Differential regulatory role of nitric oxide in mediating nitrate reductase activity in roots of tomato (Solanum lycocarpum)

Background and Aims

Nitric oxide (NO) has been demonstrated to stimulate the activity of nitrate reductase (NR) in plant roots supplied with a low level of nitrate, and to affect proteins differently, depending on the ratio of NO to the level of protein. Nitrate has been suggested to regulate the level of NO in plants. This present study examined interactive effects of NO and nitrate level on NR activity in roots of tomato (Solanum lycocarpum).

Methods

NR activity, mRNA level of NR gene and concentration of NR protein in roots fed with 0·5 mm or 5 mm nitrate and treated with the NO donors, sodium nitroprusside (SNP) and diethylamine NONOate sodium (NONOate), and the NO scavenger, 2-(4-carboxyphenyl)-4,4,5,5-tetramethyl-imidazoline-1-oxyl-3-oxide (cPTIO), were measured in 25-d-old seedlings.

Key Results

Addition of SNP and NONOate enhanced but cPTIO decreased NR activity in the roots fed with 0·5 mm nitrate. The opposite was true for the roots fed with 5 mm nitrate. However, the mRNA level of the NR gene and the protein concentration of NR enzyme in the roots were not affected by SNP treatment, irrespective of nitrate pre-treatment. Nevertheless, a low rate of NO gas increased while cPTIO decreased the NR activities of the enzyme extracts from the roots at both nitrate levels. Increasing the rate of NO gas further increased NR activity in the enzyme extracts of the roots fed with 0·5 mm nitrate but decreased it when 5 mm nitrate was supplied. Interestingly, the stimulative effect of NO gas on NR activity could be reversed by NO removal through N₂ flushing in the enzyme extracts from the roots fed with 0·5 mm nitrate but not from those with 5 mm nitrate.

Conclusions

The effects of NO on NR activity in tomato roots depend on levels of nitrate supply, and probably result from direct interactions between NO and NR protein.Key words: Nitric oxide, nitrate, nitrate reductase, post-translational regulation, tomato, Solanum lycocarpum     

Linking ascorbic acid production in Ribes nigrum with fruit development and changes in sources and sinks

Background and Aims

Understanding the synthesis of ascorbic acid (l-AsA) in green tissues in model species has advanced considerably; here we focus on its production and accumulation in fruit. In particular, our aim is to understand the links between organs which may be sources of l-AsA (leaves) and those which accumulate it (fruits). The work presented here tests the idea that changes in leaf and fruit number influence the accumulation of l-AsA. The aim was to understand the importance of leaf tissue in the production of l-AsA and to determine how this might provide routes for the manipulation of fruit tissue l-AsA.

Methods

The experiments used Ribes nigrum (blackcurrant), predominantly in field experiments, where the source–sink relationship was manipulated to alter potential leaf l-AsA production and fruit growth and accumulation of l-AsA. These manipulations included reductions in reproductive capacity, by raceme removal, and the availability of assimilates by leaf removal and branch phloem girdling. Natural variation in fruit growth and fruit abscission is also described as this influences subsequent experimental design and the interpretation of l-AsA data.

Key Results

Results show that fruit l-AsA concentration is conserved but total yield of l-AsA per plant is dependent on a number of innate factors many of which relate to raceme attributes. Leaf removal and phloem girdling reduced fruit weight, and a combination of both reduced fruit yields further. It appears that around 50 % of assimilates utilized for fruit growth came from apical leaves, while between 20 and 30 % came from raceme leaves, with the remainder from ‘storage’.

Conclusions

Despite being able to manipulate leaf area and therefore assimilate availability and stored carbohydrates, along with fruit yields, rarely were effects on fruit l-AsA concentration seen, indicating fruit l-AsA production in Ribes was not directly coupled to assimilate supply. There was no supporting evidence that l-AsA production occurred predominantly in green leaf tissue followed by its transfer to developing fruits. It is concluded that l-AsA production occurs predominantly in the fruit of Ribes nigrum.     

