Abstract

The development of novel technologies for high-throughput DNA sequencing is having a major impact on our ability to measure and define normal and pathologic variation in humans. This review discusses advances in DNA sequencing that have been applied to benign hematologic disorders, including those affecting the red blood cell, the neutrophil, and other white blood cell lineages. Relevant examples of how these approaches have been used for disease diagnosis, gene discovery, and studying complex traits are provided. High-throughput DNA sequencing technology holds significant promise for impacting clinical care. This includes development of improved disease detection and diagnosis, better understanding of disease progression and stratification of risk of disease-specific complications, and development of improved therapeutic strategies, particularly patient-specific pharmacogenomics-based therapy, with monitoring of therapy by genomic biomarkers.

Introduction

Hematology has a long history of being a discipline at the forefront of applying novel technology to understanding and diagnosing disease. Maxwell Wintrobe pointed out in his classic text, “Blood, Pure and Eloquent,” that important developments in the field of hematology were often driven by technology. For instance, early observations of blood and marrow morphology were enabled by the advances in microscopy. Similarly, quantitation of the different cellular elements of blood were made possible by development of the hemocytometer.1 

Hematology continued to lead the way into the molecular era, with the description of sickle cell anemia as the first molecular disease,2  solution of the hemoglobin molecule by x-ray crystallography (the first multisubunit protein to be understood at the molecular level3 ), and determination of the molecular basis of sickle cell disease at the amino acid level.4  As Wintrobe’s classic text was being published, breakthrough technologies in the fledgling field of molecular genetics were leading to groundbreaking developments. Studying sickle cell disease and the thalassemia syndromes, investigators linked genetic polymorphisms to human disease, identified disease-causing mutations at the DNA level, and developed strategies for prenatal diagnosis (reviewed in Sankaran and Nathan5 ). A few years later, the first human disease gene isolated by positional cloning, the chronic granulomatous disease gene CYBB, was identified.6  Recently, advances in genomic technologies have led to numerous discoveries in hematology, detailed below.

As we make our way through the 21st century, technology continues to rapidly evolve. The use of next-generation DNA sequencing has dramatically advanced the way we assess gene expression, protein-DNA interactions, long-range DNA interactions, and both normal and pathologic DNA variation.7,8  This latter area is the focus of this review, which is one of a series of reviews on the application of high-throughput sequencing approaches to hematology. In this review, we discuss the application of these approaches to benign hematology, including red blood cell, neutrophil, and other white blood cell disorders. Malignant hematologic disorders and bleeding disorders, including abnormalities in platelets, are covered in other reviews. A review from Deborah Nickerson provides an overview of the high-throughput DNA sequencing technology. Because a comprehensive review is impractical, we provide vignettes that illustrate how high-throughput DNA sequencing is impacting hematology. These highlight applications of these approaches for disease diagnosis, gene discovery, and a better understanding of the genetic basis of complex traits. Prognostic and therapeutic implications of advances driven by sequencing technology are discussed and future applications highlighted.

Disease diagnosis

Genome-wide targeted exon capture followed by high-throughput DNA sequencing (whole-exome sequencing [WES]) is a technique that provides an unbiased analysis of coding exons and their associated splice junctions.9,10  WES is an excellent tool for identifying disease-causing mutations in monogenic disease and it can be applied to disorders with recessive or dominant inheritance, or de novo mutations (Figure 1). The cost of DNA sequencing has markedly decreased and computational platforms have rapidly improved, making WES a viable alternative to traditional Sanger sequencing–based techniques for genetic diagnosis.11,12 

Figure 1

WES in NA. Integrated genome browser view of reads from select regions of the VPS13A gene generated by exome sequencing. (A) Exon 69. Approximately half of full-length reads have A instead of G, leading to a missense mutation, thereby disrupting the exon 69 donor splice junction. (B) Exon 58. Approximately half of full-length reads lack 4 nucleotides, TAAG, corresponding to the end of exon 58 and the first nucleotide of intron 58.

Figure 1

WES in NA. Integrated genome browser view of reads from select regions of the VPS13A gene generated by exome sequencing. (A) Exon 69. Approximately half of full-length reads have A instead of G, leading to a missense mutation, thereby disrupting the exon 69 donor splice junction. (B) Exon 58. Approximately half of full-length reads lack 4 nucleotides, TAAG, corresponding to the end of exon 58 and the first nucleotide of intron 58.

Excellent candidate disorders for utilizing WES are those that have great genotypic variability, that is, mutations in numerous genes lead to the same clinical phenotype, and/or where the genetic loci of interest are very large, where traditional sequencing strategies suffer from slow throughput.12  Indeed, in some cases, the use of WES or targeted exome sequencing for molecular diagnosis is cheaper than traditional Sanger sequencing. Targeted exome sequencing has been applied to many disorders with genotypic variability including the long QT syndrome, cardiomyopathy, and severe combined immunodeficiency syndrome.13  There are many potential applications for targeted WES in clinical hematology (Table 1). Clinical syndromes where targeted exome sequencing has already been applied for diagnostic purposes include Fanconi anemia (FA), the neuroacanthocytosis (NA) syndromes, and Diamond-Blackfan anemia (DBA).

Table 1

Potential applications of targeted WES in clinical hematology

Potential applications
Unknown hemolytic anemia 
Transfusion-dependent anemia 
NA syndromes 
Congenital neutropenia 
Bone marrow failure syndromes 
 DBA 
 Aplastic anemia 
 Dyskeratosis congenita 
 FA 
Potential applications
Unknown hemolytic anemia 
Transfusion-dependent anemia 
NA syndromes 
Congenital neutropenia 
Bone marrow failure syndromes 
 DBA 
 Aplastic anemia 
 Dyskeratosis congenita 
 FA 

FA is a heterogeneous bone marrow failure syndrome associated with defective DNA repair.14,15  Affected individuals exhibit cancer predisposition and frequently suffer from various congenital anomalies. Inherited primarily in an autosomal-recessive manner, over a dozen FA genes have been described. Application of exome sequencing to FA patients has identified a variety of mutations in FA-associated genes, several of which were novel.16,17  New gene discovery in FA genes has also been carried out with exome sequencing. A truncating mutation of the XRCC2 gene was discovered in a male child from a consanguineous Saudi family with an FA phenotype.18  XRCC2 is one of 5 RAD51 paralogs that act nonredundantly in the pathway of homologous recombination repair.

