Ancient Human Parasites in Ethnic Chinese Populations

Whilst archaeological evidence for many aspects of life in ancient China is well studied, there has been much less interest in ancient infectious diseases, such as intestinal parasites in past Chinese populations. Here, we bring together evidence from mummies, ancient latrines, and pelvic soil from burials, dating from the Neolithic Period to the Qing Dynasty, in order to better understand the health of the past inhabitants of China and the diseases endemic in the region. Seven species of intestinal parasite have been identified, namely roundworm, whipworm, Chinese liver fluke, oriental schistosome, pinworm, Taenia sp. tapeworm, and the intestinal fluke Fasciolopsis buski. It was found that in the past, roundworm, whipworm, and Chinese liver fluke appear to have been much more common than the other species. While roundworm and whipworm remained common into the late 20th century, Chinese liver fluke seems to have undergone a marked decline in its prevalence over time. The iconic transport route known as the Silk Road has been shown to have acted as a vector for the transmission of ancient diseases, highlighted by the discovery of Chinese liver fluke in a 2,000 year-old relay station in northwest China, 1,500 km outside its endemic range

Additional file 1: Table S1. of A novel somatic mutation in ACD induces telomere lengthening and apoptosis resistance in leukemia cells

Description of data: Non-synonymous and frame-shift mutations in ACD referenced in the public cancer database COSMIC version 71. (PDF 120 kb

Specific expression of novel long non-coding RNAs in high-hyperdiploid childhood acute lymphoblastic leukemia

<div><p>Pre-B cell childhood acute lymphoblastic leukemia (pre-B cALL) is a heterogeneous disease involving many subtypes typically stratified using a combination of cytogenetic and molecular-based assays. These methods, although widely used, rely on the presence of known chromosomal translocations, which is a limiting factor. There is therefore a need for robust, sensitive, and specific molecular biomarkers unaffected by such limitations that would allow better risk stratification and consequently better clinical outcome. In this study we performed a transcriptome analysis of 56 pre-B cALL patients to identify expression signatures in different subtypes. In both protein-coding and long non-coding RNAs (lncRNA), we identified subtype-specific gene signatures distinguishing pre-B cALL subtypes, particularly in t(12;21) and hyperdiploid cases. The genes up-regulated in pre-B cALL subtypes were enriched in bivalent chromatin marks in their promoters. LncRNAs is a new and under-studied class of transcripts. The subtype-specific nature of lncRNAs suggests they may be suitable clinical biomarkers to guide risk stratification and targeted therapies in pre-B cALL patients.</p></div

Overall accuracy of 3-nearest-neighbors classification using an increasing number of top variance genes from different biotypes.

<p>(A) Multidimensional scaling plot of distances between expression profiles only for lncRNAs. The distance between each pair of samples is the Euclidean distance between expression values (logCPM) of the 500 lncRNAs with the most variance across all samples. (B) K-nearest neighbors classification accuracy comparison between lncRNA and protein-coding transcripts. The y-axis corresponds to the fraction of samples correctly classified, averaged over 100 replicates. For each replicate, we sampled 50% of available genes and ordered them according to expression variance across samples. 3-nearest-neighbors classification was then performed using an incremental number of genes and Euclidean distance between samples. The baseline accuracy corresponds to random assignment of tumor subtypes within the cohort.</p

ENCODE TF peak enrichment near TSS of dysregulated genes.

<p>The y-axis corresponds to the minimal TF expression change observed among all subtypes. The x-axis corresponds to the peak enrichment ratio for genes that are up- or down-regulated in all subtypes. All TFs are represented as dots and text labels have been added when both expression change and (positive) peak enrichment are statistically significant (FDR < 0.1).</p

Cohort characteristics.

<p>Cohort characteristics.</p

Expression distribution for core and accessory PRC2 subunits in our pre-B cALL cohort.

<p>Gene expression box plots for (A) core and (B) accessory PCR2 subunits. Thick boxes comprise observations from the first to the third quartiles in each group. Observations farther than 1.5*IQR (inter-quartile range) from these boxes boundaries are represented as dots. Genes identified as dysregulated by the edgeR analysis (FDR<1e-3) are marked with an asterisk and associated FDR values specified underneath.</p

Effect of frequently gained chromosomes on inter-sample distances and KNN classification accuracy.

<p>(A) MDS plot obtained with the 500 top variance genes including all autosomes. (B) MDS plot obtained with the 500 top variance genes that are not located on chromosomes frequently gained in HeH (chr 4,6,10,14,17,18 and 21). (C) Effect on classification accuracy. The y-axis corresponds to the fraction of HeH samples correctly classified, averaged over 100 replicates. For each replicate, we sampled 50% of available genes and ordered them according to expression variance across samples. 3-nearest-neighbors classification was then performed using an incremental number of genes and Euclidean distance between samples. The baseline accuracy corresponds to random assignment of tumor subtypes within the cohort.</p

Comparison of differentially expressed genes in our RNA-seq and public dataset.

<p>(A) Overlap between differentially expressed genes identified from microarray data (Lee et al.) and RNA-seq for the HeH versus t(12;21) comparison. The intersection of 200 genes represents a 10-fold enrichment compared to the expected intersection (20) when DEGs are picked randomly. (B) Comparison of logFCs for DEGs identified in both the microarray and RNA-seq analysis. Pearson’s product-moment correlation between log2FCs = 0.844. Spearman’s rank correlation = 0.793. We note that expression changes are coherent (in the same direction) for all DEGs identified from both datasets</p

Histone mark distribution with respect to dysregulation status in pre-B cALL.

<p>(A) Relative peak coverage of H3K27me3 repressive mark. (B) Relative peak coverage of H3K4me3 activating mark. (C) Relative peak coverage of the H3K36me3 mark associated to active transcription. (D) Fraction of genes with H3K27me3 or both H3K27me3 and H3K4me3 (bivalency) near their TSS (-5kb to +5kb). Genes with an FDR<0.001 and a log2FC > 2 (or < -2) in all subtypes have been classified as up-regulated (or down-regulated). Genes not differentially expressed (not DE) include all genes with FDR>0.5. Only the most upstream TSS of each gene was considered. Histone peak data was obtained from ENCODE epigenome E031 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0174124#pone.0174124.ref055" target="_blank">55</a>].</p