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Seck F, Covarrubias-Pazaran G, Gueye T, Bartholomé J. Realized Genetic Gain in Rice: Achievements from Breeding Programs. Rice (N Y) 2023; 16:61. [PMID: 38099942 PMCID: PMC10724102 DOI: 10.1186/s12284-023-00677-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 12/10/2023] [Indexed: 12/18/2023]
Abstract
Genetic improvement is crucial for ensuring food security globally. Indeed, plant breeding has contributed significantly to increasing the productivity of major crops, including rice, over the last century. Evaluating the efficiency of breeding strategies necessitates a quantification of this progress. One approach involves assessing the genetic gain achieved through breeding programs based on quantitative traits. This study aims to provide a theoretical understanding of genetic gain, summarize the major results of genetic gain studies in rice breeding, and suggest ways of improving breeding program strategies and future studies on genetic gain. To achieve this, we present the concept of genetic gain and the essential aspects of its estimation. We also provide an extensive literature review of genetic gain studies in rice (Oryza sativa L.) breeding programs to understand the advances made to date. We reviewed 29 studies conducted between 1999 and 2023, covering different regions, traits, periods, and estimation methods. The genetic gain for grain yield, in particular, showed significant variation, ranging from 1.5 to 167.6 kg/ha/year, with a mean value of 36.3 kg/ha/year. This translated into a rate of genetic gain for grain yield ranging from 0.1% to over 3.0%. The impact of multi-trait selection on grain yield was clarified by studies that reported genetic gains for other traits, such as plant height, days to flowering, and grain quality. These findings reveal that while breeding programs have achieved significant gains, further improvements are necessary to meet the growing demand for rice. We also highlight the limitations of these studies, which hinder accurate estimations of genetic gain. In conclusion, we offer suggestions for improving the estimation of genetic gain based on quantitative genetic principles and computer simulations to optimize rice breeding strategies.
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Affiliation(s)
- Fallou Seck
- Rice Breeding Innovation Platform, International Rice Research Institute, DAPO Box7777, Metro Manila, Philippines
- University Iba Der Thiam of Thiès, GrandStanding, Thiès, Senegal
| | - Giovanny Covarrubias-Pazaran
- Rice Breeding Innovation Platform, International Rice Research Institute, DAPO Box7777, Metro Manila, Philippines
| | - Tala Gueye
- University Iba Der Thiam of Thiès, GrandStanding, Thiès, Senegal
| | - Jérôme Bartholomé
- CIRAD, UMR AGAP, Cali, Colombia.
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France.
- Alliance Bioversity-CIAT, Cali, Colombia.
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Zhao F, Zhang P, Wang X, Akdemir D, Garrick D, He J, Wang L. Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement. J Anim Sci Biotechnol 2023; 14:87. [PMID: 37309010 DOI: 10.1186/s40104-023-00872-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 04/02/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate the speed of genetic improvement in domestic animals. But after multi-generation selection, the rate of inbreeding and the occurrence of homozygous harmful alleles might increase, which would reduce performance and genetic diversity. To mitigate the above problems, we can utilize genomic mating (GM) based upon optimal mate allocation to construct the best genotypic combinations in the next generation. In this study, we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population. These factors included: the algorithm used to derive inbreeding coefficients; the trait heritability (0.1, 0.3 or 0.5); the kind of GM scheme (focused average GEBV or inbreeding); the approach for computing the genomic relationship matrix (by SNP or runs of homozygosity (ROH)). The outcomes were compared to three traditional mating schemes (random, positive assortative or negative assortative matings). In addition, the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population. RESULTS Genomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain. The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs. The GROH-based GM schemes with the maximum genetic gain resulted in 0.9%-2.6% higher rates of genetic gain ΔG, and 13%-83.3% lower ΔF than positive assortative mating regardless of heritability. The rates of inbreeding were always the fastest with positive assortative mating. Results from a purebred Large White pig population, confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes. CONCLUSION Compared with traditional mating schemes, genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population. Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs.
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Affiliation(s)
- Fuping Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Pengfei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Xiaoqing Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Deniz Akdemir
- Center for Blood and Marrow Transplant Research, Minneapolis, MN, USA
| | - Dorian Garrick
- AL Rae Centre for Genetics and Breeding, Massey University, Hamilton, 3240, New Zealand
| | - Jun He
- College of Animal Science and Biotechnology, Hunnan Agricultural University, Changsha, 410128, China
| | - Lixian Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
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Anilkumar C, Sunitha NC, Devate NB, Ramesh S. Advances in integrated genomic selection for rapid genetic gain in crop improvement: a review. Planta 2022; 256:87. [PMID: 36149531 DOI: 10.1007/s00425-022-03996-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 09/11/2022] [Indexed: 06/16/2023]
Abstract
Genomic selection and its importance in crop breeding. Integration of GS with new breeding tools and developing SOP for GS to achieve maximum genetic gain with low cost and time. The success of conventional breeding approaches is not sufficient to meet the demand of a growing population for nutritious food and other plant-based products. Whereas, marker assisted selection (MAS) is not efficient in capturing all the favorable alleles responsible for economic traits in the process of crop improvement. Genomic selection (GS) developed in livestock breeding and then adapted to plant breeding promised to overcome the drawbacks of MAS and significantly improve complicated traits controlled by gene/QTL with small effects. Large-scale deployment of GS in important crops, as well as simulation studies in a variety of contexts, addressed G × E interaction effects and non-additive effects, as well as lowering breeding costs and time. The current study provides a complete overview of genomic selection, its process, and importance in modern plant breeding, along with insights into its application. GS has been implemented in the improvement of complex traits including tolerance to biotic and abiotic stresses. Furthermore, this review hypothesises that using GS in conjunction with other crop improvement platforms accelerates the breeding process to increase genetic gain. The objective of this review is to highlight the development of an appropriate GS model, the global open source network for GS, and trans-disciplinary approaches for effective accelerated crop improvement. The current study focused on the application of data science, including machine learning and deep learning tools, to enhance the accuracy of prediction models. Present study emphasizes on developing plant breeding strategies centered on GS combined with routine conventional breeding principles by developing GS-SOP to achieve enhanced genetic gain.
