Dominant-negative variants in CBX1 cause a neurodevelopmental disorder.

PURPOSE: This study aimed to establish variants in CBX1, encoding heterochromatin protein 1ß (HP1ß), as a cause of a novel syndromic neurodevelopmental disorder. METHODS: Patients with CBX1 variants were identified, and clinician researchers were connected using GeneMatcher and physician referrals. Clinical histories were collected from each patient. To investigate the pathogenicity of identified variants, we performed in vitro cellular assays and neurobehavioral and cytological analyses of neuronal cells obtained from newly generated Cbx1 mutant mouse lines. RESULTS: In 3 unrelated individuals with developmental delay, hypotonia, and autistic features, we identified heterozygous de novo variants in CBX1. The identified variants were in the chromodomain, the functional domain of HP1ß, which mediates interactions with chromatin. Cbx1 chromodomain mutant mice displayed increased latency-to-peak response, suggesting the possibility of synaptic delay or myelination deficits. Cytological and chromatin immunoprecipitation experiments confirmed the reduction of mutant HP1ß binding to heterochromatin, whereas HP1ß interactome analysis demonstrated that the majority of HP1ß-interacting proteins remained unchanged between the wild-type and mutant HP1ß. CONCLUSION: These collective findings confirm the role of CBX1 in developmental disabilities through the disruption of HP1ß chromatin binding during neurocognitive development. Because HP1ß forms homodimers and heterodimers, mutant HP1ß likely sequesters wild-type HP1ß and other HP1 proteins, exerting dominant-negative effects.

Comprehensive Gene Panel Testing for Hearing Loss in Children: Understanding Factors Influencing Diagnostic Yield.

OBJECTIVE: To evaluate factors influencing the diagnostic yield of comprehensive gene panel testing (CGPT) for hearing loss (HL) in children and to understand the characteristics of undiagnosed probands. STUDY DESIGN: This was a retrospective cohort study of 474 probands with childhood-onset HL who underwent CGPT between 2016 and 2020 at a single center. Main outcomes and measures included the association between clinical variables and diagnostic yield and the genetic and clinical characteristics of undiagnosed probands. RESULTS: The overall diagnostic yield was 44% (209/474) with causative variants involving 41 genes. While the diagnostic yield was high in the probands with congenital, bilateral, and severe HL, it was low in those with unilateral, noncongenital, or mild HL; cochlear nerve deficiency; preterm birth; neonatal intensive care unit admittance; certain ancestry; and developmental delay. Follow-up studies on 49 probands with initially inconclusive CGPT results changed the diagnostic status to likely positive or negative outcomes in 39 of them (80%). Reflex to exome sequencing on 128 undiagnosed probands by CGPT revealed diagnostic findings in 8 individuals, 5 of whom had developmental delays. The remaining 255 probands were undiagnosed, with 173 (173/255) having only a single variant in the gene(s) associated with autosomal recessive HL and 28% (48/173) having a matched phenotype. CONCLUSION: CGPT efficiently identifies the genetic etiologies of HL in children. CGPT-undiagnosed probands may benefit from follow-up studies or expanded testing.

Advanced approach for comprehensive mtDNA genome testing in mitochondrial disease.

Mitochondrial disease diagnosis requires interrogation of both nuclear and mitochondrial (mtDNA) genomes for single-nucleotide variants (SNVs) and copy number alterations, both in the proband and often maternal relatives, together with careful phenotype correlation. We developed a comprehensive mtDNA sequencing test ('MitoGenome') using long-range PCR (LR-PCR) to amplify the full length of the mtDNA genome followed by next generation sequencing (NGS) to accurately detect SNVs and large-scale mtDNA deletions (LSMD), combined with droplet digital PCR (ddPCR) for LSMD heteroplasmy quantification. Overall, MitoGenome tests were performed on 428 samples from 394 patients with suspected or confirmed mitochondrial disease. The positive yield was 11% (43/394), including 34 patients with pathogenic or likely pathogenic SNVs (the most common being m.3243A > G in 8/34 (24%) patients), 8 patients with single LSMD, and 3 patients with multiple LSMD exceeding 10% heteroplasmy levels. Two patients with both LSMD and pathogenic SNV were detected. Overall, this LR-PCR/NGS assay provides a highly accurate and comprehensive diagnostic method for simultaneous mtDNA SNV detection at heteroplasmy levels as low as 1% and LSMD detection at heteroplasmy levels below 10%. Inclusion of maternal samples for variant classification and ddPCR to quantify LSMD heteroplasmy levels further enables accurate pathogenicity assessment and clinical correlation interpretation of mtDNA genome sequence variants and copy number alterations.

