Journal of Bioscience and Biotechnology Discovery

Volume 2. Page 97-103
Published 13th September, 2017
ISSN: 2536-7064

Full Length Research

Marker assisted selection for resistance to Striga gesnerioides in Cowpea (Vigna unguiculata L. Walp)

Victoria Larweh1*, Richard Akromah2, Stephen Amoah1, James Y. Asibuo1, Ruth Prempeh1 and Francis Kusi3

1CSIR-Crops Research Institute (CSIR-CRI) P.O. Box 3785, Kumasi-Ghana.
2Kwame Nkrumah University of Science and Technology (KNUST), Faculty of Agriculture, Kumasi, Ghana.
3CSIR- Savanna Agricultural Research Institute, Tamale-Ghana.

Received 24th July, 2017; Accepted 17th August, 2017

*Correspondence: Dr. Victoria Larweh, CSIR-Crops Research Institute (CSIR-CRI) P.O. Box 3785, Kumasi-Ghana. Email: victorialarweh7@gmail.com. Tel: +233-244672839.

Copyright © 2017 Larweh et al. This article remains permanently open access under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ABSTRACT

Cowpea is an important warm-season grain legume primarily found in the semi-arid tropics. It is mostly cultivated by subsistence farmers in West and Central, sub-Saharan Africa, where its grains and leaves are used mainly as food. Its productivity is challenged by several biotic and abiotic factors. A major biotic constraint in cowpea production is the parasitic weed Striga gesnerioides. This study was to assess three molecular markers (SSR-1, 61RM2 and C42-4B) and their abilities to identify resistance and susceptibility of F2 cowpea progenies to S. gesnerioides. To determine the genetic diversity among parental lines and progenies based on markers associated with Striga resistance. A total of 93 F2 progenies from a cross between IT99K-573-1-1 and Hewale were screened. The results showed that the three markers had discriminating power to distinguish between resistant and susceptible genotypes. Marker SSR-1 was found in 61 F2 individuals suggesting that the resistant alleles were highly repeatable within the population. Marker C42-2B was found in 58 F2 individuals while marker 61RM2 was also found in 68 F2 individuals. Allele frequency yielded by the three markers ranged from 0.62 to 0.73 with the mean of 0.67. Genetic diversity range from 0.39 to 0.42 with the mean of 0.43. Polymorphic Information Content (PIC) ranged from 0.32 to 0.36 with the mean of 0.34. The results obtained from these findings indicated that these markers would facilitate and shorten the breeding time as the markers can be used to screen lines or accessions two weeks after planting.

Key words: Biotic, Cowpea, genotype, marker assisted selection, resistance, stress, Striga.

INTRODUCTION

Cowpea is (Vigna unguiculata L. Walp) a member of the Phaseoleae tribe of the Leguminosae family (Timko et al., 2007). Cowpea also known as black-eye pea is an important grain legume in sub-Saharan Africa. It is initiated from the semi-arid areas of West Africa and has been cultivated for human consumption for over 4,000 years (Tweneboah, 2000). The name cowpea originated from the fact that the plant was an essential source of hay for cattle in southern United States of America and in other parts of the world (Timko et al., 2007). Some important local names for cowpea include “Beng” in Dagari, “Ayi” in Ewe, and “caupi” in Brazil. It plays a critical role in the lives of a large number of individuals in Africa and different parts of the developing world, where it is a major source of dietary protein that nutritionally supplements starchy staples. The high protein content presents a major benefit in the use of cowpea as nutritional products for infants and children; and could compensate for the huge amount of carbohydrate frequently ingested in African diets (Lambot, 2002). Cowpea is a valuable and reliable commodity that creates income for farmers and helps to replenish soil fertility for succeeding cereal crops growing in rotation.

Regardless of the significance of black-eyed pea in West Africa, its production is impeded by a myriad of biotic and abiotic factors. Notable among the biotic constraints include pests and diseases, and parasitic weeds cause serious threat to cowpea production. The parasitic angiosperm Striga gesnerioides (Willd) is one of the significant limitations to cowpea cultivation particularly, in the Guinea Savanna agro-ecology. The parasitic weed S. gesnerioides is an obligate root-parasitic blossoming plant of the Scrophulariaceae family. Yield losses attributed to these parasites are enormous. Complete crop damage has been reported in susceptible cowpea genotypes following severe S. gesnerioides infestation (Muranaka et al., 2011). It is believed that the fast spread of this parasitic weed and huge yield decrease would constitute an extreme danger to cowpea production. For the resource-poor farmers, developing S. gesnerioides-resistant cowpea genotypes in association with appropriate management practices are most conservative and effective choices to forestall yield loss.

