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Marker-Assisted Selection (MAS): Untapped Potential for Enhancing Food and Nutrition Securities in Sub-Saharan Africa

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Food Security and Safety Volume 2

Abstract

Global food security has raised concerns for the rapidly growing population and extreme weather due to climate change. Conventional plant breeding deployed the current greatly fecund crops, but there must be an increase in the genetic improvement to meet the anticipated future demand. Existing crop breeding techniques and recent technologies could resourcefully be reconnoitered to increase crop improvement in the façade of increasingly perplexing production condition, which is discussed in this chapter. Agriculture is vital in securing millions of people in sub-Saharan Africa, as it has prodigious potential to contribute to the economic development of the region, livelihood improvement through income generation, and enhancing the potential of smallholder farmers and related value chains. Moreover, scientific innovations like MAS offer great potential to drive this envisioned change; decades have passed since this technology was first used in the world, but Africa as a continent with more genetic diversity of crops remains underrepresented. Here, we reviewed a purview on screening methods and patterns of how genetic diversity of available crops in the continent are exploited, since marker-assisted selection and its potential in tackling food and nutritional insecurity as well as climate change cannot be overemphasized. In this chapter, we highlighted potential for applying MAS in the genomic resources available in Africa. We explored the most important methods of plant breeding used with their advantages and limitations. Additionally, the quiescent and consequences for assimilation of hi-tech innovations in genetics and breeding are also explored. Since smallholder farmers are the major beneficiaries, we scrutinized how to guarantee steady and sustainable production of crops in sub-Saharan Africa, thereby producing climate-smart crops in this region.

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References

  • Adekola OF, Oluleye F (2007) Induction of genetic variation in Cowpea (Vigna unguiculata L. Walp.) by gamma irradiation. Asian J Plant Sci 6:869–873

    Article  Google Scholar 

  • Andersen SB (2013) Plant breeding from laboratories to fields. Intech Open Book, Rijeka

    Book  Google Scholar 

  • Andrus CF (1963) Plant breeding systems. Euphytica 12(2):205–228

    Article  Google Scholar 

  • Antoine B, De La Salle TJB, Zakaria D, Zakaria K, Leandre P, Mahamadou S (2016) Inheritance and allelic relationship of resistance to Cowpea aphid-borne mosaic virus (CABMV) in two cowpea genotypes, KVX640 and KVX396-4-5-2D, in Burkina Faso. Int J Curr Microbiol App Sci 5:285–292

    Article  Google Scholar 

  • Atkins PA, Voytas DF (2020) Overcoming bottlenecks in plant gene editing. Curr Opin Plant Biol 54:79–84

    Article  CAS  PubMed  Google Scholar 

  • Atlin GN, Cairns JE, Das B (2017) Rapid breeding and varietal replacement are critical to adaptation of cropping systems in the developing world to climate change. Glob Food Sec 12:31–37

    Article  PubMed  PubMed Central  Google Scholar 

  • Bailey RL, West KP, Black RE (2015) The epidemiology of global micronutrient deficiencies. Ann Nutr Metab 66(Suppl. 2):22–33

    Article  CAS  PubMed  Google Scholar 

  • Batieno BJ, Danquah E, Tignegre JB, Huynh BL, Drabo I, Close TJ, Ofori K, Roberts P, Ouedraogo TJ (2016) Application of marker-assisted backcrossing to improve cowpea (Vignaunguiculata L. Walp) for drought tolerance. J Plant Breed Crop Sci 8(12):273–286

    Article  Google Scholar 

  • Blair MW, Rodnguez LM, Pedraza F, Morales F, Beebe S (2007) Gene mapping of the bean golden yellow mosaic gemini virus resistance gene bgm-l and linkage with potyvuus resistance in common bean (Phaseolus vulgaris L). Theor Appl Genet 114:261–271

    Article  CAS  PubMed  Google Scholar 

  • Blair MW, González LF, Kimani PM, Butare L (2010) Genetic diversity, inter-gene pool introgression and nutritional quality of common beans (Phaseolus vulgaris L.) from Central Africa. Theor Appl Genet 121(2):237–248