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Affiliation(s)
- C Anilkumar
- ICAR-National Rice Research Institute, Cuttack, India
| | - N C Sunitha
- University of Agricultural Sciences, Bangalore, India
| | | | - S Ramesh
- University of Agricultural Sciences, Bangalore, India.
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Singh M, Nara U. Genetic insights in pearl millet breeding in the genomic era: challenges and prospects. Plant Biotechnol Rep 2022; 17:15-37. [PMID: 35692233 PMCID: PMC9169599 DOI: 10.1007/s11816-022-00767-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 04/30/2022] [Accepted: 05/17/2022] [Indexed: 05/28/2023]
Abstract
Pearl millet, a vital staple food and an important cereal, is emerging as crop having various end-uses as feed, food as well as fodder. Advancement in high-throughput sequencing technology has boosted up pearl millet genomic research in past few years. The available draft genome of pearl millet providing an insight into the advancement of several breeding lines. Comparative and functional genomics have untangled several loci and genes regulating adaptive and agronomic traits in pearl millet. Additionally, the knowledge achieved has far away from being applicable in real breeding practices. We believe that the best path ahead is to adopt genome-based approaches for tailored designing of pearl millet as multi-functional crop with outstanding agronomic traits for various end uses. Presently review highlight several novel concepts and techniques in crop breeding, and summarize the recent advances in pearl millet genomic research, peculiarly genome-wide association dissections of several novel alleles and genes for agronomically important traits.
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Affiliation(s)
- Mandeep Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab 141004 India
| | - Usha Nara
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab 141004 India
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Chivasa W, Worku M, Teklewold A, Setimela P, Gethi J, Magorokosho C, Davis NJ, Prasanna BM. Maize varietal replacement in Eastern and Southern Africa: Bottlenecks, drivers and strategies for improvement. Glob Food Sec 2022; 32:100589. [PMID: 35300043 PMCID: PMC8907863 DOI: 10.1016/j.gfs.2021.100589] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 11/09/2022]
Abstract
Seed security is vital for food security. Rapid-cycle, climate-adaptive breeding programs and seed systems that deliver new, elite varieties to farmers to replace obsolete ones can greatly improve the productivity of maize-based cropping systems in sub-Saharan Africa (SSA). Despite the importance and benefits of accelerated varietal turnover to climate change adaptation and food security, the rate of maize varietal replacement in SSA is slow. This review outlines the major bottlenecks, drivers, risks, and benefits of active replacement of maize varieties in eastern and southern Africa (ESA) and highlights strategies that are critical to varietal turnover. Although there is an upsurge of new seed companies in ESA and introduction of new varieties with better genetics in the market, some established seed companies continue to sell old (over 15-year-old) varieties. Several recently developed maize hybrids in ESA have shown significant genetic gains under farmers’ conditions. Empirical evidence also shows that timely replacement of old products results in better business success as it helps seed companies maintain or improve market share and brand relevance. Therefore, proactive management of product life cycles by seed companies benefits both the farmers and businesses alike, contributing to improved food security and adaptation to the changing climate. Maize varietal replacement is slow in many countries in sub-Saharan Africa, despite the growth in recent years of the region’s maize seed industry. Continued use of old, obsolete varieties exposes farmers to risks due to changing climate and emergent diseases and pests. Varietal replacement is required to translate genetic gains to on-farm productivity and help farmers adapt to climate change. Proactive product life cycle management improves seed business success and enhances market share and brand relevance.
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Affiliation(s)
- Walter Chivasa
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF Campus, UN Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya
| | - Mosisa Worku
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF Campus, UN Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya
| | | | | | | | | | - Nicholas J Davis
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF Campus, UN Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya
| | - Boddupalli M Prasanna
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF Campus, UN Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya
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Abstract
The advent of plant phenomics, coupled with the wealth of genotypic data generated by next-generation sequencing technologies, provides exciting new resources for investigations into and improvement of complex traits. However, these new technologies also bring new challenges in quantitative genetics, namely, a need for the development of robust frameworks that can accommodate these high-dimensional data. In this chapter, we describe methods for the statistical analysis of high-throughput phenotyping (HTP) data with the goal of enhancing the prediction accuracy of genomic selection (GS). Following the Introduction in Sec. 1, Sec. 2 discusses field-based HTP, including the use of unoccupied aerial vehicles and light detection and ranging, as well as how we can achieve increased genetic gain by utilizing image data derived from HTP. Section 3 considers extending commonly used GS models to integrate HTP data as covariates associated with the principal trait response, such as yield. Particular focus is placed on single-trait, multi-trait, and genotype by environment interaction models. One unique aspect of HTP data is that phenomics platforms often produce large-scale data with high spatial and temporal resolution for capturing dynamic growth, development, and stress responses. Section 4 discusses the utility of a random regression model for performing longitudinal modeling. The chapter concludes with a discussion of some standing issues.
