Evaluating information content of SNPs for sample-tagging in re-sequencing projects

Development and validation of a minimal SNP genotyping panel for the differentiation of Cannabis sativa cultivars

BACKGROUND

Due to its previously illicit nature, Cannabis sativa had not fully reaped the benefits of recent innovations in genomics and plant sciences. However, Canada's legalization of C. sativa and products derived from its flower in 2018 triggered significant new demand for robust genotyping tools to assist breeders in meeting consumer demands. Early molecular marker-based research on C. sativa focused on screening for plant sex and chemotype, and more recent research has sought to use molecular markers to target traits of agronomic interest, to study populations and to differentiate between C. sativa cultivars.

RESULTS

In this study, we have conducted whole genome sequencing of 32 cultivars, mined the sequencing data for SNPs, developed a reduced SNP genotyping panel to discriminate between sequenced cultivars, then validated the 20-SNP panel using DNA from the sequenced cultivars and tested the assays on commercially available dried flower. The assay conversion rate was higher in DNA extracted from fresh plant material than in DNA extracted from dried flower samples. However, called genotypes were internally consistent, highlighting discrepancies between genotypes detected using sequencing data and observed using genotyping assays. The primary contributions of this work are to clearly document the process used to develop minimal SNP genotyping panels, the feasibility of using such panels to differentiate between C. sativa cultivars, and outline improvements and goals for future iterations of PCR-based, minimal SNP panels to enable efficient development genotyping tools to identify and screen C. sativa cultivars.

CONCLUSIONS

Our key recommendations are to increase sampling density to account for intra-cultivar variability; leverage higher read length paired-end short-read technology; conduct in-depth pre- and post-processing of reads, mapping, and variant calling data; integrate trait-associated loci to develop multi-purpose panels; and use iterative approaches for in vitro validation to ensure that only the most discriminant and performant SNPs are retained.

Screening a new set of microhaplotypes in exonic regions for sample identity testing and paternity testing during whole exome sequencing analysis

Whole exome sequencing (WES) is widely used in clinical diagnosis. Before obtaining an accurate diagnosis, it is essential to conduct sample identity testing and paternity testing on trio samples. Currently, there is a lack of optimal genetic markers for these purposes, with limited literature available in this area. Microhaplotypes (MHs) are promising genetic markers due to their high polymorphism, low mutation rate, short amplified fragments, absence of stutter and amplification bias. These characteristics make them suitable for sample tracking and paternity testing during WES analysis. In this study, we screened out a set of polymorphic MHs in exonic regions for the above purposes. The results showed that the power of discrimination (PD) and probability of exclusion (PE) of this set of markers ranged from 0.2682 to 0.8878 and 0.0178 to 0.4583, respectively. Both the cumulative power of discrimination (CPD) and cumulative probability of exclusion (CPE) exceeded 0.999999, indicating the great value of these markers in paternity testing and individual identification in the study population. However, these markers had the effective number of alleles (Ae) values ranging from 1.1784 to 3.8727 (average 2.1805) and informativeness (In) values ranging from 0.0151 to 0.2209 (average 0.0766), showing limited value in DNA mixture analysis and biogeographical ancestry inference.

Malignancy following solid organ transplantation: Current techniques for determination of donor versus recipient origin

Among the post-transplantation complications that patients may encounter, the transmission of a donor-derived malignant neoplasm is uncommon but potentially life threatening. The determination of donor versus recipient origin is essential particularly in the setting of multiple transplant recipients from the donor. Advances in molecular biology now allow accurate discrimination utilizing routine tissue samples in a timely and cost-effective manner. The techniques are routinely performed in hospital molecular biology laboratories and are also available in commercial labs. The current methodologies are discussed and future possibilities are presented for clinicians caring for solid organ recipients.

