dc.contributor.author | Stanley, A. |
dc.contributor.author | Menkir, A. |
dc.contributor.author | Agre, P. |
dc.contributor.author | Ifie, B. |
dc.contributor.author | Tongoona, P. |
dc.contributor.author | Unachukwu, N. |
dc.contributor.author | Meseka, S. |
dc.contributor.author | Mengesha Abera, W. |
dc.contributor.author | Gedil, M. |
dc.date.accessioned | 2021-01-22T11:38:56Z |
dc.date.available | 2021-01-22T11:38:56Z |
dc.date.issued | 2020 |
dc.identifier.citation | Stanley, A., Menkir, A., Agre, P., Ifie, B., Tongoona, P., Unachukwu, N., ... & Gedil, M. (2020). Genetic diversity and population structure of maize inbred lines with varying levels of resistance to striga hermonthica using agronomic trait-based and SNP markers. Plants, 9(9), 1223: 1-18. |
dc.identifier.issn | 2223-7747 |
dc.identifier.uri | https://hdl.handle.net/20.500.12478/7017 |
dc.description.abstract | Striga hermonthica is a serious biotic stress limiting maize production in sub-Saharan Africa. The limited information on the patterns of genetic diversity among maize inbred lines derived from source germplasm with mixed genetic backgrounds limits the development of inbred lines, hybrids, and synthetics with durable resistance to S. hermonthica. This study was conducted to assess the level of genetic diversity in a panel of 150 diverse maize inbred lines using agronomic and molecular data and also to infer the population structure among the inbred lines. Ten Striga-resistance-related traits were used for the phenotypic characterization, and 16,735 high-quality single-nucleotide polymorphisms (SNPs), identified by genotyping-by-sequencing (GBS), were used for molecular diversity. The phenotypic and molecular hierarchical cluster analyses grouped the inbred lines into five clusters, respectively. However, the grouping patterns between the phenotypic and molecular hierarchical cluster analyses were inconsistent due to non-overlapping information between the phenotypic and molecular data. The correlation between the phenotypic and molecular diversity matrices was very low (0.001), which is in agreement with the inconsistencies observed between the clusters formed by the phenotypic and molecular diversity analyses. The joint phenotypic and genotypic diversity matrices grouped the inbred lines into three groups based on their reaction patterns to S. hermonthica, and this was able to exploit a broad estimate of the actual diversity among the inbred lines. The joint analysis shows an invaluable insight for measuring genetic diversity in the evaluated materials. The result indicates that wide genetic variability exists among the inbred lines and that the joint diversity analysis can be utilized to reliably assign the inbred lines into heterotic groups and also to enhance the level of resistance to Striga in new maize varieties. |
dc.description.sponsorship | Deutscher Akademischer Austauschdienst |
dc.description.sponsorship | Bill & Melinda Gates Foundation |
dc.format.extent | 1-18 |
dc.language.iso | en |
dc.subject | Genetic Diversity |
dc.subject | Population Structure |
dc.subject | Maize |
dc.subject | Marker Assisted Selection |
dc.subject | Striga Hermonthica |
dc.subject | Subsaharan Africa |
dc.subject | Inbred Lines |
dc.title | Genetic diversity and population structure of maize inbred lines with varying levels of resistance to striga hermonthica using agronomic trait-based and SNP markers |
dc.type | Journal Article |
cg.contributor.crp | Maize |
cg.contributor.crp | Roots, Tubers and Bananas |
cg.contributor.affiliation | University of Ghana |
cg.contributor.affiliation | International Institute of Tropical Agriculture |
cg.coverage.region | Africa |
cg.coverage.region | West Africa |
cg.coverage.country | Nigeria |
cg.coverage.hub | Headquarters and Western Africa Hub |
cg.researchtheme | Biotech and Plant Breeding |
cg.identifier.bibtexciteid | STANLEY:2020 |
cg.isijournal | ISI Journal |
cg.authorship.types | CGIAR and developing country institute |
cg.iitasubject | Agronomy |
cg.iitasubject | Disease Control |
cg.iitasubject | Food Security |
cg.iitasubject | Genetic Improvement |
cg.iitasubject | Maize |
cg.iitasubject | Plant Breeding |
cg.iitasubject | Plant Diseases |
cg.iitasubject | Plant Production |
cg.iitasubject | Smallholder Farmers |
cg.journal | Plants |
cg.notes | Open Access Journal; Published online: 17 Sept 2020 |
cg.accessibilitystatus | Open Access |
cg.reviewstatus | Peer Review |
cg.usagerightslicense | Creative Commons Attribution 4.0 (CC BY 0.0) |
cg.targetaudience | Scientists |
cg.identifier.doi | https://dx.doi.org/10.3390/plants9091223 |
cg.iitaauthor.identifier | Abebe Menkir: 0000-0002-5907-9177 |
cg.iitaauthor.identifier | Paterne AGRE: 0000-0003-1231-2530 |
cg.iitaauthor.identifier | SILVESTRO MESEKA: 0000-0003-1004-2450 |
cg.iitaauthor.identifier | Wende Mengesha: 0000-0002-2239-7323 |
cg.iitaauthor.identifier | Melaku Gedil: 0000-0002-6258-6014 |
cg.futureupdate.required | No |