Genetic sex assignment in wild populations using genotyping‐by‐sequencing data: A statistical threshold approach

Establishing the sex of individuals in wild systems can be challenging and often requires genetic testing. Genotyping‐by‐sequencing (GBS) and other reduced‐representation DNA sequencing (RRS) protocols (e.g., RADseq, ddRAD) have enabled the analysis of genetic data on an unprecedented scale. Here, we present a novel approach for the discovery and statistical validation of sex‐specific loci in GBS data sets. We used GBS to genotype 166 New Zealand fur seals (NZFS, Arctocephalus forsteri) of known sex. We retained monomorphic loci as potential sex‐specific markers in the locus discovery phase. We then used (i) a sex‐specific locus threshold (SSLT) to identify significantly male‐specific loci within our data set; and (ii) a significant sex‐assignment threshold (SSAT) to confidently assign sex in silico the presence or absence of significantly male‐specific loci to individuals in our data set treated as unknowns (98.9% accuracy for females; 95.8% for males, estimated via cross‐validation). Furthermore, we assigned sex to 86 individuals of true unknown sex using our SSAT and assessed the effect of SSLT adjustments on these assignments. From 90 verified sex‐specific loci, we developed a panel of three sex‐specific PCR primers that we used to ascertain sex independently of our GBS data, which we show amplify reliably in at least two other pinniped species. Using monomorphic loci normally discarded from large SNP data sets is an effective way to identify robust sex‐linked markers for nonmodel species. Our novel pipeline can be used to identify and statistically validate monomorphic and polymorphic sex‐specific markers across a range of species and RRS data sets.     

Optimization of the genotyping‐by‐sequencing strategy for population genomic analysis in conifers

Flexibility and low cost make genotyping‐by‐sequencing (GBS) an ideal tool for population genomic studies of nonmodel species. However, to utilize the potential of the method fully, many parameters affecting library quality and single nucleotide polymorphism (SNP) discovery require optimization, especially for conifer genomes with a high repetitive DNA content. In this study, we explored strategies for effective GBS analysis in pine species. We constructed GBS libraries using HpaII, PstI and EcoRI‐MseI digestions with different multiplexing levels and examined the effect of restriction enzymes on library complexity and the impact of sequencing depth and size selection of restriction fragments on sequence coverage bias. We tested and compared UNEAK, Stacks and GATK pipelines for the GBS data, and then developed a reference‐free SNP calling strategy for haploid pine genomes. Our GBS procedure proved to be effective in SNP discovery, producing 7000–11 000 and 14 751 SNPs within and among three pine species, respectively, from a PstI library. This investigation provides guidance for the design and analysis of GBS experiments, particularly for organisms for which genomic information is lacking.     

SNP discovery and genotyping using restriction‐site‐associated DNA sequencing in chickens

Single nucleotide polymorphisms (SNPs) are essential to the understanding of population genetic variation and diversity. Here, we performed restriction‐site‐associated DNA sequencing (RAD‐seq) on 72 individuals from 13 Chinese indigenous and three introduced chicken breeds. A total of 620 million reads were obtained using an Illumina Hiseq2000 sequencer. An average of 75 587 SNPs were identified from each individual. Further filtering strictly validated 28 895 SNPs candidates for all populations. When compared with the NCBI dbSNP (chicken_9031), 15 404 SNPs were new discoveries. In this study, RAD‐seq was performed for the first time on chickens, implicating the remarkable effectiveness and potential applications on genetic analysis and breeding technique for whole‐genome selection in chicken and other agricultural animals.     

