An evaluation of sequencing coverage and genotyping strategies to assess neutral and adaptive diversity

Genomic diversity of the locally developed Latvian Darkheaded sheep breed

The Latvian Darkheaded is the only locally developed sheep breed. The breed was formed at the beginning of the 20th century by crossing local coarse-wooled sheep with the British Shropshire and Oxfordshire breeds. The breed was later improved by adding Ile-de-France, Texel, German blackheads, and Finnsheep to achieve higher prolificacy and better meat quality. Previous studies have reported the Latvian Darkheaded sheep to be closely related to Estonian and Lithuanian Blackface breeds, according to microsatellite data. To expand our knowledge of the genetic resources of the Latvian Darkheaded breed, we conducted a whole-genome resequencing analysis on 40 native sheep. The investigation showed that local sheep harbor genetic diversity levels similar to those observed among other improved breeds of European origin, including Charollais and Suffolk. Genome-wide nucleotide diversity (π) in Latvian Darkheaded sheep was 3.91 × 10-3, whereas the average observed heterozygosity among the 40 animals was 0.267 and 0.438 within the subsample of unrelated individuals. The Ne has rapidly decreased to 200 ten generations ago with a recent drop to Ne 73 four generations ago. However, inbreeding levels based on runs of homozygosity were, on average, low, with FROH ranging between 0.016 and 0.059. The analysis of the genomic composition of the breed confirmed shared ancestry with sheep of British origin, reflecting the history of the breed. Nevertheless, Latvian Darkheaded sheep were genetically separable. The contemporary Latvian Darkheaded sheep population is genetically diverse with a low inbreeding rate. However, further development of breed management programs is necessary to prevent an increase in inbreeding, loss of genetic diversity, and depletion of breed-specific genetic resources, ensuring the preservation of the native Latvian Darkheaded sheep.

A Fast, Reproducible, High-throughput Variant Calling Workflow for Population Genomics

The increasing availability of genomic resequencing data sets and high-quality reference genomes across the tree of life present exciting opportunities for comparative population genomic studies. However, substantial challenges prevent the simple reuse of data across different studies and species, arising from variability in variant calling pipelines, data quality, and the need for computationally intensive reanalysis. Here, we present snpArcher, a flexible and highly efficient workflow designed for the analysis of genomic resequencing data in nonmodel organisms. snpArcher provides a standardized variant calling pipeline and includes modules for variant quality control, data visualization, variant filtering, and other downstream analyses. Implemented in Snakemake, snpArcher is user-friendly, reproducible, and designed to be compatible with high-performance computing clusters and cloud environments. To demonstrate the flexibility of this pipeline, we applied snpArcher to 26 public resequencing data sets from nonmammalian vertebrates. These variant data sets are hosted publicly to enable future comparative population genomic analyses. With its extensibility and the availability of public data sets, snpArcher will contribute to a broader understanding of genetic variation across species by facilitating the rapid use and reuse of large genomic data sets.

Contrasting whole-genome and reduced representation sequencing for population demographic and adaptive inference: an alpine mammal case study

Genomes capture the adaptive and demographic history of a species, but the choice of sequencing strategy and sample size can impact such inferences. We compared whole genome and reduced representation sequencing approaches to study the population demographic and adaptive signals of the North American mountain goat (Oreamnos americanus). We applied the restriction site-associated DNA sequencing (RADseq) approach to 254 individuals and whole genome resequencing (WGS) approach to 35 individuals across the species range at mid-level coverage (9X) and to 5 individuals at high coverage (30X). We used ANGSD to estimate the genotype likelihoods and estimated the effective population size (Ne), population structure, and explicitly modelled the demographic history with δaδi and MSMC2. The data sets were overall concordant in supporting a glacial induced vicariance and extremely low Ne in mountain goats. We evaluated a set of climatic variables and geographic location as predictors of genetic diversity using redundancy analysis. A moderate proportion of total variance (36% for WGS and 21% for RADseq data sets) was explained by geography and climate variables; both data sets support a large impact of drift and some degree of local adaptation. The empirical similarities of WGS and RADseq presented herein reassuringly suggest that both approaches will recover large demographic and adaptive signals in a population; however, WGS offers several advantages over RADseq, such as inferring adaptive processes and calculating runs-of-homozygosity estimates. Considering the predicted climate-induced changes in alpine environments and the genetically depauperate mountain goat, the long-term adaptive capabilities of this enigmatic species are questionable.

