Progress 12/01/16 to 11/30/20
Outputs
Target Audience:Global wheat research community including wheat breeding and genetics program in the USA. Students, post-docs, research scientists working in plant breeding, genetics and genomics Academic and research community of US and around the world. Representative for food industry globally. Agricultural extension personnelwithin USA and globally. Changes/Problems:Nothing to report What opportunities for training and professional development has the project provided?Bethany Love (PhD student at Nottingham University) and Dipedndra Shahi at UFL work on this project and completed PhD. Dr. Jia Guo, post-doc at University of Florida, was responsible for phenotyping of two DH bi-parental populations for marker validation and KASP assay development.Intern students, Ida Vandamme and Paula Glusberger, and student worker Jordan Mc McBreen, Smita Rayamajhi and PhD student Jahangir Khan were alsotrained through the project at UF. A post-doc fellow, Dr. Zhao Liu, has been hired to perform work on this project (developing KASP assay, validation, allelic variation, etc) at wheat genotyping lab, Manhattan, Kansas. How have the results been disseminated to communities of interest?The results were presented in PAG2019, CSSA conference, and IWYP meetings.Results were presented to different industryrepresentatives in 2020. Several papers are published in peer reviewed journals andsevreal manuscripts are underprocessing for publications. What do you plan to do during the next reporting period to accomplish the goals?Nothing to report
Impacts
What was accomplished under these goals?
Objective 1: Two association panels (236 US soft red facultative wheat panelat UFL and 150 spring wheat lines with high biomass known as Hi-BAP II at the CIMMYT IWYP Hub, Ciudad Obregon) were characterized for physiological traits that determine spike and stem partitioning, fruiting efficiency (FE), HI, above ground biomass, and grain yield (GY). Hi-BAP II: GY,HI andabove-ground dry matter at A+7 days showed wide genetic variation.GY showed positive significant association with above ground DM(0.39), HI (0.28) and TGW (0.10) There was also a trade-off between AGDMand HI (-0.33). Spike PI (SPI) was positively associated with spike DMA+7 (0.60), HI (0.55) and GY (0.21). FE showed significant positive associated with grains m-2 (0.63). There was a negative association between SPI and stem internode 2 length (R2=0.08) and the peduncle length (R2=0.03). Conversely, stem internode length was positively associated with SPI for each internode. US Soft wheat panel: GY, biomass and HI values showed significant genetic variation among genotypes. GY showed significant positive associations with AGDM (0.18), HI (0.60), grain number (0.82), and grain weight (0.14). SPI was positively associated with GY (0.28), HI (0.29) and grains m-2 (0.23). SPI had strong negative association with stem PI (-0.60), and lamina PI (-0.40). SPI also showed strong negative association with I2L (-0.20), I3L (-0.23), I2PI (-0.19), and I2PI (-0.24). Reduced I2L and I2PI demonstrated significant correlation with increased grain yield (-0.14 to -0.18), HI (-0.22 to -0.20), and grain number (-0.16 to -0.12). Increased HI was also associated with I3L (-0.19) and I3PI (-0.24). FE showed strong association with GY(0.32), HI (0.35) and grains m-2 (0.47). The results indicate that genetic manipulation of FE could potentially increase HI and yield potential in wheat. The results suggest that genotypes with a decreased internode 2 or 3 length compete less with the spike for assimilate at A+7d and is related to increased HI and grains per m2. GWAS analysis: HIBAP II panel: The GWAS analysis was carried out for grain partitioning and spike hormone traits. Over 40 significant markers associated with different traits were identified. Novel markers for spike cytokinin levels at anthesis associated with grain number traits were identified on 2B and 5D. In addition, novel markers for spike levels of the cytokinin precursors isopentenyl adenosine at anthesis were identified on 1B and 3A. US soft wheat panel: GWAS analysis for 12 traits we studied, revealed 130 MTAs distributed across all 21 chromosomes with phenotypic variance explained (PVE) ranging from 4.65 to 16.72 percent. The GWAS analysis identified a total of 22 MTAs for HI, 33 for I3L, 26 for I3PI, 23 for GY, 18 for biomass, 23 for SPI, and 23 for I2L. Eight pleiotropic loci associated with HI, GY, GN, SPI, and TSPI were detected. GY shared pleiotropic marker with HI on chromosome 1A (S1A_41734769), with GN on chromosome 2A (S2A_14302507), chromosome 2D (S2D_70080067) and chromosome 4B (S4B_14543867). 3 MTAs detected with pleiotropy between SPI and TSPI on chromosome 5A (S5A_437344490, S5A_441478636 and S5A_441478661). KASP marker development and validation: A total of 61 KASP markers associated with phenotypic traits were developed. 290 bi-parental lines were genotyped using 49 KASP markers. A total of 238 diversity lines (facultative and spring lines) were genotyped using all 61 KASP markers. For bi-parental populations, KASP marker S2D_68734015 showed significant allelic effect on I2&3 PI and I2PI. Genotypes with "C" allele on S2D_68734015 marker showed 2.6% increase in internode 2 and 3 partitioning compared to genotypes with "G" allele. A KASP assay was developed for the SNP marker for FE on chromosome 1B (AX-94980956) identified in BiBAP I and validated in a bi-parental population at University of Florida phenotyped for FE. For the diverse population panel, a total of 18 KASP markers showed significant allelic effect on 9 different phenotypic traits. Most notably, genotypes with allele "C" for marker S4B_13299920 and S4B_12533949ed showed an 14.7% and 11.9%increase for grain m-2 compared to genotypes with allele "T" and "C". Genotypes with allele "C" for marker S3D_295967307 showed an 13.1% increase for FE compared to genotypes with allele "T". Genotypes with allele "G" on marker S4A_609462220 showed a 9.7% increase for HI compared to genotypes with allele "A". Genotypes with allele "A" on marker S6D_24028817 showed an 13.9% increase for TGW compared to genotypes with allele "G". Genotypes with allele "C" on marker S3A_727396932 showed an 13.1% increase for GY compared to genotypes with allele "T". ?Objective 2: Two diversity panels were evaluated at the CIMMYT IWYP Hub consisting on Primary Synthetic Panel (n=160) and a subset of Bread Wheat Diversity Panel. A 241 diverse US wheat panel was characterized for partitioning traits at Florida.Significant correlations were found between grain yield and yield component traits such as GM2, I2L, and I2PI. Genetic variation was identified for HI in both panels while no trade-off between above ground biomass and HI was identified for BW Diversity Panel. Regarding partitioning traits in both panels, FE and spike partitioning index, were positively correlated with HI, while Stem+Lamina partitioning index, and the lengths of internodes 2 and 3 were negatively correlated. Objective 3: In the HiBAP II, a more detailed analysis was carried out on a subset of 30 genotypes of thepartitioning (peduncle, internode 2 internode 3 and internode 4+) and spike morphological DM partitioning (glume, palea, lemma, awns and rachis) at GS65+7d. The correlations between the within-spike partitioning indices (glume, palea, lemma, rachis, awn) at GS65+7d and FE, grains m-2 and HI showed a weak trend for lower palea DM partitioning to be associated with increased FE and also a trend for lower palea partitioning to be associated with increased grains m-2 (r = -0.52). A detailed analysis was carried out on a subset of 20 genotypes (10 US soft wheat and 10 CIMMYT spring wheat) wheat panel of true-stem (TS) and leaf-sheath (LS) internode DM partitioning (peduncle, internode 2 and internode 3) and spike morphological DM partitioning (glume, palea, lemma, awns and rachis) at Florida. There were positive associations between FE and DM partitioning of different components (glumes, lemma, palea PIs). This likely reflected that overall smaller spikes and spike growth was associated with higher FE. Spike plant hormone levels and correlations with grain partitioning traits in a HiBAP II in glasshouse and field experiments: For a subset of 10 HiBAP II lines, three glasshouse experiments have been carried out at Nottingham Universityto investigate genetic variation in spike fertility traits and grain number and associations with spike plant hormone levels. The spike samples for hormonal profiling were collected in the central spikelets in the main shoot at GS49 (late booting) and anthesis (GS65) and analyzed for plant hormone profiles using liquid chromatography coupled to electrospray ionization tandem spectrometry (UPLC/ESI-MS/MS).Some plant hormones showed a large change between stages, e.g., IAAhad a much lower level at GS49 than GS65, as did SA. For most hormones the pattern followed between GS49 and GS65 is similar in the individual years. For example, ABAlevels are consistently higher at GS49 by approximately 100% compared to at GS65. Similarly, for both cytokinins zeatin (Z) and zeatin riboside (Zr), levels were lower at GS49 than at GS65. Cross-year analysis of the hormones showed genotype had a significant effect on all hormones at GS49 except ABA and isopentenyladenine (2iP). However, at GS65, genotype was only significant for 2iP, ABA, IAA and SA. The genotype x year interaction was significant for all hormones at GS49 except ABA and JA, and for all at GS65 except GA1, IPA and SA.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Sierra-Gonzalez, A. Molero G, Rivera-Amado C, Babar MA, Reynolds MP, Foulkes J. 2021. Exploring genetic diversity for grain partitioning traits to enhance yield in a high biomass spring wheat panel. Field Crops Research. 260 (107979).
