Identification of Quantitative Trait Loci for Alfalfa Forage Biomass Productivity during Drought Stress

Ray, I. M.; Han, Yuanhong; E, Lei; Meenach, Chris D.; Santantonio, Nicholas; Sledge, M. K.; Pierce, Christopher A.; Sterling, Tracy M.; Kersey, Rossio K.; Bhandari, Hem S.; Monteros, María J.

doi:10.2135/cropsci2014.12.0840

Cited by 34 publications

(98 citation statements)

References 71 publications

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“…GBS and other genomic investigations allowed the identification of QTL influencing various agronomic traits in alfalfa, such as biomass yield [20–22], aluminium tolerance [23], drought tolerance [24], salt tolerance [25], freezing tolerance [26] and biomass yield under drought stress [27]. However, there is a paucity of studies regarding alfalfa forage quality traits.…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

Biazzi¹,

N.²,

Pecetti³

et al. 2017

PLoS ONE

123

114

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Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3–0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits (by genomic selection or MAS) and forage yield.

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Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

Biazzi¹,

N.²,

Pecetti³

et al. 2017

PLoS ONE

123

114

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“…Mapping Population Development, Genotyping, and Genetic Linkage Maps Mapping population development, genotyping, and construction of a genetic linkage map for the current study are briefly summarized below, with additional details provided by Sledge et al (2005) and Ray et al (2015). Two tetraploid alfalfa plants, CH28 (possessing high yield and high CID) and WF1 (possessing low yield and low CID), were intermated.…”

Section: Methodsmentioning

confidence: 99%

“…Increased frequency of drought and rapidly diminishing water resources for irrigation in this region highlight the need to develop alfalfa cultivars and germplasm with improved productivity under reduced irrigation allotments. Opportunities to accelerate improvement of alfalfa drought resilience may also be realized through the identification of favorable DNA marker alleles located at, or near, quantitative trait loci (QTL) associated with drought resistance traits and forage productivity during drought stress (Ray et al, 2015;Zhang et al, 2015). Opportunities to accelerate improvement of alfalfa drought resilience may also be realized through the identification of favorable DNA marker alleles located at, or near, quantitative trait loci (QTL) associated with drought resistance traits and forage productivity during drought stress (Ray et al, 2015;Zhang et al, 2015).…”

Section: Researchmentioning

confidence: 99%

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Genetic Mapping of Water Use Efficiency and Carbon and Nitrogen Metabolism in Drought‐Stressed Alfalfa

et al. 2019

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Identifying quantitative trait loci (QTL) associated with alfalfa (Medicago sativa L.) shoot biomass (SB), water use efficiency, and C and N metabolism can resolve potential target sites for selection and provide new insight into genetic relationships that may exist between key traits in water‐limited environments. The goal of this study was to utilize a tetraploid (2n = 4x = 32) BC1 mapping population and a genetic map based on 334 molecular markers to detect QTL associated with SB, C isotope discrimination (CID), and C and N content during drought stress. Half‐sib families derived from 96 BC1 individuals were evaluated for the SB trait in seeded plots near Las Cruces, NM, during two water‐stressed forage regrowth cycles in each of 3 yr (2005–2007). High costs associated with CID phenotyping precluded evaluation of the entire population. Therefore, in 2006 and 2007, shoot tissue samples for CID, C content, and N content measurements were collected from a subset of 29 families that exhibited extreme SB phenotypes in 2005. Significant genotype effects were observed among these families for SB and CID in both years and C and N content in 2006. Interval mapping identified QTL for all traits. Phenotypic effects of QTL supported significant positive genetic correlations detected between SB and CID, and between C and N content. Estimated QTL positions within the M. truncatula Gaertn. genome sequence assembly encompassed multiple candidate genes affiliated with stomatal development, cuticular wax biosynthesis, C and N metabolism, and abiotic stress response.

