Using Portuguese BRCA pathogenic variation as a model to study the impact of human admixture on human health.

BACKGROUND: Admixture occurs between different ethnic human populations. The global colonization in recent centuries by Europeans led to the most significant admixture in human history. While admixture may enhance genetic diversity for better fitness, it may also impact on human health by transmitting genetic variants for disease susceptibility in the admixture population. The admixture by Portuguese global exploration initiated in the 15th century has reached over 20 million of Portuguese-heritage population worldwide. It provides a valuable model to study the impact of admixture on human health. BRCA1 and BRCA2 (BRCA) are two of the important tumor suppressor genes. The pathogenic variation (PV) in BRCA is well determined to cause high risk of hereditary breast and ovarian cancer. Tracing the distribution of Portuguese BRCA PV in Portuguese-heritage population will help to understand the impact of admixture on cancer susceptibility in modern humans. In this study, we analyzed the distribution of the Portuguese-originated BRCA variation in Brazilian population, which has high degree Portuguese-heritage. METHODS: By comprehensive data mining, standardization and annotation, we generated a Portuguese-derived BRCA variation dataset and a Brazilian-derived BRCA variation dataset. We compared the two BRCA variation datasets to identify the BRCA variants shared between the two populations. RESULTS: The Portuguese-derived BRCA variation dataset consists of 220 BRCA variants including 78 PVs from 11,482 Portuguese cancer patients, 93 (42.2%) in BRCA1 and 127 (57.7%) in BRCA2. Of the 556 Portuguese BRCA PV carriers carrying the 78 PVs, 331 (59.5%) carried the three Portuguese-BRCA founder PVs of BRCA1 c.2037delinsCC, BRCA1 c.3331_3334del and BRCA2 c.156_157insAlu. The Brazilian-derived BRCA variation dataset consists of 255 BRCA PVs from 7,711 cancer patients, 136 (53.3%) in BRCA1 and 119 (46.6%) in BRCA2. We developed an open database named dbBRCA-Portuguese ( https://genemutation.fhs.um.edu.mo/dbbrca-portuguese/ ) and an open database named dbBRCA-Brazilian ( https://genemutation.fhs.um.edu.mo/dbbrca-brazilian ) to host the BRCA variation data from Portuguese and Brazilian populations. We compared the BRCA PV datasets between Portuguese and Brazilian populations, and identified 29 Portuguese-specific BRCA PVs shared between Portuguese and Brazilian populations, 14 in BRCA1 including the Portuguese founder BRCA1 c.3331_3334del and BRCA1 c.2037delinsCC, and 15 in BRCA2 including the Portuguese founder BRCA2 c.156_157insAlu. Searching the 78 Portuguese BRCA PVs in over 5,000 ancient human genomes identified evolution origin for only 8 PVs in Europeans dated between 37,470 and 3,818 years before present, confirming the Portuguese-specificity of Portuguese BRCA PVs; comparing the 78 Portuguese BRCA PVs Portuguese, 255 Brazilian BRCA PVs, and 134 African BRCA PVs showed little overlapping, ruling out the possibility that the BRCA PVs shared between Portuguese and Brazilian may also be contributed by African. CONCLUSION: Our study provides evidence that the admixture in recent human history contributed to cancer susceptibility in modern humans.

Generation of longer 3' cDNA fragments from massively parallel signature sequencing tags.

Massively Parallel Signature Sequencing (MPSS) is a powerful technique for genome-wide gene expression analysis, which, similar to SAGE, relies on the production of short tags proximal to the 3'end of transcripts. A single MPSS experiment can generate over 10(7) tags, providing a 10-fold coverage of the transcripts expressed in a human cell. A significant fraction of MPSS tags cannot be assigned to known transcripts (orphan tags) and are likely to be derived from transcripts expressed at very low levels (approximately 1 copy per cell). In order to explore the potential of MPSS for the characterization of the human transcriptome, we have adapted the GLGI protocol (Generation of Longer cDNA fragments from SAGE tags for Gene Identification) to convert MPSS tags into their corresponding 3' cDNA fragments. GLGI-MPSS was applied to 83 orphan tags and 41 cDNA fragments were obtained. The analysis of these 41 fragments allowed the identification of novel transcripts, alternative tags generated from polymorphic and alternatively spliced transcripts, as well as the detection of artefactual MPSS tags. A systematic large-scale analysis of the genome by MPSS, in combination with the use of GLGI-MPSS protocol, will certainly provide a complementary approach to generate the complete catalog of human transcripts.