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Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure
Authors:Petri Kemppainen  Christopher G. Knight  Devojit K. Sarma  Thaung Hlaing  Anil Prakash  Yan Naung Maung Maung  Pradya Somboon  Jagadish Mahanta  Catherine Walton
Affiliation:1. Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK;2. Institute of Vertebrate Biology, Academy of Sciences of the Czech Republic, Brno, Czech Republic;3. Regional Medical Research Centre, NE (ICMR), Dibrugarh, India;4. Department of Medical Research (Lower Myanmar), Medical Entomology Research Division, Yangon, Myanmar;5. Department of Parasitology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
Abstract: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.
Keywords:   Anopheles dirus     Anopheles gambiae  chromosomal rearrangement  graph theory  landscape genomics  r package
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