Genomic Characterization and Initial Insight into Mastitis-Associated SNP Profiles of Local Latvian Bos taurus Breeds

Latvia has two local Bos taurus breeds-Latvian Brown (LBG) and Latvian Blue (LZG)-characterized by a good adaptation to the local climate, longevity, and high fat and protein contents in milk. Since these are desired traits in the dairy industry, this study investigated the genetic background of the LBG and LZG breeds and identified the genetic factors associated with mastitis. Blood and semen samples were acquired, and whole genome sequencing was then performed to acquire a genomic sequence with at least 35× or 10× coverage. The heterozygosity, nucleotide diversity, and LD analysis indicated that LBG and LZG cows have similar levels of genetic diversity compared to those of other breeds. An analysis of the population structure revealed that each breed clustered together, but the overall differentiation between the breeds was small. The highest genetic variance was observed in the LZG breed compared with the LBG breed. Our results show that SNP rs721295390 is associated with mastitis in the LBG breed, and SNPs rs383806754, chr29:43998719CG>C, and rs462030680 are associated with mastitis in the LZG breed. This study shows that local Latvian LBG and LZG breeds have a pronounced genetic differentiation, with each one suggesting its own mastitis-associated SNP profile.

Evaluation and Analysis of Absence of Homozygosity (AOH) Using Chromosome Analysis by Medium Coverage Whole Genome Sequencing (CMA-seq) in Prenatal Diagnosis

OBJECTIVE

Absence of homozygosity (AOH) is a genetic characteristic known to cause human diseases mainly through autosomal recessive or imprinting mechanisms. The importance and necessity of accurate AOH detection has become more clinically significant in recent years. However, it remains a challenging task for sequencing-based methods thus far.

METHODS

In this study, we developed and optimized a new bioinformatic algorithm based on the assessment of minimum sequencing coverage, optimal bin size, the Z-score threshold of four types of allele count and the frequency for accurate genotyping using 28 AOH negative samples, and redefined the AOH detection cutoff value. We showed the performance of chromosome analysis by five-fold coverage whole genome sequencing (CMA-seq) for AOH identification in 27 typical prenatal/postnatal AOH positive samples, which were previously confirmed by chromosomal microarray analysis with single nucleotide polymorphism array (CMA/SNP array).

RESULTS

The blinded study indicated that for all three forms of AOH, including whole genomic AOH, single chromosomal AOH and segmental AOH, and all kinds of sample types, including chorionic villus sampling, amniotic fluid, cord blood, peripheral blood and abortive tissue, CMA-seq showed equivalent detection power to that of routine CMA/SNP arrays (750K). The subtle difference between the two methods is that CMA-seq is prone to detect small inconsecutive AOHs, while CMA/SNP array reports it as a whole.

CONCLUSION

Based on our newly developed bioinformatic algorithm, it is feasible to detect clinically significant AOH using CMA-seq in prenatal diagnosis.

Demographic history and conservation genomics of caribou (Rangifer tarandus) in Québec

