Mapping quantitative physiological traits in apple ( Malus × domestica Borkh.)

Efficient breeding and selection of high-quality apple cultivars requires knowledge and understanding of the underlying genetics. The availability of genetic linkage maps constructed with molecular markers enables the detection and analysis of major genes and quantitative trait loci contributing to the quality traits of a genotype. A segregating population of the cross between the apple varieties 'sFiesta' (syn. 'sRed Pippin') and 'sDiscovery' has been observed over three years at three different sites in Switzerland and data on growth habit, blooming behaviour, juvenile period and fruit quality has been recorded. QTL analyses were performed, based on a genetic linkage map consisting of 804 molecular markers and covering all 17 apple chromosomes. With the maximum likelihood based interval mapping method, the investigated complex traits could be dissected into a number of QTLs affecting the observed characters. Genomic regions participating in the genetic control of stem diameter, plant height increment, leaf size, blooming time, blooming intensity, juvenile phase length, time of fruit maturity, number of fruit, fruit size and weight, fruit flesh firmness, sugar content and fruit acidity were identified and compared with previously mapped QTLs in apple. Although 'sDiscovery' fruit displayed a higher acid content, both acidity QTLs were attributed to the sweeter parent 'sFiesta'. This indicated homozygosity at the acidity loci in 'sDiscovery' preventing their detection in the progeny due to the lack of segregatio

Further evidence that imbalance of WT1 isoforms may be involved in Denys-Drash syndrome

No abstract availabl

Microsatellite markers spanning the apple ( Malus x domestica Borkh.) genome

A new set of 148 apple microsatellite markers has been developed and mapped on the apple reference linkage map Fiesta x Discovery. One-hundred and seventeen markers were developed from genomic libraries enriched with the repeats GA, GT, AAG, AAC and ATC; 31 were developed from EST sequences. Markers derived from sequences containing dinucleotide repeats were generally more polymorphic than sequences containing trinucleotide repeats. Additional eight SSRs from published apple, pear, and Sorbus torminalis SSRs, whose position on the apple genome was unknown, have also been mapped. The transferability of SSRs across Maloideae species resulted in being efficient with 41% of the markers successfully transferred. For all 156 SSRs, the primer sequences, repeat type, map position, and quality of the amplification products are reported. Also presented are allele sizes, ranges, and number of SSRs found in a set of nine cultivars. All this information and those of the previous CH-SSR series can be searched at the apple SSR database ( http://www.hidras.unimi.it ) to which updates and comments can be added. A large number of apple ESTs containing SSR repeats are available and should be used for the development of new apple SSRs. The apple SSR database is also meant to become an international platform for coordinating this effort. The increased coverage of the apple genome with SSRs allowed the selection of a set of 86 reliable, highly polymorphic, and overall the apple genome well-scattered SSRs. These SSRs cover about 85% of the genome with an average distance of one marker per 15c

Development and test of 21 multiplex PCRs composed of SSRs spanning most of the apple genome

A series of 21 multiplex (MP) polymerase chain reactions containing simple sequence repeat (SSR) markers spanning most of the apple genome has been developed. Eighty-eight SSR markers, well distributed over all 17 linkage groups (LGs), have been selected. Eighty-four of them were included in 21 different MPs while four could not be included in any MPs. The 21 MPs were then used to genotype approximately 2,000 DNA samples from the European High-quality Disease-Resistant Apples for a Sustainable agriculture project. Two SSRs (CH01d03 and NZAL08) were discarded at an early stage as they did not produce stable amplifications in the MPs, while the scoring of the multilocus (ML) SSR Hi07d11 and CN44794 was too complex for large-scale genotyping. The testing of the remaining 80 SSRs over a large number of different genotypes allowed: (1) a better estimation of their level of polymorphism; as well as of (2) the size range of the alleles amplified; (3) the identification of additional unmapped loci of some ML SSRs; (4) the development of methods to assign alleles to the different loci of ML SSRs and (5) conditions at which an SSR previously described as ML would amplify alleles of a single locus to be determined. These data resulted in the selection of 75 SSRs out of the 80 that are well suited and recommended for large genotyping project

Target Gene Analysis by Microarrays and Chromatin Immunoprecipitation Identifies HEY Proteins as Highly Redundant bHLH Repressors

