Accurate Measurement of DNA Methylation: Challenges and Bias Correction.

DNA methylation is a key epigenetic modification involved in gene regulation whose contribution to disease susceptibility is still not fully understood. As the cost of genome sequencing technologies continues to drop, it will soon become commonplace to perform genome-wide quantification of DNA methylation at a single base-pair resolution. However, the demand for its accurate quantification might vary across studies. When the scope of the analysis is to detect regions of the genome with different methylation patterns between two or more conditions, e.g., case vs control; treatments vs placebo, accuracy is not crucial. This is the case in epigenome-wide association studies used as genome-wide screening of methylation changes to detect new candidate genes and regions associated with a specific disease or condition. If the aim of the analysis is to use DNA methylation measurements as a biomarker for diseases diagnosis and treatment (Laird, Nat Rev Cancer 3:253-266, 2003; Bock, Epigenomics 1:99-110, 2009), it is instead recommended to produce accurate methylation measurements. Furthermore, if the objective is the detection of DNA methylation in subclonal tumor cell populations or in circulating tumor DNA or in any case of mosaicism, the importance of accuracy becomes critical. The aim of this chapter is to describe the factors that could affect the precise measurement of methylation levels and a recent Bayesian statistical method called MethylCal and its extension that have been proposed to minimize this problem.

Exact mapping of Illumina blind spots in the Mycobacterium tuberculosis genome reveals platform-wide and workflow-specific biases.

Whole-genome sequencing (WGS) is fundamental to Mycobacterium tuberculosis basic research and many clinical applications. Coverage across Illumina-sequenced M. tuberculosis genomes is known to vary with sequence context, but this bias is poorly characterized. Here, through a novel application of phylogenomics that distinguishes genuine coverage bias from deletions, we discern Illumina 'blind spots' in the M. tuberculosis reference genome for seven sequencing workflows. We find blind spots to be widespread, affecting 529 genes, and provide their exact coordinates, enabling salvage of unaffected regions. Fifty-seven pe/ppe genes (the primary families assumed to exhibit Illumina bias) lack blind spots entirely, while the remaining pe/ppe genes account for 55.1 % of blind spots. Surprisingly, we find coverage bias persists in homopolymers as short as 6 bp, shorter tracts than previously reported. While G+C-rich regions challenge all Illumina sequencing workflows, a modified Nextera library preparation that amplifies DNA with a high-fidelity polymerase markedly attenuates coverage bias in G+C-rich and homopolymeric sequences, expanding the 'Illumina-sequenceable' genome. Through these findings, and by defining workflow-specific exclusion criteria, we spotlight effective strategies for handling bias in M. tuberculosis Illumina WGS. This empirical analysis framework may be used to systematically evaluate coverage bias in other species using existing sequencing data.

A comparative analysis of library prep approaches for sequencing low input translatome samples.

BACKGROUND: Cell type-specific ribosome-pulldown has become an increasingly popular method for analysis of gene expression. It allows for expression analysis from intact tissues and monitoring of protein synthesis in vivo. However, while its utility has been assessed, technical aspects related to sequencing of these samples, often starting with a smaller amount of RNA, have not been reported. In this study, we evaluated the performance of five library prep protocols for ribosome-associated mRNAs when only 250 pg-4 ng of total RNA are used. RESULTS: We obtained total and RiboTag-IP RNA, in three biological replicates. We compared 5 methods of library preparation for Illumina Next Generation sequencing: NuGEN Ovation RNA-Seq system V2 Kit, TaKaRa SMARTer Stranded Total RNA-Seq Kit, TaKaRa SMART-Seq v4 Ultra Low Input RNA Kit, Illumina TruSeq RNA Library Prep Kit v2 and NEBNext® Ultra™ Directional RNA Library Prep Kit using slightly modified protocols each with 4 ng of total RNA. An additional set of samples was processed using the TruSeq kit with 70 ng, as a 'gold standard' control and the SMART-Seq v4 with 250 pg of total RNA. TruSeq-processed samples had the best metrics overall, with similar results for the 4 ng and 70 ng samples. The results of the SMART-Seq v4 processed samples were similar to TruSeq (Spearman correlation > 0.8) despite using lower amount of input RNA. All RiboTag-IP samples had an increase in the intronic reads compared with the corresponding whole tissue, suggesting that the IP captures some immature mRNAs. The SMARTer-processed samples had a higher representation of ribosomal and non-coding RNAs leading to lower representation of protein coding mRNA. The enrichment or depletion of IP samples compared to corresponding input RNA was similar across all kits except for SMARTer kit. CONCLUSION: RiboTag-seq can be performed successfully with as little as 250 pg of total RNA when using the SMART-Seq v4 kit and 4 ng when using the modified protocols of other library preparation kits. The SMART-Seq v4 and TruSeq kits resulted in the highest quality libraries. RiboTag IP RNA contains some immature transcripts.

