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Comparative Genomic Hybridization

Genetics and Genomics · NLM MeSH · updated 2026-10-29 · version 1

Citations verified against PubMedNot yet clinician-reviewed10 referencesApproximately 5 min read

A method for comparing two sets of chromosomal DNA by analyzing differences in the copy number and location of specific sequences.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 4 complete abstracts (1,065 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

A method for comparing two sets of chromosomal DNA by analyzing differences in the copy number and location of specific sequences. It is used to look for large sequence changes such as deletions, duplications, amplifications, or translocations.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: Comparative Genomic Hybridizations; Genomic Hybridization, Comparative; Genomic Hybridizations, Comparative; Hybridization, Comparative Genomic; Hybridizations, Comparative Genomic; Comparative Genome Hybridization; Comparative Genome Hybridizations; Genome Hybridization, Comparative.

Where it fits in the MeSH classification

Broader topics
Cytogenetic Analysis; Molecular Diagnostic Techniques; Nucleic Acid Hybridization

Research landscape

PubMed indexes 7,024 records tagged with the MeSH heading “Comparative Genomic Hybridization” (counts retrieved 2026-10-29). 840 of them (12.0%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 5,376 records.

Reviews account for 559 records (8.0%) and meta-analyses for 19. Randomized controlled trials number 12 (0.2%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.

PubMed records by publication periodthrough 1999: 0 records; 2000-2009: 904 records; 2010-2019: 5,376 records; 2020 onward: 840 records0through 19999042000-20095,3762010-20198402020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 19990
2000-2009904
2010-20195,376
2020 onward840
Share of records by publication typeReviews: 8.0 percent; Meta-analyses: 0.3 percent; Randomized controlled trials: 0.2 percentReviews8.0% (559)Meta-analyses0.3% (19)Randomized controlled trials0.2% (12)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 7,024 PubMed records
TypeRecordsShare
Reviews5598.0%
Meta-analyses190.3%
Randomized controlled trials120.2%

Method: PubMed query "Comparative Genomic Hybridization"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.

Reading the evidence in genetics and genomics

Genetic findings vary widely in strength. A variant linked to a condition in one study may not replicate in other ancestries, and most common variants have small effects that are meaningful only in aggregate. Studies of rare, high-impact variants can support strong causal claims about a gene, while association studies describe statistical links that need functional and independent replication. Check the sample size, the ancestry of participants, whether results were replicated, and whether a laboratory or clinical outcome was actually measured.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
Genome-wide comparative analysis of atopic dermatitis and psoriasis gives insight into opposing genetic mechanisms
Baurecht H, Hotze M, Brand S, Büning C, Cormican P, Corvin A, et al.
2015Research article
Design not recorded in structured metadata
153cc by
PMID 25574825 · DOI · PMC4289690
Comparative genomics reveals diversity among xanthomonads infecting tomato and pepper
Potnis N, Krasileva K, Chow V, Almeida NF, Patil PB, Ryan RP, et al.
2011Research article
Design not recorded in structured metadata
146cc by
PMID 21396108 · DOI · PMC3071791
Identification of the pangenome and its components in 14 distinct Aggregatibacter actinomycetemcomitans strains by comparative genomic analysis
Kittichotirat W, Bumgarner RE, Asikainen S, Chen C
2011Research article
Design not recorded in structured metadata
68cc by
PMID 21811606 · DOI · PMC3139650
Diagnostic yield of array-CGH in children with suspected rare disease
Criado-Muriel MC, Arroyo-Ruiz R, Marcos-Vadillo E, Justel-Rodriguez M, Alcubilla-García L, Isidoro-García M, et al.
2025Research article
Design not recorded in structured metadata
0cc by
PMID 40997921 · DOI · PMC12556180

Genome-wide comparative analysis of atopic dermatitis and psoriasis gives insight into opposing genetic mechanisms [1]

Research article Baurecht H, Hotze M, Brand S, Büning C, Cormican P, Corvin A, et al. · · 2015 · cited 153 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Atopic dermatitis and psoriasis are the two most common immune-mediated inflammatory disorders affecting the skin.
Closing excerpt
The approach is likely to be applicable to the investigation of the genetic basis of other complex traits with overlapping and distinct clinical features.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (208 words)