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Boukar O, Fatokun CA, Roberts PA, Abberton M, Huynh BL, Close TJ, Kyei-Boahen S, Higgins TJ, Ehlers JD (2015) Cowpea. In: Grain legumes. Springer, New York, pp 219–250

    Chapter  Google Scholar 

  • Boukar O, Belko N, Chamarthi S, Togola A, Batieno J, Owusu E, Fatokun C (2019) Cowpea (Vigna unguiculata): genetics, genomics and breeding. Plant Breed 138(4):415–424

    Article  Google Scholar 

  • Boukar O, Abberton M, Oyatomi O, Togola A, Tripathi L, Fatokun C (2020) Introgression breeding in cowpea [Vigna unguiculata (L.) walp.]. Front Plant Sci 11:567425

    Article  PubMed  PubMed Central  Google Scholar 

  • Brim CA (1966) A modified pedigree method of selection in soybeans 1. Crop Sci 6(2):220

    Article  Google Scholar 

  • Brown DCW, Thorpe TA (1995) Crop improvement through tissue culture. World J Microbiol Biotechnol 11:409–415

    Article  CAS  PubMed  Google Scholar 

  • Chukwu SC, Rafii MY, Ramlee SI (2019) Bacterial leaf blight resistance in rice: a review of conventional breeding to molecular approach. Mol Biol Rep 46(1):1519–1532

    Article  CAS  PubMed  Google Scholar 

  • Cobb JN, Juma RU, Biswas PS, Arbelaez JD, Rutkoski J, Atlin (2019) Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the Breeder’s equation. Theor Appl Genet 132:627–645

    Article  PubMed  PubMed Central  Google Scholar 

  • Collard BC, Beredo JC, Lenaerts B, Mendoza R, Santelices R, Lopena V, Islam MR (2017) Revisiting rice breeding methods evaluating the use of rapid generation advance (RGA) for routine rice breeding. Plant Prod Sci 20(4):337–352

    Article  Google Scholar 

  • Comar A, Bufger P, de Solan B, Baret F, Daumard F, Hanocq J-F (2012) A semi-automatic system for high throughput phenotyping wheat cultivars in-field conditions: description and first results. Funct Plant Biol 39:914–912

    Article  PubMed  Google Scholar 

  • de Oliveira AA, Pastina MM, da Costa Parrella RA, Noda RW, Simeone MLF, Schaffert RE, Margarido GRA (2018) Genomic prediction applied to high-biomass sorghum for bioenergy production. Mol Breed 38(4):1–16

    Article  Google Scholar 

  • Delmer DP (2005) Agriculture in the developing world: connecting innovations in plant research to downstream applications. Proc Natl Acad Sci 102(44):15739–15746

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • do Carmo Oda M, Sediyama T, Matsuo É, Cruz CD, de Barros EG, da Silva Ferreira MF (2015) Phenotypic and molecular traits diversity in soybean launched in forty years of genetic breeding. Agron Sci Biotechnol 1(1):1–1

    Article  Google Scholar 

  • Dong, O. X., & Ronald, P. C. (2019). Genetic engineering for disease resistance in plants: recent progress and future perspectives. Plant Physiol 180(1):26–38

    Google Scholar 

  • Dussle CM, Quint M, Xu ML, Melchinger AE, Lu berstedt T. (2002) Conversion of AFLP fragments tightly linked to SCMV resistance genes Scmv1 and Scmv2 into simple PCR based markers. Theor Appl Genet 105:1190–1195

    Article  CAS  PubMed  Google Scholar 

  • Enviro News Nigeria: Biosafety Agency Drafts Guidelines on Genome Editing (2019). https://www.environewsnigeria.com/biosafety-agency-drafts-guidelines-on-genome-editing

  • Evert RF (2006) Esau’s plant anatomy: meristems, cells, and tissues of the plant body: their structure, function, and development. John Wiley & Sons, Hoboken

