Literature DB >> 21227531

Population genetics of genomics-based crop improvement methods.

Martha T Hamblin1, Edward S Buckler, Jean-Luc Jannink.   

Abstract

Many genome-wide association studies (GWAS) in humans are concluding that, even with very large sample sizes and high marker densities, most of the genetic basis of complex traits may remain unexplained. At the same time, recent research in plant GWAS is showing much greater success with fewer resources. Both GWAS and genomic selection (GS), a method for predicting phenotypes by the use of genome-wide marker data, are receiving considerable attention among plant breeders. In this review we explore how differences in population genetic histories, as well as past selection for traits of interest, have produced trait architectures and patterns of linkage disequilibrium (LD) that frequently differ dramatically between domesticated plants and humans, making detection of quantitative trait loci (QTL) effects in crops more rewarding and less costly than in humans.
Copyright © 2011. Published by Elsevier Ltd.

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Year:  2011        PMID: 21227531     DOI: 10.1016/j.tig.2010.12.003

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  78 in total

1.  Evaluation of multi-locus models for genome-wide association studies: a case study in sugar beet.

Authors:  T Würschum; T Kraft
Journal:  Heredity (Edinb)       Date:  2014-10-29       Impact factor: 3.821

Review 2.  Augmentation of crop productivity through interventions of omics technologies in India: challenges and opportunities.

Authors:  Rajesh Kumar Pathak; Mamta Baunthiyal; Dinesh Pandey; Anil Kumar
Journal:  3 Biotech       Date:  2018-10-19       Impact factor: 2.406

3.  Demographic factors shaped diversity in the two gene pools of wild common bean Phaseolus vulgaris L.

Authors:  S Mamidi; M Rossi; S M Moghaddam; D Annam; R Lee; R Papa; P E McClean
Journal:  Heredity (Edinb)       Date:  2012-11-21       Impact factor: 3.821

Review 4.  Large SNP arrays for genotyping in crop plants.

Authors:  Martin W Ganal; Andreas Polley; Eva-Maria Graner; Joerg Plieske; Ralf Wieseke; Hartmut Luerssen; Gregor Durstewitz
Journal:  J Biosci       Date:  2012-11       Impact factor: 1.826

5.  Optimum design of family structure and allocation of resources in association mapping with lines from multiple crosses.

Authors:  W Liu; H P Maurer; J C Reif; A E Melchinger; H F Utz; M R Tucker; N Ranc; G Della Porta; T Würschum
Journal:  Heredity (Edinb)       Date:  2012-10-10       Impact factor: 3.821

6.  Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice.

Authors:  Kenji Yano; Eiji Yamamoto; Koichiro Aya; Hideyuki Takeuchi; Pei-Ching Lo; Li Hu; Masanori Yamasaki; Shinya Yoshida; Hidemi Kitano; Ko Hirano; Makoto Matsuoka
Journal:  Nat Genet       Date:  2016-06-20       Impact factor: 38.330

Review 7.  Crop genomics: advances and applications.

Authors:  Peter L Morrell; Edward S Buckler; Jeffrey Ross-Ibarra
Journal:  Nat Rev Genet       Date:  2011-12-29       Impact factor: 53.242

8.  Genomics of the origin and evolution of Citrus.

Authors:  Guohong Albert Wu; Javier Terol; Victoria Ibanez; Antonio López-García; Estela Pérez-Román; Carles Borredá; Concha Domingo; Francisco R Tadeo; Jose Carbonell-Caballero; Roberto Alonso; Franck Curk; Dongliang Du; Patrick Ollitrault; Mikeal L Roose; Joaquin Dopazo; Frederick G Gmitter; Daniel S Rokhsar; Manuel Talon
Journal:  Nature       Date:  2018-02-07       Impact factor: 49.962

9.  Population structure and linkage disequilibrium in Lupinus albus L. germplasm and its implication for association mapping.

Authors:  Muhammad Javed Iqbal; Sujan Mamidi; Rubina Ahsan; Shahryar F Kianian; Clarice J Coyne; Anwar A Hamama; Satya S Narina; Harbans L Bhardwaj
Journal:  Theor Appl Genet       Date:  2012-03-28       Impact factor: 5.699

Review 10.  Evolutionary genetics of plant adaptation.

Authors:  Jill T Anderson; John H Willis; Thomas Mitchell-Olds
Journal:  Trends Genet       Date:  2011-07       Impact factor: 11.639

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