Shovelomics for phenotyping root architectural traits of rapeseed/canola (Brassica napus L.) and genome-wide association mapping
Root system in plants plays an important role in mining moisture and nutrients from the soil and is positively correlated to yield in many crops including rapeseed/canola (Brassica napus L.). Substantial phenotypic diversity in root architectural traits among the B. napus growth types leads to a scope of root system improvement in breeding populations. In this study, 216 diverse genotypes were phenotyped for five different root architectural traits following shovelomics approach in the field condition during 2015 and 2016. A single nucleotide polymorphism (SNP) marker panel consisting of 30,262 SNPs was used to conduct genome-wide association study to detect marker/trait association. A total of 31 significant marker loci were identified at 0.01 percentile tail P value cutoff for different root traits. Six marker loci for soil-level taproot diameter (R1Dia), six loci for belowground taproot diameter (R2Dia), seven loci for number of primary root branches (PRB), eight loci for root angle, and eight loci for root score (RS) were detected in this study. Several markers associated with root diameters R1Dia and R2Dia were also associated with PRB and RS. Significant phenotypic correlation between these traits was observed in both environments. Therefore, taproot diameter appears to be a major determinant of the canola root system architecture and can be used as proxy for other root traits. Fifteen candidate genes related to root traits and root development were detected within 100 kbp upstream and downstream of different significant markers. The identified markers associated with different root architectural traits can be considered for marker-assisted selection for root traits in canola in future.
KeywordsGWAS Shovelomics Root architectural traits Brassica napus Marker assisted selection
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
The authors also declare that this article does not contain any studies related with human participants or animals performed by any of the authors and complies with ethical standard.
- Burridge J, Jochua CN, Bucksch A, Lynch JP (2016) Legume shovelomics: high-throughput phenotyping of common bean (Phaseolus vulgaris L.) and cowpea (Vigna unguiculata subsp, unguiculata) root architecture in the field. Field Crop Res 192:21–32. https://doi.org/10.1016/j.fcr.2016.04.008 CrossRefGoogle Scholar
- Colombi T, Kirchgessner N, Le Marie CA, et al (2015) Next generation shovelomics: set up a tent and REST. Plant Soil. https://doi.org/10.1007/s11104-015-2379-7
- Elshire RJ, Glaubitz JC, Sun Q, et al (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE. https://doi.org/10.1371/journal.pone.0019379
- Gong F, Wu X, Zhang H, et al (2015) Making better maize plants for sustainable grain production in a changing climate. Front Plant Sci. https://doi.org/10.3389/fpls.2015.00835
- Kwak SH, Schiefelbein J (2014) TRIPTYCHON, not CAPRICE, participates in feedback regulation of SCM expression in the Arabidopsis root epidermis. Plant Signal Behav. https://doi.org/10.4161/15592324.2014.973815
- Li H (2013) Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997 [q-bio.GN]
- Li X, Guo Z, Lv Y, et al (2017) Genetic control of the root system in rice under normal and drought stress conditions by genome-wide association study. PLoS Genet. https://doi.org/10.1371/journal.pgen.1006889
- Mamidi S, Lee RK, Goos JR, McClean PE (2014) Genome-wide association studies identifies seven major regions responsible for iron deficiency chlorosis in soybean (Glycine max). PLoS ONE. https://doi.org/10.1371/journal.pone.0107469
- Moghaddam SM, Mamidi S, Osorno JM, et al (2016) Genome-wide association study identifies candidate loci underlying agronomic traits in a Middle American diversity panel of common bean. Plant Genome 9:0. https://doi.org/10.3835/plantgenome2016.02.0012
- Pace J, Gardner C, Romay C, et al (2015) Genome-wide association analysis of seedling root development in maize (Zea mays L.). BMC Genom. https://doi.org/10.1186/s12864-015-1226-9
- Savage N, Yang TJW, Chen CY et al (2013) Positional signaling and expression of ENHANCER OF TRY AND CPC1 are tuned to increase root hair density in response to phosphate deficiency in Arabidopsis thaliana. PLoS ONE. https://doi.org/10.1371/journal.pone.0075452
- Tabachnick B, Fidel L (2001) Computer-assisted research design and analysis. Allyn & Bacon, Boston, MAGoogle Scholar
- UN (1935) Genome analysis in Brassica with special reference to the experimental formation of B. napus and peculiar mode of fertilization. Jpn J Bot 7:389–452Google Scholar
- Zhao Y, Wang H, Chen W, Li Y (2014) Genetic structure, linkage disequilibrium and association mapping of verticillium wilt resistance in elite cotton (Gossypium hirsutum L.) germplasm population. PLoS ONE. https://doi.org/10.1371/journal.pone.0086308