The loss of genetic diversity is a challenge many species are facing, with genomics being a potential tool to inform and prioritize decision-making. Most caribou (Rangifer tarandus) populations have experienced significant recent declines throughout Québec, Canada, and are considered of concern, threatened or endangered. Here, we calculated the ancestral and contemporary patterns of genomic diversity of five representative caribou populations and applied a comparative population genomics framework to assess the interplay between demographic events and genomic diversity. We first calculated a caribou specific mutation rate, μ, by extracting orthologous genes from related ungulates and estimating the rate of synonymous mutations. Whole genome re-sequencing was then completed on 67 caribou: from these data we calculated nucleotide diversity, θ π and estimated the coalescent or ancestral effective population size (N e), which ranged from 12,030 to 15,513. When compared to the census size, N C, the endangered Gaspésie Mountain caribou population had the highest ancestral N e:N C ratio which is consistent with recent work suggesting high ancestral N e:N C is of conservation concern. In contrast, values of contemporary N e, estimated from linkage-disequilibrium, ranged from 11 to 162, with Gaspésie having among the highest contemporary N e:N C ratio. Importantly, classic conservation genetics theory would predict this population to be of less concern based on this ratio. Interestingly, F varied only slightly between populations, and despite evidence of bottlenecks across the province, runs of homozygosity were not abundant in the genome. Tajima's D estimates mirrored the demographic models and current conservation status. Our study highlights how genomic patterns are nuanced and potentially misleading if viewed only through a contemporary lens; we argue a holistic conservation genomics view should integrate ancestral N e and Tajima's D into management decisions.

Genome-wide investigations reveal the population structure and selection signatures of Nigerian cattle adaptation in the sub-Saharan tropics

Background

Cattle are considered to be the most desirable livestock by small scale farmers. In Africa, although comprehensive genomic studies have been carried out on cattle, the genetic variations in indigenous cattle from Nigeria have not been fully explored. In this study, genome-wide analysis based on genotyping-by-sequencing (GBS) of 193 Nigerian cattle was used to reveal new insights on the history of West African cattle and their adaptation to the tropical African environment, particularly in sub-Saharan region. 

Results

The GBS data were evaluated against whole-genome sequencing (WGS) data and high rate of variant concordance between the two platforms was evident with high correlated genetic distance matrices genotyped by both methods suggestive of the reliability of GBS applicability in population genetics. The genetic structure of Nigerian cattle was observed to be homogenous and unique from other African cattle populations. Selection analysis for the genomic regions harboring imprints of adaptation revealed genes associated with immune responses, growth and reproduction, efficiency of feeds utilization, and heat tolerance. Our findings depict potential convergent adaptation between African cattle, dogs and humans with adaptive genes SPRY2 and ITGB1BP1 possibly involved in common physiological activities.

Conclusion

The study presents unique genetic patterns of Nigerian cattle which provide new insights on the history of cattle in West Africa based on their population structure and the possibility of parallel adaptation between African cattle, dogs and humans in Africa which require further investigations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08512-w.

Association between long noncoding RNA rs944289 and rs7990916 polymorphisms and the risk of colorectal cancer in a Chinese population

Long non-coding RNAs (LncRNAs) play vital roles in the tumorigenesis of many cancers. Single nucleotide polymorphisms (SNPs) of the lncRNA also play vital roles in tumorigenesis. We explored lncRNA rs944289 and rs7990916 polymorphisms and analyzed the relationship between these lncRNA polymorphisms with the colorectal cancer (CRC) risk in a Chinese population. We recruited 1003 CRC patients from the Affiliated People’s Hospital of Jiangsu University and the Fujian Medical University Union Hospital from October 2014 to August 2017. Genomic DNA was extracted using a DNA Kit from lymphocytes of peripheral blood and the genotyping was performed with a SNPscan method. We found that the rs944289 TT homozygote was associated with the decreased CRC risk in the overall population. LncRNA rs944289 TT decreased the CRC risk in the subgroup of female, male, age ≥ 61, without alcohol intake, smoking and BMI ≥ 24 by logistic regression. The subgroup analysis revealed that lncRNA rs7990916 was not associated with CRC risk except for age < 61. Logistic regression analysis revealed that lncRNA rs944289 TT homozygote was associated with the increased risk of rectum cancer (TT vs. CC + CT: adjusted OR = 1.29, 95% CI 1.10–1.66, P = 0.041) or colon cancer. In summary, we proved that lncRNA rs944289 might be significantly related to the decreased CRC risk in the Chinese Han populations and lncRNA rs7990916 was not associated with the CRC risk except for patients of age < 61. In the future, studies with larger samples should be conducted to validate our results.

