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DC Field | Value | Language |
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dc.contributor.author | Daware, Anurag | - |
dc.contributor.author | Parida, Swarup K. | - |
dc.contributor.author | Tyagi, Akhilesh K. | - |
dc.date.accessioned | 2019-09-23T10:28:57Z | - |
dc.date.available | 2019-09-23T10:28:57Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Methods in Molecular Biology, 2072: 15-25 | en_US |
dc.identifier.isbn | 978-1-4939-9865-4 | - |
dc.identifier.uri | http://223.31.159.10:8080/jspui/handle/123456789/987 | - |
dc.description | Accepted date: 21 September 2019 | en_US |
dc.description.abstract | Identification of genetic basis for important agronomic traits is essential for marker-assisted crop improvement. Linkage mapping is one of the most popular approaches utilized for identification of major quantitative trait loci (QTLs) governing important agronomic traits in cereals. However, the identified QTLs usually span large genomic intervals and very few of these are subsequently fine mapped to single major effect gene. This hinders application of these QTLs in marker-aided breeding and crop genetic enhancement. On the contrary, association mapping, another popular approach for identification of QTLs, provides very high resolution but suffers from high level of false positives. Joint linkage-association analysis provides a way to combine advantages and avoid the pitfalls associated with both these methods. In this context, we recently developed MetaQTL specific regional association analysis and demonstrated its utility to rapidly narrow down previously identified QTL intervals to few candidate genes. Here, we describe the detailed step-by-step guide for performing MetaQTL specific regional association analysis to identify important genomic regions and underlying potential major effect genes governing traits of agronomic importance in cereals. | en_US |
dc.description.sponsorship | The work in lab is supported by grants from DBT and SERB, Government of India. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature Publishing AG | en_US |
dc.subject | Association mapping | en_US |
dc.subject | Fine mapping | en_US |
dc.subject | Linkage mapping | en_US |
dc.subject | MetaQTL | en_US |
dc.subject | QTL | en_US |
dc.title | Integrated genomic strategies for cereal genetic enhancement: combining QTL and association mapping | en_US |
dc.type | Article | en_US |
dc.identifier.officialurl | https://link.springer.com/protocol/10.1007%2F978-1-4939-9865-4_3 | en_US |
dc.identifier.doi | https://doi.org/10.1007/978-1-4939-9865-4_3 | en_US |
Appears in Collections: | Institutional Publications |
Files in This Item:
File | Description | Size | Format | |
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Parida SK_2020_2.pdf Restricted Access | 6.62 MB | Adobe PDF | View/Open Request a copy |
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