553 research outputs found

    AGL1-AGL6, an Arabidopsis gene family with similarity to floral homeotic and transcription factor genes

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    The predicted products of floral homeotic genes, AGAMOUS (AG) from Arabidopsis thaliana and DEFICIENS A (DEF A) from Antirrhinum majus, have been shown previously to share strong sequence similarity with transcription factors from humans (SRF) and yeast (MCM1). The conserved sequence between these proteins is localized within a domain known to be necessary for the DNA binding and for the dimerization of SRF. We have isolated six new genes from A. thaliana, AGL1-AGL6, which also have this conserved sequence motif. On the basis of the sequence comparison between the AG and AGL genes, they can be assigned to two subfamilies of a large gene family. RNA dot blot analysis indicates that five of these genes (AGL1, AGL2, AGL4, AGL5, and AGL6) are preferentially expressed in flowers. In addition, in situ RNA hybridization experiments with AGL1 and AGL2 show that their mRNAs are detected in some floral organs but not in others. Our results suggest that these genes may act to control many steps of Arabidopsis floral morphogenesis. In contrast, the AGL3 gene is expressed in vegetative tissues as well as in flowers, suggesting that it functions in a broader range of tissues. We discuss possible roles of this gene family during the evolution of flowers

    Redundant regulation of meristem identity and plant architecture by FRUITFULL, APETALA1 and CAULIFLOWER

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    The transition from vegetative to reproductive phases during Arabidopsis development is the result of a complex interaction of environmental and endogenous factors. One of the key regulators of this transition is LEAFY (LFY), whose threshold levels of activity are proposed to mediate the initiation of flowers. The closely related APETALA1 (AP1) and CAULIFLOWER (CAL) meristem identity genes are also important for flower initiation, in part because of their roles in upregulating LFY expression. We have found that mutations in the FRUITFULL (FUL) MADS-box gene, when combined with mutations in AP1 and GAL, lead to a dramatic non-flowering phenotype in which plants continuously elaborate leafy shoots in place of flowers. We demonstrate that this phenotype is caused both by the lack of LFY upregulation and by the ectopic expression of the TERMINAL FLOWER1 (TFL1) gene. Our results suggest that the FUL, AP1 and CAL genes act redundantly to control inflorescence architecture by affecting the domains of LFY and TFL1 expression as well as the relative levels of their activities

    The FRUITFULL MADS-box gene mediates cell differentiation during Arabidopsis fruit development

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    Fruit morphogenesis is a process unique to flowering plants, and yet little is known about its developmental control, Following fertilization, fruits typically undergo a dramatic enlargement that is accompanied by differentiation of numerous distinct cell types. We have identified a mutation in Arabidopsis called fruitfull (ful-1), which abolishes elongation of the silique after fertilization. The ful-1 mutation is caused by the insertion of a DsE transposable enhancer trap element into the 5' untranslated leader of the AGL8 MADS-box gene. beta-glucuronidase (GUS) reporter gene expression in the enhancer trap line is observed specifically in all cell layers of the valve tissue, but not in the replum, the septum or the seeds, and faithfully mimics RNA in situ hybridization data reported previously, The lack of coordinated growth of the fruit tissues leads to crowded seeds, a failure of dehiscence and, frequently, the premature rupture of the carpel valves, The primary defect of ful-1 fruits is within the valves, whose cells fail to elongate and differentiate. Stomata, which are frequent along the epidermis of wild-type valves, are completely eliminated in the ful mutant valves. In addition to the effect on fruit development, ful cauline leaves are broader than those of wild type and show a reduction in the number of internal cell layers. These data suggest that AGL8/FUL regulates the transcription of genes required for cellular differentiation during fruit and leaf development

    Maize Floral Development: New Genes and Old Mutants.

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    AGL1-AGL6, an Arabidopsis gene family with similarity to floral homeotic and transcription factor genes

    Get PDF
    The predicted products of floral homeotic genes, AGAMOUS (AG) from Arabidopsis thaliana and DEFICIENS A (DEF A) from Antirrhinum majus, have been shown previously to share strong sequence similarity with transcription factors from humans (SRF) and yeast (MCM1). The conserved sequence between these proteins is localized within a domain known to be necessary for the DNA binding and for the dimerization of SRF. We have isolated six new genes from A. thaliana, AGL1-AGL6, which also have this conserved sequence motif. On the basis of the sequence comparison between the AG and AGL genes, they can be assigned to two subfamilies of a large gene family. RNA dot blot analysis indicates that five of these genes (AGL1, AGL2, AGL4, AGL5, and AGL6) are preferentially expressed in flowers. In addition, in situ RNA hybridization experiments with AGL1 and AGL2 show that their mRNAs are detected in some floral organs but not in others. Our results suggest that these genes may act to control many steps of Arabidopsis floral morphogenesis. In contrast, the AGL3 gene is expressed in vegetative tissues as well as in flowers, suggesting that it functions in a broader range of tissues. We discuss possible roles of this gene family during the evolution of flowers

    Identifying and Seeing beyond Multiple Sequence Alignment Errors Using Intra-Molecular Protein Covariation