Development of a coding SNP panel for tracking the origin of whole-exome sequencing samples

Whole-exome sequencing (WES) is widely used to diagnose complex genetic diseases and rare conditions. The implementation of a robust and effective quality control system for sample identification and tracking throughout the WES process is essential. We established a multiplex panel that included 22 coding single-nucleotide polymorphism (cSNP) loci. The personal identification and paternity identification abilities of the panel were evaluated, and a preliminary validation of the practical feasibility of the panel was conducted in a clinical WES case. These results indicate that the cSNP panel could be a useful tool for sample tracking in WES.

A pipeline for sample tagging of whole genome bisulfite sequencing data using genotypes of whole genome sequencing

BACKGROUND

In large-scale high-throughput sequencing projects and biobank construction, sample tagging is essential to prevent sample mix-ups. Despite the availability of fingerprint panels for DNA data, little research has been conducted on sample tagging of whole genome bisulfite sequencing (WGBS) data. This study aims to construct a pipeline and identify applicable fingerprint panels to address this problem.

RESULTS

Using autosome-wide A/T polymorphic single nucleotide variants (SNVs) obtained from whole genome sequencing (WGS) and WGBS of individuals from the Third China National Stroke Registry, we designed a fingerprint panel and constructed an optimized pipeline for tagging WGBS data. This pipeline used Bis-SNP to call genotypes from the WGBS data, and optimized genotype comparison by eliminating wildtype homozygous and missing genotypes, and retaining variants with identical genomic coordinates and reference/alternative alleles. WGS-based and WGBS-based genotypes called from identical or different samples were extensively compared using hap.py. In the first batch of 94 samples, the genotype consistency rates were between 71.01%-84.23% and 51.43%-60.50% for the matched and mismatched WGS and WGBS data using the autosome-wide A/T polymorphic SNV panel. This capability to tag WGBS data was validated among the second batch of 240 samples, with genotype consistency rates ranging from 70.61%-84.65% to 49.58%-61.42% for the matched and mismatched data, respectively. We also determined that the number of genetic variants required to correctly tag WGBS data was on the order of thousands through testing six fingerprint panels with different orders for the number of variants. Additionally, we affirmed this result with two self-designed panels of 1351 and 1278 SNVs, respectively. Furthermore, this study confirmed that using the number of genetic variants with identical coordinates and ref/alt alleles, or identical genotypes could not correctly tag WGBS data.

CONCLUSION

This study proposed an optimized pipeline, applicable fingerprint panels, and a lower boundary for the number of fingerprint genetic variants needed for correct sample tagging of WGBS data, which are valuable for tagging WGBS data and integrating multi-omics data for biobanks.

Performance Evaluation of Three DNA Sample Tracking Tools in a Whole Exome Sequencing Workflow

INTRODUCTION

Next-generation sequencing applications are becoming indispensable for clinical diagnostics. These experiments require numerous wet- and dry-laboratory steps, each one increasing the probability of a sample swap or contamination. Therefore, identity confirmation at the end of the process is recommended to ensure the right data are used for each patient.

METHODS

We tested three commercially available, single nucleotide polymorphism (SNP)-based sample tracking kits in a diagnostic workflow to evaluate their ease of use and performance. The coverage uniformity, on-target specificity, sample identification, and genotyping performance were determined to assess the reliability and cost effectiveness of each kit.

RESULTS AND DISCUSSION

Hands-on time and manual steps are almost identical for the kits from pxlence and Nimagen. The Swift kit has an extra purification step, making it the longest and most demanding protocol. Furthermore, the Swift kit failed to correctly genotype 26 of the 46 samples. The Nimagen kit identified all but one sample and the pxlence kit unambiguously identified all samples, making it the most reliable and robust kit of this evaluation. The Nimagen kit showed poor on-target mapping rates, resulting in deeper sequencing needs and higher sequencing costs compared with the other two kits.

CONCLUSION

Our conclusion is that the Human Sample ID kit from pxlence is the most cost effective of the three tested tools for DNA sample tracking and identification.

