Transcriptome characterization elucidates signaling networks that control human ES cell growth and differentiation.

Human embryonic stem (hES) cells hold promise for generating an unlimited supply of cells for replacement therapies. To characterize hES cells at the molecular level, we obtained 148,453 expressed sequence tags (ESTs) from undifferentiated hES cells and three differentiated derivative subpopulations. Over 32,000 different transcripts expressed in hES cells were identified, of which more than 16,000 do not match closely any gene in the UniGene public database. Queries to this EST database revealed 532 significantly upregulated and 140 significantly downregulated genes in undifferentiated hES cells. These data highlight changes in the transcriptional network that occur when hES cells differentiate. Among the differentially regulated genes are several components of signaling pathways and transcriptional regulators that likely play key roles in hES cell growth and differentiation. The genomic data presented here may facilitate the derivation of clinically useful cell types from hES cells.

Real-time quantification of microRNAs by stem-loop RT-PCR.

A novel microRNA (miRNA) quantification method has been developed using stem-loop RT followed by TaqMan PCR analysis. Stem-loop RT primers are better than conventional ones in terms of RT efficiency and specificity. TaqMan miRNA assays are specific for mature miRNAs and discriminate among related miRNAs that differ by as little as one nucleotide. Furthermore, they are not affected by genomic DNA contamination. Precise quantification is achieved routinely with as little as 25 pg of total RNA for most miRNAs. In fact, the high sensitivity, specificity and precision of this method allows for direct analysis of a single cell without nucleic acid purification. Like standard TaqMan gene expression assays, TaqMan miRNA assays exhibit a dynamic range of seven orders of magnitude. Quantification of five miRNAs in seven mouse tissues showed variation from less than 10 to more than 30,000 copies per cell. This method enables fast, accurate and sensitive miRNA expression profiling and can identify and monitor potential biomarkers specific to tissues or diseases. Stem-loop RT-PCR can be used for the quantification of other small RNA molecules such as short interfering RNAs (siRNAs). Furthermore, the concept of stem-loop RT primer design could be applied in small RNA cloning and multiplex assays for better specificity and efficiency.

Analytical Validation of Relative Average Telomere Length Measurement in a Clinical Laboratory Environment.

BACKGROUND: Average telomere length in whole blood has become a biomarker of aging, disease, and mortality risk across a broad range of clinical conditions. The most common method of telomere length measurement for large patient sample sets is based on quantitative PCR (qPCR). For laboratory-developed tests to be performed on clinical samples, they must undergo a rigorous analytical validation, currently regulated under CLIA. METHODS: Whole blood samples from 40 donors were used in the analytical validation of methods for relative average telomere length (rATL) measurement. Three technical replicate DNA samples were extracted from each whole blood sample and placed in three independent wells on a sample plate. Each of these sample plates was assayed 12 times during the validation process. The study was conducted over a 20-day period, once in the morning and once in the evening, using 3 different operators. RESULTS: Our process of rATL measurement beginning with DNA extraction followed by qPCR-based assay resulted in repeatability and reproducibility CV of <5% and amplification efficiencies near 100%. The validated assay was used to establish a reference interval derived from 2 cohorts of individuals: (a) San Francisco Bay area (n = 504) and (b) a US cross-sectional, demographic population (n = 357). CONCLUSIONS: We present advances in the establishment of a highly reproducible analytically validated process for determining rATLs in a CLIA laboratory environment.

Polymorphisms and haplotypes in the cytochrome P450 17A1, prolactin, and catechol-O-methyltransferase genes and non-Hodgkin lymphoma risk.