Population Structure With Localized Haplotype Clusters

We propose a multilocus version of F_ST and a measure of haplotype diversity using localized haplotype clusters. Specifically, we use haplotype clusters identified with BEAGLE, which is a program implementing a hidden Markov model for localized haplotype clustering and performing several functions including inference of haplotype phase. We apply this methodology to HapMap phase 3 data. With this haplotype-cluster approach, African populations have highest diversity and lowest divergence from the ancestral population, East Asian populations have lowest diversity and highest divergence, and other populations (European, Indian, and Mexican) have intermediate levels of diversity and divergence. These relationships accord with expectation based on other studies and accepted models of human history. In contrast, the population-specific F_ST estimates obtained directly from single-nucleotide polymorphisms (SNPs) do not reflect such expected relationships. We show that ascertainment bias of SNPs has less impact on the proposed haplotype-cluster-based F_ST than on the SNP-based version, which provides a potential explanation for these results. Thus, these new measures of F_ST and haplotype-cluster diversity provide an important new tool for population genetic analysis of high-density SNP data.GENOME-WIDE data sets from worldwide panels of individuals provide an outstanding opportunity to investigate the genetic structure of human populations (Conrad et al. 2006; International Hapmap Consortium 2007; Jakobsson et al. 2008; Auton et al. 2009). Populations around the globe form a continuum rather than discrete units (Serre and Paabo 2004; Weiss and Long 2009). However, notions of discrete populations can be appropriate when, for example, ancestral populations were separated by geographic distance or barriers such that little gene flow occurred.F_ST (Wright 1951; Weir and Cockerham 1984; Holsinger and Weir 2009) is a measure of population divergence. It measures variation between populations vs. within populations. One can calculate a global measure, assuming that all populations are equally diverged from an ancestral population, or one can calculate F_ST for specific populations or for pairs of populations while utilizing data from all populations (Weir and Hill 2002). One use of F_ST is to test for signatures of selection (reviewed in Oleksyk et al. 2010).F_ST may be calculated for single genetic markers. For multiallelic markers, such as microsatellites, this is useful, but single-nucleotide polymorphisms (SNPs) contain much less information when taken one at a time, and thus it is advantageous to calculate averages over windows of markers (Weir et al. 2005) or even over the whole genome. The advantage of windowed F_ST is that it can be used to find regions of the genome that show different patterns of divergence, indicative of selective forces at work during human history.Another measure of human evolutionary history is haplotype diversity. Haplotype diversity may be measured using a count of the number of observed haplotypes in a region or by the expected haplotype heterozygosity based on haplotype frequencies in a region. Application of this regional measure to chromosomal data can be achieved by a haplotype block strategy (Patil et al. 2001) or by windowing (Conrad et al. 2006; Auton et al. 2009).One problem with the analysis of population structure based on genome-wide panels of SNPs is that a large proportion of the SNPs were ascertained in Caucasians, potentially biasing the results of the analyses. Analysis based on haplotypes is less susceptible to such bias (Conrad et al. 2006). This is because haplotypes can be represented by multiple patterns of SNPs; thus lack of ascertainment of a particular SNP does not usually prevent observation of the haplotype. On a chromosome-wide scale, one cannot directly use entire haplotypes, because all the haplotypes in the sample will almost certainly be unique, thus providing no information on population structure. Instead one can use haplotypes on a local basis, either by using windows of adjacent markers or by using localized haplotype clusters, for example those obtained from fastPHASE (Scheet and Stephens 2006) or BEAGLE (Browning 2006; Browning and Browning 2007a).Localized haplotype clusters are a clustering of haplotypes on a localized basis. At the position of each genetic marker, haplotypes are clustered according to their similarity in the vicinity of the position. Both fastPHASE and BEAGLE use hidden Markov modeling to perform the clustering, although the specific models used by the two programs differ.Localized haplotype clusters derived from fastPHASE have been used to investigate haplotype diversity, to create neighbor-joining trees of populations, and to create multidimensional scaling (MDS) plots (Jakobsson et al. 2008). It was found that haplotype clusters showed different patterns of diversity to SNPs, while the neighbor-joining and MDS plots were similar between haplotype clusters and SNPs.In this work, we apply windowed F_ST methods to localized haplotype clusters derived from the BEAGLE program (Browning and Browning 2007a,b, 2009). We consider population-average, population-specific, and pairwise F_ST estimates (Weir and Hill 2002). Population-average F_ST''s either assume that all the populations are equally diverged from a common ancestor, which is not realistic, or represent the average of a set of population-specific values. This can be convenient in that the results are summarized by a single statistic; however, information is lost. A common procedure is to calculate F_ST for each pair of populations, and these values reflect the degree of divergence between the two populations. Different levels of divergence are allowed for each pair of populations but each estimate uses data from only that pair of populations. On the other hand, population-specific F_ST''s allow unequal levels of divergence in a single analysis that makes use of all the data.We compare results from the localized haplotype clusters to those using SNPs directly. The results of applying localized haplotype clusters to population-specific F_ST estimation are very striking, showing better separation of populations and a more realistic pattern of divergence than for population-specific F_ST estimation using SNPs directly. We also use BEAGLE''s haplotype clusters in a haplotype diversity measure and investigate the relationship between this measure of haplotype-cluster diversity and the recombination rate.     

Gene expression and activity of cartilage degrading glycosidases in human rheumatoid arthritis and osteoarthritis synovial fibroblasts

Introduction

Similar to matrix metalloproteinases, glycosidases also play a major role in cartilage degradation. Carbohydrate cleavage products, generated by these latter enzymes, are released from degrading cartilage during arthritis. Some of the cleavage products (such as hyaluronate oligosaccharides) have been shown to bind to Toll-like receptors and provide endogenous danger signals, while others (like N-acetyl glucosamine) are reported to have chondroprotective functions. In the current study for the first time we systematically investigated the expression of glycosidases within the joints.

Methods

Expressions of β-D-hexosaminidase, β-D-glucuronidase, hyaluronidase, sperm adhesion molecule 1 and klotho genes were measured in synovial fibroblasts and synovial membrane samples of patients with rheumatoid arthritis and osteoarthritis by real-time PCR. β-D-Glucuronidase, β-D-glucosaminidase and β-D-galactosaminidase activities were characterized using chromogenic or fluorogenic substrates. Synovial fibroblast-derived microvesicles were also tested for glycosidase activity.

Results

According to our data, β-D-hexosaminidase, β-D-glucuronidase, hyaluronidase, and klotho are expressed in the synovial membrane. Hexosaminidase is the major glycosidase expressed within the joints, and it is primarily produced by synovial fibroblasts. HexA subunit gene, one of the two genes encoding for the alpha or the beta chains of hexosaminidase, was characterized by the strongest gene expression. It was followed by the expression of HexB subunit gene and the β-D-glucuronidase gene, while the expression of hyaluronidase-1 gene and the klotho gene was rather low in both synovial fibroblasts and synovial membrane samples. Tumor growth factor-β1 profoundly downregulated glycosidase expression in both rheumatoid arthritis and osteoarthritis derived synovial fibroblasts. In addition, expression of cartilage-degrading glycosidases was moderately downregulated by proinflammatory cytokines including TNFα, IL-1β and IL-17.

Conclusions

According to our present data, glycosidases expressed by synovial membranes and synovial fibroblasts are under negative regulation by some locally expressed cytokines both in rheumatoid arthritis and osteoarthritis. This does not exclude the possibility that these enzymes may contribute significantly to cartilage degradation in both joint diseases if acting in collaboration with the differentially upregulated proteases to deplete cartilage in glycosaminoglycans.     

