Identifying Robertsonian Translocation Carriers by Microarray-Based DNA Analysis.

OBJECTIVE: To develop a noninvasive prenatal testing improvement that allows identification of Robertsonian translocation carriers. METHODS: Blood samples from 191 subjects, including 7 pregnant and 9 non-pregnant Robertsonian translocation carriers, were analyzed for fetal trisomy and Robertsonian translocation status. Digital Analysis of Selected Regions (DANSR™) assays targeting sequences common to the p arms of 5 acrocentric chromosomes were developed and added to existing DANSR assays. DANSR products were hybridized onto a custom DNA microarray for DNA analysis. The Fetal-Fraction Optimized Risk of Trisomy Evaluation (FORTE™) algorithm measures the fraction of fetal DNA and accounts for both the fetal and maternal fractions in the cell-free DNA sample to determine Robertsonian risk. The expectation in a Robertsonian translocation carrier is that DANSR assays on acrocentric p arms should have a concentration 20% less than that of controls. RESULTS: The FORTE algorithm correctly classified the fetal trisomy status and maternal Robertsonian translocation status in all 191 samples. Sixteen samples had a Robertsonian risk score above 99%, while 175 samples had a Robertsonian risk score below 0.01%. CONCLUSIONS: Robertsonian translocations are the most common chromosomal translocations and can have significant reproductive consequences. A maternal screen for Robertsonian translocation carriers would provide women valuable information regarding the risk of fetal trisomy.

Scan statistics analysis for detection of introns in time-course tiling array data.

A tiling array yields a series of abundance measurements across the genome using evenly spaced probes. These data can be used for detecting sequences that exhibit a particular behavior. Scanning window statistics are often employed for testing each probe while accounting for local correlation and smoothing noisy measurements. However, window testing may yield false probe discoveries around the sequences and false non-discoveries within the sequences, resulting in biased predicted intervals. We propose to avoid this problem by stipulating that a sequence of interest can appear at most once within a defined region, such as a gene; thus, only one window statistic is considered per region. This substantially reduces the number of tests and hence, is potentially more powerful. We compare this approach to a genome-wise scan that does not require pre-defined search regions, but considers clumps of adjacent probe discoveries. Simulations show that the gene-wise search maintains the nominal FDR level, while the genome-wise scan yields FDR that exceeds the nominal level for low interval effects, and achieves slightly less power. Using arrays to map introns in yeast, we identified 71% of the previously published introns, detected nine previously undiscovered introns, and observed no false intron discoveries by either method.

Microarray-based cell-free DNA analysis improves noninvasive prenatal testing.

OBJECTIVE: To develop a microarray-based method for noninvasive prenatal testing (NIPT) and compare it with next-generation sequencing. METHODS: Maternal plasma from 878 pregnant women, including 187 trisomy cases (18 trisomy 13, 37 trisomy 18, 132 trisomy 21), was evaluated for trisomy risk. Targeted chromosomes were analyzed using Digital Analysis of Selected Regions (DANSR™) assays. DANSR products were subsequently divided between two DNA quantification methods: microarrays and next-generation sequencing. For both microarray and sequencing methodologies, the Fetal-Fraction Optimized Risk of Trisomy Evaluation (FORTE™) algorithm was used to determine trisomy risk, assay variability across samples, and compute fetal fraction variability within samples. RESULTS: NIPT using microarrays provided faster and more accurate cell-free DNA (cfDNA) measurements than sequencing. The assay variability, a measure of variance of chromosomal cfDNA counts, was lower for microarrays than for sequencing, 0.051 versus 0.099 (p < 0.0001). Analysis time using microarrays was faster, 7.5 versus 56 h for sequencing. Additionally, fetal fraction precision was improved 1.6-fold by assaying more polymorphic sites with microarrays (p < 0.0001). Microarrays correctly classified all trisomy and nontrisomy cases. CONCLUSIONS: NIPT using microarrays delivers more accurate cfDNA analysis than next-generation sequencing and can be performed in less time.

A molecular inversion probe assay for detecting alternative splicing.

BACKGROUND: A sensitive, high-throughput method for monitoring pre-mRNA splicing on a genomic scale is needed to understand the spectrum of alternatively spliced mRNA in human cells. RESULTS: We adapted Molecular Inversion Probes (MIPs), a padlock-probe based technology, for the multiplexed capture and quantitation of individual splice events in human tissues. Individual MIP capture probes can be quantified using either DNA microarrays or high-throughput sequencing, which permits independent assessment of each spliced junction. Using our methodology we successfully identified 100% of our positive controls and showed that there is a strong correlation between the data from our alternative splicing MIP (asMIP) assay and quantitative PCR. CONCLUSION: The asMIP assay provides a sensitive, accurate and multiplexed means for measuring pre-mRNA splicing. Fully optimized, we estimate that the assay could accommodate a throughput of greater than 20,000 splice junctions in a single reaction. This would represent a significant improvement over existing technologies.

Introns regulate RNA and protein abundance in yeast.

The purpose of introns in the architecturally simple genome of Saccharomyces cerevisiae is not well understood. To assay the functional relevance of introns, a series of computational analyses and several detailed deletion studies were completed on the intronic genes of S. cerevisiae. Mining existing data from genomewide studies on yeast revealed that intron-containing genes produce more RNA and more protein and are more likely to be haplo-insufficient than nonintronic genes. These observations for all intronic genes held true for distinct subsets of genes including ribosomal, nonribosomal, duplicated, and nonduplicated. Corroborating the result of computational analyses, deletion of introns from three essential genes decreased cellular RNA levels and caused measurable growth defects. These data provide evidence that introns improve transcriptional and translational yield and are required for competitive growth of yeast.

Alternative splicing of PTC7 in Saccharomyces cerevisiae determines protein localization.

It is well established that higher eukaryotes use alternative splicing to increase proteome complexity. In contrast, Saccharomyces cerevisiae, a single-cell eukaryote, conducts predominantly regulated splicing through retention of nonfunctional introns. In this article we describe our discovery of a functional intron in the PTC7 (YHR076W) gene that can be alternatively spliced to create two mRNAs that code for distinct proteins. These two proteins localize to different cellular compartments and have distinct cellular roles. The protein translated from the spliced mRNA localizes to the mitochondria and its expression is carbon-source dependent. In comparison, the protein translated from the unspliced mRNA contains a transmembrane domain, localizes to the nuclear envelope, and mediates the toxic effects of Latrunculin A exposure. In conclusion, we identified a definitive example of functional alternative splicing in S. cerevisiae that confers a measurable fitness benefit.

High-density yeast-tiling array reveals previously undiscovered introns and extensive regulation of meiotic splicing.

Knowing gene structure is vital to understanding gene function, and accurate genome annotation is essential for understanding cellular function. To this end, we have developed a genome-wide assay for mapping introns in Saccharomyces cerevisiae. Using high-density tiling arrays, we compared wild-type yeast to a mutant deficient for intron degradation. Our method identified 76% of the known introns, confirmed 18 previously predicted introns, and revealed 9 formerly undiscovered introns. Furthermore, we discovered that all 13 meiosis-specific intronic yeast genes undergo regulated splicing, which provides posttranscriptional regulation of the genes involved in yeast cell differentiation. Moreover, we found that approximately 16% of intronic genes in yeast are incompletely spliced during exponential growth in rich medium, which suggests that meiosis is not the only biological process regulated by splicing. Our tiling-array assay provides a snapshot of the spliced transcriptome in yeast. This robust methodology can be used to explore environmentally distinct splicing responses and should be readily adaptable to the study of other organisms, including humans.