Specifications of the ACMG/AMP standards and guidelines for mitochondrial DNA variant interpretation.

Mitochondrial DNA (mtDNA) variant pathogenicity interpretation has special considerations given unique features of the mtDNA genome, including maternal inheritance, variant heteroplasmy, threshold effect, absence of splicing, and contextual effects of haplogroups. Currently, there are insufficient standardized criteria for mtDNA variant assessment, which leads to inconsistencies in clinical variant pathogenicity reporting. An international working group of mtDNA experts was assembled within the Mitochondrial Disease Sequence Data Resource Consortium and obtained Expert Panel status from ClinGen. This group reviewed the 2015 American College of Medical Genetics and Association of Molecular Pathology standards and guidelines that are widely used for clinical interpretation of DNA sequence variants and provided further specifications for additional and specific guidance related to mtDNA variant classification. These Expert Panel consensus specifications allow for consistent consideration of the unique aspects of the mtDNA genome that directly influence variant assessment, including addressing mtDNA genome composition and structure, haplogroups and phylogeny, maternal inheritance, heteroplasmy, and functional analyses unique to mtDNA, as well as specifications for utilization of mtDNA genomic databases and computational algorithms.

Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium.

Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories consider. Deciding how to weigh each type of evidence is difficult, and standards have been needed. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases. Nine molecular diagnostic laboratories involved in the Clinical Sequencing Exploratory Research (CSER) consortium piloted these guidelines on 99 variants spanning all categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign). Nine variants were distributed to all laboratories, and the remaining 90 were evaluated by three laboratories. The laboratories classified each variant by using both the laboratory's own method and the ACMG-AMP criteria. The agreement between the two methods used within laboratories was high (K-alpha = 0.91) with 79% concordance. However, there was only 34% concordance for either classification system across laboratories. After consensus discussions and detailed review of the ACMG-AMP criteria, concordance increased to 71%. Causes of initial discordance in ACMG-AMP classifications were identified, and recommendations on clarification and increased specification of the ACMG-AMP criteria were made. In summary, although an initial pilot of the ACMG-AMP guidelines did not lead to increased concordance in variant interpretation, comparing variant interpretations to identify differences and having a common framework to facilitate resolution of those differences were beneficial for improving agreement, allowing iterative movement toward increased reporting consistency for variants in genes associated with monogenic disease.

Secondary findings from clinical genomic sequencing: prevalence, patient perspectives, family history assessment, and health-care costs from a multisite study.

PURPOSE: Clinical sequencing emerging in health care may result in secondary findings (SFs). METHODS: Seventy-four of 6240 (1.2%) participants who underwent genome or exome sequencing through the Clinical Sequencing Exploratory Research (CSER) Consortium received one or more SFs from the original American College of Medical Genetics and Genomics (ACMG) recommended 56 gene-condition pair list; we assessed clinical and psychosocial actions. RESULTS: The overall adjusted prevalence of SFs in the ACMG 56 genes across the CSER consortium was 1.7%. Initially 32% of the family histories were positive, and post disclosure, this increased to 48%. The average cost of follow-up medical actions per finding up to a 1-year period was $128 (observed, range: $0-$678) and $421 (recommended, range: $141-$1114). Case reports revealed variability in the frequency of and follow-up on medical recommendations patients received associated with each SF gene-condition pair. Participants did not report adverse psychosocial impact associated with receiving SFs; this was corroborated by 18 participant (or parent) interviews. All interviewed participants shared findings with relatives and reported that relatives did not pursue additional testing or care. CONCLUSION: Our results suggest that disclosure of SFs shows little to no adverse impact on participants and adds only modestly to near-term health-care costs; additional studies are needed to confirm these findings.

