Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. Here, we performed high-resolution copy-number analysis on 125 HCC tumors and whole-exome sequencing on 24 of these tumors. We identified 135 homozygous deletions and 994 somatic mutations of genes with predicted functional consequences. We found new recurrent alterations in four genes (ARID1A, RPS6KA3, NFE2L2 and IRF2) not previously described in HCC. Functional analyses showed tumor suppressor properties for IRF2, whose inactivation, exclusively found in hepatitis B virus (HBV)-related tumors, led to impaired TP53 function. In contrast, inactivation of chromatin remodelers was frequent and predominant in alcohol-related tumors. Moreover, association of mutations in specific genes (RPS6KA3-AXIN1 and NFE2L2-CTNNB1) suggested that Wnt/β-catenin signaling might cooperate in liver carcinogenesis with both oxidative stress metabolism and Ras/mitogen-activated protein kinase (MAPK) pathways. This study provides insight into the somatic mutational landscape in HCC and identifies interactions between mutations in oncogene and tumor suppressor gene mutations related to specific risk factors.     

Assembly of microarrays for genome-wide measurement of DNA copy number.

We have assembled arrays of approximately 2,400 BAC clones for measurement of DNA copy number across the human genome. The arrays provide precise measurement (s.d. of log2 ratios=0.05-0.10) in cell lines and clinical material, so that we can reliably detect and quantify high-level amplifications and single-copy alterations in diploid, polyploid and heterogeneous backgrounds.     

Genome-wide genetic changes during modern breeding of maize

The success of modern maize breeding has been demonstrated by remarkable increases in productivity over the last four decades. However, the underlying genetic changes correlated with these gains remain largely unknown. We report here the sequencing of 278 temperate maize inbred lines from different stages of breeding history, including deep resequencing of 4 lines with known pedigree information. The results show that modern breeding has introduced highly dynamic genetic changes into the maize genome. Artificial selection has affected thousands of targets, including genes and non-genic regions, leading to a reduction in nucleotide diversity and an increase in the proportion of rare alleles. Genetic changes during breeding happen rapidly, with extensive variation (SNPs, indels and copy-number variants (CNVs)) occurring, even within identity-by-descent regions. Our genome-wide assessment of genetic changes during modern maize breeding provides new strategies as well as practical targets for future crop breeding and biotechnology.     

Identifying distinct classes of bladder carcinoma using microarrays

Bladder cancer is a common malignant disease characterized by frequent recurrences. The stage of disease at diagnosis and the presence of surrounding carcinoma in situ are important in determining the disease course of an affected individual. Despite considerable effort, no accepted immunohistological or molecular markers have been identified to define clinically relevant subsets of bladder cancer. Here we report the identification of clinically relevant subclasses of bladder carcinoma using expression microarray analysis of 40 well characterized bladder tumors. Hierarchical cluster analysis identified three major stages, Ta, T1 and T2-4, with the Ta tumors further classified into subgroups. We built a 32-gene molecular classifier using a cross-validation approach that was able to classify benign and muscle-invasive tumors with close correlation to pathological staging in an independent test set of 68 tumors. The classifier provided new predictive information on disease progression in Ta tumors compared with conventional staging (P < 0.005). To delineate non-recurring Ta tumors from frequently recurring Ta tumors, we analyzed expression patterns in 31 tumors by applying a supervised learning classification methodology, which classified 75% of the samples correctly (P < 0.006). Furthermore, gene expression profiles characterizing each stage and subtype identified their biological properties, producing new potential targets for therapy.     

