Genetic diversity is the foundation of any crop improvement programme; therefore, breeders routinely assess the genetic diversity in ﬁeld crops via different marker techniques. In Africa, biotic and abiotic stresses continue to challenge crop production throughout the continent. This is particularly evident under the current climatic conditions. At IITA, different molecular approaches are being deployed to tackle these limitations in important crops such as maize and cowpea. In maize, genetic diversity in extra-early to early and intermediate to late maturing maize inbred panels is being assessed with molecular markers which may further facilitates breeding decisions. Advances in genomics have led to the identiﬁcation of numerous DNA markers in maize during the last few decades, including thousands of mapped microsatellite or simple sequence repeat (SSR) markers, and more recently, single nucleotide polymorphisms (SNPs) and insertion-deletion (InDel) markers. In addition to the SSRs and SNPs, a large number of genes controlling various aspects of plant development, biotic and abiotic stress resistance, quality characters, etc. have been cloned and characterized in maize, and these are excellent assets for molecular marker-assisted breeding carried out at IITA.
In the IITA maize improvement program (MIP), molecular markers have been effectively utilized in recurrent selection and composite population characterization. As mentioned by Dr. Abebe Menkir, marker-aided diversity analysis was found to be a useful tool for efficiently developing improved reciprocal composites that could serve as sources of new and divergent parents for developing productive hybrids, in addition to the technique of introgressing novel alleles for broadening and diversifying the genetic base of adapted germplasm. Both SSR and SNP in-house assays are also being used by IITA to verify crosses before selfing them for mapping population development and this saves time and resources. Furthermore, one of the applications of molecular markers in MIP is in the classification of early maturing maize lines into different heterotic groups. The grouping of early white quality protein maize lines using the SNP-based method was compared with that using general combining ability-based methods and found to be more efficient and cost effective. Various germplasm development strategies have also been used within the MIP to broaden the gene pool of maize. For example, DNA-based genetic characterization and diversity analyses have proved to be valuable methods and tools for decision making for maximizing the utilization of the main classes of genetic resources, namely wild relatives of crops, landraces, and improved elite lines. Similarly, the effect of these functional gene markers on the accumulation of Provitamin A in tropical maize has been investigated at IITA in which polymerase chain reaction (PCR)-based DNA markers developed from three key genes—PSY1, lcyE, and crtRB1—were assessed for their effectiveness in marker-assisted selection for PVA content in 130 tropical maize lines.
My involvement with the MIP team in the IITA Bioscience laboratory has helped me to learn the following molecular techniques; Nucleic acid isolation and analysis (DNA and RNA extraction, Nucleic acid quantification through Polymerase Chain reaction including quantitative PCR, Quality control using Gel Electrophoresis (Agarose gel electrophoresis and Polyacrylamide gel electrophoresis protocols) and nanodrop spectrophotometer, genotyping, hybrid verification using KASP PCR, pathogen diagnostics and characterization and seed quality analysis, DArTseq and sanger sequencing of selected sections of the maize genome and utilization of advanced bioinformatics tools like BLAST, TASSEL, Plink, R-Studio, Bioedit among others in primer designing, gene mining, quantitative trait loci (QTL) analysis, genome wide association studies (GWAS), diversity studies and marker filtering and validation.
I greatly appreciate and thank the Regional Universities Forum for Capacity Building in Agriculture (RUFORUM) for the support and providing this opportunity. Equally, I appreciate IITA for providing the learning platform.