Microsatellite isolation and characterization for Colletotrichum spp, causal agent of anthracnose in Andean blackberry

Abstract

ABSTRACT. The genus Colletotrichum, comprised of pathogenic fungi that affect plants grown worldwide, causes the disease known as anthracnose in several fruit and vegetable species. Several studies conducted on plants have shown that the disease is characterized by the presence of one or several species of the fungus attacking the fruit or other organs of the same host. To develop and implement effective control strategies, it is vital to understand the genetic structure of the fungus in agricultural systems, identify associated Colletotrichum species, and define the subpopulations responsible for the disease. Molecular tools were accordingly developed to characterize genotypic populations of Colletotrichum spp, causal agent of anthracnose in commercial crops of Andean blackberry (Rubus glaucus Benth.). A microsatellite-enriched library for Colletotrichum gloeosporioides was developed to identify and characterize microsatellite loci among isolates collected in R. glaucus plantations. Thirty microsatellites were developed and tested in 36 isolates gathered from eight different blackberry-production areas of Colombia. Ten pairs of microsatellites were polymorphic.

Genetic diversity ofColletotrichum gloeosporioidesspecies complex associated withCitruswither‐tip of twigs in Tunisia using microsatellite markers

“…SSR markers are now available for Colletotrichum capsici on chili pepper anthracnose disease (Ranathunge, Ford, & Taylor, 2009), for C. acutatum on PFD on Citrus (Ciampi et al, 2011), for Colletotrichum spp. on blackberry (Marulanda, Lopez, Isaza, & Lopez, 2014) and for C. gloeosporioides on Citrus anthracnose disease (Moges et al, 2016). In addition, the application of inter-simple sequence repeat markers has been developed for C. gloeosporioides on papaya (Rampersad, 2013) and Colletotrichum spp.…”

“…Very few studies have been conducted on the causative agent of Citrus anthracnose disease worldwide (Keuete Kamdoum, Noumbo, & Kuiate, ). Understanding pathogen population structure, its spatio‐temporal dynamics and its genetic diversity leading to host adaptation and fungicide resistance are essential for the development of effective disease management strategies (Mahmodi et al, ; Marulanda et al, ; Moges et al, ; Rampersad, ; Ranathunge et al, ). The objectives of the study were (a) to identify the causative agent of anthracnose disease, associated with twig wither‐tip symptoms, across major Citrus growing areas in Tunisia and (b) to analyse the genetic diversity and population structure of Colletotrichum sp.…”

Development of Microsatellite Markers and Analysis of Genetic Diversity and Population Structure of Colletotrichum gloeosporioides from Ethiopia

“…Colletotrichum gloeosporioides has been found associated with the leaf and fruit disease of citrus across citrus growing regions of Ethiopia. Therefore, it is vital to understand the genetic diversity and population structure of the fungus, and define the regional populations of the pathogen to develop and implement effective disease management strategies [ 24 ].…”

Genomewide identification and development of microsatellite markers for Marssonina brunnea and their applications in two populations

“…In the present study, the developed markers displayed allelic diversity, with a mean number of 3.75 and a total number of 90 (Table ). The PIC was used in estimating the discriminatory power of each marker locus by considering the number and the relative frequencies of the alleles (Botstein, White, Skolnick, & Davis, ; Marulanda, Lopez, Isaza, & Lopez, ). The highest PIC value of these markers reached 0.6492 and the average value score was 0.2427 (Table ).…”

“…Furthermore, the SSR distribution of species belonging to the same genus was highly similar (Figure 2 (Dutech et al, 2007). In the present study, the developed markers displayed allelic diversity, with a mean number of 3.75 and a total number of 90 (Table 1) BJ46 BJ65 BJ60 BJ61 BJ55 BJ64 BJ63 HN75 BJ67 HN72 HN90 HN87 BJ50 BJ62 HN70 HN71 BJ57 HN73 HN91 HN93 HN76 HN89 HN78 HN88 HN74 HN84 BJ58 BJ51 HN85 HN82 BJ59 HN86 HN83 BJ56 BJ49 BJ68 HN77 BJ47 BJ53 BJ54 BJ52 BJ48 HN79 HN92 BJ66 HN81 HN80 BJ46 BJ65 BJ60 BJ61 BJ55 BJ64 BJ63 HN75 BJ67 HN72 HN90 HN87 BJ50 BJ62 HN70 HN71 BJ57 HN73 HN91 HN93 HN76 HN89 HN78 HN88 HN74 HN84 BJ58 BJ51 HN85 HN82 BJ59 HN86 HN83 BJ56 BJ49 BJ68 HN77 BJ47 BJ53 BJ54 BJ52 BJ48 HN79 HN92 BJ66 HN81 HN80 was used in estimating the discriminatory power of each marker locus by considering the number and the relative frequencies of the alleles (Botstein, White, Skolnick, & Davis, 1980;Marulanda, Lopez, Isaza, & Lopez, 2014). The highest PIC value of these markers reached 0.6492 and the average value score was 0.2427 (Table 1).…”