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QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.)

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Abstract

Key message

QTL were identified for root architectural traits in maize.

Abstract

Root architectural traits, including the number, length, orientation, and branching of the principal root classes, influence plant function by determining the spatial and temporal domains of soil exploration. To characterize phenotypic patterns and their genetic control, three recombinant inbred populations of maize were grown for 28 days in solid media in a greenhouse and evaluated for 21 root architectural traits, including length, number, diameter, and branching of seminal, primary and nodal roots, dry weight of embryonic and nodal systems, and diameter of the nodal root system. Significant phenotypic variation was observed for all traits. Strong correlations were observed among traits in the same root class, particularly for the length of the main root axis and the length of lateral roots. In a principal component analysis, relationships among traits differed slightly for the three families, though vectors grouped together for traits within a given root class, indicating opportunities for more efficient phenotyping. Allometric analysis showed that trajectories of growth for specific traits differ in the three populations. In total, 15 quantitative trait loci (QTL) were identified. QTL are reported for length in multiple root classes, diameter and number of seminal roots, and dry weight of the embryonic and nodal root systems. Phenotypic variation explained by individual QTL ranged from 0.44 % (number of seminal roots, NyH population) to 13.5 % (shoot dry weight, OhW population). Identification of QTL for root architectural traits may be useful for developing genotypes that are better suited to specific soil environments.

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Acknowledgments

We thank Lauren Gelesh, Johanna Mirenda, and Robert Snyder for technical assistance with plant cultivation and harvesting, and Anushree Sanyal for assistance with the QTL analysis. We thank Harini Rangarajan for creation of the image used in Fig. 1. This work was supported by United States Department of Agriculture National Research Initiative [grant # 207-35100-18365 to JPL and KMB].

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

The research described in this paper complies with the current laws of the country in which they were performed.

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Authors and Affiliations

  1. Department of Plant Science, The Pennsylvania State University, 102 Tyson Building, University Park, PA, 16801, USA

    Amy L. Burton, Meredith T. Hanlon, Kathleen M. Brown & Jonathan P. Lynch

  2. Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, WI, 53706, USA

    James M. Johnson, Jillian M. Foerster & Shawn M. Kaeppler

  3. Department of Plant Biology, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824, USA

    Candice N. Hirsch & C. R. Buell

  4. DOE Great Lakes Bioenergy Research Center, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824, USA

    Candice N. Hirsch & C. R. Buell

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  1. Amy L. Burton
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  2. James M. Johnson
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  3. Jillian M. Foerster
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  4. Candice N. Hirsch
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Corresponding author

Correspondence to Jonathan P. Lynch.

Additional information

Communicated by Frank Hochholdinger.

Electronic supplementary material

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122_2014_2353_MOESM1_ESM.xlsx

Map summaries IBM OhW NyH: marker number, map length, average and maximum spacing statistics of the genetic maps created for the IBM, NyH and OhW populations separated by chromosome (XLSX 13 kb)

122_2014_2353_MOESM2_ESM.xlsx

IBM bin map physicial positions: this file contains the chromosome, genetic position and physical position for each recombination bin marker in the IBM population. This information can be utilized to identify the physical location of QTL identified in mapping and narrow in on gene models that fall within the LOD support interval (XLSX 381 kb)

122_2014_2353_MOESM3_ESM.xlsx

IBM bin map rqtl: this file contains the genotypes for 8,224 recombination bins in the IBM population created using SEG-map and formatted for R/qtl. The chromosome and genetic position for each recombination bin is contained in row 2 and 3. Column 2 contains a dummy trait variable that would be replaced with trait data prior to being used in R/qtl. Additional traits may be added by inserting additional columns. B73 alleles are coded as “A” and Mo17 alleles are coded as “B” (XLSX 6310 kb)

122_2014_2353_MOESM4_ESM.tiff

IBM genetic map: B73 × Mo17 (IBM) mapping population genetic map constructed using SEG-Map with GBS marker data (TIFF 1330 kb)

122_2014_2353_MOESM5_ESM.pdf

IBM Marker pull directions: detailed instructions on how to use Marker_pull.pl for creating a subset of the raw data for a specified region of interest (PDF 26 kb)

122_2014_2353_MOESM6_ESM.pl

IBM Marker pull: this Perl script can be utilized to easily create a subset of the raw marker information that was used in the bin map construction when one is only interested in a specified region (PL 2 kb)

122_2014_2353_MOESM7_ESM.txt

IBM raw marker data: this file contains all of the raw marker information for 68,246 SNPs identified via genotyping-by-sequencing as well as 1,721 publically available SSR markers. The first six columns contain the marker name, chromosome, start position, end position, B73 consensus base and Mo17 consensus base respectively. This is followed by the marker information for each of the RILs. If the marker is a SNP, the start and end position are synonymous. Genotypes are coded A,C,G,T for homozygous, 2 bases for heterozygous and NN for missing (TXT 93684 kb)

122_2014_2353_MOESM8_ESM.tiff

IBM individual similarity plot: histogram of the proportion of markers with identical genotypes for each pair of individuals in the B73 × Mo17 (IBM) mapping population (TIFF 2930 kb)

122_2014_2353_MOESM9_ESM.tiff

IBM indivudal genotype frequency plot: genotype frequencies across all individuals in the B73 × Mo17 (IBM) mapping population (TIFF 2930 kb)

122_2014_2353_MOESM10_ESM.tiff

IBM RF plot: estimated recombination fractions (upper-left triangle) and LOD scores (lower-right triangle) for all pairs of bin markers in the B73 × Mo17 (IBM) mapping population. Red indicates linked (large LOD score or small recombination fraction) and blue indicates not linked (small LOD score or large recombination fraction) (XLSX 4219 kb)

