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.     

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.     

Genotype‐free estimation of allele frequencies reduces bias and improves demographic inference from RADSeq data

Restriction‐site associated DNA sequencing (RADSeq) facilitates rapid generation of thousands of genetic markers at relatively low cost; however, several sources of error specific to RADSeq methods often lead to biased estimates of allele frequencies and thereby to erroneous population genetic inference. Estimating the distribution of sample allele frequencies without calling genotypes was shown to improve population inference from whole genome sequencing data, but the ability of this approach to account for RADSeq‐specific biases remains unexplored. Here we assess in how far genotype‐free methods of allele frequency estimation affect demographic inference from empirical RADSeq data. Using the well‐studied pied flycatcher (Ficedula hypoleuca) as a study system, we compare allele frequency estimation and demographic inference from whole genome sequencing data with that from RADSeq data matched for samples using both genotype‐based and genotype free methods. The demographic history of pied flycatchers as inferred from RADSeq data was highly congruent with that inferred from whole genome resequencing (WGS) data when allele frequencies were estimated directly from the read data. In contrast, when allele frequencies were derived from called genotypes, RADSeq‐based estimates of most model parameters fell outside the 95% confidence interval of estimates derived from WGS data. Notably, more stringent filtering of the genotype calls tended to increase the discrepancy between parameter estimates from WGS and RADSeq data, respectively. The results from this study demonstrate the ability of genotype‐free methods to improve allele frequency spectrum‐ (AFS‐) based demographic inference from empirical RADSeq data and highlight the need to account for uncertainty in NGS data regardless of sequencing method.     

Ultra‐deep Illumina sequencing accurately identifies MHC class IIb alleles and provides evidence for copy number variation in the guppy (Poecilia reticulata)

We address the bioinformatic issue of accurately separating amplified genes of the major histocompatibility complex (MHC) from artefacts generated during high‐throughput sequencing workflows. We fit observed ultra‐deep sequencing depths (hundreds to thousands of sequences per amplicon) of allelic variants to expectations from genetic models of copy number variation (CNV). We provide a simple, accurate and repeatable method for genotyping multigene families, evaluating our method via analyses of 209 b of MHC class IIb exon 2 in guppies (Poecilia reticulata). Genotype repeatability for resequenced individuals (N = 49) was high (100%) within the same sequencing run. However, repeatability dropped to 83.7% between independent runs, either because of lower mean amplicon sequencing depth in the initial run or random PCR effects. This highlights the importance of fully independent replicates. Significant improvements in genotyping accuracy were made by greatly reducing type I genotyping error (i.e. accepting an artefact as a true allele), which may occur when using low‐depth allele validation thresholds used by previous methods. Only a small amount (4.9%) of type II error (i.e. rejecting a genuine allele as an artefact) was detected through fully independent sequencing runs. We observed 1–6 alleles per individual, and evidence of sharing of alleles across loci. Variation in the total number of MHC class II loci among individuals, both among and within populations was also observed, and some genotypes appeared to be partially hemizygous; total allelic dosage added up to an odd number of allelic copies. Collectively, observations provide evidence of MHC CNV and its complex basis in natural populations.     

Characterizing restriction enzyme‐associated loci in historic ragweed (Ambrosia artemisiifolia) voucher specimens using custom‐designed RNA probes

Population genetic studies of nonmodel organisms frequently employ reduced representation library (RRL) methodologies, many of which rely on protocols in which genomic DNA is digested by one or more restriction enzymes. However, because high molecular weight DNA is recommended for these protocols, samples with degraded DNA are generally unsuitable for RRL methods. Given that ancient and historic specimens can provide key temporal perspectives to evolutionary questions, we explored how custom‐designed RNA probes could enrich for RRL loci (Restriction Enzyme‐Associated Loci baits, or REALbaits). Starting with genotyping‐by‐sequencing (GBS) data generated on modern common ragweed (Ambrosia artemisiifolia L.) specimens, we designed 20 000 RNA probes to target well‐characterized genomic loci in herbarium voucher specimens dating from 1835 to 1913. Compared to shotgun sequencing, we observed enrichment of the targeted loci at 19‐ to 151‐fold. Using our GBS capture pipeline on a data set of 38 herbarium samples, we discovered 22 813 SNPs, providing sufficient genomic resolution to distinguish geographic populations. For these samples, we found that dilution of REALbaits to 10% of their original concentration still yielded sufficient data for downstream analyses and that a sequencing depth of ~7m reads was sufficient to characterize most loci without wasting sequencing capacity. In addition, we observed that targeted loci had highly variable rates of success, which we primarily attribute to similarity between loci, a trait that ultimately interferes with unambiguous read mapping. Our findings can help researchers design capture experiments for RRL loci, thereby providing an efficient means to integrate samples with degraded DNA into existing RRL data sets.     