    Book  Google Scholar 

  • Fahim M, Dhanapala MP, Senadhira D, Lawrence MJ (1998) Quantitative genetics of rice II. A comparison of the efficiency of four breeding methods. Field Crop Res 55(3):257–266

    Article  Google Scholar 

  • FAOSTAT (2020). http://www.fao.org/faostat/en/#data/QC. Accessed 24 Jan 2020

  • Ferguson ME, Hearne SJ, Close TJ, Wanamaker S, Moskal WA, Town CD, de Villiers EP (2012) Identification, validation and high-throughput genotyping of transcribed gene SNPs in cassava. Theor Appl Genet 124(4):685–695

    Article  CAS  PubMed  Google Scholar 

  • Fernandez-Pozo N, Menda N, Edwards JD, Saha S, Tecle IY, Strickler SR, Mueller LA (2015) The Sol Genomics Network (SGN) from genotype to phenotype to breeding. Nucleic Acids Res 43(D1):D1036–D1041

    Article  CAS  PubMed  Google Scholar 

  • Francia E, Tacconi G, Crosatti C, Barabaschi D, Bulgarelli D, Dall’Aglio E, Vale G (2005) Marker assisted selection in crop plants. Plant Cell Tiss Org Cult 82:317–342

    Article  CAS  Google Scholar 

  • FSIN (2020) Global report on food crises. Available online at: publications 2020-global-report-food-crises. Accessed on 23 Oct 2020

    Google Scholar 

  • Galla SJ, Brown L, Couch-Lewis Y, Cubrinovska I, Eason D, Gooley RM, Hamilton JA et al (2022) The relevance of pedigrees in the conservation genomics era. Mol Ecol 31:41–54

    Article  PubMed  Google Scholar 

  • Garcia-Oliveira AL, Chander S, Ortiz R, Menkir A, Gedil M (2018) Genetic basis and breeding perspectives of grain iron and zinc enrichment in cereals. Front Plant Sci 9:937

    Article  PubMed  PubMed Central  Google Scholar 

  • Gardner CO (1961) An evaluation of effects of mass selection and seed irradiation with thermal neutrons on yield of corn. Crop Sci 1(241):45

    Google Scholar 

  • Gbedevi KM, Boukar O, Ishikawa H, Abe A, Ongom PO, Unachukwu N, Rabbi I, Fatokun C (2021) Genetic diversity and population structure of Cowpea [Vigna unguiculata (L.) Walp.] Germplasm collected from Togo based on DArT markers. Genes 12(9):1451

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • George EF, Hall MA, De Klerk GJ (2008) Micropropagation: uses and methods. In: Plant propagation by tissue culture. Springer, Dordrecht, pp 29–64

    Google Scholar 

  • Germana MA (2011) Anther culture for haploid and doubled haploid production. Plant Cell Tiss Org Cult (PCTOC) 104(3):283–300

    Google Scholar 

  • Girma G, Rabbi I, Olanrewaju A, Alaba O, Kulakow P, Alabi T, Manyong V (2017) A manual for large-scale sample collection, preservation, tracking, DNA extraction, and variety identification analysis

    Google Scholar 

  • Guo X, Wang D, Gordon SG, Helliwell E, Smith T, Berry SA, Dorrance AE (2008) Genetic mapping of QTLs underlying partial resistance to Sclerotinia sclerotiorum in soybean PI 391589A and PI 391589B. Crop Sci 48(3):1129–1139

    Article  Google Scholar 

  • Gupta G, Memon AG, Pandey B, Khan MS, Iqbal MS, Srivastava JK (2021) Colchicine induced mutation in plant for the assessment of morpho-physiological and biochemical parameter anti-inflammatory activity. Open Biotechnol J 15(1):173–182

    Article  CAS  Google Scholar 

  • Hartman GL, McCormick SP, O’donnell K (2019) Trichothecene-producing Fusarium species isolated from soybean roots in Ethiopia and Ghana and their pathogenicity on soybean. Plant Dis 103(8):2070–2075

