Person: Payne, T.S.
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Payne
First Name
T.S.
Name
Payne, T.S.
ORCID ID
0000-0002-0383-4073 7 results
Search Results
Now showing 1 - 7 of 7
- Metrics for optimum allocation of resources on the composition and characterization of crop collections: The CIMMYT wheat collection as a proof of concept(Southern Cross Publishing, 2022) Reyes-Valdés, M.H.; Burgueño, J.; Sansaloni, C.; Payne, T.S.; Pacheco Gil, R.A,; González-Cortés, A.
Publication - Strategic use of Iranian bread wheat landrace accessions for genetic improvement: core set formulation and validation(Wiley, 2021) Vikram, P.; Franco, J.; Burgueño, J.; Huihui Li; Sehgal, D.; Saint Pierre, C.; Ortiz, C.; Singh, V.K.; Sneller, C.; Sharma, A.R.; Tattaris, M.; Guzman, C.; Peña-Bautista, R.J.; Sansaloni, C.; Campos, J.; Thiyagarajan, K.; Fuentes Dávila, G.; Reynolds, M.P.; Sonder, K.; Velu, G.; Ellis, M.H.; Bhavani, S.; Jalal Kamali, M.R.; Roostaei, M.; Singh, S.; Basandrai, D.; Bains, N.; Basandrai, A.K.; Payne, T.S.; Crossa, J.; Singh, S.
Publication - Diversity analysis of 80,000 wheat accessions reveals consequences and opportunities of selection footprints(Nature Publishing Group, 2020) Sansaloni, C.; Franco, J.; Santos, B.; Percival-Alwyn, L.; Singh, S.; Petroli, C.; Campos, J.; Dreher, K.; Payne, T.S.; Marshall, D.S.; Kilian, B.; Milne, I.; Raubach, S.; Shaw, P.D.; Stephen, G.; Carling, J.; Saint Pierre, C.; Burgueño, J.; Crossa, J.; Huihui Li; Guzman, C.; Kehel, Z.; Amri, A.; Kilian, A.; Wenzl, P.; Uauy, C.; Banziger, M.; Caccamo, M.; Pixley, K.V.
Publication - Harnessing genetic potential of wheat germplasm banks through impact-oriented-prebreeding for future food and nutritional security(Nature Publishing Group, 2018) Singh, S.; Vikram, P.; Sehgal, D.; Burgueño, J.; Sharma, A.R.; Singh, S.K.; Sansaloni, C.; Joynson, R.; Brabbs, T.; Ortiz, C.; Solís Moya, E.; Velu, G.; Gupta, N.; Sidhu, H.S.; Basandrai, A.K.; Basandrai, D.; Ledesma-Ramires, L.; Suaste-Franco, M.P.; Fuentes Dávila, G.; Ireta Moreno, J.; Sonder, K.; Vaibhav K. Singh; Sajid Shokat; Shokat, S.; Mian A. R. Arif; Khalil A. Laghari; Puja Srivastava; Bhavani, S.; Satish Kumar; Pal, D.; Jaiswal, J.P.; Kumar, U.; Harinder K. Chaudhary; Crossa, J.; Payne, T.S.; Imtiaz, M.; Sohu, V.S.; Singh, G.P.; Bains, N.; Hall, A.J.W.; Pixley, K.V.The value of exotic wheat genetic resources for accelerating grain yield gains is largely unproven and unrealized. We used next-generation sequencing, together with multi-environment phenotyping, to study the contribution of exotic genomes to 984 three-way-cross-derived (exotic/elite1//elite2) pre-breeding lines (PBLs). Genomic characterization of these lines with haplotype map-based and SNP marker approaches revealed exotic specific imprints of 16.1 to 25.1%, which compares to theoretical expectation of 25%. A rare and favorable haplotype (GT) with 0.4% frequency in gene bank identified on chromosome 6D minimized grain yield (GY) loss under heat stress without GY penalty under irrigated conditions. More specifically, the ‘T’ allele of the haplotype GT originated in Aegilops tauschii and was absent in all elite lines used in study. In silico analysis of the SNP showed hits with a candidate gene coding for isoflavone reductase IRL-like protein in Ae. tauschii. Rare haplotypes were also identified on chromosomes 1A, 6A and 2B effective against abiotic/biotic stresses. Results demonstrate positive contributions of exotic germplasm to PBLs derived from crosses of exotics with CIMMYT’s best elite lines. This is a major impact-oriented pre-breeding effort at CIMMYT, resulting in large-scale development of PBLs for deployment in breeding programs addressing food security under climate change scenarios.
