Development of 13 microsatellites for Gunnison Sage-grouse (Centrocercus minimus) using next-generation shotgun sequencing and their utility in Greater Sage-grouse (Centrocercus urophasianus)

Fike, Jennifer A.; Oyler‐McCance, Sara J.; Zimmerman, Shawna J.; Castoe, Todd A.

doi:10.1007/s12686-014-0336-z

Cited by 10 publications

(4 citation statements)

References 5 publications

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“…To maximize the sequence information available for BLAST searches, we did not limit ourselves to the RAD-tag 'stack' sequences but instead assembled the combined paired-end data with Abyss (Simpson et al, 2009) using a hash length of 27. We also included whole-genome shotgun data from a previous 100-bp paired-end Illumina sequencing run of C. minimus that had been performed for microsatellite detection (Castoe et al, 2012;Fike et al, 2015). This run was assembled with CLC Genomics Workbench using automatic bubble sizes, a mismatch penalty of 2 and an indel penalty of 3.…”

Section: Discussionmentioning

confidence: 99%

Z chromosome divergence, polymorphism and relative effective population size in a genus of lekking birds

et al. 2015

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Sex chromosomes contribute disproportionately to species boundaries as they diverge faster than autosomes and often have reduced diversity. Their hemizygous nature contributes to faster divergence and reduced diversity, as do some types of selection. In birds, other factors (mating system and bottlenecks) can further decrease the effective population size of Z-linked loci and accelerate divergence (Fast-Z). We assessed Z-linked divergence and effective population sizes for two polygynous sage-grouse species and compared them to estimates from birds with various mating systems. We found lower diversity and higher F ST for Z-linked loci than for autosomes, as expected. The π Z /π A ratio was 0.38 in Centrocercus minimus, 0.48 in Centrocercus urophasianus and 0.59 in a diverged, parapatric population of C. urophasianus, a broad range given the mating system among these groups is presumably equivalent. The full data set had unequal males and females across groups, so we compared an equally balanced reduced set of C. minimus and individuals pooled from both C. urophasianus subgroups recovering similar estimates: 0.54 for C. urophasianus and 0.38 for C. minimus. We provide further evidence that N eZ /N eA in birds is often lower than expected under random mating or monogamy. The lower ratio in C. minimus could be a consequence of stronger selection or drift acting on Z loci during speciation, as this species differs strongly from C. urophasianus in sexually selected characters with minimal mitochondrial divergence. As C. minimus also exhibited lower genomic diversity, it is possible that a more severe demographic history may contribute to its lower ratio.

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Section: Discussionmentioning

confidence: 99%

Z chromosome divergence, polymorphism and relative effective population size in a genus of lekking birds

et al. 2015

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“…We amplified 22 grouse-specific microsatellite loci using the Polymerase Chain Reaction (PCR) and with the components and concentrations described in Oyler-McCance and Fike [90] with thermal profiles and annealing temperatures as originally published. The microsatellite primers used included: MSP11, MSP18, reSGCA5, reSGCA11, SG21, SG23, SG24, SG28, SG29, SG30, SG31, SG33, SG36, SG38, SG39, SGCTAT1, SGMS06.4, SGMS06.8, TTT3, TUT3, TUT4, and WYBG6 [91][92][93][94][95][96]. See Zimmerman et al [73] for details on DNA extraction and genotyping.…”

Section: Microsatellite Genotypesmentioning

confidence: 99%

An empirical comparison of population genetic analyses using microsatellite and SNP data for a species of conservation concern