    Article  CAS  PubMed  Google Scholar 

  • Heffner EL, Lorenz AJ, Jannink JL, Sorrells ME (2010) Plant breeding with genomic selection: gain per unit time and cost. Crop Sci 50(5):1681–1690

    Article  Google Scholar 

  • Huynh TT, Bastien M, Iquira E, Turcotte P, Belzile F (2010) Identification of QTLs associated with partial resistance to white mold in soybean using field-based inoculation. Crop Sci 50(3):969–979

    Article  Google Scholar 

  • International Food Policy Research Institute (2016) 2016 Annual report

    Google Scholar 

  • Jia H, Zhang Y, Orbovi V, Xu J, White FF, Jones JB, Wang N (2017) Genome editing of the disease susceptibility gene CsLOB1 in citrus confers resistance to citrus canker. Plant Biotechnol J 15:817–823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jiang GL (2013) Molecular markers and marker-assisted breeding in plants. In: Plant breeding from laboratories to fields, vol 3. IntechOpen, pp 45–83

    Google Scholar 

  • Kayondo SI, Del Carpio DP, Lozano R, Ozimati A, Wolfe M, Baguma Y, Jannink JL (2018) Genome-wide association mapping and genomic prediction for CBSD resistance in Manihot esculenta. Sci Rep 8(1):1–11

    Article  CAS  Google Scholar 

  • Khatun M, Borphukan B, Alam I, Keya CA, Khan H, Reddy MK, Salimullah M (2022) An improved Agrobacterium mediated transformation and regeneration protocol for successful genetic engineering and genome editing in eggplant. Sci Hortic 293:110716

    Article  CAS  Google Scholar 

  • Kolkman JM, Kelly JD (2003) QTL conferring resistance and avoidance to white mold in common bean. Crop Sci 43(2):539–548

    Article  CAS  Google Scholar 

  • Kretzschmar T, Mbanjo EGN, Magalit GA, Dwiyanti MS, Habib MA, Diaz MG, Yamano T (2018) DNA fingerprinting at farm level maps rice biodiversity across Bangladesh and reveals regional varietal preferences. Sci Rep 8(1):1–12

    Article  CAS  Google Scholar 

  • Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124(3):743–756

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lema MA (2019) Regulatory aspects of gene editing in Argentina. In: Transgenic research, vol 28, no 2. Springer International Publishing, pp 147–150

    Google Scholar 

  • Li X, Han Y, Teng W, Zhang S, Yu K, Poysa V, Li W (2010) Pyramided QTL underlying tolerance to Phytophthora root rot in mega-environments from soybean cultivars ‘Conrad’and ‘Hefeng 25’. Theor Appl Genet 121(4):651–658

    Article  PubMed  Google Scholar 

  • Li H, Rasheed A, Hickey LT, He Z (2018) Fast-forwarding genetic gain. Trends Plant Sci 23:184–186

    Article  CAS  PubMed  Google Scholar 

  • Liang Z, Chen K, Li T, Zhang Y, Wang Y, Zhao Q (2017) Efficient DNA-free genome editing of bread wheat using CRISPR/Cas9 ribonucleoprotein complexes. Nat Commun 8:14261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mackelprang R, Lemaux PG (2020) Genetic engineering and editing of plants: an analysis of new and persisting questions. Annu Rev Plant Biol 71:659–687

    Article  CAS  PubMed  Google Scholar 

  • Mackill DJ, Collard BCY, Atlin GN, Ismail AM, Sarkarung S (2013) Overview of and historical perspectives on the EIRLSBN. In: EIRLSBN: Twenty years of achievements in rice breeding (ed. B. C. Y. Collard, A. M. Ismail and B. Hardy), pp. 1–6. International Rice Research Institute, Los Baños

    Google Scholar 

  • Makhotenko AV, Khromov AV, Snigir EA, Makarova SS, Makarov VV, Suprunova TP, Taliansky ME (2019) Functional analysis of coilin in virus resistance and stress tolerance of potato Solanum tuberosum using CRISPR-Cas9 editing. In: Doklady biochemistry and biophysics, vol 484, no 1. Pleiades Publishing, pp 88–91