Guo J, Khan J, Pradhan S, Shahi D, Khan N, Avci M, Mcbreen J, Harrison S, Brown-Guedira G, Murphy JP, Johnson J, Mergoum M, Esten Mason R, Ibrahim AMH, Sutton R, Griffey C, Babar MA. Multi-Trait Genomic Prediction of Yield-Related Traits in US Soft Wheat under Variable Water Regimes. Genes. 2020; 11(11):1270. https://doi.org/10.3390/genes11111270
Guo J, Pradhan S, Shahi D, Khan J, Mcbreen J, Bai G, Murphy JP, and Babar MA. 2020. Increased Prediction Accuracy Using Combined Genomic Information and Physiological Traits in A Soft Wheat Panel Evaluated in Multi-Environments. Scientific Reports-Nature. 10(1):1-12. (* co-first author; ppost-doc; ggraduate student) (IF=4.120)
Pradhan S, Babar MA, Bai G, Khan J, Shahi D, AVCI M, Guo J, McBreen J, Asseng S, Gezan S, Baik B, Blount A, Harrison S. 2020. Genetic Dissection of Heat-responsive Physiological Traits to Improve Adaptation and Increase Yield Potential in Soft Winter Wheat. BMC Genomics. BMC Genomics. 21:315.
Pradhan S, Babar MA, Guo J, Bai G, Mergoum M, Mason RE, Gazen S, Asseng S, Blount A, Baik B, Shahi D, Khan J, Hossain MM, Avci M, and Robbins K. 2019. Identifying novel alleles associated with spike fertility, gain number and harvest index under hot and humid environment in wheat through GWAS analysis. Frontiers in Plant Science. 10:1481.
Zhenqi Su, Sujuan Jin, Dadong Zhang, Guihua Bai. 2018. Development and validation of diagnostic markers for Fhb1 region, a major QTL for Fusarium head blight resistance in wheat. Theor Appl Genet https://doi.org/10.1007/s00122-018-3159-6
Guihua Bai, Zhenqi Su and Jin Cai. 2018. Wheat Resistance to Fusarium Head Blight. Can J. Plant Pathol (Online)https:/doi.org/10.1080/07060661.2018.1476411
M. Shao, G. Bai, T. W. Rife, J. Poland, M. Lin, S. Liu, H. Chen, T. Kumssa, A. Fritz, H. Trick, Y. Li, G. Zhang. 2018. QTL mapping of pre harvest sprouting resistance in a white wheat cultivar Danby. Theor. Appl. Genet. 131:1683-1697.
Na Liu, Guihua Bai, Meng Lin, Xiangyang Xu, Wenming Zheng. 2017. Genome-wide Association Analysis of Powdery Mildew Resistance in U.S. Winter Wheat. Sci Rep. | 7: 11743 | DOI:10.1038/s41598-017-11230-z
Hadi Ali Pour, M.R. Bihamta, V. Mohammadi, S.A. Peyghambari, G.H. Bai and G.R. Zhang. 2017. Genotyping-bysequencing (GBS) revealed molecular genetic diversity of Iranian wheat landraces and cultivars. Front. Plant Sci. | doi: 10.3389/fpls.2017.01293
- Type:
Conference Papers and Presentations
Status:
Submitted
Year Published:
2018
Citation:
Love B, Sierra Gonzalez AS, Rivera Amado CR, Munnes-Bosch S, Babar MA, Molero G, Reynolds M and J Foulkes. 2019. Raining yield potential through improved harvest index and fruiting efficiency associated with plant hormone signaling in high biomass CIMMYT spring wheat genotypes. 1st International Wheat Congress, July 21-26, Saskatoon, Saskatchewan, Canada.
Shahi D, Khan J, Avci M, Shrestha SP, Guo J, Hossain MM, Islam AFMS, Bai G, Reynolds M, Molero G, Sukumaran S, Foulkes J, Mason E and Babar MA. 2019. Identifying novel alleles contributing increased spike partitioning index and fruiting efficiency at anthesis plus 7 days in US soft wheat through genome wide association study. Plant and Animal Genomics Conference XXVII, Juanuary12-16, San Diego, CA.
Guo J, Shahi D, Shrestha SP, Khan J, Hossain MM, Islam AFMS, Bai G and Babar MA. 2019. Genomic Selection for Predicting Spike Fertility and Biomass Partitioning Traits Using Multiple Soft Wheat Populations. Plant and Animal Genomics Conference XXVII, Juanuary12-16, San Diego, CA.
Guo J, Shahi D, Pradhan SP, Khan J, Islam S, Hossain MM, Bai G and Babar MA. 2018. Genomic Selection for Predicting Spike Fertility and Biomass Partitioning Traits using multiple soft Wheat Populations. Florida Genetic Symposium. Oct 31-Nov1, UF Cancer & Genetics Research Complex Atrium.
Shahi D, Khan J, Avci MI, Shrestha SP, Guo J, Hossain MM, Bai G, Islam S Babar MA. 2018. Genome Wide Association Studies of Stem and Spike partitioning traits in Spring Wheat (Triticum aestivum L.). Florida Genetic Symposium. Oct 31-Nov1, UF Cancer & Genetics Research Complex Atrium.
Shahi D, Khan J, Avci MI, Shrestha SP, Rahman A and Babar MA. 2018. Advancing Harvest Index in Wheat through Genome Wide Association Analysis of Stem and Spike partitioning traits. ASA, CSSA International Conference International Conference, Nov 4-7, 2018, Baltimore, MD.
Shrestha SP, Khan J, Avci M, Shahi D, Guo J, Rahman A, Bai G, Asseng A and Babar MA. 2018. Identifying Genetic Loci for Traits to Improve Wheat Yield and Grain Number under Post-Anthesis Heat Stress Conditions. ASA, CSSA International Conference International Conference, Nov 4-7, 2018, Baltimore, MD.
Sierra-Gonzalez A, Molero M, Reynolds MP, Rivera-Amado C, Pi�era-Chavez FJ, Joynson R, Hall A, Foulkes MJ, Sukumaran S. 2019. Genetic analysis of physiological traits to increase grain partitioning in high biomass elite spring wheat lines. Abstracts Plant and Animal Genome Conference XXVII 12-17 January 2019 (2019) San Diego, USA.
