Identification of Single Nucleotide Polymorphisms and analysis of Linkage Disequilibrium in sunflower elite inbred lines using the candidate gene approach

Background. Association analysis is a powerful tool to identify gene loci that may contribute to phenotypic variation. This includes the estimation of nucleotide diversity, the assessment of linkage disequilibrium structure (LD) and the evaluation of selection processes. Trait mapping by allele association requires a high-density map, which could be obtained by the addition of Single Nucleotide Polymorphisms (SNPs) and short insertion and/or deletions (indels) to SSR and AFLP genetic maps. Nucleotide diversity analysis of randomly selected candidate regions is a promising approach for the success of association analysis and fine mapping in the sunflower genome. Moreover, knowledge of the distance over which LD persists, in agronomically meaningful sunflower accessions, is important to establish the density of markers and the experimental design for association analysis. Results. A set of 28 candidate genes related to biotic and abiotic stresses were studied in 19 sunflower inbred lines. A total of 14,348 bp of sequence alignment was analyzed per individual. In average, 1 SNP was found per 69 nucleotides and 38 indels were identified in the complete data set. The mean nucleotide polymorphism was moderate ( = 0.0056), as expected for inbred materials. The number of haplotypes per region ranged from 1 to 9 (mean = 3.54 1.88). Model-based population structure analysis allowed detection of admixed individuals within the set of accessions examined. Two putative gene pools were identified (G1 and G2), with a large proportion of the inbred lines being assigned to one of them (G1). Consistent with the absence of population sub-structuring, LD for G1 decayed more rapidly (r 2= 0.48 at 643 bp; trend line, pooled data) than the LD trend line for the entire set of 19 individuals (r2= 0.64 for the same distance). Conclusion. Knowledge about the patterns of diversity and the genetic relationships between breeding materials could be an invaluable aid in crop improvement strategies. The relatively high frequency of SNPs within the elite inbred lines studied here, along with the predicted extent of LD over distances of 100 kbp (r2∼0.1) suggest that high resolution association mapping in sunflower could be achieved with marker densities lower than those usually reported in the literature.Fil:Fusari, C.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Lia, V.V. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Hopp, H.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Heinz, R.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Identification of Single Nucleotide Polymorphisms and analysis of Linkage Disequilibrium in sunflower elite inbred lines using the candidate gene approach

Abstract Background Association analysis is a powerful tool to identify gene loci that may contribute to phenotypic variation. This includes the estimation of nucleotide diversity, the assessment of linkage disequilibrium structure (LD) and the evaluation of selection processes. Trait mapping by allele association requires a high-density map, which could be obtained by the addition of Single Nucleotide Polymorphisms (SNPs) and short insertion and/or deletions (indels) to SSR and AFLP genetic maps. Nucleotide diversity analysis of randomly selected candidate regions is a promising approach for the success of association analysis and fine mapping in the sunflower genome. Moreover, knowledge of the distance over which LD persists, in agronomically meaningful sunflower accessions, is important to establish the density of markers and the experimental design for association analysis. Results A set of 28 candidate genes related to biotic and abiotic stresses were studied in 19 sunflower inbred lines. A total of 14,348 bp of sequence alignment was analyzed per individual. In average, 1 SNP was found per 69 nucleotides and 38 indels were identified in the complete data set. The mean nucleotide polymorphism was moderate (θ = 0.0056), as expected for inbred materials. The number of haplotypes per region ranged from 1 to 9 (mean = 3.54 ± 1.88). Model-based population structure analysis allowed detection of admixed individuals within the set of accessions examined. Two putative gene pools were identified (G1 and G2), with a large proportion of the inbred lines being assigned to one of them (G1). Consistent with the absence of population sub-structuring, LD for G1 decayed more rapidly (r2 = 0.48 at 643 bp; trend line, pooled data) than the LD trend line for the entire set of 19 individuals (r2 = 0.64 for the same distance). Conclusion Knowledge about the patterns of diversity and the genetic relationships between breeding materials could be an invaluable aid in crop improvement strategies. The relatively high frequency of SNPs within the elite inbred lines studied here, along with the predicted extent of LD over distances of 100 kbp (r2~0.1) suggest that high resolution association mapping in sunflower could be achieved with marker densities lower than those usually reported in the literature.</p

Identification of candidate genes associated with leaf senescence in cultivated sunflower (Helianthus annuus L.).

Cultivated sunflower (Helianthus annuus L.), an important source of edible vegetable oil, shows rapid onset of senescence, which limits production by reducing photosynthetic capacity under specific growing conditions. Carbon for grain filling depends strongly on light interception by green leaf area, which diminishes during grain filling due to leaf senescence. Transcription factors (TFs) regulate the progression of leaf senescence in plants and have been well explored in model systems, but information for many agronomic crops remains limited. Here, we characterize the expression profiles of a set of putative senescence associated genes (SAGs) identified by a candidate gene approach and sunflower microarray expression studies. We examined a time course of sunflower leaves undergoing natural senescence and used quantitative PCR (qPCR) to measure the expression of 11 candidate genes representing the NAC, WRKY, MYB and NF-Y TF families. In addition, we measured physiological parameters such as chlorophyll, total soluble sugars and nitrogen content. The expression of Ha-NAC01, Ha-NAC03, Ha-NAC04, Ha-NAC05 and Ha-MYB01 TFs increased before the remobilization rate increased and therefore, before the appearance of the first physiological symptoms of senescence, whereas Ha-NAC02 expression decreased. In addition, we also examined the trifurcate feed-forward pathway (involving ORE1, miR164, and ethylene insensitive 2) previously reported for Arabidopsis. We measured transcription of Ha-NAC01 (the sunflower homolog of ORE1) and Ha-EIN2, along with the levels of miR164, in two leaves from different stem positions, and identified differences in transcription between basal and upper leaves. Interestingly, Ha-NAC01 and Ha-EIN2 transcription profiles showed an earlier up-regulation in upper leaves of plants close to maturity, compared with basal leaves of plants at pre-anthesis stages. These results suggest that the H. annuus TFs characterized in this work could play important roles as potential triggers of leaf senescence and thus can be considered putative candidate genes for senescence in sunflower

