2022

Sandro, P., Kissing Kucek, L., Sorrells, M.E., Dawson, J., Gutierrez, L. 2022. Developing high-quality value-added cereals for organic systems in the U.S. Upper Midwest: hard red winter wheat (Triticum aestivum L.) breeding. Theoretical and Applied Genetics. https://doi.org/10.1007/s00122-022-04112-0

Brzozowski, L.J., Campbell, M.T., Hu, H., Broeckling, C.D., Caffe-Treml, M., Gutierrez, L., Smith, K.P., Sorrells, M.E., Gore, M.A., and Jannink, J-L. 2022. Generalizable approaches for genomic prediction of metabolites in plants. The Plant Genome. https://doi.org/10.1002/tpg2.20205

Locatelli, A., Gutierrez, L., Mastrandea, N., Viega, L., Castro, A.J. 2022. Genetic control of barley phenology in South American environments. Euphytica 218, 53 https://doi.org/10.1007/s10681-022-02993-2

Massman, C., Meints, B., Hernandez, J., Kunze, K., Hayes, P.M., Sorrells, M.E., Smith, K.P., Dawson, J.C., Gutierrez, L. Characterization of agronomic traits in organic spring naked barley. Crop Science. https://doi.org/10.1002/csc2.20686

Locatelli, A.; Gutierrez, L.; Picasso, V. 2022. Vernalization requirements of Kernza intermediate wheatgrass (Thinopyrum intermedium). Crop Science 62(10):524-535. https://doi.org/10.1002/csc2.20667

Neyhart, J.L., Silverstein, K., Gutierrez, L., Smith, K.P. 2022. Optimizing the choice of test locations for multi-trait genotypic evaluation. Crop Science 62:192-202. https://doi.org/10.1002/csc2.20657

2021

Hu, H., Campbell, M.T., Yeats, T.H. Zheng, X., Runcie, D.E., Covarrubias-Pazaran, G., Broeckling, C., Yao, L., Caffe-Treml, M., Gutiérrez, L., Smith, K.P., Tanaka, J., Hoekenga, O.A., Sorrells, M.E., Gore, M.A., Jannink, J.-L.,. Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations. Theor Appl Genet 134, 4043–4054 (2021). https://doi.org/10.1007/s00122-021-03946-4

Brzozowski, L.; Hu, H.; Campbell, M.; Broeckling, C.; Caffe-Treml, M.; Gutierrez, L.; Smith, K.; Sorrells, M.; Gore, M.; Jannink, J.-L. Selection for seed size has indirectly shaped specialized metabolite abundance in oat (Avena sativa L.). G3 (Bethesda). 2021 Dec 10:jkab419. http://doi.org/10.1093/g3journal/jkab419

Campbell, M.C.; Hu, H.; Yeats, T.H; Brzozowski, L.J; Caffe-Treml, M; Gutierrez, L; Smith, K.P; Sorrells, M.E; Gore, M.A; Jannink, J.-L. 2021. Improving genomic prediction for seed quality traits in oat (Avena sativa L.) using trait-specific relationship matrices. Frontiers in Genetics 12: 643733. https://doi.org/10.3389/fgene.2021.643733.

Campbell, M., Hu, H., Yeats, T., Caffe-Treml, M., Gutierrez, L., Smith, K., Sorrells, M., Gore, M., Jannink, J.-L. 2021. Translating insights from the seed metabolome into improved prediction for lipid-composition traits in oat (Avena sativa L.). Genetics 217(3) iyaa043, https://doi.org/10.1093/genetics/iyaa043

Bhatta, M., Sandro, P., Smith, MR., Delaney, O., Voss-Fels, K-P., Gutierrez, L., Hickey, LT. 2021. Need for speed: manipulating plant growth to accelerate breeding cycles. Current Opinion in Plant Biology 60: 101986. https://doi.org/10.1016/j.pbi.2020.101986. Listed as #7 of 1275 articles published in Current Opinion in Plant Biology (Jan 2021) by Altimetric.

