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Agronomy
Special Issues
Advances in Genotyping Platforms for Crop Improvement
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Advances in Genotyping Platforms for Crop Improvement

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: closed (30 April 2019) | Viewed by 4573

Special Issue Editor

Prof. Dr. Jacqueline Batley

grade E-Mail Website
Guest Editor
School of Biological Sciences, The University of Western Australia, Crawley, WA 6009, Australia
Interests: crop genomics; brassica; disease resistance; pan genomics; evolutionary genomics; population genomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Plant genotyping is a rapidly advancing field. The ability to produce vast amounts of DNA sequence data has enabled the discovery of molecular markers in model organisms, crops, as well as orphan species, meaning that genotyping rather than marker development becomes the rate limiting factor. High throughput genotyping can vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and their relationships to improtant agronomic traits, is swiftly gathering momentum as genotyping methods continue to develop. These genotyping methods will give detailed insight into the origins, domestication and available trait-relevant variation of crops, facilitating novel approaches and possibilities for genomics-assisted breeding.

This Special Issue will focus on the different markers available and their applications to crop improvement. Review and original research articles on topics including, but not limited to, description of new high throughput genotyping techniques, application of high throughput genotyping in crop species, examples of crop imrovement resulting from high throughput genotyping, genomics assisted breeding and finally where we expect advances to be made in the future. This topic will enable, not only researchers already applying these technologies to learn of developments in other crops, but will also enable researchers new to the field to see how their research could be advanced.

Prof. Dr. Jacqueline Batley
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • SNPs
  • MAS
  • Pan genomics
  • Next generation sequencing
  • Genomics
  • Crop improvement
  • High throughput genotyping

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Published Papers (1 paper)

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11 pages, 2633 KiB  
Technical Note
Correcting Pervasive Errors in Genotypic Datasets to Develop Genetic Maps
by Sadal Hwang and Tong Geon Lee
Agronomy 2019, 9(4), 196; https://doi.org/10.3390/agronomy9040196 - 16 Apr 2019
Cited by 2 | Viewed by 3813
Abstract
Genetic mapping studies provide improved estimates for novel genomic loci, allelic effects and gene action controlling important traits. Such mapping studies are regularly performed by using a combination of genotypic data (e.g., genotyping markers tagging genetic variation within populations) and phenotypic data of [...] Read more.
Genetic mapping studies provide improved estimates for novel genomic loci, allelic effects and gene action controlling important traits. Such mapping studies are regularly performed by using a combination of genotypic data (e.g., genotyping markers tagging genetic variation within populations) and phenotypic data of appropriately structured mapping populations. Randomly obtained DNA information and more recent high-throughput genome sequencing efforts have dramatically increased the ability to obtain genetic markers for any plant species. Despite the presence of constantly and rapidly increasing genotypic data, necessary steps to determine whether specific markers can be associated with genetic variation may often be initially neglected, meaning that ever-growing genotypic markers do not necessarily maximize the power of mapping studies and often generate false results. To address this issue, we present a framework for analyzing genotypic data while developing a genetic linkage map. Our goal is to raise awareness of a stepwise procedure in the development of genetic maps as well as to outline the current and potential contribution of this procedure to minimize bias caused by errors in genotypic datasets. Empirical results obtained from the R/qtl package for the statistical language/software R are prepared with details of how we handled genotypic data to develop the genetic map of a major plant species. This study provides a stepwise procedure to correct pervasive errors in genotypic data while developing genetic maps. For use in custom follow-up studies, we provide input files and written R codes. Full article
(This article belongs to the Special Issue Advances in Genotyping Platforms for Crop Improvement)
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