Expressed sequence tags (ESTs) are a valuable source of molecular markers. To enhance the resolution of an existing linkage map and to identify putative functional polymorphic gene loci in hexaploid wheat (Triticum aestivum L.), over 260,000 ESTs from 5 different grass species were analyzed and 5418 SSR-containing sequences were identified. Using sequence similarity analysis, 156 cross-species superclusters and 138 singletons were used to develop primer pairs, which were then tested on the genomic DNA of barley (Hordeum vulgare), maize (Zea mays), rice (Oryza sativa), and wheat. Three-hundred sixty-eight primer pairs produced PCR amplicons from at least one species and 227 primer pairs amplified DNA from two or more species. EST-SSR sequences containing dinucleotide motifs were significantly more polymorphic (74%) than those containing trinucleotides (56%), and polymorphism was similar for markers in both coding and 5' untranslated (UTR) regions. Out of 112 EST-SSR markers, 90 identified 149 loci that were integrated into a reference wheat genetic map. These loci were distributed on 19 of the 21 wheat chromosomes and were clustered in the distal chromosomal regions. Multiple-loci were detected by 39% of the primer pairs. Of the 90 mapped ESTs, putative functions for 22 were identified using BLASTX queries. In addition, 80 EST-SSR markers (104 loci) were located to chromosomes using nullisomic-tetrasomic lines. The enhanced map from this study provides a basis for comparative mapping using orthologous and PCR-based markers and for identification of expressed genes possibly affecting important traits in wheat.
The premature germination of seeds before harvest, known as preharvest sprouting (PHS), is a serious problem in all wheat growing regions of the world. In order to determine genetic control of PHS resistance in white wheat from the relatively uncharacterized North American germplasm, a doubled haploid population consisting of 209 lines from a cross between the PHS resistant variety Cayuga and the PHS susceptible variety Caledonia was used for QTL mapping. A total of 16 environments were used to detect 15 different PHS QTL including a major QTL, QPhs.cnl-2B.1, that was significant in all environments tested and explained from 5 to 31% of the trait variation in a given environment. Three other QTL QPhs.cnl-2D.1, QPhs.cnl-3D.1, and QPhs.cnl-6D.1 were detected in six, four, and ten environments, respectively. The potentially related traits of heading date (HD), plant height (HT), seed dormancy (DOR), and rate of germination (ROG) were also recorded in a limited number of environments. HD was found to be significantly negatively correlated with PHS score in most environments, likely due to a major HD QTL, QHd.cnl-2B.1, found to be tightly linked to the PHS QTL QPhs.cnl-2B.1. Using greenhouse grown material no overlap was found between seed dormancy and the four most consistent PHS QTL, suggesting that greenhouse environments are not representative of field environments. This study provides valuable information for marker-assisted breeding for PHS resistance, future haplotyping studies, and research into seed dormancy.
Reference populations are valuable resources in genetics studies for determining marker order, marker selection, trait mapping, construction of large-insert libraries, cross-referencing marker platforms, and genome sequencing. Reference populations can be propagated indefinitely, they are polymorphic and have normal segregation. Described are two new reference populations who share the same parents of the original wheat reference population Synthetic W7984 (Altar84/ Aegilops tauschii (219) CIGM86.940) x Opata M85, an F(1)-derived doubled haploid population (SynOpDH) of 215 inbred lines and a recombinant inbred population (SynOpRIL) of 2039 F(6) lines derived by single-plant self-pollinations. A linkage map was constructed for the SynOpDH population using 1446 markers. In addition, a core set of 42 SSR markers was genotyped on SynOpRIL. A new approach to identifying a core set of markers used a step-wise selection protocol based on polymorphism, uniform chromosome distribution, and reliability to create nested sets starting with one marker per chromosome, followed by two, four, and six. It is suggested that researchers use these markers as anchors for all future mapping projects to facilitate cross-referencing markers and chromosome locations. To enhance this public resource, researchers are strongly urged to validate line identities and deposit their data in GrainGenes so that others can benefit from the accumulated information.
Drought limits cereal yields in several regions of the world and plant water status plays an important role in tolerance to drought. To investigate and understand the genetic and physiological basis of drought tolerance in barley, differentially expressed sequence tags (dESTs) and candidate genes for the drought response were mapped in a population of 167 F8 recombinant inbred lines derived from a cross between "Tadmor" (drought tolerant) and "Er/Apm" (adapted only to specific dry environments). One hundred sequenced probes from two cDNA libraries previously constructed from drought-stressed barley (Hordeum vulgare L., var. Tokak) plants and 12 candidate genes were surveyed for polymorphism, and 33 loci were added to a previously published map. Composite interval mapping was used to identify quantitative trait loci (QTL) associated with drought tolerance including leaf relative water content, leaf osmotic potential, osmotic potential at full turgor, water-soluble carbohydrate concentration, osmotic adjustment, and carbon isotope discrimination. A total of 68 QTLs with a limit of detection score > or =2.5 were detected for the traits evaluated under two water treatments and the two traits calculated from both treatments. The number of QTLs identified for each trait varied from one to 12, indicating that the genome contains multiple genes affecting different traits. Two candidate genes and ten differentially expressed sequences were associated with QTLs for drought tolerance traits.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.