|
Progress 12/01/19 to 11/30/20
Outputs
Target Audience:Global wheat research community including wheat breeding and genetics program in the USA. Students, post-docs, research scientists working in plant breeding, genetics and genomics Academic and research community of US and around the world. Representative for food industry globally. Agricultural extenion personnell within USA and globally. Changes/Problems:No changes have been made. The project will be completed in the scheduled time. What opportunities for training and professional development has the project provided? Bethany Love (PhD student registered Nottingham University) who started on the project on 1 August 2017 has continued with her PhD study during the project reporting year. She is full time on the NIFA-IWYP project. In the last reporting year she has carried out: (i) data analysis of year 1 field phenotyping data in the HiBAP II panel and of physiological and spike hormone concentration data in the glasshouse experiment in 2017 from October to December 2017, (ii) field phenotyping of grain partitioning traits in the HiBAP II panel while based at CIMMYT CENEB Ciudad Obregon, Mexico from February to May 2018 and (iii) a glasshouse experiment on a subset of 10 HiBAP lines investigating associations between spike hormone concentrations and spike fertility and grain partitioning traits from June to September 2018 (experiment is ongoing) at Nottingham University under Objectives 1-3 as outlined in the proposal. Dr. Jia Guo, post-doc at University of Florida, is responsible for phenotyping of two DH bi-parental populations for marker validation and KASP assay development. Dr. Guo characterized 300 wheat genotypes for different partitioning traits in Florida. He will also characterize 250 wheat panel for different partitioning traits in 2018-19 in Florida. Dipendra Shahi is a Ph.D. student started on the project from Nov of 2016. He is full time on the project for phenotyping of association panel. Dipendra is funded through University of Florida. His responsibility is aligned with objectives 1 and 3 in the proposal. Intern students, Ida Vandamme and Paula Glusberger, and student worker Jordan Mc McBreen, Smita Rayamajhi were also trained through the project at UF. A post-doc fellow, Dr. Zhao Liu, has been hired to perform work on this project (developing KASP assay, validation, allelic variation, etc). Dr. Liu is location at wheat genotyping lab, Manhattan, Kansas. How have the results been disseminated to communities of interest?The results were presented in PAG, 2019 and IWYP meeting, Mexico. Also results were presented to different industry representatives in 2020. Several papers are published in peer reviewed journals and also sevreal manuscripts are under processing for publications by Ph.D. students and Post-Docs. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Objective 1: Phenotypic results 2-year means of HiBAP II panel 2017- 18 and 2018-19 Field experiments were carried out at CIMMYT, Ciudad Obregon in 2017-18 and 2018-19 on the CIMMYT High Biomass Association Panel (HIBAP II). Averaging over both years, grain yield ranged form 485-716 g m-2 and harvest index (HI) from 0.40 to 0.53 (P<0.001) amongst the 150 genotypes, and there was wide genetic variation in the above-ground dry matter at both anthesis+7 days (733-1177gm-2, P<0.001) and physiological maturity (1043-1522 gm-2, P<0.001). Grain yield showed a positive linear association with above ground DMPM (R2= 0.39, P<0.001), harvest index (R2=0.28, P<0.001) and thousand-grain weight (R2= 0.10, P<0.001). There was also a trade-off between AGDMPM and HI (r=-0.33, P<0.001). Spike PI was positively associated with spike DMA+7 (r=0.60, P<0.001), HI (r=0.55, P<0.001) and grain yield (r=0.21, P<0.05) but not with grains per m2 (r=-0.001, ns). Fruiting efficiency (grains per unit spike DM at GS65+7d) was strongly positively associated with grains per m2 (r=0.63, P<0.001). There was a negative association between spike PI and stem internode 2 length (R2=0.08, P<0.001) and the peduncle length (R2=0.03, P=0.03). Conversely, stem internode length was positively associated with stem PI for each internode (P<0.05). Stem internode length 3 was also negatively associated with lamina PI (R2=0.05, P=0.007). HIBAP GWAS analysis in HIBAP I panel Priority traits for marker development include FE, SPI, internode 2 and 3 lengths, HI, grains m-2 and grain yield. SNP markers were generated using the 35K Wheat breeders array (Affymetrix, United States). Twenty eight significant markers associated with different traits were identified. A KASP assay was developed for the SNAP marker for fruiting efficiency on chromosome 1B (AX-94980956) by Dr Bai at USDA, KSU and validated in a bi-parental population at University of Florida phenotyped or FE. HIBAP II panel The HIBAP II population has been genotyped for SNP markers using an enrichment capture probe set mapped to the Refseq-v1.0 reference sequence (IWGS, 2018) through collaboration with Prof Anthony Hall at Earlham Institute, Norwich, UK. The genotyping information was provided to our project in October 2020. The GWAS analysis for the HIBAP II grain partitioning phenotyping data sets in 2017-18 and 2018-19 is currently ongoing and results will be included with the project final report. KASP marker development and validation: A total of 61 Kompetitive Allele-Specific PCR (KASP) markers associated with phenotypic traits were developed based on the results of previously conducted GWAS analysis (GWAS markers with high heterozygosity was discarded: >10%). A total of 290 bi-parental lines were genotyped using 49 KASP markers. A total of 238 diversity lines (facultative and spring lines) were genotyped using all 61 KASP markers. A total of 16 markers showed significant allelic effect on interested traits including GY, FE, HI, TGW, Grain/m2, SPI, IN2_PI, IN3_PI, and IN2_3_PI. Facultative line with combinations of allele types for GY, HI, and IN2_PI showed significant differences in the diversity panel (Figure 1). A degree of additive effect was shown for marker S1B_636796017, S3A_727396932, S4A_609462220, S7A_106952238, S2D_63397906, S2D_63397962, and S5B_479718074. Allelic effect, indicated by percentage of value change comparing lines with two types of alleles, were presented in table 2. The allelic effect ranged between 5.6% and 20.4% on targe traits. A pleiotropic or linkage pattern was shown for most of the significant markers identified in our study. For example, S4A_609462220 had significant allelic effect on HI, G/m2, GY, and IN2_wt in the facultative panel. Gene annotation using GrainGene database revealed association between KASP marker and different classes of proteins encoding genes. Annotated Protein family/domain associated with each marker was also identified. WTop 30 facultative lines were identified based on the allele types of significantly associated KASP markers. We also identified wifferent wheat lines wigth postive KASP markers for GY, TGW, G/m2, HI, SPI, and FE. Valuable facultative wheat lines can be selected from this study in future breeding programs. Objective 2: As reported in last year's report for CIMMYT diversity panels (BW Diversity, subset of 100 lines and primary synthetic, 160 lines) showing genetic variation for FE, HI, AGDM, GY.A 241 diverse US wheat panel were characterized for partitioning traits at North Florida Research and Education Center (NFREC), Quincy, FL and plant science research and education center (PSREU), Citra, FL, during 2018 to 2019. Significant correlations were found between grain yield and yield component traits such as GM2, IN2_L, and IN2_P. Genetic variation was identified for HI in both panels while no trade-off between above ground biomass and HI was identified for BW Diversity Panel. Regarding partitioning traits in both panels, FE and spike partitioning index, were positively correlated with HI while Stem+Lamina partitioning index, and the lengths of internodes 2 and 3 were negatively correlated. Objective 3: ?For the detailed spike morphology partitioning traits on the subset of 10 genotypes, there were fewer correlations with FE and HI compared to the stem internode partitioning traits. There was no association between any of the spike morphology partitioning indices or rachis specific weight and fruiting efficiency calculated using the spike dry weight at anthesis (FEA+7, Table 5). However, when fruiting efficiency was calculated using chaff weight at physiological maturity (FEchaff), rachis specific weight was negatively associated (R2=0.30, P=0.063), and lemma PI was positively associated with FEchaff (R2=0.28, P=0.077).Also, there was a positive correlation between each of palea PI (r=0.5, P<0.1) and rachis specific weight (r=0.65, P<0.05) with thousand-grain weight. Spike PI was positively correlated with awn PI (r=0.51, P<0.1), but negatively with rachis specific weight (r=-0.57, P<0.1). Finally, spike DM per unit area at anthesis was positively associated with rachis specific weight (r=0.68, P<0.05). Spike plant hormone levels and correlations with grain partitioning traits in a HiBAP II in glasshouse and field experiments For a subset of 10 HiBAP II lines, three glasshouse experiments have been carried out at Nottingham University (harvested in November 2017, October 2018 and October 2019) to investigate genetic variation in spike fertility traits and grain number and associations with spike plant hormone levels. The spike samples for hormonal profiling were collected in the central spikelets in the main shoot at GS49 (late booting) and anthesis (GS65) and analyzed for plant hormone profiles using liquid chromatography coupled to electrospray ionization tandem spectrometry (UPLC/ESI-MS/MS) by Prof Munné-Bosch, University of Barcelona. Some plant hormones showed a large change between stages, e.g., auxin Indole-3-acetic acid (IAA) had a much lower level at GS49 than GS65, as did salicylic acid (SA). For most hormones the pattern followed between GS49 and GS65 is similar in the individual years. For example, abscisic acid (ABA) levels are consistently higher at GS49 by approximately 100% compared to at GS65. Similarly for both cytokinins zeatin (Z) and zeatin riboside (Zr), levels were lower at GS49 than at GS65. Cross-year analysis of the hormones showed genotype had a significant effect on all hormones at GS49 except ABA and isopentenyladenine (2iP). However, at GS65, genotype was only significant for 2iP, ABA, IAA and SA. The genotype x year interaction was significant for all hormones at GS49 except ABA and JA, and for all at GS65 except GA1, IPA and SA.?