Correction: Secondary findings from clinical genomic sequencing: prevalence, patient perspectives, family history assessment, and health-care costs from a multisite study.

The originally published version of this Article contained errors in Fig. 2. The numbers below the black arrowheads were incorrect; please see incorrect Figure in associated Correction. These errors have now been corrected in the PDF and HTML versions of the Article.

Actionable exomic incidental findings in 6503 participants: challenges of variant classification.

Recommendations for laboratories to report incidental findings from genomic tests have stimulated interest in such results. In order to investigate the criteria and processes for assigning the pathogenicity of specific variants and to estimate the frequency of such incidental findings in patients of European and African ancestry, we classified potentially actionable pathogenic single-nucleotide variants (SNVs) in all 4300 European- and 2203 African-ancestry participants sequenced by the NHLBI Exome Sequencing Project (ESP). We considered 112 gene-disease pairs selected by an expert panel as associated with medically actionable genetic disorders that may be undiagnosed in adults. The resulting classifications were compared to classifications from other clinical and research genetic testing laboratories, as well as with in silico pathogenicity scores. Among European-ancestry participants, 30 of 4300 (0.7%) had a pathogenic SNV and six (0.1%) had a disruptive variant that was expected to be pathogenic, whereas 52 (1.2%) had likely pathogenic SNVs. For African-ancestry participants, six of 2203 (0.3%) had a pathogenic SNV and six (0.3%) had an expected pathogenic disruptive variant, whereas 13 (0.6%) had likely pathogenic SNVs. Genomic Evolutionary Rate Profiling mammalian conservation score and the Combined Annotation Dependent Depletion summary score of conservation, substitution, regulation, and other evidence were compared across pathogenicity assignments and appear to have utility in variant classification. This work provides a refined estimate of the burden of adult onset, medically actionable incidental findings expected from exome sequencing, highlights challenges in variant classification, and demonstrates the need for a better curated variant interpretation knowledge base.

Utility and limitations of exome sequencing as a genetic diagnostic tool for children with hearing loss.

PURPOSE: Hearing loss (HL) is the most common sensory disorder in children. Prompt molecular diagnosis may guide screening and management, especially in syndromic cases when HL is the single presenting feature. Exome sequencing (ES) is an appealing diagnostic tool for HL as the genetic causes are highly heterogeneous. METHODS: ES was performed on a prospective cohort of 43 probands with HL. Sequence data were analyzed for primary and secondary findings. Capture and coverage analysis was performed for genes and variants associated with HL. RESULTS: The diagnostic rate using ES was 37.2%, compared with 15.8% for the clinical HL panel. Secondary findings were discovered in three patients. For 247 genes associated with HL, 94.7% of the exons were targeted for capture and 81.7% of these exons were covered at 20× or greater. Further analysis of 454 randomly selected HL-associated variants showed that 89% were targeted for capture and 75% were covered at a read depth of at least 20×. CONCLUSION: ES has an improved yield compared with clinical testing and may capture diagnoses not initially considered due to subtle clinical phenotypes. Technical challenges were identified, including inadequate capture and coverage of HL genes. Additional considerations of ES include secondary findings, cost, and turnaround time.

Utility and limitations of exome sequencing in the molecular diagnosis of pediatric inherited platelet disorders.