Neyhart, J.L., Gutiérrez, L., Smith, K.P. 2021. Using environmental similarities to design training sets for genomewide selection. Crop Science 61(1): 396-409. https://doi.org/10.1002/csc2.20303

González-Barrios P, Bhatta M, Halley M, Sandro P, Gutiérrez L. 2021. Speed breeding and early panicle harvest accelerates oat (Avena sativa L.) breeding cycles. Crop Science 61(1):320-330. https://doi.org/10.1002/csc2.20269

2020

Rosas, J., Escobar, M., Martínez, S., Blanco, P., Pérez, F., Quero, G., Gutiérrez, L., Bonnecarrere, V. 2020. Epistasis and quantitative resistance to Pyricularia oryzae revealed by GWAS in advanced rice breeding populations. Agriculture 10:622. doi:10.3390/agriculture10120622

Baraibar, S.; García, R.; Silva, P.; Lado, B.; Castro, A.; Gutierrez, L.; Kavanová, M.; Quincke, M.; Bhavani, S.; Randhawa, M.; Germán, S.‡ 2020. QTL mapping of resistance to Ug99 and other stem rust races in bread wheat. Molecular Breeding 40:82. https://doi.org/10.1007/s11032-020-01153-5.

Hoefler, R., Gonzalez-Barrios, P., Bhatta, M., Berro, I., Nalin, R.S., Borges, A., Covarrubias, E., Diaz-Garcia, L., Gutierrez, L.‡. 2020. Do spatial designs outperform classic experimental designs? Journal of Agricultural, Biological, and Environmental Statistics 10.1007/s13253-020-00406-2

Steinmetz, O.J., Huset, D.E., Rouse, D.I., Raasch, J.A., Gutiérrez, L., Riday, H. 2020. Synthetic Cultivar Parent Number Impacts on Genetic Drift and Disease Resistance in Alfalfa (Medicago sativa L.). Crop Science. 10.1002/csc2.20219

González Barrios, P., Borges, A., Terra, J., Pérez Bidegain, M., Gutiérrez, L. 2020. Spatio-Temporal Modeling and Competition Dynamics in Forest Tillage Experiments on Early Growth of Eucalyptus grandis L. Forest Science. https://doi.org/10.1093/forsci/fxaa007

Quero, G., Bonnecarrère, V., Simondi, S., Santos, J., Fernandez, S., Gutierrez, L., Garaycochea, S., Borsani, O. 2020. Genetic architecture of photosynthesis energy partitioning as revealed by a genome-wide association approach. Photosynth Res. https://doi.org/10.1007/s11120-020-00721-2

Bhatta M, Gutierrez L, Cammarota L, Cardozo F, Germán S, Gómez-Guerrero B, Pardo MF, Lanaro V, Sayas M, Castro AJ. 2020. Multi-trait Genomic Prediction Model Increased the Predictive Ability for Agronomic and Malting Quality Traits in Barley (Hordeum vulgare L.). G3: Genes, Genomes, Genetics. Mar 1;10(3):1113-24.

2019

González-Barrios, P., Diaz-Garcia, L., Gutierrez, L. 2019. Mega-Environmental Design: using genotype by environment interaction to optimize resources for cultivar testing. Crop Science 59:1–17 doi: 10.2135/cropsci2018.11.0692. This paper proposes a new strategy for dealing with GxE in experimental designs. We are proposing a new experimental design strategy called Mega-Environmental Design (MED) that can optimize resource allocation in large genomic testing evaluations, increasing the response to selection by 40% with the same testing resources.

Borges, A., González-Reymúndez, A., Ernst, O., Cadenazzi, M., Terra, J., Gutierrez L. 2019. Can spatial modeling substitute for experimental design in agricultural experiments? Crop Science 59:44–53. doi: 10.2135/cropsci2018.03.0177.There is a current trend in using spatial corrections instead of experimental designs. By using a thorough methodological approach and state of the art geographical information system coupled with high-throughput computing we proved that experimental design cannot be substituted by spatial corrections.

