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.

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.

Assessment of fetal sex chromosome aneuploidy using directed cell-free DNA analysis.

OBJECTIVE: To examine the performance of chromosome-selective sequencing of cell-free (cf) DNA in maternal blood for assessment of fetal sex chromosome aneuploidies. METHODS: This was a case-control study of 177 stored maternal plasma samples, obtained before fetal karyotyping at 11-13 weeks of gestation, from 59 singleton pregnancies with fetal sex chromosome aneuploidies (45,X, n = 49; 47,XXX, n = 6; 47,XXY, n = 1; 47,XYY, n = 3) and 118 with euploid fetuses (46,XY, n = 59; 46,XX, n = 59). Digital analysis of selected regions (DANSR™) on chromosomes 21, 18, 13, X and Y was performed and the fetal-fraction optimized risk of trisomy evaluation (FORTE™) algorithm was used to estimate the risk for non-disomic genotypes. Performance was calculated at a risk cut-off of 1:100. RESULTS: Analysis of cfDNA provided risk scores for 172 (97.2%) samples; 4 samples (45,X, n = 2; 46,XY, n = 1; 46,XX, n = 1) had an insufficient fetal cfDNA fraction for reliable testing and 1 case (47,XXX) failed laboratory quality control metrics. The classification was correct in 43 (91.5%) of 47 cases of 45,X, all 5 of 47,XXX, 1 of 47,XXY and 3 of 47,XYY. There were no false-positive results for monosomy X. DISCUSSION: Analysis of cfDNA by chromosome-selective sequencing can correctly classify fetal sex chromosome aneuploidy with reasonably high sensitivity.

Fetal fraction estimate in twin pregnancies using directed cell-free DNA analysis.

OBJECTIVE: To estimate fetal fraction (FF) in monozygotic and dizygotic twin pregnancies. METHODS: Maternal plasma samples were obtained from 35 monochorionic twin pregnancies with male fetuses (monozygotic) and 35 dichorionic pregnancies discordant for fetal sex (dizygotic) at 11-13 weeks' gestation. Cell-free DNA was extracted and chromosome-selective sequencing with digital analysis of selected regions (DANSR™) was carried out. The fetal-fraction optimized risk of trisomy evaluation (FORTE™) algorithm was used to estimate FF using polymorphic alleles. In dizygotic twins the FORTE algorithm was modified to estimate the smallest FF contribution of the 2 fetuses. In both types of twins, FF was also determined by analysis of Y-chromosome sequences. RESULTS: In monozygotic twins, the median total FF was 14.0% (range 8.2-27.0%) and in dizygotic twins the median smallest FF was 7.9% (4.9-14.0%). There were significant associations in FF between the methods using polymorphic alleles and Y-chromosome sequences for both monozygotic (r=0.951, p<0.0001) and dizygotic (r=0.743, p<0.0001) twins. CONCLUSIONS: The study demonstrates the feasibility of an approach for cfDNA testing in twin pregnancies. This involves estimation of total FF in monozygotic twins and estimation of the lower FF of the 2 fetuses in dizygotic twins.

Methyl coenzyme M reductase (mcrA) gene abundance correlates with activity measurements of methanogenic H2 /CO2 -enriched anaerobic biomass.

Biologically produced methane (CH4) from anaerobic digesters is a renewable alternative to fossil fuels, but digester failure can be a serious problem. Monitoring the microbial community within the digester could provide valuable information about process stability because this technology is dependent upon the metabolic processes of microorganisms. A healthy methanogenic community is critical for digester function and CH4 production. Methanogens can be surveyed and monitored using genes and transcripts of mcrA, which encodes the α subunit of methyl coenzyme M reductase - the enzyme that catalyses the final step in methanogenesis. Using clone libraries and quantitative polymerase chain reaction, we compared the diversity and abundance of mcrA genes and transcripts in four different methanogenic hydrogen/CO2 enrichment cultures to function, as measured by specific methanogenic activity (SMA) assays using H2 /CO2 . The mcrA gene copy number significantly correlated with CH4 production rates using H2 /CO2 , while correlations between mcrA transcript number and SMA were not significant. The DNA and cDNA clone libraries from all enrichments were distinctive but community diversity also did not correlate with SMA. Although hydrogenotrophic methanogens dominated these enrichments, the results indicate that this methodology should be applicable to monitoring other methanogenic communities in anaerobic digesters. Ultimately, this could lead to the engineering of digester microbial communities to produce more CH4 for use as renewable fuel.

