Million-year-old DNA sheds light on the genomic history of mammoths.

Temporal genomic data hold great potential for studying evolutionary processes such as speciation. However, sampling across speciation events would, in many cases, require genomic time series that stretch well back into the Early Pleistocene subepoch. Although theoretical models suggest that DNA should survive on this timescale1, the oldest genomic data recovered so far are from a horse specimen dated to 780-560 thousand years ago2. Here we report the recovery of genome-wide data from three mammoth specimens dating to the Early and Middle Pleistocene subepochs, two of which are more than one million years old. We find that two distinct mammoth lineages were present in eastern Siberia during the Early Pleistocene. One of these lineages gave rise to the woolly mammoth and the other represents a previously unrecognized lineage that was ancestral to the first mammoths to colonize North America. Our analyses reveal that the Columbian mammoth of North America traces its ancestry to a Middle Pleistocene hybridization between these two lineages, with roughly equal admixture proportions. Finally, we show that the majority of protein-coding changes associated with cold adaptation in woolly mammoths were already present one million years ago. These findings highlight the potential of deep-time palaeogenomics to expand our understanding of speciation and long-term adaptive evolution.

Conservation Genetic Assessment of Savannah Elephants (Loxodonta africana) in the Greater Kruger Biosphere, South Africa.

Savannah elephant populations have been severely reduced and fragmented throughout its remaining range. In general, however, there is limited information regarding their genetic status, which is essential knowledge for conservation. We investigated patterns of genetic variation in savannah elephants from the Greater Kruger Biosphere, with a focus on those in previously unstudied nature reserves adjacent to Kruger National Park, using dung samples from 294 individuals and 18 microsatellites. The results of genetic structure analyses using several different methods of ordination and Bayesian clustering strongly suggest that elephants throughout the Greater Kruger National Park (GKNP) constitute a single population. No evidence of a recent genetic bottleneck was detected using three moment-based approaches and two coalescent likelihood methods. The apparent absence of a recent genetic bottleneck associated with the known early 1900s demographic bottleneck may result from a combination of rapid post-bottleneck population growth, immigration and long generation time. Point estimates of contemporary effective population size (Ne) for the GKNP were ~ 500-700, that is, at the low end of the range of Ne values that have been proposed for maintaining evolutionary potential and the current ratio of Ne to census population size (Nc) may be quite low (<0.1). This study illustrates the difficulties in assessing the impacts on Ne in populations that have suffered demographic crashes but have recovered rapidly and received gene flow, particularly in species with long generation times in which genetic time lags are longer. This work provides a starting point and baseline information for genetic monitoring of the GKNP elephants.

Detection of dynamic protein complexes through Markov Clustering based on Elephant Herd Optimization Approach.

The accessibility of a huge amount of protein-protein interaction (PPI) data has allowed to do research on biological networks that reveal the structure of a protein complex, pathways and its cellular organization. A key demand in computational biology is to recognize the modular structure of such biological networks. The detection of protein complexes from the PPI network, is one of the most challenging and significant problems in the post-genomic era. In Bioinformatics, the frequently employed approach for clustering the networks is Markov Clustering (MCL). Many of the researches for protein complex detection were done on the static PPI network, which suffers from a few drawbacks. To resolve this problem, this paper proposes an approach to detect the dynamic protein complexes through Markov Clustering based on Elephant Herd Optimization Approach (DMCL-EHO). Initially, the proposed method divides the PPI network into a set of dynamic subnetworks under various time points by combining the gene expression data and secondly, it employs the clustering analysis on every subnetwork using the MCL along with Elephant Herd Optimization approach. The experimental analysis was employed on different PPI network datasets and the proposed method surpasses various existing approaches in terms of accuracy measures. This paper identifies the common protein complexes that are expressively enriched in gold-standard datasets and also the pathway annotations of the detected protein complexes using the KEGG database.

Improving cost-efficiency of faecal genotyping: New tools for elephant species.