Publication - Unlocking the genetic diversity of Creole wheats(Nuture Publishing Group, 2016) Vikram, P.; Franco, J.; Burgueño, J.; Huihui Li; Sehgal, D.; Saint Pierre, C.; Ortiz, C.; Sneller, C.; Tattaris, M.; Guzman, C.; Sansaloni, C.; Ellis, M.; Fuentes Dávila, G.; Reynolds, M.P.; Sonder, K.; Singh, P.K.; Payne, T.S.; Wenzl, P.; Sharma, A.R.; Bains, N.; Singh, G.P.; Crossa, J.; Singh, S.Climate change and slow yield gains pose a major threat to global wheat production. Underutilized genetic resources including landraces and wild relatives are key elements for developing high-yielding and climate-resilient wheat varieties. Landraces introduced into Mexico from Europe, also known as Creole wheats, are adapted to a wide range of climatic regimes and represent a unique genetic resource. Eight thousand four hundred and sixteen wheat landraces representing all dimensions of Mexico were characterized through genotyping-by-sequencing technology. Results revealed sub-groups adapted to specific environments of Mexico. Broadly, accessions from north and south of Mexico showed considerable genetic differentiation. However, a large percentage of landrace accessions were genetically very close, although belonged to different regions most likely due to the recent (nearly five centuries before) introduction of wheat in Mexico. Some of the groups adapted to extreme environments and accumulated high number of rare alleles. Core reference sets were assembled simultaneously using multiple variables, capturing 89% of the rare alleles present in the complete set. Genetic information about Mexican wheat landraces and core reference set can be effectively utilized in next generation wheat varietal improvement.
Publication - Genomic prediction of gene bank wheat landraces(Genetics Society of America, 2016) Crossa, J.; Jarquin, D.; Franco, J.; Pérez-Rodríguez, P.; Burgueño, J.; Saint Pierre, C.; Vikram, P.; Sansaloni, C.; Petroli, C.; Akdemir, D.; Sneller, C.; Reynolds, M.P.; Tattaris, M.; Payne, T.S.; Guzman, C.; Peña, R.; Wenzl, P.; Singh, S.This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH) and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G×E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections were formed. Accounting for population structure decreased prediction accuracy by 15%-20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections but slightly lower for Iranian collections. Prediction accuracy when incorporating G×E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G×E term. For Iranian landraces, accuracies were 0.55 for the G×E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials.
Publication - A high density GBS map of bread wheat and its application for dissecting complex disease resistance traits(BioMed Central, 2015) Huihui Li; Vikram, P.; Singh, R.P.; Kilian, A.; Carling, J.; Jie Song; Burgueño, J.; Bhavani, S.; Huerta-Espino, J.; Payne, T.S.; Sehgal, D.; Wenzl, P.; Singh, S.Genotyping-by-sequencing (GBS) is a high-throughput genotyping approach that is starting to be used in several crop species, including bread wheat. Anchoring GBS tags on chromosomes is an important step towards utilizing them for wheat genetic improvement. Here we use genetic linkage mapping to construct a consensus map containing 28644 GBS markers. Results: Three RIL populations, PBW343 × Kingbird, PBW343 × Kenya Swara and PBW343 × Muu, which share a common parent, were used to minimize the impact of potential structural genomic variation on consensus-map quality. The consensus map comprised 3757 unique positions, and the average marker distance was 0.88 cM, obtained by calculating the average distance between two adjacent unique positions. Significant variation of segregation distortion was observed across the three populations. The consensus map was validated by comparing positions of known rust resistance genes, and comparing them to wheat reference genome sequences recently published by the International Wheat Genome Sequencing Consortium, Rye and Ae. tauschii genomes. Three well-characterized rust resistance genes (Sr58/Lr46/Yr29, Sr2/Yr30/Lr27, and Sr57/Lr34/Yr18) and 15 published QTLs for wheat rusts were validated with high resolution. Fifty-two per cent of GBS tags on the consensus map were successfully aligned through BLAST to the right chromosomes on the wheat reference genome sequence. Conclusion: The consensus map should provide a useful basis for analyzing genome-wide variation of complex traits. The identified genes can then be explored as genetic markers to be used in genomic applications in wheat breeding.
Publication