Application of image-based phenotyping tools to identify QTL for in-field winter survival of winter wheat (Triticum aestivum L.)

Chen, Yi; Sidhu, Harwinder S.; Kaviani, Mina; McElroy, Michel S.; Pozniak, Curtis J.; Navabi, Alireza

doi:10.1007/s00122-019-03373-6

Original Article
Published: 08 June 2019

Application of image-based phenotyping tools to identify QTL for in-field winter survival of winter wheat (Triticum aestivum L.)

Yi Chen ORCID: orcid.org/0000-0002-8210-1301¹,
Harwinder S. Sidhu¹,
Mina Kaviani¹,
Michel S. McElroy²,
Curtis J. Pozniak³ &
Alireza Navabi¹^na1

Theoretical and Applied Genetics volume 132, pages 2591–2604 (2019)Cite this article

901 Accesses
6 Citations
11 Altmetric
Metrics details

Abstract

Key message

Genome-wide association on winter survival was conducted using data from image-based phenotyping method. Nine QTL were observed and three of them with candidate gene identified.

Abstract

Winter survival is an essential trait of winter wheat (Triticum aestivum L.) grown in regions with high risk of winterkill. We characterized a diversity panel of 450 Canadian wheat varieties that included mostly winter-growth habit wheats to identify key genetic factors that contribute to higher winter survival under field conditions. To more accurately quantify winter survival differences among varieties, image-based phenotyping methods, captured by unmanned aerial vehicle (UAV) and on ground level, were used to estimate the winter survival of each varieties. Winter survival index was developed to correct for emergence when evaluating winter survival. Winter survival measurement estimated by visual estimation, UAV imagery and ground imagery showed strong correlation with each other and had comparable broad-sense heritability. Genome-wide association studies resulted in the identification of seven quantitative trait loci (QTL) for winter survival including Vrn-A1. By using the recently released annotated sequence of the wheat genome and the available RNA-Seq data, two putative candidate genes underlying the QTL for winter survival were identified. However, our study showed that certain QTL was unique to specific winter survival measurement. Collectively, our study demonstrated the feasibility of using UAV-based imagery for the identification of loci associated with winter survival in wheat. The complexity of in-field condition make our result a valuable complement to indoor frost-tolerance studies in the identification of genetic factors not directly linked to freezing tolerance.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

