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1.
While hybrid breeding is widely applied in outbreeding species, for many self‐pollinating crop plants, it has only recently been established. This may have had its reason in the limitations of methods available for hybrid performance prediction, in particular when established heterotic pools were absent. Genomic selection has been suggested as a promising approach to resolve these limitations. In our review, we briefly introduce the principles of genomic selection as an extension of marker‐assisted selection using genome‐wide high‐density molecular marker data and discuss the advantages and limitations of currently used algorithms. Including the outcome from a recent extended approach to hybrid wheat as a timely example, we summarize current progress in empirical studies on the application of genomic selection for prediction of hybrid performance. Here, we put emphasis on the factors affecting the accuracy of prediction, pointing in particular to the relevance of relatedness, genotype x environment interaction and experimental design. Finally, we discuss future research needs and potential applications. 相似文献
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Torben Schulz‐Streeck Joseph O. Ogutu Andrés Gordillo Zivan Karaman Carsten Knaak Hans‐Peter Piepho 《Plant Breeding》2013,132(6):532-538
Genomic selection has been routinely implemented in plant breeding in two stages. The first stage usually omits the marker information and estimates adjusted means of genotypes across environments. The second stage uses the adjusted means to predict genomic breeding values. However, if the effects of markers vary substantially between different environments, it may be important to account for this variation for varieties adapted to different environments. Using two maize data sets, we investigated whether modelling the marker‐by‐environment interaction can improve the predictive ability of genomic selection relative to modelling genotype‐by‐environment interaction alone. Modelling the marker‐by‐environment interaction did not substantially increase the predictive ability relative to modelling only the genotype‐by‐environment interaction for the two tested data sets. Thus, genomic selection, carried out in a stagewise fashion, such that the marker information is omitted until the last stage of the process, may suffice for most practical purposes. Moreover, predictive ability did not reduce substantially even when the number of markers with consistent effects across environments used for genomic prediction was reduced to about 50. 相似文献
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目前, 基因组选择育种主要采用线性模型估计遗传育种值指导作物遗传育种的筛选过程, 但是生物体内的基因以及遗传位点的关系主要是复杂的非线性调控。本研究将人工神经网络技术应用到作物基因组选择育种中, 对现有的作物基因组选择育种模型进行优化, 建立了高效的作物基因组选择预测系统, 并与其他线性回归预测模型进行比较。通过分析小麦的育种数据发现, 基于人工神经网络的遗传育种估计效果优于其他线性回归预测模型, 预测育种值与实际育种值间的相关系数平均值达到0.6636, 相应的岭回归BLUP、贝叶斯线性回归模型和基于系谱信息的贝叶斯回归模型的预测能力分别为0.6422、0.6294和0.6573; 最优的预测效果达到0.8379, 远高于其他2种模型的最优结果。同时, 基于人工神经网络的基因组选择模型的预测效果稳定, 与传统的统计模型相近, 因此, 利用人工神经网络技术建立基因组选择是可行的。 相似文献
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Wallace A. Cowling 《Plant Breeding》2013,132(1):1-9
Plant breeders disrupt Hardy–Weinberg equilibrium through selection, non‐random mating, drift, migration and mutation. Sustainable plant breeding can be defined as productive and competitive breeding that is achieved without loss of genetic diversity in the elite breeding population during the professional career of the breeder. Breeding is often productive but not sustainable. From 1974 to 2000, the animal breeding programme Meatlinc in the United Kingdom had effective population size of 95, population inbreeding of 0.19% per year and generation interval of 2.15 years. Genetic progress in Meatlinc tripled in the 8 years following introduction of best linear unbiased prediction (BLUP) selection (based on the information from relatives) in 1992. Canola breeding in Australia from 1970 to 2000 had longer generation interval (6 years), smaller effective population size (<11) and higher rates of inbreeding (>0.7% per year). BLUP selection in canola was first reported in 2010. Neither programme replaced genetic diversity lost through selection and drift. Most breeding programmes violate conditions of the infinitesimal model, thereby reducing predictability of selection, but breeders can minimize these limitations to sustainable plant breeding. 相似文献
