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Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection
Cassava (Manihot esculenta Crantz) is a major source of dietary carbohydrates for >700 million people globally. However, its long breeding cycle has slowed the rate of genetic gain for target traits. This study aimed to asses genetic variation, the level of inbreeding, and trait correlations in g...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Crop Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680944/ https://www.ncbi.nlm.nih.gov/pubmed/33343017 http://dx.doi.org/10.2135/cropsci2018.01.0060 |
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author | Ozimati, Alfred Kawuki, Robert Esuma, Williams Kayondo, Siraj I Pariyo, Anthony Wolfe, Marnin Jannink, Jean-Luc |
author_facet | Ozimati, Alfred Kawuki, Robert Esuma, Williams Kayondo, Siraj I Pariyo, Anthony Wolfe, Marnin Jannink, Jean-Luc |
author_sort | Ozimati, Alfred |
collection | PubMed |
description | Cassava (Manihot esculenta Crantz) is a major source of dietary carbohydrates for >700 million people globally. However, its long breeding cycle has slowed the rate of genetic gain for target traits. This study aimed to asses genetic variation, the level of inbreeding, and trait correlations in genomic selection breeding cycles. We used phenotypic and genotypic data from the National Crops Resources Research Institute (NaCRRI) foundation population (Cycle 0, C(0)) and the progeny (Cycle 1, C(1)) derived from crosses of 100 selected C0 clones as progenitors, both to evaluate and optimize genomic selection. The highest broad-sense heritability (H(2) = 0.95) and narrow-sense heritability (h(2) = 0.81) were recorded for cassava mosaic disease severity and the lowest for root weight per plot (H(2) = 0.06 and h(2) = 0.00). We observed the highest genetic correlation (r(g)= 0.80) between cassava brown streak disease root incidence measured at seedling and clonal stages of evaluation, suggesting the usefulness of seedling data in predicting clonal performance for cassava brown streak root necrosis. Similarly, high genetic correlations were observed between cassava brown streak disease severity (r(g)= 0.83) scored at 3 and 6 mo after planting (MAP) and cassava mosaic disease, scored at 3 and 6 MAP (r(g)= 0.95), indicating that data obtained on these two diseases at 6 MAP would suffice. Population differentiation between C(0) and C(1) was not well defined, implying that the 100 selected progenitors of C(1) captured the diversity in the C(0). Overall, genetic gain for most traits were observed from C(0) to C(1). |
format | Online Article Text |
id | pubmed-7680944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Crop Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76809442020-12-18 Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection Ozimati, Alfred Kawuki, Robert Esuma, Williams Kayondo, Siraj I Pariyo, Anthony Wolfe, Marnin Jannink, Jean-Luc Crop Sci Research Cassava (Manihot esculenta Crantz) is a major source of dietary carbohydrates for >700 million people globally. However, its long breeding cycle has slowed the rate of genetic gain for target traits. This study aimed to asses genetic variation, the level of inbreeding, and trait correlations in genomic selection breeding cycles. We used phenotypic and genotypic data from the National Crops Resources Research Institute (NaCRRI) foundation population (Cycle 0, C(0)) and the progeny (Cycle 1, C(1)) derived from crosses of 100 selected C0 clones as progenitors, both to evaluate and optimize genomic selection. The highest broad-sense heritability (H(2) = 0.95) and narrow-sense heritability (h(2) = 0.81) were recorded for cassava mosaic disease severity and the lowest for root weight per plot (H(2) = 0.06 and h(2) = 0.00). We observed the highest genetic correlation (r(g)= 0.80) between cassava brown streak disease root incidence measured at seedling and clonal stages of evaluation, suggesting the usefulness of seedling data in predicting clonal performance for cassava brown streak root necrosis. Similarly, high genetic correlations were observed between cassava brown streak disease severity (r(g)= 0.83) scored at 3 and 6 mo after planting (MAP) and cassava mosaic disease, scored at 3 and 6 MAP (r(g)= 0.95), indicating that data obtained on these two diseases at 6 MAP would suffice. Population differentiation between C(0) and C(1) was not well defined, implying that the 100 selected progenitors of C(1) captured the diversity in the C(0). Overall, genetic gain for most traits were observed from C(0) to C(1). Crop Science 2019-01-24 2019 /pmc/articles/PMC7680944/ /pubmed/33343017 http://dx.doi.org/10.2135/cropsci2018.01.0060 Text en © Crop Science Society of America http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Ozimati, Alfred Kawuki, Robert Esuma, Williams Kayondo, Siraj I Pariyo, Anthony Wolfe, Marnin Jannink, Jean-Luc Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection |
title | Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection |
title_full | Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection |
title_fullStr | Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection |
title_full_unstemmed | Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection |
title_short | Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection |
title_sort | genetic variation and trait correlations in an east african cassava breeding population for genomic selection |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680944/ https://www.ncbi.nlm.nih.gov/pubmed/33343017 http://dx.doi.org/10.2135/cropsci2018.01.0060 |
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