Dataset Information

Identification of individuals by trait prediction using whole-genome sequencing data.

ABSTRACT: Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demographic information is limited. However, we have developed a maximum entropy algorithm that integrates multiple predictions to determine which genomic samples and phenotype measurements originate from the same person. Using this algorithm, we have reidentified an average of >8 of 10 held-out individuals in an ethnically mixed cohort and an average of 5 of either 10 African Americans or 10 Europeans. This work challenges current conceptions of personal privacy and may have far-reaching ethical and legal implications.

SUBMITTER: Lippert C

PROVIDER: S-EPMC5617305 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Identification of individuals by trait prediction using whole-genome sequencing data.

Lippert Christoph C Sabatini Riccardo R Maher M Cyrus MC Kang Eun Yong EY Lee Seunghak S Arikan Okan O Harley Alena A Bernal Axel A Garst Peter P Lavrenko Victor V Yocum Ken K Wong Theodore T Zhu Mingfu M Yang Wen-Yun WY Chang Chris C Lu Tim T Lee Charlie W H CWH Hicks Barry B Ramakrishnan Smriti S Tang Haibao H Xie Chao C Piper Jason J Brewerton Suzanne S Turpaz Yaron Y Telenti Amalio A Roby Rhonda K RK Och Franz J FJ Venter J Craig JC

Proceedings of the National Academy of Sciences of the United States of America 20170905 38

Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demogr ...[more]

PMID: 28874526

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Project description:Transposable elements (TEs) along with simple sequence repeats (SSRs) are prevalent in eukaryotic genome, especially in mammals. Repetitive sequences form approximately one-third of the camelid genomes, so study on this part of genome can be helpful in providing deeper information from the genome and its evolutionary path. Here, in order to improve our understanding regarding the camel genome architecture, the whole genome of the two dromedaries (Yazdi and Trodi camels) was sequenced. Totally, 92- and 84.3-Gb sequence data were obtained and assembled to 137,772 and 149,997 contigs with a N50 length of 54,626 and 54,031 bp in Yazdi and Trodi camels, respectively. Results showed that 30.58% of Yazdi camel genome and 30.50% of Trodi camel genome were covered by TEs. Contrary to the observed results in the genomes of cattle, sheep, horse, and pig, no endogenous retrovirus-K (ERVK) elements were found in the camel genome. Distribution pattern of DNA transposons in the genomes of dromedary, Bactrian, and cattle was similar in contrast with LINE, SINE, and long terminal repeat (LTR) families. Elements like RTE-BovB belonging to LINEs family in cattle and sheep genomes are dramatically higher than genome of dromedary. However, LINE1 (L1) and LINE2 (L2) elements cover higher percentage of LINE family in dromedary genome compared to genome of cattle. Also, 540,133 and 539,409 microsatellites were identified from the assembled contigs of Yazdi and Trodi dromedary camels, respectively. In both samples, di-(393,196) and tri-(65,313) nucleotide repeats contributed to about 42.5% of the microsatellites. The findings of the present study revealed that non-repetitive content of mammalian genomes is approximately similar. Results showed that 9.1 Mb (0.47% of whole assembled genome) of Iranian dromedary's genome length is made up of SSRs. Annotation of repetitive content of Iranian dromedary camel genome revealed that 9,068 and 11,544 genes contain different types of TEs and SSRs, respectively. SSR markers identified in the present study can be used as a valuable resource for genetic diversity investigations and marker-assisted selection (MAS) in camel-breeding programs.

Dataset Information

Identification of individuals by trait prediction using whole-genome sequencing data.

Publications

Identification of individuals by trait prediction using whole-genome sequencing data.

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