Disentangling the effects of male age and mating history: Contrasting effects of mating history on precopulatory mating behavior and paternity success

Many studies ask whether young or older males are better at acquiring mates. Even so, how age affects reproductive success is still poorly understood because male age and mating history are confounded in most studies: older males usually have more mating experience. To what extent does mating history rather than age explain variation in male mating success? And how do mating history and male age determine paternity when there is also postcopulatory sexual selection? Here, we experimentally manipulated the mating history of old and young males in the eastern mosquitofish (Gambusia holbrooki). We then recorded male mating behavior and share of paternity (1259 offspring from 232 potential sires) when they competed for mates and fertilizations. Old males, and males with no mating experience, spent significantly more time approaching females, and attempting to mate, than did young males and those with greater mating experience. Male age and mating history interacted to affect paternity: old males benefited from having previous mating experience, but young males did not. Our results highlight that the age-related changes in male reproductive traits and in paternity that have been described in many taxa may be partly attributable to male mating history and not simply to age itself.

Evidence that genetic compatibility underpins female mate choice in a monandrous amphibian

Mate choice for genetic benefits remains controversial, largely because few studies have estimated the relative contributions of additive and non-additive sources of genetic variation to offspring fitness. Moreover, there remains a deficit of these estimates for species where female-mate preferences have been quantified in the wild, especially species characterized by monandry or monogamy. Here, we use artificial fertilization techniques combined with a cross-classified breeding design to simultaneously test for "good genes" and "compatible genes" benefits of mate choice in the monandrous red backed toadlet (Pseudophryne coriacea). In addition, we used a genomic approach to estimate effects of parental-genetic relatedness (assessed using 27, 768 single nucleotide polymorphisms) on offspring fitness. Our results revealed no significant additive genetic effects (sire effects), but highly significant non-additive genetic effects (sire × dam interaction effects), on fertilization success, survival during embryonic development, and hatching success. We also found significant associations between parental genetic similarity and offspring survival (whereby survival was higher when parents were more related), and significant positive relationships between fertilization success and embryo survival through to hatching. These results indicate that offspring viability is significantly influenced by the genetic compatibility of parental genotypes, that more related parents are more genetically compatible, and that gametes with greater compatibility at fertilization produce more viable offspring. More broadly, our findings provide new quantitative genetic evidence that genetic incompatibility underpins female mate preferences. Continued quantitative genetic assessment of the relative importance of good genes versus compatible genes is needed to ascertain the general importance of genetic benefits as a driver of female mate choice.

Mining whole genome sequence data to efficiently attribute individuals to source populations

Whole genome sequence (WGS) data could transform our ability to attribute individuals to source populations. However, methods that efficiently mine these data are yet to be developed. We present a minimal multilocus distance (MMD) method which rapidly deals with these large data sets as well as methods for optimally selecting loci. This was applied on WGS data to determine the source of human campylobacteriosis, the geographical origin of diverse biological species including humans and proteomic data to classify breast cancer tumours. The MMD method provides a highly accurate attribution which is computationally efficient for extended genotypes. These methods are generic, easy to implement for WGS and proteomic data and have wide application.

Shifts in Reproductive Investment in Response to Competitors Lower Male Reproductive Success

AbstractIn many species, males exhibit phenotypic plasticity in sexually selected traits when exposed to social cues about the intensity of sexual competition. To date, however, few studies have tested how this plasticity affects male reproductive success. We initially tested whether male mosquitofish, Gambusia holbrooki (Poeciliidae), change their investment in traits under pre- and postcopulatory sexual selection depending on the social environment. For a full spermatogenesis cycle, focal males were exposed to visual and chemical cues of rivals that were either present (competitive treatment) or absent (control). Males from the competitive treatment had significantly slower-swimming sperm but did not differ in sperm count from control males. When two males competed for a female, competitive treatment males also made significantly fewer copulation attempts and courtship displays than control males. Further, paternity analysis of 708 offspring from 148 potential sires, testing whether these changes in reproductive traits affected male reproductive success, showed that males previously exposed to cues about the presence of rivals sired significantly fewer offspring when competing with a control male. We discuss several possible explanations for these unusual findings.