Noninvasive prenatal detection and selective analysis of cell-free DNA obtained from maternal blood: evaluation for trisomy 21 and trisomy 18.

OBJECTIVE: We sought to develop a novel biochemical assay and algorithm for the prenatal evaluation of risk for fetal trisomy 21 (T21) and trisomy 18 (T18) using cell-free DNA obtained from maternal blood. STUDY DESIGN: We assayed cell-free DNA from a training set and a blinded validation set of pregnant women, comprising 250 disomy, 72 T21, and 16 T18 pregnancies. We used digital analysis of selected regions in combination with a novel algorithm, fetal-fraction optimized risk of trisomy evaluation (FORTE), to determine trisomy risk for each subject. RESULTS: In all, 163/171 subjects in the training set passed quality control criteria. Using a Z statistic, 35/35 T21 cases and 7/7 T18 cases had Z statistic >3 and 120/121 disomic cases had Z statistic <3. FORTE produced an individualized trisomy risk score for each subject, and correctly discriminated all T21 and T18 cases from disomic cases. All 167 subjects in the blinded validation set passed quality control and FORTE performance matched that observed in the training set correctly discriminating 36/36 T21 cases and 8/8 T18 cases from 123/123 disomic cases. CONCLUSION: Digital analysis of selected regions and FORTE enable accurate, scalable noninvasive fetal aneuploidy detection.

Human gene copy number spectra analysis in congenital heart malformations.

The clinical significance of copy number variants (CNVs) in congenital heart disease (CHD) continues to be a challenge. Although CNVs including genes can confer disease risk, relationships between gene dosage and phenotype are still being defined. Our goal was to perform a quantitative analysis of CNVs involving 100 well-defined CHD risk genes identified through previously published human association studies in subjects with anatomically defined cardiac malformations. A novel analytical approach permitting CNV gene frequency "spectra" to be computed over prespecified regions to determine phenotype-gene dosage relationships was employed. CNVs in subjects with CHD (n = 945), subphenotyped into 40 groups and verified in accordance with the European Paediatric Cardiac Code, were compared with two control groups, a disease-free cohort (n = 2,026) and a population with coronary artery disease (n = 880). Gains (≥200 kb) and losses (≥100 kb) were determined over 100 CHD risk genes and compared using a Barnard exact test. Six subphenotypes showed significant enrichment (P ≤ 0.05), including aortic stenosis (valvar), atrioventricular canal (partial), atrioventricular septal defect with tetralogy of Fallot, subaortic stenosis, tetralogy of Fallot, and truncus arteriosus. Furthermore, CNV gene frequency spectra were enriched (P ≤ 0.05) for losses at: FKBP6, ELN, GTF2IRD1, GATA4, CRKL, TBX1, ATRX, GPC3, BCOR, ZIC3, FLNA and MID1; and gains at: PRKAB2, FMO5, CHD1L, BCL9, ACP6, GJA5, HRAS, GATA6 and RUNX1. Of CHD subjects, 14% had causal chromosomal abnormalities, and 4.3% had likely causal (significantly enriched), large, rare CNVs. CNV frequency spectra combined with precision phenotyping may lead to increased molecular understanding of etiologic pathways.

Selective analysis of cell-free DNA in maternal blood for evaluation of fetal trisomy.