Estimation of population allele frequencies from next‐generation sequencing data: pool‐versus individual‐based genotyping

Molecular markers produced by next‐generation sequencing (NGS) technologies are revolutionizing genetic research. However, the costs of analysing large numbers of individual genomes remain prohibitive for most population genetics studies. Here, we present results based on mathematical derivations showing that, under many realistic experimental designs, NGS of DNA pools from diploid individuals allows to estimate the allele frequencies at single nucleotide polymorphisms (SNPs) with at least the same accuracy as individual‐based analyses, for considerably lower library construction and sequencing efforts. These findings remain true when taking into account the possibility of substantially unequal contributions of each individual to the final pool of sequence reads. We propose the intuitive notion of effective pool size to account for unequal pooling and derive a Bayesian hierarchical model to estimate this parameter directly from the data. We provide a user‐friendly application assessing the accuracy of allele frequency estimation from both pool‐ and individual‐based NGS population data under various sampling, sequencing depth and experimental error designs. We illustrate our findings with theoretical examples and real data sets corresponding to SNP loci obtained using restriction site–associated DNA (RAD) sequencing in pool‐ and individual‐based experiments carried out on the same population of the pine processionary moth (Thaumetopoea pityocampa). NGS of DNA pools might not be optimal for all types of studies but provides a cost‐effective approach for estimating allele frequencies for very large numbers of SNPs. It thus allows comparison of genome‐wide patterns of genetic variation for large numbers of individuals in multiple populations.     

Congruent population structure across paralogous and nonparalogous loci in Salish Sea chum salmon (Oncorhynchus keta)

Whole‐genome duplications are major evolutionary events with a lasting impact on genome structure. Duplication events complicate genetic analyses as paralogous sequences are difficult to distinguish; consequently, paralogs are often excluded from studies. The effects of an ancient whole‐genome duplication (approximately 88 MYA) are still evident in salmonids through the persistence of numerous paralogous gene sequences and partial tetrasomic inheritance. We use restriction site‐associated DNA sequencing on 10 collections of chum salmon from the Salish Sea in the USA and Canada to investigate genetic diversity and population structure in both tetrasomic and rediploidized regions of the genome. We use a pedigree and high‐density linkage map to identify paralogous loci and to investigate genetic variation across the genome. By applying multivariate statistical methods, we show that it is possible to characterize paralogous loci and that they display similar patterns of population structure as the diploidized portion of the genome. We find genetic associations with the adaptively important trait of run‐timing in both sets of loci. By including paralogous loci in genome scans, we can observe evolutionary signals in genomic regions that have routinely been excluded from population genetic studies in other polyploid‐derived species.     

Using genotyping‐by‐sequencing to predict gender in animals

Gender assignment errors are common in some animal species and lead to inaccuracies in downstream analyses. Procedures for detecting gender misassignment are available for array‐based SNP data but are still being developed for genotyping‐by‐sequencing (GBS) data. In this study, we describe a method for using GBS data to predict gender using X and Y chromosomal SNPs. From a set of 1286 X chromosomal and 23 Y chromosomal deer (Cervus sp.) SNPs discovered from GBS sequence reads, a prediction model was built using a training dataset of 422 Red deer and validated using a test dataset of 868 Red deer and Wapiti deer. Prediction was based on the proportion of heterozygous genotypes on the X chromosome and the proportion of non‐missing genotypes on the Y chromosome observed in each individual. The concordance between recorded gender and predicted gender was 98.6% in the training dataset and 99.3% in the test dataset. The model identified five individuals across both datasets with incorrect recorded gender and was unable to predict gender for another five individuals. Overall, our method predicted gender with a high degree of accuracy and could be used for quality control in gender assignment datasets or for assigning gender when unrecorded, provided a suitable reference genome is available.     