122_2014_2353_MOESM11_ESM.xlsx

NyH bin map physicial positions: this file contains the chromosome, genetic position and physical position for each recombination bin marker in the NyH population. This information can be utilized to identify the physical location of QTL identified in mapping and narrow in on gene models that fall within the LOD support interval (XLSX 209 kb)

122_2014_2353_MOESM12_ESM.xlsx

NyH bin map rqtl: this file contains the genotypes for 5,320 recombination bins in the NyH population created using SEG-map and formatted for R/qtl. The chromosome and genetic position for each recombination bin is contained in row 2 and 3. Column 2 contains a dummy trait variable that would be replaced with trait data prior to being used in R/qtl. Additional traits may be added by inserting additional columns. H99 alleles are coded as “A” and Ny821 alleles are coded as “B” (XLSX 3761 kb)

122_2014_2353_MOESM13_ESM.tiff

NyH genetic map: Ny821 × H99 (NyH) mapping population genetic map constructed using SEG-Map with GBS marker data (TIFF 2930 kb)

122_2014_2353_MOESM14_ESM.pdf

NyH Marker pull directions: detailed instructions on how to use Marker_pull.pl for creating a subset of the raw data for a specified region of interest (PDF 26 kb)

122_2014_2353_MOESM15_ESM.pl

NyH Marker pull: this Perl script can be utilized to easily create a subset of the raw marker information that was used in the bin map construction when one is only interested in a specified region (PL 2 kb)

122_2014_2353_MOESM16_ESM.txt

NyH raw marker data: This file contains all of the raw marker information for 19,970 SNPs identified via genotyping-by-sequencing. The first six columns contain the marker name, chromosome, start position, end position, H99 consensus base and Ny821 consensus base respectively. This is followed by the marker information for each of the RILs. If the marker is a SNP, the start and end position are synonymous. Genotypes are coded A,C,G,T for homozygous, 2 bases for heterozygous and NN for missing (TXT 23493 kb)

122_2014_2353_MOESM17_ESM.tiff

NyH individual similarity plot: histogram of the proportion of markers with identical genotypes for each pair of individuals in the Ny821 × H99 (NyH) mapping population (TIFF 2930 kb)

122_2014_2353_MOESM18_ESM.tiff

NyH indivudal genotype frequency_plot: Genotype frequencies across all individuals in the Ny821 × H99 (NyH) mapping population (TIFF 2930 kb)

122_2014_2353_MOESM19_ESM.tiff

NyH RF plot: estimated recombination fractions (upper-left triangle) and LOD scores (lower-right triangle) for all pairs of bin markers in the Ny821 x H99 (NyH) mapping population. Red indicates linked (large LOD score or small recombination fraction) and blue indicates not linked (small LOD score or large recombination fraction) (TIFF 4219 kb)

122_2014_2353_MOESM20_ESM.xlsx

OhW bin map physicial positions: this file contains the chromosome, genetic position and physical position for each recombination bin marker in the OHW population. This information can be utilized to identify the physical location of QTL identified in mapping and narrow in on gene models that fall within the LOD support interval (XLSX 195 kb)

122_2014_2353_MOESM21_ESM.xlsx

OhW bin map rqtl: this file contains the genotypes for 5,683 recombination bins in the OhW population created using SEG-map and formatted for R/qtl. The chromosome and genetic position for each recombination bin is contained in row 2 and 3. Column 2 contains a dummy trait variable that would be replaced with trait data prior to being used in R/qtl. Additional traits may be added by inserting additional columns. Oh43 alleles are coded as “A” and W64a alleles are coded as “B” (XLSX 4383 kb)

122_2014_2353_MOESM22_ESM.tiff

OhW_genetic map: Oh43 × W64a (OhW) mapping population genetic map constructed using SEG-Map with GBS marker data (TIFF 2930 kb)

122_2014_2353_MOESM23_ESM.pdf

OhW Marker pull directions: detailed instructions on how to use Marker_pull.pl for creating a subset of the raw data for a specified region of interest (PDF 26 kb)

122_2014_2353_MOESM24_ESM.pl

OhW Marker pull: this Perl script can be utilized to easily create a subset of the raw marker information that was used in the bin map construction when one is only interested in a specified region (PL 2 kb)

122_2014_2353_MOESM25_ESM.txt

OhW raw marker data: This file contains all of the raw marker information for 40,959 SNPs identified via genotyping-by-sequencing. The first six columns contain the marker name, chromosome, start position, end position, Oh43 consensus base and W64a consensus base respectively. This is followed by the marker information for each of the RILs. If the marker is a SNP, the start and end position are synonymous. Genotypes are coded A,C,G,T for homozygous, 2 bases for heterozygous and NN for missing (TXT 52287 kb)

122_2014_2353_MOESM26_ESM.tiff

OhW individual similarity plot: histogram of the proportion of markers with identical genotypes for each pair of individuals in the Oh43 × W64a (OhW) mapping population (TIFF 2930 kb)

122_2014_2353_MOESM27_ESM.tiff

OhW indivudal genotype frequency plot: genotype frequencies across all individuals in the Oh43 × W64a (OhW) mapping population (TIFF 2930 kb)

122_2014_2353_MOESM28_ESM.tiff

OhW RF plot: estimated recombination fractions (upper-left triangle) and LOD scores (lower-right triangle) for all pairs of bin markers in the Oh43 × W64a (OhW) mapping population. Red indicates linked (large LOD score or small recombination fraction) and blue indicates not linked (small LOD score or large recombination fraction) (TIFF 4219 kb)

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Burton, A.L., Johnson, J.M., Foerster, J.M. et al. QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.). Theor Appl Genet 127, 2293–2311 (2014). https://doi.org/10.1007/s00122-014-2353-4

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