The rin, nor and Cnr spontaneous mutations inhibit tomato fruit ripening in additive and epistatic manners

Tomato fruit ripening is regulated by transcription factors (TFs), their downstream effector genes, and the ethylene biosynthesis and signalling pathway. Spontaneous non-ripening mutants ripening inhibitor (rin), non-ripening (nor) and Colorless non-ripening (Cnr) correspond with mutations in or near the TF-encoding genes MADS-RIN, NAC-NOR and SPL-CNR, respectively. Here, we produced heterozygous single and double mutants of rin, nor and Cnr and evaluated their functions and genetic interactions in the same genetic background. We showed how these mutations interact at the level of phenotype, individual effector gene expression, and sensory and quality aspects, in a dose-dependent manner. Rin and nor have broadly similar quantitative effects on all aspects, demonstrating their additivity in fruit ripening regulation. We also found that the Cnr allele is epistatic to rin and nor and that its pleiotropic effects on fruit size and volatile production, in contrast to the well-known dominant effect on ripening, are incompletely dominant, or recessive.</p

Induced point mutations in the phytoene synthase 1 gene cause differences in carotenoid content during tomato fruit ripening

In tomato, carotenoids are important with regard to major breeding traits such as fruit colour and human health. The enzyme phytoene synthase (PSY1) directs metabolic flux towards carotenoid synthesis. Through TILLING (Targeting Induced Local Lesions IN Genomes), we have identified two point mutations in the Psy1 gene. The first mutation is a knockout allele (W180*) and the second mutation leads to an amino acid substitution (P192L). Plants carrying the Psy1 knockout allele show fruit with a yellow flesh colour similar to the r, r mutant, with no further change in colour during ripening. In the line with P192L substitution, fruit remain yellow until 3 days post-breaker and eventually turn red. Metabolite profiling verified the absence of carotenoids in the W180* line and thereby confirms that PSY1 is the only enzyme introducing substrate into the carotenoid pathway in ripening fruit. More subtle effects on carotenoid accumulation were observed in the P192L line with a delay in lycopene and β-carotene accumulation clearly linked to a very slow synthesis of phytoene. The observation of lutein degradation with ripening in both lines showed that lutein and its precursors are still synthesised in ripening fruit. Gene expression analysis of key genes involved in carotenoid biosynthesis revealed that expression levels of genes in the pathway are not feedback-regulated by low levels or absence of carotenoid compounds. Furthermore, protein secondary structure modelling indicated that the P192L mutation affects PSY1 activity through misfolding, leading to the low phytoene accumulation

Identification of candidate genes associated with less-photosensitive anthocyanin phenotype using an EMS mutant (pind) in eggplant (Solanum melongena L.)

Eggplant (Solanum melongena L.) is a highly nutritious and economically important vegetable crop. However, the fruit peel of eggplant often shows poor coloration owing to low-light intensity during cultivation, especially in the winter. The less-photosensitive varieties produce anthocyanin in low light or even dark conditions, making them valuable breeding materials. Nevertheless, genes responsible for anthocyanin biosynthesis in less-photosensitive eggplant varieties are not characterized. In this study, an EMS mutant, named purple in the dark (pind), was used to identify the key genes responsible for less-photosensitive coloration. Under natural conditions, the peel color and anthocyanin content in pind fruits were similar to that of wildtype ‘14-345’. The bagged pind fruits were light purple, whereas those of ‘14-345’ were white; and the anthocyanin content in the pind fruit peel was significantly higher than that in ‘14-345’. Genetic analysis revealed that the less-photosensitive trait was controlled by a single dominant gene. The candidate gene was mapped on chromosome 10 in the region 7.72 Mb to 11.71 Mb. Thirty-five differentially expressed genes, including 12 structural genes, such as CHS, CHI, F3H, DFR, ANS, and UFGT, and three transcription factors MYB113, GL3, and TTG2, were identified in pind using RNA-seq. Four candidate genes EGP21875 (myb domain protein 113), EGP21950 (unknown protein), EGP21953 (CAAX amino-terminal protease family protein), and EGP21961 (CAAX amino-terminal protease family protein) were identified as putative genes associated with less-photosensitive anthocyanin biosynthesis in pind. These findings may clarify the molecular mechanisms underlying less-photosensitive anthocyanin biosynthesis in eggplant

Constraint-based probabilistic learning of metabolic pathways from tomato volatiles

Clustering and correlation analysis techniques have become popular tools for the analysis of data produced by metabolomics experiments. The results obtained from these approaches provide an overview of the interactions between objects of interest. Often in these experiments, one is more interested in information about the nature of these relationships, e.g., cause-effect relationships, than in the actual strength of the interactions. Finding such relationships is of crucial importance as most biological processes can only be understood in this way. Bayesian networks allow representation of these cause-effect relationships among variables of interest in terms of whether and how they influence each other given that a third, possibly empty, group of variables is known. This technique also allows the incorporation of prior knowledge as established from the literature or from biologists. The representation as a directed graph of these relationship is highly intuitive and helps to understand these processes. This paper describes how constraint-based Bayesian networks can be applied to metabolomics data and can be used to uncover the important pathways which play a significant role in the ripening of fresh tomatoes. We also show here how this methods of reconstructing pathways is intuitive and performs better than classical techniques. Methods for learning Bayesian network models are powerful tools for the analysis of data of the magnitude as generated by metabolomics experiments. It allows one to model cause-effect relationships and helps in understanding the underlying processes

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A

The Sloan Digital Sky Survey quasar catalog: tenth data release

We present the Data Release 10 Quasar (DR10Q) catalog from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. The catalog includes all BOSS objects that were targeted as quasar candidates during the first 2.5 years of the survey and that are confirmed as quasars via visual inspection of the spectra, have luminosities M-i[z = 2] 2.15 (117 668) is similar to 5 times greater than the number of z > 2.15 quasars known prior to BOSS. Redshifts and FWHMs are provided for the strongest emission lines (C IV, C III, Mg II). The catalog identifies 16 461 broad absorption line quasars and gives their characteristics. For each object, the catalog presents five-band (u, g, r, i, z) CCD-based photometry with typical accuracy of 0.03 mag and information on the optical morphology and selection method. The catalog also contains X-ray, ultraviolet, near-infrared, and radio emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3600-10 500 angstrom at a spectral resolution in the range 1300 < R < 2500; the spectra can be retrieved from the SDSS Catalog Archive Server. We also provide a supplemental list of an additional 2376 quasars that have been identified among the galaxy targets of the SDSS-III/BOSS

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr