Genome-wide selection in cassava

Oliveira, Eder Jorge de; Resende, Marcos Deon Vilela de; Santos, V. da S.; Ferreira, Cláudia Fortes; Oliveira, Gilmara Alvarenga Fachardo; Silva, Maiane Suzarte da; Oliveira, Luciana Alves de; Aguilar-Vildoso, Carlos Ivan

doi:10.1007/s10681-012-0722-0

Cited by 101 publications

(92 citation statements)

References 56 publications

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“…The software Selegen-REML/BLUP has been used internationally (Colombari et al 2013, Oliveira et al 2012, Pedrozo et al 2011, Rosado et al 2010, Dunlop et al 2005, and is a very useful tool for plant breeding. …”

Section: Interaction Between Organismsmentioning

confidence: 99%

Software Selegen-REML/BLUP: a useful tool for plant breeding

Resende

2016

Crop Breed. Appl. Biotechnol.

458

404

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Section: Interaction Between Organismsmentioning

confidence: 99%

Software Selegen-REML/BLUP: a useful tool for plant breeding

Resende

2016

Crop Breed. Appl. Biotechnol.

458

404

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“…Efforts to improve cassava genetically with cutting edge methodologies including transgenic and genomic selection (GS) approaches are underway thanks to new genomic resources (Prochnik et al 2012;ICGMC 2015). Prediction with additive models has recently been evaluated (Oliveira et al 2012;Ly et al 2013) and genomic selection using standard models is currently being tested (http://www.nextgencassava.org). Vegetatively propagated crop (e.g., cassava) breeding can exploit nonadditive genetic effects by identifying superior clones as varieties (Ceballos et al 2015).…”

mentioning

confidence: 99%

Marker-based estimates reveal significant non-additive effects in clonally propagated cassava (Manihot esculenta): implications for the prediction of total genetic value and the selection of varieties

Wolfe

Kulakow

Rabbi

et al. 2015

Preprint

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In clonally propagated crops, nonadditive genetic effects can be effectively exploited by the identification of superior genetic individuals as varieties. Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop that feeds hundreds of millions. We quantified the amount and nature of nonadditive genetic variation for three key traits in a breeding population of cassava from sub-Saharan Africa using additive and nonadditive genome-wide marker-based relationship matrices. We then assessed the accuracy of genomic prediction for total (additive plus nonadditive) genetic value. We confirmed previous findings based on diallel crosses that nonadditive genetic variation is significant for key cassava traits. Specifically, we found that dominance is particularly important for root yield and epistasis contributes strongly to variation in cassava mosaic disease (CMD) resistance. Further, we showed that total genetic value predicted observed phenotypes more accurately than additive only models for root yield but not for dry matter content, which is mostly additive or for CMD resistance, which has high narrow-sense heritability. We address the implication of these results for cassava breeding and put our work in the context of previous results in cassava, and other plant and animal species.

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“…This reduced breeding cycles and the cost of multi-environment testing. Strategies such as GS also allow simultaneous selection for multiple traits through a selection index [52,[116][117][118][119].…”

Section: Molecular Breedingmentioning

confidence: 99%

“…Given the long cycle of breeding, African staple crops such as cassava are set to benefit from GS approaches [117,118,120], where preliminary results have indicated reduced time of breeding cycle and reasonable prediction accuracy in some traits. Various ways of refining the prediction models via repeated phenotypic evaluations are being considered.…”

Section: Molecular Breedingmentioning

confidence: 99%

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Perspectives on the Application of Next-generation Sequencing to the Improvement of Africa’s Staple Food Crops

Gedil¹,

Ferguson²,

Girma³

et al. 2016

Next Generation Sequencing - Advances, Applications and Challenges

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The persistent challenge of insufficient food, unbalanced nutrition, and deteriorating natural resources in the most vulnerable nations, characterized by fast population growth, calls for utilization of innovative technologies to curb constraints of crop production. Enhancing genetic gain by using a multipronged approach that combines conventional and genomic technologies for the development of stress-tolerant varieties with high yield and nutritional quality is necessary. The advent of nextgeneration sequencing (NGS) technologies holds the potential to dramatically impact the crop improvement process. NGS enables whole-genome sequencing (WGS) and re-sequencing, transcriptome sequencing, metagenomics, as well as high-throughput genotyping, which can be applied for genome selection (GS). It can also be applied to diversity analysis, genetic and epigenetic characterization of germplasm and pathogen detection, identification, and elimination. High-throughput phenotyping, integrated data management, and decision support tools form the necessary supporting environment for effective utilization of genome sequence information. It is important that these opportunities for mainstreaming innovative breeding strategies, enabled by cutting-edge "Omics" technologies, are seized in Africa; however, several constraints must be addressed before the benefit of NGS can be fully realized. African breeding programs must have access to high-throughput genotyping facilities, capacity in the application of genome selection and marker-assisted breeding must be built and supported by capacity in genomic analysis and bioinformatics. This chapter demonstrates how interventions with NGS-enabled innovative strategies can be applied to increase genetic gain with insights from the Consortium of International

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Genome-wide selection in cassava

Cited by 101 publications

References 56 publications

Software Selegen-REML/BLUP: a useful tool for plant breeding

Software Selegen-REML/BLUP: a useful tool for plant breeding

Marker-based estimates reveal significant non-additive effects in clonally propagated cassava (Manihot esculenta): implications for the prediction of total genetic value and the selection of varieties

Perspectives on the Application of Next-generation Sequencing to the Improvement of Africa’s Staple Food Crops

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