Root traits and yield in sugar beet: identification of AFLP markers associated with root elongation rate

Stevanato, Piergiorgio; Trebbi, Daniele; Saccomani, Massimo

doi:10.1007/s10681-009-0042-1

Cited by 19 publications

(13 citation statements)

References 59 publications

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“…In fact, the deepest fibrous roots, despite being a relatively small fraction of the sugar beet root system ( Fig. 1) (Vamerali et al 2003;Stevanato et al 2010a), can absorb large amounts of min-N, as observed in some vegetables by Kristensen and Thorup-Kristensen (2004). This is especially true in the case of drought when only deep water is available.…”

Section: Introductionmentioning

confidence: 93%

“…These layers can be a potential source of N for deep-rooted crops like sugar beet (Kristensen and Thorup-Kristensen 2008;Stevanato et al 2010a). In fact, the deepest fibrous roots, despite being a relatively small fraction of the sugar beet root system ( Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Blumenthal (2001) calculated the residual min-N content in the 0-1.8 m soil layer. By means of labeled 15 N, Peterson et al (1979) showed that sugar beet utilizes N from depths greater than 1.8 m. Using minirhizotrons, Stevanato et al (2010a) observed fibrous roots and N uptake until 3 m.…”

Section: Introductionmentioning

confidence: 99%

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Sugar Beet Yield and Processing Quality in Relation to Nitrogen Content and Microbiological Diversity of Deep Soil Layer

et al. 2015

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The aim of this study was to estimate the effects of different soil factors on sugar beet yield and processing quality. The parameters investigated included: (i) nitrogen (N) availability; (ii) overall microbial diversity and (iii) abundance of bacterial genes involved in key functions of the N cycle. These traits have been evaluated throughout the entire soil layer (0-2.5 m) explored by the sugar beet root system. Soil samples were taken from two nearby sites (A and B) in the Eastern Po Valley, Italy. At each site, three soil profiles were sampled every 0.5 m and the main soil physical and chemical characteristics were evaluated. ARISA (Amplified Ribosomal Intergenic Spacer Analysis) and Real Time PCR analyses were performed on genomic DNA extracted from soil samples for the estimation of microbial diversity and the quantitative presence of genes for ammonium monooxygenase (amoA-Archaea) and nitrite reductase (nirK). To assess the root length density, observations were made by means of minirhizotrons. At site B profile, organic matter as high as 13 % and min-N around 28 mg kg -1 were found between 2 and 2.5 m depth. Sugar beets harvested at this site showed less sugar content and processing quality than at site A (soil similar to B but without deep N accumulation). Soil collected below 0.5 m displayed a more species-rich composition of microbial communities than in the upper layer. The presence of amoA (nitrification) and nirK (denitrification) genes was found in all layers explored (down to a depth of 2.5 m). These findings highlight the contribution of the deep layers to key processes of the soil N cycle and its availability for deep-rooted crops. The usefulness of sampling soil to the depth reached by the roots to assess N fertilizer requirements is discussed.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

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Sugar Beet Yield and Processing Quality in Relation to Nitrogen Content and Microbiological Diversity of Deep Soil Layer

et al. 2015

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“…sucrose percentage), or the traits are subject to non-additive variation (e.g. root yield), that is, the combination of genes and alleles and their interactions may be more important than the state of the genes themselves (Schafer-Pregl et al 1999;Nilsson et al 1999;Setiawan et al 2000;HjerdinPanagopoulos et al 2002;Schneider et al 2002;Lein et al 2007;Grimmer et al 2008;Stevanato et al 2010;Taguchi et al 2010). This is where molecular markers can be used to gain clarity into the quantitative genetic contributions (e.g., quantitative trait loci, QTLs) as well as provide some context in which they can be deployed effectively, prior to applying markers for assisted selection.…”

Section: Present Situationmentioning

confidence: 99%

Assisted Breeding in Sugar Beets

McGrath

2010

Sugar Tech

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Molecular insight and methods applied to plant breeding and germplasm enhancement is the goal of assisted breeding, also known as marker assisted breeding, marker assisted selection, molecular plant breeding, or genome-wide selection, among others. The basic idea is that most, if not all, heritable components of agronomic performance can be assayed with an unbiased, uniform, and comparatively inexpensive set of measures that are highly or completely correlated with phenotypic values. Typically such heritable components are genetically controlled, thus the panoply of DNA-based correlative methods should provide the requisite tools for assisted breeding to be successful. Whether DNA-based methods are successful in predicting agronomic performance depends on a host of considerations, many of which remain to be completely addressed for sugar beet, and thus assisted breeding remains somewhat empirical in practice, at least with respect to the specific traits of interest. Most sugar beet breeding and improvement programs have initiated assisted breeding efforts, primarily as a first step to discover marker associations with traits. These initial activities serve a number of important functions such as determining the complexity of trait inheritance, narrowing the possible range of genes and loci involved in phenotypic expression in different populations, and following the progress of sugar beet improvement following hybridization with wild and unadapted germplasm. It is unlikely that breeding will or should ever rely completely on assisted methods, however selection of the most promising germplasm can be greatly accelerated using molecular insights and knowledge.

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“…Root traits influencing rapid soil exploitation, such as root elongation rate (RER), could be used to develop crops with greater water and nutrient acquisition (Lynch et al 2014, Saengwilai et al 2014. Recent study of sugar beet highlighted that key root traits as RER, total length, surface area, and number of tips are strictly related to sulfate acquisition and sugar beet yield (Stevanato et al 2010). A significant and positive correlation was demonstrated between yield and nitrogen uptake rate in sorghum or sulfate uptake rate in maize and sugar beet (Cacco et al 1980, Saccomani et al 1981, Nakamura et al 2002, Stevanato et al 2014.…”

Section: Introductionmentioning

confidence: 99%

Single nucleotide polymorphism markers linked to root elongation rate in sugar beet

Stevanato¹,

Trebbi²,

Saccomani³

2017

Biologia plant.

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The aim of this study was to identify single nucleotide polymorphism (SNP) markers genetically linked to root elongation rate (RER) in sugar beet (Beta vulgaris L.). A population of 244 F 3 individuals, obtained from the cross between lines L01 (low RER) and L18 (high RER), was phenotyped by measuring RER of 11-d-old seedlings grown in hydroponic culture. Two DNA bulks of 50 F 3 individuals with extremes phenotypes were used for bulk segregant analysis (BSA) by restriction-associated DNA (RAD) sequencing. A total of 20 376 SNP were identified. SNPs were filtered to reduce the number of false positive and mapped on candidate chromosomal regions the B. vulgaris reference genome. A total of SNPs were selected one of which, SNP10139, was strongly linked (P < 0.01) to RER. The pattern of association between SNP10139 genotype and RER was also evaluated on a breeding line panel comprising 40 low and 40 high RER individuals with different allele frequencies between groups (P < 0.01). The SNP10139 sequence was mapped the B. vulgaris peptide transporter (PTR) gene, a carrier that influences root elongation in Arabidopsis thaliana. Our results suggest that SNP10139 influences RER in sugar beet and sequence information can be used in markerassisted selection programs.

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Root traits and yield in sugar beet: identification of AFLP markers associated with root elongation rate

Cited by 19 publications

References 59 publications

Sugar Beet Yield and Processing Quality in Relation to Nitrogen Content and Microbiological Diversity of Deep Soil Layer

Sugar Beet Yield and Processing Quality in Relation to Nitrogen Content and Microbiological Diversity of Deep Soil Layer

Assisted Breeding in Sugar Beets

Single nucleotide polymorphism markers linked to root elongation rate in sugar beet

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