Berro, I., Nalin, R., Quincke M., Gutierrez, L. 2019. Training population optimization for genomic selection. The Plant Genome 12(3): 1-14. https://doi.org/10.3835/plantgenome2019.04.0028.

Monteverde, E., Gutierrez, L., Blanco, P., Pérez de Vida, F., Rosas, J.E., Bonnecarrère, V., Quero, G., McCouch, S. 2019. Integrating molecular markers and environmental covariates to interpret genotype by environment interaction in rice (Oryza sativa L.) grown in temperate areas. G3: Genes, Genomes, Genetics May 1, 2019 vol. 9 no. 5 1519-1531; https://doi.org/10.1534/g3.119.400064. This paper successfully models environmental covariates to predict genotypic performance in new environments.

Sandro, P., Gutierrez, L., Speranza, P. 2019. Distribution of genetic and phenotypic diversity in the autogamous perennial Paspalum dilatatum subsp. flavescens (Poaceae). Genetic Resources and Crop Evolution 66:1205-1216. doi.org/10.1007/s10722-019-00791-9. This paper uses quantitative genetics principles to study the evolutionary history of local adaptation, population structure, and geographical distribution of plant populations.

Favre, J., Albrecht, K.A., Gutierrez, L., Picasso, V.D. 2019. Harvesting oat forage at late heading increases milk production per unit of area. Crop, Forage and Turfgrass Management 5(1):180046. doi:10.2134/cftm2018.06.0046. The paper compares two oat varieties from our program in terms of forage quality.

Neyhart, J.L., Sweeney, D., Sorrells, M., Kapp, C., McFarland, A., Kephart, K.D., Sherman, J., Stockinger, E.J., Fisk, S., Hayes, P., Daba, S., Mohammadi, M., Hughes, N., Lukens, L., González Barrios, P., Gutierrez, L., Smith, K. 2019. Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection. Journal of Plant Registration 13:270-280. doi:10.3198/jpr2018.06.0037crmp. This is the registration of a mapping population.

2018

Lado, B., Vazquez, D., Quincke, M., Silva, P., Aguilar, I., Gutierrez, L. 2018. Resource Allocation Optimization with Multi-trait Genomic Prediction for Bread Wheat (Triticum aestivum L.) Quality. Theoretical and Applied Genetics 131:2719-2731. doi.org/10.1007/s00122-018-3186-3. In this paper we show how to optimize phenotyping resources for large genomic studies when multiple traits are evaluated. We showed how phenotyping only 50% of the individuals with our proposed strategy can lead to the same response to selection as phenotyping all individuals in the population.

Quero, G., Gutierrez, L., Monteverde, E., Blanco, P., Perez de Vida, F., Rosas, J., Fernandez, S., Garaycochea, S., McCouch, S., Berberian, N., Simondi, S., Bonnecarrere, V. 2018. Genome-wide association study using historical breeding population discovers genomic regions involved in high-quality rice. The Plant Genome 11(3):1-12. doi: 10.3835/plantgenome2017.08.0076. In this paper we identified genomic regions for complex quality traits in rice and identified favorable haplotypes for high grain quality in rice.

Monteverde, E.; Rosas, J.E.; Blanco, P.; Perez de Vida, F.; Bonnecarrere, V.; Quero, G.; Gutierrez, L.; McCouch, S. 2018. Multienvironment models increase prediction accuracy of complex traits in rice advanced breeding lines of rice. Crop Science 58:1519-1530. doi: 10.2135/cropsci2017.09.0564. Rice GWAS paper.

Rosas, J.E., Martinez, S., Blanco, P., Perez de Vida, F., Bonnecarrere, V., Mosquera, G., Cruz, M., Fernandez, S., Garaycochea, Monteverde, E., McCouch, S., Germán, S., Jannink, J.-L., Gutierrez, L. 2018. Resistance to Multiple Temperate and Tropical Stem and Sheath Diseases of Rice. The Plant Genome 11(1):1-13. doi: 10.3835/plantgenome2017.03.0029. This was the first paper to report on genomic regions associated to stem and sheath diseases in rice. One of those regions is being used in marker assisted selection to introgress favorable alleles for the disease resistance.