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Conventional genomic selection approaches use breeding values to evaluate individual plants or animals and to make selection decisions. Multiple variants of breeding values and selection approaches have been proposed, but they suffer two major limitations. First, selection decisions are not responsive to changes in time and resource availability. Second, selection decisions are not coordinated with related decisions such as mating and resource allocation. We present three new genomic selection approaches that attempt to address these two limitations, which were designed by engineering students in a class project at Iowa State University. Compared with previous approaches using the same data set from the literature, two of these engineering approaches were found to be comparable to the state of the art, and the third one significantly dominated all the previous approaches. 相似文献
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为促进基因组选择在植物遗传改良中的应用,笔者总结了基因组选择的原理与方法、分析了基因组选择育种的统计方法,指出了各种因素对基因组选择的影响,总结了基因组选择面临的挑战,并讨论了基因组选择在植物数量性状分子育种研究中可能的应用。认为随着基因型分析成本的降低和统计方法的发展,植物基因组选择将会逐步完善,将在植物基因组育种中发挥重要的作用。 相似文献
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Genomic selection (GS) is a disruptive methodology that is revolutionizing animal and plant breeding. However, its practical implementation is challenging since many times there is a mismatch in the distribution of the training and testing sets. Adversarial validation is an approach popular in machine learning to detect and address the difference between the training and testing distributions. For this reason, the adversarial validation method in this research was implemented using probit regression to detect the mismatch in distributions and also to select an optimal training set. We evaluated the proposed method with 14 datasets, and the results were benchmarked regarding of using the whole reference population and simple random samples. We found that the proposed method is effective for detecting the mismatch in distributions and outperformed in prediction accuracy by 11.67% (in terms of mean square error) and by 5.35% (in terms of normalized mean square error) when the whole reference population was used as training sets. Also, in general, this outperformed some existing methods for optimal training designs in the context of GS. 相似文献
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Maize is a commodity crop providing millions of people with food, feed, industrial raw material and economic opportunities. However, maize yields in Africa are relatively stagnant and low, at a mean of 1.7 t ha−1 compared with the global average of 6 t ha−1. The yield gap can be narrowed with accelerated and precision breeding strategies that are required to develop and deploy high-yielding and climate-resilient maize varieties. Genomic and phenotypic selections are complementary methods that offer opportunities for the speedy choice of contrasting parents and derived progenies for hybrid breeding and commercialization. Genomic selection (GS) will shorten the crop breeding cycle by identifying and tracking desirable genotypes and aid the timeous commercialization of market-preferred varieties. The technology, however, has not yet been fully embraced by most public and private breeding programmes, notably in Africa. This review aims to present the importance, current status, challenges and opportunities of GS to accelerate genetic gains for economic traits to speed up the breeding of high-yielding maize varieties. The first section summarizes genomic selection and the contemporary phenotypic selection and phenotyping platforms as a foundation for GS and trait integration in maize. This is followed by highlights on the reported genetic gains and progress through phenotypic selection and GS for grain yield and yield components. Training population development, genetic design and statistical models used in GS in maize breeding are discussed. Lastly, the review summarizes the challenges of GS, including prediction accuracy, and integrates GS with speed breeding, doubled haploid breeding and genome editing technologies to increase breeding efficiency and accelerate cultivar release. The paper will guide breeders in selection and trait introgression using GS to develop cultivars preferred by the marketplace. 相似文献
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Natália Botega Alves Marcio Balestre João Paulo Pennacchi Monique Caroline Nunes Fernandes Douglas Goulart Castro Flávia Barbosa Silva Botelho 《Plant Breeding》2020,139(5):853-861
