Association analysis for resistance to Striga hermonthica in diverse tropical maize inbred lines
Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for S...
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Published in | Scientific reports Vol. 11; no. 1; p. 24193 |
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Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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Nature Publishing Group UK
17.12.2021
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Abstract | Striga hermonthica
is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe
Striga
infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for
Striga
management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling
S. hermonthica
resistance and mining of relevant candidate genes will expedite the improvement of
Striga
resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under
Striga
infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of
Striga
damage ratings, emerged
Striga
plants and grain yield, hereafter referred to as
Striga
resistance-related traits, were high under
Striga
infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three
Striga
resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low
Striga
damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for
Striga
resistance breeding in maize. |
---|---|
AbstractList | Abstract Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize. Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize. Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers' lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize. Abstract Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize. |
ArticleNumber | 24193 |
Author | Mengesha, W. A. Menkir, A. Bossey, B. Tongoona, P. B. Oladejo, O. Stanley, A. E. Kwadwo, O. Gedil, M. Paterne, A. A. Meseka, S. Ifie, B. Unachukwu, N. N. Sneller, C. |
Author_xml | – sequence: 1 givenname: A. E. surname: Stanley fullname: Stanley, A. E. organization: West Africa Centre for Crop Improvement, University of Ghana, International Institute of Tropical Agriculture – sequence: 2 givenname: A. surname: Menkir fullname: Menkir, A. email: a.menkir@cgiar.org organization: International Institute of Tropical Agriculture – sequence: 3 givenname: B. surname: Ifie fullname: Ifie, B. organization: West Africa Centre for Crop Improvement, University of Ghana – sequence: 4 givenname: A. A. surname: Paterne fullname: Paterne, A. A. organization: International Institute of Tropical Agriculture – sequence: 5 givenname: N. N. surname: Unachukwu fullname: Unachukwu, N. N. organization: International Institute of Tropical Agriculture – sequence: 6 givenname: S. surname: Meseka fullname: Meseka, S. organization: International Institute of Tropical Agriculture – sequence: 7 givenname: W. A. surname: Mengesha fullname: Mengesha, W. A. organization: International Institute of Tropical Agriculture – sequence: 8 givenname: B. surname: Bossey fullname: Bossey, B. organization: International Institute of Tropical Agriculture – sequence: 9 givenname: O. surname: Kwadwo fullname: Kwadwo, O. organization: West Africa Centre for Crop Improvement, University of Ghana – sequence: 10 givenname: P. B. surname: Tongoona fullname: Tongoona, P. B. organization: West Africa Centre for Crop Improvement, University of Ghana – sequence: 11 givenname: O. surname: Oladejo fullname: Oladejo, O. organization: International Institute of Tropical Agriculture – sequence: 12 givenname: C. surname: Sneller fullname: Sneller, C. organization: Ohio Agriculture Research and Development Center, Ohio State University – sequence: 13 givenname: M. surname: Gedil fullname: Gedil, M. organization: International Institute of Tropical Agriculture |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34921181$$D View this record in MEDLINE/PubMed |
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Snippet | Striga hermonthica
is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe... Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe... Abstract Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under... Abstract Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under... |
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SubjectTerms | 631/208 631/449 Alleles Association analysis Corn Crop yield Disease resistance Disease Resistance - genetics Edible Grain - genetics Genetic Variation Genome-wide association studies Genome-Wide Association Study Genomes Genotype Genotyping Heritability Host plants Humanities and Social Sciences Inbreeding multidisciplinary Nucleotides Parasitic plants Phenotypic variations Plant breeding Plant Diseases - genetics Plant growth Plant resistance Polymorphism, Single Nucleotide Science Science (multidisciplinary) Single-nucleotide polymorphism Striga Striga - genetics Striga hermonthica Zea mays - genetics |
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Title | Association analysis for resistance to Striga hermonthica in diverse tropical maize inbred lines |
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