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Jia Guo, Jahangir Khan, Sumit Pradhan, Dipendra Shahi, Naeem Khan, Muhsin AVCI, Guo J*P, Khan J*g, Pradhan S, Shahi D, Khan N, AVCI M, McBreen J, Harrison S, Brown-Guedira G, Murphy JP, Johnson J, Mergoum M, Mason RE, Ibrahim A, Sutton R, Griffey C, and Babar MA. 2020. Multi-trait genomic prediction of yield-related traits in US soft wheat under variable water regimes. Genes. 11(11):1270.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2020
Citation:
Sierra-Gonzalez A, Molero G, Rivera-Amado C, Babar MA, Reynolds M, Foulkes J. 2020. Exploring genetic diversity for grain partitioning traits to enhance yield in a high biomass spring wheat panel. Field Crops Research. 260. 107979. https://doi.org/10.1016/j.fcr.2020.107979.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2020
Citation:
Guo JP, Shahi D, Shrestha SP, Khan J, Hossain MM, Islam AFMS, Bai G and Babar MA. 2020. Genomic Selection for Predicting Spike Fertility and Biomass Partitioning Traits Using Multiple Soft Wheat Populations. Plant and Animal Genomics Conference XXVII, Juanuary12-16, San Diego, CA.
|
Progress 12/01/18 to 11/30/19
Outputs
Target Audience:Global wheat research community including wheat breeding and genetics program in the USA. Students, post-docs, research scientists working in plant breeding, genetics and genomics Academic and research community of US and around the world. Representative for food industry globally. Agricultural extenion personnell within USA and globally. Changes/Problems:There will be no major changes in the approach to achieve the goals of the project. What opportunities for training and professional development has the project provided?Bethany Love (PhD student registered Nottingham University) who started on the project on 1 August 2017 has continued with her PhD study during the project reporting year. She is full time on the NIFA-IWYP project. In the last reporting year she has carried out: (i) data analysis of year 1 field phenotyping data in the HiBAP II panel and of physiological and spike hormone concentration data in the glasshouse experiment in 2017 from October to December 2017, (ii) field phenotyping of grain partitioning traits in the HiBAP II panel while based at CIMMYT CENEB Ciudad Obregon, Mexico from February to May 2018 and (iii) a glasshouse experiment on a subset of 10 HiBAP lines investigating associations between spike hormone concentrations and spike fertility and grain partitioning traits from June to September 2018 (experiment is ongoing) at Nottingham University under Objectives 1-3 as outlined in the proposal. Dr. Jia Guo, post-doc at University of Florida, is responsible for phenotyping of two DH bi-parental populations for marker validation and KASP assay development. Dr. Guo characterized 300 wheat genotypes for different partitioning traits in Florida. He will also characterize 250 wheat panel for different partitioning traits in 2018-19 in Florida. Dipendra Shahi is a Ph.D. student started on the project from Nov of 2016. He is full time on the project for phenotyping of association panel. Dipendra is funded through University of Florida. His responsibility is aligned with objectives 1 and 3 in the proposal. Intern students, Ida Vandamme and Paula Glusberger, and student worker Jordan Mc McBreen, Smita Rayamajhi were also trained through the project at UF. A post-doc fellow, Dr. Zhao Liu, has been hired to perform work on this project (developing KASP assay, validation, allelic variation, etc). Dr. Liu is location at wheat genotyping lab, Manhattan, Kansas. How have the results been disseminated to communities of interest?The results were presented in PAG, 2018 and IWYP meeting, Mexico What do you plan to do during the next reporting period to accomplish the goals? The PhD student Bethany Love,and Dr John Foulkes will contribute to the work activities in year 3 in Objectives 1-3 as outlined the proposal. It is expected that PhD student Aleyda Sierra will publish the GWAS results for the HiBAP I during 2019-20. Dr. Gemma Molero, and Matthew Reynolds will contribute to the activities in year 3 in objectives 1-3 at CIMMYT IWYP Hub. Dr. Md Ali Babar, Post-doc Dr. Jia Guo and Graduate student Dipendra Shahi will contribute to the work activities in year 4 in Objectives 1-3 as outlined in the proposal at university of Florida. Dr. Guihua Bai and Dr. Zhao Liu will contribute to the work activities related to marker validation and identify different alleles that influence partitioning traits. No changes have been made to the project milestones and deliverables. However, the collaboration with A. Hall (IWYP 64) and IWYP Hub have facilitated the evaluation of two high biomass panels, HiBAP I and HiBAP II. •
Impacts
What was accomplished under these goals?
Objective 1: Two association panels (one panel at UFL, Gainesville and another panel at the CIMMYT IWYP Hub, Ciudad Obregon) were characterized for physiological traits that determine spike, lamina, and stem partitioning, fruiting efficiency, HI, above ground biomass, and grain yield. The HiBAP II (High Biomass Association Panel II) panel with high biomass was characterize for different partitioning traits at the International Maize and Wheat Improvement Center (CIMMYT) experimental station in Mexico. CIMMYT, Ciudad Obregon in 2017-19. Hi-BAP II: Field experiments were carried out at CIMMYT, Ciudad Obregon in 2017-18 and 2018-19. Overall yields ranged from 476 to 722 g m-2 (P<0.001) in Y17-18 and 494 to 743 g m-2 in Y18-19 and for HI from 0.41-0.54 and 0.40 to 0.51, respectively (P< 0.001; Table 1). Results showed genetic variation in all the partitioning traits measured at GS65+7d and physiological maturity. For the 2-year combined means, strong phenotypic correlations were found amongst genotypes between grain yield and AGDM (r =0.63***) and HI (r = 0.52***). There was strong a trade-off between AGDM and HI (r = -0.33***). There was an association between enhanced HI and reduced stem partitioning index (spike DM / above-ground DM at anthesis + 7 days; SPI) (r = -0.49***) and reduced length of stem internode 3 (peduncle -2) (r = -0.26**). Stem PI and lamina PI were each negatively associated with SPI (P< 0.001). Fruiting efficiency (grains per unit spike DM and anthesis +7days) was positively associated with grains m-2 (r = 0.35**) and HI (r = 0.17*). Spike PI also showed a trend for a positive associati on with grains m-2 (r = 0.15, P< 0.10). The results from phenotypic analysis suggest that genotypes with a decreased internode 3 length compete less with the spike for assimilate at GS65+7d and this is related to increased HI and grains per m2. Genotypes with a higher fruiting efficiency were also strongly correlated with higher HI and grains per m2 and grain yield. GWAS analysis of grain partitioning traits: ?HIBAP II panel The HIBAP II population has been genotyped for SNP markers using the 35K Wheat breeders array through collaboration with Prof Anthony Hall at Earlham Institute, Norwich, UK. The genotyping information was provided to our project in September 2019. The GWAS analysis for the HIBAP II grain partitioning phenotyping data sets in 2017-18 and 2018-19 is currently ongoing. Validation of significant markers For marker validation, phenotypic evaluation of two bi-parental populations and a diverse population panel were performed at North Florida Research and Education Center (NFREC), Quincy, FL and plant science research and education center (PSREU), Citra, FL, during 2018-19. Least squares mean was calculated for each phenotypic trait. Pearson correlations among phenotypic traits were also calculated. Significant correlations were found between grain yield and yield component traits such as GM2, IN2_L, and IN2_P. A total of 61 Kompetitive Allele-Specific PCR (KASP) markers associated with phenotypic traits were developed based on the results of previously conducted GWAS analysis. A total of 290 bi-parental lines were genotyped using 48 KASP