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Affiliation(s)
- Gota Morota
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
| | - Diego Jarquin
- Agronomy Department, University of Florida, Gainesville, FL, USA
| | - Malachy T Campbell
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Hiroyoshi Iwata
- Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan
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7
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Juma RU, Bartholomé J, Thathapalli Prakash P, Hussain W, Platten JD, Lopena V, Verdeprado H, Murori R, Ndayiragije A, Katiyar SK, Islam MR, Biswas PS, Rutkoski JE, Arbelaez JD, Mbute FN, Miano DW, Cobb JN. Identification of an Elite Core Panel as a Key Breeding Resource to Accelerate the Rate of Genetic Improvement for Irrigated Rice. Rice (N Y) 2021; 14:92. [PMID: 34773509 PMCID: PMC8590642 DOI: 10.1186/s12284-021-00533-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 10/29/2021] [Indexed: 06/13/2023]
Abstract
Rice genetic improvement is a key component of achieving and maintaining food security in Asia and Africa in the face of growing populations and climate change. In this effort, the International Rice Research Institute (IRRI) continues to play a critical role in creating and disseminating rice varieties with higher productivity. Due to increasing demand for rice, especially in Africa, there is a strong need to accelerate the rate of genetic improvement for grain yield. In an effort to identify and characterize the elite breeding pool of IRRI's irrigated rice breeding program, we analyzed 102 historical yield trials conducted in the Philippines during the period 2012-2016 and representing 15,286 breeding lines (including released varieties). A mixed model approach based on the pedigree relationship matrix was used to estimate breeding values for grain yield, which ranged from 2.12 to 6.27 t·ha-1. The rate of genetic gain for grain yield was estimated at 8.75 kg·ha-1 year-1 (0.23%) for crosses made in the period from 1964 to 2014. Reducing the data to only IRRI released varieties, the rate doubled to 17.36 kg·ha-1 year-1 (0.46%). Regressed against breeding cycle the rate of gain for grain yield was 185 kg·ha-1 cycle-1 (4.95%). We selected 72 top performing lines based on breeding values for grain yield to create an elite core panel (ECP) representing the genetic diversity in the breeding program with the highest heritable yield values from which new products can be derived. The ECP closely aligns with the indica 1B sub-group of Oryza sativa that includes most modern varieties for irrigated systems. Agronomic performance of the ECP under multiple environments in Asia and Africa confirmed its high yield potential. We found that the rate of genetic gain for grain yield found in this study was limited primarily by long cycle times and the direct introduction of non-improved material into the elite pool. Consequently, the current breeding scheme for irrigated rice at IRRI is based on rapid recurrent selection among highly elite lines. In this context, the ECP constitutes an important resource for IRRI and NAREs breeders to carefully characterize and manage that elite diversity.
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Affiliation(s)
- Roselyne U Juma
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- Kenya Agricultural and Livestock Research Organization, 50100-169, Kakamega, Kenya
| | - Jérôme Bartholomé
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines.
- AGAP Institut, CIRAD, INRA, Montpellier SupAgro, Univ Montpellier, Montpellier, France.
| | - Parthiban Thathapalli Prakash
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
| | - Waseem Hussain
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
| | - John D Platten
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
| | - Vitaliano Lopena
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
| | - Holden Verdeprado
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
| | - Rosemary Murori
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- International Rice Research Institute (IRRI) C/O ILRI, Old Naivasha Road, PO Box 30709, 00100, Nairobi, Kenya
| | - Alexis Ndayiragije
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- Institiuto de Investigação de Moçambique (IIAM), Av. das FPLM nr 2698, Recinto do IIAM, Maputo, Mozambique
| | - Sanjay Kumar Katiyar
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- International Rice Research Institute, South Asia Hub, ICRISAT, Hyderabad, 502324, India
| | - Md Rafiqul Islam
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- Bangladesh Office, International Rice Research Institute (IRRI), Dhaka, Bangladesh
| | - Partha S Biswas
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- Plant Breeding Division, Bangladesh Rice Research Institute (BRRI), Gazipur, Bangladesh
| | - Jessica E Rutkoski
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- University of Illinois at Urbana-Champaign, Urbana, USA, Illinois
| | - Juan D Arbelaez
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines
- University of Illinois at Urbana-Champaign, Urbana, USA, Illinois
| | - Felister N Mbute
- Department of Plant Science and Crop Protection, University of Nairobi, PO Box 29053, 00625, Kangemi, Kenya
| | - Douglas W Miano
- Department of Plant Science and Crop Protection, University of Nairobi, PO Box 29053, 00625, Kangemi, Kenya
| | - Joshua N Cobb
- Rice Breeding Innovations Platform, International Rice Research Institute, 1301 Los Baños, Metro, DAPO Box 7777, Manila, Philippines.
- RiceTec. Inc, PO Box 1305, Alvin, TX, 77512, USA.
