Phylogenetic resolution power of microsatellites and various single-nucleotide polymorphism types assessed in 10 divergent chicken populations

Genetic diversity and population genetic structure of Cambodian indigenous chickens

Objective

Cambodia is located within the distribution range of the red junglefowl, the common ancestor of domestic chickens. Although a variety of indigenous chickens have been reared in Cambodia since ancient times, their genetic characteristics have yet to be sufficiently defined. Here, we conducted a large-scale population genetic study to investigate the genetic diversity and population genetic structure of Cambodian indigenous chickens and their phylogenetic relationships with other chicken breeds and native chickens worldwide.

Methods

A Bayesian phylogenetic tree was constructed based on 625 mitochondrial DNA D-loop sequences, and Bayesian clustering analysis was performed for 666 individuals with 23 microsatellite markers, using samples collected from 28 indigenous chicken populations in 24 provinces and three commercial chicken breeds.

Results

A total of 92 haplotypes of mitochondrial D-loop sequences belonging to haplogroups A to F and J were detected in Cambodian chickens; in the indigenous chickens, haplogroup D (44.4%) was the most common, and haplogroups A (21.0%) and B (13.2%) were also dominant. However, haplogroup J, which is rare in domestic chickens but abundant in Thai red junglefowl, was found at a high frequency (14.5%), whereas the frequency of haplogroup E was considerably lower (4.6%). Population genetic structure analysis based on microsatellite markers revealed the presence of three major genetic clusters in Cambodian indigenous chickens. Their genetic diversity was relatively high, which was similar to findings reported for indigenous chickens from other Southeast Asian countries.

Conclusion

Cambodian indigenous chickens are characterized by mitochondrial D-loop haplotypes that are common to indigenous chickens throughout Southeast Asia, and may retain many of the haplotypes that originated from wild ancestral populations. These chickens exhibit high population genetic diversity, and the geographical distribution of three major clusters may be attributed to inter-regional trade and poultry transportation routes within Cambodia or international movement between Cambodia and other countries.

Distinguishing industrial meat from that of indigenous chickens with molecular markers

The aim of investigation was to evaluate a traceability system to detect industrial chicken meat among indigenous products, considering issues that could affect assignment accuracy. The dataset included 2 Italian indigenous meat breeds, namely Bionda Piemontese (2 ecotypes) and Bianca di Saluzzo, one broiler line, and 3 layer lines. Assignment tests were performed using a standard panel of 28 microsatellite loci. To evaluate effects of inbreeding and substructure on assignment accuracy, a simulated dataset was prepared. Broilers and layers belong to homogeneous populations and never enter the clusters of indigenous breeds. Ambiguity or misallocation are expected between the Bionda ecotypes and between the 2 indigenous breeds, but it is unlikely that niche products provided by Bionda and Bianca will compete with one another. Non-random mating reduces accuracy, but only populations having weak genetic differentiation are involved, namely those that are less interesting to discriminate. The dataset can be used as a reference population to distinguish commercial meat from indigenous meat with great accuracy. Misallocations increase as number of loci decreases, but only within or between the indigenous breeds. A subpanel of the most resolving 14 loci keeps sufficient informative content to provide accuracy and to correctly allocate additional test samples within the reference population. This analytical tool is economically sustainable as a method to detect fraud or mislabeling. Adoption of a monitoring system should increase the value of typical products because the additional burden of molecular analyses would improve commercial grade and perception of quality.

Development and evaluation of 16 new microsatellite loci for the rock ptarmigan (Lagopus muta) and cross-species amplification for the willow grouse (L. lagopus)

Abstract

The genetic markers designed for this study can facilitate future genetic studies on the rock ptarmigan (Lagopus muta). To our knowledge no microsatellite markers have ever been developed specifically for this species before. These new microsatellite markers will be useful for population genetics studies and for future conservation projects.

Results

Using Next Generation Sequencing 6252 potential microsatellite sequences were found. Sixteen nonpalindromic tetranucleotide microsatellites and their respective primers were selected. The markers were tested on both the rock ptarmigan and the willow grouse (L. lagopus). The number of alleles varied between 2 and 18 for the rock ptarmigan, and between 3 and 13 for the willow grouse. Expected heterozygosity was in the range 0.1244–0.8692 and 0.1358–0.8722 for the rock ptarmigan and the willow grouse, respectively.

