Diversity Analysis of 80,000 Wheat Accessions Reveals Consequences and Opportunities of Selection Footprints

Overview

Journal Nat Commun

Specialty Biology

Date 2020 Sep 12

PMID 32917907

Citations 90

Authors

Carolina Sansaloni

Jorge Franco

Bruno Santos

Lawrence Percival-Alwyn

Sukhwinder Singh

Cesar Petroli

Jaime Campos

Kate Dreher

Thomas Payne

David Marshall

Benjamin Kilian

Iain Milne

Sebastian Raubach

Paul Shaw

Gordon Stephen

Jason Carling

Carolina Saint Pierre

Juan Burgueno

Jose Crosa

Huihui Li

Carlos Guzman

Zakaria Kehel

Ahmed Amri

Andrzej Kilian

Peter Wenzl

Cristobal Uauy

Marianne Banziger

Mario Caccamo

Kevin Pixley

Affiliations

Soon will be listed here.

Abstract

Undomesticated wild species, crop wild relatives, and landraces represent sources of variation for wheat improvement to address challenges from climate change and the growing human population. Here, we study 56,342 domesticated hexaploid, 18,946 domesticated tetraploid and 3,903 crop wild relatives in a massive-scale genotyping and diversity analysis. Using DArTseq technology, we identify more than 300,000 high-quality SNPs and SilicoDArT markers and align them to three reference maps: the IWGSC RefSeq v1.0 genome assembly, the durum wheat genome assembly (cv. Svevo), and the DArT genetic map. On average, 72% of the markers are uniquely placed on these maps and 50% are linked to genes. The analysis reveals landraces with unexplored diversity and genetic footprints defined by regions under selection. This provides fertile ground to develop wheat varieties of the future by exploring specific gene or chromosome regions and identifying germplasm conserving allelic diversity missing in current breeding programs.

Citing Articles

Genome-wide association study identifies QTL and candidate genes for grain size and weight in a Triticum turgidum collection.

Mangini G, Nigro D, Curci P, Simeone R, Blanco A Plant Genome. 2025; 18(1):e20562.

PMID: 39868635 PMC: 11771687. DOI: 10.1002/tpg2.20562.

Genotyping Genebank Collections: Strategic Approaches and Considerations for Optimal Collection Management.

Anglin N, Wenzl P, Azevedo V, Lusty C, Ellis D, Gao D Plants (Basel). 2025; 14(2).

PMID: 39861604 PMC: 11768347. DOI: 10.3390/plants14020252.

Exploring the genetic diversity and population structure of an ancient hexaploid wheat species Triticum sphaerococcum using SNP markers.

Mazumder A, Budhlakoti N, Kumar M, Pradhan A, Kumar S, Babu P BMC Plant Biol. 2024; 24(1):1188.

PMID: 39695987 PMC: 11656872. DOI: 10.1186/s12870-024-05968-8.

Efficient large-scale genomic prediction in approximate genome-based kernel model.

Liu H, Xu J, Wang X, Wang H, Wang L, Shen Y Theor Appl Genet. 2024; 138(1):6.

PMID: 39666050 DOI: 10.1007/s00122-024-04793-9.

Cytogenetic and molecular identification of novel wheat- addition lines with resistance to leaf rust and the presence of leaf pubescence trait.

Motsnyi I, Halaiev O, Alieksieieva T, Chebotar G, Chebotar S, Betekhtin A Front Plant Sci. 2024; 15:1482211.

PMID: 39600899 PMC: 11588455. DOI: 10.3389/fpls.2024.1482211.

References

Goel S, Yadav M, Singh K, Jaat R, Singh N . Exploring diverse wheat germplasm for novel alleles in HMW-GS for bread quality improvement. J Food Sci Technol. 2018; 55(8):3257-3262. PMC: 6046000. DOI: 10.1007/s13197-018-3259-y. View

Talebnia F, Karakashev D, Angelidaki I . Production of bioethanol from wheat straw: An overview on pretreatment, hydrolysis and fermentation. Bioresour Technol. 2009; 101(13):4744-53. DOI: 10.1016/j.biortech.2009.11.080. View

Wang S, Wong D, Forrest K, Allen A, Chao S, Huang B . Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array. Plant Biotechnol J. 2014; 12(6):787-96. PMC: 4265271. DOI: 10.1111/pbi.12183. View

Tanksley S, McCouch S . Seed banks and molecular maps: unlocking genetic potential from the wild. Science. 1997; 277(5329):1063-6. DOI: 10.1126/science.277.5329.1063. View