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Snowdon RJ, Wittkop B, Chen TW, Stahl A. Crop adaptation to climate change as a consequence of long-term breeding. Theor Appl Genet 2021; 134:1613-1623. [PMID: 33221941 PMCID: PMC8205907 DOI: 10.1007/s00122-020-03729-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 11/11/2020] [Indexed: 05/09/2023]
Abstract
Major global crops in high-yielding, temperate cropping regions are facing increasing threats from the impact of climate change, particularly from drought and heat at critical developmental timepoints during the crop lifecycle. Research to address this concern is frequently focused on attempts to identify exotic genetic diversity showing pronounced stress tolerance or avoidance, to elucidate and introgress the responsible genetic factors or to discover underlying genes as a basis for targeted genetic modification. Although such approaches are occasionally successful in imparting a positive effect on performance in specific stress environments, for example through modulation of root depth, major-gene modifications of plant architecture or function tend to be highly context-dependent. In contrast, long-term genetic gain through conventional breeding has incrementally increased yields of modern crops through accumulation of beneficial, small-effect variants which also confer yield stability via stress adaptation. Here we reflect on retrospective breeding progress in major crops and the impact of long-term, conventional breeding on climate adaptation and yield stability under abiotic stress constraints. Looking forward, we outline how new approaches might complement conventional breeding to maintain and accelerate breeding progress, despite the challenges of climate change, as a prerequisite to sustainable future crop productivity.
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Affiliation(s)
- Rod J Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University Giessen, Heinrich-Buff-Ring 26, 35392, Giessen, Germany.
| | - Benjamin Wittkop
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University Giessen, Heinrich-Buff-Ring 26, 35392, Giessen, Germany
| | - Tsu-Wei Chen
- Albrecht Daniel Thaer Institute of Agricultural and Horticultural Sciences, Humboldt University Berlin, Lentzeallee 75, 14195, Berlin, Germany
| | - Andreas Stahl
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University Giessen, Heinrich-Buff-Ring 26, 35392, Giessen, Germany
- Institute for Resistance Research and Stress Tolerance, Federal Research Centre for Cultivated Plants, Julius Kühn-Institut (JKI), Erwin-Baur-Strasse 27, 06484, Quedlinburg, Germany
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Krishnappa G, Savadi S, Tyagi BS, Singh SK, Mamrutha HM, Kumar S, Mishra CN, Khan H, Gangadhara K, Uday G, Singh G, Singh GP. Integrated genomic selection for rapid improvement of crops. Genomics 2021; 113:1070-1086. [PMID: 33610797 DOI: 10.1016/j.ygeno.2021.02.007] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 11/08/2020] [Accepted: 02/15/2021] [Indexed: 11/15/2022]
Abstract
An increase in the rate of crop improvement is essential for achieving sustained food production and other needs of ever-increasing population. Genomic selection (GS) is a potential breeding tool that has been successfully employed in animal breeding and is being incorporated into plant breeding. GS promises accelerated breeding cycles through a rapid selection of superior genotypes. Numerous empirical and simulation studies on GS and realized impacts on improvement in the crop yields are recently being reported. For a holistic understanding of the technology, we briefly discuss the concept of genetic gain, GS methodology, its current status, advantages of GS over other breeding methods, prediction models, and the factors controlling prediction accuracy in GS. Also, integration of speed breeding and other novel technologies viz. high throughput genotyping and phenotyping technologies for enhancing the efficiency and pace of GS, followed by its prospective applications in varietal development programs is reviewed.
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Affiliation(s)
| | | | | | | | | | - Satish Kumar
- Indian Institute of Wheat and Barley Research, Karnal, India
| | | | - Hanif Khan
- Indian Institute of Wheat and Barley Research, Karnal, India
| | | | | | - Gyanendra Singh
- Indian Institute of Wheat and Barley Research, Karnal, India
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Raoul J, Elsen JM. The levels of artificial insemination and missing sire information make genomic selection not always beneficial in meat sheep. Animal 2021; 15:100040. [PMID: 33573971 DOI: 10.1016/j.animal.2020.100040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 06/18/2020] [Accepted: 06/19/2020] [Indexed: 12/01/2022] Open
Abstract
Numerous meat sheep breeding programs in developed and developing countries are characterized by incomplete sire information and a predominant use of natural matings. These two parameters potentially affect the benefit of genomic selection (GS), especially for the selection of a late-in-life trait. Using stochastic simulations, the genetic gains obtained using genomic and conventional strategies for a maternal trait were evaluated in meat sheep population. Natural mating and artificial insemination (AI)-based designs, inspired by the current diversity of designs used for French meat sheep breeds, were modeled and three genomic strategies were tested and compared with a conventional selection strategy: parentage assignment, GS based on a male or a male and female reference population. Genomic selection based on a male reference population did not always outperform conventional selection. Its benefit depended on the design, the level of missing information on dam sires, and the level of AI. Genomic selection based on a male and female reference population always outperformed the conventional selection strategy, even if only 25 % of the females in the nucleus were genotyped.
