Francisco M. De La Vega

A genome-wide association scan of nonsynonymous SNPs identifies a susceptibility variant for Crohn disease in ATG16L1.

We performed a genome-wide association study of 19,779 nonsynonymous SNPs in 735 individuals with Crohn disease and 368 controls. A total of 7,159 of these SNPs were informative. We followed up on all 72 SNPs with P ≤ 0.01 with an allele-based disease association test in 380 independent Crohn disease trios, 498 Crohn disease singleton cases and 1,032 controls. Disease association of rs2241880 in the autophagy-related 16-like 1 gene (ATG16L1) was replicated in these samples (P = 4.0 × 10−8) and confirmed in a UK case-control sample (P = 0.0004). By haplotype and regression analysis, we found that marker rs2241880, a coding SNP (T300A), carries virtually all the disease risk exerted by the ATG16L1 locus. The ATG16L1 gene encodes a protein in the autophagosome pathway that processes intracellular bacteria. We found a statistically significant interaction with respect to Crohn disease risk between rs2241880 and the established CARD15 susceptibility variants (P = 0.039). Together with the lack of association between rs2241880 and ulcerative colitis (P > 0.4), these data suggest that the underlying biological process may be specific to Crohn disease.

Sequence and structural variation in a human genome uncovered by short-read, massively parallel ligation sequencing using two-base encoding

We describe the genome sequencing of an anonymous individual of African origin using a novel ligation-based sequencing assay that enables a unique form of error correction that improves the raw accuracy of the aligned reads to >99.9%, allowing us to accurately call SNPs with as few as two reads per allele. We collected several billion mate-paired reads yielding approximately 18x haploid coverage of aligned sequence and close to 300x clone coverage. Over 98% of the reference genome is covered with at least one uniquely placed read, and 99.65% is spanned by at least one uniquely placed mate-paired clone. We identify over 3.8 million SNPs, 19% of which are novel. Mate-paired data are used to physically resolve haplotype phases of nearly two-thirds of the genotypes obtained and produce phased segments of up to 215 kb. We detect 226,529 intra-read indels, 5590 indels between mate-paired reads, 91 inversions, and four gene fusions. We use a novel approach for detecting indels between mate-paired reads that are smaller than the standard deviation of the insert size of the library and discover deletions in common with those detected with our intra-read approach. Dozens of mutations previously described in OMIM and hundreds of nonsynonymous single-nucleotide and structural variants in genes previously implicated in disease are identified in this individual. There is more genetic variation in the human genome still to be uncovered, and we provide guidance for future surveys in populations and cancer biopsies.

An Aboriginal Australian Genome Reveals Separate Human Dispersals into Asia

Whole-genome data indicate that early modern humans expanded into Australia 62,000 to 75,000 years ago. We present an Aboriginal Australian genomic sequence obtained from a 100-year-old lock of hair donated by an Aboriginal man from southern Western Australia in the early 20th century. We detect no evidence of European admixture and estimate contamination levels to be below 0.5%. We show that Aboriginal Australians are descendants of an early human dispersal into eastern Asia, possibly 62,000 to 75,000 years ago. This dispersal is separate from the one that gave rise to modern Asians 25,000 to 38,000 years ago. We also find evidence of gene flow between populations of the two dispersal waves prior to the divergence of Native Americans from modern Asian ancestors. Our findings support the hypothesis that present-day Aboriginal Australians descend from the earliest humans to occupy Australia, likely representing one of the oldest continuous populations outside Africa.