    Google Scholar 

  • Malek MA, Emon RM, Khatun MK, Bhuiyan MSH (2022) Binasoybean-6: a high yielding mutant soybean variety developed through sustainable mutation breeding. Legume Res 1:6

    Google Scholar 

  • Malnoy M, Viola R, Jung M-H, Koo O-J, Kim S, Kim JS, Velasco R, Kanchiswamy CN (2016) DNA-free genetically edited grapevine and apple protoplast using CRISPR/Cas9 ribonucleoproteins. Front Plant Sci 7:1904

    Article  PubMed  PubMed Central  Google Scholar 

  • Metwally E, Sharshar M, Masoud A, Masry A, Fiad A, Kilian B, Rakha M (2021) Development of high yielding cowpea [Vigna unguiculata (L.) Walp.] lines with improved quality seeds through mutation and pedigree selection methods. Horticulturae 7(9):271

    Article  Google Scholar 

  • Meuwissen T, Goddard M (2010) Accurate prediction of genetic values for complex traits by whole-genome resequencing. Genetics 185(2):623–631

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Miklas PN, Fourie D, Trapp J, Davis J, Myers JR (2014) New loci including Pse-6 conferring resistance to halo bacterial blight on chromosome Pv04 in common bean. Crop Sci 54(5):2099–2108

    Article  Google Scholar 

  • Mittler R, Blumwald E (2010) Genetic engineering for modern agriculture: challenges and perspectives. Annu Rev Plant Biol 61:443–462

    Article  CAS  PubMed  Google Scholar 

  • Mohamed A, Ali R, Elhassan O, Suliman E, Mugoya C, Masiga CW, Elhusien A, Hash CT (2014) First products of DNA marker-assisted selection in sorghum released for cultivation by farmers in sub-saharan Africa. J Plant Sci Mol Breed 3(3):1–10

    Google Scholar 

  • Mohan M, Nair S, Bhagwat A, Krishna TG, Yano M, Bhatia CR, Sasaki T (1997) Genome mapping, molecular markers and marker-assisted selection in crop plants. Mol Breed 3:87–103

    Article  CAS  Google Scholar 

  • Mulugo L, Kyazze FB, Kibwika P, Omondi BA, Kikulwe EM (2020) Seed security factors driving farmer decisions on uptake of tissue culture banana seed in Central Uganda. Sustainability 12(23):10223

    Article  Google Scholar 

  • Murdock LI, Coulibaly O, Higgins TJ, Hoesung JE, Ishiya M (2008) Cowpea. In: Kole C, Hall TC (eds) Compendium of transgenic crop plants: transgenic legume grains and forages. Wiley-Blackwell, Hoboken, pp 23–56

    Chapter  Google Scholar 

  • Nadakuduti SS, Buell CR, Voytas DF, Starker CG, Douches DS (2018) Genome editing for crop improvement–applications in clonally propagated polyploids with a focus on potato (Solanum tuberosum L.). Front Plant Sci 9:1607

    Article  PubMed  PubMed Central  Google Scholar 

  • Niazian M, Niedbała G (2020) Machine learning for plant breeding and biotechnology. Agriculture 10(10):436

    Article  CAS  Google Scholar 

  • Nkouaya Mbanjo EG, Rabbi IY, Ferguson ME, Kayondo SI, Eng NH, Tripathi L, Egesi C (2020) Technological innovations for improving cassava production in Sub Saharan Africa. Front Genet 11:1829

    Google Scholar 

  • Office of the Gene Technology Regulator (OGTR) (2018) Technical Review of the Gene Technology Regulations 2001–2017-18 Amendment Proposals Consultation

    Google Scholar 

  • Ojiewo C, Monyo E, Desmae H, Boukar O, Mukankusi-Mugisha C, Thudi M, Varshney RK (2020) Genomics, genetics and breeding of tropical legumes for better livelihoods of smallholder farmers. Plant Breed 138(4):487–499