Global genotype flow in Cercospora beticola populations confirmed through genotyping-by-sequencing

Genotyping-by-sequencing (GBS) was conducted on 333 Cercospora isolates collected from Beta vulgaris (sugar beet, table beet and swiss chard) in the USA and Europe. Cercospora beticola was confirmed as the species predominantly isolated from leaves with Cercospora leaf spot (CLS) symptoms. However, C. cf. flagellaris also was detected at a frequency of 3% in two table beet fields in New York. Resolution of the spatial structure and identification of clonal lineages in C. beticola populations using genome-wide single nucleotide polymorphisms (SNPs) obtained from GBS was compared to genotyping using microsatellites. Varying distance thresholds (bitwise distance = 0, 1.854599 × 10-4, and 1.298 × 10-3) were used for delineation of clonal lineages in C. beticola populations. Results supported previous reports of long distance dispersal of C. beticola through genotype flow. The GBS-SNP data set provided higher resolution in discriminating clonal lineages; however, genotype identification was impacted by filtering parameters and the distance threshold at which the multi-locus genotypes (MLGs) were contracted to multi-locus lineages. The type of marker or different filtering strategies did not impact estimates of population differentiation and structure. Results emphasize the importance of robust filtering strategies and designation of distance thresholds for delineating clonal lineages in population genomics analyses that depend on individual assignment and identification of clonal lineages. Detection of recurrent clonal lineages shared between the USA and Europe, even in the relaxed-filtered SNP data set and with a conservative distance threshold for contraction of MLGs, provided strong evidence for global genotype flow in C. beticola populations. The implications of intercontinental migration in C. beticola populations for CLS management are discussed.

Estimating genomic diversity and population differentiation - an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri

BACKGROUND

Microsatellite markers are widely used for estimating genetic diversity within and differentiation among populations. However, it has rarely been tested whether such estimates are useful proxies for genome-wide patterns of variation and differentiation. Here, we compared microsatellite variation with genome-wide single nucleotide polymorphisms (SNPs) to assess and quantify potential marker-specific biases and derive recommendations for future studies. Overall, we genotyped 180 Arabidopsis halleri individuals from nine populations using 20 microsatellite markers. Twelve of these markers were originally developed for Arabidopsis thaliana (cross-species markers) and eight for A. halleri (species-specific markers). We further characterized 2 million SNPs across the genome with a pooled whole-genome re-sequencing approach (Pool-Seq).

RESULTS

Our analyses revealed that estimates of genetic diversity and differentiation derived from cross-species and species-specific microsatellites differed substantially and that expected microsatellite heterozygosity (SSR-H e) was not significantly correlated with genome-wide SNP diversity estimates (SNP-H e and θ Watterson) in A. halleri. Instead, microsatellite allelic richness (A r) was a better proxy for genome-wide SNP diversity. Estimates of genetic differentiation among populations (F ST) based on both marker types were correlated, but microsatellite-based estimates were significantly larger than those from SNPs. Possible causes include the limited number of microsatellite markers used, marker ascertainment bias, as well as the high variance in microsatellite-derived estimates. In contrast, genome-wide SNP data provided unbiased estimates of genetic diversity independent of whether genome- or only exome-wide SNPs were used. Further, we inferred that a few thousand random SNPs are sufficient to reliably estimate genome-wide diversity and to distinguish among populations differing in genetic variation.

CONCLUSIONS

We recommend that future analyses of genetic diversity within and differentiation among populations use randomly selected high-throughput sequencing-based SNP data to draw conclusions on genome-wide diversity patterns. In species comparable to A. halleri, a few thousand SNPs are sufficient to achieve this goal.

Revealing hidden species diversity in closely related species using nuclear SNPs, SSRs and DNA sequences - a case study in the tree genus Milicia

Background

Species delimitation in closely related plant taxa can be challenging because (i) reproductive barriers are not always congruent with morphological differentiation, (ii) use of plastid sequences might lead to misinterpretation, (iii) rare species might not be sampled. We revisited molecular-based species delimitation in the African genus Milicia, currently divided into M. regia (West Africa) and M. excelsa (from West to East Africa). We used 435 samples collected in West, Central and East Africa. We genotyped SNP and SSR loci to identify genetic clusters, and sequenced two plastid regions (psbA-trnH, trnC-ycf6) and a nuclear gene (At103) to confirm species’ divergence and compare species delimitation methods. We also examined whether ecological niche differentiation was congruent with sampled genetic structure.

Results

West African M. regia, West African and East African M. excelsa samples constituted three well distinct genetic clusters according to SNPs and SSRs. In Central Africa, two genetic clusters were consistently inferred by both types of markers, while a few scattered samples, sympatric with the preceding clusters but exhibiting leaf traits of M. regia, were grouped with the West African M. regia cluster based on SNPs or formed a distinct cluster based on SSRs. SSR results were confirmed by sequence data from the nuclear region At103 which revealed three distinct ‘Fields For Recombination’ corresponding to (i) West African M. regia, (ii) Central African samples with leaf traits of M. regia, and (iii) all M. excelsa samples. None of the plastid sequences provide indication of distinct clades of the three species-like units. Niche modelling techniques yielded a significant correlation between niche overlap and genetic distance.

