|
|
|
 |
Search published articles |
 |
|
Showing 6 results for Qtl
Reza Mir Drikvand, Goodarz Najafian, Mohammad Reza Bihamta, Asa Ebrahimi,
Volume 1, Issue 2 (2-2015)
Abstract
This study was conducted to identify markers associated with some kernel traits in bread wheat in two separate experiments under field and laboratory. One hundred wheat genotypes were evaluated in an alpha lattice experimental design with two replications. Grain hardness, seed length, seed width and thousand kernel weights were measured. Association mapping was performed based on 96 unlinked and 22 SSR QTL linked markers, using structure and Tassel software. Correction for population structure was performed using genome wide SSR markers so that genotypes were divided into six sub-populations. Totally, 35 SSR markers linked to traits were detected eight of them being QTL linked markers and other markers that were linked to traits, were used to investigate population structure. The QTLs linked markers were as follows: Chromosomes 5B, 5D and 6D had three QTL for grain hardness. Nine QTLs were detected on chromosomes 1A, 1B, 2A, 2B, 2D, 5B, 5D, 6D and 7B for kernel length, kernel width and thousand kernel weights. The results of this study demonstrate that association mapping is a useful approach to complement and enhance previous QTL information for marker-assisted selection in wheat.
Atefeh Kaviani Charati, Hossein Sabouri, Hossein Ali Fallahi, Eisa Jorjani,
Volume 3, Issue 1 (9-2016)
Abstract
Abstract In order to genetic analysis of spike characteristics in barley, an experiment was conducted with 100 F3 and F4 barley families derived from Badia × Komino cross at Research Farm college of Agricultural University of Gonbad Kavous (Iran) based on randomized complete block design with three replications. Agronomic traits such as spike length, number of seeds per spike, total of spike, total weight of spike, grain length and grain diameter were measured. Linkage map with 7 SSR and 69 polymorphic alleles of iPBS markers were prepared which covered 632.2 cM of barley genome. QTL analysis was performed based on the method of composite interval mapping (CIM). Ten QTLs (with additive effect ranged from 127.07 for spike number to -0.625 mm for grain length) were detected. Phenotypic variance explained by QTLs ranged from 10.9 to 12.9 percent, which the highest related to spike length in F3 generation and the lowest related to the total number of spikes in F3 generation and the total weight of spike in F4 generation. All detected QTL were major effects and after validation can be used in breeding programs and marker-assisted selection.
Mohsen Barajehfard, Mohammad Reza Siahpoosh, Mohammad Modarresi,
Volume 3, Issue 2 (3-2017)
Abstract
In order to identify QTLs associated with stemlet and rootlet growth in the early stages of germination of wheat, 144 recombinant inbred lines derived from the cross of Kaz and Mantana were evaluated in a completely randomized design. The linkage map using composite interval by 234 microsatellite (SSR) primers and 267 AFLP loci have been already prepared in this population which covered 20 chromosomes of wheat. For root length, 1, 2 and 2 QTLs were located on 4D, 4B and 2D chromosomes, respectively. Two QTLs of rootlet length was located on 6B and 3D chromosomes. The QTLs of rootlet number were identified on 4A, 5A and 3B chromosomes. For each of stemlet dry weight (SDW) and rootlet dry weight (RDW) traits only one QTL identified on 4A and 3D chromosomes, respectively. Overall, for SDW to RDW ratio on 2D and 3D chromosomes, three QTLs were located. The QTLs of stemlet wet weight (SWW) were detected on 6B and 2B chromosomes. On 1B, 2D and 6B chromosoms, three QTLs were recognized for SWW to RWW ratio. For all traits, the range of LOD = 2.04-6.34 and R2 =5.11-19.58 were calculated. The highest amount of LOD and R2 (5.11 and 19.58, respectively) were obtained for rootlet length QTL (QSL-chpgu-4D). The least distance to the nearest adjacent marker (AFgcCGb marker) was 0.005 Centi-Morgan which belonged to rootlet length QTL (QRL-chpgu-3D) on 3D chromosome.