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Affiliation(s)
- J Raoul
- Institut de l'Elevage, Castanet-Tolosan, France; GenPhySE, Université de Toulouse, INRAE, ENVT, F-31326 Castanet Tolosan, France.
| | - J M Elsen
- GenPhySE, Université de Toulouse, INRAE, ENVT, F-31326 Castanet Tolosan, France
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Kumar A, Raman A, Yadav S, Verulkar S, Mandal N, Singh O, Swain P, Ram T, Badri J, Dwivedi J, Das S, Singh S, Singh S, Kumar S, Jain A, Chandrababu R, Robin S, Shashidhar H, Hittalmani S, Satyanarayana P, Venkateshwarlu C, Ramayya J, Naik S, Nayak S, Dar MH, Hossain S, Henry A, Piepho H. Genetic gain for rice yield in rainfed environments in India. Field Crops Res 2021; 260:107977. [PMID: 33390645 PMCID: PMC7722510 DOI: 10.1016/j.fcr.2020.107977] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The complexity of genotype × environment interactions under drought reduces heritability, which determines the effectiveness of selection for drought tolerance and development of drought tolerant varieties. Genetic progress measured through changes in yield performance over time is important in determining the efficiency of breeding programmes in which test cultivars are replaced each year on the assumption that the new cultivars will surpass the older cultivars. The goal of our study was to determine the annual rate of genetic gain for rice grain yield in a drought-prone rainfed system in a series of multi-environment trials conducted from 2005 to 2014 under the Drought Breeding Network of Indian sites in collaboration with the International Rice Research Institute (IRRI). Our results show a positive trend in grain yield with an annual genetic yield increase of about 0.68 % under irrigated control, 0.87 % under moderate reproductive stage drought stress and 1.9 % under severe reproductive stage drought stress due to breeding efforts. The study also demonstrates the effectiveness of direct selection for grain yield under both irrigated control as well as managed drought stress screening to improve yield in typical rainfed systems. IRRI's drought breeding programme has exhibited a significant positive trend in genetic gain for grain yield over the years under both drought stress as well as favorable irrigated control conditions. Several drought tolerant varieties released from the programme have outperformed the currently grown varieties under varied conditions in the rainfed environments on farmers' fields.
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Affiliation(s)
- Arvind Kumar
- International Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines
- IRRI South Asia Regional Center (ISARC), Varanasi, India
- Corresponding author at: IRRI South Asia Regional Centre (ISARC), NSRTC Campus, G.T. Road, Collectry Farm P.O. Industrial Estate, Varanasi, 221006, Uttar Pradesh, India.
| | - Anitha Raman
- International Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines
| | - Shailesh Yadav
- International Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines
| | - S.B. Verulkar
- Indira Gandhi Krishi Vishwavidyalaya (IGKV), Raipur, India
| | - N.P. Mandal
- Central Rainfed Upland Rice Research Station (CRURRS), ICAR-NRRI, Hazaribagh, India
| | - O.N. Singh
- National Rice Research Institute (NRRI), Cuttack, India
| | - P. Swain
- National Rice Research Institute (NRRI), Cuttack, India
| | - T. Ram
- National Rice Research Institute (NRRI), Cuttack, India
| | - Jyothi Badri
- Indian Institute of Rice Research (IIRR), Hyderabad, India
| | - J.L. Dwivedi
- Narendra Dev University of Agriculture and Technology (NDUAT), Ayodhya, India
| | - S.P. Das
- ICAR Research Complex for NEH Region, Tripura Centre, Lembucherra, India
| | - S.K. Singh
- Banaras Hindu University (BHU), Varanasi, India
| | - S.P. Singh
- Bihar Agricultural University (BAU), Sabour, India
| | - Santosh Kumar
- ICAR-Research Complex for Eastern Region, Patna, India
| | - Abhinav Jain
- International Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines
- Barwale Foundation, Hyderabad, India
| | - R. Chandrababu
- Tamil Nadu Agricultural University (TNAU), Coimbatore, India
| | - S. Robin
- Tamil Nadu Agricultural University (TNAU), Coimbatore, India
| | | | - S. Hittalmani
- University of Agricultural Sciences (UAS), Bangalore, India
| | - P. Satyanarayana
- Regional Rice Research Station, Maruteru, Acharya NG Ranga Agricultural University, (ANGRAU), Guntur, India
| | - Challa Venkateshwarlu
- International Rice Research Institute, South Asia Hub, ICRISAT, Patancheru, Hyderabad, India
| | - Janaki Ramayya
- International Rice Research Institute, South Asia Hub, ICRISAT, Patancheru, Hyderabad, India
| | - Shilpa Naik
- International Rice Research Institute, South Asia Hub, ICRISAT, Patancheru, Hyderabad, India
| | - Swati Nayak
- International Rice Research Institute (IRRI), New Delhi, India
| | - Manzoor H. Dar
- International Rice Research Institute (IRRI), New Delhi, India
| | - S.M. Hossain
- International Rice Research Institute (IRRI), Bhubaneshwar, India
| | - Amelia Henry
- International Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines
| | - H.P. Piepho
- Universitaet Hohenheim, Biostatistics Unit, 70593, Stuttgart, Germany
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12
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Abstract
Lentil is an important food legume crop that has large and complex genome. During past years, considerable attention has been given on the use of next generation sequencing for enriching the genomic resources including identification of SSR and SNP markers, development of unigenes, transcripts, and identification of candidate genes for biotic and abiotic stresses, analysis of genetic diversity and identification of genes/ QTLs for agronomically important traits. However, in other crops including pulses, next generation sequencing has revolutionized the genomic research and helped in genomic assisted breeding rapidly and cost effectively. The present review discuss current status and future prospects of the use NGS based breeding in lentil.