Atopic dermatitis and psoriasis are the two most common immune-mediated inflammatory disorders affecting the skin. Genome-wide studies demonstrate a high degree of genetic overlap, but these diseases have mutually exclusive clinical phenotypes and opposing immune mechanisms. Despite their prevalence, atopic dermatitis and psoriasis very rarely co-occur within one individual. By utilizing genome-wide association study and ImmunoChip data from >19,000 individuals and methodologies developed from meta-analysis, we have identified opposing risk alleles at shared loci as well as independent disease-specific loci within the epidermal differentiation complex (chromosome 1q21.3), the Th2 locus control region (chromosome 5q31.1), and the major histocompatibility complex (chromosome 6p21-22). We further identified previously unreported pleiotropic alleles with opposing effects on atopic dermatitis and psoriasis risk in PRKRA and ANXA6/TNIP1. In contrast, there was no evidence for shared loci with effects operating in the same direction on both diseases. Our results show that atopic dermatitis and psoriasis have distinct genetic mechanisms with opposing effects in shared pathways influencing epidermal differentiation and immune response. The statistical analysis methods developed in the conduct of this study have produced additional insight from previously published data sets. The approach is likely to be applicable to the investigation of the genetic basis of other complex traits with overlapping and distinct clinical features.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 25574825 · DOI · PMC4289690

Comparative genomics reveals diversity among xanthomonads infecting tomato and pepper [2]

Research article Potnis N, Krasileva K, Chow V, Almeida NF, Patil PB, Ryan RP, et al. · · 2011 · cited 146 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundBacterial spot of tomato and pepper is caused by four Xanthomonas species and is a major plant disease in warm humid climates.
Closing excerpt
These analyses will aid in efforts towards breeding for broad and durable resistance in economically important tomato and pepper cultivars.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (337 words)

BackgroundBacterial spot of tomato and pepper is caused by four Xanthomonas species and is a major plant disease in warm humid climates. The four species are distinct from each other based on physiological and molecular characteristics. The genome sequence of strain 85-10, a member of one of the species, Xanthomonas euvesicatoria (Xcv) has been previously reported. To determine the relationship of the four species at the genome level and to investigate the molecular basis of their virulence and differing host ranges, draft genomic sequences of members of the other three species were determined and compared to strain 85-10.ResultsWe sequenced the genomes of X. vesicatoria (Xv) strain 1111 (ATCC 35937), X. perforans (Xp) strain 91-118 and X. gardneri (Xg) strain 101 (ATCC 19865). The genomes were compared with each other and with the previously sequenced Xcv strain 85-10. In addition, the molecular features were predicted that may be required for pathogenicity including the type III secretion apparatus, type III effectors, other secretion systems, quorum sensing systems, adhesins, extracellular polysaccharide, and lipopolysaccharide determinants. Several novel type III effectors from Xg strain 101 and Xv strain 1111 genomes were computationally identified and their translocation was validated using a reporter gene assay. A homolog to Ax21, the elicitor of XA21-mediated resistance in rice, and a functional Ax21 sulfation system were identified in Xcv. Genes encoding proteins with functions mediated by type II and type IV secretion systems have also been compared, including enzymes involved in cell wall deconstruction, as contributors to pathogenicity.ConclusionsComparative genomic analyses revealed considerable diversity among bacterial spot pathogens, providing new insights into differences and similarities that may explain the diverse nature of these strains. Genes specific to pepper pathogens, such as the O-antigen of the lipopolysaccharide cluster, and genes unique to individual strains, such as novel type III effectors and bacteriocin genes, have been identified providing new clues for our understanding of pathogen virulence, aggressiveness, and host preference. These analyses will aid in efforts towards breeding for broad and durable resistance in economically important tomato and pepper cultivars.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 21396108 · DOI · PMC3071791

Identification of the pangenome and its components in 14 distinct Aggregatibacter actinomycetemcomitans strains by comparative genomic analysis [3]

Research article Kittichotirat W, Bumgarner RE, Asikainen S, Chen C · · 2011 · cited 68 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundAggregatibacter actinomycetemcomitans is genetically heterogeneous and comprises distinct clonal lineages that may have different virulence potentials.
Closing excerpt
actinomycetemcomitans strains.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (275 words)

