SNP discovery in European anchovy (Engraulis encrasicolus, L) by high-throughput transcriptome and genome sequencing

Single Nucleotide Polymorphism Markers with Applications in Conservation and Exploitation of Aquatic Natural Populations

An increasing number of aquatic species have been studied for genetic polymorphism, which extends the knowledge on their natural populations. One type of high-resolution molecular marker suitable for studying the genetic diversity of large numbers of individuals is single nucleotide polymorphism (SNP). This review is an attempt to show the range of applications of SNPs in studies of natural populations of aquatic animals. In recent years, SNPs have been used in the genetic analysis of wild and enhanced fish and invertebrate populations in natural habitats, exploited migratory species in the oceans, migratory anadromous and freshwater fish and demersal species. SNPs have been used for the identification of species and their hybrids in natural environments, to study the genetic consequences of restocking for conservation purposes and the negative effects on natural populations of fish accidentally escaping from culture. SNPs are very useful for identifying genomic regions correlated with phenotypic variants relevant for wildlife protection, management and aquaculture. Experimental size-selective catches of populations created in tanks have caused evolutionary changes in life cycles of fishes. The research results have been discussed to clarify whether the fish populations in natural conditions can undergo changes due to selective harvesting targeting the fastest-growing fishes.

Aquaculture omics: An update on the current status of research and data analysis

Aquaculture is the fast-growing agricultural sector and has the ability to meet the growing demand for protein nutritional security for future population. In future aquaculture is going to be the major source of fish proteins as capture fisheries reached at its maximum. However, several challenges need to overcome such as lack of genetically improved strains/varieties, lack of species-specific feed/functional feed, round the year availability of quality fish seed, pollution of ecosystems and increased frequencies of disease occurrence etc. In recent years, the continuous development of high throughput sequencing technology has revolutionized the biological sciences and provided necessary tools. Application of 'omics' in aquaculture research have been successfully used to resolve several productive and reproductive issues and thus ensure its sustainability and profitability. To date, high quality draft genomes of over fifty fish species have been generated and successfully used to develop large number of single nucleotide polymorphism markers (SNPs), marker panels and other genomic resources etc in several aquaculture species. Similarly, transcriptome profiling and miRNAs analysis have been used in aquaculture research to identify key transcripts and expression analysis of candidate genes/miRNAs involved in reproduction, immunity, growth, development, stress toxicology and disease. Metagenome analysis emerged as a promising scientific tool to analyze the complex genomes contained within microbial communities. Metagenomics has been successfully used in the aquaculture sector to identify novel and potential pathogens, antibiotic resistance genes, microbial roles in microcosms, microbial communities forming biofloc, probiotics etc. In the current review, we discussed application of high-throughput technologies (NGS) in the aquaculture sector.

Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs

BACKGROUND

With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and F_ST) to select the most informative SNPs for ancestry inference.

RESULTS

Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof.

CONCLUSIONS

The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.

EXFI: Exon and splice graph prediction without a reference genome

For population genetic studies in nonmodel organisms, it is important to use every single source of genomic information. This paper presents EXFI, a Python pipeline that predicts the splice graph and exon sequences using an assembled transcriptome and raw whole-genome sequencing reads. The main algorithm uses Bloom filters to remove reads that are not part of the transcriptome, to predict the intron-exon boundaries, to then proceed to call exons from the assembly, and to generate the underlying splice graph. The results are returned in GFA1 format, which encodes both the predicted exon sequences and how they are connected to form transcripts. EXFI is written in Python, tested on Linux platforms, and the source code is available under the MIT License at https://github.com/jlanga/exfi.

A novel transcriptome-derived SNPs array for tench (Tinca tinca L.)

Tench (Tinca tinca L.) has great economic potential due to its high rate of fecundity and long-life span. Population genetic studies based on allozymes, microsatellites, PCR-RFLP and sequence analysis of genes and DNA fragments have revealed the presence of Eastern and Western phylogroups. However, the lack of genomic resources for this species has complicated the development of genetic markers. In this study, the tench transcriptome and genome were sequenced by high-throughput sequencing. A total of 60,414 putative SNPs were identified in the tench transcriptome using a computational pipeline. A set of 96 SNPs was selected for validation and a total of 92 SNPs was validated, resulting in the highest conversion and validation rate for a non-model species obtained to date (95.83%). The validated SNPs were used to genotype 140 individuals belonging to two tench breeds (Tabor and Hungarian), showing low (FST = 0.0450) but significant (<0.0001) genetic differentiation between the two tench breeds. This implies that set of validated SNPs array can be used to distinguish the tench breeds and that it might be useful for studying a range of associations between DNA sequence and traits of importance. These genomic resources created for the tench will provide insight into population genetics, conservation fish stock management, and aquaculture.

