186/gb-2004-5-2-r12
Venturini, L., Caim, S., Kaithakottil, G. G., Mapleson, D. L., Swarbreck, D. Leveraging multiple transcriptome assembly methods for improved gene structure annotation. GigaScience 7 (2018).
Boden, S. A. et al. Updated guidelines for gene nomenclature in wheat. Theoretical and Applied Genetics 136, 72 (2023).
pubmed: 36952017 doi: 10.1007/s00122-023-04253-w
Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nature Biotechnology 37, 907–915 (2019).
pubmed: 31375807 pmcid: 7605509 doi: 10.1038/s41587-019-0201-4
Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).
pubmed: 29750242 pmcid: 6137996 doi: 10.1093/bioinformatics/bty191
Mapleson, D., Venturini, L., Kaithakottil, G., Swarbreck, D. Efficient and accurate detection of splice junctions from RNA-seq with Portcullis. GigaScience 7 (2018).
Kovaka, S. et al. Transcriptome assembly from long-read RNA-seq alignments with StringTie2. Genome biology 20, 278 (2019).
pubmed: 31842956 pmcid: 6912988 doi: 10.1186/s13059-019-1910-1
Shao, M. & Kingsford, C. Accurate assembly of transcripts through phase-preserving graph decomposition. Nature Biotechnology 35, 1167–1169 (2017).
pubmed: 29131147 pmcid: 5722698 doi: 10.1038/nbt.4020
Gotoh, O. A space-efficient and accurate method for mapping and aligning cDNA sequences onto genomic sequence. Nucleic Acids Research 36, 2630–2638 (2008).
pubmed: 18344523 pmcid: 2377433 doi: 10.1093/nar/gkn105
Li, H. Protein-to-genome alignment with miniprot. Bioinformatics 39 (2023).
Stanke, M. & Morgenstern, B. AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Research 33, W465–W467 (2005).
pubmed: 15980513 pmcid: 1160219 doi: 10.1093/nar/gki458
Haas, B. J. et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome biology 9, R7 (2008).
pubmed: 18190707 pmcid: 2395244 doi: 10.1186/gb-2008-9-1-r7
IWGSC et al. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361 (2018).
Shumate, A. & Salzberg, S. L. Liftoff: accurate mapping of gene annotations. Bioinformatics 37, 1639–1643 (2021).
pubmed: 33320174 pmcid: 8289374 doi: 10.1093/bioinformatics/btaa1016
Seppey, M., Manni, M., Zdobnov, E. M. in Gene Prediction: Methods and Protocols (ed. Kollmar M.) BUSCO: Assessing Genome Assembly and Annotation Completeness (Springer New York, 2019).
Kong, L. et al. CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Research 35, W345–W349 (2007).
pubmed: 17631615 pmcid: 1933232 doi: 10.1093/nar/gkm391
Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nature Biotechnology 34, 525–527 (2016).
pubmed: 27043002 doi: 10.1038/nbt.3519
Gautier, R. gtrichard/deepStats: New tools and much needed fixes. Zenodo https://doi.org/10.5281/zenodo.3668336 (2020).
Consortium, U. UniProt: a hub for protein information. Nucleic Acids Res 43, D204–212 (2015).
doi: 10.1093/nar/gku989
Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014).
pubmed: 24451626 pmcid: 3998142 doi: 10.1093/bioinformatics/btu031
Kourelis, J. & Van Der Hoorn, R. A. Defended to the nines: 25 years of resistance gene cloning identifies nine mechanisms for R protein function. The Plant cell 30, 285–299 (2018).
pubmed: 29382771 pmcid: 5868693 doi: 10.1105/tpc.17.00579
Chen, R., Gajendiran, K. & Wulff, B. B. H. R we there yet? Advances in cloning resistance genes for engineering immunity in crop plants. Current opinion in plant biology 77, 102489 (2024).
pubmed: 38128298 doi: 10.1016/j.pbi.2023.102489
Steuernagel, B. et al. The NLR-Annotator Tool Enables Annotation of the Intracellular Immune Receptor Repertoire1 [OPEN]. Plant Physiology 183, 468–482 (2020).
pubmed: 32184345 pmcid: 7271791 doi: 10.1104/pp.19.01273
Ni, P. et al. DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing. Nature communications 14, 4054 (2023).
pubmed: 37422489 pmcid: 10329642 doi: 10.1038/s41467-023-39784-9
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. bioinformatics 25, 1754–1760 (2009).
pubmed: 19451168 pmcid: 2705234 doi: 10.1093/bioinformatics/btp324
NCBI Sequence Read Archive. https://identifiers.org/ncbi/insdc.sra:ERP156445 (2024).
NCBI GenBank. https://identifiers.org/ncbi/insdc.gca:GCA_963921465.1 (2024).
Grewal, S. et al. Data from: Chromosome-scale genome assembly of bread wheat’s wild relative Triticum timopheevii [Dataset]. Dryad. https://doi.org/10.5061/dryad.mpg4f4r6p (2024).
Dong, P. et al. 3D chromatin architecture of large plant genomes determined by local A/B compartments. Molecular plant 10, 1497–1509 (2017).
pubmed: 29175436 doi: 10.1016/j.molp.2017.11.005
Mascher, M. et al. A chromosome conformation capture ordered sequence of the barley genome. Nature 544, 427–433 (2017).
pubmed: 28447635 doi: 10.1038/nature22043
Anamthawat-Jónsson, K. & Heslop-Harrison, J. Centromeres, telomeres and chromatin in the interphase nucleus of cereals. Caryologia 43, 205–213 (1990).
doi: 10.1080/00087114.1990.10796999
Cowan, C. R., Carlton, P. M. & Cande, W. Z. The polar arrangement of telomeres in interphase and meiosis. Rabl organization and the bouquet. Plant Physiology 125, 532–538 (2001).
pubmed: 11161011 pmcid: 1539364 doi: 10.1104/pp.125.2.532
Rhie, A., Walenz, B. P., Koren, S. & Phillippy, A. M. Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies. Genome biology 21, 1–27 (2020).
doi: 10.1186/s13059-020-02134-9
Ou, S., Chen, J. & Jiang, N. Assessing genome assembly quality using the LTR Assembly Index (LAI). Nucleic acids research 46, e126–e126 (2018).
pubmed: 30107434 pmcid: 6265445
Poretti, M., Praz, C. R., Sotiropoulos, A. G. & Wicker, T. A survey of lineage‐specific genes in Triticeae reveals de novo gene evolution from genomic raw material. Plant Direct 7, e484 (2023).
pubmed: 36937792 pmcid: 10020141 doi: 10.1002/pld3.484
Yao, E. et al. GrainGenes: a data-rich repository for small grains genetics and genomics. Database 2022 (2022).
Krzywinski, M. et al. Circos: An information aesthetic for comparative genomics. Genome Res 19, 1639–1645 (2009).
pubmed: 19541911 pmcid: 2752132 doi: 10.1101/gr.092759.109

