Integration of multiple epigenomic marks improves prediction of variant impact in saturation mutagenesis reporter assay

The integrative analysis of highâ throughput reporter assays, machine learning, and profiles of epigenomic chromatin state in a broad array of cells and tissues has the potential to significantly improve our understanding of noncoding regulatory element function and its contribution to human disease. Here, we report results from the CAGI 5 regulation saturation challenge where participants were asked to predict the impact of nucleotide substitution at every base pair within five diseaseâ associated human enhancers and nine diseaseâ associated promoters. A library of mutations covering all bases was generated by saturation mutagenesis and altered activity was assessed in a massively parallel reporter assay (MPRA) in relevant cell lines. Reporter expression was measured relative to plasmid DNA to determine the impact of variants. The challenge was to predict the functional effects of variants on reporter expression. Comparative analysis of the full range of submitted prediction results identifies the most successful models of transcription factor binding sites, machine learning algorithms, and ways to choose among or incorporate diverse datatypes and cellâ types for training computational models. These results have the potential to improve the design of future studies on more diverse sets of regulatory elements and aid the interpretation of diseaseâ associated genetic variation.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151884/1/humu23797_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151884/2/humu23797.pd

Quantitative Analysis of Differential Expression of HOX Genes in Multiple Cancers

Transcription factors encoded by Homeobox (HOX) genes play numerous key functions during early embryonic development and differentiation. Multiple reports have shown that mis-regulation of HOX gene expression plays key roles in the development of cancers. Their expression levels in cancers tend to differ based on tissue and tumor type. Here, we performed a comprehensive analysis comparing HOX gene expression in different cancer types, obtained from The Cancer Genome Atlas (TCGA), with matched healthy tissues, obtained from Genotype-Tissue Expression (GTEx). We identified and quantified differential expression patterns that confirmed previously identified expression changes and highlighted new differential expression signatures. We discovered differential expression patterns that are in line with patient survival data. This comprehensive and quantitative analysis provides a global picture of HOX genes’ differential expression patterns in different cancer types

TREM2 has a significant, gender-specific, effect on human obesity

Abstract Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) is a membrane protein expressed on immune cells, involved in neurodegenerative diseases and cancer. Recently, it was shown that TREM2 is expressed on lipid associated macrophages in adipose tissue, and that TREM2 knockout mice suffer from metabolic symptoms. Here, a computational study using public databases, brings direct evidence for the involvement of TREM2 in human obesity. First, we show a significant correlation between TREM2 expression levels and BMI in adipose tissues in samples from the GTEx database. This association was evident for males but not for females. Second, we identified in the UK Biobank cohort a coding SNP in TREM2 with a significant effect on BMI. Compared to previously identified SNPs associated with BMI, this SNP (rs2234256 SNP, L211P) has the strongest association, reflected in significantly higher BMI values of people carrying the SNP as heterozygous and even more for homozygous. Strikingly, this association was evident only for females. These observations suggest a novel gender-specific role of TREM2 in human obesity, and call for further studies to elucidate the mechanism by which this gene correlates with an obese phenotype

Comparative genomic analysis of mollicutes with and without a chaperonin system

<div><p>The GroE chaperonin system, which comprises GroEL and GroES, assists protein folding <i>in vivo</i> and <i>in vitro</i>. It is conserved in all prokaryotes except in most, but not all, members of the class of mollicutes. In <i>Escherichia coli</i>, about 60 proteins were found to be obligatory clients of the GroE system. Here, we describe the properties of the homologs of these GroE clients in mollicutes and the evolution of chaperonins in this class of bacteria. Comparing the properties of these homologs in mollicutes with and without chaperonins enabled us to search for features correlated with the presence of GroE. Interestingly, no sequence-based features of proteins such as average length, amino acid composition and predicted folding/disorder propensity were found to be affected by the absence of GroE. Other properties such as genome size and number of proteins were also found to not differ between mollicute species with and without GroE. Our data suggest that two clades of mollicutes re-acquired the GroE system, thereby supporting the view that gaining the system occurred polyphyletically and not monophyletically, as previously debated. Our data also suggest that there might have been three isolated cases of lateral gene transfer from specific bacterial sources. Taken together, our data indicate that loss of GroE does not involve crossing a high evolutionary barrier and can be compensated for by a small number of changes within the few dozen client proteins.</p></div

Detecting Horizontal Gene Transfer between Closely Related Taxa - Fig 2

<p><b>Top:</b> The phylogeny over a group of organisms with branch lengths proportional to distances of gene <i>g</i>_<i>h</i>. <i>g</i>_<i>h</i> has undergone HGT between the two strains <i>S</i>₁ and <i>S</i>₂ and hence their distance is very short compared with two reference organisms <i>R</i>₁ and <i>R</i>₇. <b>Bottom:</b> The reference gene (blue, dashed line) must be a gene that accumulates mutations ever since the divergence of both the strains and reference organisms. There are two cases in which the suspicious gene evolves at the reference organism. (<i>A</i>) No HGT and then the constant relative conserveness is maintained (black dashed). (<i>B</i>) HGT of the SI suspicious gene at the reference organisms and the constant relative conservation is not maintained (yellow dashed).</p

Comparing properties of GroE⁺ and GroE^- homologs.

<p>Comparing properties of GroE⁺ and GroE^- homologs.</p

Comparing <i>G</i>₁ with <i>G</i>₂ for <i>k</i> = 3: <i>SI</i>(<i>g</i>, <i>G</i>₁, <i>G</i>₂) = 3, <i>SI</i>(<i>x</i>, <i>G</i>₁, <i>G</i>₂) = 0, <i>SI</i>(ℓ, <i>G</i>₁, <i>G</i>₂) = 0.

<p>Comparing <i>G</i>₁ with <i>G</i>₂ for <i>k</i> = 3: <i>SI</i>(<i>g</i>, <i>G</i>₁, <i>G</i>₂) = 3, <i>SI</i>(<i>x</i>, <i>G</i>₁, <i>G</i>₂) = 0, <i>SI</i>(ℓ, <i>G</i>₁, <i>G</i>₂) = 0.</p

Distribution of the GroE system in a 16S rRNA-based evolution tree of mollicutes.

<p>The branches of the GroE⁺ and GroE^- species are marked in red and blue, respectively. The numbers on the branching points represent the bootstrapping frequencies, the branch length represents the sequence distance and the scale shows a distance of 5%. The diamonds and squares show the two major clades that contain the GroE system. The triangle marks the species where lateral gene transfer (LGT) was suggested before and circles mark the two additional species for which we suggest LGT events.</p