2017

González Barrios, P., Castro, M., Pérez, O., Vilaró, D., Gutierrez, L. 2017. Genotype by environment interaction in Sunflower (Helianthus annus L.) to optimize trial network efficiency. Sp. J. Agric. Res. 15(4): e0705. doi: 10.5424/sjar/2017154-11016. This paper models genotype by environment interaction to optimize a trial network incorporating environmental covariates to identify yield constraints.

Lado, B., Battenfield, S., Guzman, C., Quincke, M., Singh, R.P., Dreisigacker, S., Peña, J., Fritz, A., Poland, J., Gutierrez, L. 2017. Strategies to select crosses using genomic prediction in two wheat breeding programs. The Plant Genome 10(2):1-12. doi: 10.3835/plantgenome2016.12.0128. This paper proposes a novel approach to select the best parents using parental combinations instead of selecting superior individuals and compares the strategies in two large datasets for complex quantitative traits. This paper reached the i-10 index in 2019.

González Reymúndez, A., de los Campos, G., Gutierrez, L., Lunt, S., Vazquez Saravia, A.I. 2017. Prediction of years of life after diagnosis of breast cancer using omics and omic-by-treatment interactions. Eur J Hum Genet. 2017 25(5):538-544. doi: 10.1038/ejhg.2017.12. This paper reached the i-10 index in 2019.

2016

Brandariz, S.P., González Reymúndez, A., Lado, B., Malosetti, M., Garcia, A.A.F., Quincke, M., von Zitzewitz, J., Castro, M., Matus, I., del Pozo, A., Castro, A.J., Gutierrez, L. 2016. Ascertainment bias from imputation methods evaluation in wheat. BMC Genomics 17:773 doi: 10.1186/s12864-016-3120-5. This is the first paper to demonstrate ascertainment bias in molecular marker imputation for genome-wide association studies. We demonstrated how the use of imputed data can lead to misleading conclusion in genome-wide association mapping.

Racedo, J., Gutierrez, L., Perera, M.F., Ostengo, S., Pardo, E.M., Cuenya, M.I., Wellin, B., Castagnaro, A.P. 2016. Genome-wide association mapping of quantitative traits in a breeding population of sugarcane. BMC Plant Biology 16:142. doi: 10.1186/s12870-016-0829-x. This paper reached the i-10 index in 2017.

Rosas, J., Martinez, S., Bonnecarrere, V., Perez de Vida, F., Blanco, P., Malosetti, M., Gutierrez, L. 2016. Comparison of Phenotyping Methods for Resistance to Sclerotium oryzae (Cattaneo) and Rhizoctonia oryzae-sativae (Sawada) in Rice. Crop Science 56:1619–1627. doi: 10.2135/cropsci2015.09.0598. This paper compares five phenotyping strategies for disease resistance evaluation in rice and uses the best one to characterize a large mapping population.

Lado, B., González-Barrios, P., Quincke, M., Silva, P., and Gutierrez, L. 2016. Modelling Genotype by Environment Interaction for Genomic Selection with Unbalanced Data from a Wheat (Triticum aestivum L.) Breeding Program. Crop Science 56:1-15. doi: 10.2135/cropsci2015.04.0207. This paper proposes a new strategy for dealing with GxE with genomic selection by using mega-environments. It was an invited paper to a special edition of Crop Science on genotype by environment interaction. This paper reached the i-10 index in 2017.

Mourelle, D., Gaiero, P., Speroni, G., Millan, C., Gutierrez, L., and Mazzella, C. 2016. Comparative pollen morphology and viability among endangered species of Butia (Arecaceae) and its implications for delimitation and conservation. Palinology 40:160-171. doi: 10.1080/01916122.2014.999955.

2015

Bonilla, C., Terra, J.A., Gutierrez, L., and Roel, A. 2015. Harvesting Precision Agriculture Benefits in Rice in Uruguay (in Spanish). Agrociencia (Uruguay) 19(1): 112-121. This paper uses spatial modeling to identify biological constraints to rice yield production at farm scales.