Family‐assisted inference of the genetic architecture of major histocompatibility complex variation

With their direct link to individual fitness, genes of the major histocompatibility complex (MHC) are a popular system to study the evolution of adaptive genetic diversity. However, owing to the highly dynamic evolution of the MHC region, the isolation, characterization and genotyping of MHC genes remain a major challenge. While high‐throughput sequencing technologies now provide unprecedented resolution of the high allelic diversity observed at the MHC, in many species, it remains unclear (i) how alleles are distributed among MHC loci, (ii) whether MHC loci are linked or segregate independently and (iii) how much copy number variation (CNV) can be observed for MHC genes in natural populations. Here, we show that the study of allele segregation patterns within families can provide significant insights in this context. We sequenced two MHC class I (MHC‐I) loci in 1267 European barn owls (Tyto alba), including 590 offspring from 130 families using Illumina MiSeq technology. Coupled with a high per‐individual sequencing coverage (~3000×), the study of allele segregation patterns within families provided information on three aspects of the architecture of MHC‐I variation in barn owls: (i) extensive sharing of alleles among loci, (ii) strong linkage of MHC‐I loci indicating tandem architecture and (iii) the presence of CNV in the barn owl MHC‐I. We conclude that the additional information that can be gained from high‐coverage amplicon sequencing by investigating allele segregation patterns in families not only helps improving the accuracy of MHC genotyping, but also contributes towards enhanced analyses in the context of MHC evolutionary ecology.     

Testing genotyping strategies for ultra‐deep sequencing of a co‐amplifying gene family: MHC class I in a passerine bird

Characterization of highly duplicated genes, such as genes of the major histocompatibility complex (MHC), where multiple loci often co‐amplify, has until recently been hindered by insufficient read depths per amplicon. Here, we used ultra‐deep Illumina sequencing to resolve genotypes at exon 3 of MHC class I genes in the sedge warbler (Acrocephalus schoenobaenus). We sequenced 24 individuals in two replicates and used this data, as well as a simulated data set, to test the effect of amplicon coverage (range: 500–20 000 reads per amplicon) on the repeatability of genotyping using four different genotyping approaches. A third replicate employed unique barcoding to assess the extent of tag jumping, that is swapping of individual tag identifiers, which may confound genotyping. The reliability of MHC genotyping increased with coverage and approached or exceeded 90% within‐method repeatability of allele calling at coverages of >5000 reads per amplicon. We found generally high agreement between genotyping methods, especially at high coverages. High reliability of the tested genotyping approaches was further supported by our analysis of the simulated data set, although the genotyping approach relying primarily on replication of variants in independent amplicons proved sensitive to repeatable errors. According to the most repeatable genotyping method, the number of co‐amplifying variants per individual ranged from 19 to 42. Tag jumping was detectable, but at such low frequencies that it did not affect the reliability of genotyping. We thus demonstrate that gene families with many co‐amplifying genes can be reliably genotyped using HTS, provided that there is sufficient per amplicon coverage.     

quaddRAD: a new high‐multiplexing and PCR duplicate removal ddRAD protocol produces novel evolutionary insights in a nonradiating cichlid lineage

The identification of thousands of variants across the genomes and their accurate genotyping are crucial for estimating the genetic parameters needed to address a host of molecular ecological and evolutionary questions. With rapid advances of massively parallel high‐throughput sequencing technologies, several methods have recently been developed to access genomewide data on population variation. One of the most successful and widely used techniques relies on the combination of restriction enzymes and sequencing‐by‐synthesis: restriction‐site‐associated DNA sequencing (RADSeq). We developed a new, more time‐ and cost‐efficient double‐digest RAD paired‐end protocol (quaddRAD) that simplifies and speeds up the identification of PCR duplicates and permits large‐scale multiplexing. Assessing its performance on a technical data set, we also applied the quaddRAD method on population samples of a Neotropical cichlid fish lineage (Archocentrus centrarchus) to assess its genetic structure and demographic history. While we identified allopatric interlake genetic divergence, most likely driven by drift, no signature of sympatric divergence was detected. This differs from what has been observed in the clade of Midas cichlids (Amphilophus citrinellus spp.), another cichlid lineage that inhabits the same lakes and shares a similar demographic history, but has evolved into small‐scale adaptive radiations via sympatric speciation. We demonstrate that quaddRAD is a robust and efficient method for genotyping a massive number and widely overlapping set of loci with high accuracy. Furthermore, the results on A. centrarchus open new research avenues providing an ideal system to investigate genome‐level mechanisms that could alter the speciation potential of different but closely related cichlid lineages.     

