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

0440309 - ÚBO 2016 RIV GB eng J - Journal Article
Kemppainen, Petri - Knight, C. G. - Sarma, D. K. - Hlaing, T. - Prakash, A. - Maung, Y. N. M. - Somboon, P. - Mahanta, J. - Walton, C.
Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions, local adaptation and geographic structure.
Molecular Ecology Resources. Roč. 15, č. 5 (2015), s. 1031-1045. ISSN 1755-098X. E-ISSN 1755-0998
R&D Projects: GA MŠMT EE2.3.20.0303
Institutional support: RVO:68081766
Keywords : Anopheles dirus * Anopheles gambiae * chromosomal rearrangement * graph theory * landscape genomics * R package
Subject RIV: EB - Genetics ; Molecular Biology
Impact factor: 5.298, year: 2015

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.
Permanent Link: http://hdl.handle.net/11104/0243421