References

Alessi J, Power JF (1971) Influences of method of seeding and moisture on winter wheat survival and yield. Agron J 63:81. https://doi.org/10.2134/agronj1971.00021962006300010025x
Article Google Scholar
Andrews CJ (1996) How do plants survive ice? Ann Bot 78:529–536. https://doi.org/10.1006/anbo.1996.0157
Article CAS Google Scholar
Andrews CJ, Pomeroy MK, Seaman WL et al (1997) Relationships between planting date, winter survival and stress tolerances of soft white winter wheat in eastern Ontario. Can J Plant Sci 77:507–513. https://doi.org/10.4141/P96-124
Article Google Scholar
Appels R, Eversole K, Feuillet C et al (2018) Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science. https://doi.org/10.1126/science.aar7191
Article PubMed Google Scholar
Araus JL, Cairns JE (2014) Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci 19:52–61. https://doi.org/10.1016/j.tplants.2013.09.008
Article CAS PubMed Google Scholar
Babben S, Schliephake E, Janitza P et al (2018) Association genetics studies on frost tolerance in wheat (Triticum aestivum L.) reveal new highly conserved amino acid substitutions in CBF-A3, CBF-A15, VRN3 and PPD1 genes. BMC Genom. https://doi.org/10.1186/s12864-018-4795-6
Article Google Scholar
Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263–265. https://doi.org/10.1093/bioinformatics/bth457
Article CAS Google Scholar
Basnyat P, McConkey B, Lafond GP et al (2004) Optimal time for remote sensing to relate to crop grain yield on the Canadian prairies. Can J Plant Sci 84:97–103. https://doi.org/10.4141/p03-070
Article Google Scholar
Bowley S (2015) A hitchhiker’s guide to statistics in biology. Generalized linear mixed model edition. Plants et al, Kincardine
Google Scholar
Bridger GM, Falk DE, McKersie BD, Smith DL (1996) Crown freezing tolerance and field winter survival of winter cereals in eastern Canada. Crop Sci 36:150–157. https://doi.org/10.2135/cropsci1996.0011183X003600010027x
Article Google Scholar
Browning SR, Browning BL (2007) Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084–1097. https://doi.org/10.1086/521987
Article CAS PubMed PubMed Central Google Scholar
Busemeyer L, Mentrup D, Möller K et al (2013) Breedvision—a multi-sensor platform for non-destructive field-based phenotyping in plant breeding. Sensors (Switzerland) 13:2830–2847. https://doi.org/10.3390/s130302830
Article Google Scholar
Cavanagh CR, Chao S, Wang S et al (2013) Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc Natl Acad Sci 110:8057–8062. https://doi.org/10.1073/pnas.1217133110
Article PubMed Google Scholar
Cox DJ, Larsen JK, Brun LJ (1986) Winter survival response of winter wheat—tillage and cultivar selection. Agron J 78:795–801
Article Google Scholar
Cui R, Han J, Zhao S et al (2010) Functional conservation and diversification of class e floral homeotic genes in rice (Oryza sativa). Plant J. https://doi.org/10.1111/j.1365-313x.2009.04101.x
Article PubMed PubMed Central Google Scholar
Dammer KH, Dworak V, Selbeck J (2016) On-the-go phenotyping in field potatoes using camera vision. Potato Res 59:113–127. https://doi.org/10.1007/s11540-016-9315-y
Article Google Scholar
Deery D, Jimenez-Berni J, Jones HG et al (2014) Proximal remote sensing buggies and potential applications for field-based phenotyping. Agronomy 4:349–379. https://doi.org/10.3390/agronomy4030349
Article Google Scholar
Dhillon T, Pearce SP, Stockinger EJ et al (2010) Regulation of freezing tolerance and flowering in temperate cereals: the VRN-1 connection. Plant Physiol 153:1846–1858. https://doi.org/10.1104/pp.110.159079
Article CAS PubMed PubMed Central Google Scholar
Fowler B (1982) Date of seeding, fall growth, and winter survival of winter wheat and rye. Agron J 74:1060–1063. https://doi.org/10.2134/agronj1982.00021962007400060030x
Article Google Scholar
Fowler B (2012) Wheat production in the high winter stress climate of the great plains of north America—an experiment in crop adaptation. Crop Sci 52:11–20. https://doi.org/10.2135/cropsci2011.05.0279
Article Google Scholar
Fowler DB, N’Diaye A, Laudenci-Chingcuanco D, Pozniak CJ (2016) Quantitative trait loci associated with phenological development, low-temperature tolerance, grain quality, and agronomic characters in wheat (Triticum aestivum L.). PLoS ONE. https://doi.org/10.1371/journal.pone.0152185
Article PubMed PubMed Central Google Scholar
Galiba G, Quarrie SA, Sutka J et al (1995) RFLP mapping of the vernalization (Vrn1) and frost resistance (Fr1) genes on chromosome 5A of wheat. Theor Appl Genet 90:1174–1179. https://doi.org/10.1007/BF00222940
Article CAS PubMed Google Scholar
Gorash A, Armoniene R, Liatukas Brazauskas G (2017) The relationship among freezing tolerance, vernalization requirement, Ppd alleles and winter hardiness in European wheat cultivars. J Agric Sci 155:1353–1370. https://doi.org/10.1017/S0021859617000521
Article CAS Google Scholar
Grant CA, Stobbe EH, Racz GJ (1984) The effect of N and P fertilization on winter survival of winter wheat under zero-tilled and conventially tilled management. Can J Soil Sci 64:293–296
Article Google Scholar
