The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A review of the use of ribosomal DNA (rDNA) to differentiate among cryptic Anopheles species
Abstract
Cryptic species complexes are groups of closely related species that are difficult or impossible to distinguish by morphological traits. These complexes are known from a wide variety of arthropods and are common among the well‐studied, medically‐important insects. For example, many of the anopheline vectors of malaria parasites are members of cryptic species complexes. Complexes typically include both vector and non‐vector species, and two or more member species are often found sympatrically. Until the late 1950s, only two such Anopheles complexes were known, the A. gambiae complex from Africa and the A. maculipennis complex from Europe. Today, dozens of Anopheles cryptic species complexes are recognized, and accumulating evidence suggests that most important malaria vectors are likely to be members of such complexes. A variety of methods have been developed for identifying the species of individual specimens from these complexes, although until recently only those based on species‐specific allozymes and polytene chromosome inversions were widely used. The limitations inherent in these methods have been circumvented with DNA‐based procedures, which are especially useful because both sexes and all developmental stages can be identified, and DNA can be recovered from samples stored by a wide variety of simple methods. Several DNA‐based identification techniques have been developed, including hybridization assays based on species‐specific repeat sequences, and diagnostic PCR fragments produced either by the use of random PCR primers or by amplifying DNA with primers based on known species‐specific sequences. In this review we discuss the relative merits of different methods of cryptic species identification, with emphasis on the use of ribosomal DNA as a target for species‐diagnostic PCR assays.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Green, C. A., & Hunt, R. H. (1980) · Genetica · doi:10.1007/bf00121610 · Cited by 156
Cited by
Farajollahi, A., Fonseca, D. M., Kramer, L. D., & Marm Kilpatrick, A. (2011) · Infection, Genetics and Evolution · doi:10.1016/j.meegid.2011.08.013 · Cited by 659
Favia, G., Lanfrancotti, A., Spanos, L., Sidén‐Kiamos, I., & Louis, C. (2001) · Insect Molecular Biology · doi:10.1046/j.1365-2583.2001.00236.x · Cited by 278
Malaria in the Greater Mekong Subregion: heterogeneity and complexity.
Cui, L., Yan, G., Sattabongkot, J., Cao, Y., Chen, B., Chen, X., Fan, Q., Fang, Q., Jongwutiwes, S., Parker, D., et al. (2012) · Acta Tropica · doi:10.1016/j.actatropica.2011.02.016 · Cited by 277
Chen, X., Li, S., & Aksoy, S. (1999) · Journal of Molecular Evolution · doi:10.1007/pl00006444 · Cited by 277
The Population Genetics of Using Homing Endonuclease Genes in Vector and Pest Management
Deredec, A., Burt, A., & Godfray, H. C. J. (2008) · Genetics · doi:10.1534/genetics.108.089037 · Cited by 268
Metadata
- Authors
- Collins, F. H., & Paskewitz, S. M.
- Venue
- Insect Molecular Biology
- Publisher
- Wiley
- Published
- 1996-02
- Volume
- 5
- Issue
- 1
- Pages
- 1-9
- ISSN
- 0962-1075 (ISSN-L)
- 1365-2583
- OpenAlex
- W2074583233
- Cited by
- 399
- References
- 1
- FWCI
- 9.86
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A review of the use of ribosomal DNA (rDNA) to differentiate among cryptic Anopheles species. https://app.cochat.ai/papers/10.1111/j.1365-2583.1996.tb00034.x
- The paper
- Collins, F. H., & Paskewitz, S. M. (1996). A review of the use of ribosomal DNA (rDNA) to differentiate among cryptic Anopheles species. Insect Molecular Biology. https://doi.org/10.1111/j.1365-2583.1996.tb00034.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.