The NA syndromes are a group of heterogeneous neurodegenerative disorders that share the feature of having acanthocytes present on peripheral blood smear (Figure 1). NA syndromes include chorea-acanthocytosis (ChAc), X-linked McLeod syndrome (MLS), Huntington disease–like 2 (HDL2), and pantothenate kinase-associated neurodegeneration (PKAN). Diagnosis is difficult, particularly in the early stages of disease or when the presentation is atypical. Multiple genetic loci are involved and include mutations in chorein (VPS13A) in ChAc, XK (XK) in MLS, junctophilin-3 (JPH3) in HDL2, and pantothenate kinase 2 (PANK2) in PKAN.19-21  Most NA mutations are private, that is, each kindred has a unique mutation, making mutation detection difficult, and several of the NA genes are very large, making traditional Sanger sequencing cumbersome. Walker and colleagues used exome sequencing to identify compound heterozygous mutations of the VPS13A gene in 2 NA patients, allowing precise genetic diagnosis and providing information for genetic counseling of affected patients and their family members.22 

Figure 2

Identifying hematologic diseases using WES. (A) Blood smear from a patient with HX demonstrates rare stomatocytes, target cells, and dessicytes (dense, erythrocytes with hemoglobin appearing to be puddled at the periphery). (B) WES identified mutations in PIEZO1, encoded by the FAM38A gene, as the HX disease locus. The location of this patient’s mutation is denoted by the arrow on a model of PIEZO1 created using hmmtop2 software. Adapted from Zarychanski et al35  with permission. (C) Blood marrow aspirate smear from a patient with DBA demonstrates only rare erythroblasts. (D) WES identified mutations in the GATA1 gene, leading to altered splicing and production of a short protein form of GATA1 protein (GATA1s) that lacks the NH2-terminal TD present in full-length GATA1. CF, COOH-terminal zinc finger; NF, NH2-terminal zinc finger; TD, transactivation domain. Adapted from Sankaran et al28  with permission.

Figure 2

Identifying hematologic diseases using WES. (A) Blood smear from a patient with HX demonstrates rare stomatocytes, target cells, and dessicytes (dense, erythrocytes with hemoglobin appearing to be puddled at the periphery). (B) WES identified mutations in PIEZO1, encoded by the FAM38A gene, as the HX disease locus. The location of this patient’s mutation is denoted by the arrow on a model of PIEZO1 created using hmmtop2 software. Adapted from Zarychanski et al35  with permission. (C) Blood marrow aspirate smear from a patient with DBA demonstrates only rare erythroblasts. (D) WES identified mutations in the GATA1 gene, leading to altered splicing and production of a short protein form of GATA1 protein (GATA1s) that lacks the NH2-terminal TD present in full-length GATA1. CF, COOH-terminal zinc finger; NF, NH2-terminal zinc finger; TD, transactivation domain. Adapted from Sankaran et al28  with permission.

Obtaining a precise molecular diagnosis when a patient presents with complex phenotypic features is another application of exome sequencing. Cullinane and colleagues studied a woman with oculocutaneous albinism, recurrent infections, bleeding diathesis, and neutropenia with the working clinical diagnosis of Hermansky-Pudlak syndrome.23  However, homozygosity mapping and exome sequencing identified mutations in 2 disease loci: the SLC45A2 gene locus associated with oculocutaneous albinism and the G6PC3 gene locus associated with congenital neutropenia.23  Additional findings of this woman and her sibling were described by Fernandez and coworkers.24 

Extending disease phenotype-genotype relationships and disease gene discovery

Making diagnoses in patients with hematologic disorders has proven valuable, as illustrated by the examples discussed in the prior section. In many hematologic disorders, much of the genetic etiology remains undefined. WES gives an opportunity to define and extend the spectrum of mutations causing a particular disease. DBA is a hypoplastic anemia characterized by a specific reduction in both mature red blood cells and their progenitors (Figure 2A). Approximately 50% to 70% of cases are attributable to mutations in ∼10 different ribosomal proteins (RPs), the most frequent of which is RPS19, mutated in 25% of cases.25,26  Targeted WES has been used to study RP genes in DBA patients, identifying mutations in 15 of 17 patients in 1 study.27 

WES in a family with 2 affected male siblings with a clinical diagnosis of DBA without RP gene mutations identified mutations in the critical X-linked hematopoietic transcription factor GATA1.28  An additional DBA patient was found to have similar mutations in GATA1. These mutations favor production of a short form of GATA1 that lacks the first 83 amino acids (Figure 2B). Further work is needed to understand how these mutations impair erythropoiesis and to explore whether any connection exists between these mutations and the more common RP gene mutations found in DBA. It is interesting to note that other GATA1 missense mutations found in the N-terminal zinc finger of this transcription factor result in very different phenotypes involving dyserythropoietic anemia, thalassemia, erythropoietic porphyria, and/or macrothrombocytopenia.25  These differences have been suggested to be due to variable effects on different GATA1 binding partner proteins and are distinct from the DBA-associated GATA1 mutations.29 

Iron-refractory iron-deficiency anemia is an autosomal-recessive hypochromic microcytic anemia unresponsive to oral iron supplementation and with a slow response to parenteral iron with partial correction of the anemia. Using a candidate gene approach, Finberg and colleagues identified mutations in maltriptase-2, encoded by the TMPRSS6 gene, a transmembrane serine protease that plays a critical role in downregulating hepcidin, the key regulator of iron homeostasis.30  Numerous investigators have reported additional TMPRSS6 mutations in iron-refractory iron-deficiency anemia patients. Using exome sequencing, Khuong-Quang and colleagues studied French Canadian siblings with severe hypochromic, microcytic anemia, hypoferremia, and hyperferritinemia with good response to oral iron supplementation.31  Compound heterozygous TMPRSS6 mutations were identified in the children, extending the phenotypic spectrum of TMPRSS6-associated disease.