Grieder C, Hund A, Walter A (2014) Image based phenotyping during winter: a powerful tool to assess wheat genetic variation in growth response to temperature. Funct Plant Biol 42(4):387–396
Article CAS Google Scholar
Grogan SM, Brown-Guedira G, Haley SD et al (2016) Allelic variation in developmental genes and effects on winter wheat heading date in the U.S. Great Plains. PLoS One 11:1–23. https://doi.org/10.1371/journal.pone.0152852
Article CAS Google Scholar
Gusta LV, O’Connor BJ, Gao Y-P, Jana S (2001) A re-evaluation of controlled freeze-tests and controlled environment hardening conditions to estimate the winter survival potential of hardy winter wheats. Can J Plant Sci 81:241–246. https://doi.org/10.4141/P00-068
Article Google Scholar
Haghighattalab A, González Pérez L, Mondal S et al (2016) Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries. Plant Methods 12:1–15. https://doi.org/10.1186/s13007-016-0134-6
Article CAS Google Scholar
Hamuda E, Glavin M, Jones E (2016) A survey of image processing techniques for plant extraction and segmentation in the field. Comput Electron Agric 125:184–199. https://doi.org/10.1016/j.compag.2016.04.024
Article Google Scholar
Holland JB, Nyquist WE, Cervantes-Martínez CT (2003) Estimating and interpreting heritability for plant breeding: an update. In: Janick J (ed) Plant breeding reviews, vol 22. Wiley, New York, pp 9–112
Google Scholar
Humplík JF, Lazár D, Husičková A, Spíchal L (2015) Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses—a review. Plant Methods 11:1–10. https://doi.org/10.1186/s13007-015-0072-8
Article CAS Google Scholar
Kersey PJ, Allen JE, Allot A et al (2018) Ensembl genomes 2018: an integrated omics infrastructure for non-vertebrate species. Nucleic Acids Res 46:D802–D808. https://doi.org/10.1093/nar/gkx1011
Article CAS PubMed Google Scholar
Khot LR, Sankaran S, Carter AH et al (2016) UAS imaging-based decision tools for arid winter wheat and irrigated potato production management. Int J Remote Sens 37:125–137. https://doi.org/10.1080/01431161.2015.1117685
Article Google Scholar
Laudencia-Chingcuanco D, Ganeshan S, You F et al (2011) Genome-wide gene expression analysis supports a developmental model of low temperature tolerance gene regulation in wheat (Triticum aestivum L.). BMC Genom. https://doi.org/10.1186/1471-2164-12-299
Article Google Scholar
Li L, Li N, Song SF et al (2014) Cloning and characterization of the drought-resistance OsRCI2-5 gene in rice (Oryza sativa L.). Genet Mol Res 13:4022–4035
Article CAS PubMed Google Scholar
Li Q, Zheng Q, Shen W et al (2015) Understanding the biochemical basis of temperature-induced lipid pathway adjustments in plants. Plant Cell Online 27:86–103. https://doi.org/10.1105/tpc.114.134338
Article CAS Google Scholar
Lipka AE, Tian F, Wang Q et al (2012) GAPIT: genome association and prediction integrated tool. Bioinformatics 28:2397–2399. https://doi.org/10.1093/bioinformatics/bts444
Article CAS PubMed PubMed Central Google Scholar
Loeppky H, Lafond GP, Fowler DB (1989) Seeding depth in relation to plant development, winter survival, and yield of no-till winter-wheat. Agron J 81:125–129
Article Google Scholar
Lund RE (1975) Tables for an approximate test for outliers in linear models. Technometrics 17:473–476
Article Google Scholar
Miller AK, Galiba G, Dubcovsky J (2006) A cluster of 11 CBF transcription factors is located at the frost tolerance locus Fr-Am 2 in Triticum monococcum. Mol Genet Genomics 275:193–203. https://doi.org/10.1007/s00438-005-0076-6
Article CAS PubMed Google Scholar
Murray T, Jones S, Adams E (1995) Snow mold diseases of winter wheat in washington. Washingt State Univ Coop Ext USDA, pp 1–8
Patrignani A, Ochsner TE (2015) Canopeo: a powerful new tool for measuring fractional green canopy cover. Agron J 107:2312–2320. https://doi.org/10.2134/agronj15.0150
Article CAS Google Scholar
Patterson HD, Williams ER (1976) A new class of resolvable incomplete block designs. Biometrika 63:83–92. https://doi.org/10.2307/2335087
Article Google Scholar
Pelaz S, Ditta GS, Baumann E et al (2000) B and C floral organ identity functions require SEPALLATTA MADS-box genes. Nature 405:200–203. https://doi.org/10.1038/35012103
Article CAS PubMed Google Scholar
Piepho HP, Büchse A, Truberg B (2006) On the use of multiple lattice designs and α-designs in plant breeding trials. Plant Breed. https://doi.org/10.1111/j.1439-0523.2006.01267.x
Article Google Scholar
Pittman UJ, Tipples KH (1978) Survival, yield protein content, and baking quality of hard red winter wheats grown under various fertilizer practices in southern Alberta. Can J Plant Sci 58:1049–1060
Article Google Scholar
Poland JA, Nelson RJ (2011) In the eye of the beholder: the effect of rater variability and different rating scales on QTL mapping. Phytopathology 101:290–298. https://doi.org/10.1094/phyto-03-10-0087
Article PubMed Google Scholar
Pomeroy MK, Fowler DB (1973) Use of lethal dose temperature estimates as indices of frost tolerance for wheat cold acclimationed under natural and controlled environments. Can J Plant Sci 53:489–494. https://doi.org/10.4141/cjps73-093
Article Google Scholar
R Core Team (2017) R: a language and environment for statistical computing