Mohammad Reza Jafarzadeh Razmi, Saeid Navabpour, Hossein Sabouri, Seyedeh Sanaz Ramezanpour,
Volume 6, Issue 2 (3-2020)
Abstract
In order to analyze the genetic components of agronomic traits among 116 F9 recombinant lines derived from crosses of Ahlamitarom × Sepidroud rice cultivars, an experiment was conducted as a randomized complete block design in research farm of Gonbad Kavous University of Agriculture with three replications in 2016 and 2017. Genetic linkage map provided with 80 SSR markers, 28 iPBS Markers (79 polymorphic alleles), 7 IRAP markers (17 polymorphic alleles) and 26 ISSR markers (70 polymorphic alleles), which covered 1275.4 cM of the rice genome. QTL analysis was performed by Composite Interval Mapping. In two years, 15 QTLs detected for the studied traits. The additive effected varied from 6.725 g for grain weight up to -85.626 g for grain weight. Also, R2 for the detected QTLs explained from 11.3% to 20% of the total variation. The highest R2 was related to grain weight in the first year of experiment. Among the detected QTLs, qGWs on chromosome 1, were found to be stable and large effector QTLs for rice (Oryza sativa L.) grain weight, and can be used in marker-assisted breeding and selection programs after validation.
Mahnaz Katouzi, Saeid Navabpour, Hossein Sabouri , Ali Akbar Ebadi,
Volume 7, Issue 2 (3-2021)
Abstract
In order to identify QTLs controlling agronomically traits, landrace Tarom and rice Tarom mutant were crossed. SSR, ISSR, iPBS and IRAP markers were amplified in 250 F2 individuals to prepare the linkage map. Number of tillers, 100 grain weight, number of filled grains, number of unfilled grains, plant height, panicle length, number of branches, stem diameter, grain length, grain width, grain shape, straw weight, days to maturity, flag leaf length and flag leaf width were measured for 250 individuals. The linkage map covered 970.9 cM of rice genome. The distance between two adjacent markers was calculated to be 12.77 cM. Based on the results, a total of 13 QTLs were identified for the evaluated traits. For all studied traits, alleles transferred from the parents to the QTLs detected increased grain yield. Most QTLs were detected for days to flowering. Three QTLs were located on chromosomes 10 and 4 (two QTLs) for days to flowering. qLDF-4a and qLDF-4b had a negative additive effect and the parent alleles of the mutant landrace Tarom reduced the number of days to flowering. These QTLs explained 11.6% of the phenotypic variance. Since the population under study was derived from a cross between landrace and mutant Tarom cultivars and the resulting population varied only in the mutated genes; so, the QTLs detected in this study were more accurate in location and expression levels, and after validation of them, they could be recommended for marker assistant selection breeding programs.
Elina Nazari Khakshoor, Amin Azadi, Peyman Fourozesh, Alireza Etminan, Eslam Majidi Hervan,
Volume 9, Issue 1 (9-2022)
Abstract
Salinity stress falls into the major environmental factors that limit the production of various crops, including wheat. An effective approach to reducing the impacts of stress is the production of new salinity-tolerant cultivars. Accordingly, identifying effective genes and molecular mechanisms responsible for salinity tolerance is an essential step for breeding programs. In this investigation, a population of F12 recombinant inbred lines (RIL) comprising 186 genotypes was studied to identify the loci that control some physiological traits and element concentrations in the wheat seedling stage under salinity stress. Totally, 12 quantitative traits loci (QTLs) were identified for wet weight, dry weight, length, and sodium and potassium contents using the composite interval mapping (CIM) analysis. Most of the identified QTLs were located on chromosomes B and D. A gene ontology (GO) analysis specified candidate genes in QTL regions. However, it is noteworthy that candidate genes need confirmation using marker-assisted identification. The prioritization of genes resulted in determining 3486 candidate genes in 19 GO phrases (including eight biological processes). These genes are involved in the processes of glutathione metabolism, L-phenylalanine catabolism, cytoplasmic translation, auxin-activated signaling pathway, transcriptional regulation, DNA-patterning, protoporphyrinogen IX, cell wall organization and genesis, xyloglucan tRNA metabolism, protein glycosylation, pigment biosynthesis, etc. GO may be introduced for identifying novel CGs in which the associated QTL is responsible for complicated traits.
|
|