Inherited platelet disorders (IPD) are a heterogeneous group of rare disorders that affect platelet number and function and often predispose to other significant medical complications. In spite of the identification of over 50 IPD disease-associated genes, a molecular diagnosis is only identified in a minority (10%) of affected patients without a clinically suspected etiology. We studied a cohort of 21 pediatric patients with suspected IPDs by exome sequencing (ES) to: (1) examine the performance of the exome test for IPD genes, (2) determine if this exome-wide diagnostic test provided a higher diagnostic yield than has been previously reported, (3) to evaluate the frequency of variants of uncertain significance identified, and (4) to identify candidate variants for functional evaluation in patients with an uncertain or negative diagnosis. We established a high priority gene list of 53 genes, evaluated exome capture kit performance, and determined the coverage for these genes and disease-related variants. We identified likely disease causing variants in 5 of the 21 probands (23.8%) and variants of uncertain significance in 52% of patients studied. In conclusion, ES has the potential to molecularly diagnose causes of IPD, and to identify candidate genes for functional evaluation. Robust exome sequencing also requires that coverage of genes known to be associated with clinical findings of interest need to be carefully examined and supplemented if necessary. Clinicians who undertake ES should understand the limitations of the test and the full significance of results that may be returned.

Utility and limitations of exome sequencing as a genetic diagnostic tool for conditions associated with pediatric sudden cardiac arrest/sudden cardiac death.

BACKGROUND: Conditions associated with sudden cardiac arrest/death (SCA/D) in youth often have a genetic etiology. While SCA/D is uncommon, a pro-active family screening approach may identify these inherited structural and electrical abnormalities prior to symptomatic events and allow appropriate surveillance and treatment. This study investigated the diagnostic utility of exome sequencing (ES) by evaluating the capture and coverage of genes related to SCA/D. METHODS: Samples from 102 individuals (13 with known molecular etiologies for SCA/D, 30 individuals without known molecular etiologies for SCA/D and 59 with other conditions) were analyzed following exome capture and sequencing at an average read depth of 100X. Reads were mapped to human genome GRCh37 using Novoalign, and post-processing and analysis was done using Picard and GATK. A total of 103 genes (2,190 exons) related to SCA/D were used as a primary filter. An additional 100 random variants within the targeted genes associated with SCA/D were also selected and evaluated for depth of sequencing and coverage. Although the primary objective was to evaluate the adequacy of depth of sequencing and coverage of targeted SCA/D genes and not for primary diagnosis, all patients who had SCA/D (known or unknown molecular etiologies) were evaluated with the project's variant analysis pipeline to determine if the molecular etiologies could be successfully identified. RESULTS: The majority of exons (97.6 %) were captured and fully covered on average at minimum of 20x sequencing depth. The proportion of unique genomic positions reported within poorly covered exons remained small (4 %). Exonic regions with less coverage reflect the need to enrich these areas to improve coverage. Despite limitations in coverage, we identified 100 % of cases with a prior known molecular etiology for SCA/D, and analysis of an additional 30 individuals with SCA/D but no known molecular etiology revealed a diagnostic answer in 5/30 (17 %). We also demonstrated 95 % of 100 randomly selected reported variants within our targeted genes would have been picked up on ES based on our coverage analysis. CONCLUSIONS: ES is a helpful clinical diagnostic tool for SCA/D given its potential to successfully identify a molecular diagnosis, but clinicians should be aware of limitations of available platforms from technical and diagnostic perspectives.

Mitochondrial DNA and Y chromosome variation provides evidence for a recent common ancestry between Native Americans and Indigenous Altaians.

The Altai region of southern Siberia has played a critical role in the peopling of northern Asia as an entry point into Siberia and a possible homeland for ancestral Native Americans. It has an old and rich history because humans have inhabited this area since the Paleolithic. Today, the Altai region is home to numerous Turkic-speaking ethnic groups, which have been divided into northern and southern clusters based on linguistic, cultural, and anthropological traits. To untangle Altaian genetic histories, we analyzed mtDNA and Y chromosome variation in northern and southern Altaian populations. All mtDNAs were assayed by PCR-RFLP analysis and control region sequencing, and the nonrecombining portion of the Y chromosome was scored for more than 100 biallelic markers and 17 Y-STRs. Based on these data, we noted differences in the origin and population history of Altaian ethnic groups, with northern Altaians appearing more like Yeniseian, Ugric, and Samoyedic speakers to the north, and southern Altaians having greater affinities to other Turkic speaking populations of southern Siberia and Central Asia. Moreover, high-resolution analysis of Y chromosome haplogroup Q has allowed us to reshape the phylogeny of this branch, making connections between populations of the New World and Old World more apparent and demonstrating that southern Altaians and Native Americans share a recent common ancestor. These results greatly enhance our understanding of the peopling of Siberia and the Americas.