High‐throughput SNP discovery in the rabbit (Oryctolagus cuniculus) genome by next‐generation semiconductor‐based sequencing

The European rabbit (Oryctolagus cuniculus) is a domesticated species with one of the broadest ranges of economic and scientific applications and fields of investigation. Rabbit genome information and assembly are available (oryCun2.0), but so far few studies have investigated its variability, and massive discovery of polymorphisms has not been published yet for this species. Here, we sequenced two reduced representation libraries (RRLs) to identify single nucleotide polymorphisms (SNPs) in the rabbit genome. Genomic DNA of 10 rabbits belonging to different breeds was pooled and digested with two restriction enzymes (HaeIII and RsaI) to create two RRLs which were sequenced using the Ion Torrent Personal Genome Machine. The two RRLs produced 2 917 879 and 4 046 871 reads, for a total of 280.51 Mb (248.49 Mb with quality >20) and 417.28 Mb (360.89 Mb with quality >20) respectively of sequenced DNA. About 90% and 91% respectively of the obtained reads were mapped on the rabbit genome, covering a total of 15.82% of the oryCun2.0 genome version. The mapping and ad hoc filtering procedures allowed to reliably call 62 491 SNPs. SNPs in a few genomic regions were validated by Sanger sequencing. The Variant Effect Predictor Web tool was used to map SNPs on the current version of the rabbit genome. The obtained results will be useful for many applied and basic research programs for this species and will contribute to the development of cost‐effective solutions for high‐throughput SNP genotyping in the rabbit.     

Genotyping‐in‐Thousands by sequencing reveals marked population structure in Western Rattlesnakes to inform conservation status

Delineation of units below the species level is critical for prioritizing conservation actions for species at‐risk. Genetic studies play an important role in characterizing patterns of population connectivity and diversity to inform the designation of conservation units, especially for populations that are geographically isolated. The northernmost range margin of Western Rattlesnakes (Crotalus oreganus) occurs in British Columbia, Canada, where it is federally classified as threatened and restricted to five geographic regions. In these areas, Western Rattlesnakes hibernate (den) communally, raising questions about connectivity within and between den complexes. At present, Western Rattlesnake conservation efforts are hindered by a complete lack of information on genetic structure and degree of isolation at multiple scales, from the den to the regional level. To fill this knowledge gap, we used Genotyping‐in‐Thousands by sequencing (GT‐seq) to genotype an optimized panel of 362 single nucleotide polymorphisms (SNPs) from individual samples (n = 461) collected across the snake's distribution in western Canada and neighboring Washington (USA). Hierarchical STRUCTURE analyses found evidence for population structure within and among the five geographic regions in BC, as well as in Washington. Within these regions, 11 genetically distinct complexes of dens were identified, with some regions having multiple complexes. No significant pattern of isolation‐by‐distance and generally low levels of migration were detected among den complexes across regions. Additionally, snakes within dens generally were more related than those among den complexes within a region, indicating limited movement. Overall, our results suggest that the single, recognized designatable unit for Western Rattlesnakes in Canada should be re‐assessed to proactively focus conservation efforts on preserving total genetic variation detected range‐wide. More broadly, our study demonstrates a novel application of GT‐seq for investigating patterns of diversity in wild populations at multiple scales to better inform conservation management.     

Genotyping‐by‐sequencing analysis of Orobanche crenata populations in Algeria reveals genetic differentiation

Crenate broomrape (Orobanche crenata Forsk.) is a serious long‐standing parasitic weed problem in Algeria, mainly affecting legumes but also vegetable crops. Unresolved questions for parasitic weeds revolve around the extent to which these plants undergo local adaptation, especially with respect to host specialization, which would be expected to be a strong selective factor for obligate parasitic plants. In the present study, the genotyping‐by‐sequencing (GBS) approach was used to analyze genetic diversity and population structure of 10 Northern Algerian O. crenata populations with different geographical origins and host species (faba bean, pea, chickpea, carrot, and tomato). In total, 8004 high‐quality single‐nucleotide polymorphisms (5% missingness) were obtained and used across the study. Genetic diversity and relationships of 95 individuals from 10 populations were studied using model‐based ancestry analysis, principal components analysis, discriminant analysis of principal components, and phylogeny approaches. The genetic differentiation (F _ST) between pairs of populations was lower between adjacent populations and higher between geographically separated ones, but no support was found for isolation by distance. Further analyses identified four genetic clusters and revealed evidence of structuring among populations and, although confounded with location, among hosts. In the clearest example, O. crenata growing on pea had a SNP profile that was distinct from other host/location combinations. These results illustrate the importance and potential of GBS to reveal the dynamics of parasitic weed dispersal and population structure.     