Reif J, Zhang P, Dreisigacker S, Warburton M, van Ginkel M, Hoisington D . Wheat genetic diversity trends during domestication and breeding. Theor Appl Genet. 2005; 110(5):859-64. DOI: 10.1007/s00122-004-1881-8. View

McCouch S, Baute G, Bradeen J, Bramel P, Bretting P, Buckler E . Agriculture: Feeding the future. Nature. 2013; 499(7456):23-4. DOI: 10.1038/499023a. View

Bhatta M, Morgounov A, Belamkar V, Poland J, Baenziger P . Unlocking the novel genetic diversity and population structure of synthetic Hexaploid wheat. BMC Genomics. 2018; 19(1):591. PMC: 6090860. DOI: 10.1186/s12864-018-4969-2. View

Milner S, Jost M, Taketa S, Mazon E, Himmelbach A, Oppermann M . Genebank genomics highlights the diversity of a global barley collection. Nat Genet. 2018; 51(2):319-326. DOI: 10.1038/s41588-018-0266-x. View

Muller T, Schierscher-Viret B, Fossati D, Brabant C, Schori A, Keller B . Unlocking the diversity of genebanks: whole-genome marker analysis of Swiss bread wheat and spelt. Theor Appl Genet. 2017; 131(2):407-416. DOI: 10.1007/s00122-017-3010-5. View

10.

Langridge P, Waugh R . Harnessing the potential of germplasm collections. Nat Genet. 2019; 51(2):200-201. DOI: 10.1038/s41588-018-0340-4. View

11.

Pixley K, Falck-Zepeda J, Giller K, Glenna L, Gould F, Mallory-Smith C . Genome Editing, Gene Drives, and Synthetic Biology: Will They Contribute to Disease-Resistant Crops, and Who Will Benefit?. Annu Rev Phytopathol. 2019; 57:165-188. DOI: 10.1146/annurev-phyto-080417-045954. View

12.

Vikram P, Franco J, Burgueno-Ferreira J, Li H, Sehgal D, Saint Pierre C . Unlocking the genetic diversity of Creole wheats. Sci Rep. 2016; 6:23092. PMC: 4791556. DOI: 10.1038/srep23092. View

13.

Romay M, Millard M, Glaubitz J, Peiffer J, Swarts K, Casstevens T . Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biol. 2013; 14(6):R55. PMC: 3707059. DOI: 10.1186/gb-2013-14-6-r55. View

14.

Singh S, Vikram P, Sehgal D, Burgueno J, Sharma A, Singh S . Harnessing genetic potential of wheat germplasm banks through impact-oriented-prebreeding for future food and nutritional security. Sci Rep. 2018; 8(1):12527. PMC: 6104032. DOI: 10.1038/s41598-018-30667-4. View

15.

Crossa J, Jarquin D, Franco J, Perez-Rodriguez P, Burgueno J, Saint-Pierre C . Genomic Prediction of Gene Bank Wheat Landraces. G3 (Bethesda). 2016; 6(7):1819-34. PMC: 4938637. DOI: 10.1534/g3.116.029637. View

16.

Khazaei H, Street K, Bari A, Mackay M, Stoddard F . The FIGS (focused identification of germplasm strategy) approach identifies traits related to drought adaptation in Vicia faba genetic resources. PLoS One. 2013; 8(5):e63107. PMC: 3648475. DOI: 10.1371/journal.pone.0063107. View

17.

Romero Navarro J, Willcox M, Burgueno J, Romay C, Swarts K, Trachsel S . A study of allelic diversity underlying flowering-time adaptation in maize landraces. Nat Genet. 2017; 49(3):476-480. DOI: 10.1038/ng.3784. View

18.

Wittenberg A, van der Lee T, Cayla C, Kilian A, Visser R, Schouten H . Validation of the high-throughput marker technology DArT using the model plant Arabidopsis thaliana. Mol Genet Genomics. 2005; 274(1):30-9. DOI: 10.1007/s00438-005-1145-6. View

19.

Alam M, Neal J, OConnor K, Kilian A, Topp B . Ultra-high-throughput DArTseq-based silicoDArT and SNP markers for genomic studies in macadamia. PLoS One. 2018; 13(8):e0203465. PMC: 6118395. DOI: 10.1371/journal.pone.0203465. View

20.

Zheng X, Levine D, Shen J, Gogarten S, Laurie C, Weir B . A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics. 2012; 28(24):3326-8. PMC: 3519454. DOI: 10.1093/bioinformatics/bts606. View