markers. A total of 238 diverse lines were genotyped using all 61 KASP markers. For bi-parental populations, KASP marker S2D_68734015 showed significant allelic effect on IN2&3_P and IN2_P. Allele type "C" showed significantly higher IN2&3_P than allele type "G" and "H". Internode 2 and 3 partitioning and internode 2 partitioning traits are highly correlated with grain yield. Genotypes with "C" allele on S2D_68734015 marker showed 2.6% increase in internode 2 and 3 partitioning compared to genotypes with "G" allele. Genotypes with "C" allele on S2D_68734015 showed 2.9% increase in internode 2 partitioning compared to genotypes with "G" allele. For the diverse population panel, a total of 18 KASP markers showed significant allelic effect on 9 different phenotypic traits. Most notably, genotypes with allele "C" on marker S4B_13299920 showed an 14.7% increase for grain number m-2 compared to genotypes with allele "T". Genotypes with allele "C" on marker S4B_12533949 showed an 11.9% increase for grain number m-2 compared to genotypes with allele "G". Genotypes with allele "C" on marker S3D_295967307 showed an 13.1% increase for fruiting efficiency compared to genotypes with allele "T". Genotypes with allele "G" on marker S4A_609462220 showed an 9.7% increase for harvest index compared to genotypes with allele "A". Genotypes with allele "A" on marker S6D_24028817 showed an 13.9% increase for 1000 grain weight compared to genotypes with allele "G". Genotypes with allele "C" on marker S3A_727396932 showed an 13.1% increase for grain yield compared to genotypes with allele "T". Objective 2: Two diversity panels were evaluated during two years at the CIMMYT IWYP Hub consisting on Primary Synthetic Panel (n=160) and a subset of Bread Wheat Diversity Panel (n=370 lines). Genetic variation was identified for HI in both panels while no trade-off between above ground biomass and HI was identified for BW Diversity Panel. Regarding partitioning traits in both panels, FE and spike partitioning index, were positively correlated with HI while Stem+Lamina partitioning index, and the lengths of internodes 2 and 3 were negatively correlated. A 241 diverse US wheat panel were characterized for partitioning traits at North Florida Research and Education Center (NFREC), Quincy, FL and plant science research and education center (PSREU), Citra, FL, during 2018 to 2019. Two rows of mature plant samples were collected from inside of each plot at 0.5 m length. Least squares mean was calculated for each phenotypic trait. Pearson correlations among phenotypic traits were also calculated. Significant correlations were found between grain yield and yield component traits such as GM2, IN2_L, and IN2_P. Objective 3: Analysis of stem-internode traits in HiBAP II subset in field experiments In the HiBAP II field experiments in 2017-19, a more detailed analysis was carried out on a subset of 30 genotypes of the stem-internode DM partitioning and spike morphological DM partitioning at GS65+7d. There was a negative linear association between stem-internode 3 PI and spike PI (P = 0.058) consistent with results observed in the HiBAP I panel in 2016-17 and 2017-18. There was also a negative association between stem-internode PI 2 and SPI (P = 0.077), but there was no association between peduncle PI and SPI (P = 0.955). The correlations between the within-spike partitionung indices (glume, palea, lemma, rachis, awn) at GS65+7d and FE, grains m-2 and HI are shown in Table 1 for the combined 2-year means. There was a weak trend for lower palea DM partioning to be associated with increased FE and also a trend for lower palea partitioning to be associated with increased grains m-2 (r = -0.52, P= 0.08). A more detailed analysis was carried out on a subset of 20 genotypes (10 US soft wheat and 10 CIMMYT spring wheat) wheat panel of true-stem (TS) and leaf-sheath (LS) internode DM partitioning (peduncle, internode 2 and internode 3) and spike morphological DM partitioning (glume, palea, lemma, awns and rachis) at GS65+7d at PSREU and NFREC at Florida. Genetic variation among genotypes was found for true stem (TS) and leaf sheath (LS) DM partitioning indices at each internode (internode PI) with a strong negative association between Spike PI and true-stem internode 3 PI (R2 = 0.43***) and between Spike PI and true-stem internode 2 PI (R2=0.24*). Genetic variation was found for different spike component partitioning indices (spike component DM/total spike DM, excluding grain) (P< 0.05). There were positive associations between FE and DM partitioning of different components (glumes, lemma, palea PIs). This likely reflected that overall smaller spikes and spike growth was associated with higher FE.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Shrestha SP, Babar MA, Guo J, Bai G, Mergoum M, Mason RE, Gazen S, Asseng S, Blount A, Baik B, Shahi D, Khan J, Hossain MM, Avci M, and Robbins K. 2019. Identifying novel alleles associated with spike fertility, gain number and harvest index under hot and humid environment in wheat through GWAS analysis. Frontiers in Plant Science. 10:1481.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2019
Citation:
Pradhan S, Babar MA, Bai G, Khan J, Shahi D, AVCI M, Guo J, McBreen J, Asseng S, Gezan S, Baik B, Blount A, Harrison S. 2019. Genetic Dissection of Heat-responsive Physiological Traits to Improve Adaptation and Increase Yield Potential in Soft Winter Wheat. BMC Genomics.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2019
Citation:
Guo J, Pradhan S, Shahi D, Khan J, Mcbreen J, Bai G, Murphy JP, and Babar MA. 2019. Increased Prediction Accuracy Using Combined Genomic Information and Physiological Traits in A Soft Wheat Panel Evaluated in Multi-Environments. Scientific Reports-Nature.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
Love B, Sierra Gonzalez AS, Rivera Amado CR, Munnes-Bosch S, Babar MA, Molero G, Reynolds M and J Foulkes. 2019. Raining yield potential through improved harvest index and fruiting efficiency associated with plant hormone signaling in high biomass CIMMYT spring wheat genotypes. 1st International Wheat Congress, July 21-26, Saskatoon, Saskatchewan, Canada.
Shahi D, Khan J, Avci M, Shrestha SP, Guo J, Hossain MM, Islam AFMS, Bai G, Reynolds M, Molero G, Sukumaran S, Foulkes J, Mason E and Babar MA. 2019. Identifying novel alleles contributing increased spike partitioning index and fruiting efficiency at anthesis plus 7 days in US soft wheat through genome wide association study. Plant and Animal Genomics Conference XXVII, Juanuary12-16, San Diego, CA.
Guo J, Shahi D, Shrestha SP, Khan J, Hossain MM, Islam AFMS, Bai G and Babar MA. 2019. Genomic Selection for Predicting Spike Fertility and Biomass Partitioning Traits Using Multiple Soft Wheat Populations. Plant and Animal Genomics Conference XXVII, Juanuary12-16, San Diego, CA.
Guo J, Shahi D, Pradhan SP, Khan J, Islam S, Hossain MM, Bai G and Babar MA. 2018. Genomic Selection for Predicting Spike Fertility and Biomass Partitioning Traits using multiple soft Wheat Populations. Florida Genetic Symposium. Oct 31-Nov1, UF Cancer & Genetics Research Complex Atrium.
Shahi D, Khan J, Avci MI, Shrestha SP, Guo J, Hossain MM, Bai G, Islam S Babar MA. 2018. Genome Wide Association Studies of Stem and Spike partitioning traits in Spring Wheat (Triticum aestivum L.). Florida Genetic Symposium. Oct 31-Nov1, UF Cancer & Genetics Research Complex Atrium.
Shahi D, Khan J, Avci MI, Shrestha SP, Rahman A and Babar MA. 2018. Advancing Harvest Index in Wheat through Genome Wide Association Analysis of Stem and Spike partitioning traits. ASA, CSSA International Conference International Conference, Nov 4-7, 2018, Baltimore, MD.
Shrestha SP, Khan J, Avci M, Shahi D, Guo J, Rahman A, Bai G, Asseng A and Babar MA. 2018. Identifying Genetic Loci for Traits to Improve Wheat Yield and Grain Number under Post-Anthesis Heat Stress Conditions. ASA, CSSA International Conference International Conference, Nov 4-7, 2018, Baltimore, MD.