Expression of prolactin and of prolactin and estrogen receptors in lymphocytes, bone marrow, and lymphoma cell lines suggests that hormonal modulation may influence lymphoma risk. Prolactin and estrogen promote the proliferation and survival of B cells, factors that may increase non-Hodgkin lymphoma risk, and effects of estrogen may be modified by catechol-O-methyltransferase (COMT), an enzyme that alters estrogenic activity. Cytochrome P450 17A1 (CYP17A1), a key enzyme in estrogen biosynthesis, has been associated with increased cancer risk and may affect lymphoma susceptibility. We studied the polymorphisms prolactin (PRL) -1149G>T, CYP17A1 -34T>C, and COMT 108/158Val>Met, and predicted haplotypes among a subset of participants (n = 308 cases, n = 684 controls) in a San Francisco Bay Area population-based non-Hodgkin lymphoma study (n = 1,593 cases, n = 2,515 controls) conducted from 1988 to 1995. Oral contraceptive and other hormone use also was analyzed. Odds ratios (OR) for non-Hodgkin lymphoma and follicular lymphoma were reduced for carriers of the PRL -1149TT genotype [OR, 0.64; 95% confidence interval (95% CI), 0.41-1.0; OR, 0.53; 95% CI, 0.26-1.0, respectively]. Diffuse large-cell lymphoma risk was increased for those with CYP17A1 polymorphisms including CYP17A1 -34CC (OR, 2.0; 95% CI, 1.1-3.5). ORs for all non-Hodgkin lymphoma and follicular lymphoma among women were decreased for COMT IVS1 701A>G [rs737865; variant allele: OR, 0.53; 95% CI, 0.34-0.82; OR, 0.42; 95% CI, 0.23-0.78, respectively]. Compared with never users of oral contraceptives, a 35% reduced risk was observed among oral contraceptive users in the total population. Reduced ORs for all non-Hodgkin lymphoma were observed with use of exogenous estrogens among genotyped women although 95% CIs included unity. These results suggest that PRL, CYP17A1, and COMT may be relevant genetic loci for non-Hodgkin lymphoma and indicate a possible role for prolactin and estrogen in lymphoma pathogenesis.

An efficient and high-throughput approach for experimental validation of novel human gene predictions.

A highly automated RT-PCR-based approach has been established to validate novel human gene predictions with no prior experimental evidence of mRNA splicing (ab initio predictions). Ab initio gene predictions were selected for high-throughput validation using predicted protein classification, sequence similarity to other genomes, colocalization with an MPSS tag, or microarray expression. Initial microarray prioritization followed by RT-PCR validation was the most efficient combination, resulting in approximately 35% of the ab initio predictions being validated by RT-PCR. Of the 7252 novel genes that were prioritized and processed, 796 constituted real transcripts. In addition, high-throughput RACE successfully extended the 5' and/or 3' ends of >60% of RT-PCR-validated genes. Reevaluation of these transcripts produced 574 novel transcripts using RefSeq as a reference. RT-PCR sequencing in combination with RACE on ab initio gene predictions could be used to define the transcriptome across all species.

Recreational music-making modulates the human stress response: a preliminary individualized gene expression strategy.

BACKGROUND: A central component of the complex human biological stress response is the modulation of the neuro-endocrine-immune system with its intricate feedback loops that support homeostatic regulation. Well-documented marked gene expression variability among human and animal subjects coupled with sample collection timing and delayed effects, as well as a host of molecular detection challenges renders the quest for deciphering the human biological stress response challenging from many perspectives. MATERIAL/METHODS: A novel Recreational Music-Making (RMM) program was used in combination with a new strategy for peripheral blood gene expression analysis to assess individualized genomic stress induction signatures. The expression of 45 immune response-related genes was determined using a multiplex preamplification step prior to conventional quantitative Real Time Polymerase Chain Reaction (qRT-PCR) mRNA analysis to characterize the multidimensional biological impact of a 2-phase controlled stress induction/amelioration experimental protocol in 32 randomly assigned individuals. RESULTS: In subjects performing the RMM activity following a 1-hour stress induction protocol, 19 out of 45 markers demonstrated reversal with significant (P = 0.05) Pearson correlations in contrast to 6 out of 45 markers in the resting control group and 0 out of 45 in the ongoing stressor group. CONCLUSIONS: The resultant amelioration of stress-induced genomic expression supports the underlying premise that RMM warrants additional consideration as a rational choice within our armamentarium of stress reduction strategies. Modulation of individualized genomic stress induction signatures in peripheral blood presents a new opportunity for elucidating the dynamics of the human stress response.

The linkage disequilibrium maps of three human chromosomes across four populations reflect their demographic history and a common underlying recombination pattern.

The extent and patterns of linkage disequilibrium (LD) determine the feasibility of association studies to map genes that underlie complex traits. Here we present a comparison of the patterns of LD across four major human populations (African-American, Caucasian, Chinese, and Japanese) with a high-resolution single-nucleotide polymorphism (SNP) map covering almost the entire length of chromosomes 6, 21, and 22. We constructed metric LD maps formulated such that the units measure the extent of useful LD for association mapping. LD reaches almost twice as far in chromosome 6 as in chromosomes 21 or 22, in agreement with their differences in recombination rates. By all measures used, out-of-Africa populations showed over a third more LD than African-Americans, highlighting the role of the population's demography in shaping the patterns of LD. Despite those differences, the long-range contour of the LD maps is remarkably similar across the four populations, presumably reflecting common localization of recombination hot spots. Our results have practical implications for the rational design and selection of SNPs for disease association studies.