Molecular defects identified by whole exome sequencing in a child with Fanconi anemia

Fanconi anemia is a rare genetic disease characterized by bone marrow failure, multiple congenital malformations, and an increased susceptibility to malignancy. At least 15 genes have been identified that are involved in the pathogenesis of Fanconi anemia. However, it is still a challenge to assign the complementation group and to characterize the molecular defects in patients with Fanconi anemia. In the current study, whole exome sequencing was used to identify the affected gene(s) in a boy with Fanconi anemia. A recurring, non-synonymous mutation was found (c.3971C>T, p.P1324L) as well as a novel frameshift mutation (c.989_995del, p.H330LfsX2) in FANCA gene. Our results indicate that whole exome sequencing may be useful in clinical settings for rapid identification of disease-causing mutations in rare genetic disorders such as Fanconi anemia.     

Telomere length alterations in microsatellite stable colorectal cancer and association with the immune response

Telomeres are repetitive sequences (TTAGGG) located at the end of chromosomes. Telomeres progressively shorten with each cell replication cycle, ultimately leading to chromosomal instability and loss of cell viability. Telomere length anomaly appears to be one of the earliest and most prevalent genetic alterations in malignant transformation. Here we aim to estimate telomere length from whole-exome sequencing data in colon tumors and normal colonic mucosa, and to analyze the potential association of telomere length with clinical factors and gene expression in colon cancer.Reads containing at least five repetitions of the telomere sequence (TTAGGG) were extracted from the raw sequences of 42 adjacent normal-tumor paired samples. The number of reads from the tumor sample was normalized to build the Tumor Telomere Length Ratio (TTLR), considered an estimation of telomere length change in the tumor compared to the paired normal tissue. We evaluated the associations between TTLR and clinical factors, gene expression and copy number (CN) aberrations measured in the same tumor samples.Colon tumors showed significantly shorter telomeres than their paired normal samples. No significant association was observed between TTLR and gender, age, tumor location, prognosis, stromal infiltration or molecular subtypes. The functional gene set enrichment analysis showed pathways related to immune response significantly associated with TLLR.By extracting a relative measure of telomere length from whole-exome sequencing data, we have assessed that colon tumor cells predominantly shorten telomeres, and this alteration is associated with expression changes in genes related to immune response and inflammation in tumor cells.     

Performance comparison of four exome capture systems for deep sequencing

Background

Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen’s SeqCap EZ v3.0, Agilent’s SureSelect v4.0, Illumina’s TruSeq Exome, and Illumina’s Nextera Exome, all applied to the same human tumor DNA sample.

Results

Each capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content.

Conclusions

We show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-449) contains supplementary material, which is available to authorized users.     

Tissue-specific temporal exome capture revealed muscle-specific genes and SNPs in Indian buffalo (Bubalus bubalis)

Whole genome sequencing of buffalo is yet to be completed,and in the near future it may not be possible to identify an exome(coding region of genome) through bioinformatics for designing probes to capture it.In the present study,we employed in solution hybridization to sequence tissue specific temporal exomes(TST exome) in buffalo.We utilized cDNA prepared from buffalo muscle tissue as a probe to capture TST exomes from the buffalo genome.This resulted in a prominent reduction of repeat sequences(up to 40%) and an enrichment of coding sequences(up to 60%).Enriched targets were sequenced on a 454 pyro-sequencing platform,generating 101,244 reads containing 24,127,779 high quality bases.The data revealed 40,100 variations,of which 403 were indels and 39,218 SNPs containing 195 nonsynonymous candidate SNPs in protein-coding regions.The study has indicated that 80% of the total genes identified from capture data were expressed in muscle tissue.The present study is the first of its kind to sequence TST exomes captured by use of cDNA molecules for SNPs found in the coding region without any prior sequence information of targeted molecules.     

Exome‐based proteogenomics of HEK‐293 human cell line: Coding genomic variants identified at the level of shotgun proteome

Genomic and proteomic data were integrated into the proteogenomic workflow to identify coding genomic variants of Human Embryonic Kidney 293 (HEK‐293) cell line at the proteome level. Shotgun proteome data published by Geiger et al. (2012), Chick et al. (2015), and obtained in this work for HEK‐293 were searched against the customized genomic database generated using exome data published by Lin et al. (2014). Overall, 112 unique variants were identified at the proteome level out of ～1200 coding variants annotated in the exome. Seven identified variants were shared between all the three considered proteomic datasets, and 27 variants were found in any two datasets. Some of the found variants belonged to widely known genomic polymorphisms originated from the germline, while the others were more likely resulting from somatic mutations. At least, eight of the proteins bearing amino acid variants were annotated as cancer‐related ones, including p53 tumor suppressor. In all the considered shotgun datasets, the variant peptides were at the ratio of 1:2.5 less likely being identified than the wild‐type ones compared with the corresponding theoretical peptides. This can be explained by the presence of the so‐called “passenger” mutations in the genes, which were never expressed in HEK‐293 cells. All MS data have been deposited in the ProteomeXchange with the dataset identifier PXD002613 ( http://proteomecentral.proteomexchange.org/dataset/PXD002613 ).     

Lessons in biology from patients with inborn errors of vitamin B12 metabolism

Background

Since 1975 cells lines from patients with suspected inborn errors of vitamin B₁₂ metabolism have been referred to our laboratory because of elevations of homocysteine, methylmalonic acid, or both.

