Computational protocol: Loss of Genetic Diversity Means Loss of Geological Information: The Endangered Japanese Crayfish Exhibits Remarkable Historical Footprints

Similar protocols

Protocol publication

[…] We collected a total of 600 crayfish from 71 locations covering the entire native range, including two main islands (Hokkaido and Honshu) and five small islands near Hokkaido (Okushiri, Rishiri, Rebun, Teuri and Yagishiri, , ). No permission was required to collect the crayfish or to enter the public lands where the samples were collected. Because preliminary analysis showed low genetic diversity within and high diversity among locations (see Results), sampling effort was directed toward collecting from a larger number of locations rather than large numbers of individuals within locations to maximize information at the species level (average 8.5 individuals per location). Genetic diversity (i.e. number of haplotypes within populations) and genetic divergence (i.e. FST and Nei's DA) were calculated (see below) using only 51 locations where enough samples (≧ 5 individuals) were collected (average; 11.0 individuals per location, range; 5–30 individuals). Muscle tissue was taken from a chelipod or a pereiopod and stored in ethanol at −20°C until DNA extraction.Genomic DNA was extracted using Chelex100 (Bio-Rad, CA, USA) according to the manufacturer's instruction. A part of 16S rRNA mitochondrial DNA region was selected as a molecular marker because this appears to be the most powerful marker to identify inter- and intra-specific genetic diversity in freshwater crayfish –. A 490 base pair section of the 16S mtDNA was amplified by polymerase chain reaction (PCR) using primers 1471 (5′-CCTGTTTANCAAAAACAT-3′) and 1472 (5′-AGATAGAAACCAACCTGG-3′) . Amplifications were carried out in a thermal cycler (Perkin-Elmer, CA, USA) in 20 µl of reaction mixture containing 50 mM KCl, 1.5 mM MgCl2, 10 mM Tris-HCl (pH 8.3), 0.2 mM dNTP, 0.5 µM of each primer and 0.5 units of taq DNA polymerase (TaKaRa, Tokyo, Japan) with ca. 10 ng of genomic DNA. The thermal cycling parameters were as follows: 95°C/2 min for hot start, 36 cycles of dissociation (95°C/30 s), annealing (55°C/30 s) and extension (72°C/1 min), followed by a further extension (72°C/19 min). PCR products were purified with QIAquick™ PCR Purification Kit (Qiagen, CA, USA). These products were sequenced using 3100 Genetic Analizer ABI Prism (Applied Biosystem, CA, USA) and the BigDye Terminator Cycle Sequencing kit (Applied Biosystem, CA, USA). To investigate the congruence between different genes, the more conservative 28S rRNA gene region in nuclear DNA was also amplified for 55 subsamples from 52 locations covering the entire distributional range (). These samples were amplified using the primers rD4.8a (5′-ACCTATTCTCAAACTTTAAATGG-3′) and rD7b1 (5′-GACTTCCCTTACCTACAT-3′) with the following cyclic conditions: 95°C/2 min for hot start, 36 cycles of dissociation (95°C/1 min), annealing (50°C/1 min) and extension (72°C/1 min), followed by a further extension (72°C/5 min). Purification and sequencing were done in the same way as for the 16S mtDNA analysis.The sequences were aligned using ClustalX version 1.81 and BIOEDIT version 5.0.9 . Due to the extremely low diversity in 28S rRNA sequences, population genetic analysis was not performed except for describing a haplotype network (i.e. minimum spanning network) using ARLEQUIN version 2.001 . Therefore, the subsequent analyses were only performed using 16S mtDNA. Population differentiation was calculated as FST and Nei's DA, implemented in ARLEQUIN . These parameters were correlated with geographic (Euclidian) distance among populations to see whether dispersal is restricted (i.e. isolation-by-distance). Significance in the correlation analysis was evaluated by a Mantel test in FSTAT . A haplotype network was constructed based on the minimum spanning network using ARLEQUIN. Network loops were resolved based on the criterion of Crandall and Templeton and haplotype distributions. The haplotype network was then hierarchically nested following Templeton and Sing . We also tested for the effects of natural selection and/or past demographic change based on Tajima's D and mismatch distribution implemented in ARLEQUIN. If Tajima's D shows a negative value, stabilizing selection and/or rapid population expansion is suggested. A positive value, on the other hand, indicates balancing selection and/or population subdivision. A unimodal mismatch distribution, together with a negative Tajima's D, strengthens the inference of rapid population expansion. No significant deviation of Tajima's D interprets selective neutrality on mtDNA haplotypes.Patterns of colonization can be inferred once an ancestral population has been determined –. Slatkin mathematically formulated a stepwise colonization model derived from one proposed by David Good in his unpublished manuscript, which is qualitatively similar to the “stepping stone dispersal” model of Ponniah and Hughes . In Good's model, an ancestral population gives rise to one neighbouring population with the same allele frequency, and they are subsequently isolated (i.e. no gene flow following colonization). After a time, which allows the two populations to diverge, the new population itself gives rise to another population in the same manner. That is, a new population is colonized always from the adjacent (second newest) population. Under the gradual range expansion model, genetic divergence is expected to be higher among older populations than among more recent ones even over the same geographic distances. Unlike general isolation-by-distance patterns, Slatkin showed that estimated gene flow between a pair of populations (M), which is calculated from the inverse relationship with pairwise genetic divergence, i.e. M = (1/FST−1)/4, did not depend on geographic distance between the two populations. Instead, the pairwise gene flow was positively correlated with the distance between the ancestral population (i.e. the original area) and one of the populations closer to the ancestral population (i.e. older population of the pair). In other words, the level of gene flow would be higher when both populations are more distant from the ancestor (i.e. more recent). In this stepwise colonization process, therefore, genetic divergence should be negatively correlated with the distance from the ancestral population , , because of the inverse relationship between gene flow and divergence. In the present study, we plotted the distance from an ancestral population against Nei's genetic divergence DA, instead of M or FST, because M cannot be calculated when FST is zero and because FST ranges only from zero to one. Similarly, gene diversity should be negatively correlated with distance from the ancestral population, because intra-population genetic diversity should be higher in older populations than in more recently founded ones .We also developed a new graphical approach to investigate the colonization process in the Japanese crayfish. Based on coalescent theory, the relative ages of each haplotype can be compared within a haplotype network: interior haplotypes in a network should be older and tip haplotypes should be younger , . Therefore, after determining the relative ages of each haplotype from the network, distributions of each haplotype were projected on maps in the order of their estimated ages (i.e., from the ancestral haplotype to the most recent one with one mutation step in each projection). In other words, if 10 mutation steps separated the oldest and newest haplotypes, 10 maps were generated that represent the different ages for each haplotype. By looking at the distributions of old and recent haplotypes, the direct spread of haplotypes could be visualized. […]

Pipeline specifications

Software tools Clustal W, BioEdit, Arlequin
Application Population genetic analysis