Progress 08/01/00 to 07/31/04
Outputs
The objectives of the current grant were to test the following three hypotheses: 1.) Factors (QTLs) controlling much of the yield and yield component variation within an environment (E) due to genes on chromosome 3A can be localized and quantified, 2.) QTLs are expressed in both the CNN and WI backgrounds, and 3.)QTL x E interaction is an important effect in populations using adapted cultivars and is sufficiently large that it hinders the identification of QTLs that are expressed across environments. Initially, 11 wheat, 11 barley, six rye, three rice, two oat and two Triticeae consensus maps were used for the comparative mapping in order to identify markers for group 3 chromosomes of wheat. Twenty-six probes were mapped on the RICL population. Sixteen of these markers were used for QTL mapping using the field evaluation data. Ninety-five CNN(RICLs3A) were evaluated in 7 environments (1999-2001) and used for QTL mapping and QTL x environment interaction (QEI) studies.
QTLs were detected for seven of the eight agronomic traits measured (anthesis date (AD), plant height (PHT), grain volume weight (GVWT), grain yield (GYLD), 1000 kernel weight (TKWT), spikes per square meter (SPSM), kernels per spike (KPS), and kernels per square meter (KPSM)). These QTLs were present as clusters in four distinct regions. Region 1 contained QTLs for GYLD, KPSM, PHT, KPS, and TKWT and was present between marker cdo549 and xtam055,xtam61. Region 2 contained QTLs for GYLD and KPSM, and was flanked by markers ksuA6 and Xbcd366, Xcmwg680. Region 3 contained QTLs for GVWT and SPSM and was flanked by Xbcd366, Xcmwg680 and Xbcd155, Xbcd141. Region 4 contained KPS and was flanked by markers bcd1555, Xbcd141 and bcd372. QTL x environment interactions were detected for some QTLs and these interactions were caused by changes in magnitude and by crossover interactions. The QEI was caused by changes in magnitude, wherein the positive effect (+66 kg/ha) of the Wichita QTL allele was
larger in higher yielding environments. This is the first study where we were able to map QTLs for grain yield, most likely due to our having 95 RICLs and using more sophisticated experimental designs (incomplete block designs with four replications). We were unable to determine if the QTLs identified in CNN(RICLs3A) were at the same location in the mirror population, WI(RICLs3A), because we discovered a univalent shift must have occurred early in our WI(RICLs3A) population development and about 40% of the WI(RICLs3A) were unusable (heterozygous, heterogeneous for markers on chromosome 3A). We used a number of different approaches to better understand QEI that include extending the stability concept of Eberhart and Russell (1966) to marker genotypes to integrating weather data and crop models as environmental covariables into the QEI analyses. The former method was useful in describing QTLs, which differed due to changes in magnitude from those due to cross-over interactions. The
latter approach explained relatively little of the total QTL differences and we would not recommend others pursue this avenue of research until better phenological data is taken.
Impacts
This effort is undertaken to develop a better genetic understanding of grain yeild and agronomic traits. It will lead to more efficient breeding strategies and how we approach understadning agronomic performance.
Publications
- Eskridge, K. M., M. M. Shah, P.S. Baenziger and D.A. Travnicek. 2000. Correcting for classification errors when estimating the number of genes using recombinant inbred chromosome lines. Crop Sci. 40:398-403.
- Shah, M. M., Y. Yen, K. S. Gill, and P. S. Baenziger. 2000. Comparisons of RFLP and PCR-Based Molecular Marker Systems to Detect Polymorphism in Wheat. Euphytica 114:135-142.
- Campbell, B. T., P. S. Baenziger, K. S. Gill, K. M. Eskridge, H. Budak, M. Erayman, I. Dweikat, and Y. Yen. 2003. Identification of QTLs and Environmental Interactions Associated with Agronomic Traits on Chromosome 3A of Wheat. Crop Science 43:1493-1505
- Campbell, B.T., P.S. Baenziger, K. M. Eskridge, H. Budak, N.A. Streck, A. Weiss, K.S. Gill, and M. Erayman. 2004. Using environmental covariates to explain genotype x environments and QTL x environment interactions for agronomic traits on chromosome 3A of wheat. Crop Sci.44: 620-627.
