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Record W2046558909 · doi:10.1242/dev.085860

An introduction to decoding genomes

2012· article· en· W2046558909 on OpenAlexaff
Jennifer A. Mitchell

Bibliographic record

VenueDevelopment · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyGenomeComputational biologyDecoding methodsEvolutionary biologyGeneticsGeneComputer science

Abstract

fetched live from OpenAlex

The past 20 years has seen a revolution in genomics. From the completion of the human genome in 2003, which took 13 years, we are well on our way to achieving the next benchmark goal of having 1000 human genomes sequenced (The 1000 Genomes Project). This endeavour will provide a deep catalogue of human genetic variation. In addition, and as part of The Genome 10K Project (which aims to sequence the genomes of 10,000 vertebrate species), 2012 saw the initial assembly of the medium ground finch (Geospiza fortis) genome, one of the iconic Galapagos finches described by Charles Darwin. The results of these genome sequencing projects are available through freely accessible public databases, thus accelerating discoveries in diverse fields of biology. With the advent of next-generation sequencing platforms, the time and cost of sequencing have dropped dramatically, making the ability to sequence the human genome in a day for less than $1000 no longer science fiction but rather an event that will happen in the immediate future. The effects of this genomics revolution are widespread, and no field of biology or medicine remains untouched by the changes in sequencing throughput. Furthermore, genomic studies are so commonly highlighted by the media that a working understanding of genomics is increasingly important in undergraduate biology education.The second edition of Introduction to Genomics by Arthur M. Lesk is a comprehensive introduction to genomics that covers a diversity of topics, from genome sequencing to systems biology approaches used for understanding the metabolome, transcriptome and proteome. This new edition strives to highlight the progress made in genomics due to the increased application of high-throughput sequencing techniques. The text is accessible to undergraduate students; it does a thorough job of providing the basic principles before moving on to more in-depth concepts. The author presents an important discussion of the ethical issues surrounding genome sequencing, including the efforts taken to protect individuals who contribute samples to the large-scale human genome sequencing projects that are currently underway. These issues are presented in a well-balanced and unbiased manner. Importantly, the text is a pleasure to read; detailed colour illustrations are provided throughout, as well as helpful analogies that allow the reader to get to grips with difficult concepts. For example, biological networks are compared to the London Underground map, where the stations are the nodes and the edges the tracks that connect them.This new edition highlights recent advances in sequencing techniques while still presenting the historical context for the discovery of genomes. Early in the text, the history of the discovery of DNA structure, the need to understand the ‘language of the genome’, and early progress in sequencing techniques are discussed in a narrative manner. Lesk writes, “the sequence of the bases was like a text everyone wanted to read, not only was the text in an unknown language, but there were not even any examples of the language, because the sequences were unknown”, thus framing the importance of early DNA sequencing efforts in ultimately decoding the human genome. This leads into the development of Sanger sequencing, a method developed by Frederick Sanger, and the sequencing of the 5386 bp ΦX174 bacteriophage genome, the first completed DNA genome sequence. Following on from this is the adaptation of Sanger sequencing to automated DNA sequencing using fluorescent tags and next-generation high-throughput sequencing techniques. As in the rest of the book, colour illustrations are used to great effect to explain the techniques and to provide examples of data output. These examples of data output are increasingly important, as so few students today will ever perform a Sanger sequencing reaction and see how the individual base-terminated chains resolved on the gel are composed into a sequence. So, although this technique has been replaced with higher throughput variations, the visual understanding of the sequencing process provided by inspecting a Sanger sequencing gel remains unmatched.At the end of each chapter, selected additional reading is provided with problems that test the concepts discussed. The problems posed range from testing the basic understanding of the material to more thought-provoking questions that will allow students to test and deepen their understanding of the material. Of special note are the ‘weblem’ problems, which require the use of online genomics resources. These encourage students to develop a proficiency in the use of these resources, many of which are linked to the text through the publisher’s website. A ‘guided tour’ of genomics websites provides a list of websites with short descriptions and links to instructions or tutorials where available; however, this is merely a teaser that will hopefully push young scientists to explore more thoroughly the information that is available online to the scientific community.Although the second edition is updated with expanded content, the information on data gathered from next-generation sequencing projects is rather limited. However, as the author points out, this is a moving target with advances made weekly, and it is therefore difficult to ensure that the material is up to date in a text of this type. Even with this in mind, I found that the section on deep sequencing of transcriptomes and functional genomics could have been expanded upon; there is a huge wealth of genome-wide functional genomics data for human, mouse, fly and worm genomes generated by the ENCODE and modENCODE projects, which are only briefly mentioned (Gerstein et al., 2010; modENCODE Consortium, 2010; ENCODE Project Consortium, 2011). These data are easily accessible through online browsers (UCSC Genome Browser, modENCODE GBrowse), massively accelerating the discovery of new genes, non-coding RNAs and regulatory elements such as enhancers and insulators. With the focus on students exploring genomics data on the web, these resources could have been better highlighted.Given the widespread impact that sequenced genomes have on research, medicine and the general public, an introductory text such as this is an important resource. Introduction to Genomics is beautifully illustrated, supported by end of chapter and additional online resources, and written in an eloquent and readable style. Beyond focusing on genome sequencing and comparative genomics, a good deal of the text is concerned with transcripts, proteins and proteomics. However, there is minimal mention of transcriptional regulatory regions of the genome. I would have liked to see more emphasis given to transcription factor binding in the genome, epigenetic modifications and chromatin features, which are proving invaluable in identifying intergenic regulatory regions. Given the observation that disease-linked single-nucleotide polymorphisms are more often found in non-coding than in coding regions (Manolio, 2010), understanding how regulatory regions function is crucial in decoding the human genome and understanding predisposition to disease. Nonetheless, Introduction to Genomics is a comprehensive textbook that provides a solid introduction to the study of genomes and will be a great resource to undergraduate students with a background in molecular biology. The text also provides a useful resource for graduate students in other fields who want to make use of the growing number of online genomics resources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.248
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2012
Admission routes1
Has abstractyes

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