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dc.creatorKumar, Sandeep
dc.creatorSaini, Dinesh Kumar
dc.creatorJan, Farkhandah
dc.creatorJan, Sofora
dc.creatorTahir, Mohd
dc.creatorĐalović, Ivica
dc.creatorLatković, Dragana
dc.creatorKhan, Mohd Anwar
dc.creatorKuma, Sundeep
dc.creatorVikas, V. K.
dc.creatorKumar, Upendra
dc.creatorKumar, Sundip
dc.creatorDhaka, Narendra Singh
dc.creatorDhankher, Om Parkash
dc.creatorRustgi, Sachin
dc.creatorMir, Reyazul Rouf
dc.date.accessioned2023-05-16T08:02:31Z
dc.date.available2023-05-16T08:02:31Z
dc.date.issued2023
dc.identifier.issn1471-2164
dc.identifier.urihttp://fiver.ifvcns.rs/handle/123456789/3562
dc.description.abstractYellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker–trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of developmentsr
dc.language.isoensr
dc.publisherSpringer Naturesr
dc.rightsopenAccesssr
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceBMC Genomicssr
dc.subjectstripe rustsr
dc.subjectmeta-analysissr
dc.subjectconsensus mapsr
dc.subjectMQTLsr
dc.subjectcandidate genessr
dc.titleComprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheatsr
dc.typearticlesr
dc.rights.licenseBYsr
dc.citation.rankM21~
dc.citation.spage259
dc.citation.volume24
dc.identifier.doi10.1186/s12864-023-09336-y
dc.identifier.fulltexthttp://fiver.ifvcns.rs/bitstream/id/9499/bitstream_9499.pdf
dc.identifier.scopus2-s2.0-85159739039
dc.type.versionpublishedVersionsr


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