WES has identified over 100 genes associated with Mendelian disorders (reviewed in Rabbani et al32 ) including several hematologic disorders. Hereditary xerocytosis (HX) is an autosomal-dominant hemolytic anemia characterized by primary erythrocyte dehydration (Figure 2C).33  Although a locus for HX had been identified at 16q23-q24 by traditional linkage analysis, a number of factors complicated identifying the disease gene including a paucity of large, informative kindreds, and large blocks of repetitive, recombinant DNA sequence in the region containing the HX locus.34  Zarychanski and colleagues used WES to study individuals from one of the original HX kindreds from Rochester, NY and additional kindred from Winnipeg, MB.35  This led to discovery of mutations in PIEZO1, encoded by the FAM38A gene, in both HX kindreds (Figure 2D). These findings were confirmed in additional HX kindreds by 2 other groups who also used WES to identify the HX disease gene.36,37  PIEZO proteins are recently identified channels that mediate mechanotransduction in mammalian cells.38  In a large genome-wide association study, a single-nucleotide polymorphism near the PIEZO1 gene was strongly associated with cellular volume, as determined by mean corpuscular hemoglobin concentration.39  These findings indicate that this newly discovered protein plays an important role in erythrocyte volume homeostasis.

Congenital neutropenia and primary myelofibrosis are both very rare conditions in infancy. Five infants with neutropenia, recurrent and severe infections, defective platelet aggregation, myelofibrosis, and progressive bone marrow failure were studied by homozygosity mapping and WES.40  Independently, another group examined 7 patients with similar phenotypes in 5 families by linkage mapping and WES.41  These studies revealed missense mutations in VPS45, which encodes a protein that participates in trafficking in the endosomal pathway. Interestingly, fibroblasts from affected patients lacked lysosomes, suggesting a role for VPS45 in biogenesis of the endosomal-lysosomal pathway.40  This adds VPS45 to the growing list of lysosomal-related proteins associated with congenital neutropenia, including those associated with Chediak-Higashi syndrome, Hermansky-Pudlak syndrome type 2, Griscelli syndrome, Cohen syndrome, and variants in the endosomal adaptor protein p14 associated with primary immunodeficiency.

Inherited aplastic anemia syndromes include FA and dyskeratosis congenita. However, the primary cause in a subset of familial aplastic anemia patients is unknown. Walne and coworkers studied 2 children from a consanguineous Tunisian family affected with familial aplastic anemia without a known genetic diagnosis.42  WES identified homozygous nonsense mutations in the thrombopoietin receptor gene, MPL. Previously, biallelic mutations in the MPL gene have been associated with congenital amegakaryocytic thrombocytopenia. Study of 33 additional aplastic anemia patients identified a homozygous missense mutation 22 amino acids away from the Tunisian mutation,42  further supporting a role for MPL in trilineage hematopoiesis and as a cause of aplastic anemia. In other cases, the use of WES has been useful to identify potential new disease genes implicated in cases of aplastic anemia syndromes, such as SRP72 as a possible candidate gene in aplastic anemia associated with myelodysplasia43  and RTEL1 in dyskeratosis congenita.44,45 

Mutations in the critical hematopoietic transcription factor gene GATA2 have been associated with autosomal-dominant and sporadic monocytopenia and susceptibility to mycobacterial infection, the MonoMAC syndrome, which evolves over time to predispose to familial myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) later in life.46-48  WES of several individuals with familial MDS/AML or MonoMAC syndrome with primary lymphedema identified germline GATA2 gene mutations. Additional studies revealed a critical role for GATA2 in lymphoid development and indicated that haploinsufficiency or loss-of-function mutations are critical for predisposition to lymphedema, extending the phenotypic spectrum of GATA2 gene mutations.49  In some cases, haploinsufficiency is due to mutation in a conserved intronic element of the GATA2 gene.50  WES of patients from the French Severe Chronic Neutropenia Registry revealed GATA2 gene mutations in 7 kindreds with unexplained neutropenia, which in several cases evolved to MonoMAC or MDS/AML.51  These studies indicate that GATA2 gene mutations should be added to the list of congenital neutropenia genes associated with susceptibility to infection including the ELANE, HAX1, CXCR4, WAS, SBDS, GFI1, and G6PC3 loci.

Genetic basis of complex traits

Genome-wide association studies (GWAS) have consistently demonstrated, with a few exceptions, that common variants have small to modest phenotypic effects, often requiring tens to hundreds of thousands of patient samples to have sufficient power to detect statistically-significant associations.9  When studying complex diseases or traits, a priori, it is unknown whether the likelihood of developing a specific disease complication or trait is more closely linked to common or rare variants. To address the former, many GWAS have been performed, attempting to identify common variants contributing to complex disease.52-56  These studies have revealed that in most complex diseases, common variants explain only a small fraction of genetic risk.

Recent studies suggest that rare, independent mutations may also contribute to phenotypic variation in complex diseases such as hypertension, hypertriglyceridemia, and cholesterol level variation.57-62  Thus, for genes subject solely to purifying selection, rare, independent mutations and not common variants predominate.58  Sequencing of linked genes identified by functional, genetic, or other methods, provide information to our understanding of the genetic contribution to complex disease. This has led to the studies that combine WES with genome-wide linkage or association analyses for identification of complex trait–associated variants.

These strategies have been successful leveraged to identify genes that may underlie common variation in hematologic traits found from GWAS.63-67  Galarneau and colleagues performed one of the first studies showing that rare variants in genes implicated from GWAS studies can help identify causal genes in these loci for hematologic traits.68  By sequencing candidate genes near loci implicated in fetal hemoglobin (HbF) level variation from GWAS, they were able to show that rare variants in MYB were associated with HbF levels. This suggests that MYB is likely, at least in part, responsible for the effect seen from GWAS signals at the 6q23 locus.

Auer and colleagues performed WES on 761 African Americans and then imputed newly discovered variants into a larger sample of 13 000 African Americans for association with traits for hemoglobin, hematocrit, white blood cell count, and platelet count.69  This led to discovery of association between coding variants in MPL and higher platelet count, CD36 and lower platelet counts, LCT and higher white blood cell count, and α-globin gene variants with lower hemoglobin. This was one of the first studies to demonstrate that imputation of low-frequency missense variants identified by WES onto GWAS data are a powerful approach to dissecting complex, genetically heterogeneous traits in population-based studies.69 

Although promising, the appropriate numbers of patients needed to power these types of studies have not been determined and statistical approaches to test for such associations are rapidly being developed and are evolving.53,58,70 