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    BACKGROUND: There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively important residue pairs in a sequence alignment. Different alignments of the same protein family give different results demonstrating that covariation depends on the quality of the sequence alignment. We thus hypothesized that current criteria are insufficient to build alignments for use with covariation analyses. METHODOLOGY/PRINCIPAL FINDINGS: We show that current criteria are insufficient to build alignments for use with covariation analyses as systematic sequence alignment errors are present even in hand-curated structure-based alignment datasets like those from the Conserved Domain Database. We show that current non-parametric covariation statistics are sensitive to sequence misalignments and that this sensitivity can be used to identify systematic alignment errors. We demonstrate that removing alignment errors due to 1) improper structure alignment, 2) the presence of paralogous sequences, and 3) partial or otherwise erroneous sequences, improves contact prediction by covariation analysis. Finally we describe two non-parametric covariation statistics that are less sensitive to sequence alignment errors than those described previously in the literature. CONCLUSIONS/SIGNIFICANCE: Protein alignments with errors lead to false positive and false negative conclusions (incorrect assignment of covariation and conservation, respectively). Covariation analysis can provide a verification step, independent of traditional criteria, to identify systematic misalignments in protein alignments. Two non-parametric statistics are shown to be somewhat insensitive to misalignment errors, providing increased confidence in contact prediction when analyzing alignments with erroneous regions because of an emphasis on they emphasize pairwise covariation over group covariation

    An Observational Cohort Study of the Kynurenine to Tryptophan Ratio in Sepsis: Association with Impaired Immune and Microvascular Function

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    Both endothelial and immune dysfunction contribute to the high mortality rate in human sepsis, but the underlying mechanisms are unclear. In response to infection, interferon-Ξ³ activates indoleamine 2,3-dioxygenase (IDO) which metabolizes the essential amino acid tryptophan to the toxic metabolite kynurenine. IDO can be expressed in endothelial cells, hepatocytes and mononuclear leukocytes, all of which contribute to sepsis pathophysiology. Increased IDO activity (measured by the kynurenine to tryptophan [KT] ratio in plasma) causes T-cell apoptosis, vasodilation and nitric oxide synthase inhibition. We hypothesized that IDO activity in sepsis would be related to plasma interferon-Ξ³, interleukin-10, T cell lymphopenia and impairment of microvascular reactivity, a measure of endothelial nitric oxide bioavailability. In an observational cohort study of 80 sepsis patients (50 severe and 30 non-severe) and 40 hospital controls, we determined the relationship between IDO activity (plasma KT ratio) and selected plasma cytokines, sepsis severity, nitric oxide-dependent microvascular reactivity and lymphocyte subsets in sepsis. Plasma amino acids were measured by high performance liquid chromatography and microvascular reactivity by peripheral arterial tonometry. The plasma KT ratio was increased in sepsis (median 141 [IQR 64–235]) compared to controls (36 [28–52]); p<0.0001), and correlated with plasma interferon-Ξ³ and interleukin-10, and inversely with total lymphocyte count, CD8+ and CD4+ T-lymphocytes, systolic blood pressure and microvascular reactivity. In response to treatment of severe sepsis, the median KT ratio decreased from 162 [IQR 100–286] on day 0 to 89 [65–139] by day 7; pβ€Š=β€Š0.0006) and this decrease in KT ratio correlated with a decrease in the Sequential Organ Failure Assessment score (p<0.0001). IDO-mediated tryptophan catabolism is associated with dysregulated immune responses and impaired microvascular reactivity in sepsis and may link these two fundamental processes in sepsis pathophysiology

    Phylogenetic Dependency Networks: Inferring Patterns of CTL Escape and Codon Covariation in HIV-1 Gag

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    HIV avoids elimination by cytotoxic T-lymphocytes (CTLs) through the evolution of escape mutations. Although there is mounting evidence that these escape pathways are broadly consistent among individuals with similar human leukocyte antigen (HLA) class I alleles, previous population-based studies have been limited by the inability to simultaneously account for HIV codon covariation, linkage disequilibrium among HLA alleles, and the confounding effects of HIV phylogeny when attempting to identify HLA-associated viral evolution. We have developed a statistical model of evolution, called a phylogenetic dependency network, that accounts for these three sources of confounding and identifies the primary sources of selection pressure acting on each HIV codon. Using synthetic data, we demonstrate the utility of this approach for identifying sites of HLA-mediated selection pressure and codon evolution as well as the deleterious effects of failing to account for all three sources of confounding. We then apply our approach to a large, clinically-derived dataset of Gag p17 and p24 sequences from a multicenter cohort of 1144 HIV-infected individuals from British Columbia, Canada (predominantly HIV-1 clade B) and Durban, South Africa (predominantly HIV-1 clade C). The resulting phylogenetic dependency network is dense, containing 149 associations between HLA alleles and HIV codons and 1386 associations among HIV codons. These associations include the complete reconstruction of several recently defined escape and compensatory mutation pathways and agree with emerging data on patterns of epitope targeting. The phylogenetic dependency network adds to the growing body of literature suggesting that sites of escape, order of escape, and compensatory mutations are largely consistent even across different clades, although we also identify several differences between clades. As recent case studies have demonstrated, understanding both the complexity and the consistency of immune escape has important implications for CTL-based vaccine design. Phylogenetic dependency networks represent a major step toward systematically expanding our understanding of CTL escape to diverse populations and whole viral genes
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