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Affiliation(s)
- Jitendra Kumar
- Division of Crop Improvement, ICAR-Indian Institute of Pulses Research, Kalyanpur, Kanpur, 208024, India.
| | - Debjyoti Sen Gupta
- Division of Crop Improvement, ICAR-Indian Institute of Pulses Research, Kalyanpur, Kanpur, 208024, India
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13
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Hernandez CO, Wyatt LE, Mazourek MR. Genomic Prediction and Selection for Fruit Traits in Winter Squash. G3 (Bethesda) 2020; 10:3601-3610. [PMID: 32816923 PMCID: PMC7534422 DOI: 10.1534/g3.120.401215] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 07/21/2020] [Indexed: 11/20/2022]
Abstract
Improving fruit quality is an important but challenging breeding goal in winter squash. Squash breeding in general is resource-intensive, especially in terms of space, and the biology of squash makes it difficult to practice selection on both parents. These restrictions translate to smaller breeding populations and limited use of greenhouse generations, which in turn, limit genetic gain per breeding cycle and increases cycle length. Genomic selection is a promising technology for improving breeding efficiency; yet, few studies have explored its use in horticultural crops. We present results demonstrating the predictive ability of whole-genome models for fruit quality traits. Predictive abilities for quality traits were low to moderate, but sufficient for implementation. To test the use of genomic selection for improving fruit quality, we conducted three rounds of genomic recurrent selection in a butternut squash (Cucurbita moschata) population. Selections were based on a fruit quality index derived from a multi-trait genomic selection model. Remnant seed from selected populations was used to assess realized gain from selection. Analysis revealed significant improvement in fruit quality index value and changes in correlated traits. This study is one of the first empirical studies to evaluate gain from a multi-trait genomic selection model in a resource-limited horticultural crop.
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Affiliation(s)
- Christopher O Hernandez
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY
| | - Lindsay E Wyatt
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY
| | - Michael R Mazourek
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY
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14
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Chairi F, Sanchez-Bragado R, Serret MD, Aparicio N, Nieto-Taladriz MT, Luis Araus J. Agronomic and physiological traits related to the genetic advance of semi-dwarf durum wheat: The case of Spain. Plant Sci 2020; 295:110210. [PMID: 32534614 DOI: 10.1016/j.plantsci.2019.110210] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Revised: 07/18/2019] [Accepted: 07/31/2019] [Indexed: 05/16/2023]
Abstract
Knowledge of the agronomic and physiological traits associated with genetic gains in yield is essential to improve understanding of yield-limiting factors and to inform future breeding strategies. The aim of this paper is to dissect the agronomic and physiological traits related to genetic gain and to propose an ideotype with high yield that is best adapted to Spanish Mediterranean environments. Six semi-dwarf (i.e. modern) durum wheat genotypes were grown in a wide range of growing conditions in Spain during two successive years. Diverse agronomic, physiological and leaf morphological traits were evaluated. Kernels spike-1 was the yield component most affected by the genetic gain. While no interaction between genotype and growing conditions existed for grain yield, the more productive genotypes were characterized by a plant height of around 85 cm, small erect flag leaves, more open stomata, a better balance between N sources and N sinks and a higher capacity to re-fix CO2 respired by the grain. Moreover, in general the non-laminar parts of the plants play a key role in providing assimilates during grain filling. The high heritability of most of the studied parameters allows their consideration as traits for phenotyping durum wheat better adapted to a wide range of Mediterranean conditions.
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Affiliation(s)
- Fadia Chairi
- Section of Plant Physiology, University of Barcelona, Barcelona, Spain; AGROTECNIO (Center of Research in Agrotechnology), Lleida, Spain
| | - Rut Sanchez-Bragado
- AGROTECNIO (Center of Research in Agrotechnology), Lleida, Spain; Department of Crop and Forest Sciences, University of Lleida, Lleida, Spain
| | - Maria Dolores Serret
- Section of Plant Physiology, University of Barcelona, Barcelona, Spain; AGROTECNIO (Center of Research in Agrotechnology), Lleida, Spain
| | - Nieves Aparicio
- Instituto de Tecnología Agraria de Castilla y León (ITACyL), Valladolid, Spain
| | | | - José Luis Araus
- Section of Plant Physiology, University of Barcelona, Barcelona, Spain; AGROTECNIO (Center of Research in Agrotechnology), Lleida, Spain.
