Mapping Autotetraploid Alfalfa. Joseph G. Robins and E. Charles Brummer

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1 Mapping Autotetraploid Alfalfa Joseph G. Robins and E. Charles Brummer

2 Objective Determine the genetic basis of forage yield in alfalfa. 1) Develop a genetic linkage map of tetraploid alfalfa. 2) Map quantitative trait loci (QTL) associated with forage yield. 3) Implement a marker-assisted selection (MAS) program for alfalfa improvement.

3 Problem Lack of gain in alfalfa forage yield since the early 1980s. Yield (Mg/ha) Upper Midwest Iowa USA Courtesy: Riday and Brummer, Year

4 Autopolyploid Genetics Forage yield gain is complicated by the complexities of alfalfa genetics. 1) Complementary gene action (Bingham et al. 1994). 2) Irregular meiosis, when compared to diploids, with non-conventional segregation patterns. a) Potential multivalent pairing. b) Potential double reduction.

5 Our Approach A potential solution is to identify genomic regions associated with forage yield. 1) Create genetic map of a segregating population using molecular markers. 2) Combine marker and phenotype data to identify associations between markers and phenotype (QTL) 3) Utilize QTL in a marker-assisted breeding program to increase forage yield.

6 Experiment Created F 1 mapping population by crossing WISFAL-6 (M. sativa subsp. falcata) x ABI-408 (M. sativa subsp. sativa). 1) Placed at Ames, IA, Nashua, IA & Ithaca, NY for forage yield analysis from ) Measurements were also taken for a variety of other traits. 3) Lsmeans across years and locations.

7 Forage Yield Results Population exhibits large amount of genetic variation for forage yield. 1) Broad-sense heritability = 0.57 ± a) H 2 = σ 2 G / σ2 P. Where σ 2 G = σ2 A + σ2 D + σ2 F + σ2 T + σ2 I. a) Based on entry means across years and locations. 2) Identified high and low transgressive segregants.

8 Genetic Mapping Developed a genetic map of the population using RFLPs, AFLPs, and SSRs. 1) Autopolyploid genetics complicate mapping. 2) Used RFLPs, AFLPs, and SSRs. a) Single and double dose alleles. 3) Developed maps of both parents.

9 Mapping Summary Both parental maps are preliminary and currently composed of fourteen consensus linkage groups. 1) ABI-408: 120 RFLPs, 201 AFLPs, 7 SSRs a) 179 single-dose, 32 double-dose, 120 distorted. 2) WISFAL-6: 106 RFLPs, 139 AFLPs, 4 SSRs a) 115 single-dose, 50 double-dose, 84 distorted.

10 QTL Analysis Utilized single-marker analysis (ANOVA) to identify molecular markers significantly associated with forage yield. 1) ABI-408: Identification of three potential forage yield QTL. 2) WISFAL-6: Identification of two potential forage yield QTL.

11 Possible QTL Associations based on average forage yield (g plant -1 ) across locations and years. Parent Marker Yield (marker present/absent) P-value ABI-408 UGA189a 175 / Vg2D11a 174 / AGC/CAC / WISFAL-6 Vg2D / UGA /

12 ABI-408 QTL Mapping Markers (highlighted in red) associated with forage yield in the sativa parent. 0.0 AGC/CAA AGC/CTC UGA189a AGC/CAG276 AGC/CAG141 AGC/CAA288 AGC/CAA201 AGC/CAA230 ACG/CAT433 AGC/CAC296 ACG/CAT155 AGC/CAC216 ACG/CAT467 ACG/CTA156 AGC/CAC201 AGC/CAC230 AGC/CAC251 AGC/CAC366 ACG/CAT264 AGC/CAC AGC/CTT162 ACG/CAA380 UGA522b ACG/CAC227 AGC/CAA253 ACG/CTG325 MS14 UGA564 UGA1208 Vg2D11a UGA328 AGC/CAG241 UGA5 ACG/CAT283 AGC/CAG239 AGC/CAG304 ACG/CAC UGA246 UGA543 ACG-CTC177 UGA286 ACG/CTG283 UGA189b Only three of fourteen consensus linkage groups shown AGC/CAC148

13 WISFAL-6 QTL Mapping Markers (highlighted in red) associated with forage yield in the falcata parent. 0.0 UGA85b 0.0 UGA UGA219 ACG/CTA142 ACG/CTG277 AGC/CTT167 UGA28 UGA449 UGA792 UGA189a UGA671 UGA83 RC2B-63BV8 ARC3D Vg2D11 ACG/CTG211 afctt1 ACG/CAC324 UGA744 afct45 MSAICB RC-1-51dT23V20 UGA540 Only two of fourteen consensus linkage groups shown afct32 AGC/CTT ACG/CTG AGC/CTT276

14 QTL x Environment Our next step will be to analyze QTL as they change over the different locations and years. 1) The extent of our phenotypic data will allow us to identify QTL that are specific to individual locations, years, or location/year combinations. 2) This should allow us to identify QTL that are important in the developmental process of alfalfa (as the plant ages, it is possible that QTL may change) and QTL that are or are not influenced by environmental factors. 3) We hope to have results from these analyses shortly.

15 Summary We have: 1) Developed preliminary linkage maps of ABI-408 and WISFAL-6. a) We are continuing to add SSRs. 2) Used single-marker analysis to identify potential QTL associated with forage yield in both parents. a) Associations will be further verified with permutation testing. 3) We then hope to incorporate the results for alfalfa forage yield improvement.

16 Acknowledgements Dr. Charlie Brummer Dr. Diane Luth Dr. Heathcliffe Riday Meenakshi Santra Baldomero Alarcón-Zúñiga ISU-Forage Breeding Group Iowa State University Plant Science Institute USDA-NRI Competitive Grants Program