Testing for Spatially Divergent Selection: Comparing QST to FST

Q_ST is a standardized measure of the genetic differentiation of a quantitative trait among populations. The distribution of Q_ST''s for neutral traits can be predicted from the F_ST for neutral marker loci. To test for the neutral differentiation of a quantitative trait among populations, it is necessary to ask whether the Q_ST of that trait is in the tail of the probability distribution of neutral traits. This neutral distribution can be estimated using the Lewontin–Krakauer distribution and the F_ST from a relatively small number of marker loci. We develop a simulation method to test whether the Q_ST of a given trait is consistent with the null hypothesis of selective neutrality over space. The method is most powerful with small mean F_ST, strong selection, and a large number (>10) of measured populations. The power and type I error rate of the new method are far superior to the traditional method of comparing Q_ST and F_ST.IN 1993, Spitze (1993) and Prout and Barker (1993) introduced Q_ST, a quantitative genetic analog of Wright''s F_ST. Just as F_ST gives a standardized measure of the genetic differentiation among populations for a genetic locus, Q_ST measures the amount of genetic variance among populations relative to the total genetic variance. In the years since, Q_ST has been frequently used to test for the effects of spatially divergent (or less commonly, spatially uniform) selection (see reviews in Lynch et al. 1999; Merilä and Crnokrak 2001; McKay and Latta 2002; Howe et al. 2003; Leinonen et al. 2008; Whitlock 2008). In principle, the average Q_ST of a neutral additive quantitative trait is expected to be equal to the mean value of F_ST for neutral genetic loci. F_ST can be readily measured on commonly available genetic markers, and Q_ST can be measured as well with an appropriate breeding design in a common-garden setting. As a result, Q_ST promises to be an index of the effect of selection on the quantitative trait. If Q_ST is higher than F_ST, then this is taken as evidence of spatially divergent selection on the trait. If Q_ST is much smaller than F_ST, then this has been taken as evidence of spatially uniform stabilizing selection, which makes the trait diverge less than expected by chance.The comparison with F_ST is essential to rule out genetic drift as an alternative mechanism for phenotypic divergence among populations. Because finite populations may diverge genetically in the absence of selection, divergence must be greater than expected by drift alone if we are to conclusively demonstrate that divergent selection has played a role in genetic differentiation among populations. Therefore it has become common practice to use F_ST of putatively neutral markers as a control for the effects of genetic drift and to compare observed Q_ST values for traits to these neutral F_ST values.These comparisons follow two separate methods, to address related but distinct questions. First, many studies of quantitative genetic differentiation measure the Q_ST of many traits and the F_ST of many loci, followed by a comparison of the mean Q_ST to the mean F_ST. Such a comparison may judge whether the conditions are suitable in that species for local adaptation, that is, whether selective differences between populations are large enough relative to gene flow to allow adaptive differentiation (Whitlock 2008). We do not consider this sort of comparison in this article.The other type of comparison asks whether the Q_ST of a single trait is greater than expected by drift, as measured by F_ST. This type of comparison is most common, but it is statistically difficult. Unfortunately, as emphasized in a recent review by Whitlock (2008), there is great variation in the expected F_ST among neutral loci and among the Q_ST of different neutral traits (see Figure 1). The majority of this variation results from evolutionary differences between loci and not sampling error in the observations. Rogers and Harpending (1983) imply that the distribution of Q_ST of a single neutral trait should be approximately equivalent to that for F_ST of a single neutral locus, and this has been confirmed by simulation for traits determined by additive loci compared to biallelic marker loci (Whitlock 2008). The two distributions are similar, but there is great heterogeneity among traits or loci. As a result, to show that selection is acting on a trait, it is necessary to show that the value of Q_ST has a low probability of being observed given the distribution of neutral Q_ST.Open in a separate windowFigure 1.—The distribution of F_ST for neutral loci and Q_ST for neutral quantitative traits. The histograms show the results of simulations of a set of 10 local populations each of 100 individuals, connected by 5% migration following island model assumptions. The solid line shows the distribution predicted by the Lewontin–Krakauer distribution. The distribution of Q_ST for neutral traits is very similar to the distribution of F_ST for single neutral loci, as can be seen by their mutual good fit to the Lewontin–Krakauer distribution (Figure modified from Whitlock 2008).Comparing Q_ST to the distribution inferred from F_ST is difficult for two reasons. First, typical data sets rarely include enough loci to directly infer the distribution of F_ST without extra inferential steps. In our approach, we use the distribution of Q_ST predicted from the mean F_ST and the χ² distribution by Lewontin and Krakauer (1973) to bridge this gap. Whitlock (2008) has shown that this distribution is appropriate for nearly all realistic situations for traits determined by additive genetic effects. Second, Q_ST for a trait is rarely measured with high precision, so the position of a given estimated Q_ST value in the distribution cannot be known without error.To test the null hypothesis that the spatial distribution of a particular trait is not affected by selection, we wish to compare the observed of that trait (marked with a hat to indicate it is an estimate) to the distribution of Q_ST expected for neutral traits. Unfortunately, calculating the distribution of Q_ST for neutral traits is not straightforward, because the estimate of Q_ST for a particular trait is variable for several reasons. The estimate of Q_ST is subject to measurement error, caused by the finite samples of families and individuals in the quantitative genetic experiment. These cause error in the estimate of the additive genetic variance within populations (V_A,within) and the genetic variance among populations (V_G,among), which translate into error of the estimate of Q_ST. In addition, there is another source of variation in Q_ST among neutral traits, caused by the idiosyncrasies of the evolutionary process in each local population in the study. The true value of Q_ST for the set of populations being studied can vary tremendously around its expectation, even for neutral traits, because by chance a finite set of populations may drift in a similar direction (Whitlock 2008). As a result, measurements of Q_ST can vary because of both statistical and evolutionary variation.Fortunately, these two sources of variation are fairly well understood individually. The sampling error for the estimates of the variance components can be estimated from standard approaches, and this variation can be well approximated using information from the mean squares of the analysis of the breeding experiment (O''Hara and Merilä 2005). The variation in neutral Q_ST that results from heterogeneity of evolutionary history can be approximated by the Lewontin–Krakauer distribution (Lewontin and Krakauer 1973), if information is available on the mean Q_ST of neutral traits (Whitlock 2008). This approximation does not depend on the demographic details of the populations in question (Whitlock 2008), but the effects of deviations from assumptions of additive gene effect have not yet been tested. The mean of the distribution of values of Q_ST for neutral traits is usually not known, but fortunately the mean of the distribution of F_ST of neutral loci is expected to be approximately equal to the mean Q_ST of neutral traits (Spitze 1993), and this does not depend on demographic details (Whitlock 1999). Therefore the mean F_ST measured from a series of genetic markers thought to be selectively neutral can be combined with the Lewontin–Krakauer distribution to predict the distribution of true neutral Q_ST across the range of possible evolutionary trajectories.Given that the mean value of of neutral traits is expected to equal the mean F_ST of neutral markers under certain assumptions (discussed later), we will use as a test statistic and compare the observed quantity to the zero value proposed by the null hypothesis. We will use a traditional hypothesis testing approach, which means that we need to specify the sampling distribution of under the assumption of neutrality. Traditionally, the sampling distribution of is inferred from the data on the trait itself, for example, using bootstrapping to infer the sampling distribution. This is appropriate when calculating a confidence interval for Q_ST but is a biased measure of the sampling variance of neutral Q_ST. The variance of the sampling distribution of varies with its expected value; larger values of true Q_ST have more variable sampling distributions than traits with smaller true Q_ST. This association between Q_ST and its sampling error is quite strong, as shown in Figure 2. As a result, if the sampling properties of neutral are inferred from a trait with high Q_ST, the estimate of the variance of the null distribution will be too high, and the hypothesis test comparing to F_ST will be conservative. On the other hand, if a low Q_ST is used to estimate the variance of the null distribution, the estimated error will be too small, and the test will reject true null hypotheses too often.Open in a separate windowFigure 2.—The width of the estimated sampling distribution of varies with mean Q_ST. The solid line shows the sampling distribution of Q_ST when the true mean Q_ST value is 0.05. The dotted line shows the sampling distribution that would be estimated for Q_ST from a trait that by chance was at the first percentile of this distribution, and the dashed line shows the sampling distribution that would be inferred from a value taken at the 99th percentile. If the Q_ST of a trait differs from the expectation by chance, then the width of the sampling distribution will also be estimated with substantial error. In particular, the error variance of is overestimated with Q_ST estimates that are too high and underestimated for small Q_ST values.We address this problem by using F_ST from putatively neutral maker loci in combination with estimates of the additive genetic variance within populations to predict the sampling variance that would be expected for the Q_ST of a neutral trait. We show that the power and type I error rate of this test are greatly superior to traditional methods.     