Female choice for related males in wild red-backed toadlets (Pseudophryne coriacea)

Mate choice for genetic benefits is assumed to be widespread in nature, yet very few studies have comprehensively examined relationships between female mate choice and male genetic quality in wild populations. Here, we use exhaustive sampling and single nucleotide polymorphisms to provide a partial test of the “good genes as heterozygosity” hypothesis and the “genetic compatibility” hypothesis in an entire population of terrestrial breeding red-backed toadlets, Pseudophryne coriacea. We found that successful males did not display higher heterozygosity, despite a positive relationship between male heterozygosity and offspring heterozygosity. Rather, in the larger of 2 breeding events, we found that successful males were more genetically similar to their mate than expected under random mating, indicating that females can use pre- or post-copulatory mate choice mechanisms to bias paternity toward more related males. These findings provide no support for the good genes as heterozygosity hypothesis but lend support to the genetic compatibility hypothesis. A complete test of this hypothesis will now require evaluating how parental genetic similarity impacts offspring fitness. Terrestrial toadlets show a high degree of site fidelity, high levels of genetic structuring between populations, and frequently hybridize with sister species. As such, female mate choice for related males may be an adaptive strategy to reduce outbreeding depression. Our findings provide the first population-wide evidence for non-random preferential inbreeding in a wild amphibian. We argue that such reproductive patterns may be common in amphibians because extreme genetic differentiation within meta-populations creates an inherently high risk of outbreeding depression.

The future of parentage analysis: From microsatellites to SNPs and beyond

Parentage analysis is a cornerstone of molecular ecology that has delivered fundamental insights into behaviour, ecology and evolution. Microsatellite markers have long been the king of parentage, their hypervariable nature conferring sufficient power to correctly assign offspring to parents. However, microsatellite markers have seen a sharp decline in use with the rise of next-generation sequencing technologies, especially in the study of population genetics and local adaptation. The time is ripe to review the current state of parentage analysis and see how it stands to be affected by the emergence of next-generation sequencing approaches. We find that single nucleotide polymorphisms (SNPs), the typical next-generation sequencing marker, remain underutilized in parentage analysis but are gaining momentum, with 58 SNP-based parentage analyses published thus far. Many of these papers, particularly the earlier ones, compare the power of SNPs and microsatellites in a parentage context. In virtually every case, SNPs are at least as powerful as microsatellite markers. As few as 100-500 SNPs are sufficient to resolve parentage completely in most situations. We also provide an overview of the analytical programs that are commonly used and compatible with SNP data. As the next-generation parentage enterprise grows, a reliance on likelihood and Bayesian approaches, as opposed to strict exclusion, will become increasingly important. We discuss some of the caveats surrounding the use of next-generation sequencing data for parentage analysis and conclude that the future is bright for this important realm of molecular ecology.

Robust in-silico identification of Cancer Cell Lines based on RNA and targeted DNA sequencing data

Cancer cell lines (CCL) are an integral part of modern cancer research but are susceptible to misidentification. The increasing popularity of sequencing technologies motivates the in-silico identification of CCLs based on their mutational fingerprint, but care must be taken when identifying heterogeneous data. We recently developed the proof-of-concept Uniquorn 1 method which could reliably identify heterogeneous sequencing data from selected sequencing technologies. Here we present Uniquorn 2, a generic and robust in-silico identification method for CCLs with DNA/RNA-seq and panel-seq information. We benchmarked Uniquorn 2 by cross-identifying 1612 RNA and 3596 panel-sized NGS profiles derived from 1516 CCLs, five repositories, four technologies and three major cancer panel-designs. Our method achieves an accuracy of 96% for RNA-seq and 95% for mixed DNA-seq and RNA-seq identification. Even for a panel of only 94 cancer-related genes, accuracy remains at 82% but decreases when using smaller panels. Uniquorn 2 is freely available as R-Bioconductor-package ‘Uniquorn’.

