Identification of genomic regions associated with cereal cyst nematode (Heterodera avenae Woll.) resistance in spring and winter wheat
Uloženo v:
| Název: | Identification of genomic regions associated with cereal cyst nematode (Heterodera avenae Woll.) resistance in spring and winter wheat |
|---|---|
| Autoři: | Chaturvedi, Deepti, Pundir, Saksham, Singh, Vikas Kumar, Kumar, Deepak, Sharma, Rajiv, Röder, Marion, Sharma, Shiveta, Sharma, Shailendra |
| Zdroj: | Sci Rep Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023) Scientific reports, 13(1):5916 |
| Informace o vydavateli: | Springer Science and Business Media LLC, 2023. |
| Rok vydání: | 2023 |
| Témata: | 2. Zero hunger, Edible Grain/genetics, Nematoda, Cysts, Science, Nematoda/genetics, Genomics, Article, Triticum/genetics, Medicine, Animals, Edible Grain, Triticum, Genome-Wide Association Study |
| Popis: | Cereal cyst nematode (CCN) is a major threat to cereal crop production globally including wheat (Triticum aestivum L.). In the present study, single-locus and multi-locus models of Genome-Wide Association Study (GWAS) were used to find marker trait associations (MTAs) against CCN (Heterodera avenae) in wheat. In total, 180 wheat accessions (100 spring and 80 winter types) were screened against H. avenae in two independent years (2018/2019 “Environment 1” and 2019/2020 “Environment 2”) under controlled conditions. A set of 12,908 SNP markers were used to perform the GWAS. Altogether, 11 significant MTAs, with threshold value of −log10 (p-values) ≥ 3.0, were detected using 180 wheat accessions under combined environment (CE). A novel MTA (wsnp_Ex_c53387_56641291) was detected under all environments (E1, E2 and CE) and considered to be stable MTA. Among the identified 11 MTAs, eight were novel and three were co-localized with previously known genes/QTLs/MTAs. In total, 13 putative candidate genes showing differential expression in roots, and known to be involved in plant defense mechanisms were reported. These MTAs could help us to identify resistance alleles from new sources, which could be used to identify wheat varieties with enhanced CCN resistance. |
| Druh dokumentu: | Article Other literature type |
| Jazyk: | English |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/s41598-023-32737-8 |
| Přístupová URL adresa: | https://pubmed.ncbi.nlm.nih.gov/37041155 https://doaj.org/article/9adde264b22343a499f7f81bcc0a291c https://pure.sruc.ac.uk/en/publications/585a21df-247b-41c1-a6d4-46eb7f5153bf https://doi.org/10.1038/s41598-023-32737-8 https://repository.publisso.de/resource/frl:6441349 |
| Rights: | CC BY |
| Přístupové číslo: | edsair.doi.dedup.....c197482c0ed64e932882ece3cbda908f |
| Databáze: | OpenAIRE |
| Abstrakt: | Cereal cyst nematode (CCN) is a major threat to cereal crop production globally including wheat (Triticum aestivum L.). In the present study, single-locus and multi-locus models of Genome-Wide Association Study (GWAS) were used to find marker trait associations (MTAs) against CCN (Heterodera avenae) in wheat. In total, 180 wheat accessions (100 spring and 80 winter types) were screened against H. avenae in two independent years (2018/2019 “Environment 1” and 2019/2020 “Environment 2”) under controlled conditions. A set of 12,908 SNP markers were used to perform the GWAS. Altogether, 11 significant MTAs, with threshold value of −log10 (p-values) ≥ 3.0, were detected using 180 wheat accessions under combined environment (CE). A novel MTA (wsnp_Ex_c53387_56641291) was detected under all environments (E1, E2 and CE) and considered to be stable MTA. Among the identified 11 MTAs, eight were novel and three were co-localized with previously known genes/QTLs/MTAs. In total, 13 putative candidate genes showing differential expression in roots, and known to be involved in plant defense mechanisms were reported. These MTAs could help us to identify resistance alleles from new sources, which could be used to identify wheat varieties with enhanced CCN resistance. |
|---|---|
| ISSN: | 20452322 |
| DOI: | 10.1038/s41598-023-32737-8 |
Full Text Finder
Nájsť tento článok vo Web of Science