Tolerance of combined submergence and salinity in the halophytic stem-succulent Tecticornia pergranulata

Background and Aims

Habitats occupied by many halophytes are not only saline, but are also prone to flooding. Few studies have evaluated submergence tolerance in halophytes.

Methods

Responses to submergence, at a range of salinity levels, were studied for the halophytic stem-succulent Tecticornia pergranulata subsp. pergranulata (syn. Halosarcia pergranulata subsp. pergranulata). Growth and total sugars in succulent stems were assessed as a function of time after submergence. Underwater net photosynthesis, dark respiration, total sugars, glycinebetaine, Na⁺, Cl⁻ and K⁺, in succulent stems, were assessed in a NaCl dose-response experiment.

Key Results

Submerged plants ceased to grow, and tissue sugars declined. Photosynthesis by succulent stems was reduced markedly when underwater, as compared with in air. Capacity for underwater net photosynthesis (P_N) was not affected by 10–400 mm NaCl, but it was reduced by 30 % at 800 mm. Dark respiration, underwater, increased in succulent stems at 200–800 mm NaCl, as compared with those at 10 mm NaCl. On an ethanol-insoluble dry mass basis, K⁺ concentration in succulent stems of submerged plants was equal to that in drained controls, across all NaCl treatments. Na⁺ and Cl⁻ concentrations, however, were elevated in stems of submerged plants, but so was glycinebetaine. Submerged stems increased in succulence, so solutes would have been ‘diluted’ on a tissue-water basis.

Conclusions

Tecticornia pergranulata tolerates complete submergence, even in waters of high salinity. A ‘quiescence response’, i.e. no shoot growth, would conserve carbohydrates, but tissue sugars still declined with time. A low K⁺ : Na⁺ ratio, typical for tissues of succulent halophytes, was tolerated even during prolonged submergence, as evidenced by maintenance of underwater P_N at up to 400 mm NaCl. Underwater P_N provides O₂ and sugars, and thus should enhance survival of submerged plants.Key words: Flooding, halophyte, Halosarcia pergranulata, inundation, inland salt marsh, respiration, Salicornioideae, salt lake, submergence–salinity interaction, tissue solutes, underwater net photosynthesis     

Studies of cardiac muscle with a high permeability to calcium produced by treatment with ethylenediaminetetraacetic acid

Thin strips of frog ventricle were isolated and bathed for 15 min in a solution containing 140 mM KCl, 5 mM Na₂ATP, 3 mM EDTA, and 10 mM Tris buffer at pH 7.0. The muscle was then exposed to contracture solutions containing 140 mM KCl, 5 mM Na₂ATP, 1 mM MgCl₂, 10 mM Tris, 3 mM EGTA, and CaCl₂ in amounts to produce concentrations of free calcium from 10^-4.8 M to 10^-9 M. The muscles developed some tension at approximately 10^-8 M, and maximum tension was achieved in 10^-5 M Ca⁺⁺. They relaxed in Ca⁺⁺ concentrations less than 10^-8 M. The development of tension by the EDTA-treated muscles was normalized by comparison with twitch tension at a stimulation rate of 9 per min before exposure to EDTA. In 10^-5 M Ca⁺⁺ tension was always several times the twitch tension and was greater than the contracture tension of a frog ventricular strip in KCl low Na-Ringer. Tension equal to half-maximum was produced at approximately 10^-6.2 M Ca⁺⁺. Intracellular recording of membrane potential indicated that after EDTA treatment the resting potential of cells in Ringer solution with 10^-5 M Ca or less was between 5 and 20 mv. Contracture solutions did not produce tension without prior treatment with EDTA. The high permeability of the membrane produced by EDTA was reversed and the normal resting and action potentials restored in 1 mM Ca-Ringer. Similar studies of EDTA-treated rabbit right ventricular papillary muscle produced a similar tension vs. Ca⁺⁺ concentration relation, and the high permeability state reversed with exposure to normal Krebs solution.     