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15
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Bohra A, Saxena KB, Varshney RK, Saxena RK. Genomics-assisted breeding for pigeonpea improvement. Theor Appl Genet 2020; 133:1721-1737. [PMID: 32062675 DOI: 10.1007/s00122-020-03563-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 02/08/2020] [Indexed: 05/25/2023]
Abstract
The review outlines advances in pigeonpea genomics, breeding and seed delivery systems to achieve yield gains at farmers' field. Pigeonpea is a nutritious and stress-tolerant grain legume crop of tropical and subtropical regions. Decades of breeding efforts in pigeonpea have resulted in development of a number of high-yielding cultivars. Of late, the development of CMS-based hybrid technology has allowed the exploitation of heterosis for yield enhancement in this crop. Despite these positive developments, the actual on-farm yield of pigeonpea is still well below its potential productivity. Growing needs for high and sustainable pigeonpea yields motivate scientists to improve the breeding efficiency to deliver a steady stream of cultivars that will provide yield benefits under both ideal and stressed environments. To achieve this objective in the shortest possible time, it is imperative that various crop breeding activities are integrated with appropriate new genomics technologies. In this context, the last decade has seen a remarkable rise in the generation of important genomic resources such as genome-wide markers, high-throughput genotyping assays, saturated genome maps, marker/gene-trait associations, whole-genome sequence and germplasm resequencing data. In some cases, marker/gene-trait associations are being employed in pigeonpea breeding programs to improve the valuable yield and market-preferred traits. Embracing new breeding tools like genomic selection and speed breeding is likely to improve genetic gains. Breeding high-yielding pigeonpea cultivars with key adaptation traits also calls for a renewed focus on systematic selection and utilization of targeted genetic resources. Of equal importance is to overcome the difficulties being faced by seed industry to take the new cultivars to the doorstep of farmers.
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Affiliation(s)
- Abhishek Bohra
- ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, 208024, India.
| | - K B Saxena
- , 17, NMC Housing, Al Ain, Abu Dhabi, United Arab Emirates
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Rachit K Saxena
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
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16
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Joshi DC, Chaudhari GV, Sood S, Kant L, Pattanayak A, Zhang K, Fan Y, Janovská D, Meglič V, Zhou M. Revisiting the versatile buckwheat: reinvigorating genetic gains through integrated breeding and genomics approach. Planta 2019; 250:783-801. [PMID: 30623242 DOI: 10.1007/s00425-018-03080-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 12/20/2018] [Indexed: 05/09/2023]
Abstract
Emerging insights in buckwheat molecular genetics allow the integration of genomics driven breeding to revive this ancient crop of immense nutraceutical potential from Asia. Out of several thousand known edible plant species, only four crops-rice, wheat, maize and potato provide the largest proportion of daily nutrition to billions of people. While these crops are the primary supplier of carbohydrates, they lack essential amino acids and minerals for a balanced nutrition. The overdependence on only few crops makes the future cropping systems vulnerable to the predicted climate change. Diversifying food resources through incorporation of orphan or minor crops in modern cropping systems is one potential strategy to improve the nutritional security and mitigate the hostile weather patterns. One such crop is buckwheat, which can contribute to the agricultural sustainability as it grows in a wide range of environments, requires relatively low inputs and possess balanced amino acid and micronutrient profiles. Additionally, gluten-free nature of protein and nutraceutical properties of secondary metabolites make the crop a healthy alternative of wheat-based diet in developed countries. Despite enormous potential, efforts for the genetic improvement of buckwheat are considerably lagged behind the conventional cereal crops. With the draft genome sequences in hand, there is a great scope to speed up the progress of genetic improvement of buckwheat. This article outlines the state of the art in buckwheat research and provides concrete perspectives how modern breeding approaches can be implemented to accelerate the genetic gain. Our suggestions are transferable to many minor and underutilized crops to address the issue of limited genetic gain and low productivity.
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Affiliation(s)
- D C Joshi
- Indian Council of Agricultural Research-Vivekananda Institute of Hill Agriculture, Almora, Uttarakhand, India.
| | - Ganesh V Chaudhari
- Indian Council of Agricultural Research-Vivekananda Institute of Hill Agriculture, Almora, Uttarakhand, India
| | - Salej Sood
- Indian Council of Agricultural Research-Central Potato Research Institute, Shimla, Himachal Pradesh, India
| | - Lakshmi Kant
- Indian Council of Agricultural Research-Vivekananda Institute of Hill Agriculture, Almora, Uttarakhand, India
| | - A Pattanayak
- Indian Council of Agricultural Research-Vivekananda Institute of Hill Agriculture, Almora, Uttarakhand, India
| | - Kaixuan Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yu Fan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dagmar Janovská
- Department of Gene Bank, Crop Research Institute, Drnovská, Prague, Czech Republic
| | - Vladimir Meglič
- Agricultural Institute of Slovenia, Hacquetova ulica, Ljubljana, Slovenia
| | - Meiliang Zhou
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
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17
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Opoola O, Mrode R, Banos G, Ojango J, Banga C, Simm G, Chagunda MGG. Current situations of animal data recording, dairy improvement infrastructure, human capacity and strategic issues affecting dairy production in sub-Saharan Africa. Trop Anim Health Prod 2019; 51:1699-705. [PMID: 30945155 DOI: 10.1007/s11250-019-01871-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 03/15/2019] [Indexed: 10/31/2022]
Abstract
An online survey on the state of existing dairy data, dairy improvement infrastructure and human capacity in sub-Saharan Africa (SSA) was undertaken with the aim of assessing whether the state of existing animal recording, dairy improvement methods and key issues facing dairy production together with means of addressing the issues differ among countries and regions of SSA. Respondents comprised experts and practitioners in livestock production and genetic resources from research institutes, animal breeding companies, universities, non-governmental organisations and government agricultural ministries. The main dairy farming system in which the respondents were involved was mixed crop-livestock system (30.2%), and this was mainly practised in the private land tenure system (46.3%). Data were analysed using linear model and paired Student t test in R software package. Respondents identified key issues affecting dairy production as poor genetic assessment of imported exotic breeds and crosses in Africa (62.3%), fluctuations in milk prices within both the formal and informal markets (50.9%), no comprehensive sire ranking systems (39.6%), housing and health management regimes which adversely affect milk yield (32.1%), poor market networks for dairy products (25.5%), poor feeding (13.3%), inadequate genetic technologies (9.4%) and poor animal performance recording systems (9.4%). Respondents emphasised the need for updated breeding policies, sire ranking systems, adequate farm management systems, capacity building, across-country collaborations and joint genetic assessments of dairy breeds found in sub-Saharan Africa. The current situation of dairy production though similar for the different countries, differed in order of emphasis and magnitude across the countries and regions in sub-Saharan Africa.