Sierra-Gonzalez A, Molero M, Reynolds MP, Rivera-Amado C, Piñera-Chavez FJ, Joynson R, Hall A, Foulkes MJ, Sukumaran S. 2019. Genetic analysis of physiological traits to increase grain partitioning in high biomass elite spring wheat lines. Abstracts Plant and Animal Genome Conference XXVII 12-17 January 2019 (2019) San Diego, USA.
|
Progress 12/01/17 to 11/30/18
Outputs
Target Audience:Global wheat research community including wheat breeding and genetics program in the USA. Students, post-docs, research scientists working in plant breeding, genetics and genomics Academic and research community of US and around the world. Representative for food industry globally. Agricultural extenion personnell within USA and globally. Changes/Problems:There will be no major changes in the approach to achieve the goals of the project. What opportunities for training and professional development has the project provided?Bethany Love (PhD student registered Nottingham University) who started on the project on 1 August 2017 has continued with her PhD study during the project reporting year. She is full time on the NIFA-IWYP project. In the last reporting year she has carried out: (i) data analysis of year 1 field phenotyping data in the HiBAP II panel and of physiological and spike hormone concentration data in the glasshouse experiment in 2017 from October to December 2017, (ii) field phenotyping of grain partitioning traits in the HiBAP II panel while based at CIMMYT CENEB Ciudad Obregon, Mexico from February to May 2018 and (iii) a glasshouse experiment on a subset of 10 HiBAP lines investigating associations between spike hormone concentrations and spike fertility and grain partitioning traits from June to September 2018 (experiment is ongoing) at Nottingham University under Objectives 1-3 as outlined in the proposal. Dr. Jia Guo, post-doc at University of Florida, is responsible for phenotyping of two DH bi-parental populations for marker validation and KASP assay development. Dr. Guo characterized 300 wheat genotypes for different partitioning traits in Florida. He will also characterize 250 wheat panel for different partitioning traits in 2018-19 in Florida. Dipendra Shahi is a Ph.D. student started on the project from Nov of 2016. He is full time on the project for phenotyping of association panel. Dipendra is funded through University of Florida. His responsibility is aligned with objectives 1 and 3 in the proposal. Intern students, Ida Vandamme and Paula Glusberger, and student worker Jordan Mc McBreen, Smita Rayamajhi were also trained through the project at UF. A new post-doc fellow, Dr. Zhao Liu, has been hired to perform work on this project (developing KASP assay, validation, allelic variation, etc). Dr. Liu is location at wheat genotyping lab, Manhattan, Kansas. How have the results been disseminated to communities of interest?The results were presented in PAG, 2018 and IWYP meeting, 2018 at San Diego, LA and Norwich, UK What do you plan to do during the next reporting period to accomplish the goals?The PhD student Bethany Love,and Dr John Foulkes will contribute to the work activities in year 3 in Objectives 1-3 as outlined the proposal. It is expected that PhD student Aleyda Sierra will publish the GWAS results for the HiBAP I during 2019. Dr. Gemma Molero, and Matthew Reynolds will contribute to the activities in year 3 in objectives 1-3 at CIMMYT IWYP Hub including the evaluation of the panel LR19. Dr. Md Ali Babar, Post-doc Dr. Jia Guo and Graduate student Dipendra Shahi will contribute to the work activities in year 3 in Objectives 1-3 as outlined in the proposal at university of Florida. Dr. Guihua Bai and Dr. Zhao Liu will contribute to the work activities related to marker validation and identify different alleles that influence partitioning traits. No changes have been made to the project milestones and deliverables. However, the collaboration with A. Hall (IWYP 64) and IWYP Hub have facilitated the evaluation of two high biomass panels, HiBAP I and HiBAP II. Objective 1 Develop new breeder-friendly molecular markers for grain partitioning traits (GWAS) At the CIMMYT IWYP Hub, the HiBAP II panel (150 lines) will be phenotyped in 2018-19 for the second year. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis + 7 days and iii) yield and yield components. Analysis of marker-trait associations will be carried out using TASSEL and R software (GAPIT package) on the 2017-18 and 2018-19 data sets. Objective 2. Screen wider resources: CIMMYT exotic panel and US soft and hard wheat panel A US wheat panel (hard, soft and spring wheat) will be screened for different partitioning traits at the University of Florida in 2018-19, and a CIMMYT wider germplasmhave been already screened CIMMYT IWYP Hub. This will help to gain a better understanding of the range of potential loci and alleles that influence these grain traits and interactions with the environment and in terms of epistasis. An additional panel, LR19, with 16 lines will be screened in the IWYP-Hub during 2018-2019. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis + 7 days and iii) yield and yield components. Objective 3. Identify mechanisms determining grain traits and quantify genotype-by-environment interaction A set of 20 genotypes (10 representative lines of each of the HiBAP II and US association panels) will be used as common checks for the two association panels in Objective 1. A more detailed set of physiological measurements will be carried out on these 20 genotypes at UFL to identify the mechanisms determining the grain sink traits and to quantify G x E and the heritability of the traits. The measurements will include: Growth and partitioning: Stem structural and soluble DM in internode 1 (peduncle), internode 2, internode 3 and internode 4+ at GS65 Spike partitioning at harvest (awns, rachis, glume, palea, lemma). Stem water soluble carbohydrate % at harvest. Photosynthetic capacity: Flag-leaf stomatal conductance weekly measured from GS51 to mid-senescence (GS75) The glasshouse experiment currently being carried out in 2018 at Nottingham for the subset of 10 genotypes from the CIMMYT HiBAP II (sown in June 2018) will be completed. The spike samples from booting and anthesis (currently stored at -80oC) will be submitted to the laboratory for plant growth regulator profile analysis. The data analysis for the 2018 experiment will be carried out. Spikes for the same subset of 10 HiBAP II lines will be sampled at anthesis in the field experiment at the CIMMYT IWYP Hub in 2018-9 to confirm that the spike hormone differences amongst genotypes translate to the field. These results will provide the basis for future GWAS analysis for these plant signalling traits.
Impacts
What was accomplished under these goals?
Objective 1 accomplishments: Two association panels (one panel at UFL, Gainesville and another panel at the CIMMYT IWYP Hub, Ciudad Obregon) were characterized for physiological traits that determine spike, lamina, and stem partitioning, fruiting efficiency, HI, above ground biomass, and grain yield. At harvest, machine harvested yield, HI and yield components were assessed. CIMMYT HIBAP panel: Overall yields ranged from 476 to 722 g m-2 (P<0.001) and above-ground biomass at physiological maturity (AGDM) from 956 to 1520 g m-2 (P< 0.001). Results showed genetic variation in most of the partitioning traits measured at GS65+7d and physiological maturity. Strong phenotypic correlations were found amongst genotypes between grain yield and AGDM (r =0.66***) and HI (r = 0.50***,). There was strong a trade-off between AGDM and HI (r = -0.33***). There was an association between enhanced HI and reduced stem partitioning index (r = -0.27***) at anthesis (GS65 +7d) and reduced length of true-stem internode 3 (peduncle -2) (r = -0.29**). Stem PI and lamina PI were each negatively associated with spike PI (spike DM / above-ground DM at anthesis + 7 days; SPI) (P< 0.001). US soft wheat panel: Overall yield values ranged from 392 to 613 g m-2 (P<0.001) and above-ground biomass from 1224 to 3213 g m-2 (P< 0.001). Results showed genetic variation in most of the partitioning traits measured at GS65+7d and physiological maturity. Strong associations were found amongst genotypes between grain yield and AGDM (r =0.32***) and HI (r = 0.37***). Fruiting effcicency (FE) showed very strong association with grain yield (0.40***), HI (0.47***) and grains m-2 (0.48***). There was a significant association between reduced length of true-stem internode 3 and higher grains m-2 and (r = -0.23**), and with higher HI (-0.21***) at anthesis (GS65 +7d). Spike PI was positively associated with grain yield (0.21***), HI (0.27***) and grains m-2 (0.28***). The results indicate that the increased assimilate supply at GS65+7d could potentially be an effective way of increasing grain yield.Considering the partitioning indices at GS65+7d, there was a very strong negative association between spike PI and stem PI (R2 = 0.54***), but a weak negative association between spike PI and lamina PI (R2 = 0.06*). There was a negative significant association between spike PI and true stem internode 2 and 3 PI and length. The results from phenotypic analysis in both panel suggest that genotypes with a decreased internode 3 length compete less with the spike for assimilate at GS65+7d and this is related to increased HI and grains per m2. Genotypes with a higher fruiting efficiency were also strongly correlated with higher HI and grains per m2 and grain yield. Genomewide association analysis: GWAS analysis was carried out on the HiBAP phenotyping data from 2015-2016 and 2016-17. The GWAS analysis was carried out using a 35K SNP map for the HiBAP. The 35K SNP assembly map constitutes 13,726 markers distributed throughout the 7 chromosomes including 3 genomes (A, B and D) that make up the whole wheat genome. Genetic data was analyzed using the TASSEL 5 software package to evaluate traits associations, evolutionary patterns, and linkage disequilibrium (GWAS). SNP markers were associated with grain partitioning traits in HiBAP through marker-trait association. A