Despite the critical need for non-invasive tools to improve monitoring of wildlife populations, especially for endangered and elusive species, faecal genetic sampling has not been adopted as regular practice, largely because of the associated technical challenges and cost. Substantial work needs to be undertaken to refine sample collection and preparation methods in order to improve sample set quality and provide cost-efficient tools that can effectively support wildlife management. In this study, we collected an extensive set of forest elephant (Loxodonta cyclotis) faecal samples throughout Gabon, Central Africa, and prepared them for genotyping using 107 single-nucleotide polymorphism assays. We developed a new quantitative polymerase chain reaction (PCR) assay targeting a 130-bp nuclear DNA fragment and demonstrated its suitability for degraded samples in all three elephant species. Using this assay to compare the efficacy of two sampling methods for faecal DNA recovery, we found that sampling the whole surface of a dung pile with a swab stored in a small tube of lysis buffer was a convenient method producing high extraction success and DNA yield. We modelled the influence of faecal quality and storage time on DNA concentration in order to provide recommendations for optimized collection and storage. The maximum storage time to ensure 75% success was two months for samples collected within 24 hours after defecation and extended to four months for samples collected within one hour. Lastly, the real-time quantitative PCR assay allowed us to predict genotyping success and pre-screen DNA samples, thus further increasing the cost-efficiency of our approach. We recommend combining the validation of an efficient sampling method, the build of in-country DNA extraction capacity for reduced storage time and the development of species-specific quantitative PCR assays in order to increase the cost-efficiency of routine non-invasive DNA analyses and expand the use of next-generation markers to non-invasive samples.

Visualizing spatial population structure with estimated effective migration surfaces.

Genetic data often exhibit patterns broadly consistent with 'isolation by distance'-a phenomenon where genetic similarity decays with geographic distance. In a heterogeneous habitat, this may occur more quickly in some regions than in others: for example, barriers to gene flow can accelerate differentiation between neighboring groups. We use the concept of 'effective migration' to model the relationship between genetics and geography. In this paradigm, effective migration is low in regions where genetic similarity decays quickly. We present a method to visualize variation in effective migration across a habitat from geographically indexed genetic data. Our approach uses a population genetic model to relate effective migration rates to expected genetic dissimilarities. We illustrate its potential and limitations using simulations and data from elephant, human and Arabidopsis thaliana populations. The resulting visualizations highlight important spatial features of population structure that are difficult to discern using existing methods for summarizing genetic variation.

Personality assessment and its association with genetic factors in captive Asian and African elephants.

Elephants live in a complex society based on matrilineal groups. Management of captive elephants is difficult, partly because each elephant has a unique personality. For a better understanding of elephant well being in captivity, it would be helpful to systematically evaluate elephants' personalities and their underlying biological basis. We sent elephant' personality questionnaires to keepers of 75 elephants. We also used 196 elephant DNA samples to search for genetic polymorphisms in genes expressed in the brain that have been suggested to be related to personality traits. Three genes, androgen receptor (AR), fragile X related mental retardation protein interacting protein (NUFIP2), and acheate-scute homologs 1 (ASH1) contained polymorphic regions. We examined the association of personality with intraspecific genetic variation in 17 Asian and 28 African elephants. The results suggest that the ASH1 genotype was associated with neuroticism in Asian elephants. Subjects with short alleles had lower scores of neuroticism than those with long alleles. This is the first report of an association between a genetic polymorphism and personality in elephants.

Where sociality and relatedness diverge: the genetic basis for hierarchical social organization in African elephants.

Hierarchical properties characterize elephant fission-fusion social organization whereby stable groups of individuals coalesce into higher order groups or split in a predictable manner. This hierarchical complexity is rare among animals and, as such, an examination of the factors driving its emergence offers unique insight into the evolution of social behaviour. Investigation of the genetic basis for such social affiliation demonstrates that while the majority of core social groups (second-tier affiliates) are significantly related, this is not exclusively the case. As such, direct benefits received through membership of these groups appear to be salient to their formation and maintenance. Further analysis revealed that the majority of groups in the two higher social echelons (third and fourth tiers) are typically not significantly related. The majority of third-tier members are matrilocal, carrying the same mtDNA control region haplotype, while matrilocality among fourth-tier groups was slightly less than expected at random. Comparison of results to those from a less disturbed population suggests that human depredation, leading to social disruption, altered the genetic underpinning of social relations in the study population. These results suggest that inclusive fitness benefits may crystallize elephant hierarchical social structuring along genetic lines when populations are undisturbed. However, indirect benefits are not critical to the formation and maintenance of second-, third- or fourth-tier level bonds, indicating the importance of direct benefits in the emergence of complex, hierarchical social relations among elephants. Future directions and conservation implications are discussed.