Chloroplast genome analyses and genomic resource development for epilithic sister genera Oresitrophe and Mukdenia (Saxifragaceae), using genome skimming data

Background

Epilithic sister genera Oresitrophe and Mukdenia (Saxifragaceae) have an epilithic habitat (rocky slopes) and a parapatric distribution in East Asia, which makes them an ideal model for a more comprehensive understanding of the demographic and divergence history and the influence of climate changes in East Asia. However, the genetic background and resources for these two genera are scarce.

Results

The complete chloroplast (cp) genomes of two Oresitrophe rupifraga and one Mukdenia rossii individuals were reconstructed and comparative analyses were conducted to examine the evolutionary pattern of chloroplast genomes in Saxifragaceae. The cp genomes ranged from 156,738 bp to 156,960 bp in length and had a typical quadripartite structure with a conserved genome arrangement. Comparative analysis revealed the intron of rpl2 has been lost in Heuchera parviflora, Tiarella polyphylla, M. rossii and O. rupifraga but presents in the reference genome of Penthorum chinense. Seven cp hotspot regions (trnH-psbA, trnR-atpA, atpI-rps2, rps2-rpoC2, petN-psbM, rps4-trnT and rpl33-rps18) were identified between Oresitrophe and Mukdenia, while four hotspots (trnQ-psbK, trnR-atpA, trnS-psbZ and rpl33-rps18) were identified within Oresitrophe. In addition, 24 polymorphic cpSSR loci were found between Oresitrophe and Mukdenia. Most importantly, we successfully developed 126 intergeneric polymorphic gSSR markers between Oresitrophe and Mukdenia, as well as 452 intrageneric ones within Oresitrophe. Twelve randomly selected intergeneric gSSRs have shown that these two genera exhibit a significant genetic structure.

Conclusions

In this study, we conducted genome skimming for Oresitrophe rupifraga and Mukdenia rossii. Using these data, we were able to not only assemble their complete chloroplast genomes, but also develop abundant genetic resources (cp hotspots, cpSSRs, polymorphic gSSRs). The genomic patterns and genetic resources presented here will contribute to further studies on population genetics, phylogeny and conservation biology in Saxifragaceae.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4633-x) contains supplementary material, which is available to authorized users.

Genetic fingerprinting of salmon louse (Lepeophtheirus salmonis) populations in the North-East Atlantic using a random forest classification approach

Caligid sea lice represent a significant threat to salmonid aquaculture worldwide. Population genetic analyses have consistently shown minimal population genetic structure in North Atlantic Lepeophtheirus salmonis, frustrating efforts to track louse populations and improve targeted control measures. The aim of this study was to test the power of reduced representation library sequencing (IIb-RAD sequencing) coupled with random forest machine learning algorithms to define markers for fine-scale discrimination of louse populations. We identified 1286 robustly supported SNPs among four L. salmonis populations from Ireland, Scotland and Northern Norway. Only weak global structure was observed based on the full SNP dataset. The application of a random forest machine-learning algorithm identified 98 discriminatory SNPs that dramatically improved population assignment, increased global genetic structure and resulted in significant genetic population differentiation. A large proportion of SNPs found to be under directional selection were also identified to be highly discriminatory. Our data suggest that it is possible to discriminate between nearby L. salmonis populations given suitable marker selection approaches, and that such differences might have an adaptive basis. We discuss these data in light of sea lice adaption to anthropogenic and environmental pressures as well as novel approaches to track and predict sea louse dispersal.