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18
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Cros D, Bocs S, Riou V, Ortega-Abboud E, Tisné S, Argout X, Pomiès V, Nodichao L, Lubis Z, Cochard B, Durand-Gasselin T. Genomic preselection with genotyping-by-sequencing increases performance of commercial oil palm hybrid crosses. BMC Genomics 2017; 18:839. [PMID: 29096603 PMCID: PMC5667528 DOI: 10.1186/s12864-017-4179-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 10/05/2017] [Indexed: 01/14/2023] Open
Abstract
Background There is great potential for the genetic improvement of oil palm yield. Traditional progeny tests allow accurate selection but limit the number of individuals evaluated. Genomic selection (GS) could overcome this constraint. We estimated the accuracy of GS prediction of seven oil yield components using A × B hybrid progeny tests with almost 500 crosses for training and 200 crosses for independent validation. Genotyping-by-sequencing (GBS) yielded +5000 single nucleotide polymorphisms (SNPs) on the parents of the crosses. The genomic best linear unbiased prediction method gave genomic predictions using the SNPs of the training and validation sets and the phenotypes of the training crosses. The practical impact was illustrated by quantifying the additional bunch production of the crosses selected in the validation experiment if genomic preselection had been applied in the parental populations before progeny tests. Results We found that prediction accuracies for cross values plateaued at 500 to 2000 SNPs, with high (0.73) or low (0.28) values depending on traits. Similar results were obtained when parental breeding values were predicted. GS was able to capture genetic differences within parental families, requiring at least 2000 SNPs with less than 5% missing data, imputed using pedigrees. Genomic preselection could have increased the selected hybrids bunch production by more than 10%. Conclusions Finally, preselection for yield components using GBS is the first possible application of GS in oil palm. This will increase selection intensity, thus improving the performance of commercial hybrids. Further research is required to increase the benefits from GS, which should revolutionize oil palm breeding. Electronic supplementary material The online version of this article (10.1186/s12864-017-4179-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- David Cros
- CIRAD, UMR AGAP (Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit), F-34398, Montpellier, France.
| | - Stéphanie Bocs
- CIRAD, UMR AGAP (Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit), F-34398, Montpellier, France.,South Green Bioinformatics Platform, Montpellier, France
| | - Virginie Riou
- CIRAD, UMR AGAP (Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit), F-34398, Montpellier, France
| | - Enrique Ortega-Abboud
- CIRAD, UMR AGAP (Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit), F-34398, Montpellier, France.,South Green Bioinformatics Platform, Montpellier, France
| | - Sébastien Tisné
- CIRAD, UMR AGAP (Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit), F-34398, Montpellier, France
| | - Xavier Argout
- CIRAD, UMR AGAP (Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit), F-34398, Montpellier, France
| | - Virginie Pomiès
- CIRAD, UMR AGAP (Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit), F-34398, Montpellier, France
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19
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Bassi FM, Bentley AR, Charmet G, Ortiz R, Crossa J. Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.). Plant Sci 2016; 242:23-36. [PMID: 26566822 DOI: 10.1016/j.plantsci.2015.08.021] [Citation(s) in RCA: 136] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2015] [Revised: 08/23/2015] [Accepted: 08/27/2015] [Indexed: 05/18/2023]
Abstract
In the last decade the breeding technology referred to as 'genomic selection' (GS) has been implemented in a variety of species, with particular success in animal breeding. Recent research shows the potential of GS to reshape wheat breeding. Many authors have concluded that the estimated genetic gain per year applying GS is several times that of conventional breeding. GS is, however, a new technology for wheat breeding and many programs worldwide are still struggling to identify the best strategy for its implementation. This article provides practical guidelines on the key considerations when implementing GS. A review of the existing GS literature for a range of species is provided and used to prime breeder-oriented considerations on the practical applications of GS. Furthermore, this article discusses potential breeding schemes for GS, genotyping considerations, and methods for effective training population design. The components of selection intensity, progress toward inbreeding in half- or full-sibs recurrent schemes, and the generation of selection are also presented.
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Affiliation(s)
- Filippo M Bassi
- International Center for Agricultural Research in the Dry Areas (ICARDA), Av. Mohamed Alaoui, Rabat 10000, Morocco
| | - Alison R Bentley
- The John Bingham Laboratory, NIAB, Huntingdon Road, Cambridge CB3 0LE, United Kingdom
| | - Gilles Charmet
- Institut national de la Recherche Agronomique, INRA UMR1095 GDEC Clermont-Ferrand, 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France
| | - Rodomiro Ortiz
- Swedish University of Agricultural Sciences (SLU), Sundsvagen 14 Box 101, SE23453, Alnarp, Sweden.
| | - Jose Crossa
- Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600 Mexico DF, Mexico
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