AMPKα modulation in cancer progression: multilayer integrative analysis of the whole transcriptome in Asian gastric cancer.

Gastric cancer is the most common cancer in Asia and most developing countries. Despite the use of multimodality therapeutics, it remains the second leading cause of cancer death in the world. To identify the molecular underpinnings of gastric cancer in the Asian population, we applied an RNA-sequencing approach to gastric tumor and noncancerous specimens, generating 680 million informative short reads to quantitatively characterize the entire transcriptome of gastric cancer (including mRNAs and miRNAs). A multilayer analysis was then developed to identify multiple types of transcriptional aberrations associated with different stages of gastric cancer, including differentially expressed mRNAs, recurrent somatic mutations, and key differentially expressed miRNAs. Through this approach, we identified the central metabolic regulator AMP-activated protein kinase (AMPK)α as a potential functional target in Asian gastric cancer. Furthermore, we experimentally showed the translational relevance of this gene as a potential therapeutic target for early-stage gastric cancer in Asian patients. Together, our findings not only provide a valuable information resource for identifying and elucidating the molecular mechanisms of Asian gastric cancer, but also represent a general integrative framework to develop more effective therapeutic targets.

Consanguinity in Centre d'Étude du Polymorphisme Humain (CEPH) pedigrees.

A set of Centre d'Étude du Polymorphisme Humain (CEPH) cell lines serves as a large reference collection that has been widely used as a benchmark for allele frequencies in the analysis of genetic variants, to create linkage maps of the human genome, to study the genetics of gene expression, to provide samples to the HapMap and 1000 Genomes projects, and for a variety of other applications. An explicit feature of the CEPH collection is that these multigenerational families represent reference panels of known relatedness, consisting mostly of three-generation pedigrees with large sibships, two parents, and grandparents. We applied identity-by-state (IBS) and identity-by-descent (IBD) methods to high-density genotype data from 186 CEPH individuals in 13 families. We identified unexpected relatedness between nominally unrelated grandparents both within and between pedigrees. For one pair, the estimated Cotterman coefficient of relatedness k1 exceeded 0.2, consistent with one-eighth sharing (eg, first-cousins). Unexpectedly, significant IBD2 values were discovered in both second-degree and parent-child relationships. These were accompanied by regions of homozygosity in the offspring, which corresponded to blocks lacking IBS0 in purportedly unrelated parents, consistent with inbreeding. Our findings support and extend a 1999 report, based on the use of short tandem-repeat polymorphisms, that several CEPH families had regions of homozygosity consistent with autozygosity. We benchmarked our IBD approach (called kcoeff) against both RELPAIR and PREST software packages. Our findings may affect the interpretation of previous studies and the design of future studies that rely on the CEPH resource.

Inference of relationships in population data using identity-by-descent and identity-by-state.

It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data.

Primary and secondary transcriptional effects in the developing human Down syndrome brain and heart.

BACKGROUND: Down syndrome, caused by trisomic chromosome 21, is the leading genetic cause of mental retardation. Recent studies demonstrated that dosage-dependent increases in chromosome 21 gene expression occur in trisomy 21. However, it is unclear whether the entire transcriptome is disrupted, or whether there is a more restricted increase in the expression of those genes assigned to chromosome 21. Also, the statistical significance of differentially expressed genes in human Down syndrome tissues has not been reported. RESULTS: We measured levels of transcripts in human fetal cerebellum and heart tissues using DNA microarrays and demonstrated a dosage-dependent increase in transcription across different tissue/cell types as a result of trisomy 21. Moreover, by having a larger sample size, combining the data from four different tissue and cell types, and using an ANOVA approach, we identified individual genes with significantly altered expression in trisomy 21, some of which showed this dysregulation in a tissue-specific manner. We validated our microarray data by over 5,600 quantitative real-time PCRs on 28 genes assigned to chromosome 21 and other chromosomes. Gene expression values from chromosome 21, but not from other chromosomes, accurately classified trisomy 21 from euploid samples. Our data also indicated functional groups that might be perturbed in trisomy 21. CONCLUSIONS: In Down syndrome, there is a primary transcriptional effect of disruption of chromosome 21 gene expression, without a pervasive secondary effect on the remaining transcriptome. The identification of dysregulated genes and pathways suggests molecular changes that may underlie the Down syndrome phenotypes.

Evaluation of gene expression measurements from commercial microarray platforms.

Multiple commercial microarrays for measuring genome-wide gene expression levels are currently available, including oligonucleotide and cDNA, single- and two-channel formats. This study reports on the results of gene expression measurements generated from identical RNA preparations that were obtained using three commercially available microarray platforms. RNA was collected from PANC-1 cells grown in serum-rich medium and at 24 h following the removal of serum. Three biological replicates were prepared for each condition, and three experimental replicates were produced for the first biological replicate. RNA was labeled and hybridized to microarrays from three major suppliers according to manufacturers' protocols, and gene expression measurements were obtained using each platform's standard software. For each platform, gene targets from a subset of 2009 common genes were compared. Correlations in gene expression levels and comparisons for significant gene expression changes in this subset were calculated, and showed considerable divergence across the different platforms, suggesting the need for establishing industrial manufacturing standards, and further independent and thorough validation of the technology.