Validation of Genotyping-By-Sequencing Analysis in Populations of Tetraploid Alfalfa by 454 Sequencing

Genotyping-by-sequencing (GBS) is a relatively low-cost high throughput genotyping technology based on next generation sequencing and is applicable to orphan species with no reference genome. A combination of genome complexity reduction and multiplexing with DNA barcoding provides a simple and affordable way to resolve allelic variation between plant samples or populations. GBS was performed on ApeKI libraries using DNA from 48 genotypes each of two heterogeneous populations of tetraploid alfalfa (Medicago sativa spp. sativa): the synthetic cultivar Apica (ATF0) and a derived population (ATF5) obtained after five cycles of recurrent selection for superior tolerance to freezing (TF). Nearly 400 million reads were obtained from two lanes of an Illumina HiSeq 2000 sequencer and analyzed with the Universal Network-Enabled Analysis Kit (UNEAK) pipeline designed for species with no reference genome. Following the application of whole dataset-level filters, 11,694 single nucleotide polymorphism (SNP) loci were obtained. About 60% had a significant match on the Medicago truncatula syntenic genome. The accuracy of allelic ratios and genotype calls based on GBS data was directly assessed using 454 sequencing on a subset of SNP loci scored in eight plant samples. Sequencing depth in this study was not sufficient for accurate tetraploid allelic dosage, but reliable genotype calls based on diploid allelic dosage were obtained when using additional quality filtering. Principal Component Analysis of SNP loci in plant samples revealed that a small proportion (<5%) of the genetic variability assessed by GBS is able to differentiate ATF0 and ATF5. Our results confirm that analysis of GBS data using UNEAK is a reliable approach for genome-wide discovery of SNP loci in outcrossed polyploids.     

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.     

Helping decision making for reliable and cost‐effective 2b‐RAD sequencing and genotyping analyses in non‐model species

High‐throughput sequencing has revolutionized population and conservation genetics. RAD sequencing methods, such as 2b‐RAD, can be used on species lacking a reference genome. However, transferring protocols across taxa can potentially lead to poor results. We tested two different IIB enzymes (AlfI and CspCI) on two species with different genome sizes (the loggerhead turtle Caretta caretta and the sharpsnout seabream Diplodus puntazzo) to build a set of guidelines to improve 2b‐RAD protocols on non‐model organisms while optimising costs. Good results were obtained even with degraded samples, showing the value of 2b‐RAD in studies with poor DNA quality. However, library quality was found to be a critical parameter on the number of reads and loci obtained for genotyping. Resampling analyses with different number of reads per individual showed a trade‐off between number of loci and number of reads per sample. The resulting accumulation curves can be used as a tool to calculate the number of sequences per individual needed to reach a mean depth ≥20 reads to acquire good genotyping results. Finally, we demonstrated that selective‐base ligation does not affect genomic differentiation between individuals, indicating that this technique can be used in species with large genome sizes to adjust the number of loci to the study scope, to reduce sequencing costs and to maintain suitable sequencing depth for a reliable genotyping without compromising the results. Here, we provide a set of guidelines to improve 2b‐RAD protocols on non‐model organisms with different genome sizes, helping decision‐making for a reliable and cost‐effective genotyping.     

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.     

MultiplexSSR: A pipeline for developing multiplex SSR‐PCR assays from resequencing data

Next‐generation sequencing has greatly promoted the investigation of single nucleotide polymorphisms, while studies of simple sequence repeats are sharply decreasing. However, simple sequence repeats still present some advantages in conservation genetics. In this study, an end‐to‐end pipeline referred to as MultiplexSSR was established to develop multiplex PCR assays in batches with highly polymorphic simple sequence repeats for capillary platforms from resequencing data. The distribution of single sequence repeats in the genome, the error profiles of genotypes and allelotypes, and the increase in the allele length range depending on the number of individuals were investigated. A total of 98% of single sequence repeats presented lengths of less than 100 bp. The error rate of the genotyping and allelotyping of dimeric patterns was ten times higher than those for other patterns. The error rate of allelotyping was less than that of genotyping. The allele length range reached approximate saturation with 10 individuals. This pipeline uses allele numbers to select highly polymorphic loci, masks loci with variation, and applies in silico PCR to improve primer specificity. The application of the developed multiplex SSR‐PCR assays validated the pipeline's robustness, showing higher polymorphism and stability for the developed simple sequence repeats and a lower cost for genotyping and providing low‐depth resequencing data from less than a dozen individuals for the development of markers. This pipeline fills the gap between next‐generation sequencing and multiplex SSR‐PCR.     