Mining the human genome using microarrays of open reading frames

To test the hypothesis that the human genome project will uncover many genes not previously discovered by sequencing of expressed sequence tags (ESTs), we designed and produced a set of microarrays using probes based on open reading frames (ORFs) in 350 Mb of finished and draft human sequence. Our approach aims to identify all genes directly from genomic sequence by querying gene expression. We analysed genomic sequence with a suite of ORF prediction programs, selected approximately one ORF per gene, amplified the ORFs from genomic DNA and arrayed the amplicons onto treated glass slides. Of the first 10,000 arrayed ORFs, 31% are completely novel and 29% are similar, but not identical, to sequences in public databases. Approximately one-half of these are expressed in the tissues we queried by microarray. Subsequent verification by other techniques confirmed expression of several of the novel genes. Expressed sequence tags (ESTs) have yielded vast amounts of data, but our results indicate that many genes in the human genome will only be found by genomic sequencing.     

Genome-wide analysis of single-nucleotide polymorphisms in human expressed sequences

Single-nucleotide polymorphisms (SNPs) have been explored as a high-resolution marker set for accelerating the mapping of disease genes. Here we report 48,196 candidate SNPs detected by statistical analysis of human expressed sequence tags (ESTs), associated primarily with coding regions of genes. We used Bayesian inference to weigh evidence for true polymorphism versus sequencing error, misalignment or ambiguity, misclustering or chimaeric EST sequences, assessing data such as raw chromatogram height, sharpness, overlap and spacing, sequencing error rates, context-sensitivity and cDNA library origin. Three separate validations-comparison with 54 genes screened for SNPs independently, verification of HLA-A polymorphisms and restriction fragment length polymorphism (RFLP) testing-verified 70%, 89% and 71% of our predicted SNPs, respectively. Our method detects tenfold more true HLA-A SNPs than previous analyses of the EST data. We found SNPs in a large fraction of known disease genes, including some disease-causing mutations (for example, the HbS sickle-cell mutation). Our comprehensive analysis of human coding region polymorphism provides a public resource for mapping of disease genes (available at http://www.bioinformatics.ucla.edu/snp).     

Genome-wide functional analysis of pathogenicity genes in the rice blast fungus

Rapid translation of genome sequences into meaningful biological information hinges on the integration of multiple experimental and informatics methods into a cohesive platform. Despite the explosion in the number of genome sequences available, such a platform does not exist for filamentous fungi. Here we present the development and application of a functional genomics and informatics platform for a model plant pathogenic fungus, Magnaporthe oryzae. In total, we produced 21,070 mutants through large-scale insertional mutagenesis using Agrobacterium tumefaciens-mediated transformation. We used a high-throughput phenotype screening pipeline to detect disruption of seven phenotypes encompassing the fungal life cycle and identified the mutated gene and the nature of mutation for each mutant. Comparative analysis of phenotypes and genotypes of the mutants uncovered 202 new pathogenicity loci. Our findings demonstrate the effectiveness of our platform and provide new insights on the molecular basis of fungal pathogenesis. Our approach promises comprehensive functional genomics in filamentous fungi and beyond.     

Epigenome analyses using BAC microarrays identify evolutionary conservation of tissue-specific methylation of SHANK3

CpG islands are present in one-half of all human and mouse genes and typically overlap with promoters or exons. We developed a method for high-resolution analysis of the methylation status of CpG islands genome-wide, using arrays of BAC clones and the methylation-sensitive restriction enzyme NotI. Here we demonstrate the accuracy and specificity of the method. By computationally mapping all NotI sites, methylation events can be defined with single-nucleotide precision throughout the genome. We also demonstrate the unique expandability of the array method using a different methylation-sensitive restriction enzyme, BssHII. We identified and validated new CpG island loci that are methylated in a tissue-specific manner in normal human tissues. The methylation status of the CpG islands is associated with gene expression for several genes, including SHANK3, which encodes a structural protein in neuronal postsynaptic densities. Defects in SHANK3 seem to underlie human 22q13 deletion syndrome. Furthermore, these patterns for SHANK3 are conserved in mice and rats.     

Large scale cDNA sequencing for analysis of quantitative and qualitative aspects of gene expression.