Reduced Single Nucleotide Polymorphism Panels for Assigning Atlantic Albacore and Bay of Biscay Anchovy Individuals to Their Geographic Origin: Toward Sustainable Fishery Management

There is an increasing trend upon adding a detailed description of the origin of seafood products driven by a general interest in the implementation of sustainable fishery management plans for the conservation of marine ecosystems. North Atlantic albacore ("Bonito del Norte con Eusko Label") and Bay of Biscay anchovy ("Anchoa del Cantábrico") are two commercially important fish populations with high economical value and vulnerable to commercial fraud. This fact, together with the overexploited situation of these two populations, makes it necessary to develop a tool to identify individual origin and to detect commercial fraud. In the present study, we have developed and validated a traceability tool consisting of reduced panels of gene-associated single nucleotide polymorphisms (SNPs) suitable for assigning individuals of two species to their origin with unprecedented accuracy levels. Only 48 SNPs are necessary to assign 81.1% albacore and 93.4% anchovy individuals with 100% accuracy to their geographic origin. The total accuracy of the results demonstrates how gene-associated SNPs can revolutionize food traceability. Gene-associated SNP panels are not of mere commercial interest, but they also can result in a positive impact on sustainability of marine ecosystems through conservation of fish populations through establishing a more effective and sustainable fishery management framework and contributing to the prevention of falsified labeling.

Large-scale SNP screenings identify markers linked with GCRV resistant traits through transcriptomes of individuals and cell lines in Ctenopharyngodon idella

Grass carp (Ctenopharyngodon idella) is an important economic species in freshwater aquaculture and its industry has been confined due to variety degeneration and frequent diseases. Marker-assisted selection is a feasible method for selective breeding of new varieties. Transcriptome data have greatly facilitated high-throughput single nucleotide polymorphism (SNP) marker discovery and phenotype association study. In this study, we gained a total of 25,981 and 5,775 high quality SNPs in two transcriptomes from individuals and cell lines, respectively. Comparative transcriptome analysis identified 413 and 832 grass carp reovirus (GCRV)-resistant-association SNPs as well as 1,381 and 1,606 GCRV-susceptible-association SNPs in individuals and cell lines, respectively. Integrated analysis indicated 22 genes with single SNP share common resistant/susceptible traits in two transcriptomes. Furthermore, we infected grass carp with GCRV, genotyping and association analyses were performed, and 9 in 22 SNPs were confirmed by PCR-RFLP. Meanwhile, mRNA expression profiles of 6 genes containing confirmed SNPs were examined by qRT-PCR. The results demonstrated that mRNA expressions were significant differences in resistant/susceptible individuals and cell lines. The present study develops an important strategy for high throughput screening of phenotype association genetic markers and the results will serve in grass carp breeding for GCRV resistance.

Transcriptomic SNP discovery for custom genotyping arrays: impacts of sequence data, SNP calling method and genotyping technology on the probability of validation success

BACKGROUND

Single nucleotide polymorphism (SNP) discovery is an important goal of many studies. However, the number of 'putative' SNPs discovered from a sequence resource may not provide a reliable indication of the number that will successfully validate with a given genotyping technology. For this it may be necessary to account for factors such as the method used for SNP discovery and the type of sequence data from which it originates, suitability of the SNP flanking sequences for probe design, and genomic context. To explore the relative importance of these and other factors, we used Illumina sequencing to augment an existing Roche 454 transcriptome assembly for the Antarctic fur seal (Arctocephalus gazella). We then mapped the raw Illumina reads to the new hybrid transcriptome using BWA and BOWTIE2 before calling SNPs with GATK. The resulting markers were pooled with two existing sets of SNPs called from the original 454 assembly using NEWBLER and SWAP454. Finally, we explored the extent to which SNPs discovered using these four methods overlapped and predicted the corresponding validation outcomes for both Illumina Infinium iSelect HD and Affymetrix Axiom arrays.

RESULTS

Collating markers across all discovery methods resulted in a global list of 34,718 SNPs. However, concordance between the methods was surprisingly poor, with only 51.0 % of SNPs being discovered by more than one method and 13.5 % being called from both the 454 and Illumina datasets. Using a predictive modeling approach, we could also show that SNPs called from the Illumina data were on average more likely to successfully validate, as were SNPs called by more than one method. Above and beyond this pattern, predicted validation outcomes were also consistently better for Affymetrix Axiom arrays.

CONCLUSIONS

Our results suggest that focusing on SNPs called by more than one method could potentially improve validation outcomes. They also highlight possible differences between alternative genotyping technologies that could be explored in future studies of non-model organisms.