Using findings from high-throughput sequencing to guide treatment

WES and other high-throughput sequencing approaches have already had and will continue to have a major impact upon disease diagnosis at the molecular level and disease gene discovery, but a major question that remains is whether these findings are actionable for therapeutic purposes. A few examples exist in the literature where targeted therapies resulted from the findings of WES. An excellent example of this involves the case of a child who presented at a young age with severe inflammatory bowel disease.71  However, a definitive diagnosis could not be made based upon clinical findings alone. WES helped to identify an XIAP mutation in this child, which is associated with a unique X-linked immunodeficiency syndrome. As a result, this child received an allogeneic hematopoietic stem cell transplant and had complete resolution of their previously intractable inflammatory bowel disease. In another example, WGS of an individual who was followed using a variety of genomic tools over a 14-month period predicted an increased risk of diabetes from the additive effects of multiple genetic variants present.72  The individual was found to have signs of glucose intolerance, and resultant lifestyle modifications led to improved glucose tolerance.72 

These examples are only single case reports and larger scale studies have yet to demonstrate whether such high-throughput sequencing approaches can have a major impact on therapy. The immediate utility of identifying new disease and quantitative trait loci is an improved understanding of disease pathogenesis. From these findings, the goal is the elucidation of novel, targeted therapeutic strategies. However, as is evident from study of numerous other Mendelian diseases, the road from genetic discovery, to understanding underlying biology, and ultimately to patient therapy is lengthy and plagued by a numerous hurdles along the way.

Ethical concerns and other considerations

Identification of actionable, incidental findings during genome-wide DNA sequencing genetic studies is a major concern of many patients, as well as health care providers. A well-known case is that of a patient who underwent WES in a search for autism-associated genetic variants. In the course of these studies, he was found to have pyruvate kinase deficiency. Known to suffer from an undiagnosed, lifelong hemolytic anemia, the results were conveyed to the patient’s hematologist, confirming the clinical diagnosis.73 

Many ethical and practical questions remain unanswered. How frequent are actionable findings found when performing WES or whole-genome sequencing (WGS)? Data are conflicting even answering this simple question.74-76  When WES or WGS data are obtained, should the data be curated for a set of specific variants? When potential deleterious variants are identified, how should they be handled? Who should notify and counsel the patient? In 2012, the American College of Medical Genetics (ACMG), stated that for “results that are generated in the course of screening asymptomatic individuals, it is critical that the standards for what is reported be high to avoid burdening the health care system and consumers with what could be large numbers of false positive results.”77  In 2013, the Working Group on Incidental Findings in Clinical Exome and Genome Sequencing of the ACMG provided specific recommendations, focusing on incidental findings of clinical import with actionable results, identifying a subset of variants they felt laboratories have an obligation to report.78  Already concerns have been voiced about these recommendations.79  These discussions are beyond the scope of this review. Interested readers can consult recent discussion of these topics.8,75,80,81 

Whole-genome sequencing

WGS holds the promise of revealing the critical deleterious and at-risk alleles in an individual genome wide (or at least in those parts of the genome that can be sequenced, as discussed in the next paragraph below). Although the cost of WGS has dramatically fallen, issues of data storage, workflow and analysis, and clinical and ethical concerns persist. A recent report of patients who underwent WGS at the Medical College of Wisconsin revealed that a definitive diagnosis was obtained in 7 of 26 (27%) patients.82  Although initial concerns revolved around cost and data accuracy, the major challenges faced were logistics of delivering the data to clinicians, how clinicians used the genetic data, and how patients and their families dealt with incidental findings. Another major challenge that plagues the interpretation of WGS is the fact that alterations in most parts of the genome are still not interpretable, in contrast to the modifications in coding regions that cause clearly interpretable changes in amino acid sequence or splicing sites. As a result, even in cases where WGS is performed, often the analysis is limited to coding regions of the genome that can more readily be analyzed.83 

It is also important to remember that some diseases are caused by mutations located in regions of the genome that cannot be sequenced using even the latest WGS approaches, as was recently described for medullary cystic kidney disease.84  It is likely that some unidentified hematologic diseases may lie in such regions of the genome, which are refractory to current high-throughput sequencing approaches.

Implications for clinical hematology

From our discussion here, it is clear that there is a great deal of uncertainty in how best to interpret and apply the findings from WES and WGS. Nevertheless, these approaches are already showing promise for clinical applications and in some centers sequencing of patients by these approaches has already been initiated. As such, it is important for practicing hematologists to be aware of both the type of information produced from such approaches and the limitations of these findings.

In general, having both unaffected and affected family members undergo sequencing (at least confirmatory sequencing for any potential mutations identified) helps to delineate causal mutations from those that are likely to be uninvolved in the clinical phenotype of interest. The information gleaned from the clinical differential diagnosis can be useful to narrow potential candidate mutations, particularly when the high-throughput approaches are used for disease diagnosis. For example, if one was examining a child suspected of having a congenital neutropenia, then one could initially focus the analysis on genes already implicated as having a role in this condition, including ELANE, HAX1, CXCR4, WAS, SBDS, GFI1, G6PC3, GATA2, and VPS45. This set of genes should be assessed first if the goal is identifying mutations likely to cause the disease observed in the patient, just as individual gene sequencing using Sanger methods would be sent as clinical tests. In cases where no mutations are identified, then it is possible that the individual has a new genetic cause of their disease, but without a sufficient number of other family members or without other confirmatory information, such findings can rarely be of immediate clinical utility without performing a variety of research tests. We recommend that when information from clinical WES or WGS is going to be reported to patients or their families, that the known clinical information be used to determine the likely differential a priori to narrow the search for potential causal variants and then any identified mutations be evaluated in light of the known clinical information. When there is discrepancy between the clinical findings and the identified mutations, appropriate evaluation is necessary prior to reporting such information to patients and their families.

In addition, as with any other diagnostic test, there can be a variety of false-positive results. Geneticists have traditionally not had large healthy control populations to examine and with the deluge of high-throughput sequencing data, the certainty of presumed “validated” mutations in a variety of human diseases is coming into question.85  This may be attributable to the finding that many of the disease gene mutation databases include a large number of false positives (potentially as high as 25% of the reported mutations) and also may reflect the concept that many human diseases show substantial incomplete penetrance that was previously unappreciated due to ascertainment bias.86,87 

Conclusions and future directions

High-throughput DNA sequencing technology, which has already had an impact upon hematologic disease diagnosis and gene discovery, holds significant promise for the future. In the coming years, genomic studies will permit discovery of new disease genes and modifier alleles and provide important insights into disease pathobiology. These findings can be leveraged into better understanding of disease progression and allow stratification of risk of disease-specific complications. Novel, specific diagnostic approaches can be developed using genomic-based datasets. Improved therapeutic strategies can be created, particularly patient-specific pharmacogenomics-based therapy, with better monitoring of therapy by genomic biomarkers.

