scholarly journals Agronomic characterization, genetic diversity and association analysis of cotton cultivars using simple sequence repeat molecular markers

2011 ◽  
Vol 10 (1) ◽  
pp. 208-217 ◽  
Author(s):  
A. Kalivas ◽  
F. Xanthopoulos ◽  
O. Kehagia ◽  
A.S. Tsaftaris
2015 ◽  
Vol 14 (25) ◽  
pp. 2066-2079 ◽  
Author(s):  
Silva Rosa Pazeto Mariana ◽  
Helena Uneda Trevisoli Sandra ◽  
Arcenio Pimentel Correa Aretha ◽  
Formice Vianna Viviane ◽  
Carvalho Leite Daniel ◽  
...  

2019 ◽  
Author(s):  
Nnamdi Ifechukwude Chidi ◽  
Adedotun Adeyinka Adekunle ◽  
Temitope Oluwaseun Samuel ◽  
Emmanuel Ifechukwude Eziashi ◽  
David Okeh Igwe

Abstract Background Improving oil palm in Nigeria for food security and subsequent export requires a better understanding of the genetic diversity among oil palm progenies tolerant and susceptible to Fusarium wilt disease. In view of the limitations of the orthodox method used in screening this disease, and the advantages of molecular markers, fourteen (14) Inter-simple sequence repeat (ISSR) DNA markers were applied to evaluate the genetic diversity, population structure and cluster resolutions of alleles responsible for tolerance of 560 Elaeis guineensis Jacq palms representing 8 different progenies distributed across NigeriaResults The amplification product revealed a moderately high level of genetic diversity with a total of 46 alleles identified, resulting in an average of 4.9091 alleles per locus detected between the oil palm progenies. Polymorphic information content (PIC) values varied between 0.3706-0.7861, with a mean value of 0.6829. The genetic diversity values ranged from 0.4063-0.8125 with a mean of 0.7216, while the major allele frequency ranged from 0.2500- 0.7500 with a mean value of 0.3750. Shannon's information index (I), Nei's gene diversity (H), and the effective number of alleles (Ne) had values of 0.6931, 0.5000, and 2.000, respectively. The genetic diversity was highest in progeny 3023, and lowest in progeny 4189. Mean values of the total gene diversity (Ht), gene diversity within the population (Hs) of the progenies, coefficient of gene differentiation among the progenies (Gst) and level of gene flow (Nm) were 0.4899, 0.3520, 0.2815 and 1.2764, respectively. The dendrogram clustered the progenies into six major clusters, while Principal Component Analysis (PCA) grouped the progenies into five clusters. PCA further identified the coordinate positions of tolerant and susceptible alleles of oil palm progeniesConclusion This study confirmed the identification of the coordinate positions of tolerant alleles in the gene loci, which could be exploited by breeders to developing tolerant oil palm seedlings.


2021 ◽  
Vol 22 (9) ◽  
Author(s):  
Evy Nasrika ◽  
Amin Retnoningsih

Abstract. Nasrika E, Retnonongsih A. 2021. Inter Simple Sequence Repeat molecular markers to reveal the genetic diversity of superior durian of Gunungpati, Semarang, Indonesia. Biodiversitas 22: 4054-4059. Kalimantan is the center of many tropical fruits, including durian. One of the edible durians and favorited by many is Durio zibethinus, which has many superior varieties. Almost all regions in Indonesia have superior durian varieties; for example, superior durian Gunungpati from Gunungpati Sub-district, the center for producing durian in Semarang City, Central Java, Indonesia. ISSR analysis was carried out to reveal the genetic diversity of the superior durian Gunungpati. DNA isolation of 16 superior durians used the modified CTAB method. The genomic DNA was amplified using 10 ISSR primers and then electrophoresed using 2% agarose gel. Data were analyzed using NTSYS PC version 2.02. The resulting allele has a relative size of 220 bp-1800 bp, with 87.9% are polymorphic. The similarity coefficient of 16 varieties was ranged between 0.54-0.88. All the superior durian varieties examined were different accessions so that each variety has the potential to be registered as a new variety of superior Indonesian durian. Specific alleles are found in G1, G3, G7, G8, and G13, which can be an identity of these varieties.


Genome ◽  
2005 ◽  
Vol 48 (2) ◽  
pp. 257-272 ◽  
Author(s):  
B Tar'an ◽  
C Zhang ◽  
T Warkentin ◽  
A Tullu ◽  
A Vandenberg

Random amplified polymorphic DNA, simple sequence repeat, and inter-simple sequence repeat markers were used to estimate the genetic relations among 65 pea varieties (Pisum sativum L.) and 21 accessions from wild Pisum subspecies (subsp.) abyssinicum, asiaticum, elatius, transcaucasicum, and var. arvense. Fifty-one of these varieties are currently available for growers in western Canada. Nei and Li's genetic similarity (GS) estimates calculated using the marker data showed that pair-wise comparison values among the 65 varieties ranged from 0.34 to 1.00. GS analysis on varieties grouped according to their originating breeding programs demonstrated that different levels of diversity were maintained at different breeding programs. Unweighted pair-group method arithmetic average cluster analysis and principal coordinate analysis on the marker-based GS grouped the cultivated varieties separately from the wild accessions. The majority of the food and feed varieties were grouped separately from the silage and specialty varieties, regardless of the originating breeding programs. The analysis also revealed some genetically distinct varieties such as Croma, CDC Handel, 1096M-8, and CDC Acer. The relations among the cultivated varieties, as revealed by molecular-marker-based GS, were not significantly correlated with those based on the agronomic characters, suggesting that the 2 systems give different estimates of genetic relations among the varieties. However, on a smaller scale, a consistent subcluster of genotypes was identified on the basis of agronomic characters and their marker-based GS. Furthermore, a number of variety-specific markers were identified in the current study, which could be useful for variety identification. Breeding strategies to maintain or enhance the genetic diversity of future varieties are proposed.Key words: Pisum sativum, molecular markers, genetic relationships, cluster analysis.


2019 ◽  
Vol 51 (5) ◽  
Author(s):  
Huifang Cao ◽  
Qiang Lin ◽  
Peiwang Li ◽  
Jingzhen Chen ◽  
Changzhu Li ◽  
...  

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