Over the years, plant breeders use innovative procedures to develop varieties with desirable traits. These techniques enable breeders and molecular geneticists to introgress the desired gene with specificity. With the advent technology, breeders are using molecular tools to quicken the breeding process. Marker Assisted Selection (MAS) is one of the tools used to select genotypes that carry a trait of interest. The importance of this method is that, genotypes with desirable traits are recognized at the seedling stage, reducing plant growth period in population size (Yu et al., 2000). Using marker-assisted selection processes are promising for Striga resistance since phenotyping in the field is intricate, costly and sometime unpredictable (Haussmann et al., 2000). Various genomic markers have been developed for MAS in several crops. These are mostly SSRs and SCAR markers which have numerous benefits including a simple automating procedure, more open SSR availability, and profitable once the oligonucleotides are designed (McCouch et al., 1997). In cereals major markers such as simple sequence repeats (SSRs) or microsatellites have been extensively used in modern times (Gupta et al., 1999; Gupta and Varshney, 2000). These markers are highly dependable, co-dominant in inheritance, comparatively simple and cheap to use and largely highly polymorphic.

Marker assisted selection has major advantages. It permits the determination for an extensive range of characteristics at the seedling stage and hence reduces the time required before the phenotype of an individual plant is recognized. For characters expressed at advanced formative stages, unwanted genotypes can be rapidly removed by marker-assisted selection. The utilization of markers is not influenced by environment, in this approach allowing the selection to be made under any natural conditions such like in the nursery and during off-season. MAS is simpler to use than phenotypic screening thus saves time, resources and efforts. Classical examples of traits that are problematic and strenuous to measure are cereals cyst nematode and root lesion nematode resistance in wheat (Eastwood et al., 1991; Eagles et al., 2001; Zwart et al., 2004). MAS has been use to improve the recurrent parent by fast-tracking in backcross selection in a higher proportion of recurrent parent genomes. This method has been used with great achievement for ‘enhancing’ rice varieties for traits such as bacterial blight resistance gene XA21 (Chen et al., 2000). The objective of this study therefore was to use molecular markers to identify F2 cowpea progenies resistant to S. gesnerioides. To determine the genetic diversity among cowpea parental lines and their progenies based on markers associated with S. gesnerioides resistance.

MATERIALS AND METHODS

F2 populations were developed from resistant genotype IT99K-573-1-1 (IITA, Ibadan), and susceptible variety Hewale (CSIR-Crops Research Institute) during 2015 and 2016 growing seasons. The F2 plants together with their parental lines were grown in plastic pots with diameter of 23 cm and depth of 20 cm. Seeds of Striga were obtained from farmers’ field in the Mamprusi District in the Upper East Region, Ghana. Striga seeds of 5 g were inoculated into each plastic pot. To identify F2 resistant genotypes, a representative sample of 93 F2 progenies were used. Two SCAR markers (Sequence Characterized Amplified Region) and one microsatellite marker (simple sequence repeat) known to be associated with S. gesnerioides resistance in cowpea were used. The SCAR markers used were 61RM2 and C42-2B, and SSR marker used was SSR-1 (Timko’s Laboratory of the University of Virginia, and commercially synthesized (Sigma-Aldrich, St Louis, MO, USA)).

Young apical leaves of two weeks old were harvested and put on silica gel. One hundred and fifty milligram of leaf sample was weighed into ZR Bashing BeadTM and crushed in liquid nitrogen and 750 µl lysis buffer was added. Total genomic DNA was isolated from the leaf tissues of cowpea plant using ZR plant/seed DNA MiniPrepTm (Zymo Research Corporation, South Africa) (Zymo Research, 2010) at the Molecular Biology Laboratory of the CSIR-Crops Research Institute. Quality of DNA was assessed using 0.8% (w/v) agarose gel electrophoresis. Concentration of the DNA was determined using Nanodrop (spectrophotometer 2000C, Inqaba biotecTM, South Africa).

Polymerase Chain Reaction (PCR) analysis was conducted using Biolab Inc, South Africa protocol. The PCR amplifications were performed in an Eppendorf Master Cycler (Gene Amp, PCR System 9700, Germany). The thermal cycle used comprised an initial denaturation at 95oC for 1 min followed by 35 cycles of denaturation for 1 min at 94oC, annealing at 55 or 60oC for 1 min, extension at 72oC for 1 min and final extension at 72oC for 10 min (Asare et al., 2010). SCAR marker C42-2B could anneal at a higher temperature than 61RM2 and SSR-1. PCR products were resolved for 45 min at 120 V on 1.5% (w/v) agarose gel in 1X TAE buffer using horizontal gel electrophoresis apparatus. Gel was stained with ethidium bromide and photographed using minibus camera (DNR-Bio imaging systems) + high per-formance UV transiluminator (Upland). Scoring of bands was carried out manually. A 100 bp DNA ladder from invitrogen was used as a molecular-weight size marker for each gel alongside the DNA samples. Qualitative score of presence and absence were recorded base on the molecular weight of the markers. The primer sequence and their annealing temperatures are given in (Table 1).


Table 1


F2 individuals having either all three markers, two, one or none of the markers, were identify using a cluster analysis. Allele frequency, gene diversity, polymorphism information content (PIC) were determined and dendrogram was constructed using Power marker software version 6.25

RESULTS AND DISCUSSION

The results revealed that the three makers, SSR-1 (Figure1), C42-2B (Figure 2) and 61RM2 (Figure 3) were able to identify the resistant genotype out of the population. A total of 93 F2 progenies were observed from a cross between IT99K-573-1-1 and Hewale. The three markers have previously been shown to be associated with S. gesnerioides resistance (Ouédraogo et al., 2012; Asare et al., 2010). Thus, the presence of the three markers in a genotype was an indication that, the genotype had the Striga resistant allele(s). The results revealed that the three markers, SSR-1, C42-2B and 61RM2 were sensitive at 150, 280 and 400 bp respectively (Figures 1, 2 and 3). Similar results were observed by Omoigui et al. (2009), using marker C42-2B.


