Singh Vikas K, Khan Aamir W, Saxena Rachit K, Sinha Pallavi, Kale Sandip M, Parupalli Swathi, Kumar Vinay, Chitikineni Annapurna, Vechalapu Suryanarayana, Sameer Kumar Chanda Venkata, Sharma Mamta, Ghanta Anuradha, Yamini Kalinati Narasimhan, Muniswamy Sonnappa, Varshney Rajeev K
International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Telangana State, India.
Agricultural Research Station (ARS)-Tandur, Professor Jayashankar Telangana State Agricultural University (PJTSAU), Hyderabad, Telangana State, India.
Plant Biotechnol J. 2017 Jul;15(7):906-914. doi: 10.1111/pbi.12685. Epub 2017 Feb 9.
Identification of candidate genomic regions associated with target traits using conventional mapping methods is challenging and time-consuming. In recent years, a number of single nucleotide polymorphism (SNP)-based mapping approaches have been developed and used for identification of candidate/putative genomic regions. However, in the majority of these studies, insertion-deletion (Indel) were largely ignored. For efficient use of Indels in mapping target traits, we propose Indel-seq approach, which is a combination of whole-genome resequencing (WGRS) and bulked segregant analysis (BSA) and relies on the Indel frequencies in extreme bulks. Deployment of Indel-seq approach for identification of candidate genomic regions associated with fusarium wilt (FW) and sterility mosaic disease (SMD) resistance in pigeonpea has identified 16 Indels affecting 26 putative candidate genes. Of these 26 affected putative candidate genes, 24 genes showed effect in the upstream/downstream of the genic region and two genes showed effect in the genes. Validation of these 16 candidate Indels in other FW- and SMD-resistant and FW- and SMD-susceptible genotypes revealed a significant association of five Indels (three for FW and two for SMD resistance). Comparative analysis of Indel-seq with other genetic mapping approaches highlighted the importance of the approach in identification of significant genomic regions associated with target traits. Therefore, the Indel-seq approach can be used for quick and precise identification of candidate genomic regions for any target traits in any crop species.
使用传统作图方法鉴定与目标性状相关的候选基因组区域具有挑战性且耗时。近年来,已开发出多种基于单核苷酸多态性(SNP)的作图方法,并用于鉴定候选/推定的基因组区域。然而,在大多数这些研究中,插入缺失(Indel)在很大程度上被忽视了。为了在目标性状作图中有效利用Indel,我们提出了Indel-seq方法,该方法是全基因组重测序(WGRS)和混合分组分析法(BSA)的结合,并依赖于极端分组中的Indel频率。采用Indel-seq方法鉴定木豆中与枯萎病(FW)和不育花叶病(SMD)抗性相关的候选基因组区域,已鉴定出16个Indel,影响26个推定的候选基因。在这26个受影响的推定候选基因中,24个基因在基因区域的上游/下游显示出效应,两个基因在基因中显示出效应。在其他抗FW和SMD以及感FW和SMD的基因型中对这16个候选Indel进行验证,发现5个Indel(3个与FW抗性相关,2个与SMD抗性相关)存在显著关联。Indel-seq与其他遗传作图方法的比较分析突出了该方法在鉴定与目标性状相关的重要基因组区域中的重要性。因此,Indel-seq方法可用于快速、精确地鉴定任何作物物种中任何目标性状的候选基因组区域。