    Article  Google Scholar 

  • Ojuederie OB, Ogunmoyela O, Omidiji O, Oyedeji SI (2011) Agricultural biotechnology the panacea for food security in Sub-Saharan Africa. Libyan Agric Res Cent J Int 2(3):123–132

    Google Scholar 

  • Okogbenin E, Egesi CN, Olasanmi B, Ogundapo O, Kahya S, Hurtado P, Fregene M (2012) Molecular marker analysis and validation of resistance to cassava mosaic disease in elite cassava genotypes in Nigeria. Crop Sci 52(6):2576–2586

    Article  CAS  Google Scholar 

  • Olasanmi B, Kyallo M, Yao N (2021) Marker-assisted selection complements phenotypic screening at seedling stage to identify cassava mosaic disease-resistant genotypes in African cassava populations. Sci Rep 11(1):1–8

    Article  Google Scholar 

  • Ongom PO, Fatokun C, Togola A, Salvo S, Oyebode OG, Ahmad MS, Jockson ID, Bala G, Boukar O (2021) Molecular fingerprinting and hybridity authentication in cowpea using single nucleotide polymorphism based Kompetitive Allele-specific PCR assay. Front Plant Sci 12:734117

    Article  PubMed  PubMed Central  Google Scholar 

  • Organization for Economic Cooperation and Development (OECD) (2019) Conference on genome editing: applications in agriculture. Paris. http://www.oecd.org/environment/genome-editing-agriculture

  • Ortiz-Andrade RR, Garcia-Jimenez S, Castillo-Espana P, Ramirez-Avila G, Villalobos-Molina R, Estrada-Soto S (2007) α-Glucosidase inhibitory activity of the methanolic extract from Tournefortia hartwegiana: an anti-hyperglycemic agent. J Ethnopharmacol 109(1):48–53

    Article  CAS  PubMed  Google Scholar 

  • Patella A, Scariolo F, Palumbo F, Barcaccia G (2019) Genetic structure of cultivated varieties of radicchio (Cichorium intybus l.): a comparison between f1 hybrids and synthetics. Plants 8(7):213

    Article  CAS  PubMed Central  Google Scholar 

  • Patzoldt ME, Grau CR, Stephens PA, Kurtzweil NC, Carlson SR, Diers BW (2005) Localization of a quantitative trait locus providing brown stem rot resistance in the soybean cultivar Bell. Crop Sci 45(4):1241–1248

    Article  CAS  Google Scholar 

  • Phillips GC, Garda M (2019) Plant tissue culture media and practices: an overview. In Vitro Cell Dev Biol Plant 55(3):242–257

    Article  Google Scholar 

  • Pierik RLM (1991) Commercial aspects of micropropagation. In: Horticulture—new technologies and applications. Springer, Dordrecht, pp 141–153

    Chapter  Google Scholar 

  • Rabbi IY, Kayondo SI, Bauchet G, Yusuf M, Aghogho CI, Ogunpaimo K (2020) Genome-wide association analysis reveals new insights into the genetic architecture of defensive, agro-morphological and quality-related traits in cassava. Plant Mol Biol 30:20

    Google Scholar 

  • Rafalski A (2002) Applications of single nucleotide polymorphisms in crop genetics. Curr Opin Plant Biol 5(2):94–100

    Article  CAS  PubMed  Google Scholar 

  • Rajsic P, Weersink A, Navabi A, Pauls KP (2016) Economics of genomic selection: the role of prediction accuracy and relative genotyping costs. Euphytica 210(2):259–276

    Article  Google Scholar 

  • Razzaq A, Saleem F, Kanwal M, Mustafa G, Yousaf S, Imran Arshad HM, ... & Joyia FA (2019) Modern trends in plant genome editing: an inclusive review of the CRISPR/Cas9 toolbox. Int J Mol Sci 20(16):4045

    Article  CAS  PubMed Central  Google Scholar 

  • Ruane J, Sonnino A (2007) Marker-assisted selection as a tool for genetic improvement of crops, livestock, forestry and fish in developing countries: an overview of the issues. In: Marker-assisted selection-current status and future perspectives in crops, livestock, forestry and fish. Food and Agriculture Organization of the United Nations (FAO), Rome, pp 3–13