Molecular Inversion Probes for targeted resequencing in non-model organisms

Applications that require resequencing of hundreds or thousands of predefined genomic regions in numerous samples are common in studies of non-model organisms. However few approaches at the scale intermediate between multiplex PCR and sequence capture methods are available. Here we explored the utility of Molecular Inversion Probes (MIPs) for the medium-scale targeted resequencing in a non-model system. Markers targeting 112 bp of exonic sequence were designed from transcriptome of Lissotriton newts. We assessed performance of 248 MIP markers in a sample of 85 individuals. Among the 234 (94.4%) successfully amplified markers 80% had median coverage within one order of magnitude, indicating relatively uniform performance; coverage uniformity across individuals was also high. In the analysis of polymorphism and segregation within family, 77% of 248 tested MIPs were confirmed as single copy Mendelian markers. Genotyping concordance assessed using replicate samples exceeded 99%. MIP markers for targeted resequencing have a number of advantages: high specificity, high multiplexing level, low sample requirement, straightforward laboratory protocol, no need for preparation of genomic libraries and no ascertainment bias. We conclude that MIP markers provide an effective solution for resequencing targets of tens or hundreds of kb in any organism and in a large number of samples.

Comparative transcriptome analysis of two oysters, Crassostrea gigas and Crassostrea hongkongensis provides insights into adaptation to hypo-osmotic conditions

Environmental salinity creates a key barrier to limit the distribution of most aquatic organisms. Adaptation to osmotic fluctuation is believed to be a factor facilitating species diversification. Adaptive evolution often involves beneficial mutations at more than one locus. Bivalves hold great interest, with numerous species living in waters, as osmoconformers, who maintain the osmotic pressure balance mostly by free amino acids. In this study, 107,076,589 reads from two groups of Crassostrea hongkongensis were produced and the assembled into 130,629 contigs. Transcripts putatively involved in stress-response, innate immunity and cell processes were identified according to Gene ontology and KEGG pathway analyses. Comparing with the transcriptome of C. gigas to characterize the diversity of transcripts between species with osmotic divergence, we identified 182,806 high-quality single nucleotide polymorphisms (SNPs) for C. hongkongensis, and 196,779 SNPs for C. gigas. Comparison of 11,602 pairs of putative orthologs allowed for identification of 14 protein-coding genes that experienced strong positive selection (Ka/Ks>1). In addition, 45 genes that may show signs of moderate positive selection (1 ≥ Ka/Ks>0.5) were also identified. Based on Ks ratios and divergence time between the two species published previously, we estimated a neutral transcriptome-wide substitution mutation rate of 1.39 × 10(-9) per site per year. Several genes were differentially expressed across the control and treated groups of each species. This is the first time to sequence the transcriptome of C. hongkongensis and provide the most comprehensive transcriptomic resource available for it. The increasing amount of transcriptome data on Crassostrea provides an excellent resource for phylogenetic analysis. A large number of SNPs identified in this work are expected to provide valuable resources for future marker and genotyping assay development. The analysis of natural selection provides an innovative view on the adaptation within species and sets the basis for future genetic and evolutionary studies.

Population genomics of marine fishes: next-generation prospects and challenges

Over the past few years, technological advances have facilitated giant leaps forward in our ability to generate genome-wide molecular data, offering exciting opportunities for gaining new insights into the ecology and evolution of species where genomic information is still limited. Marine fishes are valuable organisms for advancing our understanding of evolution on historical and contemporary time scales, and here we highlight areas in which research on these species is likely to be particularly important in the near future. These include possibilities for gaining insights into processes on ecological time scales, identifying genomic signatures associated with population divergence under gene flow, and determining the genetic basis of phenotypic traits. We also consider future challenges pertaining to the implementation of genome-wide coverage through next-generation sequencing and genotyping methods in marine fishes. Complications associated with fast decay of linkage disequilibrium, as expected for species with large effective population sizes, and the possibility that adaptation is associated with both soft selective sweeps and polygenic selection, leaving complex genomic signatures in natural populations, are likely to challenge future studies. However, the combination of high genome coverage and new statistical developments offers promising solutions. Thus, the next generation of studies is likely to truly facilitate the transition from population genetics to population genomics in marine fishes. This transition will advance our understanding of basic evolutionary processes and will offer new possibilities for conservation and management of valuable marine resources.