Paralogs are revealed by proportion of heterozygotes and deviations in read ratios in genotyping‐by‐sequencing data from natural populations

Whole‐genome duplications have occurred in the recent ancestors of many plants, fish, and amphibians, resulting in a pervasiveness of paralogous loci and the potential for both disomic and tetrasomic inheritance in the same genome. Paralogs can be difficult to reliably genotype and are often excluded from genotyping‐by‐sequencing (GBS) analyses; however, removal requires paralogs to be identified which is difficult without a reference genome. We present a method for identifying paralogs in natural populations by combining two properties of duplicated loci: (i) the expected frequency of heterozygotes exceeds that for singleton loci, and (ii) within heterozygotes, observed read ratios for each allele in GBS data will deviate from the 1:1 expected for singleton (diploid) loci. These deviations are often not apparent within individuals, particularly when sequence coverage is low; but, we postulated that summing allele reads for each locus over all heterozygous individuals in a population would provide sufficient power to detect deviations at those loci. We identified paralogous loci in three species: Chinook salmon (Oncorhynchus tshawytscha) which retains regions with ongoing residual tetrasomy on eight chromosome arms following a recent whole‐genome duplication, mountain barberry (Berberis alpina) which has a large proportion of paralogs that arose through an unknown mechanism, and dusky parrotfish (Scarus niger) which has largely rediploidized following an ancient whole‐genome duplication. Importantly, this approach only requires the genotype and allele‐specific read counts for each individual, information which is readily obtained from most GBS analysis pipelines.     

Haplotype‐based genotyping‐by‐sequencing in oat genome research

In a de novo genotyping‐by‐sequencing (GBS) analysis of short, 64‐base tag‐level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag‐level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635‐line diversity panel were used to infer chromosome‐level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high‐resolution genome analysis and genomic selection in oats. A combined genome‐wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component‐based genome‐wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS‐derived markers facilitate genome analysis and genomic selection in oat.     

Genotyping‐by‐sequencing‐based genome‐wide association studies on Verticillium wilt resistance in autotetraploid alfalfa (Medicago sativa L.)

Verticillium wilt (VW) is a fungal disease that causes severe yield losses in alfalfa. The most effective method to control the disease is through the development and use of resistant varieties. The identification of marker loci linked to VW resistance can facilitate breeding for disease‐resistant alfalfa. In the present investigation, we applied an integrated framework of genome‐wide association with genotyping‐by‐sequencing (GBS) to identify VW resistance loci in a panel of elite alfalfa breeding lines. Phenotyping was performed by manual inoculation of the pathogen to healthy seedlings, and scoring for disease resistance was carried out according to the standard test of the North America Alfalfa Improvement Conference (NAAIC). Marker–trait association by linkage disequilibrium identified 10 single nucleotide polymorphism (SNP) markers significantly associated with VW resistance. Alignment of the SNP marker sequences to the M. truncatula genome revealed multiple quantitative trait loci (QTLs). Three, two, one and five markers were located on chromosomes 5, 6, 7 and 8, respectively. Resistance loci found on chromosomes 7 and 8 in the present study co‐localized with the QTLs reported previously. A pairwise alignment (blastn ) using the flanking sequences of the resistance loci against the M. truncatula genome identified potential candidate genes with putative disease resistance function. With further investigation, these markers may be implemented into breeding programmes using marker‐assisted selection, ultimately leading to improved VW resistance in alfalfa.     

