Estimation of intrafamilial DNA contamination in family trio genome sequencing using deviation from Mendelian inheritance.

With the increasing number of sequencing projects involving families, quality control tools optimized for family genome sequencing are needed. However, accurately quantifying contamination in a DNA mixture is particularly difficult when genetically related family members are the sources. We developed TrioMix, a maximum likelihood estimation (MLE) framework based on Mendel's law of inheritance, to quantify DNA mixture between family members in genome sequencing data of parent-offspring trios. TrioMix can accurately deconvolute any intrafamilial DNA contamination, including parent-offspring, sibling-sibling, parent-parent, and even multiple familial sources. In addition, TrioMix can be applied to detect genomic abnormalities that deviate from Mendelian inheritance patterns, such as uniparental disomy (UPD) and chimerism. A genome-wide depth and variant allele frequency plot generated by TrioMix facilitates tracing the origin of Mendelian inheritance deviations. We showed that TrioMix could accurately deconvolute genomes in both simulated and real data sets.

Genome-wide functional analysis using the barcode sequence alignment and statistical analysis (Barcas) tool.

BACKGROUND: Pooled library screen analysis using shRNAs or CRISPR-Cas9 hold great promise to genome-wide functional studies. While pooled library screens are effective tools, erroneous barcodes can potentially be generated during the production of many barcodes. However, no current tools can distinguish erroneous barcodes from PCR or sequencing errors in a data preprocessing step. RESULTS: We developed the Barcas program, a specialized program for the mapping and analysis of multiplexed barcode sequencing (barcode-seq) data. For fast and efficient mapping, Barcas uses a trie data structure based imperfect matching algorithm which generates precise mapping results containing mismatches, shifts, insertions and deletions (indel) in a flexible manner. Barcas provides three functions for quality control (QC) of a barcode library and distinguishes erroneous barcodes from PCR or sequencing errors. It also provides useful functions for data analysis and visualization. CONCLUSIONS: Barcas is an all-in-one package providing useful functions including mapping, data QC, library QC, statistical analysis and visualization in genome-wide pooled screens.

A guide for bioinformaticians: 'omics-based drug discovery for precision oncology.

Bioinformatics-centric drug development is inevitable in the era of precision medicine. Clinical 'omics information, including genomics, epigenomics, transcriptomics, and proteomics, provides the most comprehensive molecular landscape in which each patient's pathological history is delineated. Hence, the capability of bioinformaticians to manage integrative 'omics data is crucial to current drug development. Bioinformatics can accelerate drug development from initial time-consuming discoveries to the clinical stage by providing information-guided solutions. However, many bioinformaticians do not have opportunities to participate in drug discovery programs. As a starting point for bioinformaticians with no prior drug development experience, here we discuss bioinformatics applications during drug development with a focus on working-level omics-based methodologies.

Intrinsic Molecular Processes: Impact on Mutagenesis.

Mutations provide resources for genome evolution by generating genetic variability. In addition, mutations act as a driving force leading to disease pathogenesis, and thus have important implications for disease diagnosis, prognosis, and treatment. Understanding the mechanisms underlying how mutations occur is therefore of prime importance for elucidating evolutionary and pathogenic processes. Recent genomics studies have revealed that mutations occur non-randomly across the human genome. In particular, the distribution of mutations is highly associated with intrinsic molecular processes including transcription, chromatin organization, DNA replication timing, and DNA repair. Interplay between intrinsic processes and extrinsic mutagenic exposure may thus imprint a characteristic mutational landscape on tumors. We discuss the impact of intrinsic molecular processes on mutation acquisition in cancer.

Variability in Chromatin Architecture and Associated DNA Repair at Genomic Positions Containing Somatic Mutations.

Dynamic chromatin structures result in differential chemical reactivity to mutational processes throughout the genome. To identify chromatin features responsible for mutagenesis, we compared chromatin architecture around single-nucleotide variants (SNV), insertion/deletions (indels), and their context-matched, nonmutated positions. We found epigenetic differences between genomic regions containing missense SNVs and those containing frameshift indels across multiple cancer types. Levels of active histone marks were higher around frameshift indels than around missense SNV, whereas repressive histone marks exhibited the reverse trend. Accumulation of repressive histone marks and nucleosomes distinguished mutated positions (both SNV and indels) from the context-matched, nonmutated positions, whereas active marks were associated with substitution- and cancer type-specific mutagenesis. We also explained mutagenesis based on genome maintenance mechanisms, including nucleotide excision repair (NER), mismatch repair (MMR), and DNA polymerase epsilon (POLE). Regional NER variation correlated strongly with chromatin features; NER machineries exhibited shifted or depleted binding around SNV, resulting in decreased NER at mutation positions, especially at sites of recurrent mutations. MMR-deficient tumors selectively acquired SNV in regions with high active histone marks, especially H3K36me3, whereas POLE-deficient tumors selectively acquired indels and SNV in regions with low active histone marks. These findings demonstrate the importance of fine-scaled chromatin structures and associated DNA repair mechanisms in mutagenesis. Cancer Res; 77(11); 2822-33. ©2017 AACR.

Genome-wide mutation profiles of colorectal tumors and associated liver metastases at the exome and transcriptome levels.

To characterize the mutation profiles of colorectal cancer (CRC) primary tumors (PTs) and liver metastases (CLMs), we performed both whole-exome and RNA sequencing. Ten significantly mutated genes, including BMI1, CARD11, and NRG1, were found in 34 CRCs with CLMs. We defined three mutation classes (Class 1 to 3) based on the absence or presence of mutations during liver metastasis. Most mutations were classified into Class 1 (shared between PTs and CLMs), suggesting the common clonal origin of PTs and CLMs. Class 1 was more strongly associated with the clinical characteristics of advanced cancer and was more frequently superimposed with chromosomal deletions in CLMs than Class 2 (PT-specific). The integration of exome and RNA sequencing revealed that variant-allele frequencies (VAFs) of mutations in the transcriptome tended to have stronger functional implications than those in the exome. For instance, VAFs of the TP53 and APC mutations in the transcriptome significantly correlated with the expression level of their target genes. Additionally, mutations with high functional impact were enriched with high VAFs in the CLM transcriptomes. We identified 11 mutation-associated splicing events in the CRC transcriptomes. Thus, the integration of the exome and the transcriptome may elucidate the underlying molecular events responsible for CLMs.