Figure1



Figure2



Figure3


Over Sixty (60) progenies were expressed by marker SSR-1; whereas less than 60 and over 65 progenies had markers C42-2B and 61RM2 respectively (Table 2). Individual that had all three or two markers expressed indicated that such progenies elucidate genetic relationship within the population and had the Strgia resistant alleles.

The study showed that the three markers had discriminating powers to differentiate between resistant and susceptible genotypes and the markers link at high frequencies with the genes. The three markers showed susceptibility of Hewale to Striga as none of them produce a band (Figures 1, 2 and 3). This confirmed the phenotypic observation in the field where the susceptible genotypes had many Striga shoots whereas the resistant genotypes were totally free of Striga shoots.


Table 2


Allele frequencies yielded by the three markers ranged from 0.62 to 0.73 with a mean of 0.67 (Table 3). This implies that 67% of the progenies carry the resistant alleles or genes. Gene diversity ranged from 0.39 to 0.47 with a mean of 0.44. This indicates that genetic variation among the progenies was 44%. Based on the genetic diversity, each locus for allelic polymorphism information content (PIC) ranged from 0.32 to 0.36 with a mean of 0.34 (Table 3). The PIC values of the SSR-1 markers can be compared to results reported by Li et al. (2001) with PIC ranging from 0.02 to 0.73. However, the PIC values obtained by Asare et al. (2010) varied from 0.07 to 0.66 with an average of 0.38. The PIC values observed in the current study compared favourably with results obtained by Asare et al. (2010). The PIC value is a means of detected alleles and distribution of their frequencies (Moghaddam et al., 2009). However, a marker with high allelic frequency has low PIC as found in 61RM2 and a maker with low allele frequency has a high PIC as found with C42-2B. In this case, the higher major allele frequencies (MAF), the lower the PIC and vice versa. It must be noted that the allelic frequency, PIC and gene diversity reported in this study are in relation to the marker alleles used.


Table 3


The allele frequency for marker SSR-1 was 65% suggesting that the resistant alleles associated with the marker SSR-1 is highly repeatable within the population. This also means that the population had high breeding values. It means that the number of individuals having average performance of its offspring was high hence the possibility to choose parents for future crosses. Marker 61RM2 had 73% of the allele frequency suggesting that such a marker can be very useful in discriminating resistant alleles from susceptible alleles within the population. The larger the number of alleles identifies by the marker the better the efficiency of that marker. Given the magnitude and difficulty of selection required in breedin programs, one can appreciate the importance of markers in identify a resistant progenies. This advocates that this marker could be used to increase upon a variety to assist long-term gains from selection, and decrease genetic vulnerability to parasite epidemics. Li et al. (2001) confirmed that microsatellite markers were conserved between Vigna species. Henceforth microsatellite markers can offer a simple method of assessing the introduction of such genetic material.

The dendrogram generated five major clusters (Table 4) I, II, III, IV and V and 14 sub-clusters (Figure 4). The result of the cluster analysis based on the molecular markers revealed individuals that possessed all three markers associated with resistance to Striga. Cluster I showed those individuals that had all the three markers present and also showed resistance under field conditions. Clusters II, III and IV consisted of individuals with two markers and resistant under field condition. Cluster V consists of individuals that did not have any of the three markers. However, for some individuals, there were lack of consistency between the marker and the phenotype. For those individuals, marker showed resistance; nevertheless under field condition they were susceptible. These may be attributed to the fact that the markers were not able to identify the gene of interest or the genes were masked. Others showed resistance while the marker indicated susceptible. This could be attributed to epistatic interactions among the genes or the marker may have segregated away from the genes conferring resistance. Sometimes recombination may have occurred between the marker and the gene of interest. As reported by Li et al. (2009), gene markers connected with resistance have been characterized, and a few SCARs (sequence-characterized amplified regions) have been designed for use in marker-based breeding programs.


Table 4



Figure 4

CONCLUSION

These three markers were able to differentiate between resistant and susceptible progenies. The SCAR markers showed high percentage of resistance within the genotypic population with 61RM2 having the highest marker depicted. Therefore, such markers would be used to facilitate the breeding processes. The application of MAS appears to be the best and most immediately effective strategy to improve cowpea genotypes for S. gesnerioides resistance.

ACKNOWLEDGMENT

We wish to thank the members of the CSIR-CRI laboratory who helped either directly or indirectly in carrying out the work. We also thank Dr. Aaron T. Asare of the Department of Molecular Biology and Biotechnology, University of Cape Coast, Ghana, for his contribution to the success of the work. This work was supported by West Africa Agricultural Productivity Programme (WAAPP).

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