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Genomic Selection in Wheat

Since its introduction in 2001, genomic selection or prediction has become a popular tool, which is now routinely used in many breeding programmes. Genomic prediction requires training a prediction model on a reference population with dense enough genotyping and accurate phenotyping, then applying this model to a target population which has only been genotyped to predict its performance. It was first developed by dairy cow breeders to estimate the genetic value for milk production of bulls (which obviously do not produce milk), using milk performance of their related females (mother, sisters, daughters, etc.) and a method called BLUP (best linear unbiased predictor), which rely on a relationship matrix, initially estimated using pedigrees. The use of molecular markers to estimate “realized” instead of “expected” relationship (GBLUP) has been first proposed in 1994, but the expression “genomic selection” only in 2001. Its principle stems from marker assisted selection, but without any step of marker selection based on QTL detection, which usually require specific methods to deal with the N >> p problem (more parameters than observation). One method is the ridge regression (penalized), which is strictly equivalent to GBLUP, but many other approaches have been proposed, including Bayesian or machine learning. Genomic or genome wide selection or prediction have theoretical advantages over phenotypic selection for traits with low heritability, traits difficult/expensive to measure or only available at late stage of a breeding programme). In wheat breeding, this apply to traits such as yield or bread making quality. Other advantages of genomic compared to phenotypic selection rely on lower cost of genotyping, possibility of shortening breeding cycles, predicting crosses based on expected progeny performance, etc.

In this special issue, we will review the use of genomic prediction in wheat, either from theoretical or practical point of view. The most pending questions are about the choice of a reference population, how to deal with G x E, multitrait or genomic assisted selection (i.e., simultaneous use of markers and secondary traits), practical implementation in applied breeding programmes, including resource allocation, etc. Please note that wheat initiative (www.wheatinitiative.org) has set up an expert working group to specifically address such question related to wheat (https://www.wheatinitiative.org/wheat-breeding-methods-and-strategies), where I am acting as Chair.

Guest Editor

Dr. Gilles Charmet

UMR 1095 Génétique, Diversité et Ecophysiologie des Céréales, INRA Site de Crouël, 5 Chemin de Beaulieu, 63000 Clermont-Ferrand, France


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Submission Deadline: 15 September 2020

Online Submission

Manuscripts should be submitted online through Hapres Online Submission System. Please visit Guide for Authors before submitting a manuscript. Authors are encouraged to submit a paper as soon as it is ready and don’t need to wait until the deadline. Submissions will be sent to peer-review in order of arrival. Accepted papers will be published continuously in Crop Breeding, Genetics and Genomics (CBGG) and then gathered together on the special issue webpage. We welcome Research articles, Review papers and Short Communications. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for approval.


Virtual Special Issue (VSI) is a collection of papers centered around a specific topic, led by an expert (Guest Editor) in the field. Virtual Special Issues are an important component of our journal and cover current hot topics within the scope of the journal.

All papers belonging to a Virtual Special Issue will be gathered together on a single webpage. They are published in the regular issues of the journal as soon as publishable, and labeled as belonging to the Virtual Special Issue. A link from each paper will take you to the Virtual Special Issue website.

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