Literature DB >> 24196158

Estimation of coefficient of coancestry using molecular markers in maize.

R Bernardo1.   

Abstract

The coefficient of coancestry (fAB) between individuals A and B is the classical measure of genetic relationship. fAB is determined from pedigree records and is the probability that random alleles at the same locus in A and B are copies of the same ancestral allele or identical by descent (ibd). Recently, the proportion of molecular marker variants shared between A and B (SAB) has been used to measure genetic relationship. But SAB is an upwardly-biased estimator of fAB, especially between distantly-related lines. fAB, SAB, and adjusted (to remove bias) estimates of molecular marker similarity (f AB (M) ) were compared. RFLP banding patterns at 46 probe-restriction enzyme combinations were obtained for 23 maize inbred lines derived from the Iowa Stiff Stalk Synthetic (BSSS) maize (Zea mays L.) population, and for 4 non-BSSS lines. f AB (M) was estimated as [Formula: see text], where δ A (or δ B) was the average proportion of RFLP variants shared between inbred A (or inbred B) and the non-BSSS lines. The average fAB among 253 pairwise combinations of BSSS lines was 0.212, whereas the average SAB was 0.397. The average f AB (M) was 0.162, indicating that the upward bias in SAB was effectively removed. SAB and fAB were significantly different (α = 0.05) in 76.3% of the comparisons, whereas 24.9% of the f AB (M) values differed significantly from fAB. The latter result suggests that selection and/or drift were present during inbred line development and that fAB may not be an accurate measure of the true proportion of ibd alleles between two lines. Cluster analyses based on S AB (M) and f AB (M) grouped lines according to pedigree, although several exceptions were noted. The presence of shared molecular marker variants between unrelated lines must be considered when setting SAB-based minimum distances for varietal protection. Under simplified conditions, more than 250 molecular marker loci are necessary to obtain sufficiently precise estimates of coefficient of coancestry using molecular markers.

Entities:  

Year:  1993        PMID: 24196158     DOI: 10.1007/BF00215047

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  5 in total

1.  Construction of genetic linkage maps in maize and tomato using restriction fragment length polymorphisms.

Authors:  T Helentjaris; M Slocum; S Wright; A Schaefer; J Nienhuis
Journal:  Theor Appl Genet       Date:  1986-09       Impact factor: 5.699

2.  Genetic diversity among progenitors and elite lines from the Iowa Stiff Stalk Synthetic (BSSS) maize population: comparison of allozyme and RFLP data.

Authors:  M M Messmer; A E Melchinger; M Lee; W L Woodman; E A Lee; K R Lamkey
Journal:  Theor Appl Genet       Date:  1991-11       Impact factor: 5.699

3.  Estimation of relatedness by DNA fingerprinting.

Authors:  M Lynch
Journal:  Mol Biol Evol       Date:  1988-09       Impact factor: 16.240

4.  Relationship of restriction fragment length polymorphisms to single-cross hybrid performance of maize.

Authors:  E B Godshalk; M Lee; K R Lamkey
Journal:  Theor Appl Genet       Date:  1990-08       Impact factor: 5.699

5.  Similarities among a group of elite maize inbreds as measured by pedigree, F1 grain yield, grain yield, heterosis, and RFLPs.

Authors:  O S Smith; J S Smith; S L Bowen; R A Tenborg; S J Wall
Journal:  Theor Appl Genet       Date:  1990-12       Impact factor: 5.699

  5 in total
  34 in total

1.  Quantitative trait loci (QTL) detection in multicross inbred designs: recovering QTL identical-by-descent status information from marker data.

Authors:  Sébastien Crepieux; Claude Lebreton; Bertrand Servin; Gilles Charmet
Journal:  Genetics       Date:  2004-11       Impact factor: 4.562

2.  Tropical maize germplasm: what can we say about its genetic diversity in the light of molecular markers?

Authors:  P R Laborda; K M Oliveira; A A F Garcia; M E A G Z Paterniani; A P de Souza
Journal:  Theor Appl Genet       Date:  2005-11-15       Impact factor: 5.699

3.  Marker-based estimation of the coefficient of coancestry in hybrid breeding programmes.

Authors:  S Maenhout; B De Baets; G Haesaert
Journal:  Theor Appl Genet       Date:  2009-02-18       Impact factor: 5.699

4.  Use of selection with recurrent backcrossing and QTL mapping to identify loci contributing to southern leaf blight resistance in a highly resistant maize line.

Authors:  John C Zwonitzer; David M Bubeck; Dinakar Bhattramakki; Major M Goodman; Consuelo Arellano; Peter J Balint-Kurti
Journal:  Theor Appl Genet       Date:  2009-01-08       Impact factor: 5.699

5.  Cross-validation in association mapping and its relevance for the estimation of QTL parameters of complex traits.

Authors:  T Würschum; T Kraft
Journal:  Heredity (Edinb)       Date:  2013-12-11       Impact factor: 3.821

Review 6.  Association mapping: critical considerations shift from genotyping to experimental design.

Authors:  Sean Myles; Jason Peiffer; Patrick J Brown; Elhan S Ersoz; Zhiwu Zhang; Denise E Costich; Edward S Buckler
Journal:  Plant Cell       Date:  2009-08-04       Impact factor: 11.277

7.  Prediction of maize single-cross hybrid performance: support vector machine regression versus best linear prediction.

Authors:  Steven Maenhout; Bernard De Baets; Geert Haesaert
Journal:  Theor Appl Genet       Date:  2009-11-11       Impact factor: 5.699

8.  Genome-based prediction of testcross values in maize.

Authors:  Theresa Albrecht; Valentin Wimmer; Hans-Jürgen Auinger; Malena Erbe; Carsten Knaak; Milena Ouzunova; Henner Simianer; Chris-Carolin Schön
Journal:  Theor Appl Genet       Date:  2011-04-20       Impact factor: 5.699

9.  Mapping QTLs with main and epistatic effects underlying grain yield and heading time in soft winter wheat.

Authors:  Jochen C Reif; Hans P Maurer; Viktor Korzun; Erhard Ebmeyer; T Miedaner; Tobias Würschum
Journal:  Theor Appl Genet       Date:  2011-04-08       Impact factor: 5.699

10.  Genome-wide association mapping reveals epistasis and genetic interaction networks in sugar beet.

Authors:  Tobias Würschum; Hans Peter Maurer; Britta Schulz; Jens Möhring; Jochen Christoph Reif
Journal:  Theor Appl Genet       Date:  2011-03-30       Impact factor: 5.699

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