Testing the effectiveness of genetic monitoring using genetic non-invasive sampling

Effective conservation requires accurate data on population genetic diversity, inbreeding, and genetic structure. Increasingly, scientists are adopting genetic non-invasive sampling (gNIS) as a cost-effective population-wide genetic monitoring approach. gNIS has, however, known limitations which may impact the accuracy of downstream genetic analyses. Here, using high-quality single nucleotide polymorphism (SNP) data from blood/tissue sampling of a free-ranging koala population (n = 430), we investigated how the reduced SNP panel size and call rate typical of genetic non-invasive samples (derived from experimental and field trials) impacts the accuracy of genetic measures, and also the effect of sampling intensity on these measures. We found that gNIS at small sample sizes (14% of population) can provide accurate population diversity measures, but slightly underestimated population inbreeding coefficients. Accurate measures of internal relatedness required at least 33% of the population to be sampled. Accurate geographic and genetic spatial autocorrelation analysis requires between 28% and 51% of the population to be sampled. We show that gNIS at low sample sizes can provide a powerful tool to aid conservation decision-making and provide recommendations for researchers looking to apply these techniques to free-ranging systems.

Genomic Uniqueness of Local Sheep Breeds From Morocco

Sheep farming is a major source of meat in Morocco and plays a key role in the country's agriculture. This study aims at characterizing the whole-genome diversity and demographic history of the main Moroccan sheep breeds, as well as to identify selection signatures within and between breeds. Whole genome data from 87 individuals representing the five predominant local breeds were used to estimate their level of neutral genetic diversity and to infer the variation of their effective population size over time. In addition, we used two methods to detect selection signatures: either for detecting selective sweeps within each breed separately or by detecting differentially selected regions by contrasting different breeds. We identified hundreds of genomic regions putatively under selection, which related to several biological terms involved in local adaptation or the expression of zootechnical performances such as Growth, UV protection, Cell maturation or Feeding behavior. The results of this study revealed selection signatures in genes that have an important role in traits of interest and increased our understanding of how genetic diversity is distributed in these local breeds. Thus, Moroccan local sheep breeds exhibit both a high genetic diversity and a large set of adaptive variations, and therefore, represent a valuable genetic resource for the conservation of sheep in the context of climate change.

Whole-genome sequence analysis unveils different origins of European and Asiatic mouflon and domestication-related genes in sheep

The domestication and subsequent development of sheep are crucial events in the history of human civilization and the agricultural revolution. However, the impact of interspecific introgression on the genomic regions under domestication and subsequent selection remains unclear. Here, we analyze the whole genomes of domestic sheep and their wild relative species. We found introgression from wild sheep such as the snow sheep and its American relatives (bighorn and thinhorn sheep) into urial, Asiatic and European mouflons. We observed independent events of adaptive introgression from wild sheep into the Asiatic and European mouflons, as well as shared introgressed regions from both snow sheep and argali into Asiatic mouflon before or during the domestication process. We revealed European mouflons might arise through hybridization events between a now extinct sheep in Europe and feral domesticated sheep around 6000-5000 years BP. We also unveiled later introgressions from wild sheep to their sympatric domestic sheep after domestication. Several of the introgression events contain loci with candidate domestication genes (e.g., PAPPA2, NR6A1, SH3GL3, RFX3 and CAMK4), associated with morphological, immune, reproduction or production traits (wool/meat/milk). We also detected introgression events that introduced genes related to nervous response (NEURL1), neurogenesis (PRUNE2), hearing ability (USH2A), and placental viability (PAG11 and PAG3) into domestic sheep and their ancestral wild species from other wild species.

VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Background

Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra.

Findings

A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin.

Conclusions

We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00659-6.