Non-Sterilized Fermentative Production of Polymer-Grade L-Lactic Acid by a Newly Isolated Thermophilic Strain Bacillus sp. 2–6

Background

The demand for lactic acid has been increasing considerably because of its use as a monomer for the synthesis of polylactic acid (PLA), which is a promising and environment-friendly alternative to plastics derived from petrochemicals. Optically pure l-lactic acid is essential for polymerization of PLA. The high fermentation cost of l-lactic acid is another limitation for PLA polymers to compete with conventional plastics.

Methodology/Principal Findings

A Bacillus sp. strain 2–6 for production of l-lactic acid was isolated at 55°C from soil samples. Its thermophilic characteristic made it a good lactic acid producer because optically pure l-lactic acid could be produced by this strain under open condition without sterilization. In 5-liter batch fermentation of Bacillus sp. 2–6, 118.0 g/liter of l-lactic acid with an optical purity of 99.4% was obtained from 121.3 g/liter of glucose. The yield was 97.3% and the average productivity was 4.37 g/liter/h. The maximum l-lactic acid concentration of 182.0 g/liter was obtained from 30-liter fed-batch fermentation with an average productivity of 3.03 g/liter/h and product optical purity of 99.4%.

Conclusions/Significance

With the newly isolated Bacillus sp. strain 2–6, high concentration of optically pure l-lactic acid could be produced efficiently in open fermentation without sterilization, which would lead to a new cost-effective method for polymer-grade l-lactic acid production from renewable resources.     

Silicon modifies root anatomy, and uptake and subcellular distribution of cadmium in young maize plants

Background and Aims

Silicon (Si) has been shown to ameliorate the negative influence of cadmium (Cd) on plant growth and development. However, the mechanism of this phenomenon is not fully understood. Here we describe the effect of Si on growth, and uptake and subcellular distribution of Cd in maize plants in relation to the development of root tissues.

Methods

Young maize plants (Zea mays) were cultivated for 10 d hydroponically with 5 or 50 µm Cd and/or 5 mm Si. Growth parameters and the concentrations of Cd and Si were determined in root and shoot by atomic absorption spectrometry or inductively coupled plasma mass spectroscopy. The development of apoplasmic barriers (Casparian bands and suberin lamellae) and vascular tissues in roots were analysed, and the influence of Si on apoplasmic and symplasmic distribution of ¹⁰⁹Cd applied at 34 nm was investigated between root and shoot.

Key Results

Si stimulated the growth of young maize plants exposed to Cd and influenced the development of Casparian bands and suberin lamellae as well as vascular tissues in root. Si did not affect the distribution of apoplasmic and symplasmic Cd in maize roots, but considerably decreased symplasmic and increased apoplasmic concentration of Cd in maize shoots.

Conclusions

Differences in Cd uptake of roots and shoots are probably related to the development of apoplasmic barriers and maturation of vascular tissues in roots. Alleviation of Cd toxicity by Si might be attributed to enhanced binding of Cd to the apoplasmic fraction in maize shoots.     

Disorganized distribution of homogalacturonan epitopes in cell walls as one possible mechanism for aluminium-induced root growth inhibition in maize

Background and Aims

Aluminium (Al) toxicity is one of the most severe limitations to crop production in acid soils. Inhibition of root elongation is the primary symptom of Al toxicity. However, the underlying basis of the process is unclear. Considering the multiple physiological and biochemical functions of pectin in plants, possible involvement of homogalacturonan (HG), one of the pectic polysaccharide domains, was examined in connection with root growth inhibition induced by Al.

Methods

An immunolabelling technique with antibodies specific to HG epitopes (JIM5, unesterified residues flanked by methylesterifed residues; JIM7, methyl-esterified residues flanked by unesterified residues) was used to visualize the distribution of different types of HG in cell walls of root apices of two maize cultivars differing in Al resistance.

Key Results

In the absence of Al, the JIM5 epitope was present around the cell wall with higher fluorescence intensity at cell corners lining the intercellular spaces, and the JIM7 epitope was present throughout the cell wall. However, treatment with 50 µm Al for 3 h produced 10 % root growth inhibition in both cultivars and caused the disappearance of fluorescence in the middle lamella of both epitopes. Prolonged Al treatment (24 h) with 50 % root growth inhibition in ‘B73’, an Al-sensitive cultivar, resulted in faint and irregular distribution of both epitopes. In ‘Nongda3138’, an Al-resistant cultivar, the distribution of HG epitopes was also restricted to the lining of intercellular spaces when a 50 % inhibition to root growth was induced by Al (100 µm Al, 9 h). Altered distribution of both epitopes was also observed when of roots were exposed to 50 µm LaCl₃ for 24 h, resulting in 40 % inhibition of root growth.

Conclusions

Changes in HG distribution and root growth inhibition were highly correlated, indicating that Al-induced perturbed distribution of HG epitopes is possibly involved in Al-induced inhibition of root growth in maize.Key words: Al toxicity, cell wall, homogalacturnonan, immunofluorescence, methylesterification, pectin     

Uptake of aluminium into Arabidopsis root cells measured by fluorescent lifetime imaging

Background and Aims

Measuring the Al³⁺ uptake rate across the plasma membrane of intact root cells is crucial for understanding the mechanisms and time-course of Al toxicity in plants. However, a reliable method with the sufficient spatial and temporal resolution to estimate Al³⁺ uptake in intact root cells does not exist.

Methods

In the current study, fluorescent lifetime imaging (FLIM) analysis was used to quantify Al³⁺ uptake in the root-cell cytoplasm in vivo. This was performed via the estimation of the fluorescence lifetime of Al–lumogallion {5-chloro-3[(2,4-dihydroxyphenyl)azo]-2-hydroxybenzenesulfonic acid} complexes and measurements of intracellular pH while exposing arabidopsis seedlings to acidic and Al³⁺ stresses.