    Google Scholar 

  • Ruprecht C, Lohaus R, Vanneste K, Mutwil M, Nikoloski Z, Van de Peer Y, Persson S (2017) Revisiting ancestral polyploidy in plants. Sci Adv 3(7):e16031

    Article  Google Scholar 

  • Salifou M, Tignegre JBLS, Togoona P, Offei S, OFori K, Danquah E (2016) Introgression of Striga resistant gene into farmers preferred cowpea varieties in Niger. Int J Plant Breed Genet 3(6):2333–2240

    Google Scholar 

  • Santantonio N, Atanda SA, Beyene Y, Varshney RK, Olsen M, Jones E, Robbins KR (2020) Strategies for effective use of genomic information in crop breeding programs serving Africa and South Asia. Front Plant Sci 11:353

    Article  PubMed  PubMed Central  Google Scholar 

  • Shaibu AS, Miko ZL, Ajeigbe HA, Mohammed SG, Usman A, Muhammad MS, Umar ML, Ahmed HO, Adnan AA, Sneller C (2021) Genome-wide detection of markers associated with early leaf spot and pod weight in groundnut using SNP and DArT markers. J Crop Improv 35(4):522–535

    Article  CAS  Google Scholar 

  • Shen X, Guo W, Zhu X, Yuan Y, John ZY, Kohel RJ, Zhang T (2005) Molecular mapping of QTLs for fiber qualities in three diverse lines in Upland cotton using SSR markers. Mol Breed 15(2):169–181

    Article  CAS  Google Scholar 

  • Shi A, Chen P, Li D, Zheng C, Zhang B, Hou A (2009) Pyramiding multiple genes for resistance to soybean mosaic virus m soybean using molecular markers. Mol Breed 23:113–124

    Article  CAS  Google Scholar 

  • Smyth SJ (2017) Canadian regulatory perspectives on genome engineered crops. GM Crops Food 8(1):35–43

    Article  PubMed  Google Scholar 

  • Sobda G, Boukar O, Tongoona PB, Ayertey J, Offei KS (2017) Quantitative trait loci (QTL) for cowpea resistance to flower bud thrips (Megalurothrips sjostedti Trybom). Int J Plant Breed Genet 4(6):292–299

    Google Scholar 

  • Somo M, Jannink JL (2020) Incorporating selfing to purge deleterious alleles in a cassava genomic selection program. BioRxiv. https://doi.org/10.1101/2020.04.04.025841

  • Sonnino A, Carena MJ, Guimarães EP, Baumung R, Pilling D, Rischkowsky B (2007) An assessment of the use of molecular markers in developing countries. Marker-assisted selection: Current status and future perspectives in crops, livestock, forestry, and fish. Food and Agriculture Organization of the United Nations, Rome, 15–26

    Google Scholar 

  • Stam P (1995) Marker-assisted breeding. Biometrics in plant breeding: applications of molecular markers. In: Proc. 9th Mtg. EUCARPIA section on biometrics in plant breeding. CPRO-DLO, Wageningen, pp 32–44

    Google Scholar 

  • Stebbins GL (1980) Polyploidy in plants: unsolved problems and prospects. In: Polyploidy. Springer, Boston, pp 495–520

    Chapter  Google Scholar 

  • Tate JA, Soltis DE, Sostis PS (2005) Polyploidy in plants. In: The evolution of the genome. Academic Press, pp 371–426

    Chapter  Google Scholar 

  • Tester M, Langridge P (2010) Breeding technologies to increase crop production in a changing world. Science 327(5967):818–822

    Article  CAS  PubMed  Google Scholar 

  • Thompson AL, Thorp KR, Conley MM, Roybal M, Moller D, Long JC (2020) A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system. Plant Methods 16(1):1–13

    Article  Google Scholar 

  • Torres LG, Vilela de Resende MD, Azevedo CF, Fonseca e Silva F, de Oliveira EJ (2019) Genomic selection for productive traits in biparental cassava breeding populations. PLoS One 14(7):e0220245