New options for national population surveys: The implications of internet and smartphone coverage.

Challenges to survey data collection have increased the costs of social research via face-to-face surveys so much that it may become extremely difficult for social scientists to continue using these methods. A key drawback to less expensive Internet-based alternatives is the threat of biased results from coverage errors in survey data. The rise of Internet-enabled smartphones presents an opportunity to re-examine the issue of Internet coverage for surveys and its implications for coverage bias. Two questions (on Internet access and smartphone ownership) were added to the National Survey of Family Growth (NSFG), a U.S. national probability survey of women and men age 15-44, using a continuous sample design. We examine 16 quarters (4 years) of data, from September 2012 to August 2016. Overall, we estimate that 82.9% of the target NSFG population has Internet access, and 81.6% has a smartphone. Combined, this means that about 90.7% of U.S. residents age 15-44 have Internet access, via either traditional devices or a smartphone. We find some evidence of compensatory coverage when looking at key race/ethnicity and age subgroups. For instance, while Black teens (15-18) have the lowest estimated rate of Internet access (81.9%) and the lowest rate of smartphone usage (72.6%), an estimated 88.0% of this subgroup has some form of Internet access. We also examine the socio-demographic correlates of Internet and smartphone coverage, separately and combined, as indicators of technology access in this population. In addition, we look at the effect of differential coverage on key estimates produced by the NSFG, related to fertility, family formation, and sexual activity. While this does not address nonresponse or measurement biases that may differ for alternative modes, our paper has implications for possible coverage biases that may arise when switching to a Web-based mode of data collection, either for follow-up surveys or to replace the main face-to-face data collection.

Including mobile-only telephone users in a statewide preventive health survey-Differences in the prevalence of health risk factors and impact on trends.

The Queensland preventive health survey is conducted annually to monitor the prevalence of behavioural risk factors in the north-east Australian state. Prompted by domestic and international trends in mobile telephone usage, the 2015 survey incorporated both mobile and landline telephone numbers from a list-based sampling frame. Estimates for landline-accessible and mobile-only respondents are compared to assess potential bias in landline-only surveys in the context of public health surveillance. Significant differences were found in subcategories of all health prevalence estimates considered (alcohol consumption, body mass index, smoking, and physical activity) from 2015 survey results. Results from Australian and international studies that have considered mobile telephone non-coverage bias are also summarised and discussed. We find that adjusting for sampling biases of telephone surveys by weighting does not fully compensate for the differences in prevalence estimates. However, predicted trends from previous years' surveys only differ significantly for the 2015 prevalence estimates of alcohol consumption. We conclude that the inclusion of mobile telephones into standard telephones surveys is important for obtaining valid, reliable and representative data to reduce bias in health prevalence estimates. Importantly, unlike some international experiences, the addition of mobiles telephones into the Queensland preventive health survey occurred before population trends were significantly affected.

Profiling the mobile-only population in Australia: insights from the Australian National Health Survey.

BACKGROUND: The Australian population that relies on mobile phones exclusively has increased from 5% in 2005 to 29% in 2014. Failing to include this mobile-only population leads to a potential bias in estimates from landline-based telephone surveys. This paper considers the impacts on selected health prevalence estimates with and without the mobile-only population. METHODS: Using data from the Australian Health Survey - which, for the first time, included a question on telephone status - we examined demographic, geographic and health differences between the landline-accessible and mobile-only population. These groups were also compared to the full population, controlling for the sampling design and differential non-response patterns in the observed sample through weighting and benchmarking. RESULTS: The landline-accessible population differs from the mobile-only population for selected health measures resulting in biased prevalence estimates for smoking, alcohol risk and private health insurance coverage in the full population. The differences remain even after adjusting for age and gender. CONCLUSIONS: Using landline telephones only for conducting population health surveys will have an impact on prevalence rate estimates of health risk factors due to the differing profiles of the mobile-only population from the landline-accessible population.

