Literature DB >> 25795171

Breeding-assisted genomics.

Jesse Poland1.   

Abstract

The revolution of inexpensive sequencing has ushered in an unprecedented age of genomics. The promise of using this technology to accelerate plant breeding is being realized with a vision of genomics-assisted breeding that will lead to rapid genetic gain for expensive and difficult traits. The reality is now that robust phenotypic data is an increasing limiting resource to complement the current wealth of genomic information. While genomics has been hailed as the discipline to fundamentally change the scope of plant breeding, a more symbiotic relationship is likely to emerge. In the context of developing and evaluating large populations needed for functional genomics, none excel in this area more than plant breeders. While genetic studies have long relied on dedicated, well-structured populations, the resources dedicated to these populations in the context of readily available, inexpensive genotyping is making this philosophy less tractable relative to directly focusing functional genomics on material in breeding programs. Through shifting effort for basic genomic studies from dedicated structured populations, to capturing the entire scope of genetic determinants in breeding lines, we can move towards not only furthering our understanding of functional genomics in plants, but also rapidly improving crops for increased food security, availability and nutrition.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2015        PMID: 25795171     DOI: 10.1016/j.pbi.2015.02.009

Source DB:  PubMed          Journal:  Curr Opin Plant Biol        ISSN: 1369-5266            Impact factor:   7.834


  19 in total

1.  Can we harness digital technologies and physiology to hasten genetic gain in US maize breeding?

Authors:  Christine H Diepenbrock; Tom Tang; Michael Jines; Frank Technow; Sara Lira; Dean Podlich; Mark Cooper; Carlos Messina
Journal:  Plant Physiol       Date:  2022-02-04       Impact factor: 8.340

2.  Data-driven, participatory characterization of farmer varieties discloses teff breeding potential under current and future climates.

Authors:  Aemiro Bezabih Woldeyohannes; Sessen Daniel Iohannes; Mara Miculan; Leonardo Caproni; Jemal Seid Ahmed; Kauê de Sousa; Ermias Abate Desta; Carlo Fadda; Mario Enrico Pè; Matteo Dell'Acqua
Journal:  Elife       Date:  2022-09-02       Impact factor: 8.713

3.  A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations.

Authors:  Laxman Adhikari; Sandesh Shrestha; Shuangye Wu; Jared Crain; Liangliang Gao; Byron Evers; Duane Wilson; Yoonha Ju; Dal-Hoe Koo; Pierre Hucl; Curtis Pozniak; Sean Walkowiak; Xiaoyun Wang; Jing Wu; Jeffrey C Glaubitz; Lee DeHaan; Bernd Friebe; Jesse Poland
Journal:  Sci Rep       Date:  2022-10-20       Impact factor: 4.996

4.  Improvement of Rice Biomass Yield through QTL-Based Selection.

Authors:  Kazuki Matsubara; Eiji Yamamoto; Nobuya Kobayashi; Takuro Ishii; Junichi Tanaka; Hiroshi Tsunematsu; Satoshi Yoshinaga; Osamu Matsumura; Jun-Ichi Yonemaru; Ritsuko Mizobuchi; Toshio Yamamoto; Hiroshi Kato; Masahiro Yano
Journal:  PLoS One       Date:  2016-03-17       Impact factor: 3.240

Review 5.  Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses.

Authors:  Shyamal K Talukder; Malay C Saha
Journal:  Front Plant Sci       Date:  2017-07-26       Impact factor: 5.753

Review 6.  Genomics-assisted breeding in fruit trees.

Authors:  Hiroyoshi Iwata; Mai F Minamikawa; Hiromi Kajiya-Kanegae; Motoyuki Ishimori; Takeshi Hayashi
Journal:  Breed Sci       Date:  2016-01-01       Impact factor: 2.086

7.  Initiating maize pre-breeding programs using genomic selection to harness polygenic variation from landrace populations.

Authors:  Gregor Gorjanc; Janez Jenko; Sarah J Hearne; John M Hickey
Journal:  BMC Genomics       Date:  2016-01-05       Impact factor: 3.969

8.  Assessing Predictive Properties of Genome-Wide Selection in Soybeans.

Authors:  Alencar Xavier; William M Muir; Katy Martin Rainey
Journal:  G3 (Bethesda)       Date:  2016-08-09       Impact factor: 3.154

9.  UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought.

Authors:  Riccardo Ludovisi; Flavia Tauro; Riccardo Salvati; Sacha Khoury; Giuseppe Mugnozza Scarascia; Antoine Harfouche
Journal:  Front Plant Sci       Date:  2017-09-27       Impact factor: 5.753

10.  Phenotyping of field-grown wheat in the UK highlights contribution of light response of photosynthesis and flag leaf longevity to grain yield.

Authors:  Elizabete Carmo-Silva; P John Andralojc; Joanna C Scales; Steven M Driever; Andrew Mead; Tracy Lawson; Christine A Raines; Martin A J Parry
Journal:  J Exp Bot       Date:  2017-06-15       Impact factor: 6.992

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