BackgroundAggregatibacter actinomycetemcomitans is genetically heterogeneous and comprises distinct clonal lineages that may have different virulence potentials. However, limited information of the strain-to-strain genomic variations is available.Methodology/principal findingsThe genome sequences of 11 A. actinomycetemcomitans strains (serotypes a-f) were generated de novo, annotated and combined with three previously sequenced genomes (serotypes a-c) for comparative genomic analysis. Two major groups were identified; serotypes a, d, e, and f, and serotypes b and c. A serotype e strain was found to be distinct from both groups. The size of the pangenome was 3,301 genes, which included 2,034 core genes and 1,267 flexible genes. The number of core genes is estimated to stabilize at 2,060, while the size of the pangenome is estimated to increase by 16 genes with every additional strain sequenced in the future. Within each strain 16.7-29.4% of the genome belonged to the flexible gene pool. Between any two strains 0.4-19.5% of the genomes were different. The genomic differences were occasionally greater for strains of the same serotypes than strains of different serotypes. Furthermore, 171 genomic islands were identified. Cumulatively, 777 strain-specific genes were found on these islands and represented 61% of the flexible gene pool.Conclusions/significanceSubstantial genomic differences were detected among A. actinomycetemcomitans strains. Genomic islands account for more than half of the flexible genes. The phenotype and virulence of A. actinomycetemcomitans may not be defined by any single strain. Moreover, the genomic variation within each clonal lineage of A. actinomycetemcomitans (as defined by serotype grouping) may be greater than between clonal lineages. The large genomic data set in this study will be useful to further examine the molecular basis of variable virulence among A. actinomycetemcomitans strains.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 21811606 · DOI · PMC3139650

Diagnostic yield of array-CGH in children with suspected rare disease [4]

Research article Criado-Muriel MC, Arroyo-Ruiz R, Marcos-Vadillo E, Justel-Rodriguez M, Alcubilla-García L, Isidoro-García M, et al. · · 2025

Abstract reading summary — source excerpts
Opening excerpt
ObjectiveThis study aims to analyze the diagnostic yield of aCGH in pediatric patients with suspected rare diseases, focusing on its diagnostic value and effectiveness depending on different clinical symptoms.
Closing excerpt
This technique enables earlier diagnosis, improves clinical management, and provides better counseling for affected families.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (245 words)

ObjectiveThis study aims to analyze the diagnostic yield of aCGH in pediatric patients with suspected rare diseases, focusing on its diagnostic value and effectiveness depending on different clinical symptoms.MethodsThis observational study analyzed 600 aCGH tests performed in a pediatric unit (2018-2022) for patients with suspected rare diseases. DNA was extracted from peripheral blood; aCGH resolution was adjusted to clinical features. CNVs were classified per international guidelines. Forty sociodemographic, clinical, and genetic variables were analyzed using IBM SPSS v.26.ResultsOf the 600 patients analyzed, 543 were included in the final study. The median age was 4.7 years (IQR: 6.36 years), and 66.3% were male. Most referrals came from pediatric neurology (84.3%), and the most common clinical manifestations were altered phenotype (38.6%), autism spectrum disorder (ASD) (38.6%), dysmorphia (28.2%), global developmental delay (GDD) (27.1%), and intellectual disability (21.0%). Among 543 patients, 30.4% presented CNVs, with 12.4% identified as pathogenic and 18.1% as variants of uncertain significance. Diagnostic yield was 12.2%, with 66 conclusive results - 90.9% of which were pathogenic. CNVs were most frequently detected on chromosomes 15 and 16. The highest yield was observed in clinical features such as coordination problems (35.7%), learning disorders (28.6%), and microcephaly (22.6%).ConclusionThe diagnostic yield of aCGH in this study was 12.2%. The test demonstrated higher diagnostic value in patients with multiple clinical manifestations, highlighting the importance of aCGH as a first-line diagnostic tool for rare diseases. This technique enables earlier diagnosis, improves clinical management, and provides better counseling for affected families.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40997921 · DOI · PMC12556180

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article Prenatal diagnosis by chromosomal microarray analysis [5]
    Levy B, Wapner R · Fertil Steril · 2018 · cited 257 times (Europe PMC)
  • Research article ACMG Standards and Guidelines for constitutional cytogenomic microarray analysis, including postnatal and prenatal applications: revision 2013 [6]
    South ST, Lee C, Lamb AN, Higgins AW, Kearney HM, Working Group for the American College of Medical Genetics and Genomics Laboratory Quality Assurance Committee · Genet Med · 2013 · cited 250 times (Europe PMC)
  • Research article Additional information from array comparative genomic hybridization technology over conventional karyotyping in prenatal diagnosis: a systematic review and meta-analysis [7]
    Hillman SC, Pretlove S, Coomarasamy A, McMullan DJ, Davison EV, Maher ER, et al. · Ultrasound Obstet Gynecol · 2011 · cited 174 times (Europe PMC)
  • Research article Array CGH in patients with learning disability (mental retardation) and congenital anomalies: updated systematic review and meta-analysis of 19 studies and 13,926 subjects [8]
    Sagoo GS, Butterworth AS, Sanderson S, Shaw-Smith C, Higgins JP, Burton H · Genet Med · 2009 · cited 151 times (Europe PMC)
  • Research article Circulating tumor cells: advances in detection methods, biological issues, and clinical relevance [9]
    Sun YF, Yang XR, Zhou J, Qiu SJ, Fan J, Xu Y · J Cancer Res Clin Oncol · 2011 · cited 130 times (Europe PMC)
  • Research article Array comparative genomic hybridization and fetal congenital heart defects: a systematic review and meta-analysis [10]
    Jansen FA, Blumenfeld YJ, Fisher A, Cobben JM, Odibo AO, Borrell A, et al. · Ultrasound Obstet Gynecol · 2015 · cited 80 times (Europe PMC)

