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Sökning: WFRF:(Yiu Lin Yu Nancy)

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1.
  • Einarsdottir, Elisabet, et al. (författare)
  • Identification of NCAN as a candidate gene for developmental dyslexia.
  • 2017
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7:1
  • Tidskriftsartikel (refereegranskat)abstract
    • A whole-genome linkage analysis in a Finnish pedigree of eight cases with developmental dyslexia (DD) revealed several regions shared by the affected individuals. Analysis of coding variants from two affected individuals identified rs146011974G > A (Ala1039Thr), a rare variant within the NCAN gene co-segregating with DD in the pedigree. This variant prompted us to consider this gene as a putative candidate for DD. The RNA expression pattern of the NCAN gene in human tissues was highly correlated (R > 0.8) with that of the previously suggested DD susceptibility genes KIAA0319, CTNND2, CNTNAP2 and GRIN2B. We investigated the association of common variation in NCAN to brain structures in two data sets: young adults (Brainchild study, Sweden) and infants (FinnBrain study, Finland). In young adults, we found associations between a common genetic variant in NCAN, rs1064395, and white matter volume in the left and right temporoparietal as well as the left inferior frontal brain regions. In infants, this same variant was found to be associated with cingulate and prefrontal grey matter volumes. Our results suggest NCAN as a new candidate gene for DD and indicate that NCAN variants affect brain structure.
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2.
  • Yu, Nancy Yiu-Lin, et al. (författare)
  • Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium
  • 2015
  • Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 43:14, s. 6787-6798
  • Tidskriftsartikel (refereegranskat)abstract
    • Understanding the normal state of human tissue transcriptome profiles is essential for recognizing tissue disease states and identifying disease markers. Recently, the Human Protein Atlas and the FANTOM5 consortium have each published extensive transcriptome data for human samples using Illumina-sequenced RNA-Seq and Heliscope-sequenced CAGE. Here, we report on the first large-scale complex tissue transcriptome comparison between full-length versus 5'-capped mRNA sequencing data. Overall gene expression correlation was high between the 22 corresponding tissues analyzed (R > 0.8). For genes ubiquitously expressed across all tissues, the two data sets showed high genome-wide correlation (91% agreement), with differences observed for a small number of individual genes indicating the need to update their gene models. Among the identified single-tissue enriched genes, up to 75% showed consensus of 7-fold enrichment in the same tissue in both methods, while another 17% exhibited multiple tissue enrichment and/or high expression variety in the other data set, likely dependent on the cell type proportions included in each tissue sample. Our results show that RNA-Seq and CAGE tissue transcriptome data sets are highly complementary for improving gene model annotations and highlight biological complexities within tissue transcriptomes. Furthermore, integration with image-based protein expression data is highly advantageous for understanding expression specificities for many genes.
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