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Progress 10/01/02 to 09/30/03
Outputs
In 2002-2003, we continued to finish up our research on the agronomic evaluation of the recombinant inbred lines involving Cheyenne (CNN) and chromosome 3A from Wichita (WI). The lines are designated as CNN(RICLs3A). One manuscript was published on this work and a second manuscript has been accepted. Basically, the first manuscript showed that chromosome 3A had more than one QTL (gene) affecting the traits of interest and the QTLs were affected by the environment, which was expected, but often not found in previous QTL research. These results were important because it helped answer the debate over is yield determined by numerous small genes which are indistinguishable or by a relatively few major genes. In our case, grain yield was determined by a few genes on chromosome 3A. We were fortuitous that all of the positive QTLs for yield were on WI3A, hence could be found in chromosome substitution lines and later in RICLs. It is presumed that many of the chromosomes which
initially did not show any effects on grain yield either did not have genes affecting grain yield or they has beneficial and detrimental genes and the chromosome was effectively neutral. The second manuscript attempted to use growth models, environmental data, and our QTL analyses to determine if we could develop a better understanding of genotype x environmental (G x E) interactions. While we were successful, and the environment could explain much of a few QTL x E interactions, the end result was that environmental variable could explain a significant amount of QTL x E interactions, but that the QTL x E interaction only explained a small part of the QTL effect which also only explained a small part of the amount of trait of interest. It is expected that with better growth and development models that better explanations of QTL x E can be obtained. More closely linked markers and larger populations should help increase the amount of the trait that is explained by the QTL. Future work
is concentrating on developing more CNN(RICLs3A) and WI(RICLs3A) and finding more markers.
Impacts
This effort is undertaken to develop a better genetic understanding of grain yeild and agronomic traits. It will lead to more efficient breeding strategies and how we approach understadning agronomic performance.
Publications
- Campbell, B. T., P. S. Baenziger, K. S. Gill, K. M. Eskridge, H. Budak, M. Erayman, I. Dweikat, and Y. Yen. 2003. Identification of QTLs and Environmental Interactions Associated with Agronomic Traits on Chromosome 3A of Wheat. Crop Science 43:1493-1505.
- Haliloglu, K., and P. S. Baenziger. 2003. Agrobacterium tumefaciens mediated wheat transformation. Cereal Res. Comm.31: 9-16.
- Baenziger, P. Stephen, Mary J. Shipman, Robert A. Graybosch, and Ismail Dweikat. 2003. The integration of biotechnology into plant breeding: promises and products. pp. 111-125. In O.K. Chung and J. L. Steele (ed) Proceedings of the 2nd International Wheat Quality Conference. May 20-24, 2001. Manhattan, Kansas, U.S.A. Grain Industry Alliance, Manhattan, KS
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Progress 10/01/01 to 09/30/02
Outputs
Genetic analyses of complex traits in wheat (Triticum aestivum L.) are facilitated by the availability of unique genetic tools such as chromosome substitution lines and recombinant inbred chromosome lines (RICLs), which allow the effects of genes on single chromosomes to be studied individually. Chromosome 3A of 'Wichita' is known to contain alleles at quantitative trait loci (QTLs) that influence variation in grain yield and agronomic performance traits relative to alleles of 'Cheyenne'. To determine the number, location, and environmental interactions of genes related to agronomic performance on chromosome 3A, QTL and QTL x environment analyses of 98 RICLs-3A were conducted in seven locations across Nebraska from 1999 - 2001. QTLs were detected for seven of eight agronomic traits measured and generally localized to three regions of chromosome 3A. QTL x environment interactions were detected for some QTLs and these interactions were caused by changes in magnitude and
crossover interactions. Major QTLs for kernels per square meter and grain yield were associated with an interval of 5 cM and appeared to represent a single QTL with pleiotropic effects. This particular QTL displayed environmental interactions caused by changes in magnitude, wherein the positive effect of the Wichita QTL allele was larger in higher yielding environments. Efforts are under way to create additional RICLs via doubled haploids in cooperation with CIMMYT. Additional molecular markers are being added to the chromosome map to aid in reducing the region surrounding the QTLs of interest. A univalent shift occurred in the creation of the mirror population [WI(RICLs3A)], which effectively made this population useless, hence we are recreating this population.