Key Results

The lifetime of Al–lumogallion complexes fluorescence is pH-dependent. The primary sites for Al³⁺ entry are the meristem and distal elongation zones, while Al³⁺ uptake via the cortex and epidermis of the mature root zone is limited. The maximum rates of Al uptake into the cytoplasm (2–3 µmol m⁻³ min⁻¹ for the meristematic root zone and 3–7 µmol m⁻³ min⁻¹ for the mature zone) were observed after a 30-min exposure to 100 µm AlCl₃ (pH 4·2). Intracellular Al concentration increased to 0·4 µm Al within the first 3 h of exposure to 100 µm AlCl₃.

Conclusions

FLIM analysis of the fluorescence of Al–lumogallion complexes can be used to reliably quantify Al uptake in the cytoplasm of intact root cells at the initial stages of Al³⁺ stress.Key words: Acid stress, Al³⁺, aluminium toxicity, Arabidopsis thaliana, low pH, fluorescent lifetime imaging (FLIM), lumogallion     

Detecting Selection in Population Trees: The Lewontin and Krakauer Test Extended

Detecting genetic signatures of selection is of great interest for many research issues. Common approaches to separate selective from neutral processes focus on the variance of F_ST across loci, as does the original Lewontin and Krakauer (LK) test. Modern developments aim to minimize the false positive rate and to increase the power, by accounting for complex demographic structures. Another stimulating goal is to develop straightforward parametric and computationally tractable tests to deal with massive SNP data sets. Here, we propose an extension of the original LK statistic (T_LK), named T_F–LK, that uses a phylogenetic estimation of the population''s kinship () matrix, thus accounting for historical branching and heterogeneity of genetic drift. Using forward simulations of single-nucleotide polymorphisms (SNPs) data under neutrality and selection, we confirm the relative robustness of the LK statistic (T_LK) to complex demographic history but we show that T_F–LK is more powerful in most cases. This new statistic outperforms also a multinomial-Dirichlet-based model [estimation with Markov chain Monte Carlo (MCMC)], when historical branching occurs. Overall, T_F–LK detects 15–35% more selected SNPs than T_LK for low type I errors (P < 0.001). Also, simulations show that T_LK and T_F–LK follow a chi-square distribution provided the ancestral allele frequencies are not too extreme, suggesting the possible use of the chi-square distribution for evaluating significance. The empirical distribution of T_F–LK can be derived using simulations conditioned on the estimated matrix. We apply this new test to pig breeds SNP data and pinpoint outliers using T_F–LK, otherwise undetected using the less powerful T_LK statistic. This new test represents one solution for compromise between advanced SNP genetic data acquisition and outlier analyses.THE development of methods aiming at detecting molecular signatures of selection is one of the major concerns of modern population genetics. Broadly, such methods can be classified into four groups: methods focusing on (i) the interspecific comparison of gene substitution patterns, (ii) the frequency spectrum and models of selective sweeps, (iii) linkage disequilibrium (LD) and haplotype structure, and (iv) patterns of genetic differentiation among populations (for a review see Nielsen 2005). Tests based on the comparison of polymorphism and divergence at the species level inform on mostly ancient selective processes. Population-based approaches, however, are designed to pinpoint modern processes of local adaptation and speciation occurring among populations within a species. Such approaches also become crucial in the fields of agronomical and biomedical sciences, for instance, to pinpoint possible interesting (QTL) regions and disease susceptibility genes. Especially, human, livestock, and cultivated plants genetics may benefit from such methods while whole-genome single-nucleotide polymorphisms (SNPs) genotyping technologies are becoming routinely available (e.g., Barreiro et al. 2008; Flori et al. 2009).In the population genomic era (Luikart et al. 2003), identifying genes under selection or neutral markers influenced by nearby selected genes is a task in itself for quantifying the role of selection in the evolutionary history of species. Conversely, the accurate inference of demographic parameters such as effective population sizes, migration rates, and divergence times between populations relies on the use of neutral marker data sets. One approach of detecting loci under selection (outliers) with population genetic data is based on the genetic differentiation between loci influenced only by neutral processes (genetic drift, mutation, migration) and loci influenced by selection.Lewontin and Krakauer''s (LK) test for the heterogeneity of the inbreeding coefficient (F) across loci was the first to be developed with regard to this concept (Lewontin and Krakauer 1973). The LK test was immediately subject to criticisms (Nei and Maruyama 1975; Lewontin and Krakauer 1975; Robertson, 1975a,b; Tsakas and Krimbas 1976; Nei and Chakravarti 1977; Nei et al. 1977). Indeed, its assumptions are likely to be violated due to loci with high mutation rate, variation of F due to unequal effective population size (N_e) among demes, and correlation of allele frequencies among demes due to historical branching. The robustness of the LK test to the effects of demography was tested through coalescent simulations by Beaumont and Nichols (1996). They tested the influence of different models of population structure on the joint distribution of F_ST (i.e., the inbreeding coefficient F) and heterozygosity (H_e). The F_ST distribution under an infinite-island model is inflated for low H_e values under both the infinite-allele model (IAM) and the stepwise mutation model (SMM) (Beaumont and Nichols 1996). This tendency becomes, however, more marked when strong differences in effective size N_e and gene flow among demes occur, that is, when allele frequencies are correlated among local demes. This suggests an excess of false significant loci when one assumes an infinite-island model as a null hypothesis, while correlations of gene frequencies substantially occur. However, the F_ST distribution shows robustness properties for high H_e values (typical from microsatellite markers). Therefore, Beaumont and Nichols (1996) suggested the possibility of detecting outliers by using the distribution of neutral F_ST conditionally on H_e under the infinite-island model of symmetric migration, with mutation.The problem of accounting for correlations of allele frequencies among subpopulations was discussed by Robertson (1975a), who showed how these correlations inflated the variance of the LK test. Different approaches were taken to cope with the problem. It was, for instance, proposed to restrict the analysis to pairwise comparisons (Tsakas and Krimbas 1976; Vitalis et al. 2001). However, as pointed out by Beaumont (2005), reducing the number of populations to be compared to many pairwise comparisons raises the problem of nonindependence in multiple testing and may reduce the power to detect outliers. Another way was to assume that subpopulation allele frequencies are correlated through a common migrant gene pool, that is, the ancestral population in a star-like population divergence. In this case, subpopulations evolve with an unequal number of migrants coming from the migrant pool and/or to different amounts of genetic drift. This demographic scenario can be explicitly modeled using the multinomial-Dirichlet likelihood approach (Balding 2003). This multinomial-Dirichlet likelihood (or Beta-binomial for biallelic markers such as SNPs) was implemented by Beaumont and Balding (2004) and subsequently by Foll and Gaggiotti (2008), Gautier et al. (2009), Guo et al. (2009), and Riebler et al. (2010), in a Bayesian hierarchical model in which the F_ST is decomposed into two components: a locus-specific (α) effect and a population-specific (β) effect. This Bayesian statistical model together with prior assumptions on α and β was implemented in a Markov chain Monte Carlo (MCMC) algorithm. A substantial improvement made by Foll and Gaggiotti (2008) was to use a reverse-jumping (RJ)-MCMC to simultaneously estimate the posterior distribution of a model with selection (with α and β) and of a model without selection (with β only). More recently, Excoffier et al. (2009) addressed the issue of accounting for “heterogeneous affinities between sampled populations”—in other words, accounting for migrant genes that do not necessarily originate from the same pool—by using a hierarchically structured population model. They showed by simulations that the false positive rate is lower under a hierarchically structured population model than under a simple island model, for the IAM and the SMM applicable to microsatellite markers and for a SNP mutation model. Excoffier et al.(2009) thus proposed to extend the Beaumont and Nichols (1996) method to a hierarchically structured population model.Nowadays, a computational challenge is to analyze data sets with increasing numbers of markers and populations, under complex demographic histories, in a reasonable amount of time. This is especially the case in agronomical and biomedical sciences with the increasingly used biallelic SNP markers. A question arises as to whether F_ST-based methods would be sufficiently powerful to detect outliers with SNP markers. Indeed, for low H_e values, the inflation of the F_ST distribution under the infinite-island model accentuates dramatically when assuming a mutation model typical for SNPs (simulations of Eveno et al. 2008). Excoffier et al. (2009) corroborated these results and also indicated that the F_ST distribution is generally broader under a model of hierarchically structured populations when using SNP markers. In addition, as the authors pinpoint, although the hierarchical island model is more conservative than the island model, an excess of false positives can be obtained “if the underlying genetic structure is more complex …, for instance in case of complex demographic histories, involving population splits, range expansion, bottleneck or admixture events” (Excoffier et al. 2009, p. 12). The Bayesian hierarchical models developed by Beaumont and Balding (2004) and Foll and Gaggiotti (2008) effectively account for strong effective size and migration rate variation among subpopulations, but they still impose a star-like demographic model in which the current populations share a common migrant pool and are not supposed to have undergone historical branching. More practically, MCMC-based methods might suffer from a computational time requirement when analyzing large marker data sets such as SNP chips data sets. Therefore, the development of simple parametric tests potentially dealing with a summary of the population tree, including historical branching as well as population size variation, remains an alternative solution to achieve a good compromise between advanced genetic data acquisition and outlier analyses.In this article, we describe an extension of the original parametric LK test for biallelic markers that deals with complex population trees through a statistic that takes into account the kinship (or coancestry) matrix between populations, under pure drift with no migration. The statistics of the classical test (T_LK) and its extension (T_F–LK) are expected to follow a chi-square distribution with (n – 1) d.f., where n is the number of populations studied. Through forward simulations of neutral SNPs data under increasingly complex demographic histories, we obtained the empirical distribution of both statistics and showed that they follow a chi-square distribution provided the ancestral allele frequencies are not too extreme. These results also emphasize the robustness of these statistics to variation in demographic histories. Forward simulations of the same demographic models but including selection in one population allowed us to evaluate the power of both statistics to detect selection. We show that the extension of the LK test is more powerful at detecting outliers than the classical LK test for complex demographic histories. A comparison with one of the MCMC methods for multinomial-Dirichlet models (Foll and Gaggiotti 2008) also revealed substantial additional power. We apply this new statistical test to a data set of SNP markers in known genes of the pig genome, taking advantage of the availability of microsatellite markers for the estimation of the kinship matrix. This new parametric test can help to screen large marker data sets and large numbers of populations for outliers in a reasonable amount of time, although we recommend to simulate the empirical distribution of the T_F–LK statistics conditionally on the estimated kinship matrix.     

