Real Time deployment of pathogen resistance genes in rice
Real Time deployment of pathogen resistance genes in rice
批准号:
BB/N01362X/1
负责人:
Frank Van Den Bosch
金额:
$61.09万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --
中文摘要
白叶枯病和稻瘟病是世界范围内水稻减产的两种主要病原菌。品种抗性是保护水稻免受这些病原体侵害的有效、可靠和环境友好的方法。现代分子育种技术的发展和应用,使水稻品种推广的优良品系世代由8-10年缩短到2-3年。这意味着,通过基因轮换或在单一遗传背景下的混合,可以定制具有各种抗性基因组合的抗性品种的实时部署。当前育种项目产生的新品种将在两到三年内发布。这使得种植者可以获得一系列具有独特抗性基因组合的品种。那么,一个关键问题是:这些品种应该在哪里部署?每个品种都应部署在病原体群体中不存在匹配毒力或毒力频率极低的地方。这确保了抗性品种在尽可能长的时间内保持有效。因此,我们需要一种方法来确定的情况下,或可能存在的频率极低,病原体毒力在field.We因此,我们的目标是开发和应用一个组合的建模和现场监测方法,以确定一个新的抗性基因可以安全地部署,因为毒力是在一个足够低的频率在病原体种群的领域。方法:-1-将量化易感品种的观察地块中的感染数量。具有新抗性品种的类似地块将显示无感染(理想地)。使用统计方法,我们将能够估计田间病原体种群中毒力的最大预期频率。如果这个频率足够小(例如10-10),我们可以决定释放新的抗性品种。2-将从外地扩大到区域一级。这将使我们能够在更大的空间尺度上做出关于品种释放的决定。该模型将根据目前在泰国北部扩张的侵略性细菌爆炸菌株的现场监测进行参数化。3-将提供,与必要的培训,为未来使用的水稻研究界。4-将开始与其开发一起使用,以帮助解决威胁泰国北方水稻生产的新的侵略性细菌稻瘟病菌株所带来的新问题。该项目的成果将是一套方法,以确定在菲律宾和泰国可以发布新的抗性品种,以最大限度地提高品种抗性的持久性。这将对种植者有明显的好处,因为他们将减少因破坏新抗性的强毒株而遭受的损失。这反过来又会增加贫困种植者的收入。该项目还将对工作人员进行统计方法、流行病学建模和使用项目中开发的方法方面的培训。该项目还将帮助育种者确定育种目标,向他们提供有关田间病原体毒性的信息。
英文摘要
Bacterial blight and rice blast are two key pathogens reducing rice productivity worldwide. Varietal resistance is an effective, reliable and environmentally friendly way of protecting rice against these pathogens. The development and use of modern molecular breeding techniques has shortened the generation of elite rice lines for varietal release from 8-10 years to 2-3 years. This means that real-time deployment of resistant varieties with various combinations of resistance genes can be customized through gene rotation or mixture in a single genetic background.New varieties resulting from current breeding projects will be released in two to three years. This makes a range of varieties each with a unique combination of resistance genes available to growers. A key question, then, is: Where should these varieties be deployed? Each variety should be deployed where the matching virulence is not present, or is at an extremely low frequency, in the pathogen population. This ensures that the resistant variety remains effective for the maximum possible time. We thus need a method to ascertain the absence, or possible presence in extremely small frequency, of pathogen virulence in the field.We therefore aim to develop and apply a combined modelling and field monitoring approach to determine areas where a novel resistance gene can safely be deployed because virulence is at a sufficiently low frequency in the pathogen population. The method:-1- Will quantify the number of infections in observational plots of a susceptible variety. A similar plot with the novel resistant variety will show no infections (ideally). Using a statistical method we will then be able to estimate the maximum expected frequency of virulence in a field pathogen population. If this frequency is small enough (e.g. 10-10) we can decide that the new resistant variety be released.-2- Will be scaled-up from the field level to a regional level. This will enable us to make decisions about variety release at larger spatial scales. The model will be parameterised from field monitoring of an aggressive bacterial blast strain currently expanding in the north of Thailand.-3- Will be made available, with the necessary training, for future use to the rice research community.-4- Will start to be used alongside its development to help solve the emerging problem posed by the new expanding aggressive bacterial blast strain that threatens northern Thailand's rice production.The outputs of the project will be a set of methods to establish where in the Philippines and Thailand novel resistant varieties can be released to maximise the durability of varietal resistance. This will be of clear benefit to growers as they will suffer less from virulent strains breaking the novel resistance. This in turn will improve the income of poor growers. The project will also train staff in statistical methods, epidemiological modelling and the use of the methods developed in the project. The project will also help breeders to establish breeding targets by providing them with information on the presence of pathogen virulence in the field.
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DOI:
10.1111/ppa.12453
发表时间:
2016-02
期刊:
Plant pathology
影响因子:
2.7
作者:
[McQuaid CF, Sseruwagi P, Pariyo A, van den Bosch F]
通讯作者:
van den Bosch F
DOI:
10.1007/s10658-021-02452-z
发表时间:
2022-01-07
期刊:
EUROPEAN JOURNAL OF PLANT PATHOLOGY
影响因子:
1.8
作者:
[Niones, Jennifer T., Sharp, Ryan T., Oliva, Ricardo]
通讯作者:
Oliva, Ricardo
DOI:
10.1371/journal.pcbi.1005654
发表时间:
2017-07
期刊:
PLoS computational biology
影响因子:
4.3
作者:
[McQuaid CF, van den Bosch F, Szyniszewska A, Alicai T, Pariyo A, Chikoti PC, Gilligan CA]
通讯作者:
Gilligan CA
DOI:
10.1098/rspb.2017.0547
发表时间:
2017-07-26
期刊:
Proceedings. Biological sciences
影响因子:
--
作者:
[Brown N, van den Bosch F, Parnell S, Denman S]
通讯作者:
Denman S
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