Best practices for analyzing imputed genotypes from low-pass sequencing in dogs

Although DNA array-based approaches for genome-wide association studies (GWAS) permit the collection of thousands of low-cost genotypes, it is often at the expense of resolution and completeness, as SNP chip technologies are ultimately limited by SNPs chosen during array development. An alternative low-cost approach is low-pass whole genome sequencing (WGS) followed by imputation. Rather than relying on high levels of genotype confidence at a set of select loci, low-pass WGS and imputation rely on the combined information from millions of randomly sampled low-confidence genotypes. To investigate low-pass WGS and imputation in the dog, we assessed accuracy and performance by downsampling 97 high-coverage (> 15×) WGS datasets from 51 different breeds to approximately 1× coverage, simulating low-pass WGS. Using a reference panel of 676 dogs from 91 breeds, genotypes were imputed from the downsampled data and compared to a truth set of genotypes generated from high-coverage WGS. Using our truth set, we optimized a variant quality filtering strategy that retained approximately 80% of 14 M imputed sites and lowered the imputation error rate from 3.0% to 1.5%. Seven million sites remained with a MAF > 5% and an average imputation quality score of 0.95. Finally, we simulated the impact of imputation errors on outcomes for case-control GWAS, where small effect sizes were most impacted and medium-to-large effect sizes were minorly impacted. These analyses provide best practice guidelines for study design and data post-processing of low-pass WGS-imputed genotypes in dogs.

Evaluation of low-pass genome sequencing in polygenic risk score calculation for Parkinson's disease

Background

Low-pass sequencing (LPS) has been extensively investigated for applicability to various genetic studies due to its advantages over genotype array data including cost-effectiveness. Predicting the risk of complex diseases such as Parkinson’s disease (PD) using polygenic risk score (PRS) based on the genetic variations has shown decent prediction accuracy. Although ultra-LPS has been shown to be effective in PRS calculation, array data has been favored to the majority of PRS analysis, especially for PD.

Results

Using eight high-coverage WGS, we assessed imputation approaches for downsampled LPS data ranging from 0.5 × to 7.0 × . We demonstrated that uncertain genotype calls of LPS diminished imputation accuracy, and an imputation approach using genotype likelihoods was plausible for LPS. Additionally, comparing imputation accuracies between LPS and simulated array illustrated that LPS had higher accuracies particularly at rare frequencies. To evaluate ultra-low coverage data in PRS calculation for PD, we prepared low-coverage WGS and genotype array of 87 PD cases and 101 controls. Genotype imputation of array and downsampled LPS were conducted using a population-specific reference panel, and we calculated risk scores based on the PD-associated SNPs from an East Asian meta-GWAS. The PRS models discriminated cases and controls as previously reported when both LPS and genotype array were used. Also strong correlations in PRS models for PD between LPS and genotype array were discovered.

Conclusions

Overall, this study highlights the potentials of LPS under 1.0 × followed by genotype imputation in PRS calculation and suggests LPS as attractive alternatives to genotype array in the area of precision medicine for PD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00357-w.

Distinct interspecific and intraspecific vulnerability of coastal species to global change

Characterising and predicting species responses to anthropogenic global change is one of the key challenges in contemporary ecology and conservation. The sensitivity of marine species to climate change is increasingly being described with forecasted species distributions, yet these rarely account for population level processes such as genomic variation and local adaptation. This study compares inter- and intraspecific patterns of biological composition to determine how vulnerability to climate change, and its environmental drivers, vary across species and populations. We compare species trajectories for three ecologically important southern African marine invertebrates at two time points in the future, both at the species level, with correlative species distribution models, and at the population level, with gradient forest models. Reported range shifts are species-specific and include both predicted range gains and losses. Forecasted species responses to climate change are strongly influenced by changes in a suite of environmental variables, from sea surface salinity and sea surface temperature, to minimum air temperature. Our results further suggest a mismatch between future habitat suitability (where species can remain in their ecological niche) and genomic vulnerability (where populations retain their genomic composition), highlighting the inter- and intraspecific variability in species' sensitivity to global change. Overall, this study demonstrates the importance of considering species and population level climatic vulnerability when proactively managing coastal marine ecosystems in the Anthropocene.