Design

Cultured fibroblasts from patients were subjected to a battery of tests: incorporation of labelled propionate and methyltetrahydrofolate into cellular macromolecules, to test the functional integrity of methylmalonyl-CoA mutase and methionine synthase, respectively; uptake of labelled cyanocobalamin and synthesis of adenosylcobalamin and methylcobalamin; and, where applicable, complementation analysis.

Results

This approach has allowed for the discovery of novel steps in the cellular transport and metabolism of vitamin B₁₂, including those involving cellular uptake, the efflux of vitamin B₁₂ from lysosomes, and the synthesis of adenosylcobalamin and methylcobalamin. For all of these disorders, the responsible genes have been discovered.

Conclusion

The study of highly selected patients with suspected inborn errors of metabolism has consistently resulted in the discovery of previously unknown metabolic steps and has provided new lessons in biology.     

Exome sequencing reveals genetic architecture in patients with isolated or syndromic short stature

Short stature is among the most common endocrinological disease phenotypes of childhood and may occur as an isolated finding or in conjunction with other clinical manifestations. Although the diagnostic utility of clinical genetic testing in short stature has been implicated, the genetic architecture and the utility of genomic studies such as exome sequencing(ES) in a sizable cohort of patients with short stature have not been investigated systematically. In this study, we recruited 561 individuals with short stature from two centers in China during a 4-year period. We performed ES for all patients and available parents. All patients were retrospectively divided into two groups: an isolated short stature group(group I, n = 257) and an apparently syndromic short stature group(group II, n = 304). Causal variants were identified in 135 of 561(24.1%) patients. In group I, 29 of 257(11.3%) of the patients were solved by variants in 24 genes. In group II, 106 of 304(34.9%) patients were solved by variants in 57 genes. Genes involved in fundamental cellularprocess played an important role in the genetic architecture of syndromic short stature. Distinct genetic architectures and pathophysiological processes underlie isolated and syndromic short stature.     

Comparison and evaluation of two exome capture kits and sequencing platforms for variant calling

Background

To promote the clinical application of next-generation sequencing, it is important to obtain accurate and consistent variants of target genomic regions at low cost. Ion Proton, the latest updated semiconductor-based sequencing instrument from Life Technologies, is designed to provide investigators with an inexpensive platform for human whole exome sequencing that achieves a rapid turnaround time. However, few studies have comprehensively compared and evaluated the accuracy of variant calling between Ion Proton and Illumina sequencing platforms such as HiSeq 2000, which is the most popular sequencing platform for the human genome. The Ion Proton sequencer combined with the Ion TargetSeq™ Exome Enrichment Kit together make up TargetSeq-Proton, whereas SureSelect-Hiseq is based on the Agilent SureSelect Human All Exon v4 Kit and the HiSeq 2000 sequencer.

Results

Here, we sequenced exonic DNA from four human blood samples using both TargetSeq-Proton and SureSelect-HiSeq. We then called variants in the exonic regions that overlapped between the two exome capture kits (33.6 Mb). The rates of shared variant loci called by two sequencing platforms were from 68.0 to 75.3 % in four samples, whereas the concordance of co-detected variant loci reached 99 %. Sanger sequencing validation revealed that the validated rate of concordant single nucleotide polymorphisms (SNPs) (91.5 %) was higher than the SNPs specific to TargetSeq-Proton (60.0 %) or specific to SureSelect-HiSeq (88.3 %). With regard to 1-bp small insertions and deletions (InDels), the Sanger sequencing validated rates of concordant variants (100.0 %) and SureSelect-HiSeq-specific (89.6 %) were higher than those of TargetSeq-Proton-specific (15.8 %).

Conclusions

In the sequencing of exonic regions, a combination of using of two sequencing strategies (SureSelect-HiSeq and TargetSeq-Proton) increased the variant calling specificity for concordant variant loci and the sensitivity for variant loci called by any one platform. However, for the sequencing of platform-specific variants, the accuracy of variant calling by HiSeq 2000 was higher than that of Ion Proton, specifically for the InDel detection. Moreover, the variant calling software also influences the detection of SNPs and, specifically, InDels in Ion Proton exome sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1796-6) contains supplementary material, which is available to authorized users.     

Exome sequencing and targeted gene panels: a simulated comparison of diagnostic yield using data from 158 patients with rare diseases

Next-generation sequencing (NGS) has altered clinical genetic testing by widening the access to molecular diagnosis of genetically determined rare diseases. However, physicians may face difficulties selecting the best diagnostic approach. Our goal is to estimate the rate of possible molecular diagnoses missed by different targeted gene panels using data from a cohort of patients with rare genetic diseases diagnosed with exome sequencing (ES). For this purpose, we simulated a comparison between different targeted gene panels and ES: the list of genes harboring clinically relevant variants from 158 patients was used to estimate the theoretical rate of diagnoses missed by NGS panels from 53 different NGS panels from eight different laboratories. Panels presented a mean rate of missed diagnoses of 64% (range 14%-100%) compared to ES, representing an average predicted sensitivity of 36%. Metabolic abnormalities represented the group with highest mean of missed diagnoses (86%), while seizure represented the group with lowest mean (46%). Focused gene panels are restricted in covering select sets of genes implicated in specific diseases and they may miss molecular diagnoses of rare diseases compared to ES. However, their role in genetic diagnosis remains important especially for well-known genetic diseases with established genetic locus heterogeneity.