Conclusions

Our genetic data suggest that three species of Milicia could be recognized. It is surprising that the occurrence of two species in Central Africa was not reported for this well-known timber tree. Globally, our work highlights the importance of collecting samples in a systematic way and the need for combining different nuclear markers when dealing with species complexes. Recognizing cryptic species is particularly crucial for economically exploited species because some hidden taxa might actually be endangered as they are merged with more abundant species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0831-9) contains supplementary material, which is available to authorized users.

Genetic variability of two Italian indigenous chicken breeds inferred from microsatellite marker analysis

The objective of this study was to determine the genetic structure and variability of Bionda Piemontese and Bianca di Saluzzo (Piedmont, Northwest Italy) using an international set of microsatellite loci (AVIANDIV-FAO). Differences compared with commercial lines and other Italian breeds were verified to justify the implementation of conservation programmes. Flock contribution to genetic variability was assessed following the approach implemented in the MolKin software. Comparison was performed using the fixation index and the Reynolds genetic distance. The most likely number of different populations was estimated using the clustering procedure implemented in STRUCTURE. The molecular information suggests that management practices could have prevented random mating and produced inbreeding and heterogeneity across flocks. In this respect, Bionda and Bianca show substructuring and are more similar to British breeds than other continental European breeds. Bionda and Bianca fit into the European breeds provided with the highest number of alleles and expected heterozygosity. There is a clear distinction between the Piedmont breeds and the other populations. The Piedmont poultry differ from both commercial lines and other Italian breeds and retain a high level of genetic variability. As for other indigenous breeds, Bionda and Bianca could make an original contribution to the industry in the future. A collective planned approach to restoration is essential, because the flocks are managed with poor regulation. Enhancing connection between breeders with an efficient replacement interchange and mating plan is the right way of controlling inbreeding, preventing substructuring and increasing variability within the flocks.

Developing informative microsatellite markers for non-model species using reference mapping against a model species' genome

Microsatellites have a wide range of applications from behavioral biology, evolution, to agriculture-based breeding programs. The recent progress in the next-generation sequencing technologies and the rapidly increasing number of published genomes may greatly enhance the current applications of microsatellites by turning them from anonymous to informative markers. Here we developed an approach to anchor microsatellite markers of any target species in a genome of a related model species, through which the genomic locations of the markers, along with any functional genes potentially linked to them, can be revealed. We mapped the shotgun sequence reads of a non-model rodent species Apodemus semotus against the genome of a model species, Mus musculus, and presented 24 polymorphic microsatellite markers with detailed background information for A. semotus in this study. The developed markers can be used in other rodent species, especially those that are closely related to A. semotus or M. musculus. Compared to the traditional approaches based on DNA cloning, our approach is likely to yield more loci for the same cost. This study is a timely demonstration of how a research team can efficiently generate informative (neutral or function-associated) microsatellite markers for their study species and unique biological questions.

Sequence differences at orthologous microsatellites inflate estimates of human-chimpanzee differentiation

Background

Microsatellites---contiguous arrays of 2–6 base-pair motifs---have formed the cornerstone of population-genetic studies for over two decades. Their genotype data typically takes the form of PCR fragment lengths obtained using locus-specific primer pairs to amplify the genomic region encompassing the microsatellite. Recently, we reported a dataset of 5,795 human and 84 chimpanzee individuals with genotypes at 246 human-derived autosomal microsatellites as a resource to facilitate interspecies comparisons. A major assumption underlying this dataset is that PCR amplicons at orthologous microsatellites are commensurable between species.

Results

We find this assumption to be frequently incorrect owing to discordance in microsatellite organization and variability, as well as nontrivial length imbalances caused by small species-specific indels in microsatellite flanking sequences. Converting PCR fragment lengths into the repeat numbers they represent at 138 microsatellites whose organization and variability was found to be highly similar in both species, we show that interspecies incommensurability among PCR amplicons can inflate F_ST and D_PS estimates by up to 10.6%. Separate investigations of determinants of microsatellite variability in humans and chimpanzees uncover similar patterns with mean and maximum numbers of repeats, as well as numbers and ranges of distinct alleles, all important factors in predicting heterozygosity. In contrast, across microsatellites, numbers of repeats were significantly smaller in chimpanzees than in humans, while numbers and ranges of distinct alleles were instead larger.

Conclusions

Our findings have fundamental implications for interspecies comparisons using microsatellites and offer new opportunities for more accurate comparisons of patterns of human and chimpanzee genetic variation in numerous areas of application.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-990) contains supplementary material, which is available to authorized users.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.