Development of Personalized Tumor Biomarkers Using Massively Parallel Sequencing

Rapid detection of specific aberrant rearrangements in tumors from individuals yields a well-poised technological advance toward personalized oncology. PARE Personalizes Cancer Genetics A diagnosis of cancer shatters the view of the world in an individual’s mind. A world that once moved as comfortably as the pace of one’s own life suddenly moves all too quickly. The individual starts asking questions and searching for possible remedies, and soon learns about the shockingly slow pace of successful cancer research. In the case of solid tumors, conventional surgical excision blanketed with “one size fits all” drug treatments simply fails to be universally effective in the long term. Cancer research has begun to shift to a more focused, personal approach that involves tailoring therapies directly to the complexity inherent in each individual—an area that holds considerable promise. But the differences among individuals are not the only layer of complexity hindering effective treatment. The intrinsic differences that accumulate over the course of tumor progression among similar tumor types hold the key to unlocking a truly personal remedy, a barcode, to cancer. Now, Leary et al. make use of a massively parallel sequencing technique—personalized analysis of rearranged ends (PARE)—to home in on the unique DNA rearrangements present in tumors that differ from the rearrangements present in nontumor DNA from a small subset of individuals. They provide evidence for a highly sensitive, reliable, and cost-effective method, a foundation from which the annotation of large numbers of such tumor signatures will yield a personal cancer code. In an arena that takes small steps, PARE offers a leap forward in the clinical management and treatment of solid tumors, revealing true biomarkers that enable monitoring of individual tumor progression, tailoring of response to therapeutic treatment, and identification of residual disease at a level previously undetectable by current methods. Clinical management of human cancer is dependent on the accurate monitoring of residual and recurrent tumors. The evaluation of patient-specific translocations in leukemias and lymphomas has revolutionized diagnostics for these diseases. We have developed a method, called personalized analysis of rearranged ends (PARE), which can identify translocations in solid tumors. Analysis of four colorectal and two breast cancers with massively parallel sequencing revealed an average of nine rearranged sequences (range, 4 to 15) per tumor. Polymerase chain reaction with primers spanning the breakpoints was able to detect mutant DNA molecules present at levels lower than 0.001% and readily identified mutated circulating DNA in patient plasma samples. This approach provides an exquisitely sensitive and broadly applicable approach for the development of personalized biomarkers to enhance the clinical management of cancer patients.

Ancestry Informative Marker Sets for Determining Continental Origin and Admixture Proportions in Common Populations in America

To provide a resource for assessing continental ancestry in a wide variety of genetic studies, we identified, validated, and characterized a set of 128 ancestry informative markers (AIMs). The markers were chosen for informativeness, genome‐wide distribution, and genotype reproducibility on two platforms (TaqMan® assays and Illumina arrays). We analyzed genotyping data from 825 subjects with diverse ancestry, including European, East Asian, Amerindian, African, South Asian, Mexican, and Puerto Rican. A comprehensive set of 128 AIMs and subsets as small as 24 AIMs are shown to be useful tools for ascertaining the origin of subjects from particular continents, and to correct for population stratification in admixed population sample sets. Our findings provide general guidelines for the application of specific AIM subsets as a resource for wide application. We conclude that investigators can use TaqMan assays for the selected AIMs as a simple and cost efficient tool to control for differences in continental ancestry when conducting association studies in ethnically diverse populations. Hum Mutat 0,1–10, 2008.

Genomics for the world

Medical genomics has focused almost entirely on those of European descent. Other ethnic groups must be studied to ensure that more people benefit, say Carlos D. Bustamante, Esteban Gonzalez Burchard and Francisco M. De La Vega.

Genome and Transcriptome Sequencing in Prospective Metastatic Triple-Negative Breast Cancer Uncovers Therapeutic Vulnerabilities

Triple-negative breast cancer (TNBC) is characterized by the absence of expression of estrogen receptor, progesterone receptor, and HER-2. Thirty percent of patients recur after first-line treatment, and metastatic TNBC (mTNBC) has a poor prognosis with median survival of one year. Here, we present initial analyses of whole genome and transcriptome sequencing data from 14 prospective mTNBC. We have cataloged the collection of somatic genomic alterations in these advanced tumors, particularly those that may inform targeted therapies. Genes mutated in multiple tumors included TP53, LRP1B, HERC1, CDH5, RB1, and NF1. Notable genes involved in focal structural events were CTNNA1, PTEN, FBXW7, BRCA2, WT1, FGFR1, KRAS, HRAS, ARAF, BRAF, and PGCP. Homozygous deletion of CTNNA1 was detected in 2 of 6 African Americans. RNA sequencing revealed consistent overexpression of the FOXM1 gene when tumor gene expression was compared with nonmalignant breast samples. Using an outlier analysis of gene expression comparing one cancer with all the others, we detected expression patterns unique to each patients tumor. Integrative DNA/RNA analysis provided evidence for deregulation of mutated genes, including the monoallelic expression of TP53 mutations. Finally, molecular alterations in several cancers supported targeted therapeutic intervention on clinical trials with known inhibitors, particularly for alterations in the RAS/RAF/MEK/ERK and PI3K/AKT/mTOR pathways. In conclusion, whole genome and transcriptome profiling of mTNBC have provided insights into somatic events occurring in this difficult to treat cancer. These genomic data have guided patients to investigational treatment trials and provide hypotheses for future trials in this irremediable cancer. Mol Cancer Ther; 12(1); 104–16. ©2012 AACR.

