The Genetic Architecture of Maize Stalk Strength
Publication Date
June 20, 2013
Journal
PLOS ONE
Authors
Jason A. Peiffer, Sherry A. Flint Garcia, Natalia De Leon, Michael D. Mc Mullen, et al
Volume
8
Issue
6
Pages
e67066
DOI
https://dx.plos.org/10.1371/journal.pone.0067066
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0067066
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23840585
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3688621
Europe PMC
http://europepmc.org/abstract/MED/23840585
Web of Science
000322342800117
Scopus
84879253452
Mendeley
http://www.mendeley.com/research/genetic-architecture-maize-stalk-strength
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Mendeley | Further Information

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CrossRef

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/1094855", "https://ndownloader.figshare.com/files/1094856", "https://ndownloader.figshare.com/files/1094859", "https://ndownloader.figshare.com/files/1094861", "https://ndownloader.figshare.com/files/1094862", "https://ndownloader.figshare.com/files/1094864", "https://ndownloader.figshare.com/files/1094866", "https://ndownloader.figshare.com/files/1094867", "https://ndownloader.figshare.com/files/1094868", "https://ndownloader.figshare.com/files/1094869", "https://ndownloader.figshare.com/files/1094871"], "description"=>"<div><p>Stalk strength is an important trait in maize (Zea mays L.). Strong stalks reduce lodging and maximize harvestable yield. Studies show rind penetrometer resistance (RPR), or the force required to pierce a stalk rind with a spike, is a valid approximation of strength. We measured RPR across 4,692 recombinant inbreds (RILs) comprising the maize nested association mapping (NAM) panel derived from crosses of diverse inbreds to the inbred, B73. An intermated B73×Mo17 family (IBM) of 196 RILs and a panel of 2,453 diverse inbreds from the North Central Regional Plant Introduction Station (NCRPIS) were also evaluated. We measured RPR in three environments. Family-nested QTL were identified by joint-linkage mapping in the NAM panel. We also performed a genome-wide association study (GWAS) and genomic best linear unbiased prediction (GBLUP) in each panel. Broad sense heritability computed on a line means basis was low for RPR. Only 8 of 26 families had a heritability above 0.20. The NCRPIS diversity panel had a heritability of 0.54. Across NAM and IBM families, 18 family-nested QTL and 141 significant GWAS associations were identified for RPR. Numerous weak associations were also found in the NCRPIS diversity panel. However, few were linked to loci involved in phenylpropanoid and cellulose synthesis or vegetative phase transition. Using an identity-by-state (IBS) relationship matrix estimated from 1.6 million single nucleotide polymorphisms (SNPs) and RPR measures from 20% of the NAM panel, genomic prediction by GBLUP explained 64±2% of variation in the remaining RILs. In the NCRPIS diversity panel, an IBS matrix estimated from 681,257 SNPs and RPR measures from 20% of the panel explained 33±3% of variation in the remaining inbreds. These results indicate the high genetic complexity of stalk strength and the potential for genomic prediction to hasten its improvement.</p></div>", "links"=>[], "tags"=>["biofuels", "crops", "cereals", "genetics", "Plant genetics", "Crop genetics", "population genetics", "Genetic polymorphism", "natural selection", "genomics", "Genome analysis tools", "Linkage maps", "Plant science", "Agronomy", "Plant genomics", "maize", "stalk"], "article_id"=>726569, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Jason A. Peiffer", "Sherry A. Flint-Garcia", "Natalia de Leon", "Michael D. McMullen", "Shawn M. Kaeppler", "Edward S. Buckler"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067066.s001", "https://dx.doi.org/10.1371/journal.pone.0067066.s002", "https://dx.doi.org/10.1371/journal.pone.0067066.s003", "https://dx.doi.org/10.1371/journal.pone.0067066.s004", "https://dx.doi.org/10.1371/journal.pone.0067066.s005", "https://dx.doi.org/10.1371/journal.pone.0067066.s006", "https://dx.doi.org/10.1371/journal.pone.0067066.s007", "https://dx.doi.org/10.1371/journal.pone.0067066.s008", "https://dx.doi.org/10.1371/journal.pone.0067066.s009", "https://dx.doi.org/10.1371/journal.pone.0067066.s010", "https://dx.doi.org/10.1371/journal.pone.0067066.s011"], "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Genetic_Architecture_of_Maize_Stalk_Strength_/726569", "title"=>"The