dc.contributor.author | Gedil, M. |
dc.contributor.author | Ferguson, M. |
dc.contributor.author | Girma Tessema, G. |
dc.contributor.author | Gisel, A. |
dc.contributor.author | Stavolone, L. |
dc.contributor.author | Rabbi, Ismail Y |
dc.date.accessioned | 2019-12-04T11:04:36Z |
dc.date.available | 2019-12-04T11:04:36Z |
dc.date.issued | 2016-01-14 |
dc.identifier.citation | Gedil, M., Ferguson, M., Girma Tessema, G., Gisel, A., Stavolone, L. & Rabbi, I. (2016). Perspectives on the application of next-generation sequencing to the improvement of Africa’s staple food crops. In J.K. Kulski, Next generation sequencing - advances, applications and challenges(287-321). Croatia: Intech |
dc.identifier.isbn | 978-953-51-2240-1 |
dc.identifier.uri | https://hdl.handle.net/20.500.12478/1465 |
dc.description.abstract | 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 next-generation 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 Agricultural Research (CGIAR) in general and the International Institute of Tropical Agriculture (IITA) in particular. |
dc.format.extent | 287-321 |
dc.language.iso | en |
dc.subject | Food Crops |
dc.subject | Nutrition |
dc.subject | Plant Breeding |
dc.subject | Next-Generation Sequencing |
dc.subject | Genome Selection |
dc.subject | Developing Countries |
dc.subject | Food Security |
dc.subject | Bioinformatics |
dc.subject | Dna |
dc.title | perspectives on the application of next generation sequencing to the improvement of Africa's staple food crops |
dc.type | Book Chapter |
dc.description.version | Peer Review |
cg.contributor.crp | Agriculture for Nutrition and Health |
cg.contributor.crp | Climate Change, Agriculture and Food Security |
cg.contributor.affiliation | International Institute of Tropical Agriculture |
cg.contributor.affiliation | Institute for Biomedical Technologies, Italy |
cg.contributor.affiliation | Institute for Sustainable Plant Protection, Italy |
cg.coverage.region | Africa |
cg.coverage.region | West Africa |
cg.coverage.country | Nigeria |
cg.researchtheme | BIOTECH & PLANT BREEDING |
cg.researchtheme | NUTRITION & HUMAN HEALTH |
cg.authorship.types | CGIAR and advanced research institute |
cg.iitasubject | Food Security |
cg.iitasubject | Nutrition |
cg.iitasubject | Plant Breeding |
cg.iitasubject | Plant Genetic Resources |
cg.howpublished | Formally Published |
cg.accessibilitystatus | Open Access |
local.dspaceid | 80372 |
cg.targetaudience | Scientists |
cg.identifier.doi | https://dx.doi.org/10.5772/61665 |