Effective population size dynamics reveal impacts of historic climatic events and recent anthropogenic pressure in African elephants.

Two hundred years of elephant hunting for ivory, peaking in 1970-1980s, caused local extirpations and massive population declines across Africa. The resulting genetic impacts on surviving populations have not been studied, despite the importance of understanding the evolutionary repercussions of such human-mediated events on this keystone species. Using Bayesian coalescent-based genetic methods to evaluate time-specific changes in effective population size, we analysed genetic variation in 20 highly polymorphic microsatellite loci from 400 elephants inhabiting the greater Samburu-Laikipia region of northern Kenya. This area experienced a decline of between 80% and 90% in the last few decades when ivory harvesting was rampant. The most significant change in effective population size, however, occurred approximately 2500 years ago during a mid-Holocene period of climatic drying in tropical Africa. Contrary to expectations, detailed analyses of four contemporary age-based cohorts showed that the peak poaching epidemic in the 1970s caused detectable temporary genetic impacts, with genetic diversity rebounding as juveniles surviving the poaching era became reproductively mature. This study demonstrates the importance of climatic history in shaping the distribution and genetic history of a keystone species and highlights the utility of coalescent-based demographic approaches in unravelling ancestral demographic events despite a lack of ancient samples. Unique insights into the genetic signature of mid-Holocene climatic change in Africa and effects of recent poaching pressure on elephants are discussed.

An integrated-likelihood method for estimating genetic differentiation between populations.

The aim of this article is to develop an integrated-likelihood (IL) approach to estimate the genetic differentiation between populations. The conventional maximum-likelihood (ML) and pseudolikelihood (PL) methods that use sample counts of alleles may cause severe underestimations of FST, which means overestimations of theta=4Nm, when the number of sampling localities is small. To reduce such bias in the estimation of genetic differentiation, we propose an IL method in which the mean allele frequencies over populations are regarded as nuisance parameters and are eliminated by integration. To maximize the IL function, we have developed two algorithms, a Monte Carlo EM algorithm and a Laplace approximation. Our simulation studies show that the method proposed here outperforms the conventional ML and PL methods in terms of unbiasedness and precision. The IL method was applied to real data for Pacific herring and African elephants.

Population differentiation within and among Asian elephant (Elephas maximus) populations in southern India.

Southern India, one of the last strongholds of the endangered Asian elephant (Elephas maximus), harbours about one-fifth of the global population. We present here the first population genetic study of free-ranging Asian elephants, examining within- and among-population differentiation by analysing mitochondrial DNA (mtDNA) and nuclear microsatellite DNA differentiation across the Nilgiris-Eastern Ghats, Anamalai, and Periyar elephant reserves of southern India. Low mtDNA diversity and 'normal' microsatellite diversity were observed. Surprisingly, the Nilgiri population, which is the world's single largest Asian elephant population, had only one mtDNA haplotype and lower microsatellite diversity than the two other smaller populations examined. There was almost no mtDNA or microsatellite differentiation among localities within the Nilgiris, an area of about 15,000 km2. This suggests extensive gene flow in the past, which is compatible with the home ranges of several hundred square kilometres of elephants in southern India. Conversely, the Nilgiri population is genetically distinct at both mitochondrial and microsatellite markers from the two more southerly populations, Anamalai and Periyar, which in turn are not genetically differentiated from each other. The more southerly populations are separated from the Nilgiris by only a 40-km-wide stretch across a gap in the Western Ghats mountain range. These results variably indicate the importance of population bottlenecks, social organization, and biogeographic barriers in shaping the distribution of genetic variation among Asian elephant populations in southern India.