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Analysis of tag-position bias in MPSS technology

Overview of attention for article published in BMC Genomics, April 2006
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Title
Analysis of tag-position bias in MPSS technology
Published in
BMC Genomics, April 2006
DOI 10.1186/1471-2164-7-77
Pubmed ID
Authors

Junfeng Chen, Magnus Rattray

Abstract

Massively Parallel Signature Sequencing (MPSS) technology was recently developed as a high-throughput technology for measuring the concentration of mRNA transcripts in a sample. It has previously been observed that the position of the signature tag in a transcript (distance from 3' end) can affect the measurement, but this effect has not been studied in detail. We quantify the effect of tag-position bias in Classic and Signature MPSS technology using published data from Arabidopsis, rice and human. We investigate the relationship between measured concentration and tag-position using nonlinear regression methods. The observed relationship is shown to be broadly consistent across different data sets. We find that there exist different and significant biases in both Classic and Signature MPSS data. For Classic MPSS data, genes with tag-position in the middle-range have highest measured abundance on average while genes with tag-position in the high-range, far from the 3' end, show a significant decrease. For Signature MPSS data, high-range tag-position genes tend to have a flatter relationship between tag-position and measured abundance. Thus, our results confirm that the Signature MPSS method fixes a substantial problem with the Classic MPSS method. For both Classic and Signature MPSS data there is a positive correlation between measured abundance and tag-position for low-range tag-position genes. Compared with the effects of mRNA length and number of exons, tag-position bias seems to be more significant in Arabadopsis. The tag-position bias is reflected both in the measured abundance of genes with a significant tag count and in the proportion of unexpressed genes identified. Tag-position bias should be taken into consideration when measuring mRNA transcript abundance using MPSS technology, both in Classic and Signature MPSS methods.

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Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 20%
Unknown 12 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 47%
Professor 3 20%
Student > Doctoral Student 3 20%
Professor > Associate Professor 1 7%
Unknown 1 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 67%
Biochemistry, Genetics and Molecular Biology 2 13%
Computer Science 1 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Unknown 1 7%