Since the development of technologies that can determine the base-pair sequence of DNA, the ability to sequence genes has contributed much to science and medicine. However, it has remained a relatively costly and laborious process, hindering its use as a routine biomedical tool. Recent times are seeing rapid developments in this field, both in the availability of novel sequencing platforms, as well as supporting technologies involved in processes such as targeting and data analysis. This is leading to significant reductions in the cost of sequencing a human genome and the potential for its use as a routine biomedical tool. This review is a snapshot of this rapidly moving field examining the current state of the art, forthcoming developments and some of the issues still to be resolved prior to the use of new sequencing technologies in routine clinical diagnosis.

Background

Cell-free fetal DNA (cffDNA) can be detected in maternal blood during pregnancy, opening the possibility of early non-invasive prenatal diagnosis for a variety of genetic conditions. Since 1997, many studies have examined the accuracy of prenatal fetal sex determination using cffDNA, particularly for pregnancies at risk of an X-linked condition. Here we report a review and meta-analysis of the published literature to evaluate the use of cffDNA for prenatal determination (diagnosis) of fetal sex. We applied a sensitive search of multiple bibliographic databases including PubMed (MEDLINE), EMBASE, the Cochrane library and Web of Science.

Results

Ninety studies, incorporating 9,965 pregnancies and 10,587 fetal sex results met our inclusion criteria. Overall mean sensitivity was 96.6% (95% credible interval 95.2% to 97.7%) and mean specificity was 98.9% (95% CI = 98.1% to 99.4%). These results vary very little with trimester or week of testing, indicating that the performance of the test is reliably high.

Conclusions

Based on this review and meta-analysis we conclude that fetal sex can be determined with a high level of accuracy by analyzing cffDNA. Using cffDNA in prenatal diagnosis to replace or complement existing invasive methods can remove or reduce the risk of miscarriage. Future work should concentrate on the economic and ethical considerations of implementing an early non-invasive test for fetal sex.

The diverse sequences of viral populations within individual hosts are the starting material for selection and subsequent evolution of RNA viruses such as foot-and-mouth disease virus (FMDV). Using next-generation sequencing (NGS) performed on a Genome Analyzer platform (Illumina), this study compared the viral populations within two bovine epithelial samples (foot lesions) from a single animal with the inoculum used to initiate experimental infection. Genomic sequences were determined in duplicate sequencing runs, and the consensus sequence of the inoculum determined by NGS was identical to that previously determined using the Sanger method. However, NGS revealed the fine polymorphic substructure of the viral population, from nucleotide variants present at just below 50% frequency to those present at fractions of 1%. Some of the higher-frequency polymorphisms identified encoded changes within codons associated with heparan sulfate binding and were present in both foot lesions, revealing intermediate stages in the evolution of a tissue culture-adapted virus replicating within a mammalian host. We identified 2,622, 1,434, and 1,703 polymorphisms in the inoculum and in the two foot lesions, respectively: most of the substitutions occurred in only a small fraction of the population and represented the progeny from recent cellular replication prior to onset of any selective pressures. We estimated the upper limit for the genome-wide mutation rate of the virus within a cell to be 7.8 × 10−4 per nucleotide. The greater depth of detection achieved by NGS demonstrates that this method is a powerful and valuable tool for the dissection of FMDV populations within hosts.

In June 2009, the Science and Technology Committee of the UK House of Lords published a report on genomic medicine, based on expert evidence collected over an 18-month period. Crucially, the report signaled that the use of genomic medicine was at a crossroads, due to the rapid development of new technologies, and opened up opportunities across the whole of medicine and healthcare. This commentary responds to the report's call for a new health service strategy, including a new genetics White Paper from the Government, and suggests some of the important elements that need further consideration.

The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice.The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality.Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction.A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines.These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.

The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.

The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.