Genome

Genomics

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Genome sequencing brought the first complete description of the cell's components to light. It is a topic of ever increasing prominence with the advent of technologies that can sequence entire eukaryotic genomes in less than a week at a cost of less than a thousand dollars. Besides assembly and maintenance of such large amounts of data, data interpretation via automated annotation algorithms, and data access through tools such as genome browsers are active topics.

Introductory reading

Bakke et al. (2009) Evaluation of three automated genome annotations for Halorhabdus utahensis. PLoS ONE 4:e6291. (pmid: 19617911)

[ PubMed ] [ DOI ] Abstract Genome annotations are accumulating rapidly and depend heavily on automated annotation systems. Many genome centers offer annotation systems but no one has compared their output in a systematic way to determine accuracy and inherent errors. Errors in the annotations are routinely deposited in databases such as NCBI and used to validate subsequent annotation errors. We submitted the genome sequence of halophilic archaeon Halorhabdus utahensis to be analyzed by three genome annotation services. We have examined the output from each service in a variety of ways in order to compare the methodology and effectiveness of the annotations, as well as to explore the genes, pathways, and physiology of the previously unannotated genome. The annotation services differ considerably in gene calls, features, and ease of use. We had to manually identify the origin of replication and the species-specific consensus ribosome-binding site. Additionally, we conducted laboratory experiments to test H. utahensis growth and enzyme activity. Current annotation practices need to improve in order to more accurately reflect a genome's biological potential. We make specific recommendations that could improve the quality of microbial annotation projects.

Petty (2010) Genome annotation: man versus machine. Nat Rev Microbiol 8:762. (pmid: 20948549)

[ PubMed ] [ DOI ]

Cancer Genome Atlas Research Network (2011) Integrated genomic analyses of ovarian carcinoma. Nature 474:609-15. (pmid: 21720365)

[ PubMed ] [ DOI ] Abstract A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients' lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.

 

Contents

• Genome sequencing and assembly
• Genome annotation
• Genome browsers working with genome-scale information
• Programmatic access to genome sequences

 

Exercises

Pevsner (2009) Analysis of genomic DNA with the UCSC genome browser. Methods Mol Biol 537:277-301. (pmid: 19378150)

[ PubMed ] [ DOI ] Abstract Genomic DNA is being sequenced and annotated at a rapid rate, with terabases of DNA currently deposited in GenBank and other repositories. Genome browsers provide an essential collection of resources to visualize and analyze chromosomal DNA. The University of California, Santa Cruz (UCSC) Genome Browser provides annotations from the level of single nucleotides to whole chromosomes for four dozen metazoan and other species. The Genome Browser may be used to address a wide range of problems in bioinformatics (e.g., sequence analysis), comparative genomics, and evolution.

 

Further reading and resources

Harbison et al. (2004) Transcriptional regulatory code of a eukaryotic genome. Nature 431:99-104. (pmid: 15343339)

[ PubMed ] [ DOI ] Abstract DNA-binding transcriptional regulators interpret the genome's regulatory code by binding to specific sequences to induce or repress gene expression. Comparative genomics has recently been used to identify potential cis-regulatory sequences within the yeast genome on the basis of phylogenetic conservation, but this information alone does not reveal if or when transcriptional regulators occupy these binding sites. We have constructed an initial map of yeast's transcriptional regulatory code by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species. The organization of regulatory elements in promoters and the environment-dependent use of these elements by regulators are discussed. We find that environment-specific use of regulatory elements predicts mechanistic models for the function of a large population of yeast's transcriptional regulators.

Karolchik et al. (2007) Comparative genomic analysis using the UCSC genome browser. Methods Mol Biol 395:17-34. (pmid: 17993665)

[ PubMed ] [ DOI ] Abstract Comparative analysis of DNA sequence from multiple species can provide insights into the function and evolutionary processes that shape genomes. The University of California Santa Cruz (UCSC) Genome Bioinformatics group has developed several tools and methodologies in its study of comparative genomics, many of which have been incorporated into the UCSC Genome Browser (http://genome.ucsc.edu), an easy-to-use online tool for browsing genomic data and aligned annotation "tracks" in a single window. The comparative genomics annotations in the browser include pairwise alignments, which aid in the identification of orthologous regions between species, and conservation tracks that show measures of evolutionary conservation among sets of multiply aligned species, highlighting regions of the genome that may be functionally important. A related tool, the UCSC Table Browser, provides a simple interface for querying, analyzing, and downloading the data underlying the Genome Browser annotation tracks. Here, we describe a procedure for examining a genomic region of interest in the Genome Browser, analyzing characteristics of the region, filtering the data, and downloading data sets for further study.