Ramírez-González RH, Borrill P, Lang D et al (2018) The transcriptional landscape of polyploid wheat. Science. https://doi.org/10.1126/science.aar6089
Article PubMed Google Scholar
Ribera J, Chen Y, Boomsma C, Delp EJ (2017) Counting plants using deep learning. In: 2017 IEEE global conference on signal and information processing (GlobalSIP), pp 1344–1348
Roy B, Mondal AK, Roy CK et al (2017) Towards a reference architecture for cloud-based plant genotyping and phenotyping analysis frameworks. In: 2017 IEEE international conference on software architecture (ICSA), pp 41–50
Sankaran S, Khot LR, Carter AH (2015) Field-based crop phenotyping: multispectral aerial imaging for evaluation of winter wheat emergence and spring stand. Comput Electron Agric 118:372–379. https://doi.org/10.1016/j.compag.2015.09.001
Article Google Scholar
SAS Institute Inc (2018) SAS
Sãulescu NN, Braun HJ (2001) Cold tolerance. Application of physiology in wheat breeding. CIMMYT, Mexico City, pp 111–123
Google Scholar
Schneider EF, Seaman WL (1987) Snow mold diseases and their distribution on witner wheat in Ontario in 1982-84. Can Plant Diease Surv 67:35–39
Google Scholar
Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52:591–611. https://doi.org/10.2307/2333709
Article Google Scholar
Singh D, Wang X, Kumar U et al (2019) High-throughput phenotyping enabled genetic dissection of crop lodging in wheat. Front Plant Sci 10:394. https://doi.org/10.3389/fpls.2019.00394
Article PubMed PubMed Central Google Scholar
Smith RN, Aleksic J, Butano D et al (2012) InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data. Bioinformatics 28:3163–3165. https://doi.org/10.1093/bioinformatics/bts577
Article CAS PubMed PubMed Central Google Scholar
Steponkus PL, Webb MS (1992) Freeze-induced dehydration and membrane destabilization in plants. In: Somero GN, Osmond CB, Bolis CL (eds) Water and Life. Springer, Berlin, pp 338–362
Chapter Google Scholar
Steponkus PL, Uemura M, Joseph RA et al (1998) Mode of action of the COR15a gene on the freezing tolerance of Arabidopsis thaliana. Proc Natl Acad Sci 95:14570–14575. https://doi.org/10.1073/pnas.95.24.14570
Article CAS PubMed Google Scholar
Sultana SR, Ali A, Ahmad A et al (2014) Normalized difference vegetation index as a tool for wheat yield estimation: a case study from Faisalabad. Sci World J, Pakistan. https://doi.org/10.1155/2014/725326
Book Google Scholar
Thomas JB, Schaalije GB, Grant MN (1993) Survival, height and genotype by environment interaction in winter wheat. Can J Plant Sci 73:417–427
Article Google Scholar
Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150. https://doi.org/10.1016/0034-4257(79)90013-0
Article Google Scholar
Vágújfalvi A, Galiba G, Cattivelli L, Dubcovsky J (2003) The cold-regulated transcriptional activator Cbf3 is linked to the frost-tolerance locus Fr-2A on wheat chromosome 5A. Mol Genet Genom 269:60–67. https://doi.org/10.1097/00000658-195204000-00007
Article Google Scholar
Vágújfalvi A, Aprile A, Miller A et al (2005) The expression of several Cbf genes at the Fr-A2 locus is linked to frost resistance in wheat. Mol Genet Genom 274:506–514. https://doi.org/10.1007/s00438-005-0047-y
Article CAS Google Scholar
VanRaden PM (2008) Efficient methods to compute genomic predictions. J Dairy Sci 91:4414–4423. https://doi.org/10.3168/jds.2007-0980
Article CAS PubMed PubMed Central Google Scholar
Wang S, Wong D, Forrest K et al (2014) Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796. https://doi.org/10.1111/pbi.12183
Article CAS PubMed PubMed Central Google Scholar
Whittal A, Kaviani M, Graf R et al (2018) Allelic variation of vernalization and photoperiod response genes in a diverse set of North American high latitude winter wheat genotypes. PLoS ONE 13:5. https://doi.org/10.1371/journal.pone.0203068
Article CAS Google Scholar
Würschum T, Longin CFH, Hahn V et al (2017) Copy number variations of CBF genes at the Fr-A2 locus are essential components of winter hardiness in wheat. Plant J 89:764–773. https://doi.org/10.1111/tpj.13424
Article CAS PubMed Google Scholar
Yan L, Loukoianov A, Tranquilli G et al (2003) Positional cloning of the wheat vernalization gene VRN1. Proc Natl Acad Sci 100:6263–6268. https://doi.org/10.1073/pnas.0937399100
Article CAS PubMed Google Scholar
Yin L (2018) CMplot: circle manhattan plot
Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:5. https://doi.org/10.1111/j.1365-3180.1974.tb01084.x
Article Google Scholar
Zhang Z, Ersoz E, Lai CQ et al (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360. https://doi.org/10.1038/ng.546
Article CAS PubMed PubMed Central Google Scholar
Zheng D, Yang X, Mínguez MI et al (2018) Effect of freezing temperature and duration on winter survival and grain yield of winter wheat. Agric For Meteorol 260–261:1–8. https://doi.org/10.1016/j.agrformet.2018.05.011
Article Google Scholar
Zhu J, Pearce S, Burke A et al (2014) Copy number and haplotype variation at the VRN-A1 and central FR-A2 loci are associated with frost tolerance in hexaploid wheat. Theor Appl Genet 127:1183–1197. https://doi.org/10.1007/s00122-014-2290-2
Article CAS PubMed PubMed Central Google Scholar

