“DNA Barcoding”: new initiative in determining the diversity and checking the spread of pathogens

Diagnostic tools is vital to disease surveillance, development of host plant resistance, quarantine monitoring, and supporting safe conservation and exchange of germplasm. Good knowledge on pathogen population structure and genetic diversity is a pre-requisite to developing unambiguous diagnostic tools and is critical in establishing disease management tactics. Increasingly, modern diagnostic tools are being based on the DNA characteristics of the pathogen.

Clustering of 25 yam isolates based on rDNA sequences. Image by Lava Kumar, IITA.
Clustering of 25 yam isolates based on rDNA sequences. Image by Lava Kumar, IITA.

We undertook a new initiative to genetically characterize pathogen populations and recognize unique stretches of sequences. Called ‘DNA Barcodes’, they can be used as markers for diagnosing pathogens and pests affecting African food crops.

For instance, we conducted molecular characterization of fungal pathogen(s) causing anthracnose – the most destructive disease of yam and cassava in West Africa. In yams, anthracnose appears as leaf spot that spreads rapidly, killing the leaves, shoots, and entire plant. In cassava, it appears as cankers on stems at the base of leaf petioles, and also kills the leaves, shoots, and whole plant. The disease causes severe yield losses in both crops.

The causal fungus, Colletotrichum gloeosporioides Penz., is widespread in West Africa. We identified various isolates of this fungi differing in morphology, growth characters, and pathogenicity, and investigated their genetic relatedness and diversity through molecular analysis using a set of 25 reference isolates (17 from yam and 8 from cassava). Based on the symptoms they induce, they were grouped into spot (S) and blight (B) isolates. Both isolates infect yam, but only B isolates infect cassava. We assessed the genetic diversity in these isolates by nucleotide sequencing and cluster analysis of the ~540 base pair (bp) nuclear ribosomal internal transcribed spacer region (ITS1, ITS2 and the 5.8S gene) and partial gene sequences of actin (~240 bp) and histone (~370 bp).

Phylogenetic cluster analysis grouped the 25 isolates into two major clades and two sub-clades within the major clades. Both the S and B isolates were distributed between the two clades (see figure). All the isolates in clade 1 were unique to yam. Seven of these isolates (YA08-1, YA08-2, YA08-3, YA08-4, YA08-7, Y-83, Y-84) formed a genetically-distinct lineage indicating that they could be new strains unique to yam. Isolates in clade 2 infect both cassava and yam suggesting their capability to infect wide range of plants. Clade 2 isolates could be the most frequently occurring on yam and cassava because of their ability to survive on weeds and other crops. We recognized unique sequence motifs and designed diagnostic PCR primers for specific amplification of C. gloeosporioides infecting yam and cassava directly from infected plant tissues.

Using a similar approach, we characterized the fungal agent associated with grey leaf spot (GLS), the most destructive disease of maize. We found that GLS in Nigeria is caused by a distinct species of Cercospora, but not C. zeae-maydis. This work, in addition to confirming the GLS etiology, allowed us to establish a unique set of primers for specific identification of GLS pathogen prevalent in Nigeria.

Through comparative genomics, we identified common genome regions in cassava mosaic begomoviruses occurring in sub-Saharan Africa. We developed a simple multiplex PCR assay that can detect all the major viruses in cassava mosaic disease etiology. This test has been institutionalized for virus indexing of cassava propagated in vitro.

To aid in diagnostics research, we developed a simple and cost-effective procedure suitable for extraction of DNA from seeds, leaves, stems, tubers, and even roots. The resultant DNA is suitable for PCR-based diagnoses of fungi, bacteria, and viruses in the infected tissues in a wide range of plant species, and is handy for quarantine monitoring of germplasm. We are establishing a repository of diagnostic protocols in an approach we call “Diagnostic Basket” and make it available to users.