Pop & Salzberg (2008) Bioinformatics challenges of new sequencing technology. Trends Genet 24:142-9. (pmid: 18262676)

[ PubMed ] [ DOI ] Abstract New DNA sequencing technologies can sequence up to one billion bases in a single day at low cost, putting large-scale sequencing within the reach of many scientists. Many researchers are forging ahead with projects to sequence a range of species using the new technologies. However, these new technologies produce read lengths as short as 35-40 nucleotides, posing challenges for genome assembly and annotation. Here we review the challenges and describe some of the bioinformatics systems that are being proposed to solve them. We specifically address issues arising from using these technologies in assembly projects, both de novo and for resequencing purposes, as well as efforts to improve genome annotation in the fragmented assemblies produced by short read lengths.

Picardi & Pesole (2010) Computational methods for ab initio and comparative gene finding. Methods Mol Biol 609:269-84. (pmid: 20221925)

[ PubMed ] [ DOI ] Abstract High-throughput DNA sequencing is increasing the amount of public complete genomes even though a precise gene catalogue for each organism is not yet available. In this context, computational gene finders play a key role in producing a first and cost-effective annotation. Nowadays a compilation of gene prediction tools has been made available to the scientific community and, despite the high number, they can be divided into two main categories: (1) ab initio and (2) evidence based. In the following, we will provide an overview of main methodologies to predict correct exon-intron structures of eukaryotic genes falling in such categories. We will take into account also new strategies that commonly refine ab initio predictions employing comparative genomics or other evidence such as expression data. Finally, we will briefly introduce metrics to in house evaluation of gene predictions in terms of sensitivity and specificity at nucleotide, exon, and gene levels as well.

Nagarajan & Pop (2010) Sequencing and genome assembly using next-generation technologies. Methods Mol Biol 673:1-17. (pmid: 20835789)

[ PubMed ] [ DOI ] Abstract Several sequencing technologies have been introduced in recent years that dramatically outperform the traditional Sanger technology in terms of throughput and cost. The data generated by these technologies are characterized by generally shorter read lengths (as low as 35 bp) and different error characteristics than Sanger data. Existing software tools for assembly and analysis of sequencing data are, therefore, ill-suited to handle the new types of data generated. This paper surveys the recent software packages aimed specifically at analyzing new generation sequencing data.

Han et al. (2011) SnapShot: High-throughput sequencing applications. Cell 146:1044, 1044.e1-2. (pmid: 21925324)

[ PubMed ] [ DOI ]

Kenny & Bustamante (2011) SnapShot: Human biomedical genomics. Cell 147:248-248.e1. (pmid: 21962520)

[ PubMed ] [ DOI ]

Tran et al. (2012) Cancer genomics: technology, discovery, and translation. J Clin Oncol 30:647-60. (pmid: 22271477)

[ PubMed ] [ DOI ] Abstract In recent years, the increasing awareness that somatic mutations and other genetic aberrations drive human malignancies has led us within reach of personalized cancer medicine (PCM). The implementation of PCM is based on the following premises: genetic aberrations exist in human malignancies; a subset of these aberrations drive oncogenesis and tumor biology; these aberrations are actionable (defined as having the potential to affect management recommendations based on diagnostic, prognostic, and/or predictive implications); and there are highly specific anticancer agents available that effectively modulate these targets. This article highlights the technology underlying cancer genomics and examines the early results of genome sequencing and the challenges met in the discovery of new genetic aberrations. Finally, drawing from experiences gained in a feasibility study of somatic mutation genotyping and targeted exome sequencing led by Princess Margaret Hospital-University Health Network and the Ontario Institute for Cancer Research, the processes, challenges, and issues involved in the translation of cancer genomics to the clinic are discussed.