Large scale sequencing of cDNAs provides a complementary approach to structural analysis of the human genome by generating expressed sequence tags (ESTs). We have initiated the large-scale sequencing of a 3'-directed cDNA library from the human liver cell line HepG2, that is a non-biased representation of the mRNA population. 982 random cDNA clones were sequenced yielding more than 270 kilobases. A significant portion of the identified genes encoded secretable proteins and components for protein-synthesis. The abundance of cDNA species varied from 2.2% to less than 0.004%. Fifty two percent of the mRNA were abundant species consisting of 173 genes and the rest were non-abundant, consisting of about 6,600 genes.     

Estimate of human gene number provided by genome-wide analysis using Tetraodon nigroviridis DNA sequence

The number of genes in the human genome is unknown, with estimates ranging from 50,000 to 90,000 (refs 1, 2), and to more than 140,000 according to unpublished sources. We have developed 'Exofish', a procedure based on homology searches, to identify human genes quickly and reliably. This method relies on the sequence of another vertebrate, the pufferfish Tetraodon nigroviridis, to detect conserved sequences with a very low background. Similar to Fugu rubripes, a marine pufferfish proposed by Brenner et al. as a model for genomic studies, T. nigroviridis is a more practical alternative with a genome also eight times more compact than that of human. Many comparisons have been made between F. rubripes and human DNA that demonstrate the potential of comparative genomics using the pufferfish genome. Application of Exofish to the December version of the working draft sequence of the human genome and to Unigene showed that the human genome contains 28,000-34,000 genes, and that Unigene contains less than 40% of the protein-coding fraction of the human genome.     

Molecular analysis of the muscle pathology associated with mitochondrial DNA deletions.

Large-scale deletions of mitochondrial DNA (mtDNA) are associated with a subgroup of mitochondrial encephalomyopathies. We studied seven patients with Kearns-Sayre syndrome or isolated ocular myopathy who harboured a sub-population of partially-deleted mitochondrial genomes in skeletal muscle. Variable cytochrome c oxidase (COX) deficiencies and reduction of mitochondrially-encoded polypeptides were found in affected muscle fibres, but while many COX-deficient fibres had increased levels of mutant mtDNA, they almost invariably had reduced levels of normal mtDNA. Our results suggest that a specific ratio between mutant and wild-type mitochondrial genomes is the most important determinant of a focal respiratory chain deficiency, even though absolute copy numbers may vary widely.     

Merlin--rapid analysis of dense genetic maps using sparse gene flow trees.

Efforts to find disease genes using high-density single-nucleotide polymorphism (SNP) maps will produce data sets that exceed the limitations of current computational tools. Here we describe a new, efficient method for the analysis of dense genetic maps in pedigree data that provides extremely fast solutions to common problems such as allele-sharing analyses and haplotyping. We show that sparse binary trees represent patterns of gene flow in general pedigrees in a parsimonious manner, and derive a family of related algorithms for pedigree traversal. With these trees, exact likelihood calculations can be carried out efficiently for single markers or for multiple linked markers. Using an approximate multipoint calculation that ignores the unlikely possibility of a large number of recombinants further improves speed and provides accurate solutions in dense maps with thousands of markers. Our multipoint engine for rapid likelihood inference (Merlin) is a computer program that uses sparse inheritance trees for pedigree analysis; it performs rapid haplotyping, genotype error detection and affected pair linkage analyses and can handle more markers than other pedigree analysis packages.     

Exclusion of DNA changes in the beta-subunit of the c-GMP phosphodiesterase gene as the cause for Huntington's disease.

To identify expressed sequences within candidate regions for the Huntington's disease (HD) gene in 4p16.3, we isolated the gene encoding the beta subunit of the human cGMP phosphodiesterase (PDEB). We formally assessed this as a candidate gene for HD based on it's expression in brain, the demonstration of linkage disequilibrium between intragenic DNA markers and HD, and the demonstration that mice with a mutation in this gene have a reduction of neurons in particular brain regions. We investigated all 22 exons of PDEB and 5'-flanking region for point mutations in 16 HD patients of different ethnic origins using single strand conformational polymorphism analysis. The underlying DNA changes found initially exclusively in HD patients were excluded as the cause for HD.