novel locus on chromosome 6A co-linear with stem internode 3 length and harvest index was identified. GWAS analysis were performed using a compressed mixed linear model (CMLM) in the Genome Association Prediction Integrated Tool (GAPIT) package in R. The model incorporated kinship information and principal components as corrections for population structure and genotypic relationship. Marker-trait associations were detected in all chromosomes based on a significance threshold of p<0.0001. A total of 131 markers showed significant association with different traits. Validation of significant markers We designed KASP assays for 6 chip-based SNPs that were identified to be associated with yield traits from the evaluation of HiBAP I in CIMMYT. Phenotypic evaluations of two bi-parental populations were performed at Quincy and Citra, FL. One KASP marker associated with FE showed polymorphic segregation among genotypes in both populations. The FE of the bi-parental lines with A allele showed higher value than in those with the B allele in AX-94980956. The lines with both AB-alleles showed slightly higher FE value than AA- and BB-allele type. Objective 2 accomplishments. Two diversity panels were evaluated during two years at the CIMMYT IWYP Hub consisting on Primary Synthetic Panel (n=160) and a subset of Bread Wheat Diversity Panel (n=370 lines). Genetic variation was identified for HI in both panels while no trade-off between above ground biomass and HI was identified for BW Diversity Panel. Regarding partitioning traits in both panels, FE and spike partitioning index, were positively correlated with HI while Stem+Lamina partitioning index, and the lengths of internodes 2 and 3 were negatively correlated. Primary Synthetic material (n=160)was screened at the CIMMYT IWYP Hub in 2017-18 to gain a better understanding of the range of potential loci and alleles that influence these grain traits and interactions with the environment and in terms of epistasis. This will be the third year of evaluation. The database from this evaluation is still not available and the results will be presented in the next report.The traits scored in the panels include yield, HI and grains m-2. Objective 3 accomplishment: A more detailed analysis was carried out on a subset of 30 genotypes of HiBAP panel of true-stem (TS) and leaf-sheath (LS) internode DM partitioning (peduncle, internode 2, 3 and 4+) and spike morphological DM partitioning (glume, palea, lemma, awns and rachis) at GS65+7d. Significant genetic variation among genotypes was found for true stem (TS) and leaf sheath (LS) DM partitioning indices at each internode. There was a negative linear association between true stem internode 3 PI and spike PI. A more detailed analysis was carried out on a subset of 20 genotypes (10 US soft wheat and 10 CIMMYT spring wheat) wheat panel at UFL for true-stem (TS) and leaf-sheath (LS) internode DM partitioning (peduncle, internode 2 and 3) and spike morphological DM partitioning (glume, palea, lemma, awns and rachis) at GS65+7d at Quincy and Citra, Florida.Significant genetic variation was found for true stem (TS) and leaf sheath (LS) DM partitioning indices at each internode (internode PI) with a strong negative association between Spike PI and true-stem internode 3 PI (R2 = 0.43***) and between Spike PI and true-stem internode 2 PI (R2=0.24*). Genetic variation was also found for different spike component partitioning indices (spike component DM/total spike DM, excluding grain) (P< 0.05). There were positive associations between FE and DM partitioning of different components (glumes, lemma, palea PIs). Analysis of spike plant hormone concentration: A glasshouse experiment was carried out at Nottingham University in 2017 to investigate genetic variation in spike fertility traits and grain number and associations with spike plant hormone concentrations. Results showed Gibberellin (GA1) levels measured at GS490 and GS65 were associated with fertile florets per spike at anthesis. Cytokinin (Zeatin) levels at GS65 were also associated with the fruiting efficiency. A second experiment was sown with four replicates including additional sampling replicates for destructive assessments at booting and anthesis. The plants were sampled for partitioning traits and fruiting efficiency at anthesis and for spike plant hormone analysis at booting and anthesis. The plants are presently at late grain filling and this experiment is ongoing.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Zhenqi Su, Sujuan Jin, Dadong Zhang, Guihua Bai. 2018. Development and validation of diagnostic markers for Fhb1 region, a major QTL for Fusarium head blight resistance in wheat. Theor Appl Genet https://doi.org/10.1007/s00122-018-3159-6
Guihua Bai, Zhenqi Su and Jin Cai. 2018. Wheat Resistance to Fusarium Head Blight. Can J. Plant Pathol (Online) https:/doi.org/10.1080/07060661.2018.1476411
M. Shao, G. Bai, T. W. Rife, J. Poland, M. Lin, S. Liu, H. Chen, T. Kumssa, A. Fritz, H. Trick, Y. Li, G. Zhang. 2018. QTL mapping of pre harvest sprouting resistance in a white wheat cultivar Danby. Theor. Appl. Genet. 131:1683-1697.
Na Liu, Guihua Bai, Meng Lin, Xiangyang Xu, Wenming Zheng. 2017. Genome-wide Association Analysis of Powdery Mildew Resistance in U.S. Winter Wheat. Sci Rep. | 7: 11743 | DOI:10.1038/s41598-017-11230-z
Hadi Ali Pour, M.R. Bihamta, V. Mohammadi, S.A. Peyghambari, G.H. Bai and G.R. Zhang. 2017. Genotyping-by-sequencing (GBS) revealed molecular genetic diversity of Iranian wheat landraces and cultivars. Front. Plant Sci. | doi: 10.3389/fpls.2017.01293
|
Progress 12/01/16 to 11/30/17
Outputs
Target Audience:Global wheat research community including wheat breeding and genetics program in the USA. Academic and research community of US and around the world. Representative for food industry globally. Agricultural extenion personnell within USA and globally. Changes/Problems:No major changes in objectives, goals, and research approaches anticipated for 2017-18. What opportunities for training and professional development has the project provided?Bethany Love (PhD student registered Nottingham University) started on the project on August 2017. She will carry out the glasshouse experiments at Nottingham and contribute to the phenotyping of the HiBAP population and wider germplasm and associated GWAS analysis under Objectives 1-3 as outlined in the proposal. Dr. Jia Guo is newly appointed post-doc at University of Florida and is responsible for phenotyping of US soft wheat association panel at two locations in Florida. In addition, Dr. Guo will phenotype two double haploid population for marker conversion and validation, haplotype analysis and introgression of QTLs in different genetic background at UF. Dipendra Shahi is a Ph.D. student started on the project from Nov of 2016. He is full time on the project for phenotyping of association panel. Dipendra is funded through University of Florida. His responsibility is aligned with objectives 1 and 3 in the proposal. Student assistant Abdul Halim and Smita Rayamajhi were also trained through the project at UF. How have the results been disseminated to communities of interest?The results of 2016-17 WIll be presented at PAG meeting at San Diego and IWYP project directors meeting in 2018. What do you plan to do during the next reporting period to accomplish the goals?Objective 1 Develop new breeder-friendly molecular markers for grain partitioning traits (GWAS) At the CIMMYT IWYP Hub the HiBAP wil be phenotyped in 2017-8. While US soft wheat will be phenotyped at PSREU and NFREC, Florida. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Analysis of marker-trait associations will be carried out using TASSEL and R software (GAPIT package). For each QTL identified through GWAS analysis, 2-3 KASP markers will be developed, their haplotypes will be determined and validated in at least one linkage mapping population, and the validated KASP markers will be used for selecting the target QTL regions in breeding and for pyramiding the QTLs for grain traits through marker-assisted selection. Dr. Guihua Bai will lead breeder friendly KASP marker development. Dr. Babar and post-doc Dr. Jia Guo will be responsible for phenotyping of two double haploid populations at Florida for marker conversion and validation. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Objective 2. Screen wider resources: CIMMYT exotic panel and US soft and hard wheat panel Wider germplasmwill be screened at the CIMMYT IWYP Hub to gain a better understanding of the range of potential loci and alleles that influence these grain traits and interactions with the environment and in terms of epistasis. The panel of wider germplasm will comprise selected genotypes of three other CIMMYT panels: a) Primary Synthetics Diversity panel (n=160). b) Bread wheat diversity panel (n=370). c) 7Ag.7DL translocation lines panel. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Objective 3. Identify mechanisms determining grain traits and quantify genotype-by-environment interaction A set of 20 genotypes (10 representative lines of each of the HiBAP and US association panels) will be used as common checks for the two association panels in Objective 1. A more detailed set of physiological measurements will be carried out on these 20 genotypes at both UFL and IWYP hub to identify the mechanisms determining the grain sink traits and to quantify G x E and the heritability of the traits. The measurements will include: Growth and partitioning: Stem structural and soluble DM in internode 1 (peduncle), internode 2, internode 3 and internode 4+ at GS65 Spike partitioning at harvest (awns, rachis, glume, palea, lemma). Stem water soluble carbohydrate % at harvest. Photosynthetic capacity: Flag-leaf stomatal conductance weekly measured from GS51 to mid-senescence (GS75) The subset of 10 genotypes from the CIMMYT HiBAP will be assessed in a glasshouse experiment at UoN in 2017-8 for fruiting efficiency, grain number and plant growth regulator profiles. These results will also provide the basis for future GWAS analysis for these plant signalling traits.