Much more work needs to be done to realize the lofty goals outlined here. Limitations of current technologies, for example, coverage of regions of the genome that are refractory to high-throughput sequencing methods, need to be addressed. Improving understanding of the relevance of disease-associated variants is needed, as are efficient strategies for functional validation of results obtained from sequencing studies. At the same time, development of approaches to handle incidental findings, from dealing with uncertainty in causality of variants of unknown significance, to reporting and counseling of actionable variants, is needed. The clinical validity and diagnostic utility for genetic testing for hematologic-associated disease need to be defined. The need for education of both patients and clinicians to embrace and fully understand and use genomic data is great.

Thus, as Wintrobe referred to historical technologic developments in his classic text,1  there is little doubt that hematology continues to be dramatically influenced by the use of newer technologies, as illustrated by high-throughput DNA sequencing.

Acknowledgments

This work was supported in part by RO1HL065449 (P.G.G.) and HL007574-30 (V.G.S.) from the National Institutes of Health, National Heart, Lung, and Blood Institute, and a grant from the Doris Duke Research Foundation (P.G.G.).

Authorship

Contribution: V.G.S. and P.G.G. designed, organized, researched, and wrote this review.

Conflict-of-interest disclosure: The authors declare no competing financial interests.

Correspondence: Vijay G. Sankaran, Division of Hematology/Oncology, Boston Children’s Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, 3 Blackfan Circle, CL 03001, Boston, MA 02115; e-mail: sankaran@broadinstitute.org; and Patrick G. Gallagher, Division of Neonatal/Perinatal Medicine, Departments of Pediatrics, Pathology, and Genetics, Yale University School of Medicine, 333 Cedar St, PO Box 208064, New Haven, CT 06520-8064; e-mail: patrick.gallagher@yale.edu.

References

References
1
Wintrobe
 
MM
Blood, Pure and Eloquent: A Story of Discovery, of People, and of Ideas
1980
New York, NY
McGraw-Hill
2
Pauling
 
L
Itano
 
HA
, et al. 
Sickle cell anemia a molecular disease.
Science
1949
, vol. 
110
 
2865
(pg. 
543
-
548
)
3
Perutz
 
MF
Rossmann
 
MG
Cullis
 
AF
Muirhead
 
H
Will
 
G
North
 
AC
Structure of haemoglobin: a three-dimensional Fourier synthesis at 5.5-A. resolution, obtained by x-ray analysis.
Nature
1960
, vol. 
185
 
4711
(pg. 
416
-
422
)
4
Ingram
 
VM
A specific chemical difference between the globins of normal human and sickle-cell anaemia haemoglobin.
Nature
1956
, vol. 
178
 
4537
(pg. 
792
-
794
)
5
Sankaran
 
VG
Nathan
 
DG
Thalassemia: an overview of 50 years of clinical research.
Hematol Oncol Clin North Am
2010
, vol. 
24
 
6
(pg. 
1005
-
1020
)
6
Royer-Pokora
 
B
Kunkel
 
LM
Monaco
 
AP
, et al. 
Cloning the gene for an inherited human disorder—chronic granulomatous disease—on the basis of its chromosomal location.
Nature
1986
, vol. 
322
 
6074
(pg. 
32
-
38
)
7
Shendure
 
J
Lieberman Aiden
 
E
The expanding scope of DNA sequencing.
Nat Biotechnol
2012
, vol. 
30
 
11
(pg. 
1084
-
1094
)
8
McCarthy
 
JJ
McLeod
 
HL
Ginsburg
 
GS
 
Genomic medicine: a decade of successes, challenges, and opportunities. Sci Transl Med. 2013;5(189):189sr184
9
Kiezun
 
A
Garimella
 
K
Do
 
R
, et al. 
Exome sequencing and the genetic basis of complex traits.
Nat Genet
2012
, vol. 
44
 
6
(pg. 
623
-
630
)
10
Senapathy
 
P
Bhasi
 
A
Mattox
 
J
Dhandapany
 
PS
Sadayappan
 
S
Targeted genome-wide enrichment of functional regions.
PLoS ONE
2010
, vol. 
5
 
6
pg. 
e11138
 
11
Stitziel
 
NO
Kiezun
 
A
Sunyaev
 
S
Computational and statistical approaches to analyzing variants identified by exome sequencing.
Genome Biol
2011
, vol. 
12
 
9
pg. 
227
 
12
Biesecker
 
LG
Burke
 
W
Kohane
 
I
Plon
 
SE
Zimmern
 
R
Next-generation sequencing in the clinic: are we ready?
Nat Rev Genet
2012
, vol. 
13
 
11
(pg. 
818
-
824
)
13
Rehm
 
HL
Disease-targeted sequencing: a cornerstone in the clinic.
Nat Rev Genet
2013
, vol. 
14
 
4
(pg. 
295
-
300
)
14
Kee
 
Y
D’Andrea
 
AD
Molecular pathogenesis and clinical management of Fanconi anemia.
J Clin Invest
2012
, vol. 
122
 
11
(pg. 
3799
-
3806
)
15
Kottemann
 
MC
Smogorzewska
 
A
Fanconi anaemia and the repair of Watson and Crick DNA crosslinks.
Nature
2013
, vol. 
493
 
7432
(pg. 
356
-
363
)
16
Knies
 
K
Schuster
 
B
Ameziane
 
N
, et al. 
Genotyping of fanconi anemia patients by whole exome sequencing: advantages and challenges.
PLoS ONE
2012
, vol. 
7
 
12
pg. 
e52648
 
17
Schuster
 
B
Knies
 
K
Stoepker
 
C
, et al. 
Whole exome sequencing reveals uncommon mutations in the recently identified Fanconi anemia gene SLX4/FANCP.
Hum Mutat
2013
, vol. 
34
 
1
(pg. 
93
-
96
)
18
Shamseldin
 
HE
Elfaki
 
M
Alkuraya
 
FS
Exome sequencing reveals a novel Fanconi group defined by XRCC2 mutation.
J Med Genet
2012
, vol. 
49
 