Y-chromosome analysis reveals genetic divergence and new founding native lineages in Athapaskan- and Eskimoan-speaking populations.

For decades, the peopling of the Americas has been explored through the analysis of uniparentally inherited genetic systems in Native American populations and the comparison of these genetic data with current linguistic groupings. In northern North America, two language families predominate: Eskimo-Aleut and Na-Dene. Although the genetic evidence from nuclear and mtDNA loci suggest that speakers of these language families share a distinct biological origin, this model has not been examined using data from paternally inherited Y chromosomes. To test this hypothesis and elucidate the migration histories of Eskimoan- and Athapaskan-speaking populations, we analyzed Y-chromosomal data from Inuvialuit, Gwich'in, and Tlich populations living in the Northwest Territories of Canada. Over 100 biallelic markers and 19 chromosome short tandem repeats (STRs) were genotyped to produce a high-resolution dataset of Y chromosomes from these groups. Among these markers is an SNP discovered in the Inuvialuit that differentiates them from other Aboriginal and Native American populations. The data suggest that Canadian Eskimoan- and Athapaskan-speaking populations are genetically distinct from one another and that the formation of these groups was the result of two population expansions that occurred after the initial movement of people into the Americas. In addition, the population history of Athapaskan speakers is complex, with the Tlich being distinct from other Athapaskan groups. The high-resolution biallelic data also make clear that Y-chromosomal diversity among the first Native Americans was greater than previously recognized.

Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

BACKGROUND: Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. RESULTS: Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. CONCLUSIONS: Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for clinical genetic diagnosis.

Processes and preliminary outputs for identification of actionable genes as incidental findings in genomic sequence data in the Clinical Sequencing Exploratory Research Consortium.

As genomic and exomic testing expands in both the research and clinical arenas, determining whether, how, and which incidental findings to return to the ordering clinician and patient becomes increasingly important. Although opinion is varied on what should be returned to consenting patients or research participants, most experts agree that return of medically actionable results should be considered. There is insufficient evidence to fully inform evidence-based clinical practice guidelines regarding return of results from genome-scale sequencing, and thus generation of such evidence is imperative, given the rapidity with which genome-scale diagnostic tests are being incorporated into clinical care. We present an overview of the approaches to incidental findings by members of the Clinical Sequencing Exploratory Research network, funded by the National Human Genome Research Institute, to generate discussion of these approaches by the clinical genomics community. We also report specific lists of "medically actionable" genes that have been generated by a subset of investigators in order to explore what types of findings have been included or excluded in various contexts. A discussion of the general principles regarding reporting of novel variants, challenging cases (genes for which consensus was difficult to achieve across Clinical Sequencing Exploratory Research network sites), solicitation of preferences from participants regarding return of incidental findings, and the timing and context of return of incidental findings are provided.Genet Med 15 11, 860-867.Genetics in Medicine (2013); 15 11, 860-867. doi:10.1038/gim.2013.133.

Clan, language, and migration history has shaped genetic diversity in Haida and Tlingit populations from Southeast Alaska.

The linguistically distinctive Haida and Tlingit tribes of Southeast Alaska are known for their rich material culture, complex social organization, and elaborate ritual practices. However, much less is known about these tribes from a population genetic perspective. For this reason, we analyzed mtDNA and Y-chromosome variation in Haida and Tlingit populations to elucidate several key issues pertaining to the history of this region. These included the genetic relationships of Haida and Tlingit to other indigenous groups in Alaska and Canada; the relationship between linguistic and genetic data for populations assigned to the Na-Dene linguistic family, specifically, the inclusion of Haida with Athapaskan, Eyak, and Tlingit in the language family; the possible influence of matrilineal clan structure on patterns of genetic variation in Haida and Tlingit populations; and the impact of European entry into the region on the genetic diversity of these indigenous communities. Our analysis indicates that, while sharing a "northern" genetic profile, the Haida and the Tlingit are genetically distinctive from each other. In addition, Tlingit groups themselves differ across their geographic range, in part due to interactions of Tlingit tribes with Athapaskan and Eyak groups to the north. The data also reveal a strong influence of maternal clan identity on mtDNA variation in these groups, as well as the significant influence of non-native males on Y-chromosome diversity. These results yield new details about the histories of the Haida and Tlingit tribes in this region.