HEY bHLH transcription factors have been shown to regulate multiple key steps in cardiovascular development. They can be induced by activated NOTCH receptors, but other upstream stimuli mediated by TGFß and BMP receptors may elicit a similar response. While the basic and helix-loop-helix domains exhibit strong similarity, large parts of the proteins are still unique and may serve divergent functions. The striking overlap of cardiac defects in HEY2 and combined HEY1/HEYL knockout mice suggested that all three HEY genes fulfill overlapping function in target cells. We therefore sought to identify target genes for HEY proteins by microarray expression and ChIPseq analyses in HEK293 cells, cardiomyocytes, and murine hearts. HEY proteins were found to modulate expression of their target gene to a rather limited extent, but with striking functional interchangeability between HEY factors. Chromatin immunoprecipitation revealed a much greater number of potential binding sites that again largely overlap between HEY factors. Binding sites are clustered in the proximal promoter region especially of transcriptional regulators or developmental control genes. Multiple lines of evidence suggest that HEY proteins primarily act as direct transcriptional repressors, while gene activation seems to be due to secondary or indirect effects. Mutagenesis of putative DNA binding residues supports the notion of direct DNA binding. While class B E-box sequences (CACGYG) clearly represent preferred target sequences, there must be additional and more loosely defined modes of DNA binding since many of the target promoters that are efficiently bound by HEY proteins do not contain an E-box motif. These data clearly establish the three HEY bHLH factors as highly redundant transcriptional repressors in vitro and in vivo, which explains the combinatorial action observed in different tissues with overlapping expression

Search for the standard model Higgs boson decaying to a bbˉb\bar{b} pair in events with no charged leptons and large missing transverse energy using the full CDF data set

We report on a search for the standard model Higgs boson produced in association with a vector boson in the full data set of proton-antiproton collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II detector at the Tevatron, corresponding to an integrated luminosity of 9.45 fb$^{-1}$. We consider events having no identified charged lepton, a transverse energy imbalance, and two or three jets, of which at least one is consistent with originating from the decay of a $b$ quark. We place 95% credibility level upper limits on the production cross section times standard model branching fraction for several mass hypotheses between 90 and $150 \mathrm{GeV}/c^2$. For a Higgs boson mass of $125 \mathrm{GeV}/c^2$, the observed (expected) limit is 6.7 (3.6) times the standard model prediction.Comment: Accepted by Phys. Rev. Let

Search for the standard model Higgs boson decaying to a bb pair in events with one charged lepton and large missing transverse energy using the full CDF data set

We present a search for the standard model Higgs boson produced in association with a W boson in sqrt(s) = 1.96 TeV p-pbar collision data collected with the CDF II detector at the Tevatron corresponding to an integrated luminosity of 9.45 fb-1. In events consistent with the decay of the Higgs boson to a bottom-quark pair and the W boson to an electron or muon and a neutrino, we set 95% credibility level upper limits on the WH production cross section times the H->bb branching ratio as a function of Higgs boson mass. At a Higgs boson mass of 125 GeV/c2 we observe (expect) a limit of 4.9 (2.8) times the standard model value.Comment: Submitted to Phys. Rev. Lett (v2 contains clarifications suggested by PRL

Search for the standard model Higgs boson decaying to a bb pair in events with two oppositely-charged leptons using the full CDF data set

We present a search for the standard model Higgs boson produced in association with a Z boson in data collected with the CDF II detector at the Tevatron, corresponding to an integrated luminosity of 9.45/fb. In events consistent with the decay of the Higgs boson to a bottom-quark pair and the Z boson to electron or muon pairs, we set 95% credibility level upper limits on the ZH production cross section times the H -> bb branching ratio as a function of Higgs boson mass. At a Higgs boson mass of 125 GeV/c^2 we observe (expect) a limit of 7.1 (3.9) times the standard model value.Comment: To be submitted to Phys. Rev. Let

Biodiversity effects on ecosystem functioning in a 15-year grassland experiment: Patterns, mechanisms, and open questions