Genetic Architecture of Maize Stalk Strength", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-06-20 01:49:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1094852"], "description"=>"<p>The reported resample model inclusion probabilities (RMIP) of this table detail the number of models one or more markers located within three cM of the noted association was selected out of 100 models. Each of these models was constructed from family-stratified sampling of the RILs with replacement. Physical positions are stated with respect to reference genome AGPv1.</p>", "links"=>[], "tags"=>["biofuels", "crops", "cereals", "genetics", "Plant genetics", "Crop genetics", "population genetics", "Genetic polymorphism", "natural selection", "genomics", "Genome analysis tools", "Linkage maps", "Plant science", "Agronomy", "Plant genomics", "qtl", "rpr", "ril"], "article_id"=>726566, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Jason A. Peiffer", "Sherry A. Flint-Garcia", "Natalia de Leon", "Michael D. McMullen", "Shawn M. Kaeppler", "Edward S. Buckler"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0067066.t002", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Family_nested_QTL_for_RPR_in_RIL_families_/726566", "title"=>"Family-nested QTL for RPR in RIL families.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-06-20 01:49:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1094849"], "description"=>"<p>Positive correlations between RPR and DTA were greater among plot means (A) than line means (B) across all RILs of the NAM families. However, the opposite relationship was observed between these traits among plot means (C) and line means (D) in the inbreds of the NCRPIS diversity panel. The relationship between RPR and EHT was less varied between the NAM and NCRPIS diversity panels.</p>", "links"=>[], "tags"=>["biofuels", "crops", "cereals", "genetics", "Plant genetics", "Crop genetics", "population genetics", "Genetic polymorphism", "natural selection", "genomics", "Genome analysis tools", "Linkage maps", "Plant science", "Agronomy", "Plant genomics", "correlations", "eht"], "article_id"=>726563, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Jason A. Peiffer", "Sherry A. Flint-Garcia", "Natalia de Leon", "Michael D. McMullen", "Shawn M. Kaeppler", "Edward S. Buckler"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0067066.g004", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Trait_correlations_between_RPR_DTA_and_EHT_variation_/726563", "title"=>"Trait correlations between RPR, DTA, and EHT variation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-06-20 01:49:23"}
  • {"files"=>["https://ndownloader.figshare.com/files/1094848"], "description"=>"<p>About 15% of the total variation in RPR across all NAM and IBM families was attributable to genetic factors. This proportion of genetic variation was smaller than that observed for DTA or EHT. Despite this reduction in genetic variation of RPR, the proportion of genetic-by-environment variation were slightly larger for RPR than the other surveyed traits. Differences in the remaining RPR, DTA, and EHT variation were due to environmental factors or could not be attributed to known sources of variation.</p>", "links"=>[], "tags"=>["biofuels", "crops", "cereals", "genetics", "Plant genetics", "Crop genetics", "population genetics", "Genetic polymorphism", "natural selection", "genomics", "Genome analysis tools", "Linkage maps", "Plant science", "Agronomy", "Plant genomics", "days", "anthesis"], "article_id"=>726562, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Jason A. Peiffer", "Sherry A. Flint-Garcia", "Natalia de Leon", "Michael D. McMullen", "Shawn M. Kaeppler", "Edward S. Buckler"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0067066.g003", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Variation_in_RPR_days_to_anthesis_DTA_and_ear_height_EHT_/726562", "title"=>"Variation in RPR, days to anthesis (DTA), and ear height (EHT).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-06-20 01:49:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1094851"], "description"=>"<p>All reported broad-sense heritability estimates are calculated on a line means basis. RPR, DTA, and EHT detail the proportion of variance between and within lines explained by between line variance after accounting for known environmental variance in the trait. RPR (DTA cov) and RPR (EHT cov) detail the proportion of variance between and within lines explained by between line variance after accounting for known environmental variance and the covariance of RPR with DTA and EHT, respectively.