Analyses of a set of 128 ancestry informative single-nucleotide polymorphisms in a global set of 119 population samples

BackgroundUsing DNA to determine an individuals ancestry from among human populations is generally interesting and useful for many purposes, including admixture mapping, controlling for population structure in disease or trait association studies and forensic ancestry inference. However, to estimate ancestry, including possible admixture within an individual, as well as heterogeneity within a group of individuals, allele frequencies are necessary for what are believed to be the contributing populations. For this purpose, panels of ancestry informative markers (AIMs) have been developed.ResultsWe are presenting our work on one such panel, composed of 128 ancestry informative single-nucleotide polymorphisms (AISNPs) already proposed in the literature. Compared to previous studies of these AISNPs, we have studied three times the number of individuals (4,871) in three times as many population samples (119). We have validated this panel for many ancestry assignment and admixture studies, especially those that were the rationale for the original selection of the 128 SNPs: African Americans and Mexican Americans. At the same time, the limitations of the panel for distinguishing ancestry and quantifying admixture among Eurasian populations are noted.ConclusionWe demonstrate the simultaneous importance of the specific set of population samples and their relative sample sizes in the use of the structure program to determine which groups cluster together and consequently influence the ability of a marker panel to infer ancestry. We demonstrate the strengths and weaknesses of this particular panel of AISNPs in a global context.

An ancestry informative marker set for determining continental origin: validation and extension using human genome diversity panels

BackgroundCase-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia.ResultsIn this study, genotypes from Human Genome Diversity Panel populations were used to further evaluate a 93 SNP AIM panel, a subset of the 128 AIMS set, for distinguishing continental origins. Using both model-based and relatively model-independent methods, we here confirm the ability of this AIM set to distinguish diverse population groups that were not previously evaluated. This study included multiple population groups from Oceana, South Asia, East Asia, Sub-Saharan Africa, North and South America, and Europe. In addition, the 93 AIM set provides population substructure information that can, for example, distinguish Arab and Ashkenazi from Northern European population groups and Pygmy from other Sub-Saharan African population groups.ConclusionThese data provide additional support for using the 93 AIM set to efficiently identify continental subject groups for genetic studies, to identify study population outliers, and to control for admixture in association studies.

Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations

Due to growing throughput and shrinking cost, massively parallel sequencing is rapidly becoming an attractive alternative to microarrays for the genome-wide study of gene expression and copy number alterations in primary tumors. The sequencing of transcripts (RNA-Seq) should offer several advantages over microarray-based methods, including the ability to detect somatic mutations and accurately measure allele-specific expression. To investigate these advantages we have applied a novel, strand-specific RNA-Seq method to tumors and matched normal tissue from three patients with oral squamous cell carcinomas. Additionally, to better understand the genomic determinants of the gene expression changes observed, we have sequenced the tumor and normal genomes of one of these patients. We demonstrate here that our RNA-Seq method accurately measures allelic imbalance and that measurement on the genome-wide scale yields novel insights into cancer etiology. As expected, the set of genes differentially expressed in the tumors is enriched for cell adhesion and differentiation functions, but, unexpectedly, the set of allelically imbalanced genes is also enriched for these same cancer-related functions. By comparing the transcriptomic perturbations observed in one patient to his underlying normal and tumor genomes, we find that allelic imbalance in the tumor is associated with copy number mutations and that copy number mutations are, in turn, strongly associated with changes in transcript abundance. These results support a model in which allele-specific deletions and duplications drive allele-specific changes in gene expression in the developing tumor.