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Saint Pierre, C.

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Saint Pierre
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Saint Pierre, C.

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  • Correction to: Strategic crossing of biomass and harvest index—source and sink—achieves genetic gains in wheat (Euphytica, (2017), 213, 257, 10.1007/s10681-017-2040-z)
    (Springer, 2018) Reynolds, M.P.; Pask, A.; Hoppitt, W.J.E.; Sonder, K.; Sukumaran, S.; Molero, G.; Saint Pierre, C.; Payne, T.S.; Singh, R.P.; Braun, H.J.; González, F.G.; Terrile, I.I.; Barma, N.C.D.; Hakim M.A.; He Zhonghu; Zheru Fan; Novoselovic, D.; Maghraby, M.; Gad, K.I.M.; Galal, E.G.; Hagras, A.; Mohamed M. Mohamed; Morad, A.F.A.; Kumar, U.; Singh, G.P.; Naik, R.; Kalappanavar, I.K.; Biradar, S.; Prasad, S.V.S.; Chatrath, R.; Sharma, I.; Panchabhai, K.; Sohu, V.S.; Gurvinder Singh Mavi; Mishra, V.K.; Balasubramaniam, A.; Jalal Kamali, M.R.; Khodarahmi, M.; Dastfal, M.; Tabib Ghaffary, S.M.; Jafarby, J.; Nikzad, A.R.; Moghaddam, H.A.; Hassan Ghojogh; Mehraban, A.; Solís Moya, E.; Camacho Casas, M.A.; Figueroa, P.; Ireta Moreno, J.; Alvarado Padilla, J.I.; Borbón Gracia, A.; Torres, A.; Quiche, YN.; Upadhyay, S.R.; Pandey, D.; Imtiaz, M.; Rehman, M.U.; Hussain, M.; Ud-din, R.; Qamar, M.; Sohail, Q.; Mujahid, M.Y.; Ahmad, G.; Khan, A.J.; Mahboob Ali Sial; Mustatea, P.; Well, E. von; Ncala, M.; Groot, S. de; Hussein, A.H.A.; Tahir, I.S.A.; Idris, A.A.M.; Elamein, H.M.M.; Yann Manes; Joshi, A.K.
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  • AP01 - Exploring genetic diversity for biomass and traits related to canopy photosynthesis
    (CIMMYT, 2019) Molero, G.; Pinto Espinosa, F.; Piñera Chavez, F.J; Rivera-Amado, C.; Sukumaran, S.; Gimeno, J.; Saint Pierre, C.; Reynolds, M.P.
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  • Incorporating complex physiological traits into wheat breeding pipelines
    (CIMMYT, 2018) Molero, G.; Piñera Chavez, F.J; Rivera-Amado, C.; Gimeno, J.; Pinto Espinosa, F.; Sukumaran, S.; Saint Pierre, C.; Reynolds, M.P.
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  • Strategic crossing of biomass and harvest index—source and sink—achieves genetic gains in wheat
    (Springer, 2017) Reynolds, M.P.; Pask, A.; Hoppitt, W.J.E.; Sonder, K.; Sukumaran, S.; Molero, G.; Saint Pierre, C.; Payne, T.S.; Singh, R.P.; Braun, H.J.; González, F.G.; Terrile, I.I.; Barma, N.C.D.; Abdul Hakim, M.; He Zhonghu; Zheru Fan; Novoselovic, D.; Maghraby, M.; Gad, K.I.M.; Galal, E.G.; Hagras, A.; Mohamed M. Mohamed; Morad, A.F.A.; Kumar, U.; Singh, G.P.; Naik, R.; Kalappanavar, I.K.; Biradar, S.; Prasad, S.V.S.; Chatrath, R.; Sharma, I.; Panchabhai, K.; Sohu, V.S.; Gurvinder Singh Mavi; Mishra, V.K.; Balasubramaniam, A.; Jalal Kamali, M.R.; Khodarahmi, M.; Dastfal, M.; Tabib Ghaffary, S.M.; Jafarby, J.; Nikzad, A.R.; Moghaddam, H.A.; Hassan Ghojogh; Mehraban, A.; Solís Moya, E.; Camacho Casas, M.A.; Figueroa, P.; Ireta Moreno, J.; Alvarado Padilla, J.I.; Borbón Gracia, A.; Torres, A.; Quiche, YN.; Upadhyay, S.R.; Pandey, D.; Imtiaz, M.; Rehman, M.U.; Hussain, M.; Ud-din, R.; Qamar, M.; Muhammad Kundi; Mujahid, M.Y.; Ahmad, G.; Khan, A.J.; Mehboob Ali Sial; Mustatea, P.; Well, E. von; Ncala, M.; Groot, S. de; Hussein, A.H.A.; Tahir, I.S.A.; Idris, A.A.M.; Elamein, H.M.M.; Yann Manes; Joshi, A.K.
