RESUMEN
In Citrus, the response to environmental floral inductive signals is inhibited by the presence of developing fruits. The mechanism involves epigenetic activation of the CcMADS19 locus (FLC orthologue), encoding a floral repressor. To understand how this epigenetic regulation is reverted to allow flowering in the following season, we have forced precocious sprouting of axillary buds in fruit-bearing shoots, and examined the competence to floral inductive signals of old and new leaves derived from them. We have found that CcMADS19 is enriched in repressive H3K27me3 marks in young, but not old leaves, revealing that axillary buds retain a silenced version of the floral repressor that is mitotically transmitted to the newly emerging leaves, which are able to induce flowering. Therefore, we propose that flowering in Citrus is necessarily preceded by vegetative sprouting, so that the competence to respond to floral inductive signals is reset in the new leaves.
Asunto(s)
Proteínas de Arabidopsis , Citrus , Proteínas de Arabidopsis/metabolismo , Citrus/genética , Citrus/metabolismo , Epigénesis Genética , Flores/genética , Flores/metabolismo , Frutas/genética , Frutas/metabolismo , Regulación de la Expresión Génica de las PlantasRESUMEN
The comparison of homologous proteins from different species is a first step toward a function assignment and a reconstruction of the species evolution. Though local alignment is mostly used for this purpose, global alignment is important for constructing multiple alignments or phylogenetic trees. However, statistical significance of global alignments is not completely clear, lacking a specific statistical model to describe alignments or depending on computationally expensive methods like Z-score. Recently we presented a normalized global alignment, defined as the best compromise between global alignment cost and length, and showed that this new technique led to better classification results than Z-score at a much lower computational cost. However, it is necessary to analyze the statistical significance of the normalized global alignment in order to be considered a completely functional algorithm for protein alignment. Experiments with unrelated proteins extracted from the SCOP ASTRAL database showed that normalized global alignment scores can be fitted to a log-normal distribution. This fact, obtained without any theoretical support, can be used to derive statistical significance of normalized global alignments. Results are summarized in a table with fitted parameters for different scoring schemes.
Asunto(s)
Algoritmos , Filogenia , Proteínas/genética , Alineación de Secuencia/métodos , Biología Computacional , Modelos Estadísticos , Análisis de Secuencia de Proteína , Programas InformáticosRESUMEN
Global alignment is used to compare proteins in different fields, for example in phylogenetic research. In order to reduce the length and composition dependence of global alignment scores, Z-score is computed with a Monte-Carlo algorithm. This technique requires a great number of sequence alignments on shuffled sequences, leading to a high computational cost. In this work, a normalized global alignment score is introduced in order to correct the length dependence of global alignments. This score is defined as the best ratio between the score of an alignment and its length, and an algorithm to compute it based on fractional programming is implemented. The properties and effectiveness of normalized global alignment applied to protein comparison are analyzed. Experiments with proteins selected from the SCOP ASTRAL database were run to study relationship of normalized global alignment with Z-score and performance in homologous detection. Results show that normalized global alignment has a computational cost equivalent to 2.5 Needleman-Wunsch runs and a linear relationship with Z-score. This linearity allows us to use normalized global alignment as a cheap substitute to a computationally expensive Z-score. Experiments show that normalized global alignment improves the ability to identify homologous proteins. Software used to compute normalized global alignments is available from http://www3.uji.es/â¼peris/nga.