The rice crop is affected by diseases throughout its cycle, impacting negatively on grain yield and quality. The control of the disease impact can be accomplished via crop breeding, using highly multiple resistant genotypes. This study aimed to evaluate the efficiency of multiple-character and specific selection of multiple resistance to major culture-associated diseases (neck blast, leaf scald and grain discoloration) in rice lines of the Upland Rice Genetic Breeding Program. The experiments were conducted in 35 sites during 12 agricultural years, where 124 lines were evaluated for the severity of fungal diseases, under natural field conditions. Multiple parameters were calculated based on the diseases´ scores: genetic, phenotypic and environmental variances, heritability, selection gain, renewal rate, and genetic and renewal progress. Genetic variance for the disease resistance was identified in the population, and the selection gain for multiple-character selection was of 3.16 year−1 throughout the breeding process with a renewal rate of over 35%. The programme has showed efficiency in selecting multiple resistant genotypes to the mentioned diseases, highlighting genotypes with high potential for market release. 相似文献
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Fusarium head blight is among the most extensively studied fungal diseases of wheat and other small grain cereals due to its impact on yield and quality, but particularly due to its potential to produce mycotoxins, which are harmful to humans and animals. Since our last comprehensive review on QTL mapping and marker-assisted selection for FHB resistance in wheat in 2009, numerous studies have been conducted to identify, validate or fine-map resistance QTL. The main aim of this review is to update and summarize findings on FHB resistance breeding of wheat published during the last decade. Furthermore, we compiled a user-friendly table listing FHB resistance QTL data providing a valuable resource for further FHB resistance research. The role of morphological and phenological traits on FHB resistance and possible consequences for resistance breeding are discussed. This review concentrates current knowledge on breeding for FHB resistance and suggests strategies to enhance resistance by deploying molecular breeding methods, including marker-assisted and genomic selection. 相似文献
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Tobias Würschum Hans Peter Maurer Sigrid Weissmann Volker Hahn Willmar L. Leiser 《Plant Breeding》2017,136(2):230-236
Genomic prediction has emerged as a powerful genomic tool to assist breeding of complex traits. In this study, we employed a population of 647 triticale doubled haploid lines derived from four families to assess the potential of this approach for triticale breeding. All lines were phenotyped for grain yield, thousand‐kernel weight, biomass yield, plant height, frost tolerance and Fusarium head blight resistance. The obtained prediction accuracies were moderate to high and consisted to varying degrees of within‐ and among‐family variance, in line with the different degrees of phenotypic differences between family means. The prediction accuracy within individual families also varied with the genetic complexity of the traits and was generally highest based on effect estimation with lines from the respective family, whereas the prediction accuracy decreased with decreasing relatedness among the families. Taken together, our results illustrate the potential of genomic prediction to increase selection gain in triticale breeding, but the composition of the training set is of utmost importance, and consequently, the implementation of this approach in applied breeding programmes is not straightforward. 相似文献
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This study compared three strategies to develop new recipients for quantitative trait loci (QTL) introgression (background recovery [BG], selective sweep [SS] and breeding value [BV]) in a short-term rice breeding programme (over five breeding cycles). Furthermore, we evaluated two different numbers of recipients (10 and 20) in the introgression process and how they influence the population performance and the QTL fixation over cycles. Finally, we used the International Rice Research Institute (IRRI) rice breeding framework as the model to perform the stochastic simulations. Each strategy was simulated and replicated 100 times. Regardless of the selection strategy used, the QTL introgression resulted in substantial penalties in yield performance. However, introducing fewer new parents to the augmentation process minimized this effect. Conversely, the time required to achieve fixation of target QTLs showed substantial differences, with selection for BV during augmentation outperforming other methods. Overall, the BV_10 strategy (10 parents selected based on genomic estimated BV) displayed the best trade-off between reduced penalty from introducing new QTLs with a reasonable speed at which those QTLs can achieve fixation over subsequent breeding cycles. 相似文献