Cobertura de linhas telefônicas residenciais e vícios potenciais em estudos epidemiológicos / Home landline telephone coverage and potential bias in epidemiological surveys

OBJETIVO: Estimar o efeito da taxa de cobertura de linhas telefônicas residenciais em potenciais vícios de informação em inquéritos epidemiológicos. MÉTODOS: Foram utilizadas as bases de dados da Pesquisa Nacional por Amostra de Domicílios no período de 1998 a 2003 para a estimativa das taxas de cobertura de linhas telefônicas residenciais nas cinco regiões geográficas brasileiras. Utilizou-se a regressão logística múltipla para identificar os fatores associados à posse de linha telefônica fixa. O impacto do vício nos intervalos com 95% de confiança foi avaliado em função da precisão alcançada em cada situação. RESULTADOS: Nas regiões metropolitanas Sudeste, Sul e Centro-Oeste com 70% e mais de cobertura, os vícios associados foram considerados desprezíveis. Nas demais regiões, os vícios relativos estavam acima do limite aceitável (0,4), indicando possíveis erros nas inferências construídas sob intervalo com 95% de confiança. A chance de acesso à linha telefônica residencial foi maior para população com cor da pele branca e maior escolaridade. CONCLUSÕES: Os achados mostram que o uso de cadastro de linhas telefônicas residenciais é indicado para a realização de inquéritos epidemiológicos apenas para estados com cobertura acima de 70%. Metodologias específicas para o tratamento de estimativas obtidas em localidades com taxas inferiores, precisam ser estudadas e divulgadas.

OBJECTIVE: To estimate landline telephone coverage effects on potential information bias in epidemiological surveys. METHODS: Databases of the Pesquisa Nacional por Amostra de Domicílios (National Household Sample Survey), from 1998 to 2003, were used to estimate landline telephone coverage rates in the five Brazilian geographic regions. Multiple regression analysis was used to identify factors associated with owning a landline telephone. Bias impact on 95% confidence intervals was assessed, according to the accuracy achieved in each situation. RESULTS: In the Southern and Central-west metropolitan regions, with 70% coverage or more, associated bias was considered insignificant. In the remaining regions, related bias was above the acceptable limit (0.4), indicating possible errors in inferences drawn with a 95% confidence interval. Likelihood of access to a home landline telephone was greater among the white population with higher level of education. CONCLUSIONS: Findings reveal that the use of residential telephone records is indicated to conduct epidemiological surveys in Brazilian states where coverage is above 70% exclusively. Specific methodologies to treat estimates obtained in regions with lower rates need to be analyzed and published.

OBJETIVO: Estimar el efecto de la tasa de cobertura de líneas telefónicas residenciales en potenciales vicios de información en investigaciones epidemiológicas. MÉTODOS: Fueron utilizadas las bases de datos de la Pesquisa Nacional por Muestra de Domicilios en el período de 1998 a 2003 para la estimación de las tasas de cobertura de líneas telefónicas residenciales en las cinco regiones geográficas brasileras. Se utilizó la regresión logística múltiple para identificar los factores asociados al poseer línea telefónica fija. El impacto del vicio en los intervalos con 95% de confianza fue evaluado en función de la precisión alcanzada en cada situación.RESULTADOS: En la regiones metropolitanas Sureste, Sur y Centro-Oeste con 70% y más de cobertura, los vicios asociados fueron considerados despreciables. En las demás regiones, los vicios relativos estaban por encima del límite aceptable (0,4), indicando posibles errores en las inferencias construidas bajo el intervalo con 95% de confianza. La probabilidad de acceso a la línea telefónica residencial fue mayor para la población con color de piel blanca y mayor escolaridad. CONCLUSIONES: Los resultados muestran que el uso de registro de líneas telefónicas residenciales es indicado para la realización de investigaciones epidemiológicas apenas para estados con cobertura por encima de 70%. Metodologías específicas para el tratamiento de estimativas obtenidas en localidades con tasas inferiores, precisan ser estudiadas y divulgadas.