González-Barrios, P., Pérez-Bidegain, M., and Gutierrez, L. 2015. Effects of tillage intensities on spatial soil variability and site-specific management in early growth of Eucalyptus grandis. Forest Ecology and Management 346:41-50. doi:10.1016/j.foreco.2015.02.031. This paper uses spatial modeling to address micro-environmental variability within experimental units.

Cajarville, C., Britos, A., Errandonea, N., Gutierrez, L., Cozzolino, D., and Repetto, J. 2015. Diurnal changes in water soluble carbohydrate concentration and effect on in vitro fermentation of Lucerne and fescue in autumn. New Zealand Journal of Agricultural Research 58:281-291. doi: 10.1080/00288233.2015.1018391.

Silva, P., Calvo-Salazar, V., Condon, F., Quincke, M., Pritsch, C., Gutierrez, L., Castro, A., Herrera-Foessel, S., von Zitzewitz, J., and German, S. 2015. Effects and interactions of genes Lr34, Lr68 and Sr2 on wheat leaf rust adult plant resistance in Uruguay. Euphytica 204:599-608. doi: 10.1007/s10681-014-1343-6. This paper reached the i-10 index in 2017.

González-Barrios, P., Speranza, P., Glison, N., Piccardi, M., Balzarni, M., and Gutierrez, L. 2015 Analysis of flowering dynamics heritability in the perennial warm-season grass Paspalum dilatatum. Grass and Forage Science 71:123-131. doi: 10.1111/gfs.12159. This paper identifies the most heritable components of flowering curves as well as the best time to harvest plants. It proposes some novel approaches to phenotyping asynchronous plants.

Gutierrez, L., Germán, S., Pereyra, S., Hayes, PM., Pérez, C.A., Capettini, F., Locatelli, A., Berberian, N.M., Falcioni, E., Estrada, R., Fros, D., Gonza, V., Altamirano, H., Huerta-Espino, J., Neyra, E., Orjeda, G., Sandoval-Islas, S., Singh, R., Turkington, K., and Castro A.J. 2015. Multi-environment multi-QTL association mapping identifies disease resistance QTLs in barley germplasm from Latin America. Theoretical and Applied Genetics 128(3): 501-516. doi: 10.1007/s00122-014-2448-y. This is a critical paper in which a quantitative trait loci by environment interaction (QTLxE) model was explicitly proposed for QTL and GWAS mapping studies. This paper reached the i-10 index in 2016.

Bao, L., Scatoni, I.B., Gaggero, C., Gutierrez, L., Monza, J., and Walker, M.A. 2015. Genetic Diversity of Grape Phylloxera Leaf Galling Populations on Vitis species in Uruguay. American Journal of Enology and Viticulture 66:46-53. doi: 10.5344/ajev.2014.14026

Glison, N., Viega, L., Cornaglia, P, Gutierrez, L, and Speranza, P. 2015. Variability in germination behaviour of Paspalum dilatatum Poir. seeds is genotype dependent. Grass and Forage Science 70(1): 144-153. doi 10.1111/gfs.12119

2014

Rivas, M., Jaurena, M., Gutierrez, L., and Barbieri, R.L. 2014. Grassland diversity under Butia odorata (Barb. Rodr.) Noblick in Uruguay (in Spanish). Agrociencia (Uruguay) 18:14-27.

Peña-Malavera, A., Gutierrez, L., and Balzarini, M. 2014. Principal Components in Associative Mapping. Journal of Basic and Applied Genetics 25(2): 34-40

Picasso, V., Modernel, P.D., Becoña, G., Salvo, L., Gutierrez, L., and Astigarraga, L. 2014. Sustainability of meat production beyond carbon footprint: a synthesis of case studies from grazing systems in Uruguay. Meat Science 98(3): 346 – 354. This paper reached the i-10 index in 2015.