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Congwei Sun Huiting Hu Yongzhen Cheng Xi Yang Qi Qiao Canguan Wang Leilei Zhang Daiying Chen Simin Zhao Zhongdong Dong Feng Chen 《Plant Breeding》2023,142(3):259-268
Common wheat provides approximately 20% of the total dietary calorie intake of human beings. Recent technological advances in whole-genome sequencing and their application in wheat and its progenitor species provide new opportunities to uncover the genetic variation of wheat traits and to accelerate the traditional breeding (TB) strategies in the context of genomics-assisted breeding (GAB). Integration of TB, marker-assisted selection (MAS) and genomic selection (GS) with high-density SNP markers is expected to accelerate the breeding process and to further enhance genetic gain. With the assistance of the next- or third-generation sequencing technologies and high-throughput phenotyping platforms, GAB can now realistically be considered in the following area: (i) genome sequencing and high-quality assembly to uncover new variations, (ii) whole-genome sequence-based association studies, (iii) gene function (or functional gene) identification and (iv) integration of whole genomic breeding information, utilizing multi-omics data and different breeding strategies. We argue that GAB is becoming the preferred strategy in pursuit of new wheat cultivars with superior traits on high yielding, high nutritional quality, climate-resilience and so on. 相似文献
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为更好的解释农村剩余劳动力转移的影响因素,在国内外农村剩余劳动力研究的基础上,笔者运用定性和定量相结合的分析方法进行分析。为避免多重共线性在模型中的影响,采用岭回归模型对相应影响变量进行分析。通过模型综合分析,验证了影响中国农村剩余劳动力转移的推动因素和制约因素。同时提出发展区域经济,提高农民收入;推进城镇化进程,拓宽农民就业渠道;促进二、三产业发展转型与加强农民专业培训齐头并进;深化以户籍制度为中心的制度变革等4项政策建议。 相似文献
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Common scab, caused by Streptomyces scabies, is a disease that produces scab-like surface lesions on potato tubers. Testing for susceptibility/resistance of breeding
lines at the Potato Research Centre of Agriculture & Agri-Food Canada (AFC) is carried out in a scab nursery maintained at
AFC for the annual scab evaluation field trials. A replicated field trial routinely consists of breeding lines from previous
testing season(s) plus newly selected lines. Data of scab scores generated from long-term experiments thus formulate an incomplete
2-way table over combinations of breeding lines (genotypes) and trials (years). This requires an advanced statistical method
to estimate genetic parameters for evaluation purposes. A data base with 1,435 scab index scores from 344 breeding lines were
extracted from 5 years (1995–1999) of field experiments in the scab nursery maintained at AFC. The statistical method Residual
Maximum Likelihood (REML) was employed to estimate variance components of the breeding population and Best Linear Unbiased
Predictor (BLUP) was used to predict genetic merit of breeding lines. High heritability was obtained from variance components
estimated by REML. The BLUP scores of breeding lines provided reliable evaluation of their responses to common scab. Two data
base sub-sets were separately formulated from the original data base for those parents and grandparents of the breeding lines
having pedigree records available. They were again subjected to REML and BLUP analyses to compare the responses to common
scab and identify sources of resistance at the parental and grandparental levels. Two random data sets with equal sized samples
of breeding lines were also generated from the over-all data base. The two sets of BLUP scores between corresponding breeding
lines and parents showed high association which provides an assessment of the validity of the evaluation process. 相似文献
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Kulbhushan Saxena Abhishek Bohra Arbind K. Choudhary Rafat Sultana Mamta Sharma Lekha T. Pazhamala Rachit K. Saxena 《Plant Breeding》2021,140(1):74-86
Pigeonpea is an important food legume crop of semi‐arid tropical regions. Plateauing of pigeonpea yield has been worrying breeders for the past 6–7 decades. Serious breeding efforts made during this period resulted in various high‐yielding and disease resistant cultivars. However, the gains in pigeonpea productivity have been modest. The authors, while reviewing this situation, conclude that long generation turnover, complexity of biological traits, low selection response and overreliance upon pedigree breeding present the key bottlenecks for this situation. In this paper, some alternative breeding approaches and technologies are suggested for the genetic enhancement of yield stability and stress response of pigeonpea. 相似文献