2020

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Background Use of genomic tools to characterize wildlife populations has increased in recent years. In the past, genetic characterization has been accomplished with more traditional genetic tools (e.g., microsatellites). The explosion of genomic methods and the subsequent creation of large SNP datasets has led to the promise of increased precision in population genetic parameter estimates and identification of demographically and evolutionarily independent groups, as well as questions about the future usefulness of the more traditional genetic tools. At present, few empirical comparisons of population genetic parameters and clustering analyses performed with microsatellites and SNPs have been conducted. Results Here we used microsatellite and SNP data generated from Gunnison sage-grouse (Centrocercus minimus) samples to evaluate concordance of the results obtained from each dataset for common metrics of genetic diversity (HO, HE, FIS, AR) and differentiation (FST, GST, DJost). Additionally, we evaluated clustering of individuals using putatively neutral (SNPs and microsatellites), putatively adaptive, and a combined dataset of putatively neutral and adaptive loci. We took particular interest in the conservation implications of any differences. Generally, we found high concordance between microsatellites and SNPs for HE, FIS, AR, and all differentiation estimates. Although there was strong correlation between metrics from SNPs and microsatellites, the magnitude of the diversity and differentiation metrics were quite different in some cases. Clustering analyses also showed similar patterns, though SNP data was able to cluster individuals into more distinct groups. Importantly, clustering analyses with SNP data suggest strong demographic independence among the six distinct populations of Gunnison sage-grouse with some indication of evolutionary independence in two or three populations; a finding that was not revealed by microsatellite data. Conclusion We demonstrate that SNPs have three main advantages over microsatellites: more precise estimates of population-level diversity, higher power to identify groups in clustering methods, and the ability to consider local adaptation. This study adds to a growing body of work comparing the use of SNPs and microsatellites to evaluate genetic diversity and differentiation for a species of conservation concern with relatively high population structure and using the most common method of obtaining SNP genotypes for non-model organisms.

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“…Details on DNA extraction, microsatellite characterization, and duplicate sample elimination were previously published (Zimmerman et al, 2019). Samples were genotyped with 22 microsatellite loci (Caizergues et al, 2003; Fike et al, 2015; Oyler‐McCance & St. John, 2010; Piertney & Höglund, 2001; Segelbacher et al, 2000; Taylor et al, 2003), using polymerase chain reaction (PCR) with components and concentrations as described in Oyler‐McCance and Fike (2011) and thermal profiles as originally published. Duplicate noninvasive samples (Gunnison Basin only) were identified and removed using a combination of the R package allelematch (Galpern et al, 2012) and the stand‐alone program Dropout (McKelvey & Schwartz, 2005).…”

Section: Methodsmentioning

confidence: 99%

Scale‐dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage‐grouse

et al. 2022

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Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk.Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision-making. We used a landscape genetics approach implementing a recently developed statistical model based on the generalized Wishart probability distribution to identify the primary landscape features affecting gene flow and estimate the degree to which each component influences connectivity for Gunnison sage-grouse (Centrocercus minimus). We were interested in two spatial scales: among distinct populations rangewide and among leks (i.e., breeding grounds) within the largest population, Gunnison Basin. Populations and leks are nested within a landscape fragmented by rough terrain and anthropogenic features, although requisite sagebrush habitat is more contiguous within populations.Our best fit models for each scale confirm the importance of sagebrush habitat in connectivity, although the important sagebrush characteristics differ. For Gunnison Basin, taller shrubs and higher quality nesting habitat were the primary drivers of connectivity, while more sagebrush cover and less conifer cover facilitated connectivity rangewide. Our findings support previous assumptions that Gunnison sage-grouse range contraction is largely the result of habitat loss and degradation. Importantly, we report direct estimates of resistance for landscape components that can be used to create resistance surfaces for prioritization of specific locations for conservation or management (i.e., habitat preservation, restoration, or development) or as we demonstrated, can be combined with simulation techniques to predict impacts to connectivity from potential management actions.

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Development of 13 microsatellites for Gunnison Sage-grouse (Centrocercus minimus) using next-generation shotgun sequencing and their utility in Greater Sage-grouse (Centrocercus urophasianus)

Cited by 10 publications

References 5 publications

Z chromosome divergence, polymorphism and relative effective population size in a genus of lekking birds

Z chromosome divergence, polymorphism and relative effective population size in a genus of lekking birds

An empirical comparison of population genetic analyses using microsatellite and SNP data for a species of conservation concern

Scale‐dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage‐grouse

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