Quero, G., Gutierrez, L., Lascano, R., Monza, J., Sandal, N., and Borsani, O., 2014. Identification of QTLs for shoot and root growth under ionic-osmotic stress in Lotus, using a RIL population. Crop and Pasture Science 65(2): 139-149. doi.org/10.1071/CP13222. This paper uses a quantitative trait loci by environment interaction (QTLxE) model to identify genomic regions associated to abiotic stress.

Porta, B., Rivas, M., Gutierrez, L., and Galván, G. 2014. Variability, Heritability, and Correlations of Agronomic Traits in an Onion Landrace and Derived S1-Lines. Crop Breeding and Applied Biotechnology 14: 29-35

2013 and before

Bellini, I., Gutierrez, L., Tarlera, S., and Fernández, A. 2013. Isolation and Functional Analysis of Denitrifiers in an Aquifer with High Potential for Denitrification. Systematic and Applied Microbiology 36 (7): 507-516. This paper reached the i-10 index in 2017.

Quero, G., Borsani, O., Gutierrez, L., Melchiorre, M., Monza, J., and Lascano, R. 2013. A phenotyping system for evaluating plant stress response in Lotus (in Spanish). Agrociencia (Uruguay) 17(1): 11-21. This paper proposes a phenotyping system for evaluating abiotic stress in plants.

Locatelli, A., Cuesta-Marcos, A., Gutierrez, L., Hayes, P.M., Smith, K.P., and Castro, A.J. 2013. Genome-wide association mapping of agronomic traits in relevant barley germplasm in Uruguay. Molecular Breeding, 31: 631-654. doi 10.1007/s11032-012-9820-x. This paper reached the i-10 index in 2017.

González, P., Pérez, M., Gutierrez, L., Martinez, L., and Garcia-Prechac, F. 2012. Evaluation of Different Tillage Intensities on Eucalyptus grandis on a Typic Hapludult of Uruguay. Agrociencia (Uruguay). 16(3): 302-305. In this paper we used within plot spatial modeling to improve treatment mean comparisons.

Gutierrez, L., Cuesta-Marcos, A., Castro, A.J., Zitzewitz von, J., Schmitt, Mark, and Hayes, P.M. 2011. Association Mapping of Malting Quality Quantitative Trait Loci in Winter Barley: Positive Signals from Small Germplasm Arrays. The Plant Genome 4: 256-272. This paper compared sixteen GWAS methods including several population structure corrections using mixed models for QTL detection. We found that the best model is trait and environment dependent, but most mixed models will identify the QTL of major effect. This paper reached the i-10 index in 2014.

Zitzewitz von, J., Cuesta-Marcos, A., Condon, F., Castro, A.J., Chao, S., Corey, A., Filichkin, T., Fisk, S.P., Gutierrez, L., Haggard, K., Karsai, I., Muehlbauer, G.J., Smith, K.P., Veisz, O., and Hayes, P.M. 2011. The Genetics of Winterhardiness in Barley: Perspectives from Genome-Wide Association Mapping. The Plant Genome 4(1): 76-91. We used the marker cofactor analysis that allowed the independent determination of the two genomic regions for winterhardiness. This paper was key in understanding the genetics of winterhardiness. This paper reached the i-10 index in 2012.

Vidal, R., González, A., Gutierrez, L., Umana, R., and Speranza, P. 2011. Genetic diversity distribution and reproductive system of Stipa neesiana Trin. et Rupr. In Uruguay (in Spanish). Agrociencia (Uruguay). 15(1): 1-12

Gutierrez, L., Nason, J.D., and Jannink, J.-L. Morphological Diversity of Worldwide Barley and Mega-Targets of Selection. 2009. Crop Science 49: 483-497. This paper was part of my Ph.D. Dissertation.

Gutierrez, L., Franco, J., Crossa, J., and Abadie, T. 2003. Comparing a Preliminary Racial Classification with a Numerical Classification of the Maize Landraces of Uruguay. Crop Science 43: 718-727. This paper was part of my undergraduate thesis. This paper reached the i-10 index in 2008.