</p>", "links"=>[], "tags"=>["biofuels", "crops", "cereals", "genetics", "Plant genetics", "Crop genetics", "population genetics", "Genetic polymorphism", "natural selection", "genomics", "Genome analysis tools", "Linkage maps", "Plant science", "Agronomy", "Plant genomics", "heritability", "ril", "ncrpis"], "article_id"=>726565, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Jason A. Peiffer", "Sherry A. Flint-Garcia", "Natalia de Leon", "Michael D. McMullen", "Shawn M. Kaeppler", "Edward S. Buckler"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0067066.t001", "stats"=>{"downloads"=>1, "page_views"=>30, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Broad_sense_heritability_of_RIL_families_and_the_NCRPIS_diversity_panel_/726565", "title"=>"Broad-sense heritability of RIL families and the NCRPIS diversity panel.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-06-20 01:49:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/1094850"], "description"=>"<p>Cross-validation revealed steady gains in prediction accuracy with respect to the NAM family-stratified calibration set size (A). About 80% of the variation in BLUP line means for RPR was explained using an identity-by-state (IBS) genomic relationship matrix constructed from 1.6 million SNPs of the maize HapMapV1 (B). Using the same SNP set, prediction accuracy was not significant in the IBM family (C), and the variation explained by the entire family was only 56% (D). In the NCRPIS diversity panel, prediction accuracies were lower than in the NAM panel when using an IBS genomic relationship matrix of 681,257 SNPs constructed and fit in the same manner (E). In total, 71% of the variation in RPR was explained upon fitting the entire panel (F).</p>", "links"=>[], "tags"=>["biofuels", "crops", "cereals", "genetics", "Plant genetics", "Crop genetics", "population genetics", "Genetic polymorphism", "natural selection", "genomics", "Genome analysis tools", "Linkage maps", "Plant science", "Agronomy", "Plant genomics", "rpr", "ril", "ncrpis"], "article_id"=>726564, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Jason A. Peiffer", "Sherry A. Flint-Garcia", "Natalia de Leon", "Michael D. McMullen", "Shawn M. Kaeppler", "Edward S. Buckler"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0067066.g005", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prediction_of_RPR_in_RIL_families_and_NCRPIS_diversity_panel_by_GBLUP_/726564", "title"=>"Prediction of RPR in RIL families and NCRPIS diversity panel by GBLUP.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-06-20 01:49:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1094847"], "description"=>"<p>Comparisons of parent, mid-parent, and progeny BLUE line means for RPR revealed transgressive segregation. Parents of the NAM and IBM families were not chosen from populations divergently selected for RPR. Recombination of additive effects and novel mutations likely play a role in the transgressive variation among their inbred progeny. Furthermore, the asymmetry present in these distributions suggests a role for epistasis.</p>", "links"=>[], "tags"=>["biofuels", "crops", "cereals", "genetics", "Plant genetics", "Crop genetics", "population genetics", "Genetic polymorphism", "natural selection", "genomics", "Genome analysis tools", "Linkage maps", "Plant science", "Agronomy", "Plant genomics", "transgressive", "segregation", "observed"], "article_id"=>726561, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Jason A. Peiffer", "Sherry A. Flint-Garcia", "Natalia de Leon", "Michael D. McMullen", "Shawn M. Kaeppler", "Edward S. Buckler"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0067066.g002", "stats"=>{"downloads"=>3, "page_views"=>34, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Asymmetric_transgressive_segregation_observed_for_RPR_/726561", "title"=>"Asymmetric transgressive segregation observed for RPR.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-06-20 01:49:21"}

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Relative Metric

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