In the past two decades, a large number of studies have investigated the relationship between biodiversity and ecosystem functioning, most of which focussed on a limited set of ecosystem variables. The Jena Experiment was set up in 2002 to investigate the effects of plant diversity on element cycling and trophic interactions, using a multi-disciplinary approach. Here, we review the results of 15 years of research in the Jena Experiment, focussing on the effects of manipulating plant species richness and plant functional richness. With more than 85,000 measures taken from the plant diversity plots, the Jena Experiment has allowed answering fundamental questions important for functional biodiversity research. First, the question was how general the effect of plant species richness is, regarding the many different processes that take place in an ecosystem. About 45% of different types of ecosystem processes measured in the ‘main experiment’, where plant species richness ranged from 1 to 60 species, were significantly affected by plant species richness, providing strong support for the view that biodiversity is a significant driver of ecosystem functioning. Many measures were not saturating at the 60-species level, but increased linearly with the logarithm of species richness. There was, however, great variability in the strength of response among different processes. One striking pattern was that many processes, in particular belowground processes, took several years to respond to the manipulation of plant species richness, showing that biodiversity experiments have to be long-term, to distinguish trends from transitory patterns. In addition, the results from the Jena Experiment provide further evidence that diversity begets stability, for example stability against invasion of plant species, but unexpectedly some results also suggested the opposite, e.g. when plant communities experience severe perturbations or elevated resource availability. This highlights the need to revisit diversity–stability theory. Second, we explored whether individual plant species or individual plant functional groups, or biodiversity itself is more important for ecosystem functioning, in particular biomass production. We found strong effects of individual species and plant functional groups on biomass production, yet these effects mostly occurred in addition to, but not instead of, effects of plant species richness. Third, the Jena Experiment assessed the effect of diversity on multitrophic interactions. The diversity of most organisms responded positively to increases in plant species richness, and the effect was stronger for above- than for belowground organisms, and stronger for herbivores than for carnivores or detritivores. Thus, diversity begets diversity. In addition, the effect on organismic diversity was stronger than the effect on species abundances. Fourth, the Jena Experiment aimed to assess the effect of diversity on N, P and C cycling and the water balance of the plots, separating between element input into the ecosystem, element turnover, element stocks, and output from the ecosystem. While inputs were generally less affected by plant species richness, measures of element stocks, turnover and output were often positively affected by plant diversity, e.g. carbon storage strongly increased with increasing plant species richness. Variables of the N cycle responded less strongly to plant species richness than variables of the C cycle. Fifth, plant traits are often used to unravel mechanisms underlying the biodiversity–ecosystem functioning relationship. In the Jena Experiment, most investigated plant traits, both above- and belowground, were plastic and trait expression depended on plant diversity in a complex way, suggesting limitation to using database traits for linking plant traits to particular functions. Sixth, plant diversity effects on ecosystem processes are often caused by plant diversity effects on species interactions. Analyses in the Jena Experiment including structural equation modelling suggest complex interactions that changed with diversity, e.g. soil carbon storage and greenhouse gas emission were affected by changes in the composition and activity of the belowground microbial community. Manipulation experiments, in which particular organisms, e.g. belowground invertebrates, were excluded from plots in split-plot experiments, supported the important role of the biotic component for element and water fluxes. Seventh, the Jena Experiment aimed to put the results into the context of agricultural practices in managed grasslands. The effect of increasing plant species richness from 1 to 16 species on plant biomass was, in absolute terms, as strong as the effect of a more intensive grassland management, using fertiliser and increasing mowing frequency. Potential bioenergy production from high-diversity plots was similar to that of conventionally used energy crops. These results suggest that diverse ‘High Nature Value Grasslands’ are multifunctional and can deliver a range of ecosystem services including production-related services. A final task was to assess the importance of potential artefacts in biodiversity–ecosystem functioning relationships, caused by the weeding of the plant community to maintain plant species composition. While the effort (in hours) needed to weed a plot was often negatively related to plant species richness, species richness still affected the majority of ecosystem variables. Weeding also did not negatively affect monoculture performance; rather, monocultures deteriorated over time for a number of biological reasons, as shown in plant-soil feedback experiments. To summarize, the Jena Experiment has allowed for a comprehensive analysis of the functional role of biodiversity in an ecosystem. A main challenge for future biodiversity research is to increase our mechanistic understanding of why the magnitude of biodiversity effects differs among processes and contexts. It is likely that there will be no simple answer. For example, among the multitude of mechanisms suggested to underlie the positive plant species richness effect on biomass, some have received limited support in the Jena Experiment, such as vertical root niche partitioning. However, others could not be rejected in targeted analyses. Thus, from the current results in the Jena Experiment, it seems likely that the positive biodiversity effect results from several mechanisms acting simultaneously in more diverse communities, such as reduced pathogen attack, the presence of more plant growth promoting organisms, less seed limitation, and increased trait differences leading to complementarity in resource uptake. Distinguishing between different mechanisms requires careful testing of competing hypotheses. Biodiversity research has matured such that predictive approaches testing particular mechanisms are now possible