Molecular Diagnostic Outcomes from 700 Cases: What Can We Learn from a Retrospective Analysis of Clinical Exome Sequencing?

Clinical exome sequencing (CES) aids in the diagnosis of rare genetic disorders. Herein, we report the molecular diagnostic yield and spectrum of genetic alterations contributing to disease in 700 pediatric cases analyzed at the Children's Hospital of Philadelphia. The overall diagnostic yield was 23%, with three cases having more than one molecular diagnosis and 2.6% having secondary/additional findings. A candidate gene finding was reported in another 8.4% of cases. The clinical indications with the highest diagnostic yield were neurodevelopmental disorders (including seizures), whereas immune- and oncology-related indications were negatively associated with molecular diagnosis. The rapid expansion of knowledge regarding the genome's role in human disease necessitates reanalysis of CES samples. To capture these new discoveries, a subset of cases (n = 240) underwent reanalysis, with an increase in diagnostic yield. We describe our experience reporting CES results in a pediatric setting, including reporting of secondary findings, reporting newly discovered genetic conditions, and revisiting negative test results. Finally, we highlight the challenges associated with implementing critical updates to the CES workflow. Although these updates are necessary, they demand an investment of time and resources from the laboratory. In summary, these data demonstrate the clinical utility of exome sequencing and reanalysis, while highlighting the critical considerations for continuous improvement of a CES test in a clinical laboratory.

Mitochondrial genome sequence analysis: a custom bioinformatics pipeline substantially improves Affymetrix MitoChip v2.0 call rate and accuracy.

BACKGROUND: Mitochondrial genome sequence analysis is critical to the diagnostic evaluation of mitochondrial disease. Existing methodologies differ widely in throughput, complexity, cost efficiency, and sensitivity of heteroplasmy detection. Affymetrix MitoChip v2.0, which uses a sequencing-by-genotyping technology, allows potentially accurate and high-throughput sequencing of the entire human mitochondrial genome to be completed in a cost-effective fashion. However, the relatively low call rate achieved using existing software tools has limited the wide adoption of this platform for either clinical or research applications. Here, we report the design and development of a custom bioinformatics software pipeline that achieves a much improved call rate and accuracy for the Affymetrix MitoChip v2.0 platform. We used this custom pipeline to analyze MitoChip v2.0 data from 24 DNA samples representing a broad range of tissue types (18 whole blood, 3 skeletal muscle, 3 cell lines), mutations (a 5.8 kilobase pair deletion and 6 known heteroplasmic mutations), and haplogroup origins. All results were compared to those obtained by at least one other mitochondrial DNA sequence analysis method, including Sanger sequencing, denaturing HPLC-based heteroduplex analysis, and/or the Illumina Genome Analyzer II next generation sequencing platform. RESULTS: An average call rate of 99.75% was achieved across all samples with our custom pipeline. Comparison of calls for 15 samples characterized previously by Sanger sequencing revealed a total of 29 discordant calls, which translates to an estimated 0.012% for the base call error rate. We successfully identified 4 known heteroplasmic mutations and 24 other potential heteroplasmic mutations across 20 samples that passed quality control. CONCLUSIONS: Affymetrix MitoChip v2.0 analysis using our optimized MitoChip Filtering Protocol (MFP) bioinformatics pipeline now offers the high sensitivity and accuracy needed for reliable, high-throughput and cost-efficient whole mitochondrial genome sequencing. This approach provides a viable alternative of potential utility for both clinical diagnostic and research applications to traditional Sanger and other emerging sequencing technologies for whole mitochondrial genome analysis.