Yankai Jia | bioRxiv Science

bioRxiv2016

A framework for RNA quality correction in differential expression analysis

RNA sequencing (RNA-seq) is a powerful approach for measuring gene expression levels in cells and tissues, but it relies on high-quality RNA. We demonstrate here that statistical adjustment employing existing quality measures largely fails to remove the effects of RNA degradation when RNA quality associates with the outcome of interest. Using RNA-seq data from a molecular degradation experiment of human brain tissue, we introduce the quality surrogate variable (qSVA) analysis framework for estimating and removing the confounding effect of RNA quality in differential expression analysis. We show this approach results in greatly improved replication rates (>3x) across two large independent postmortem human brain studies of schizophrenia. Finally, we explored public datasets to demonstrate potential RNA quality confounding when comparing expression levels of different brain regions and diagnostic groups beyond schizophrenia. Our approach can therefore improve the interpretation of differential expression analysis of transcriptomic data from the human brain.

Bioinformatics↗

bioRxiv2015

Strong Components of Epigenetic Memory in Cultured Human Fibroblasts Related to Site of Origin and Donor Age

Differentiating pluripotent cells from fibroblast progenitors is a potentially transformative tool in personalized medicine. We previously identified relatively greater success culturing dura-derived fibroblasts than scalp-derived fibroblasts from postmortem tissue. We hypothesized that these differences in culture success were related to epigenetic differences between the cultured fibroblasts by sampling location, and therefore generated genome-wide DNA methylation and transcriptome data on 11 intrinsically matched pairs of dural and scalp fibroblasts from donors across the lifespan (infant to 85 years). While these cultured fibroblasts were several generations removed from the primary tissue and morphologically indistinguishable, we found widespread epigenetic differences by sampling location at the single CpG (N=101,989), region (N=697), \"block\" (N=243), and global spatial scales suggesting a strong epigenetic memory of original fibroblast location. Furthermore, many of these epigenetic differences manifested in the transcriptome, particularly at the region-level. We further identified 7,265 CpGs and 11 regions showing significant epigenetic memory related to the age of the donor, as well as an overall increased epigenetic variability, preferentially in scalp-derived fibroblasts -83% of loci were more variable in scalp, hypothesized to result from cumulative exposure to environmental stimuli in the primary tissue. By integrating publicly available DNA methylation datasets on individual cell populations in blood and brain, we identified significantly increased inter-individual variability in our scalp- and other skin-derived fibroblasts on a similar scale as epigenetic differences between different lineages of blood cells. Lastly, these epigenetic differences did not appear to be driven by somatic mutation - while we identified 64 probable de-novo variants across the 11 subjects, there was no association between mutation burden and age of the donor (p=0.71). These results depict a strong component of epigenetic memory in cell culture from primary tissue, even after several generations of daughter cells, related to cell state and donor age.

Cell Biology↗