Genetic load has potential in large populations but is realized in small inbred populations

Populations with higher genetic diversity and larger effective sizes have greater evolutionary capacity (i.e., adaptive potential) to respond to ecological stressors. We are interested in how the variation captured in protein-coding genes fluctuates relative to overall genomic diversity and whether smaller populations suffer greater costs due to their genetic load of deleterious mutations compared with larger populations. We analyzed individual whole-genome sequences (N = 74) from three different populations of Montezuma quail (Cyrtonyx montezumae), a small ground-dwelling bird that is sustainably harvested in some portions of its range but is of conservation concern elsewhere. Our historical demographic results indicate that Montezuma quail populations in the United States exhibit low levels of genomic diversity due in large part to long-term declines in effective population sizes over nearly a million years. The smaller and more isolated Texas population is significantly more inbred than the large Arizona and the intermediate-sized New Mexico populations we surveyed. The Texas gene pool has a significantly smaller proportion of strongly deleterious variants segregating in the population compared with the larger Arizona gene pool. Our results demonstrate that even in small populations, highly deleterious mutations are effectively purged and/or lost due to drift. However, we find that in small populations the realized genetic load is elevated because of inbreeding coupled with a higher frequency of slightly deleterious mutations that are manifested in homozygotes. Overall, our study illustrates how population genomics can be used to proactively assess both neutral and functional aspects of contemporary genetic diversity in a conservation framework while simultaneously considering deeper demographic histories.

An 85K SNP Array Uncovers Inbreeding and Cryptic Relatedness in an Antarctic Fur Seal Breeding Colony

High density single nucleotide polymorphism (SNP) arrays allow large numbers of individuals to be rapidly and cost-effectively genotyped at large numbers of genetic markers. However, despite being widely used in studies of humans and domesticated plants and animals, SNP arrays are lacking for most wild organisms. We developed a custom 85K Affymetrix Axiom array for an intensively studied pinniped, the Antarctic fur seal (Arctocephalus gazella). SNPs were discovered from a combination of genomic and transcriptomic resources and filtered according to strict criteria. Out of a total of 85,359 SNPs tiled on the array, 75,601 (88.6%) successfully converted and were polymorphic in 270 animals from a breeding colony at Bird Island in South Georgia. Evidence was found for inbreeding, with three genomic inbreeding coefficients being strongly intercorrelated and the proportion of the genome in runs of homozygosity being non-zero in all individuals. Furthermore, analysis of genomic relatedness coefficients identified previously unknown first-degree relatives and multiple second-degree relatives among a sample of ostensibly unrelated individuals. Such “cryptic relatedness” within fur seal breeding colonies may increase the likelihood of consanguineous matings and could therefore have implications for understanding fitness variation and mate choice. Finally, we demonstrate the cross-amplification potential of the array in three related pinniped species. Overall, our SNP array will facilitate future studies of Antarctic fur seals and has the potential to serve as a more general resource for the wider pinniped research community.

PACVr: plastome assembly coverage visualization in R

Background

Plastid genomes typically display a circular, quadripartite structure with two inverted repeat regions, which challenges automatic assembly procedures. The correct assembly of plastid genomes is a prerequisite for the validity of subsequent analyses on genome structure and evolution. The average coverage depth of a genome assembly is often used as an indicator of assembly quality. Visualizing coverage depth across a draft genome is a critical step, which allows users to inspect the quality of the assembly and, where applicable, identify regions of reduced assembly confidence. Despite the interplay between genome structure and assembly quality, no contemporary, user-friendly software tool can visualize the coverage depth of a plastid genome assembly while taking its quadripartite genome structure into account. A software tool is needed that fills this void.

Results

We introduce ’PACVr’, an R package that visualizes the coverage depth of a plastid genome assembly in relation to the circular, quadripartite structure of the genome as well as the individual plastome genes. By using a variable window approach, the tool allows visualizations on different calculation scales. It also confirms sequence equality of, as well as visualizes gene synteny between, the inverted repeat regions of the input genome. As a tool for plastid genomics, PACVr provides the functionality to identify regions of coverage depth above or below user-defined threshold values and helps to identify non-identical IR regions. To allow easy integration into bioinformatic workflows, PACVr can be invoked from a Unix shell, facilitating its use in automated quality control. We illustrate the application of PACVr on four empirical datasets and compare visualizations generated by PACVr with those of alternative software tools.

