Valuable lessons-learned in transcriptomics experimentation

Bruning, Oskar; Rauwerda, Han; Dekker, R.J.; Leeuw, Wim C. de; Wackers, Paul; Ensink, Wim A.; Jonker, Martijs J.; Breit, Timo M.

doi:10.1080/21541264.2015.1064195

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…Second, pooling may be necessary if individual sample size does not yield sufficient product to be detectable in current methods or by current instruments (Schisterman and Vexler, 2008). Some have made the argument that pooling can reduce biological variation due to an outlier, and thus reduce noise in the data set (Zhang and Gant, 2005;Schisterman and Vexler, 2008;Bruning et al, 2015). Others have argued that pooling samples will remove natural variation and generate an artificial "in-between" phenotype (Bruning et al, 2015).…”

Section: Sample Poolingmentioning

confidence: 99%

“…Some have made the argument that pooling can reduce biological variation due to an outlier, and thus reduce noise in the data set (Zhang and Gant, 2005;Schisterman and Vexler, 2008;Bruning et al, 2015). Others have argued that pooling samples will remove natural variation and generate an artificial "in-between" phenotype (Bruning et al, 2015). However, the consequences of sample pooling are the loss of statistical power and the ability to assess real biological effects and variation.…”

Section: Sample Poolingmentioning

confidence: 99%

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Symposium review: Omics in dairy and animal science—Promise, potential, and pitfalls

Lippolis

Powell

Reinhardt

et al. 2019

Journal of Dairy Science

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Sequencing the first genome took 15 yr and $3 billion to complete. Currently, a genome can be sequenced in a day for a few thousand dollars. Comparing the relative abundance of nearly every mRNA transcript and small RNAs from cells and tissues from different experimental conditions has become so easy that it can take longer to transfer the data between computers than to perform the experiment. Nucleotide sequencing techniques have become so sensitive that the greatest concern is not detecting a gene or transcript but rather, falsely identifying one. Better genome sequencing has led to more complete transcriptomic and proteomic databases and, combined with more sensitive instrumentation and separation techniques, is bringing us closer to detecting complete transcriptomes and proteomes. The promise of these powerful omics techniques is to lead us to new and unexpected connections between molecular processes in the context of animal health. This promise cannot be achieved without hypothesis-driven research that connects omics data with animal health experiments. Any researcher who wishes to invest the time and resources in omics experiments should be aware of the common pitfalls and limitations of these techniques so they can avoid these issues and maximize the use of these research tools. Several important questions must be asked: What is the quality of the databases and how they are annotated? Are the annotations based on experimental results or computational predictions? What assumptions are made by the analysis algorithms, and how will this affect the result? Finally, how can the research community use the vast amount of data being generated by omics experiments in ways to achieve the goals of better animal health and production (which is the promise of omics technologies)? Until the observations shown in omics data sets are used to achieve the goals of better animal health and production, the potential of omics technology will not be fully realized.

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Section: Sample Poolingmentioning

confidence: 99%

Section: Sample Poolingmentioning

confidence: 99%

Symposium review: Omics in dairy and animal science—Promise, potential, and pitfalls

Lippolis

Powell

Reinhardt

et al. 2019

Journal of Dairy Science

View full text Add to dashboard Cite

show abstract

“…Another relevant question about data is its heterogeneity in term of quality, which is originated from multiple sources from experimental design, execution and analysis. Data quality from transcriptomics experiments should be seriously considered, as reviewed in [96]. Since TCM itself is a complex system, more attention should be paid to avoid confounding factors future science group Transcriptomics: a sword to cut the Gordian knot of traditional Chinese medicine Review in transcriptomics experimentations, such as sample pooling and statistical analysis of data, which would improve data quality and allow more biologically relevant interpretation.…”

Section: Accumulation Of Tcm Datamentioning

confidence: 99%

Transcriptomics: a Sword to Cut the Gordian knot of Traditional Chinese Medicine

Liu

Liao

et al. 2015

Biomark. Med.

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The systemic effects of traditional Chinese medicine (TCM) seem to be a Gordian knot, impossible to untie for decades. With the advent of transcriptomics, a useful sword is provided to cut the knot and shed some light on complex bioprocesses and intrinsic connections among them. Here, we revisit studies on TCM ZHENGs using this approach, highlight its applications on elucidating the potential scientific basis of ZHENG and investigating mechanisms of action for the TCM formula, and demonstrating its unique role in novel TCM drug design and discovery through active ingredient detection from TCM and compatibility theory study of TCM. The limitations and future perspectives of transcriptomics approaches to TCM study are also discussed.

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“…Transcriptomic studies using next-generation sequencing can comprehensively profile protein-coding (mRNAs) as well as non-coding RNAs (e.g., microRNAs, long non-coding RNAs, tRNAs), which play an equally important role in the cell as coding RNAs. Most recently, epitranscriptomics 26 —a study of the regulation and function of post-transcriptional RNA modifications—has emerged as an important link between environmental exposures and disease 27 – 31 . Studies in various model systems show that environmental stressors can change RNA modifications and reprogram regulatory RNAs 32 .…”

Section: Introductionmentioning

confidence: 99%

A precision environmental health approach to prevention of human disease

2023

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Human health is determined by the interaction of our environment with the genome, epigenome, and microbiome, which shape the transcriptomic, proteomic, and metabolomic landscape of cells and tissues. Precision environmental health is an emerging field leveraging environmental and system-level (‘omic) data to understand underlying environmental causes of disease, identify biomarkers of exposure and response, and develop new prevention and intervention strategies. In this article we provide real-life illustrations of the utility of precision environmental health approaches, identify current challenges in the field, and outline new opportunities to promote health through a precision environmental health framework.

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Valuable lessons-learned in transcriptomics experimentation

Cited by 4 publications

References 20 publications

Symposium review: Omics in dairy and animal science—Promise, potential, and pitfalls

Symposium review: Omics in dairy and animal science—Promise, potential, and pitfalls

Transcriptomics: a Sword to Cut the Gordian knot of Traditional Chinese Medicine

A precision environmental health approach to prevention of human disease

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