3
(pg. 
184
-
186
)
19
Dobson-Stone
 
C
Danek
 
A
Rampoldi
 
L
, et al. 
Mutational spectrum of the CHAC gene in patients with chorea-acanthocytosis.
Eur J Hum Genet
2002
, vol. 
10
 
11
(pg. 
773
-
781
)
20
Hayflick
 
SJ
Westaway
 
SK
Levinson
 
B
, et al. 
Genetic, clinical, and radiographic delineation of Hallervorden-Spatz syndrome.
N Engl J Med
2003
, vol. 
348
 
1
(pg. 
33
-
40
)
21
Lee
 
S
The value of DNA analysis for antigens of the Kell and Kx blood group systems.
Transfusion
2007
, vol. 
47
 
suppl 1
(pg. 
32S
-
39S
)
22
Walker
 
RH
Schulz
 
VP
Tikhonova
 
IR
, et al. 
Genetic diagnosis of neuroacanthocytosis disorders using exome sequencing.
Mov Disord
2012
, vol. 
27
 
4
(pg. 
539
-
543
)
23
Cullinane
 
AR
Vilboux
 
T
O’Brien
 
K
, et al. 
NISC Comparative Sequencing Program
Homozygosity mapping and whole-exome sequencing to detect SLC45A2 and G6PC3 mutations in a single patient with oculocutaneous albinism and neutropenia.
J Invest Dermatol
2011
, vol. 
131
 
10
(pg. 
2017
-
2025
)
24
Fernandez
 
BA
Green
 
JS
Bursey
 
F
, et al. 
FORGE Canada Consortium
Adult siblings with homozygous G6PC3 mutations expand our understanding of the severe congenital neutropenia type 4 (SCN4) phenotype.
BMC Med Genet
2012
, vol. 
13
 pg. 
111
 
25
Weiss
 
MJ
Mason
 
PJ
Bessler
 
M
What’s in a name?
J Clin Invest
2012
, vol. 
122
 
7
(pg. 
2346
-
2349
)
26
Boria
 
I
Garelli
 
E
Gazda
 
HT
, et al. 
The ribosomal basis of Diamond-Blackfan anemia: mutation and database update.
Hum Mutat
2010
, vol. 
31
 
12
(pg. 
1269
-
1279
)
27
Gerrard
 
G
Valgañón
 
M
Foong
 
HE
, et al. 
Target enrichment and high-throughput sequencing of 80 ribosomal protein genes to identify mutations associated with Diamond-Blackfan anaemia.
Br J Haematol
2013
, vol. 
162
 
4
(pg. 
530
-
536
)
28
Sankaran
 
VG
Ghazvinian
 
R
Do
 
R
, et al. 
Exome sequencing identifies GATA1 mutations resulting in Diamond-Blackfan anemia.
J Clin Invest
2012
, vol. 
122
 
7
(pg. 
2439
-
2443
)
29
Campbell
 
AE
Wilkinson-White
 
L
Mackay
 
JP
Matthews
 
JM
Blobel
 
GA
Analysis of disease-causing GATA1 mutations in murine gene complementation systems.
Blood
2013
, vol. 
121
 
26
(pg. 
5218
-
5227
)
30
Finberg
 
KE
Heeney
 
MM
Campagna
 
DR
, et al. 
Mutations in TMPRSS6 cause iron-refractory iron deficiency anemia (IRIDA).
Nat Genet
2008
, vol. 
40
 
5
(pg. 
569
-
571
)
31
Khuong-Quang
 
DA
Schwartzentruber
 
J
Westerman
 
M
, et al. 
Iron refractory iron deficiency anemia: presentation with hyperferritinemia and response to oral iron therapy.
Pediatrics
2013
, vol. 
131
 
2
(pg. 
e620
-
e625
)
32
Rabbani
 
B
Mahdieh
 
N
Hosomichi
 
K
Nakaoka
 
H
Inoue
 
I
Next-generation sequencing: impact of exome sequencing in characterizing Mendelian disorders.
J Hum Genet
2012
, vol. 
57
 
10
(pg. 
621
-
632
)
33
Gallagher
 
PG
Disorders of red cell volume regulation.
Curr Opin Hematol
2013
, vol. 
20
 
3
(pg. 
201
-
207
)
34
Carella
 
M
Stewart
 
G
Ajetunmobi
 
JF
, et al. 
Genomewide search for dehydrated hereditary stomatocytosis (hereditary xerocytosis): mapping of locus to chromosome 16 (16q23-qter).
Am J Hum Genet
1998
, vol. 
63
 
3
(pg. 
810
-
816
)
35
Zarychanski
 
R
Schulz
 
VP
Houston
 
BL
, et al. 
Mutations in the mechanotransduction protein PIEZO1 are associated with hereditary xerocytosis.
Blood
2012
, vol. 
120
 
9
(pg. 
1908
-
1915
)
36
Albuisson
 
J
Murthy
 
SE
Bandell
 
M
, et al. 
Dehydrated hereditary stomatocytosis linked to gain-of-function mutations in mechanically activated PIEZO1 ion channels.
Nat Commun
2013
, vol. 
4
 pg. 
1884
 
37
Andolfo
 
I
Alper
 
SL
De Franceschi
 
L
, et al. 
 
Multiple clinical forms of dehydrated hereditary stomatocytosis arise from mutations in PIEZO1. Blood. 2013;121(19):3925-3935
38
Coste
 
B
Xiao
 
B
Santos
 
JS
, et al. 
Piezo proteins are pore-forming subunits of mechanically activated channels.
Nature
2012
, vol. 
483
 
7388
(pg. 
176
-
181
)
39
van der Harst
 
P
Zhang
 
W
Mateo Leach
 
I
, et al. 
Seventy-five genetic loci influencing the human red blood cell.
Nature
2012
, vol. 
492
 
7429
(pg. 
369
-
375
)
40
Stepensky
 
P
Saada
 
A
Cowan
 
M
, et al. 
The Thr224Asn mutation in the VPS45 gene is associated with the congenital neutropenia and primary myelofibrosis of infancy.
Blood
2013
, vol. 
121
 
25
(pg. 
5078
-
5087
)
41
Vilboux
 
T
Lev
 
A
Malicdan
 
MC
, et al. 
A congenital neutrophil defect syndrome associated with mutations in VPS45.
N Engl J Med
2013
, vol. 
369
 