References

  1. Baurecht H, Hotze M, Brand S, Büning C, Cormican P, Corvin A, et al.. Genome-wide comparative analysis of atopic dermatitis and psoriasis gives insight into opposing genetic mechanisms. . 2015. PMID 25574825 · DOI · PMC4289690
  2. Potnis N, Krasileva K, Chow V, Almeida NF, Patil PB, Ryan RP, et al.. Comparative genomics reveals diversity among xanthomonads infecting tomato and pepper. . 2011. PMID 21396108 · DOI · PMC3071791
  3. Kittichotirat W, Bumgarner RE, Asikainen S, Chen C. Identification of the pangenome and its components in 14 distinct Aggregatibacter actinomycetemcomitans strains by comparative genomic analysis. . 2011. PMID 21811606 · DOI · PMC3139650
  4. Criado-Muriel MC, Arroyo-Ruiz R, Marcos-Vadillo E, Justel-Rodriguez M, Alcubilla-García L, Isidoro-García M, et al.. Diagnostic yield of array-CGH in children with suspected rare disease. . 2025. PMID 40997921 · DOI · PMC12556180
  5. Levy B, Wapner R. Prenatal diagnosis by chromosomal microarray analysis. Fertil Steril. 2018. PMID 29447663 · DOI · PMC5856154
  6. South ST, Lee C, Lamb AN, Higgins AW, Kearney HM, Working Group for the American College of Medical Genetics and Genomics Laboratory Quality Assurance Committee. ACMG Standards and Guidelines for constitutional cytogenomic microarray analysis, including postnatal and prenatal applications: revision 2013. Genet Med. 2013. PMID 24071793 · DOI
  7. Hillman SC, Pretlove S, Coomarasamy A, McMullan DJ, Davison EV, Maher ER, et al.. Additional information from array comparative genomic hybridization technology over conventional karyotyping in prenatal diagnosis: a systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2011. PMID 20658510 · DOI
  8. Sagoo GS, Butterworth AS, Sanderson S, Shaw-Smith C, Higgins JP, Burton H. Array CGH in patients with learning disability (mental retardation) and congenital anomalies: updated systematic review and meta-analysis of 19 studies and 13,926 subjects. Genet Med. 2009. PMID 19367186 · DOI
  9. Sun YF, Yang XR, Zhou J, Qiu SJ, Fan J, Xu Y. Circulating tumor cells: advances in detection methods, biological issues, and clinical relevance. J Cancer Res Clin Oncol. 2011. PMID 21681690 · DOI · PMC11828336
  10. Jansen FA, Blumenfeld YJ, Fisher A, Cobben JM, Odibo AO, Borrell A, et al.. Array comparative genomic hybridization and fetal congenital heart defects: a systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2015. PMID 25319878 · DOI

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-10-29.

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Evidence strength

EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.

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Related research topics

  • In Situ HybridizationGenetics and Genomics
  • Cytogenetic AnalysisGenetics and Genomics
  • Genomic LibraryGenetics and Genomics
  • Gene EditingGenetics and Genomics
  • Genetic LociGenetics and Genomics
  • Genomic ImprintingGenetics and Genomics

All 95 articles in Genetics and Genomics →

At a glance

7,024
PubMed records on this heading
12%
published since 2020
559
review articles
12
randomized trials
10
verified references below

Counts come from PubMed on 2026-10-29; they show how much has been written, not how strong the evidence is.

Related topics See all →

  • In Situ HybridizationGenetics and Genomics
  • Cytogenetic AnalysisGenetics and Genomics
  • Genomic LibraryGenetics and Genomics
  • Gene EditingGenetics and Genomics
  • Genetic LociGenetics and Genomics

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