Identification of Single Nucleotide Polymorphisms and analysis of Linkage Disequilibrium in sunflower elite inbred lines using the candidate gene approach-1

E data calculated for the G1 subset of individuals identified in the STRUCTURE analysis (HA52, HA61, HA89, HA370, HAR3, HAR5, KLM280, PAC2, RHA266, RHA274, RHA293 and RHA374).<p><b>Copyright information:</b></p><p>Taken from "Identification of Single Nucleotide Polymorphisms and analysis of Linkage Disequilibrium in sunflower elite inbred lines using the candidate gene approach"</p><p>http://www.biomedcentral.com/1471-2229/8/7</p><p>BMC Plant Biology 2008;8():7-7.</p><p>Published online 23 Jan 2008</p><p>PMCID:PMC2266750.</p><p></p

Exploring gene networks in two sunflower lines with contrasting leaf senescence phenotype using a system biology approach

Background: Leaf senescence is a complex process, controlled by multiple genetic and environmental variables. In sunflower, leaf senescence is triggered abruptly following anthesis thereby limiting the capacity of plants to keep their green leaf area during grain filling, which subsequently has a strong impact on crop yield. Recently, we performed a selection of contrasting sunflower inbred lines for the progress of leaf senescence through a physiological, cytological and molecular approach. Here we present a large scale transcriptomic analysis using RNA-seq and its integration with metabolic profiles for two contrasting sunflower inbred lines, R453 and B481-6 (early and delayed senescence respectively), with the aim of identifying metabolic pathways associated to leaf senescence. Results: Gene expression profiles revealed a higher number of differentially expressed genes, as well as, higher expression levels in R453, providing evidence for early activation of the senescence program in this line. Metabolic pathways associated with sugars and nutrient recycling were differentially regulated between the lines. Additionally, we identified transcription factors acting as hubs in the co-expression networks; some previously reported as senescence-associated genes in model species but many are novel candidate genes. Conclusions: Understanding the onset and the progress of the senescence process in crops and the identification of these new candidate genes will likely prove highly useful for different management strategies to mitigate the impact of senescence on crop yield. Functional characterization of candidate genes will help to develop molecular tools for biotechnological applications in breeding crop yield.Fil: Moschen, Sebastián Nicolás. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Tucuman-Santiago del Estero. Estación Experimental Agropecuaria Famaillá; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Marino, Johanna Magali. Universidad Nacional de San Martín; ArgentinaFil: Nicosia, Salvador. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Higgins, Janet. Earlham Institute; Reino UnidoFil: Alseekh, Saleh. No especifíca;Fil: Astigueta, Francisco Horacio. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Bengoa Luoni, Sofia Ailin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); ArgentinaFil: Rivarola, Maximo Lisandro. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Fernie, Alisdair R.. No especifíca;Fil: Blanchet, Nicolas. Centre National de la Recherche Scientifique; FranciaFil: Langlade, Nicolas B.. Centre National de la Recherche Scientifique; FranciaFil: Paniego, Norma Beatriz. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Fernández, Paula. No especifíca;Fil: Heinz, Ruth Amelia. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; Argentin

qPCR expression data.

<p>(A) Leaf 10. (B) Leaf 20. Relative transcript level for each candidate gene at different sampled points determined by qPCR. The x –axis showed the thermal time after emergence (°Cd). Asterisks indicate significant difference between each sampling in relation to first sampling point (S-1) and reference genes (p-value<0.05). The red line indicates anthesis time. Error bars correspond to standard errors.</p

Physiological measurements of the progression of senescence.

<p>(A) Chlorophyll content in mg.cm⁻². (B) Total soluble carbohydrates in µg/cm² and (C) Total nitrogen percentage. The red line indicates anthesis time. Blue and green arrows show the date when the <i>Ha-NAC01</i> expression ratio reaches a value of 4 (Log2 ratio = 2) relative to first sampling point in leaf 10 and 20, respectively, determined by qPCR (<i>Ha-EF1α</i> as RG). Error bars correspond to standard errors.</p

<i>Ha-EIN2, Ha-NAC01</i> and <i>miR164</i> expression profiles.

<p>(A) and (C) Transcript levels of <i>Ha-EIN2</i> and <i>Ha-NAC01</i> in relation to the first sampling point, using <i>Ha-EF1α</i> as RG in leaf 10 and 20 respectively. The red line indicates anthesis time. (B) and (D) Northern blot analysis of <i>miR164</i> levels in leaf 10 and 20, RNA from leaves 10 and 20 with an accumulation of degree days (°Cd) between 432 to 861 (B: lanes 1–7) and 670 to 1180 (D:1–10), respectively, was blotted to nylon membrane and hybridized to radioactively labelled sunflower microRNA164 probe. rRNA bands stained with ethidium bromide are shown as loading control. Error bars correspond to standard errors.</p

<i>Ha-CAB2</i> expression profile.

<p>Relative values of <i>Ha-CAB2</i> transcript levels referred to first sampling point, determined by qPCR (leaf 10 and 20) (<i>Ha-EF1α</i> as RG). The red line indicates anthesis time. Error bars correspond to standard errors.</p