1
(pg. 
54
-
65
)
42
Walne
 
AJ
Dokal
 
A
Plagnol
 
V
, et al. 
Exome sequencing identifies MPL as a causative gene in familial aplastic anemia.
Haematologica
2012
, vol. 
97
 
4
(pg. 
524
-
528
)
43
Kirwan
 
M
Walne
 
AJ
Plagnol
 
V
, et al. 
Exome sequencing identifies autosomal-dominant SRP72 mutations associated with familial aplasia and myelodysplasia.
Am J Hum Genet
2012
, vol. 
90
 
5
(pg. 
888
-
892
)
44
Walne
 
AJ
Vulliamy
 
T
Kirwan
 
M
Plagnol
 
V
Dokal
 
I
Constitutional mutations in RTEL1 cause severe dyskeratosis congenita.
Am J Hum Genet
2013
, vol. 
92
 
3
(pg. 
448
-
453
)
45
Ballew
 
BJ
Yeager
 
M
Jacobs
 
K
, et al. 
Germline mutations of regulator of telomere elongation helicase 1, RTEL1, in Dyskeratosis congenita.
Hum Genet
2013
, vol. 
132
 
4
(pg. 
473
-
480
)
46
Hsu
 
AP
Sampaio
 
EP
Khan
 
J
, et al. 
Mutations in GATA2 are associated with the autosomal dominant and sporadic monocytopenia and mycobacterial infection (MonoMAC) syndrome.
Blood
2011
, vol. 
118
 
10
(pg. 
2653
-
2655
)
47
Hahn
 
CN
Chong
 
CE
Carmichael
 
CL
, et al. 
Heritable GATA2 mutations associated with familial myelodysplastic syndrome and acute myeloid leukemia.
Nat Genet
2011
, vol. 
43
 
10
(pg. 
1012
-
1017
)
48
Ostergaard
 
P
Simpson
 
MA
Connell
 
FC
, et al. 
Mutations in GATA2 cause primary lymphedema associated with a predisposition to acute myeloid leukemia (Emberger syndrome).
Nat Genet
2011
, vol. 
43
 
10
(pg. 
929
-
931
)
49
Kazenwadel
 
J
Secker
 
GA
Liu
 
YJ
, et al. 
Loss-of-function germline GATA2 mutations in patients with MDS/AML or MonoMAC syndrome and primary lymphedema reveal a key role for GATA2 in the lymphatic vasculature.
Blood
2012
, vol. 
119
 
5
(pg. 
1283
-
1291
)
50
Hsu
 
AP
Johnson
 
KD
Falcone
 
EL
, et al. 
 
GATA2 haploinsufficiency caused by mutations in a conserved intronic element leads to MonoMAC syndrome. Blood. 2013;121(19):3830-3837
51
Pasquet
 
M
Bellanné-Chantelot
 
C
Tavitian
 
S
, et al. 
High frequency of GATA2 mutations in patients with mild chronic neutropenia evolving to MonoMac syndrome, myelodysplasia, and acute myeloid leukemia.
Blood
2013
, vol. 
121
 
5
(pg. 
822
-
829
)
52
Bhatnagar
 
P
Purvis
 
S
Barron-Casella
 
E
, et al. 
Genome-wide association study identifies genetic variants influencing F-cell levels in sickle-cell patients.
J Hum Genet
2011
, vol. 
56
 
4
(pg. 
316
-
323
)
53
Cole
 
JW
Stine
 
OC
Liu
 
X
, et al. 
Rare variants in ischemic stroke: an exome pilot study.
PLoS ONE
2012
, vol. 
7
 
4
pg. 
e35591
 
54
Dworkis
 
DA
Klings
 
ES
Solovieff
 
N
, et al. 
Severe sickle cell anemia is associated with increased plasma levels of TNF-R1 and VCAM-1.
Am J Hematol
2011
, vol. 
86
 
2
(pg. 
220
-
223
)
55
Milton
 
JN
Sebastiani
 
P
Solovieff
 
N
, et al. 
A genome-wide association study of total bilirubin and cholelithiasis risk in sickle cell anemia.
PLoS ONE
2012
, vol. 
7
 
4
pg. 
e34741
 
56
Sebastiani
 
P
Solovieff
 
N
Hartley
 
SW
, et al. 
Genetic modifiers of the severity of sickle cell anemia identified through a genome-wide association study.
Am J Hematol
2010
, vol. 
85
 
1
(pg. 
29
-
35
)
57
Nelson
 
MR
Wegmann
 
D
Ehm
 
MG
, et al. 
An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people.
Science
2012
, vol. 
337
 
6090
(pg. 
100
-
104
)
58
Tennessen
 
JA
Bigham
 
AW
O’Connor
 
TD
, et al. 
Broad GO; Seattle GO; NHLBI Exome Sequencing Project
Evolution and functional impact of rare coding variation from deep sequencing of human exomes.
Science
2012
, vol. 
337
 
6090
(pg. 
64
-
69
)
59
Coppola
 
G
Chinnathambi
 
S
Lee
 
JJ
, et al. 
Alzheimer’s Disease Genetics Consortium
Evidence for a role of the rare p.A152T variant in MAPT in increasing the risk for FTD-spectrum and Alzheimer’s diseases.
Hum Mol Genet
2012
, vol. 
21
 
15
(pg. 
3500
-
3512
)
60
Ji
 
W
Foo
 
JN
O’Roak
 
BJ
, et al. 
Rare independent mutations in renal salt handling genes contribute to blood pressure variation.
Nat Genet
2008
, vol. 
40
 
5
(pg. 
592
-
599
)
61
Cohen
 
JC
Kiss
 
RS
Pertsemlidis
 
A
Marcel
 
YL
McPherson
 
R
Hobbs
 
HH
Multiple rare alleles contribute to low plasma levels of HDL cholesterol.
Science
2004
, vol. 
305
 
5685
(pg. 
869
-
872
)
62
Romeo
 
S
Pennacchio
 
LA
Fu
 
Y
, et al. 
Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL.
Nat Genet
2007
, vol. 
39
 
4
(pg. 
513
-
516
)
63
Peters
 
LL
Lambert
 
AJ
Zhang
 
W
Churchill
 
GA
Brugnara
 
C
Platt
 
OS
Quantitative trait loci for baseline erythroid traits.
Mamm Genome
2006
, vol. 
17
 
