Xijin Ge1, Qingfa Wu, Yong-Chul Jung, Jun Chen, San Ming Wang. 1. Center for Functional Genomics, Division of Medical Genetics, Department of Medicine, ENH Research Institute, Northwestern University Feinberg School of Medicine 1001 University Place, Evanston, IL 60201 USA.
Abstract
MOTIVATION: Taking advantage of the high sensitivity and specificity of LongSAGE tag for transcript detection and genome mapping, we analyzed the 632 813 unique human LongSAGE tags deposited in public databases to identify novel human antisense transcripts. RESULTS: Our study identified 45 321 tags that match the antisense strand of 9804 known mRNA sequences, 6606 of which contain antisense ESTs and 3198 are mapped only by SAGE tags. Quantitative analysis showed that the detected antisense transcripts are present at levels lower than their counterpart sense transcripts. Experimental results confirmed the presence of antisense transcripts detected by the antisense tags. We also constructed an antisense tag database that can be used to identify the antisense SAGE tags originated from the antisense strand of known mRNA sequences included in the RefSeq database. CONCLUSIONS: Our study highlights the benefits of exploring SAGE data for comprehensive identification of human antisense transcripts and demonstrates the prevalence of antisense transcripts in the human genome.
MOTIVATION: Taking advantage of the high sensitivity and specificity of LongSAGE tag for transcript detection and genome mapping, we analyzed the 632 813 unique human LongSAGE tags deposited in public databases to identify novel human antisense transcripts. RESULTS: Our study identified 45 321 tags that match the antisense strand of 9804 known mRNA sequences, 6606 of which contain antisense ESTs and 3198 are mapped only by SAGE tags. Quantitative analysis showed that the detected antisense transcripts are present at levels lower than their counterpart sense transcripts. Experimental results confirmed the presence of antisense transcripts detected by the antisense tags. We also constructed an antisense tag database that can be used to identify the antisense SAGE tags originated from the antisense strand of known mRNA sequences included in the RefSeq database. CONCLUSIONS: Our study highlights the benefits of exploring SAGE data for comprehensive identification of human antisense transcripts and demonstrates the prevalence of antisense transcripts in the human genome.
Authors: Yeong C Kim; Qingfa Wu; Jun Chen; Zhenyu Xuan; Yong-Chul Jung; Michael Q Zhang; Janet D Rowley; San Ming Wang Journal: Proc Natl Acad Sci U S A Date: 2009-04-30 Impact factor: 11.205
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