Impacts
This research is a critical first step in understanding and eventually cloning the genes that are involved in agronomic performance. This improved understanding will be translated into improved breeding strategies and great crop productivity.
Publications
- Campbell, B. T., P. S. Baenziger, K. S. Gill, K. M. Eskridge, D. Nettleton, M. M. Shah, H. Budak, and M. Erayman. 2001. Genetic analysis of wheat chromosome 3A recombinant inbred chromosome lines for agronomic traits. Agronomy abstracts. American Society of Agronomy, Charlotte, NC.
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Progress 10/01/00 to 09/30/01
Outputs
Our efforts continue to evaluate recombinant inbred chromosome lines (RICLs) for chromosome 3A in Cheyenne (CNN) and Wichita (WI) backgrounds. CNN3A reduces grain yield by 15 percent when it replaces WI3A in WI. WI3A increases grain yield by 15 percent when it replaces CNN3A in CNN. To understand the genes on these important chromosomes, we have tested 98 CNN(RICLs3A) in 7 environments (the final three environments were harvested in 2001). Data analyses from these experiments are continuing. In a mirror image experiment, we have tested WI(RICLs3A) in 1 environment using an augmented design and have planted the WI(RICLs3A) in an additional five environments this year (2001-2002) for data collection in 2002. In addition, we are adding new molecular markers to our chromosome 3A map to develop a denser map so that we can identify quantitative trait loci (QTLs) for grain yield, yield components, plant height, grain volume weight, and earliness per se. Our short term goal
will be to see if the QTLs identified in CNN(RICLs3A) will map to the same locations as inWI(RICLs3A). Our longterm goal is to use our markers and BACs to find and clone genes that control important agronomic traits.
Impacts
An understanding of the genes that control agronomic performance is critical for plant breeding to become more efficient and successful. The cultivars used in this study are the foundation cultivars for most modern cultivars grown in the central Great Plains.
Publications
- Shah, M. M., Y. Yen, K. S. Gill, and P. S. Baenziger. 2000. Comparisons of RFLP and PCR-based molecular marker systems to detect polymorphism in wheat. Euphytica 114:135-142.
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Progress 10/01/99 to 09/30/00
Outputs
This project is a recently funded project that will support an ongoing effort to better understand the genetics of grain yeild and adaptation in hard winter wheat. As part of this effort we have harvested 98 recombinant inbred chromosome lines (RICLS) from four locations, of which three were in the 1999 to 2000 growing season. We have further planted an additional three locations for the 2000-2001 growing season. Hence we will have data from 7 environments to understand how the environment affects quantitative trait loci (QTLs). We continue to identify polymorphic markers among our RICLs for mapping QTLs and to genotype our lines. Using deletion lines, we are physically mapping each polymorphic marker. In addition, we have developed a reciprocal set of RICLS (i.e. the same chromosome, but in a different background) and we planted them in the 2000-2001 growing cycle to begin to obtain field data and to increase seed for future field evaluations.
Impacts
The project was funded in August, 2000, so it is premature to expect an impact of the efforts to date.
Publications
- Shah, M. M., K. S. Gill, P. S. Baenziger*, Y. Yen, S. M. Kaeppler, and H. M. Ariyarathne. 1999. Molecular mapping of loci for agronomic traits on chromosome 3A of bread wheat. Crop Sci. 39: 1728-1732.
- Shah, M. M., Y. Yen, K. S. Gill, and P. S. Baenziger. 2000. Comparisons of RFLP and PCR-based molecular marker systems to detect polymorphism in wheat. Euphytica 114:135-142.
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