Genomic divergence of zebu and taurine cattle identified through high-density SNP genotyping

Background

Natural selection has molded evolution across all taxa. At an arguable date of around 330,000 years ago there were already at least two different types of cattle that became ancestors of nearly all modern cattle, the Bos taurus taurus more adapted to temperate climates and the tropically adapted Bos taurus indicus. After domestication, human selection exponentially intensified these differences. To better understand the genetic differences between these subspecies and detect genomic regions potentially under divergent selection, animals from the International Bovine HapMap Experiment were genotyped for over 770,000 SNP across the genome and compared using smoothed F_ST. The taurine sample was represented by ten breeds and the contrasting zebu cohort by three breeds.

Results

Each cattle group evidenced similar numbers of polymorphic markers well distributed across the genome. Principal components analyses and unsupervised clustering confirmed the well-characterized main division of domestic cattle. The top 1% smoothed F_ST, potentially associated to positive selection, contained 48 genomic regions across 17 chromosomes. Nearly half of the top F_ST signals (n = 22) were previously detected using a lower density SNP assay. Amongst the strongest signals were the BTA7:~50 Mb and BTA14:~25 Mb; both regions harboring candidate genes and different patterns of linkage disequilibrium that potentially represent intrinsic differences between cattle types. The bottom 1% of the smoothed F_ST values, potentially associated to balancing selection, included 24 regions across 13 chromosomes. These regions often overlap with copy number variants, including the highly variable region at BTA23:~24 Mb that harbors a large number of MHC genes. Under these regions, 318 unique Ensembl genes are annotated with a significant overrepresentation of immune related pathways.