Genotyping‐by‐sequencing for estimating relatedness in nonmodel organisms: Avoiding the trap of precise bias

There has been remarkably little attention to using the high resolution provided by genotyping‐by‐sequencing (i.e., RADseq and similar methods) for assessing relatedness in wildlife populations. A major hurdle is the genotyping error, especially allelic dropout, often found in this type of data that could lead to downward‐biased, yet precise, estimates of relatedness. Here, we assess the applicability of genotyping‐by‐sequencing for relatedness inferences given its relatively high genotyping error rate. Individuals of known relatedness were simulated under genotyping error, allelic dropout and missing data scenarios based on an empirical ddRAD data set, and their true relatedness was compared to that estimated by seven relatedness estimators. We found that an estimator chosen through such analyses can circumvent the influence of genotyping error, with the estimator of Ritland (Genetics Research, 67, 175) shown to be unaffected by allelic dropout and to be the most accurate when there is genotyping error. We also found that the choice of estimator should not rely solely on the strength of correlation between estimated and true relatedness as a strong correlation does not necessarily mean estimates are close to true relatedness. We also demonstrated how even a large SNP data set with genotyping error (allelic dropout or otherwise) or missing data still performs better than a perfectly genotyped microsatellite data set of tens of markers. The simulation‐based approach used here can be easily implemented by others on their own genotyping‐by‐sequencing data sets to confirm the most appropriate and powerful estimator for their data.     

Resolving allele dosage in duplicated loci using genotyping‐by‐sequencing data: A path forward for population genetic analysis

Whole‐genome duplications have occurred in the recent ancestors of many plants, fish and amphibians. Signals of these whole‐genome duplications still exist in the form of paralogous loci. Recent advances have allowed reliable identification of paralogs in genotyping‐by‐sequencing (GBS) data such as that generated from restriction‐site‐associated DNA sequencing (RADSeq); however, excluding paralogs from analyses is still routine due to difficulties in genotyping. This exclusion of paralogs may filter a large fraction of loci, including loci that may be adaptively important or informative for population genetic analyses. We present a maximum‐likelihood method for inferring allele dosage in paralogs and assess its accuracy using simulated GBS, empirical RADSeq and amplicon sequencing data from Chinook salmon. We accurately infer allele dosage for some paralogs from a RADSeq data set and show how accuracy is dependent upon both read depth and allele frequency. The amplicon sequencing data set, using RADSeq‐derived markers, achieved sufficient depth to infer allele dosage for all paralogs. This study demonstrates that RADSeq locus discovery combined with amplicon sequencing of targeted loci is an effective method for incorporating paralogs into population genetic analyses.     

Sorting duplicated loci disentangles complexities of polyploid genomes masked by genotyping by sequencing

Many plants and animals of polyploid origin are currently enjoying a genomics explosion enabled by modern sequencing and genotyping technologies. However, routine filtering of duplicated loci in most studies using genotyping by sequencing introduces an unacceptable, but often overlooked, bias when detecting selection. Retained duplicates from ancient whole‐genome duplications (WGDs) may be found throughout genomes, whereas retained duplicates from recent WGDs are concentrated at distal ends of some chromosome arms. Additionally, segmental duplicates can be found at distal ends or nearly anywhere in a genome. Evidence shows that these duplications facilitate adaptation through one of two pathways: neo‐functionalization or increased gene expression. Filtering duplicates removes distal ends of some chromosomes, and distal ends are especially known to harbour adaptively important genes. Thus, filtering of duplicated loci impoverishes the interpretation of genomic data as signals from contiguous duplicated genes are ignored. We review existing strategies to genotype and map duplicated loci; we focus in detail on an overlooked strategy of using gynogenetic haploids (1N) as a part of new genotyping by sequencing studies. We provide guidelines on how to use this haploid strategy for studies on polyploid‐origin vertebrates including how it can be used to screen duplicated loci in natural populations. We conclude by discussing areas of research that will benefit from better inclusion of polyploid loci; we particularly stress the sometimes overlooked fact that basing genomic studies on dense maps provides value added in the form of locating and annotating outlier loci or colocating outliers into islands of divergence.     