OBJECTIVE: To develop a novel prenatal assay based on selective analysis of cell-free DNA in maternal blood for evaluation of fetal Trisomy 21 (T21) and Trisomy 18 (T18). METHODS: Two hundred ninety-eight pregnancies, including 39 T21 and seven T18 confirmed fetal aneuploidies, were analyzed using a novel, highly multiplexed assay, termed digital analysis of selected regions (DANSR™). Cell-free DNA from maternal blood samples was analyzed using DANSR assays for loci on chromosomes 21 and 18. Products from 96 separate patients were pooled and sequenced together. A standard Z-test of chromosomal proportions was used to distinguish aneuploid samples from average-risk pregnancy samples. DANSR aneuploidy discrimination was evaluated at various sequence depths. RESULTS: At the lowest sequencing depth, corresponding to 204,000 sequencing counts per sample, average-risk cases where distinguished from T21 and T18 cases, with Z statistics for all cases exceeding 3.6. Increasing the sequencing depth to 410,000 counts per sample substantially improved separation of aneuploid and average-risk cases. A further increase to 620,000 counts per sample resulted in only marginal improvement. This depth of sequencing represents less than 5% of that required by massively parallel shotgun sequencing approaches. CONCLUSION: Digital analysis of selected regions enables highly accurate, cost efficient, and scalable noninvasive fetal aneuploidy assessment.

Non-invasive prenatal detection of trisomy 21 using tandem single nucleotide polymorphisms.

BACKGROUND: Screening tests for Trisomy 21 (T21), also known as Down syndrome, are routinely performed for the majority of pregnant women. However, current tests rely on either evaluating non-specific markers, which lead to false negative and false positive results, or on invasive tests, which while highly accurate, are expensive and carry a risk of fetal loss. We outline a novel, rapid, highly sensitive, and targeted approach to non-invasively detect fetal T21 using maternal plasma DNA. METHODS AND FINDINGS: Highly heterozygous tandem Single Nucleotide Polymorphism (SNP) sequences on chromosome 21 were analyzed using High-Fidelity PCR and Cycling Temperature Capillary Electrophoresis (CTCE). This approach was used to blindly analyze plasma DNA obtained from peripheral blood from 40 high risk pregnant women, in adherence to a Medical College of Wisconsin Institutional Review Board approved protocol. Tandem SNP sequences were informative when the mother was heterozygous and a third paternal haplotype was present, permitting a quantitative comparison between the maternally inherited haplotype and the paternally inherited haplotype to infer fetal chromosomal dosage by calculating a Haplotype Ratio (HR). 27 subjects were assessable; 13 subjects were not informative due to either low DNA yield or were not informative at the tandem SNP sequences examined. All results were confirmed by a procedure (amniocentesis/CVS) or at postnatal follow-up. Twenty subjects were identified as carrying a disomy 21 fetus (with two copies of chromosome 21) and seven subjects were identified as carrying a T21 fetus. The sensitivity and the specificity of the assay was 100% when HR values lying between 3/5 and 5/3 were used as a threshold for normal subjects. CONCLUSIONS: In summary, a targeted approach, based on calculation of Haplotype Ratios from tandem SNP sequences combined with a sensitive and quantitative DNA measurement technology can be used to accurately detect fetal T21 in maternal plasma when sufficient fetal DNA is present in maternal plasma.

Bioaugmentation for improved recovery of anaerobic digesters after toxicant exposure.

Bioaugmentation was investigated as a method to decrease the recovery period of anaerobic digesters exposed to a transient toxic event. Two sets of laboratory-scale digesters (SRT = 10 days, OLR = 2 g COD/L-day), started with inoculum from a digester stabilizing synthetic municipal wastewater solids (MW) and synthetic industrial wastewater (WW), respectively, were transiently exposed to the model toxicant, oxygen. Bioaugmented digesters received 1.2 g VSS/L-day of an H2-utilizing culture for which the archaeal community was analyzed. Soon after oxygen exposure, the bioaugmented digesters produced 25-60% more methane than non-bioaugmented controls (p < 0.05). One set of digesters produced lingering high propionate concentrations, and bioaugmentation resulted in significantly shorter recovery periods. The second set of digesters did not display lingering propionate, and bioaugmented digesters recovered at the same time as non-bioaugmented controls. The difference in the effect of bioaugmentation on recovery may be due to differences between microbial communities of the digester inocula originally employed. In conclusion, bioaugmentation with an H(2)-utilizing culture is a potential tool to decrease the recovery period, decrease propionate concentration, and increase biogas production of some anaerobic digesters after a toxic event. Digesters already containing rapidly adaptable microbial communities may not benefit from bioaugmentation, whereas other digesters with poorly adaptable microbial communities may benefit greatly.