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Tripathi L, Ntui VO, Tripathi JN (2020) CRISPR/Cas9-based genome editing of banana for disease resistance. Curr Opin Plant Biol 56:118–126

    Article  CAS  PubMed  Google Scholar 

  • Trushar Shah (2019) Breeding management system training at International Institute of Tropical Agriculture, Kano Station

    Google Scholar 

  • Turyagyenda LF, Kizito EB, Ferguson ME, Baguma Y, Harvey JW, Gibson P, Osiru DSO (2012) Genetic diversity among farmer-preferred cassava landraces in Uganda. Afr Crop Sci J 20(1)

    Google Scholar 

  • van Harten AM (1998) Mutation breeding: theory and practical applications. Cambridge University Press, Cambridge

    Google Scholar 

  • Vikas P, Borcherding N, Zhang W (2018) The clinical promise of immunotherapy in triple-negative breast cancer. Cancer Manag Res 10:6823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Voss-Fels KP, Stahl A, Hickey LT (2019) Q & A: modern crop breeding for future food security. BMC Biol 17(1):1–7

    Article  Google Scholar 

  • Wang H, Waller L, Tripathy S, St. Martin SK, Zhou L, Krampis K, Dorrance AE (2010) Analysis of genes underlying soybean quantitative trait loci conferring partial resistance to Phytophthora sojae. Plant Genome 3(1):23–40

    Article  CAS  Google Scholar 

  • Watson A, Ghosh S, Williams MJ, Cuddy WS, Simmonds J, Rey MD, Hickey LT (2018) Speed breeding is a powerful tool to accelerate crop research and breeding. Nat Plants 4(1):23–29

    Article  PubMed  Google Scholar 

  • Wight AJ (2018) Strict EU ruling on gene-edited crops squeezes science. Nature 563(7729):15–16

    Article  CAS  PubMed  Google Scholar 

  • Wolfe MD, Del Carpio DP, Alabi O, Ezenwaka LC, Ikeogu UN, Kayondo IS, Jannink JL (2017) Prospects for genomic selection in cassava breeding. Plant Genome 10(3). https://doi.org/10.3835/plantgenome2017.03.0015

  • Yohannes T, Weldetsion M, Abraha N, Manyasa EO (2015) Combine selection for earliness and yield in pedigree developed sorghum (Sorghum bicolor L. Moench) progenies in Eritrea. Int J Plant Breed Genet 3(1):1–8

    Google Scholar 

  • Yonis BO, Del Carpio DP, Wolfe M, Jannink JL, Kulakow P, Rabbi I (2020) Improving root characterisation for genomic prediction in cassava. Sci Rep 10(1):1–12

    Article  Google Scholar 

  • Zhang T, Yuan Y, Yu J, Guo W, Kohel RJ (2003) Molecular tagging of a major QTL for fiber strength in Upland cotton and its marker-assisted selection. Theor Appl Genet 106(2):262–268

    Article  CAS  PubMed  Google Scholar 

  • Zhou PH, Tan YF, He YQ, Xu CG, Zhang Q (2003) Simultaneous improvement for four quality traits of Zhenshan 97, an elite parent of hybrid rice, by molecular marker-assisted selection. Theor Appl Genet 106:326–331

    Article  CAS  PubMed  Google Scholar 

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Authors’ Contribution

AWM apprehended this review and drafted the manuscript. OB and SG edited the document. MSA and AT conscripted a section of the document. OPO and UML provided critical edits. All authors did approval of submission and contribution.

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The authors declare no conflict of interest.

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Correspondence to Wajiha Mu’az Abdullahi .

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Mu’az Abdullahi, W. et al. (2023). Marker-Assisted Selection (MAS): Untapped Potential for Enhancing Food and Nutrition Securities in Sub-Saharan Africa. In: Babalola, O.O., Ayangbenro, A.S., Ojuederie, O.B. (eds) Food Security and Safety Volume 2. Springer, Cham. https://doi.org/10.1007/978-3-031-09614-3_13

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