Impacts
What was accomplished under these goals?
Objective 1): Develop new breeder-friendly molecular markers for grain partitioning traits that permit photosynthesis products to be consistently translated to grain yield through genome-wide association study (GWAS) using two association panels in high biomass backgrounds, one panel comprising of US southern, eastern, and southeastern facultative soft wheats, and one CIMMYT spring wheats Two association panels (one panel at UFL, Gainesville and another panel at the CIMMYT IWYP Hub, Ciudad Obregon) were characterized for physiological traits that determine spike, lamina, and stem partitioning, fruiting efficiency, HI, above ground biomass, and grain yield. At UFL, the panel is comprised of 248 US soft red facultative wheat genotypes developed by different public and private wheat breeding programs. The panel was planted at Plant Science Research and Education Unit (PSREU), Citra, FL and North Florida Research and Education Center (NFREC), Quincy, FL for phenotypic characterization, The High Biomass Association Panel (HiBAP) was characterized at the CIMMYT IWYP Hub at Obregon, Mexico. The HiBAP panel comprised of 150 spring lines has been assembled by systematic screening of: (i) recent CIMMYT international bread wheat nurseries targeted to high yield environments, (ii) outstanding pre-breeding lines crossed and selected for high yield and biomass, and (iii) elite synthetic-derived lines. The HiBAP (High Biomass Association Panel) panel with high biomass was sown on 2 November 2016, in an alpha-lattice design with 4 replicates, at the International Maize and Wheat Improvement Center (CIMMYT) experimental station Norman E. Borlaug located in Yaqui Valley in Mexico. Physiological traits were measured at anthesis (GS65) +7d, when a full DM partitioning analysis was carried out (spike, leaf lamina and stem and leaf sheath DM proportions) including stem internode lengths: internode 2 and 3 (peduncle -1 and -2, respectively). At harvest, machine harvested yield, HI and yield components were assessed. The same traits were measured for US soft wheat panel at two locations (NFREC and PSREU) at anthesis+7d. Soft wheat panel was planted in a modified augmented design using three commercial varieties as repeated checks. HiBAP panel: Overall yields that ranged from 437 to 618 g m-2 (P<0.001) and above-ground biomass from 1123 to 1552 g m-2 (P< 0.001). Results showed genetic variation in most of the partitioning traits measured at GS65+7d and physiological maturity. Strong relations were found amongst genotypes between grain yield and AGDM (r =0.46, P< 0.001) and HI (r = 0.35, P< 001). There was strong a trade-off between AGDM and HI (r = -0.57, P<0.001) There was an association between enhanced grains m-2 and reduced length of true-stem internode 3 (peduncle -2) (r = -0.29, P<0.01) at anthesis (GS65 +7d) and reduced length of true-stem internode 2 (peduncle -1) (r = -0.32; P<0.01). Internode 2 and 3 lengths were also negatively associated with SPI (P< 0.001; Fig.1a) There was a positive linear association between fruiting efficiency (grain per unit spike DM at GS65+7d; FE) and grains m-2 (r = 0.46, P<0.001). Considering the partitioning indices at GS65+7d, there was a strong negative linear association between spike PI and stem PI (R2 = -0.58, P< 0.001) but a weak negative association between spike PI and lamina PI (R2 = -0.04; P< 0.05). US Soft wheat panel: Gneotypes showed significant genetic variations for grain yield(P<0.001) and for above-ground biomassm-2 (P< 0.001). Results showed genetic variation in most of the partitioning traits measured at GS65+7d and physiological maturity. Strong relations were found amongst genotypes between grain yield and AGDM (r =0.35***) and HI (r = 0.64***). There was signififcant trade-off between AGDM and HI (r = -0.21**). There was an association between enhanced grains m-2 and reduced length of true-stem internode 3 (peduncle -2) (r = -0.23**) at anthesis (GS65 +7d) . Spike partitioning index was strongly associated with grain yield (0.23**), HI (0.30***) and grains m-2 (0.25**). There was a positive linear association between fruiting efficiency and grains m-2 (r = 0.49***) and with harvest index (0.402***). Considering the partitioning indices at GS65+7d, there was a strong negative association between spike PI and stem PI (R2 = 0.42***) and between spike PI and lamina PI (R2 = 0.29***). These preliminary results suggest that genotypes with a longer internode 2 and 3 compete more with the spike for assimilate at GS65+7d and this is related to decreased Spike PI, grain number per unit area and HI. The genotyping of both panel is in progress by using the GBS (US soft wheat panel) and exom capture (CIMMYT HiBAP panel).The genotyping data will be used to identify QTLs for different traits. The genotyping information will be used for GWAS analysis. Genetic data will be analyzed using the TASSEL 5 software package to evaluate traits associations, evolutionary patterns, and linkage disequilibrium (GWAS). The genotyping of both panel is in progress and expected to completed by end of October. SNPs identified from Exon Capture and GBS that link to these QTLs will be converted into breeder-friendly KASP markers for breeding. Objective 2: Screen diverse sets of genetic resources including CIMMYT primary synthetic lines and US soft wheats for markers for grain traits determining grain partitioning in high biomass backgrounds. Wider germplasmwill be screened at the CIMMYT IWYP Hub to gain a better understanding of the range of potential loci and alleles that influence these grain traits and interactions with the environment and in terms of epistasis in 2017-18. The core phenotyping measurements will include: i) phenology, ii) growth and partitioning at anthesis and iii) yield and yield components. Objective 3): Identify mechanisms determining grain partitioning traits and genotype-by-environment interaction through physiological dissection of subsets of wheat genotypes. A more detailed analysis was carried out on a subset of 30 genotypes in the HiBAP and 10 genotypes in the US soft wheat panel for true-stem (TS) and leaf-sheath (LS) internode DM partitioning (peduncle, internode 2 and internode 3) and spike morphological DM partitioning (glume, palea, lemma, awns and rachis) at GS65+7d.Genetic variation among genotypes was found for true stem (TS) and leaf sheath (LS) DM partitioning indices at each internode (internode PI) with a strong negative association between Spike PI and true-stem internode 3 PI.Genetic variation was found for all spike component partitioning indices (spike component DM/total spike DM, excluding grain) (P< 0.05). There were negative linear associations between FE and DM partitioning to each component (glumes, lemma, palea, awns PIs). This likely reflected that overall smaller spikes and spike growth was associated with higher FE. The strongest trade-off appeared to be between FE with lemma PI.Seed for a subset of 10 HiBAP lines has been sent to University of Nottingham and a glasshouse experiment is currently ongoing at Nottingham to investigate genetic variation in grain number and fruiting efficiency and associations with plant growth regulator profiles. 4) Design ideal plant ideotypes and establish pre-breeding crosses in the USA and CIMMYT wheat breeding programs. This research will be conducted at year 2018-19.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
1. C. Li, C. Li, B. F. Carver, R. Bowden, Z. Su, Z. Wang, and G. Bai. 2017. Mapping of Quantitative Trait Loci for Leaf Rust Resistance in the Wheat Population Ning7840 � Clark. Plant Dis. https://doi.org/10.1094/PDIS-12-16-1743-RE
2. Y. Lu, R. L. Bowden, G. Zhang, X. Xu, A. K. Fritz, and G. Bai. 2017. Quantitative Trait Loci for Slow-Rusting Resistance to Leaf 1 Rust in Doubled Haploid Wheat Population CI13227 x Lakin. Phytopathology https://doi.org/10.1094/PHYTO-09-16-0347-R
|
|