Next-generation sequencing and epigenome technologies: potential medical applications

Review on the Application of Machine Learning Algorithms in the Sequence Data Mining of DNA

Deoxyribonucleic acid (DNA) is a biological macromolecule. Its main function is information storage. At present, the advancement of sequencing technology had caused DNA sequence data to grow at an explosive rate, which has also pushed the study of DNA sequences in the wave of big data. Moreover, machine learning is a powerful technique for analyzing largescale data and learns spontaneously to gain knowledge. It has been widely used in DNA sequence data analysis and obtained a lot of research achievements. Firstly, the review introduces the development process of sequencing technology, expounds on the concept of DNA sequence data structure and sequence similarity. Then we analyze the basic process of data mining, summary several major machine learning algorithms, and put forward the challenges faced by machine learning algorithms in the mining of biological sequence data and possible solutions in the future. Then we review four typical applications of machine learning in DNA sequence data: DNA sequence alignment, DNA sequence classification, DNA sequence clustering, and DNA pattern mining. We analyze their corresponding biological application background and significance, and systematically summarized the development and potential problems in the field of DNA sequence data mining in recent years. Finally, we summarize the content of the review and look into the future of some research directions for the next step.

Transforming Ocean Conservation: Applying the Genetic Rescue Toolkit

Although oceans provide critical ecosystem services and support the most abundant populations on earth, the extent of damage impacting oceans and the diversity of strategies to protect them is disconcertingly, and disproportionately, understudied. While conventional modes of conservation have made strides in mitigating impacts of human activities on ocean ecosystems, those strategies alone cannot completely stem the tide of mounting threats. Biotechnology and genomic research should be harnessed and developed within conservation frameworks to foster the persistence of viable ocean ecosystems. This document distills the results of a targeted survey, the Ocean Genomics Horizon Scan, which assessed opportunities to bring novel genetic rescue tools to marine conservation. From this Horizon Scan, we have identified how novel approaches from synthetic biology and genomics can alleviate major marine threats. While ethical frameworks for biotechnological interventions are necessary for effective and responsible practice, here we primarily assessed technological and social factors directly affecting technical development and deployment of biotechnology interventions for marine conservation. Genetic insight can greatly enhance established conservation methods, but the severity of many threats may demand genomic intervention. While intervention is controversial, for many marine areas the cost of inaction is too high to allow controversy to be a barrier to conserving viable ecosystems. Here, we offer a set of recommendations for engagement and program development to deploy genetic rescue safely and responsibly.

Impact of New Genomic Technologies on Understanding Adverse Drug Reactions

It is well established that variations in genes can alter the pharmacokinetic and pharmacodynamic profile of a drug and immunological responses to it. Early advances in pharmacogenetics were made with traditional genetic techniques such as functional cloning of genes using knowledge gained from purified proteins, and candidate gene analysis. Over the past decade, techniques for analysing the human genome have accelerated greatly as knowledge and technological capabilities have grown. These techniques were initially focussed on understanding genetic factors of disease, but increasingly they are helping to clarify the genetic basis of variable drug responses and adverse drug reactions (ADRs). We examine genetic methods that have been applied to the understanding of ADRs, review the current state of knowledge of genetic factors that influence ADR development, and discuss how the application of genome-wide association studies and next-generation sequencing approaches is supporting and extending existing knowledge of pharmacogenetic processes leading to ADRs. Such approaches have identified single genes that are major contributing genetic risk factors for an ADR, (such as flucloxacillin and drug-induced liver disease), making pre-treatment testing a possibility. They have contributed to the identification of multiple genetic determinants of a single ADR, some involving both pharmacologic and immunological processes (such as phenytoin and severe cutaneous adverse reactions). They have indicated that rare genetic variants, often not previously reported, are likely to have more influence on the phenotype than common variants that have been traditionally tested for. The problem of genotype/phenotype discordance affecting the interpretation of pharmacogenetic screening and the future of genome-based testing applied to ADRs are also discussed.

