Long-read sequence assembly of the gorilla genome

Abstract

Improving on the gorilla genome Access to complete, high-quality genomes of nonhuman primates will also help us understand human biology. Gordon et al. used long-read sequencing technology to improve genome data on our close relative the gorilla. Sequencing from a single individual decreased assembly fragmentation and recovered previously missed genes and noncoding loci. Mapping short-read sequences from additional gorillas helped reconstruct a “pan” gorilla sequence documenting genetic variation. Comparison with human genomes revealed species-specific differences ranging in size from one to thousands of bases in length, including some that are likely to affect gene regulation. Science , this issue p. 10.1126/science.aae0344

Keywords

GorillaSequence (biology)Computational biologySequence assemblyGenomeBiologyEvolutionary biologyWhole genome sequencingGeneticsPaleontologyGene

MeSH Terms

AnimalsContig MappingEvolutionMolecularExpressed Sequence TagsFemaleGenetic VariationGenomeHumanGenomicsGorilla gorillaHumansSequence AlignmentSequence AnalysisDNA

Affiliated Institutions

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Publication Info

Year: 2016
Type: article
Volume: 352
Issue: 6281
Pages: aae0344-aae0344
Citations: 391
Access: Closed

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APA Style

                            
                                
                                    David Gordon, 
                                
                                    John Huddleston, 
                                
                                    Mark Chaisson
                                
                                et al.
                            
                            (2016). 
                            Long-read sequence assembly of the gorilla genome. 
                            Science
                            , 352
                            (6281)
                            , aae0344-aae0344.
                            https://doi.org/10.1126/science.aae0344
                        

Identifiers

DOI: 10.1126/science.aae0344
PMID: 27034376
PMCID: PMC4920363

Data Quality

Data completeness: 90%