Whole‐genome sequencing approaches for conservation biology: Advantages,limitations and practical recommendations

Whole‐genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled‐individual DNA (Pool‐seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.     

Population and phylogenomic decomposition via genotyping‐by‐sequencing in Australian Pelargonium

Species delimitation has seen a paradigm shift as increasing accessibility of genomic‐scale data enables separation of lineages with convergent morphological traits and the merging of recently diverged ecotypes that have distinguishing characteristics. We inferred the process of lineage formation among Australian species in the widespread and highly variable genus Pelargonium by combining phylogenomic and population genomic analyses along with breeding system studies and character analysis. Phylogenomic analysis and population genetic clustering supported seven of the eight currently described species but provided little evidence for differences in genetic structure within the most widely distributed group that containing P. australe. In contrast, morphometric analysis detected three deep lineages within Australian Pelargonium; with P. australe consisting of five previously unrecognized entities occupying separate geographic ranges. The genomic approach enabled elucidation of parallel evolution in some traits formerly used to delineate species, as well as identification of ecotypic morphological differentiation within recognized species. Highly variable morphology and trait convergence each contribute to the discordance between phylogenomic relationships and morphological taxonomy. Data suggest that genetic divergence among species within the Australian Pelargonium may result from allopatric speciation while morphological differentiation within and among species may be more strongly driven by environmental differences.     

Mapping‐by‐sequencing in complex polyploid genomes using genic sequence capture: a case study to map yellow rust resistance in hexaploid wheat

Previously we extended the utility of mapping‐by‐sequencing by combining it with sequence capture and mapping sequence data to pseudo‐chromosomes that were organized using wheat–Brachypodium synteny. This, with a bespoke haplotyping algorithm, enabled us to map the flowering time locus in the diploid wheat Triticum monococcum L. identifying a set of deleted genes (Gardiner et al., 2014). Here, we develop this combination of gene enrichment and sliding window mapping‐by‐synteny analysis to map the Yr6 locus for yellow stripe rust resistance in hexaploid wheat. A 110 MB NimbleGen capture probe set was used to enrich and sequence a doubled haploid mapping population of hexaploid wheat derived from an Avalon and Cadenza cross. The Yr6 locus was identified by mapping to the POPSEQ chromosomal pseudomolecules using a bespoke pipeline and algorithm (Chapman et al., 2015). Furthermore the same locus was identified using newly developed pseudo‐chromosome sequences as a mapping reference that are based on the genic sequence used for sequence enrichment. The pseudo‐chromosomes allow us to demonstrate the application of mapping‐by‐sequencing to even poorly defined polyploidy genomes where chromosomes are incomplete and sub‐genome assemblies are collapsed. This analysis uniquely enabled us to: compare wheat genome annotations; identify the Yr6 locus – defining a smaller genic region than was previously possible; associate the interval with one wheat sub‐genome and increase the density of SNP markers associated. Finally, we built the pipeline in iPlant, making it a user‐friendly community resource for phenotype mapping.     