Conclusions

PACVr provides a user-friendly tool to visualize (a) the coverage depth of a plastid genome assembly on a circular, quadripartite plastome map and in relation to individual plastome genes, and (b) gene synteny across the inverted repeat regions. It contributes to optimizing plastid genome assemblies and increasing the reliability of publicly available plastome sequences. The software, example datasets, technical documentation, and a tutorial are available with the package at https://cran.r-project.org/package=PACVr.

On the origin of European sheep as revealed by the diversity of the Balkan breeds and by optimizing population-genetic analysis tools

Background

In the Neolithic, domestic sheep migrated into Europe and subsequently spread in westerly and northwesterly directions. Reconstruction of these migrations and subsequent genetic events requires a more detailed characterization of the current phylogeographic differentiation.

Results

We collected 50 K single nucleotide polymorphism (SNP) profiles of Balkan sheep that are currently found near the major Neolithic point of entry into Europe, and combined these data with published genotypes from southwest-Asian, Mediterranean, central-European and north-European sheep and from Asian and European mouflons. We detected clines, ancestral components and admixture by using variants of common analysis tools: geography-informative supervised principal component analysis (PCA), breed-specific admixture analysis, across-breed \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f_{4}$$\end{document}f4 profiles and phylogenetic analysis of regional pools of breeds. The regional Balkan sheep populations exhibit considerable genetic overlap, but are clearly distinct from the breeds in surrounding regions. The Asian mouflon did not influence the differentiation of the European domestic sheep and is only distantly related to present-day sheep, including those from Iran where the mouflons were sampled. We demonstrate the occurrence, from southeast to northwest Europe, of a continuously increasing ancestral component of up to 20% contributed by the European mouflon, which is assumed to descend from the original Neolithic domesticates. The overall patterns indicate that the Balkan region and Italy served as post-domestication migration hubs, from which wool sheep reached Spain and north Italy with subsequent migrations northwards. The documented dispersal of Tarentine wool sheep during the Roman period may have been part of this process. Our results also reproduce the documented 18th century admixture of Spanish Merino sheep into several central-European breeds.

Conclusions

Our results contribute to a better understanding of the events that have created the present diversity pattern, which is relevant for the management of the genetic resources represented by the European sheep population.

Association of Long Noncoding RNAs Polymorphisms with the Risk of Esophagogastric Junction Adenocarcinoma: A Three-Center Study of 1063 Cases and 1677 Controls

Increasing evidence suggested that long noncoding RNAs (lncRNAs) variants may be involved in the progression of various cancers. However, the association of the lncRNAs polymorphisms with the risk for esophagogastric junction adenocarcinoma (EGJA) is still unknown. In this case-control study, we selected two cancer-related lncRNAs polymorphisms (rs944289 C > T and rs7990916 C>T), and recruited a total of 1063 EGJA patients and 1677 noncancer controls to determine whether the lncRNAs rs944289 C > T and rs7990916 C > T polymorphisms could influence EGJA susceptibility and lymph node status. And SNPscan™ genotyping assay was applied to test the genotypes of the mentioned two variants. We found no statistically significant differences in the distribution of lncRNAs rs944289 C > T and rs7990916 C > T polymorphisms between EGJA patients and healthy controls. Similar negative findings were also revealed in the correlation of those polymorphisms with different lymph node status. However, after adjustment by multiple environmental factors, including gender, age, drinking, and smoking consumption, the stratified analyses showed that the lncRNAs rs944289 C > T variant was significantly related with the risk of EGJA in <60 years populations [CT vs. CC: adjusted odds ratio (OR) = 0.75, 95% confidence interval (CI) = 0.58-0.98, p = 0.032] and ever smoking populations (CT/CC vs. TT: adjusted OR = 1.65, 95% CI = 1.11-2.46, p = 0.013). In short, this population-based study highlights that lncRNAs rs944289 C > T polymorphism may be associated with genetic susceptibility to EGJA in the <60 years and ever smoking populations.

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.