Download references

Acknowledgements

Wheat breeding team at the University of Guelph including N. Wilker and K. Bosnic for their technical support, Dr. Robert Graf of AAFC-Lethbridge for providing Western Canadian and winter-hardy spring wheat genotypes, NSERC, SeCan, OMAFRA, and Genome Canada for financial support of the project, and Dr. Matthew Hayden for SNP calling bioinformatics support are duly acknowledged.

Author information

Alireza Navabi: Deceased 10 March 2019.

Affiliations

Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
Yi Chen, Harwinder S. Sidhu, Mina Kaviani & Alireza Navabi
Centre de recherche sur les grains (CÉROM), 740 Chemin Trudeau, Saint-Mathieu-de-Beloeil, QC, J3G 0E2, Canada
Michel S. McElroy
Crop Development Centre, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada
Curtis J. Pozniak

Authors

Yi Chen
View author publications
You can also search for this author in PubMed Google Scholar
Harwinder S. Sidhu
View author publications
You can also search for this author in PubMed Google Scholar
Mina Kaviani
View author publications
You can also search for this author in PubMed Google Scholar
Michel S. McElroy
View author publications
You can also search for this author in PubMed Google Scholar
Curtis J. Pozniak
View author publications
You can also search for this author in PubMed Google Scholar
Alireza Navabi
View author publications
You can also search for this author in PubMed Google Scholar

Contributions

YC and AN designed the study. YC collected phenotypic data and performed the analyses. HSS assembled the panel used in the study and performed population structure analysis. MK collected the DNA samples for the panel and CP provided the SNP data. MM tested the diversity panel in Quebec. YC prepared the first draft of the manuscript. YC, HSS, MK, MM, CP, and AN reviewed and edited the manuscript.

Corresponding author

Correspondence to Yi Chen.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Communicated by Jessica Rutkoski.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 1316 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Chen, Y., Sidhu, H.S., Kaviani, M. et al. Application of image-based phenotyping tools to identify QTL for in-field winter survival of winter wheat (Triticum aestivum L.). Theor Appl Genet 132, 2591–2604 (2019). https://doi.org/10.1007/s00122-019-03373-6

Download citation

Received: 06 February 2019
Accepted: 03 June 2019
Published: 08 June 2019
Issue Date: 01 September 2019
DOI: https://doi.org/10.1007/s00122-019-03373-6

Abstract

Key message

Abstract

Access options

Buy single article

References

Acknowledgements

Author information

Affiliations

Contributions

Corresponding author

Ethics declarations

Conflict of interest

Additional information

Publisher's Note

Electronic supplementary material

Supplementary material 1 (PDF 1316 kb)

Rights and permissions

About this article

Cite this article

Share this article