Auteurs

Surbhi Grewal (S)

Wheat Research Centre, Department of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Loughborough, LE12 5RD, UK. surbhi.grewal@nottingham.ac.uk.

Cai-Yun Yang (CY)

Wheat Research Centre, Department of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Loughborough, LE12 5RD, UK.

Duncan Scholefield (D)

Wheat Research Centre, Department of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Loughborough, LE12 5RD, UK.

Stephen Ashling (S)

Wheat Research Centre, Department of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Loughborough, LE12 5RD, UK.

Sreya Ghosh (S)

Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK.

David Swarbreck (D)

Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK.

Joanna Collins (J)

Genome Reference Informatics Team, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1RQ, UK.

Eric Yao (E)

University of California, Department of Bioengineering, Berkeley, CA, 94720, USA.
United States Department of Agriculture-Agricultural Research Service, Western Regional Research Center, Crop Improvement and Genetics Research Unit, 800 Buchanan St., Albany, CA, 94710, USA.

Taner Z Sen (TZ)

University of California, Department of Bioengineering, Berkeley, CA, 94720, USA.
United States Department of Agriculture-Agricultural Research Service, Western Regional Research Center, Crop Improvement and Genetics Research Unit, 800 Buchanan St., Albany, CA, 94710, USA.

Michael Wilson (M)

University of Nottingham, University Park, Nottingham, NG7 2RD, UK.

Levi Yant (L)

University of Nottingham, University Park, Nottingham, NG7 2RD, UK.

Ian P King (IP)

Wheat Research Centre, Department of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Loughborough, LE12 5RD, UK.

Julie King (J)

Wheat Research Centre, Department of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Loughborough, LE12 5RD, UK.

Articles similaires

Genome Size Genome, Plant Magnoliopsida Evolution, Molecular Arabidopsis
Triticum Transcription Factors Gene Expression Regulation, Plant Plant Proteins Salt Stress
Zea mays Triticum China Seasons Crops, Agricultural
Humans DNA Methylation Female Male Alcohol Oxidoreductases

Classifications MeSH