Sample tracking in microbiome community profiling assays using synthetic 16S rRNA gene spike-in controls

Workflows for microbiome community profiling by high-throughput sequencing are prone to sample mix-ups and cross-contamination due to the complexity of the procedures and large number of samples typically analyzed in parallel. We employed synthetic 16S rRNA gene spike-in controls to establish a method for tracking of sample identity and detection of cross-contamination in microbiome community profiling assays based on 16S rRNA gene amplicon sequencing (16S-seq). Results demonstrated that combinatorial sample tracking mixes (STMs) can be reliably resolved by Illumina sequencing and faithfully represent their sample of origin. In a single-blinded experiment, addition of STMs at low levels was shown to be sufficient to unambiguously identify and resolve swapped samples. Using artificial admixtures of individually SMT-tagged samples, we further established the ability to detect and quantify cross-contamination down to a level of approximately 1%. The utility of our technique was underscored through detection of an unplanned case of cross-contamination that occurred during this study. By enabling detection of sample mix-ups and cross-contamination throughout 16S-seq workflows, the present technique thus assures provenance of sequence data on a per-sample basis. The method can be readily implemented in standard 16S-seq workflows and its routine application is expected to enhance the reliability of 16S-seq data.

Heritability of climate-relevant traits in a rainforest skink

There is justified concern about the impact of global warming on the persistence of tropical ectotherms. There is also growing evidence for strong selection on climate-relevant physiological traits. Understanding the evolutionary potential of populations is especially important for low dispersal organisms in isolated populations, because these populations have little choice but to adapt. Despite this, direct estimates of heritability and genetic correlations for physiological traits in ectotherms-which will determine their evolutionary responses to selection-are sparse, especially for reptiles. Here we examine the heritabilities and genetic correlations for a set of four morphological and six climate-relevant physiological traits in an isolated population of an Australian rainforest lizard, Lampropholis coggeri. These traits show considerable variation across populations in this species, suggesting local adaptation. From laboratory crosses, we estimated very low to moderate heritability of temperature-related physiological traits (h² < 0.31), but significant and higher heritability of desiccation resistance (h²~0.42). These values contrasted with uniformly higher heritabilities (h² > 0.51) for morphological traits. At the phenotypic level, there were positive associations among the morphological traits and between thermal limits. Growth rate was positively correlated with thermal limits, but there was no indication that morphology and physiology were linked in any other way. We found some support for a specialist-generalist trade-off in the thermal performance curve, but otherwise there was no evidence for evolutionary constraints, suggesting broadly labile multivariate trait structure. Our results indicate little potential to respond to selection on thermal traits in this population and provide new insights into the capacity of tropical ectotherms to adapt in situ to rapid climate change.

Robust in-silico identification of cancer cell lines based on next generation sequencing

Cancer cell lines (CCL) are important tools for cancer researchers world-wide. However, handling of cancer cell lines is error-prone, and critical errors such as misidentification and cross-contamination occur more often than acceptable. Based on the fact that CCL today very often are sequenced (partly or entirely) anyway as part of the studies performed, we developed Uniquorn, a computational method that reliably identifies CCL samples based on variant profiles derived from whole exome or whole genome sequencing. Notably, Uniquorn does neither require a particular sequencing technology nor downstream analysis pipeline but works robustly across different NGS platforms and analysis steps. We evaluated Uniquorn by comparing more than 1900 CCL profiles from three large CCL libraries, embracing 1585 duplicates, against each other. In this setting, our method achieves a sensitivity of 97% and specificity of 99%. Errors are strongly associated to low quality mutation profiles. The R-package Uniquorn is freely available as Bioconductor-package.

Detection of Cross-Sample Contamination in Multiple Myeloma Samples and Sequencing Data

The increasing applicability and sensitivity of next generation sequencing methods exacerbate one of the main issues in the molecular biology laboratory, namely cross-sample contamination. This type of contamination, which could massively increase the rate of false-positive calls in sequencing experiments, can originate at each step during the processing of multiple myeloma samples, such as CD138-selection of tumor cells, RNA and DNA isolation or the processing of sequencing libraries. Here we describe a Droplet Digital PCR (ddPCR) method and a simple bioinformatic solution for the detection of contamination in patient's samples and derived sequencing data, which are based on the same principle: detection of alternative alleles for single-nucleotide polymorphisms (SNPs) that are homozygous according to the control (germ line) sample.

