|10-710 Project Manager: D. C. Jones|
GENETIC ANALYSIS OF PHYSIOLOGICAL TRAITS CONFERRING HEAT AND DROUGHT TOLERANCE IN COTTON
Michael A. Gore, USDA-ARS
In the past century, high yielding cotton has been adapted to the low desert, irrigated agricultural areas of central Arizona. Despite progress, it will be perhaps a greater challenge to further increase the yield of cotton in this period of global climate change and diminishing fresh water supplies. Genetic improvement of cotton via modern plant breeding is the most sustainable and economical approach to address these eminent problems. However, the development of superior heat tolerant and water-use efficient cotton cultivars has been slowed by a limited knowledge of the key genes and alleles that underlie physiological and developmental mechanisms that relate to improved productivity under high temperatures and water deficit. This project is striving to elucidate the genetic basis of physiological stress responses, productivity, and fiber quality in upland cotton under well-watered and water-deficit conditions through the integration of approaches that cross numerous disciplines.
A genetic mapping population of recombinant inbred lines (RILs) was constructed from the cross of NM24016 with TM1. NM24016 is a stable interspecific line with introgressions from both G. hirsutum and G. barbadense. TM-1 is a genetic standard for G. hirsutum. The TM1 × NM24016 mapping population contains tremendous genetic variability for agronomic and fiber quality traits which could be harnessed for genetic improvement efforts in G. hirsutum. Moreover, this population segregates for a combination of physiological traits from both upland and pima cotton that confer adaptation of cotton to high temperature, arid environments. Thus, the TM1 × NM24016 population is well-suited to evaluate the contribution of physiological traits to enhance productivity and fiber quality under high temperatures and water deficit.
Cotton breeding efforts in the southwestern United States will benefit from a better understanding of the connection between productivity and local adaptation. We conducted the present study to (i) measure the extent of phenotypic variation for physiological traits in the TM1 × NM24016 mapping population with high-throughput methods, and (ii) identify quantitative trait loci (QTL) responsible for quantitative variation of physiological traits that are potentially important for the local adaptation of cotton to the desert southwest.
Subsurface drip irrigation scheduling was performed using a daily soil water balance model calculated for the cotton root zone. Soil water balance inputs included estimated daily evapotranspiration, determined from FAO-56 crop coefficient procedures, metered irrigation depths, and precipitation data obtained from a farm weather station near the field. Irrigations to the well watered plots were applied to refill the root zone water content to field capacity and were given at approximately 35% soil water depletion. Starting on the 6th of July, the water deficit plots received one half of the irrigation amount applied to the well watered plots. The start of the water deficit coincided with the average first flower date of the RIL population. This was done to minimize the interaction of flowering time and water deficit, which can be a confounding factor when attempting to separate the interaction of drought tolerance and maturity. Weekly soil water content measurements to a depth of 1.5-m were made in plots to monitor the actual soil water deletion and adjust the modeled soil water balance when needed. The drip tape was periodically cleansed with Di-Oxy Flush to maintain an optimal water flow rate and equitable distribution of water through emitters.
Similar to the prior two years, visual measurements of days to first flower, nodes above white flower (NAWF), and plant height were recorded with hand-held barcoded phenotyping tools throughout the growing season. Leaf thickness and pollen sterility were measured on all experimental plots several weeks after the initiation of the water deficit. We scored pollen sterility on a scale of 1 (completely sterile) to 5 (completely fertile). In addition, a high-clearance tractor with mounted sensors was used for proximal remote sensing of canopy temperature, spectral reflectance, and height on multiple days with 2-3 data collection runs at different times on most days. The tractor-based proximal remote sensing work is supported by sister project 11-891: "High-Throughput Phenotyping for Time-Related QTL Mapping of Traits Under Supra-optimal Temperatures and Water-limited Conditions," and as such, will be discussed at greater length in its associated technical summary.
All plots were machine-harvested with a one-row harvester. We hand harvested 25-boll samples from each plot for the determination of yield component and fiber traits prior to machine harvest. Fiber samples were sent to Cotton Incorporated for analysis, but 2012 data have not been received. We also collected leaf tissue from all experimental plots to measure the content of chlorophyll a and b (indicator of drought tolerance), total soluble sugar (changes in response to water stress), abscisic acid (plant hormone that mediates the adaption to water deficit), and carbon isotope discrimination (an indirect measure of water-use efficiency). We are in the process of analyzing tissue samples for chlorophyll a and b contents, but are waiting to receive the carbon isotope discrimination data from the UC-Davis Stable Isotope Facility. Next month, we will send tissue samples to a collaborator at Cornell University for measuring the amount of total soluble sugar and abscisic acid.
The population of 95 RILs was genotyped with a set of microsatellite markers and the genotyping-by-sequencing (GBS) protocol of Poland et al. (2012). The JOINMAP software was used to construct a linkage map that consisted of 424 microsatellite and 394 SNP markers. Inclusive composite interval mapping (ICIM) with a Type I error rate of 0.05 will be used for QTL mapping all of the agronomic and physiological traits that have been phenotyped over the past three years.
The mean phenotypic values for most of the traits scored on the RIL population, their parents, and commercial checks were higher for well watered than water deficit plots in 2010, 2011, and 2012. Statistically significant genotypic differences (P<0.05) among the RILs, their parents, and checks were detected for all of the measured traits across the three years. Plant height (P<0.0001) and boll size (P<0.001) had a significant treatment effect (α = 0.05) in 2010, while plant height (P<0.0001), seed per boll (P<0.0001), yield (P<0.0001), boll size (P<0.01), and first flower (P<0.05) had a significant treatment effect (α = 0.05) in 2011. In contrast to 2010 and 2011, only plant height (P<0.05) and seed index (P<0.05) had a significant (α = 0.05) but weak treatment effect. These markedly different year to year results can likely be explained by the unintentional severe drought treatment in 2011 from the clogging of drip tape emitters. Even though the drip tape clogging was resolved midway through the growing season, the phenotypic consequences were still very evident. Furthermore, the excessive rain from the 2012 monsoon season lessened the severity of the water deficit treatment, resulting in only a weak significant treatment effect for plant height and seed index. Interesting, seed index (P<0.05) was only significant—albeit weak—in 2012. Plant height had a significant genotype × treatment interaction across the three years. With the exception of seed index in 2012, none of the other measured traits had a significant genotype × treatment interaction in 2010 or 2011. As previously presented, heritability estimates on a family mean basis for traits measured on the 95 RILs, their parents, and commercial checks were moderate to high for 2010 and 2011, ranging from 0.44 for nodes above white flower (NAWF) to 0.97 for lint percentage. A similar range of heritability estimates were obtained for most of the same traits in 2012; however, uncharacteristically low heritability estimates on a family mean basis (0.06 to 0.33) were obtained for days to first flower, NAWF, and pollen sterility. Given that these traits were visually scored on five randomly plants per plots by mostly first-year phenotypers with no prior field experience, it is not unexpected that these three traits have especially low heritability estimates. If the error variance cannot be reduced through statistical modeling, then data of these traits from 2012 will not be used for QTL mapping. This is not a limitation because the phenotypic data collected in 2011 was moderately-to-highly heritable.
|Project Year: 2012|
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