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

Whole genome sequences (WGS) greatly increase our ability to precisely infer population genetic parameters, demographic processes, and selection signatures. However, WGS may still be not affordable for a representative number of individuals/populations. In this context, our goal was to assess the efficiency of several SNP genotyping strategies by testing their ability to accurately estimate parameters describing neutral diversity and to detect signatures of selection. We analysed 110 WGS at 12× coverage for four different species, i.e., sheep, goats and their wild counterparts. From these data we generated 946 data sets corresponding to random panels of 1K to 5M variants, commercial SNP chips and exome capture, for sample sizes of five to 48 individuals. We also extracted low‐coverage genome resequencing of 1×, 2× and 5× by randomly subsampling reads from the 12× resequencing data. Globally, 5K to 10K random variants were enough for an accurate estimation of genome diversity. Conversely, commercial panels and exome capture displayed strong ascertainment biases. Besides the characterization of neutral diversity, the detection of the signature of selection and the accurate estimation of linkage disequilibrium (LD) required high‐density panels of at least 1M variants. Finally, genotype likelihoods increased the quality of variant calling from low coverage resequencing but proportions of incorrect genotypes remained substantial, especially for heterozygote sites. Whole genome resequencing coverage of at least 5× appeared to be necessary for accurate assessment of genomic variations. These results have implications for studies seeking to deploy low‐density SNP collections or genome scans across genetically diverse populations/species showing similar genetic characteristics and patterns of LD decay for a wide variety of purposes.     

GIbPSs: a toolkit for fast and accurate analyses of genotyping‐by‐sequencing data without a reference genome

Genotyping‐by‐sequencing (GBS) and related methods are increasingly used for studies of non‐model organisms from population genetic to phylogenetic scales. We present GIbPSs, a new genotyping toolkit for the analysis of data from various protocols such as RAD, double‐digest RAD, GBS, and two‐enzyme GBS without a reference genome. GIbPSs can handle paired‐end GBS data and is able to assign reads from both strands of a restriction fragment to the same locus. GIbPSs is most suitable for population genetic and phylogeographic analyses. It avoids genotyping errors due to indel variation by identifying and discarding affected loci. GIbPSs creates a genotype database that offers rich functionality for data filtering and export in numerous formats. We performed comparative analyses of simulated and real GBS data with GIbPSs and another program, pyRAD. This program accounts for indel variation by aligning homologous sequences. GIbPSs performed better than pyRAD in several aspects. It required much less computation time and displayed higher genotyping accuracy. GIbPSs retained smaller numbers of loci overall in analyses of real GBS data. It nevertheless delivered more complete genotype matrices with greater locus overlap between individuals and greater numbers of loci sampled in all individuals.     

simMSG: an experimental design tool for high‐throughput genotyping of hybrids

Hybridization between closely related species, whether naturally occurring or laboratory generated, is a useful tool for mapping the genetic basis of the phenotypic traits that distinguish species. The development of next‐generation sequencing techniques has greatly improved our ability to assign ancestry to hybrid genomes. One such next‐generation sequencing technique, multiplexed shotgun genotyping (or MSG), can be a powerful tool for genotyping hybrids. However, it is difficult a priori to predict the accuracy of MSG in natural hybrids because accuracy depends on ancestry tract length and number of ancestry informative markers. Here, we present a simulator, ‘simMSG’, that will allow researchers to design MSG experiments and show that in many cases MSG can accurately assign ancestry to hundreds of thousands of sites in the genomes of natural hybrids. The simMSG tool can be used to design experiments for diverse applications including QTL mapping, genotyping introgressed lines or admixture mapping.     

Genetic diversity and population structure of Quercus fabri Hance in China revealed by genotyping‐by‐sequencing

Analysis of genetic diversity and population structure among Quercus fabri populations is essential for the conservation and utilization of Q. fabri resources. Here, the genetic diversity and structure of 158 individuals from 13 natural populations of Quercus fabri in China were analyzed using genotyping‐by‐sequencing (GBS). A total of 459,564 high‐quality single nucleotide polymorphisms (SNPs) were obtained after filtration for subsequent analysis. Genetic structure analysis revealed that these individuals can be clustered into two groups and the structure can be explained mainly by the geographic barrier, showed gene introgression from coastal to inland areas and high mountains could significantly hinder the mutual introgression of genes. Genetic diversity analysis indicated that the individual differences within groups are greater than the differences between the two groups. These results will help us better understand the genetic backgrounds of Q. fabri.