Conclusions

Genomic regions that are potentially linked to purifying or balancing selection processes in domestic cattle were identified. These regions are of particular interest to understand the natural and human selective pressures to which these subspecies were exposed to and how the genetic background of these populations evolved in response to environmental challenges and human manipulation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-876) contains supplementary material, which is available to authorized users.     

Acetyl-l-Carnitine and Oxfenicine on Cardiac Pumping Mechanics in Streptozotocin-Induced Diabetes in Male Wistar Rats

Introduction

In the treatment of patients with diabetes, one objective is an improvement of cardiac metabolism to alleviate the left ventricular (LV) function. For this study, we compared the effects of acetyl-l-carnitine (one of the carnitine derivatives) and of oxfenicine (a carnitine palmitoyltransferase-1 inhibitor) on cardiac pumping mechanics in streptozotocin-induced diabetes in male Wistar rats, with a particular focus on the pressure-flow-volume relationship.

Methods

Diabetes was induced by a single tail vein injection of 55 mg kg⁻¹ streptozotocin. The diabetic animals were treated on a daily basis with either acetyl-L-carnitine (1 g L⁻¹ in drinking water) or oxfenicine (150 mg kg⁻¹ by oral gavage) for 8 wk. They were also compared with untreated age-matched diabetic controls. LV pressure and ascending aortic flow signals were recorded to calculate the maximal systolic elastance (E _max) and the theoretical maximum flow (Q _max). Physically, E _max reflects the contractility of the myocardium as an intact heart, whereas Q _max has an inverse relationship with the LV internal resistance.

Results

When comparing the diabetic rats with their age-matched controls, the cardiodynamic condition was characterized by a decline in E _max associated with the unaltered Q _max. Acetyl-l-carnitine (but not oxfenicine) had reduced cardiac levels of malondialdehyde in these insulin-deficient animals. However, treating with acetyl-l-carnitine or oxfenicine resulted in an increase in E _max, which suggests that these 2 drugs may protect the contractile status from deteriorating in the diabetic heart. By contrast, Q _max showed a significant fall after administration of oxfenicine, but not with acetyl-L-carnitine. The decrease in Q _max corresponded to an increase in total vascular resistance when treated with oxfenicine.

Conclusions

Acetyl-l-carnitine, but not oxfencine, optimizes the integrative nature of cardiac pumping mechanics by preventing the diabetes-induced deterioration in myocardial intrinsic contractility associated with unaltered LV internal resistance.     

Effects of phosphorus supply on growth, phosphate concentration and cluster-root formation in three Lupinus species

Background and Aims

In some lupin species, phosphate deficiency induces cluster-root formation, which enhances P uptake by increasing root surface area and, more importantly, the release of root exudates which enhances P availability.

Methods

Three species of Lupinus, L. albus, L. atlanticus and L. micranthus, with inherently different relative growth rates were cultivated under hydroponics in a greenhouse at four phosphate concentrations (1, 10, 50 and 150 µm) to compare the role of internal P in regulating cluster-root formation.

Key Results

The highest growth rate was observed in L. atlanticus, followed by L. albus and L. micranthus. At 1 µm P, cluster-root formation was markedly induced in all three species. The highest P uptake and accumulation was observed in L. micranthus, followed by L. atlanticus and then L. albus. Inhibition of cluster-root formation was severe at 10 µm P in L. atlanticus, but occurred stepwise with increasing P concentration in the root medium in L. albus.

Conclusions

In L. atlanticus and L. albus cluster-root formation was suppressed by P treatments above 10 µm, indicating a P-inducible regulating system for cluster-root formation, as expected. By contrast, production of cluster roots in L. micranthus, in spite of a high internal P concentration, indicated a lower sensitivity to P status, which allowed P-toxicity symptoms to develop.     

Response to non-uniform salinity in the root zone of the halophyte Atriplex nummularia: growth, photosynthesis, water relations and tissue ion concentrations

Background and Aims

Soil salinity is often heterogeneous, yet the physiology of halophytes has typically been studied with uniform salinity treatments. An evaluation was made of the growth, net photosynthesis, water use, water relations and tissue ions in the halophytic shrub Atriplex nummularia in response to non-uniform NaCl concentrations in a split-root system.

Methods

Atriplex nummularia was grown in a split-root system for 21 d, with either the same or two different NaCl concentrations (ranging from 10 to 670 mm), in aerated nutrient solution bathing each root half.

Key Results

Non-uniform salinity, with high NaCl in one root half (up to 670 mm) and 10 mm in the other half, had no effect on shoot ethanol-insoluble dry mass, net photosynthesis or shoot pre-dawn water potential. In contrast, a modest effect occurred for leaf osmotic potential (up to 30 % more solutes compared with uniform 10 mm NaCl treatment). With non-uniform NaCl concentrations (10/670 mm), 90 % of water was absorbed from the low salinity side, and the reduction in water use from the high salinity side caused whole-plant water use to decrease by about 30 %; there was no compensatory water uptake from the low salinity side. Leaf Na⁺ and Cl⁻ concentrations were 1·9- to 2·3-fold higher in the uniform 670 mm treatment than in the 10/670 mm treatment, whereas leaf K⁺ concentrations were 1·2- to 2·0-fold higher in the non-uniform treatment.

Conclusions

Atriplex nummularia with one root half in 10 mm NaCl maintained net photosynthesis, shoot growth and shoot water potential even when the other root half was exposed to 670 mm NaCl, a concentration that inhibits growth by 65 % when uniform in the root zone. Given the likelihood of non-uniform salinity in many field situations, this situation would presumably benefit halophyte growth and physiology in saline environments.Key words: Split-root system, salinity heterogeneity, root zone heterogeneity, water potential, water use, stomatal conductance, saltbush, leaf ions, photosynthesis, NaCl