Epigenetics in the Neoliberal "Regime of Truth": A Biopolitical Perspective on Knowledge Translation

Recent findings in epigenetics have been attracting much attention from social scientists and bioethicists because they reveal the molecular mechanisms by which exposure to socioenvironmental factors, such as pollutants and social adversity, can influence the expression of genes throughout life. Most surprisingly, some epigenetic modifications may also be heritable via germ cells across generations. Epigenetics may be the missing molecular evidence of the importance of using preventive strategies at the policy level to reduce the incidence and prevalence of common diseases. But while this "policy translation" of epigenetics introduces new arguments in favor of public health strategies and policy-making, a more "clinical translation" of epigenetics is also emerging. It focuses on the biochemical mechanisms and epigenetic variants at the origin of disease, leading to novel biomedical means of assessing epigenetic susceptibility and reversing detrimental epigenetic variants. In this paper, we argue that the impetus to create new biomedical interventions to manipulate and reverse epigenetic variants is likely to garner more attention than effective social and public health interventions and therefore also to garner a greater share of limited public resources. This is likely to happen because of the current biopolitical context in which scientific findings are translated. This contemporary neoliberal "regime of truth," to use a term from Michel Foucault, greatly influences the ways in which knowledge is being interpreted and implemented. Building on sociologist Thomas Lemke's Foucauldian "analytics of biopolitics" and on literature from the field of science and technology studies, we present two sociological trends that may impede the policy translation of epigenetics: molecularization and biomedicalization. These trends, we argue, are likely to favor the clinical translation of epigenetics-in other words, the development of new clinical tools fostering what has been called "personalized" or "precision" medicine. In addition, we argue that an overemphasized clinical translation of epigenetics may further reinforce this biopolitical landscape through four processes closely related to neoliberal pathways of thinking: the internalization and isolation (aspects of liberal individualism) of socioenvironmental determinants of health and increased opportunities for commodification and technologicalization (aspects of economic liberalism) of health care interventions.

Non-coding RNAs in pluripotency and neural differentiation of human pluripotent stem cells

Several studies have demonstrated the important role of non-coding RNAs as regulators of posttranscriptional processes, including stem cells self-renewal and neural differentiation. Human embryonic stem cells (hESCs) and induced pluripotent stem cells (ihPSCs) show enormous potential in regenerative medicine due to their capacity to differentiate to virtually any type of cells of human body. Deciphering the role of non-coding RNAs in pluripotency, self-renewal and neural differentiation will reveal new molecular mechanisms involved in induction and maintenances of pluripotent state as well as triggering these cells toward clinically relevant cells for transplantation. In this brief review we will summarize recently published studies which reveal the role of non-coding RNAs in pluripotency and neural differentiation of hESCs and ihPSC.

Gaucher disease: transcriptome analyses using microarray or mRNA sequencing in a Gba1 mutant mouse model treated with velaglucerase alfa or imiglucerase

Gaucher disease type 1, an inherited lysosomal storage disorder, is caused by mutations in GBA1 leading to defective glucocerebrosidase (GCase) function and consequent excess accumulation of glucosylceramide/glucosylsphingosine in visceral organs. Enzyme replacement therapy (ERT) with the biosimilars, imiglucerase (imig) or velaglucerase alfa (vela) improves/reverses the visceral disease. Comparative transcriptomic effects (microarray and mRNA-Seq) of no ERT and ERT (imig or vela) were done with liver, lung, and spleen from mice having Gba1 mutant alleles, termed D409V/null. Disease-related molecular effects, dynamic ranges, and sensitivities were compared between mRNA-Seq and microarrays and their respective analytic tools, i.e. Mixed Model ANOVA (microarray), and DESeq and edgeR (mRNA-Seq). While similar gene expression patterns were observed with both platforms, mRNA-Seq identified more differentially expressed genes (DEGs) (∼3-fold) than the microarrays. Among the three analytic tools, DESeq identified the maximum number of DEGs for all tissues and treatments. DESeq and edgeR comparisons revealed differences in DEGs identified. In 9V/null liver, spleen and lung, post-therapy transcriptomes approximated WT, were partially reverted, and had little change, respectively, and were concordant with the corresponding histological and biochemical findings. DEG overlaps were only 8–20% between mRNA-Seq and microarray, but the biological pathways were similar. Cell growth and proliferation, cell cycle, heme metabolism, and mitochondrial dysfunction were most altered with the Gaucher disease process. Imig and vela differentially affected specific disease pathways. Differential molecular responses were observed in direct transcriptome comparisons from imig- and vela-treated tissues. These results provide cross-validation for the mRNA-Seq and microarray platforms, and show differences between the molecular effects of two highly structurally similar ERT biopharmaceuticals.