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靶向测序基因型检测(GBTS)技术及其应用 被引量:55
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作者 徐云碧 杨泉女 +10 位作者 郑洪建 许彦芬 桑志勤 郭子锋 彭海 张丛 蓝昊发 王蕴波 吴坤生 陶家军 张嘉楠 《中国农业科学》 CAS CSCD 北大核心 2020年第15期2983-3004,共22页
借助于分子标记进行基因型检测的技术在生物遗传改良等领域发挥着重要的作用。国际跨国种业公司凭借其高通量、自动化、大规模的共享检测平台,基因型检测技术得到广泛应用。随着从3G时代的高成本固相芯片和随机测序式基因型检测(genotyp... 借助于分子标记进行基因型检测的技术在生物遗传改良等领域发挥着重要的作用。国际跨国种业公司凭借其高通量、自动化、大规模的共享检测平台,基因型检测技术得到广泛应用。随着从3G时代的高成本固相芯片和随机测序式基因型检测(genotyping by sequencing,GBS)发展到成本低、对检测平台要求较低、基于靶向测序基因型检测(genotyping by target sequencing,GBTS)的液相芯片,基因型检测技术完成了向4G时代的转变。在本文中首先介绍了两项最新的GBTS技术(基于多重PCR的GenoPlexs和基于液相探针捕获的GenoBaits)及其原理。同时,发展了可以在单个扩增子内检测多个SNP,称之为多聚单核苷酸多态性(multiple single-nucleotide-polymorphism cluster,mSNP或multiple dispersed nucleotide polymorphism,MNP)的技术,极大地提高了目标位点(扩增子)内变异的检测效率。与GBS和固相芯片相比,GBTS技术具有平台广适性、标记灵活性、检测高效性、信息可加性、支撑便捷性和应用广谱性。同一款标记集(例如玉米40K mSNP),可以获得3种不同的标记形式(40K mSNP、260K SNP和754K单倍型);并可以根据应用场景的需求,通过控制测序深度获得多种不同的标记密度(1-40K mSNP)。GenoPlexs和GenoBaits 2种技术相结合,可广泛应用于生物进化、遗传图谱构建、基因定位克隆、标记性状关联检测(全基因组关联分析——GWAS和混合样本分析——BSA)、后裔鉴定、基因渐渗、基因累加、品种权保护、品种质量监测、转基因成分/基因编辑/伴生生物检测等领域。目前,已经在20余种主要农作物、蔬菜以及部分动物和微生物中开发了GBTS标记50余套,并已广泛应用于上述领域。最后,展望了与未来GBTS应用相关的几个问题,包括便携式、自动化、高通量、智能化检测平台;根据用户需求定制的可变密度、多功能分子检测;GBTS与其他技术(KASP、高密度芯片� 展开更多
关键词 靶向测序基因型检测(GBTS) 多重PCR 液相探针 多聚单核苷酸多态性(mSNP) 多个分散型核苷酸多态性(MNP) 单倍型 遗传改良 开源育种
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Enhancing Genetic Gain through Genomic Selection: From Livestock to Plants 被引量:10
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作者 Yunbi Xu Xiaogang Liu +7 位作者 Junjie Fu Hongwu Wang Jiankang Wang Changling Huang Boddupalli MPrasanna Michael SOlsen Guoying Wang Aimin Zhang 《Plant Communications》 2020年第1期4-24,共21页
Although long-term genetic gain has been achieved through increasing use of modern breeding methods and technologies,the rate of genetic gain needs to be accelerated to meet humanity’s demand for agricultural product... Although long-term genetic gain has been achieved through increasing use of modern breeding methods and technologies,the rate of genetic gain needs to be accelerated to meet humanity’s demand for agricultural products.In this regard,genomic selection(GS)has been considered most promising for genetic improvement of the complex traits controlled by many genes each with minor effects.Livestock scientists pioneered GS application largely due to livestock’s significantly higher individual values and the greater reduction in generation interval that can be achieved in GS.Large-scale application of GS in plants can be achieved by refining field management to improve heritability estimation and prediction accuracy and developing optimum GS models with the consideration of genotype-by-environment interaction and non-additive effects,along with significant cost reduction.Moreover,it would be more effective to integrate GS with other breeding tools and platforms for accelerating the breeding process and thereby further enhancing genetic gain.In addition,establishing an open-source breeding network and developing transdisciplinary approaches would be essential in enhancing breeding efficiency for small-and medium-sized enterprises and agricultural research systems in developing countries.New strategies centered on GS for enhancing genetic gain need to be developed. 展开更多
关键词 genomic selection genetic gain open-source breeding genomic prediction molecular marker livestock breeding
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