    To accelerate genetic gains in breeding, physiological trait (PT) characterization of candidate parents can help make more strategic crosses, increasing the probability of accumulating favorable alleles compared to crossing relatively uncharacterized lines. In this study, crosses were designed to complement “source” with “sink” traits, where at least one parent was selected for favorable expression of biomass and/or radiation use efficiency—source—and the other for sink-related traits like harvest-index, kernel weight and grains per spike. Female parents were selected from among genetic resources—including landraces and products of wide-crossing (i.e. synthetic wheat)—that had been evaluated in Mexico at high yield potential or under heat stress, while elite lines were used as males. Progeny of crosses were advanced to the F4 generation within Mexico, and F4-derived F5 and F6 generations were yield tested to populate four international nurseries, targeted to high yield environments (2nd and 3rd WYCYT) for yield potential, and heat stressed environments (2nd and 4th SATYN) for climate resilience, respectively. Each nursery was grown as multi-location yield trials. Genetic gains were achieved in both temperate and hot environments, with most new PT-derived lines expressing superior yield and biomass compared to local checks at almost all international sites. Furthermore, the tendency across all four nurseries indicated either the superiority of the best new PT lines compared with the CIMMYT elite checks, or the superiority of all new PT lines as a group compared with all checks, and in some cases, both. Results support—in a realistic breeding context—the hypothesis that yield and radiation use efficiency can be increased by improving source:sink balance, and validate the feasibility of incorporating exotic germplasm into mainstream breeding efforts to accelerate genetic gains for yield potential and climate resilience.
    Publication
  • Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones
    (Nature Publishing Group, 2016) Saint Pierre, C.; Burgueño, J.; Fuentes Dávila, G.; Figueroa, P.; Solís Moya, E.; Ireta Moreno, J.; Hernández Muela, V.M.; Zamora Villa, V.; Vikram, P.; Mathews, K.L.; Sansaloni, C.; Sehgal, D.; Jarquin, D.; Wenzl, P.; Singh, S.; Crossa, J.
    Genomic and pedigree predictions for grain yield and agronomic traits were carried out using high density molecular data on a set of 803 spring wheat lines that were evaluated in 5 sites characterized by several environmental co-variables. Seven statistical models were tested using two random cross-validations schemes. Two other prediction problems were studied, namely predicting the lines’ performance at one site with another (pairwise-site) and at untested sites (leave-one-site-out). Grain yield ranged from 3.7 to 9.0 t ha−1 across sites. The best predictability was observed when genotypic and pedigree data were included in the models and their interaction with sites and the environmental co-variables. The leave-one-site-out increased average prediction accuracy over pairwise-site for all the traits, specifically from 0.27 to 0.36 for grain yield. Days to anthesis, maturity, and plant height predictions had high heritability and gave the highest accuracy for prediction models. Genomic and pedigree models coupled with environmental co-variables gave high prediction accuracy due to high genetic correlation between sites. This study provides an example of model prediction considering climate data along-with genomic and pedigree information. Such comprehensive models can be used to achieve rapid enhancement of wheat yield enhancement in current and future climate change scenario.
    Publication
  • Phenotyping for breeding and physiological pre-breeding
    (CIMMYT, 2016) Reynolds, M.P.; Molero, G.; Pinto Espinosa, F.; Rivera-Amado, C.; Piñera Chavez, F.J; Sukumaran, S.; Lopes, M.; Saint Pierre, C.
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  • 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.; 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
  • From genebank to field-leveraging genomics to identify and bring novel native variation to breeding pools
    (CIMMYT, 2016) Romero, A.; Hickey, J.; Kilian, A.; Buckler, E.; Marshall, D.S.; Crossa, J.; Petroli, C.; Sansaloni, C.; Molnar, T.L.; Pixley, K.V.; Wenzl, P.; Singh, S.; Burgueño, J.; Charles Chen; Salinas García, G.; Willcox, M.; Saint Pierre, C.
    Potentially valuable genetic variation, the raw material for crop improvement, remains untapped on genebank shelves, at a time when challenges to crop production are unprecedented. Genebanks should NOT be museums. They should enable breeders worldwide to use high-value genetic diversity to meet tomorrow’s challenges
    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, Roberto; 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
  • Exploring and mobilizing the Gene Bank Biodiversity for wheat improvement
    (Public Library of Science, 2015) Sehgal, D.; Vikram, P.; Sansaloni, C.; Ortiz, C.; Saint Pierre, C.; Payne, T.S.; Ellis, M.H.; Amri, A.; Petroli, C.; Wenzl, P.; Singh, S.
    Identifying and mobilizing useful genetic variation from germplasm banks to breeding programs is an important strategy for sustaining crop genetic improvement. The molecular diversity of 1,423 spring bread wheat accessions representing major global production environments was investigated using high quality genotyping-by-sequencing (GBS) loci, and gene-based markers for various adaptive and quality traits. Mean diversity index (DI) estimates revealed synthetic hexaploids to be genetically more diverse (DI= 0.284) than elites (DI = 0.267) and landraces (DI = 0.245). GBS markers discovered thousands of new SNP variations in the landraces which were well known to be adapted to drought (1273 novel GBS SNPs) and heat (4473 novel GBS SNPs) stress environments. This may open new avenues for pre-breeding by enriching the elite germplasm with novel alleles for drought and heat tolerance. Furthermore, new allelic variation for vernalization and glutenin genes was also identified from 47 landraces originating from Iraq, Iran, India, Afghanistan, Pakistan, Uzbekistan and Turkmenistan. The information generated in the study has been utilized to select 200 diverse gene bank accessions to harness their potential in pre-breeding and for allele mining of candidate genes for drought and heat stress tolerance, thus channeling novel variation into breeding pipelines. This research is part of CIMMYT’s ongoing ‘Seeds of Discovery’ project visioning towards the development of high yielding wheat varieties that address future challenges from climate change.
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