PeanutMap: an online genome database for comparative molecular maps of peanut

BACKGROUND: Molecular maps have been developed for many species, and are of particular importance for varietal development and comparative genomics. However, despite the existence of multiple sets of linkage maps, databases of these data are lacking for many species, including peanut. DESCRIPTION: PeanutMap provides a web-based interface for viewing specific linkage groups of a map set. PeanutMap can display and compare multiple maps of a set based upon marker or trait correspondences, which is particularly important as cultivated peanut is a disomic tetraploid. The database can also compare linkage groups among multiple map sets, allowing identification of corresponding linkage groups from results of different research projects. Data from the two published peanut genome map sets, and also from three maps sets of phenotypic traits are present in the database. Data from PeanutMap have been incorporated into the Legume Information System website to allow peanut map data to be used for cross-species comparisons. CONCLUSION: The utility of the database is expected to increase as several SSR-based maps are being developed currently, and expanded efforts for comparative mapping of legumes are underway. Optimal use of these data will benefit from the development of tools to facilitate comparative analysis

Identification of several small main-effect QTLs and a large number of epistatic QTLs for drought tolerance related traits in groundnut (Arachishypogaea L.)

Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 × ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2–3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48–33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3–15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54–44.72% PVE) and 63 (7.11–21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7–8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2–9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut

Progress and Variability After Four Cycles of Recurrent Selection in Peanut1

Abstract Recurrent selection procedures are becoming more popular as a means of population improvement in self-pollinated crops. Four cycles of recurrent selection for yield in a broad-based peanut (Arachis hypogaea L.) population have been completed. The objectives of this study were to determine (a) progress made after four cycles of recurrent selection for fruit yield and (b) if sufficient variability remained in the population to permit further improvements in yield from additional cycles of selection. The 40 highest yielding lines from 100 random-paired matings, were intercrossed to produce each successive cycle, resulting in a selection intensity of 40%. Bulked seed of the parental lines from each cycle were evaluated for yield to determine progress made after four cycles of selection. The observed variation in yield among entries was mainly due to differences among cycle means. Differences among cycle means were also detected for pod length, but not for any of the other fruit traits measured. The response to selection for yield was linear with a significant (p = 0.01) and positive regression coefficient (b = 190.7 kg ha-1). Selection based on fruit yield did not significantly change the means for any of the fruit traits measured. Significant estimates of genetic variability among entries within the cycle 4 population for yield and all fruit traits measured suggest that continued progress from additional cycles of selection should be expected in this population. Greater progress from selection may have resulted had a higher selection intensity been applied. However, estimates of genetic variability would be expected to decrease with each cycle of selection as the selection intensity increases and as the genetic base of the original population narrows. In the use of a broad-based population and a relatively low selection intensity, we chose to accept a lower rate of progress/cycle for yield in order to maintain a greater level of genetic variability within the recurrent selection population.</jats:p

Soil carbon and plant richness relationships differ among grassland types, disturbance history and plant functional groups

AbstractUnderstanding the relationship of soil carbon storage and species diversity in grasslands can provide insights into managing these ecosystems. We studied relationships among soil C and plant species richness within ~ 9700 ha of grasslands in Colorado, US. Using 141 grassland transects, we tested how soil C was related to plant species richness, grassland type, soil texture, and prairie dog presence. Soil C was significantly, positively related to plant species richness, while native perennial graminoid species richness exhibited an even stronger positive relationship. However, the relationship of soil C and plant richness was not found in all three grassland types studied, but instead was unique to the most common grassland type, mixed grass prairie, and absent from both xeric tallgrass and mesic tallgrass prairie. The presence of a single indicator species, Andropogon gerardii, showed a significant, positive relationship with soil carbon. Our best possible model explained 45% of the variance in soil C using species richness, grassland type, and their interaction. Surprisingly, soil C was negatively related to soil clay, suggesting that surface clays amplify evaporation and water runoff rather than protecting soil organic matter from decomposition. Soil C was negatively related to prairie dog presence, suggesting that prairie dogs do not enhance soil carbon sequestration; in fact, prairie dog occupied sites had significantly lower soil C, likely related to loss of topsoil from prairie dog colonies. Our results suggest that management for species richness provides the co-benefit of soil C storage, and high clay and prairie dog disturbance compromises both.</jats:p

The Effectiveness of Early Generation Testing as Applied to a Recurrent Selection Program in Peanut1

Abstract The effectiveness of early generation testing for yield improvement in peanut (Arachis hypogaea L.) was evaluated in an attempt to increase the efficiency of an on-going recurrent selection program by reducing the time required for evaluation and selection. The objectives of the study were to (1) determine if the number of years required per cycle of selection could be reduced; and (2) estimate the amount of genetic variability remaining in the population for yield and four agronomic traits after four cycles of recurrent selection. Sixty-eight random-mated crosses, among the 40 highest yielding lines from the cycle 3 population, were evaluated for yield and agronomic traits in 1985 (S0:1), 1986 (S0:2), and 1987 (S0:3). The results were compared to determine if early generation performance accurately predicts the performance of cross bulks in later generations. No significant correlations were found for yield of entries in the S0:3 and S0:2 or in the S0:3 and S0:1; however, there was a significant correlation between yield of entries in the S0:2 and S0:1 generations. No correlations were found between yield and any of the agronomic traits measured in the S0:3; however, significant correlations were found in the S0:2 between yield and most traits measured. Significant correlations were also found for entries in the S0:3 and S0:2 generations for each agronomic trait measured except number of seed per 20 pods. Early generation testings appears to be useful for selection of certain agronomic traits, but of limited value when selecting for yield. A decrease in genetic variation for yield in the population from the S0:1 to the S0:3 generation was observed; however, the number of crosses equal to or exceeding the yield of the check cultivar increased in later generations. All agronomic traits measured, except number of seed per 20 pods, showed significant genetic variation remaining in the population in both the S0:2 and S0:3 generations. The greater the genetic variation remaining in the population for a given trait, the more likely it is that further improvement of that trait will be realized with additional cycles of selection.</jats:p