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Title: Genetic Diversity Analysis and QTL Mapping of Selected Traits in Sorghum (Sorghum Bicolor (L.) Moench)
???metadata.dc.contributor.*???: Dr. Tileye Feyissa
Disasa, Tesfaye
Issue Date: May-2016
Publisher: Addis Ababa University
Abstract: Sorghum (Sorghum bicolor (L.) Moench) is one of the most important multipurpose crops grown globally. It can be used as food, feed, fiber and biofuel feedstock. In Ethiopia, sorghum is among the most important cereal crops accounting for 18 % of annual production and 16 % of land cover allocated to the entire grain crops including cereals, pulses and oilseeds. Despite this importance and huge potential as bioenergy feedstock, detailed study on characterization, identification and mapping of novel genes that code for sugar content related and drought tolerance traits using Ethiopian sorghum was lacking. Therefore, this study is aimed at germplasm collection, characterization, and identification and mapping of novel QTLs using both grain and sweet type of sorghum germplasm of Ethiopia. Both morphological and molecular evaluation of Ethiopian sweet sorghum germplasm was undertaken. Genotyping of 175 Ethiopian sweet sorghum genotypes alongside 27 improved accessions from eastern and southern Africa was undertaken. Two independent experiments were also carried out to identify and map QTLs associated to Brix and stay-green related traits using F2.3 segregating mapping populations derived from a cross between grain sorghum with stay-green feature (Sorcoll 163/07) and sweet sorghum (Gambella). A genetic map was constructed using 192 F2 populations genotyped with 76 SSR markers. Research was carried out to screen and compile the most informative SSR markers across some accessions. A total of 304 markers were used to identify the most polymorphic SSR markers across eleven farmers preferred sorghum genotypes. Combined analysis of variance for Brix and other morphological characters to evaluate - 181 sweet sorghum accessions collected from the major producing regions of Ethiopia showed that there is a significant effect of the environment on all tested traits. Mean separation analysis revealed that collections from northern Ethiopia were found to be superior in terms of Brix degree. Collections from the rest of collection regions showed relatively low Brix mean value but characterized by higher biomass. Broad sense heritability estimate showed most characters are highly heritable except grain yield. Pearson correlation coefficients (r) of the seven traits presented Brix degree was negatively correlated to most of the traits. Cluster analysis based on the Brix and other morphological characters grouped the accessions into five clusters. The constructed dendrogram based on mean of collection zones for the tested traits also clearly put adjacent regions or zones together. All the tested markers detected 159 alleles and a high degree of polymorphism information content (PIC) averaging 0.69. A comparison between Ethiopian and improved accessions revealed higher allele numbers (124) in Ethiopian than improved accessions (92 alleles). More than half (65 out of 124) of the alleles observed in the Ethiopian accessions were rare (<5%) while 64 were private (only present within Ethiopian accessions) while in the improved accessions, 41% and 38% of the alleles detected were rare and private respectively. Both weighted Neighbor Joining-based clustering and hierarchical clustering grouped the 202 accessions into three major clusters based on geographical origin. Ethiopian accessions from the north (Wello and south Tigray) not only clustered separately from accessions from the west central and eastern Ethiopia, but were also distinct from most of the improved genotypes. A total of seven QTLs distributed across five linkage groups that controls Brix content were detected using Inclusive Composite Interval Mapping (ICIM). Each QTL contributed 17.2 to 44.2% of the total phenotypic variation. Using the same genotypic data ICIM detected Aw stay-green QTLs using F2.3 populations evaluated under regulated irrigation supply. Four QTLs distributed on linkage groups SBI-01, SBI-06, SBI- 08 and SBI-09 were detected under rain fed drought prone environment. Three QTLs that controls chlorophyll content also detected on SBI-03, SBI-06 and SBI-07. Out of the total SSRs used across eleven farmers preferred sorghum genotypes, nearly half of the markers 139 (45.7%) detected 543 alleles and a high degree of polymorphism information content (PIC) averaging 0.53.The overall observed heterozygosity (Ho) over loci varied from 0.00 to 1.00 with an average of 0.16. Nearly 60 %> (83 markers) have showed zero value of the Ho. The gene diversity index (expected heterozygosity, He) ranged from 0.17 to 0.91 with a mean of 0.58. Weighted neighborjoining cluster analysis grouped the genotypes into three distinct groups. All genotypes with staygreen future (B 35, Sorcoll 163/07, E 36-1 and Sorcoll 141/07) were clustered together. Genotypes such as Gambella, Macia, 76T423, Meko and Melkam were distinct from the rest of the genotypes and grouped together. The third group consists ofTeshale and Sorcoll 146/07. The results from both morphological and molecular based evaluation reveal an unexploited highly diverse sweet sorghum genetic resource from Ethiopia that can be more efficiently included in the regional breeding programs in order to efficiently optimize productivity. Co-localization of staygreen QTL with QTLs for chlorophyll content in two environments has the implication that the two traits were governed by genes found on same linkage group and useful QTLs to be used in breeding program in the future. The current study forms an essential foundation for future grain and sweet sorghum breeding programs of the country as well as for ongoing programs at International Crop Research Institutes for Semi-Arid Tropics.
Description: A Thesis Presented to the School of Graduate Studies of the Addis Ababa University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biology (Applied Genetics).
Appears in Collections:Thesis - Biology

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