Overview of BioCreative II gene mention recognition.

Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. Here we present brief descriptions of all the methods used and a statistical analysis of the results. We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible, and furthermore that the best result makes use of the lowest scoring submissions.

Molecular targets of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) within the zebrafish ovary: insights into TCDD-induced endocrine disruption and reproductive toxicity.

TCDD is a reproductive toxicant and endocrine disruptor, yet the mechanisms by which it causes these reproductive alterations are not fully understood. In order to provide additional insight into the molecular mechanisms that underlie TCDD's reproductive toxicity, we assessed TCDD-induced transcriptional changes in the ovary as they relate to previously described impacts on serum estradiol concentrations and altered follicular development in zebrafish. In silico computational approaches were used to correlate candidate regulatory motifs with observed changes in gene expression. Our data suggest that TCDD inhibits follicle maturation via attenuated gonadotropin responsiveness and/or depressed estradiol biosynthesis, and that interference of estrogen-regulated signal transduction may also contribute to TCDD's impacts on follicular development. TCDD may also alter ovarian function by disrupting various signaling pathways such as glucose and lipid metabolism, and regulation of transcription. Furthermore, events downstream from initial TCDD molecular-targets likely contribute to ovarian toxicity following chronic exposure to TCDD. Data presented here provide further insight into the mechanisms by which TCDD disrupts follicular development and reproduction in fish, and can be used to formulate new hypotheses regarding previously documented ovarian toxicity.

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

Analysis of concordance of different haplotype block partitioning algorithms.

BACKGROUND: Different classes of haplotype block algorithms exist and the ideal dataset to assess their performance would be to comprehensively re-sequence a large genomic region in a large population. Such data sets are expensive to collect. Alternatively, we performed coalescent simulations to generate haplotypes with a high marker density and compared block partitioning results from diversity based, LD based, and information theoretic algorithms under different values of SNP density and allele frequency. RESULTS: We simulated 1000 haplotypes using the standard coalescent for three world populations--European, African American, and East Asian--and applied three classes of block partitioning algorithms--diversity based, LD based, and information theoretic. We assessed algorithm differences in number, size, and coverage of blocks inferred under different conditions of SNP density, allele frequency, and sample size. Each algorithm inferred blocks differing in number, size, and coverage under different density and allele frequency conditions. Different partitions had few if any matching block boundaries. However they still overlapped and a high percentage of total chromosomal region was common to all methods. This percentage was generally higher with a higher density of SNPs and when rarer markers were included. CONCLUSION: A gold standard definition of a haplotype block is difficult to achieve, but collecting haplotypes covered with a high density of SNPs, partitioning them with a variety of block algorithms, and identifying regions common to all methods may be the best way to identify genomic regions that harbor SNP variants that cause disease.

Studying the functional genomics of stress responses in loblolly pine with the Expresso microarray experiment management system.

Conception, design, and implementation of cDNA microarray experiments present a variety of bioinformatics challenges for biologists and computational scientists. The multiple stages of data acquisition and analysis have motivated the design of Expresso, a system for microarray experiment management. Salient aspects of Expresso include support for clone replication and randomized placement; automatic gridding, extraction of expression data from each spot, and quality monitoring; flexible methods of combining data from individual spots into information about clones and functional categories; and the use of inductive logic programming for higher-level data analysis and mining. The development of Expresso is occurring in parallel with several generations of microarray experiments aimed at elucidating genomic responses to drought stress in loblolly pine seedlings. The current experimental design incorporates 384 pine cDNAs replicated and randomly placed in two specific microarray layouts. We describe the design of Expresso as well as results of analysis with Expresso that suggest the importance of molecular chaperones and membrane transport proteins in mechanisms conferring successful adaptation to long-term drought stress.