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

Sarma, Devojit Kumar; Prakash, Anil; OʼLoughlin, Samantha; Bhattacharyya, D. R.; Mohapatra, P. K.; Bhattacharjee, Kanta; Das, Kaushik; Singh, Sanatsujat; Sarma, N. P.; Ahmed, Gulzar; Walton, Catherine; Mahanta, Jagadish

doi:10.1186/1475-2875-11-76

Cited by 21 publications

(15 citation statements)

References 45 publications

(57 reference statements)

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“…From 2008 to 2012, Assam reported the maximum number of malaria cases, followed by Meghalaya. The maximum number of cases (91,413, Pf -66,557) in the study period was observed in Assam followed by Meghalaya (76,759) in 2009. In Assam, from 2009 onwards, there has been a steady decline in malaria cases, and in 2018, the number of cases recorded were 3816 (Pf -2859), below Tripura (13,079) and Meghalaya (6394).…”

Section: Malaria Epidemiology (2008 To 2018)mentioning

confidence: 87%

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Malaria in North-East India: Importance and Implications in the Era of Elimination

Sarma¹,

Mohapatra

Bhattacharyya

et al. 2019

Microorganisms

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Worldwide and in India, malaria elimination efforts are being ramped up to eradicate the disease by 2030. Malaria elimination efforts in North-East (NE) India will have a great bearing on the overall efforts to eradicate malaria in the rest of India. The first cases of chloroquine and sulfadoxine-pyrimethamine resistance were reported in NE India, and the source of these drug resistant parasites are most likely from South East Asia (SEA). NE India is the only land route through which the parasites from SEA can enter the Indian mainland. India’s malaria drug policy had to be constantly updated due to the emergence of drug resistant parasites in NE India. Malaria is highly endemic in many parts of NE India, and Plasmodium falciparum is responsible for the majority of the cases. Highly efficient primary vectors and emerging secondary vectors complicate malaria elimination efforts in NE India. Many of the high transmission zones in NE India are tribal belts, and are difficult to access. The review details the malaria epidemiology in seven NE Indian states from 2008 to 2018. In addition, the origin and evolution of resistance to major anti-malarials are discussed. Furthermore, the bionomics of primary vectors and emergence of secondary malaria vectors, and possible strategies to prevent and control malaria in NE are outlined.

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Section: Malaria Epidemiology (2008 To 2018)mentioning

confidence: 87%

“…Lack of an effective control strategy against An. baimaii is the major reason for its large population size (Ne), high genetic diversity and lack of population bottleneck in its evolutionary history in the NE [76]. The distribution of primary malaria vectors (An.…”

Section: Vectors Of Ne Indiamentioning

confidence: 99%

Malaria in North-East India: Importance and Implications in the Era of Elimination

Sarma¹,

Mohapatra

Bhattacharyya

et al. 2019

Microorganisms

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“… 2011 ; Sarma et al . 2012 ). Anopheles baimaii has a widespread distribution extending from northeast India, through Myanmar and into Thailand (Obsomer et al .…”

Section: Introductionmentioning

confidence: 99%

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions, local adaptation and geographic structure

Kemppainen

Knight

Sarma

et al. 2015

Molecular Ecology Resources

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140

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Recent advances in sequencing allow population-genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction-site-associated DNA sequence (RAD-seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well-characterized single nucleotide polymorphism (SNP) data set from 21 three-spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single-outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population-genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population-demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population-genomic data set, making it especially valuable for nonmodel species.

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“…The proportions of total genetic variance among and within populations were calculated by the analysis of molecular variance (AMOVA) framework in ARLEQUIN v3.5.2.2 (Excoffier and Lischer. 2010;Excoffier et al 1992), and the significance was tested by 1000 permutations (Sarma et al 2012;Shepherd et al 2016;Yu et al 2014…”

Section: Analysis Of Sequence Datamentioning

confidence: 99%

Genetic population variation and phylogeny ofSinomenium acutum(Menispermaceae) in subtropical China through chloroplast marker

Yang

Guo

et al. 2018

Preprint

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Sinomenium acutum (Menispermaceae) is a traditional Chinese medicine. In recent years, extensive harvesting for medicinal purposes has resulted in a sharp decline in its population. Genetic information is crucial for the proper exploitation and conservation of Sinomenium acutum, but little is known about it at present. In this study, we analyzed 77 samples from 4 populations using four non-coding regions (atpI-atpH, trnQ-5 ' rps16, trnH-psbA, and trnL-trnF) of chloroplast DNA and 14 haplotypes (from C1 to C14) were identified. C1 and C3 were common haplotypes, 2 which were shared by all populations, and C3 was an ancestral haplotype, the rest were rare haplotypes. Obvious phylogeographic structure was not existed inferred by G ST / N ST test. Mismatch distribution, Tajima's D and Fu's F S tests failed to support a rapid demographic expansion in Sinomenium acutum. AMOVA highlighted that the high level of genetic differentiation within population. Low genetic variation among populations illustrated gene flow was not restricted. Genetic diversity analyses demonstrated that the populations of Xuefeng, Dalou, and Daba Mountains were possible refugia localities of Sinomenium acutum. Based on this study, we proposed a preliminary protection strategy for it that C1, C3, C11 and C12 must be collected.These results offer an valuable and useful information for this species of population genetic study as well as further conservation.

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

Cited by 21 publications

References 45 publications

Malaria in North-East India: Importance and Implications in the Era of Elimination

Malaria in North-East India: Importance and Implications in the Era of Elimination

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions, local adaptation and geographic structure

Genetic population variation and phylogeny ofSinomenium acutum(Menispermaceae) in subtropical China through chloroplast marker

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