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Open Access Research

Genetic population structure of the malaria vector Anopheles baimaii in north-east India using mitochondrial DNA

Devojit K Sarma1, Anil Prakash1*, Samantha M O'Loughlin2, Dibya R Bhattacharyya1, Pradumnya K Mohapatra1, Kanta Bhattacharjee13, Kanika Das14, Sweta Singh1, Nilanju P Sarma1, Gias U Ahmed5, Catherine Walton6 and Jagadish Mahanta1

Author Affiliations

1 Regional Medical Research Centre, NE (ICMR), Dibrugarh-786001, Assam, India

2 Department of Ecology and Evolution, Imperial College London, Silwood Park SL5 7PY, UK

3 College of Veterinary Sciences, Assam Agriculture University, Guwahati-781022 Assam, India

4 Assam Agricultural University, Jorhat - 785013 Assam, India

5 Department of Biotechnology, Gauhati University, Guwahati-781014 Assam, India

6 Faculty of Life Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK

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Malaria Journal 2012, 11:76  doi:10.1186/1475-2875-11-76

Published: 20 March 2012

Abstract

Background

Anopheles baimaii is a primary vector of human malaria in the forest settings of Southeast Asia including the north-eastern region of India. Here, the genetic population structure and the basic population genetic parameters of An. baimaii in north-east India were estimated using DNA sequences of the mitochondrial cytochrome oxidase sub unit II (COII) gene.

Methods

Anopheles baimaii were collected from 26 geo-referenced locations across the seven north-east Indian states and the COII gene was sequenced from 176 individuals across these sites. Fifty-seven COII sequences of An. baimaii from six locations in Bangladesh, Myanmar and Thailand from a previous study were added to this dataset. Altogether, 233 sequences were grouped into eight population groups, to facilitate analyses of genetic diversity, population structure and population history.

Results

A star-shaped median joining haplotype network, unimodal mismatch distribution and significantly negative neutrality tests indicated population expansion in An. baimaii with the start of expansion estimated to be ~0.243 million years before present (MYBP) in north-east India. The populations of An. baimaii from north-east India had the highest haplotype and nucleotide diversity with all other populations having a subset of this diversity, likely as the result of range expansion from north-east India. The north-east Indian populations were genetically distinct from those in Bangladesh, Myanmar and Thailand, indicating that mountains, such as the Arakan mountain range between north-east India and Myanmar, are a significant barrier to gene flow. Within north-east India, there was no genetic differentiation among populations with the exception of the Central 2 population in the Barail hills area that was significantly differentiated from other populations.

Conclusions

The high genetic distinctiveness of the Central 2 population in the Barail hills area of the north-east India should be confirmed and its epidemiological significance further investigated. The lack of genetic population structure in the other north-east Indian populations likely reflects large population sizes of An. baimaii that, historically, were able to disperse through continuous forest habitats in the north-east India. Additional markers and analytical approaches are required to determine if recent deforestation is now preventing ongoing gene flow. Until such information is acquired, An. baimaii in north-east India should be treated as a single unit for the implementation of vector control measures.

Keywords:
Anopheles baimaii; Cytochrome oxidase II; Southeast Asia; Malaria vector; North-east India; Population genetics