Detection and phasing of single base de novo mutations in biopsies from human in vitro fertilized embryos by advanced whole-genome sequencing.

Currently, the methods available for preimplantation genetic diagnosis (PGD) of in vitro fertilized (IVF) embryos do not detect de novo single-nucleotide and short indel mutations, which have been shown to cause a large fraction of genetic diseases. Detection of all these types of mutations requires whole-genome sequencing (WGS). In this study, advanced massively parallel WGS was performed on three 5- to 10-cell biopsies from two blastocyst-stage embryos. Both parents and paternal grandparents were also analyzed to allow for accurate measurements of false-positive and false-negative error rates. Overall, >95% of each genome was called. In the embryos, experimentally derived haplotypes and barcoded read data were used to detect and phase up to 82% of de novo single base mutations with a false-positive rate of about one error per Gb, resulting in fewer than 10 such errors per embryo. This represents a ∼ 100-fold lower error rate than previously published from 10 cells, and it is the first demonstration that advanced WGS can be used to accurately identify these de novo mutations in spite of the thousands of false-positive errors introduced by the extensive DNA amplification required for deep sequencing. Using haplotype information, we also demonstrate how small de novo deletions could be detected. These results suggest that phased WGS using barcoded DNA could be used in the future as part of the PGD process to maximize comprehensiveness in detecting disease-causing mutations and to reduce the incidence of genetic diseases.

Genomic alterations in gastric cancers discovered via whole-exome sequencing.

BACKGROUND: Gastric cancer (GC) ranks the second in mortality rate among all cancers. Metastases account for most of the deaths in GC patients. Yet our understanding of GC and its metastasis mechanism is still very limited. METHODS: We performed 20 whole-exome sequencing (WES) on 5 typical metastatic gastric adenocarcinoma (GAC) patients with lymph node metastasis. We compared both the primary tumors to their metastatic lymph nodes, and a specific analysis pipeline was used to detect single nucleotide variants (SNVs), small insertions/deletions (indels) and copy number variants (CNVs). RESULTS: (1) We confirmed 30 candidate mutations in both primary and lymph nodes tissues, and other 7 only in primary tumors. (2) Copy number gains were observed in a large section of 17q12-21, as well as copy number losses in regions containing CDKN2A and CDKN2B in both primary and lymph nodes tissues. CONCLUSIONS: Our results provide preliminary insights in the molecular mechanisms of GC initiation, development, and metastatic progression. These results need to be validated through large-scale studies.

Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells.

Recent advances in whole-genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, long fragment read (LFR) technology, which is similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ∼100 picograms of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants were assembled into long haplotype contigs. Removal of false positive single nucleotide variants not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10 megabases. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.

OTG-snpcaller: an optimized pipeline based on TMAP and GATK for SNP calling from ion torrent data.

Because the new Proton platform from Life Technologies produced markedly different data from those of the Illumina platform, the conventional Illumina data analysis pipeline could not be used directly. We developed an optimized SNP calling method using TMAP and GATK (OTG-snpcaller). This method combined our own optimized processes, Remove Duplicates According to AS Tag (RDAST) and Alignment Optimize Structure (AOS), together with TMAP and GATK, to call SNPs from Proton data. We sequenced four sets of exomes captured by Agilent SureSelect and NimbleGen SeqCap EZ Kit, using Life Technology's Ion Proton sequencer. Then we applied OTG-snpcaller and compared our results with the results from Torrent Variants Caller. The results indicated that OTG-snpcaller can reduce both false positive and false negative rates. Moreover, we compared our results with Illumina results generated by GATK best practices, and we found that the results of these two platforms were comparable. The good performance in variant calling using GATK best practices can be primarily attributed to the high quality of the Illumina sequences.

Identifying Human Genome-Wide CNV, LOH and UPD by Targeted Sequencing of Selected Regions.

Copy-number variations (CNV), loss of heterozygosity (LOH), and uniparental disomy (UPD) are large genomic aberrations leading to many common inherited diseases, cancers, and other complex diseases. An integrated tool to identify these aberrations is essential in understanding diseases and in designing clinical interventions. Previous discovery methods based on whole-genome sequencing (WGS) require very high depth of coverage on the whole genome scale, and are cost-wise inefficient. Another approach, whole exome genome sequencing (WEGS), is limited to discovering variations within exons. Thus, we are lacking efficient methods to detect genomic aberrations on the whole genome scale using next-generation sequencing technology. Here we present a method to identify genome-wide CNV, LOH and UPD for the human genome via selectively sequencing a small portion of genome termed Selected Target Regions (SeTRs). In our experiments, the SeTRs are covered by 99.73%~99.95% with sufficient depth. Our developed bioinformatics pipeline calls genome-wide CNVs with high confidence, revealing 8 credible events of LOH and 3 UPD events larger than 5M from 15 individual samples. We demonstrate that genome-wide CNV, LOH and UPD can be detected using a cost-effective SeTRs sequencing approach, and that LOH and UPD can be identified using just a sample grouping technique, without using a matched sample or familial information.

IGFL: A secreted family with conserved cysteine residues and similarities to the IGF superfamily.

We have discovered a family of small secreted proteins in Homo sapiens and Mus musculus. The IGF-like (IGFL) genes encode proteins of approximately 100 amino acids that contain 11 conserved cysteine residues at fixed positions, including two CC motifs. In H. sapiens, the family is composed of four genes and two pseudogenes that are referred as IGFL1 to IGFL4 and IGFL1P1 and IGFL1P2, respectively. Human IGFL genes are clustered together on chromosome 19 within a 35-kb interval. M. musculus has a single IGFL family member that is located on chromosome 7. Further, evolutionary analysis shows a lack of direct orthology between any of the four human members and the mouse gene. This relationship between the mouse and the human family members suggests that the multiple members in the human complement have arisen from recent duplication events that appear limited to the primate lineage. Structural considerations and sequence comparisons would suggest that IGFL proteins are distantly related to the IGF superfamily of growth factors. IGFL mRNAs display specific expression patterns; they are expressed in fetal tissues, breast, and prostate, and in many cancers as well, and this pattern is consistent with that of the IGF family members.

PAQR proteins: a novel membrane receptor family defined by an ancient 7-transmembrane pass motif.

An emerging series of papers has identified new receptor proteins that predict seven-transmembrane pass topologies. We have consolidated this family to 11 human genes and have named the family PAQR, after two of the initially described ligands (progestin and adipoQ receptors). This protein family has ancient evolutionary roots, with identified homologs found in eubacteria. To date, published data indicate that the prokaryotic members of this family appear to encode hemolysin-type proteins, while in eukaryotes, PAQR proteins encode functional receptors with a broad range of apparent ligand specificities. We provide the complete human and mouse complement of this family, suggest a conserved structure/topology with invariant intracellular amino acid residues, and have measured mRNA expression levels for these genes across a range of human tissues.