What If We Knew All the Genes for a Quantitative Trait in Hybrid Crops

By R. Bernardo. 2001

113 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c5b7960181d1385b17bb33bd0b13b9dad92455fc

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Citations in the corpus

Usefulness of gene information in marker-assisted recurrent selection: A simulation appraisal (2006, background): “The problem, as Bernardo (2001) and Johnson (2004) pointed out, is statistical: it is difficult to get good estimates of 100 QTL effects with a population size of N 5 100.”
Molecular Markers and Selection for Complex Traits in Plants: Learning from the Last 20 Years (2008, background): “Previous reviews have indicated that QTL mapping studies have typically detected an average of 3 to 5 QTL for each trait (Kearsey and Farquhar, 1998; Bernardo, 2002, p. 309–311).”
Mapping As You Go (2004, background): “The if any power over traditional phenotypic selection (e.g.,approach considered in this paper, referred to as the Mapping As You Go (MAYG) approach, continually revises estimates of QTL Bernardo, 2001).”
Revealing the genetic architecture of FHB resistance in hexaploid wheat (Triticum aestivum L.) by QTL meta-analysis (2009, background): “The phenotypic variance explained by a QTL (R(2)) is the key component for assessing the relative advantage of MAS over phenotypic selection as simulation studies showed that it is often advantageous for MAS to consider only major QTL as selecting for minor QTL may diminish response to selection (Be”
QTL Mapping for Fusarium Ear Rot and Fumonisin Contamination Resistance in Two Maize Populations (2006, methodology): “Bernardo (2001) used computer simulation to determine the usefulness of markerassisted selections assuming that all of the QTL positions affecting yield were known.”
Implementation of molecular markers for quantitative traits in breeding programs - challenges and opportunities (2004, background): “Bernardo (2001) simulated MAS when the positions, but not the effects, of all of the genes controlling yield were known without error.”
Genomic Selection for Crop Improvement (2017, unknown): “The validation in locally adapted germplasm is important because poor estimates of the numerous small-eff ect QTL will lead to gains from MAS that are inferior to traditional phenotypic selection (Bernardo, 2001).”
Improving Lives: 50 Years of Crop Breeding, Genetics, and Cytology (C‐1) (2006, background): “…may increase as more high-resolution QTL maps, higher throughput marker technology, and integration of functional genomics with QTL mapping are developed (Collard et al., 2005), although the usefulness of MAS to improve polygenic traits in the long term has been questioned (Bernardo, 2001).”