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“…El cultivo de la alfalfa mejora la calidad de los suelos al asociarse en sus raíces con bacterias fijadoras del nitrógeno, mejora la productividad en entornos de sequía y, en un esquema de rotación de cultivos, reduce erosión del suelo y mejora sus propiedades físicas (Moreira y Kumar, 2010). El cultivo demanda climas secos con altas temperaturas en verano, por lo que se le encuentra principalmente en regiones áridas y semiáridas (Rojas et al, 2016) donde el ambiente induce diferentes grados de estrés hídrico y los materiales utilizados tienen diferentes atributos para tolerar este estrés (Ray et al, 2015), como ocurre en el Distrito de Riego 05-Delicias (DR-05), en el Estado de Chihuahua.…”

Section: Introductionunclassified

Análisis de la eficiencia productiva del cultivo de alfalfa mediante regresión logística de datos categóricos en el Distrito de Riego 05-Delicias, Chihuahua, México

Cano

Chávez

Morales-Nieto

et al. 2018

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Introducción: La alfalfa es la leguminosa más utilizada en la alimentación del ganado a nivel mundial, su alto valor nutritivo, principalmente por su contenido de proteína, lo hacen un ingrediente atractivo para su inclusión en la dieta. El Estado de Chihuahua es el principal productor de alfalfa en México y el Distrito de Riego 05-Delicias ocupa el segundo lugar en la producción de alfalfa de los distritos de riego en el país, con el 18% la producción, pues este cultivo llega a cubrir casi la mitad de su superficie. El objetivo de este trabajo fue determinar el impacto de cuatro factores de producción sobre la eficiencia productiva del cultivo y generar información de utilidad para la toma de decisiones de productores y autoridades.Método: En este estudio se seleccionaron cuatro variables predictoras (factores de producción) en escala dicotómica: Tenencia de la tierra, Propiedad del predio, Maquinaria especializada y Riego tecnificado, para determinar su efecto sobre la eficiencia productiva en el cultivo de alfalfa como variable de respuesta. Para determinar el mejor ajuste del modelo se recurrió al método de selección de variables por pasos hacia atrás (backward), los datos se analizaron bajo un modelo de Regresión Logística utilizando el procedimiento CATMOD del paquete SAS 9.4 y mediante contrastes para la determinación de los efectos de los factores en las interacciones significativas.Resultados: Se encontró efecto significativo de la triple interacción Propiedad-Maquinaria especializada-Riego tecnificado, así como, en general, de los efectos principales Maquinaria especializada y Riego tecnificado. Al determinar, mediante contrastes, los efectos de las variables dentro de la triple interacción, sobresalió el impacto potencial que produce la existencia de Maquinaria especializada-Riego tecnificado en conjunto, cuando se cuenta con la propiedad del predio con un valor tasa de momios de 16 (número de veces en que se incrementa la probabilidad potencial de alcanzar la eficiencia productiva con estos factores de producción); seguido del efecto de la Maquinaria especializada cuando se tiene la Propiedad, con una tasa de momios de 13.56; y el efecto del Riego tecnificado, cuando se tiene la Propiedad del predio con una tasa de momios de 8.0.Discusión o Conclusión: La eficiencia productiva del cultivo de alfalfa se explicó de manera significativa por la triple interacción de las variables Propiedad-Maquinaria especializada-Riego tecnificado. Se presentó el máximo efecto cuando se es propietario del predio por el efecto conjunto de Maquinaria especializada-Riego tecnificado. La interacción Maquinaria especializada-Riego tecnificado muestra efecto significativo, pero su impacto fue menor cuando no se es propietario del predio.

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Identification of Quantitative Trait Loci for Alfalfa Forage Biomass Productivity during Drought Stress

Cited by 34 publications

References 71 publications

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

Genetic Mapping of Water Use Efficiency and Carbon and Nitrogen Metabolism in Drought‐Stressed Alfalfa

Análisis de la eficiencia productiva del cultivo de alfalfa mediante regresión logística de datos categóricos en el Distrito de Riego 05-Delicias, Chihuahua, México

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