4
(pg. 
298
-
309
)
64
Mahaney
 
MC
Brugnara
 
C
Lease
 
LR
Platt
 
OS
Genetic influences on peripheral blood cell counts: a study in baboons.
Blood
2005
, vol. 
106
 
4
(pg. 
1210
-
1214
)
65
Strzalkowska
 
A
Unrug-Bielawska
 
K
Bluszcz
 
A
, et al. 
Quantitative trait loci analysis for peripheral blood parameters in a (BALB/cW x C57BL/6J-Mpl (hlb219)/J) F(2) mice.
Exp Anim
2011
, vol. 
60
 
4
(pg. 
405
-
416
)
66
Soranzo
 
N
Spector
 
TD
Mangino
 
M
, et al. 
A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium.
Nat Genet
2009
, vol. 
41
 
11
(pg. 
1182
-
1190
)
67
Ferreira
 
MA
Hottenga
 
JJ
Warrington
 
NM
, et al. 
Sequence variants in three loci influence monocyte counts and erythrocyte volume.
Am J Hum Genet
2009
, vol. 
85
 
5
(pg. 
745
-
749
)
68
Galarneau
 
G
Palmer
 
CD
Sankaran
 
VG
Orkin
 
SH
Hirschhorn
 
JN
Lettre
 
G
Fine-mapping at three loci known to affect fetal hemoglobin levels explains additional genetic variation.
Nat Genet
2010
, vol. 
42
 
12
(pg. 
1049
-
1051
)
69
Auer
 
PL
Johnsen
 
JM
Johnson
 
AD
, et al. 
Imputation of exome sequence variants into population- based samples and blood-cell-trait-associated loci in African Americans: NHLBI GO Exome Sequencing Project.
Am J Hum Genet
2012
, vol. 
91
 
5
(pg. 
794
-
808
)
70
Cheung
 
YH
Wang
 
G
Leal
 
SM
Wang
 
S
A fast and noise-resilient approach to detect rare-variant associations with deep sequencing data for complex disorders.
Genet Epidemiol
2012
, vol. 
36
 
7
(pg. 
675
-
685
)
71
Worthey
 
EA
Mayer
 
AN
Syverson
 
GD
, et al. 
 
Making a definitive diagnosis: successful clinical application of whole exome sequencing in a child with intractable inflammatory bowel disease. Genet Med. 2011;13(3):255-262
72
Chen
 
R
Mias
 
GI
Li-Pook-Than
 
J
, et al. 
Personal omics profiling reveals dynamic molecular and medical phenotypes.
Cell
2012
, vol. 
148
 
6
(pg. 
1293
-
1307
)
73
Lyon
 
GJ
Jiang
 
T
Van Wijk
 
R
, et al. 
Exome sequencing and unrelated findings in the context of complex disease research: ethical and clinical implications.
Discov Med
2011
, vol. 
12
 
62
(pg. 
41
-
55
)
74
Cassa
 
CA
Savage
 
SK
Taylor
 
PL
Green
 
RC
McGuire
 
AL
Mandl
 
KD
Disclosing pathogenic genetic variants to research participants: quantifying an emerging ethical responsibility.
Genome Res
2012
, vol. 
22
 
3
(pg. 
421
-
428
)
75
Tabor
 
HK
Berkman
 
BE
Hull
 
SC
Bamshad
 
MJ
Genomics really gets personal: how exome and whole genome sequencing challenge the ethical framework of human genetics research.
Am J Med Genet A
2011
, vol. 
155A
 
12
(pg. 
2916
-
2924
)
76
Solomon
 
BD
Hadley
 
DW
Pineda-Alvarez
 
DE
, et al. 
 
Incidental medical information in whole-exome sequencing. Pediatrics. 2012;129(6):e1605-e1611
77
ACMG Board of Directors
Points to consider in the clinical application of genomic sequencing.
Genet Med
2012
, vol. 
14
 
8
(pg. 
759
-
761
)
78
Green
 
RC
Berg
 
JS
Grody
 
WW
, et al. 
ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing.
Genet Med
2013
, vol. 
15
 
7
(pg. 
565
-
574
)
79
Allyse
 
M
Michie
 
M
Not-so-incidental findings: the ACMG recommendations on the reporting of incidental findings in clinical whole genome and whole exome sequencing.
Trends Biotechnol
2013
, vol. 
31
 
8
(pg. 
439
-
441
)
80
Wolf
 
SM
Annas
 
GJ
Elias
 
S
Point-counterpoint. Patient autonomy and incidental findings in clinical genomics.
Science
2013
, vol. 
340
 
6136
(pg. 
1049
-
1050
)
81
McGuire
 
AL
Joffe
 
S
Koenig
 
BA
, et al. 
Point-counterpoint. Ethics and genomic incidental findings.
Science
2013
, vol. 
340
 
6136
(pg. 
1047
-
1048
)
82
Jacob
 
HJ
Abrams
 
K
Bick
 
DP
, et al. 
 
Genomics in clinical practice: lessons from the front lines. Sci Transl Med. 2013;5(194):194cm5
83
Lupski
 
JR
Reid
 
JG
Gonzaga-Jauregui
 
C
, et al. 
Whole-genome sequencing in a patient with Charcot-Marie-Tooth neuropathy.
N Engl J Med
2010
, vol. 
362
 
13
(pg. 
1181
-
1191
)
84
Kirby
 
A
Gnirke
 
A
Jaffe
 
DB
, et al. 
Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing.
Nat Genet
2013
, vol. 
45
 
3
(pg. 
299
-
303
)
85
Piton
 
A
Redin
 
C
Mandel
 
JL
XLID-causing mutations and associated genes challenged in light of data from large-scale human exome sequencing.
Am J Hum Genet
2013
, vol. 
pii
 pg. 
S0002-9297(13)00282-6
 
86
Cooper
 
DN
Krawczak
 
M
Polychronakos
 
C
Tyler-Smith
 
C
Kehrer-Sawatzki
 
H
Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease [published online ahead of print July 3, 2013].
Hum Genet
87
Xue
 
Y
Chen
 
Y
Ayub
 
Q
, et al. 
1000 Genomes Project Consortium
Deleterious- and disease-allele prevalence in healthy individuals: insights from current predictions, mutation databases, and population-scale resequencing.
Am J Hum Genet
2012
, vol. 
91
 
6
(pg. 
1022
-
1032
)

Author notes

V.G.S. and P.G.G. contributed equally to this review.