Dataset Information

Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

ABSTRACT: Many proteins or other biological macromolecules are localized to more than one subcellular structure. The fraction of a protein in different cellular compartments is often measured by colocalization with organelle-specific fluorescent markers, requiring availability of fluorescent probes for each compartment and acquisition of images for each in conjunction with the macromolecule of interest. Alternatively, tailored algorithms allow finding particular regions in images and quantifying the amount of fluorescence they contain. Unfortunately, this approach requires extensive hand-tuning of algorithms and is often cell type-dependent. Here we describe a machine-learning approach for estimating the amount of fluorescent signal in different subcellular compartments without hand tuning, requiring only the acquisition of separate training images of markers for each compartment. In testing on images of cells stained with mixtures of probes for different organelles, we achieved a 93% correlation between estimated and expected amounts of probes in each compartment. We also demonstrated that the method can be used to quantify drug-dependent protein translocations. The method enables automated and unbiased determination of the distributions of protein across cellular compartments, and will significantly improve imaging-based high-throughput assays and facilitate proteome-scale localization efforts.

SUBMITTER: Peng T

PROVIDER: S-EPMC2840343 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

Peng Tao T Bonamy Ghislain M C GM Glory-Afshar Estelle E Rines Daniel R DR Chanda Sumit K SK Murphy Robert F RF

Proceedings of the National Academy of Sciences of the United States of America 20100201 7

Many proteins or other biological macromolecules are localized to more than one subcellular structure. The fraction of a protein in different cellular compartments is often measured by colocalization with organelle-specific fluorescent markers, requiring availability of fluorescent probes for each compartment and acquisition of images for each in conjunction with the macromolecule of interest. Alternatively, tailored algorithms allow finding particular regions in images and quantifying the amoun ...[more]

PMID: 20133616

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Project description:BackgroundAmplified fragment length polymorphism (AFLP) markers are frequently used for a wide range of studies, such as genome-wide mapping, population genetic diversity estimation, hybridization and introgression studies, phylogenetic analyses, and detection of signatures of selection. An important issue to be addressed for some of these fields is the distribution of the markers across the genome, particularly in relation to gene sequences.ResultsUsing in-silico restriction fragment analysis of the genomes of nine eukaryotic species we characterise the distribution of AFLP fragments across the genome and, particularly, in relation to gene locations. First, we identify the physical position of markers across the chromosomes of all species. An observed accumulation of fragments around (peri) centromeric regions in some species is produced by repeated sequences, and this accumulation disappears when AFLP bands rather than fragments are considered. Second, we calculate the percentage of AFLP markers positioned within gene sequences. For the typical EcoRI/MseI enzyme pair, this ranges between 28 and 87% and is usually larger than that expected by chance because of the higher GC content of gene sequences relative to intergenic ones. In agreement with this, the use of enzyme pairs with GC-rich restriction sites substantially increases the above percentages. For example, using the enzyme system SacI/HpaII, 86% of AFLP markers are located within gene sequences in A. thaliana, and 100% of markers in Plasmodium falciparun. We further find that for a typical trait controlled by 50 genes of average size, if 1000 AFLPs are used in a study, the number of those within 1 kb distance from any of the genes would be only about 1-2, and only about 50% of the genes would have markers within that distance.ConclusionsThe high coverage of AFLP markers across the genomes and the high proportion of markers within or close to gene sequences make them suitable for genome scans and detecting large islands of differentiation in the genome. However, for specific traits, the percentage of AFLP markers close to genes can be rather small. Therefore, genome scans directed towards the search of markers closely linked to selected loci can be a difficult task in many instances.

Dataset Information

Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

Publications

Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

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