Sexual selection on male body size, genital length and heterozygosity: Consistency across habitats and social settings

Spatial and temporal variation in environmental factors and the social setting can help to maintain genetic variation in sexually selected traits if it affects the strength of directional selection. A key social parameter which affects the intensity of, and sometimes predicts the response to, mating competition is the operational sex ratio (OSR; ratio of receptive males to females). How the OSR affects selection for specific male traits is poorly understood. It is also unclear how sexual selection is affected by interactions between the OSR and environmental factors, such as habitat complexity, that alter key male-female interactions such as mate encounter rates. Here, we experimentally manipulated the OSR and habitat complexity and quantified sexual selection on male mosquitofish (Gambusia holbrooki) by directly measuring male reproductive success (i.e. paternity). We show that despite a more equitable sharing of paternity (i.e. higher levels of multiple paternity) under a male-biased OSR, selection on focal male traits was unaffected by the OSR or habitat complexity. Instead, sexual selection consistently, and significantly, favoured smaller bodied males, males with higher genome wide heterozygosity (based on >3,000 SNP markers) and males with a relatively long gonopodium (intromittent organ). Our results show that sexual selection on male body size, relative genital size and heterozygosity in this system is consistent across environments that vary in ecological parameters that are expected to influence mate encounter rates.

Why does inbreeding reduce male paternity? Effects on sexually selected traits

Mating with relatives has often been shown to negatively affect offspring fitness (inbreeding depression). There is considerable evidence for inbreeding depression due to effects on naturally selected traits, particularly those expressed early in life, but there is less evidence of it for sexually selected traits. This is surprising because sexually selected traits are expected to exhibit strong inbreeding depression. Here, we experimentally created inbred and outbred male mosquitofish (Gambusia holbrooki). Inbred males were the offspring of matings between full siblings. We then investigated how inbreeding influenced a number of sexually selected male traits, specifically: attractiveness, sperm number and velocity, as well as sperm competitiveness based on a male's share of paternity. We found no inbreeding depression for male attractiveness or sperm traits. There was, however, evidence that lower heterozygosity decreased paternity due to reduced sperm competitiveness. Our results add to the growing evidence that competitive interactions exacerbate the negative effects of the increased homozygosity that arises when there is inbreeding.

A SNP panel and online tool for checking genotype concordance through comparing QR codes

In the current precision medicine era, more and more samples get genotyped and sequenced. Both researchers and commercial companies expend significant time and resources to reduce the error rate. However, it has been reported that there is a sample mix-up rate of between 0.1% and 1%, not to mention the possibly higher mix-up rate during the down-stream genetic reporting processes. Even on the low end of this estimate, this translates to a significant number of mislabeled samples, especially over the projected one billion people that will be sequenced within the next decade. Here, we first describe a method to identify a small set of Single nucleotide polymorphisms (SNPs) that can uniquely identify a personal genome, which utilizes allele frequencies of five major continental populations reported in the 1000 genomes project and the ExAC Consortium. To make this panel more informative, we added four SNPs that are commonly used to predict ABO blood type, and another two SNPs that are capable of predicting sex. We then implement a web interface (http://qrcme.tech), nicknamed QRC (forQR code based Concordance check), which is capable of extracting the relevant ID SNPs from a raw genetic data, coding its genotype as a quick response (QR) code, and comparing QR codes to report the concordance of underlying genetic datasets. The resulting 80 fingerprinting SNPs represent a significant decrease in complexity and the number of markers used for genetic data labelling and tracking. Our method and web tool is easily accessible to both researchers and the general public who consider the accuracy of complex genetic data as a prerequisite towards precision medicine.