Demographic inferences using short‐read genomic data in an approximate Bayesian computation framework: in silico evaluation of power,biases and proof of concept in Atlantic walrus

Approximate Bayesian computation (ABC) is a powerful tool for model‐based inference of demographic histories from large genetic data sets. For most organisms, its implementation has been hampered by the lack of sufficient genetic data. Genotyping‐by‐sequencing (GBS) provides cheap genome‐scale data to fill this gap, but its potential has not fully been exploited. Here, we explored power, precision and biases of a coalescent‐based ABC approach where GBS data were modelled with either a population mutation parameter (θ) or a fixed site (FS) approach, allowing single or several segregating sites per locus. With simulated data ranging from 500 to 50 000 loci, a variety of demographic models could be reliably inferred across a range of timescales and migration scenarios. Posterior estimates were informative with 1000 loci for migration and split time in simple population divergence models. In more complex models, posterior distributions were wide and almost reverted to the uninformative prior even with 50 000 loci. ABC parameter estimates, however, were generally more accurate than an alternative composite‐likelihood method. Bottleneck scenarios proved particularly difficult, and only recent bottlenecks without recovery could be reliably detected and dated. Notably, minor‐allele‐frequency filters – usual practice for GBS data – negatively affected nearly all estimates. With this in mind, we used a combination of FS and θ approaches on empirical GBS data generated from the Atlantic walrus (Odobenus rosmarus rosmarus), collectively providing support for a population split before the last glacial maximum followed by asymmetrical migration and a high Arctic bottleneck. Overall, this study evaluates the potential and limitations of GBS data in an ABC‐coalescence framework and proposes a best‐practice approach.     

SNP discovery in wild and domesticated populations of blue catfish,Ictalurus furcatus,using genotyping‐by‐sequencing and subsequent SNP validation

Blue catfish, Ictalurus furcatus, are valued in the United States as a trophy fishery for their capacity to reach large sizes, sometimes exceeding 45 kg. Additionally, blue catfish × channel catfish (I. punctatus) hybrid food fish production has recently increased the demand for blue catfish broodstock. However, there has been little study of the genetic impacts and interaction of farmed, introduced and stocked populations of blue catfish. We utilized genotyping‐by‐sequencing (GBS) to capture and genotype SNP markers on 190 individuals from five wild and domesticated populations (Mississippi River, Missouri, D&B, Rio Grande and Texas). Stringent filtering of SNP‐calling parameters resulted in 4275 SNP loci represented across all five populations. Population genetics and structure analyses revealed potential shared ancestry and admixture between populations. We utilized the Sequenom MassARRAY to validate two multiplex panels of SNPs selected from the GBS data. Selection criteria included SNPs shared between populations, SNPs specific to populations, number of reads per individual and number of individuals genotyped by GBS. Putative SNPs were validated in the discovery population and in two additional populations not used in the GBS analysis. A total of 64 SNPs were genotyped successfully in 191 individuals from nine populations. Our results should guide the development of highly informative, flexible genotyping multiplexes for blue catfish from the larger GBS SNP set as well as provide an example of a rapid, low‐cost approach to generate and genotype informative marker loci in aquatic species with minimal previous genetic information.     

Development,validation and genetic analysis of a large soybean SNP genotyping array

Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under‐use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high‐density genetic mapping and genome‐wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome‐wide association analyses. More than four million high‐quality SNPs identified from high‐depth genome re‐sequencing of 16 soybean accessions and low‐depth genome re‐sequencing of 31 soybean accessions were used to select 180 961 SNPs for creation of the Axiom^® SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170 223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene‐rich chromosomal regions suggest that this array may be suitable for genome‐wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.