Reliable Single Nucleotide Polymorphisms Research Articles

Identification and high-throughput genotyping of single nucleotide polymorphism markers in a non-model conifer (Abies nordmanniana (Steven) Spach)

Single nucleotide polymorphism (SNP) markers are powerful tools for investigating population structures, linkage analysis, and genome-wide association studies, as well as for breeding and population management. The availability of SNP markers has been limited to the most commercially important timber species, primarily due to the cost of genome sequencing required for SNP discovery. In this study, a combination of reference-based and reference-free approaches were used to identify SNPs in Nordmann fir (Abies nordmanniana), a species previously lacking genomic sequence information. Using a combination of a genome assembly of the closely related Silver fir (Abies alba) species and a de novo assembly of low-copy regions of the Nordmann fir genome, we identified a high density of reliable SNPs. Reference-based approaches identified two million SNPs in common between the Silver fir genome and low-copy regions of Nordmann fir. A combination of one reference-free and two reference-based approaches identified 250 shared SNPs. A subset of 200 SNPs were used to genotype 342 individuals and thereby tested and validated in the context of identity analysis and/or clone identification. The tested SNPs successfully identified all ramets per clone and five mislabeled individuals via identity and genomic relatedness analysis. The identified SNPs will be used in ad hoc breeding of Nordmann fir in Denmark.

A FEN 1-driven DNA walker-like reaction coupling with magnetic bead-based separation for specific SNP detection.

Single-nucleotide polymorphism (SNP) plays a key role in the carcinogenesis of the human genome, and understanding the intrinsic relationship between individual genetic variations and carcinogenesis lies heavily in the establishment of a precise and sensitive SNP detection platform. Given this, a powerful and reliable SNP detection platform is proposed by a flap endonuclease 1 (FEN 1)-driven DNA walker-like reaction coupling with a magnetic bead (MB)-based separation. A carboxyfluorescein (FAM)-labeled downstream probe (DP) was decorated on a streptavidin magnetic bead (SMB). The target DNA, as a walker strand, was captured by hybridization with DP and an upstream probe (UP) to form a three-base overlapping structure and execute the walking function on the surface of SMB. FEN 1 was employed to specifically recognize the three-base overlapping structure and cut the 5'flap at the SNP site to report the walking event and signal amplification. Considering the fact that the fluorescence was labeled on the cleavage and uncleavage sequences of DP and the target DNA-triggered walking event was undistinguishable from the mixtures, magnetic separation came in handy for cleavage probe (CP) isolation and discrimination of the amplified signal from the background signal. In comparison with the conventional DNA walker reaction, this strategy was coupling with SMB-based separation, thus promising a powerful and reliable method for SNP detection and signal amplification.

Genetic variation of tea plant in Ningde and its adjacent regions revealed by single nucleotide polymorphism genotyping

AbstractNingde (ND), situated in China's prominent tea‐producing region, is recognized as the origin of white tea. It also boasts a wealth of premium tea germplasm resources, which are of vital importance in tea breeding programs. In this investigation, utilizing nanofluidic single nucleotide polymorphisms (SNPs) genotyping technology, the genetic diversity and population structure of tea germplasms sourced from ND and its surrounding regions were scrutinized. A comprehensive collection of 101 tea plant germplasm accessions sourced from ND and its neighboring regions was acquired. Our analysis identified 75 stable and reliable SNP loci that demonstrated the rich genetic diversity of the ND tea germplasms, with an average observed heterozygosity of 0.411 and an expected heterozygosity of 0.382. Notably, the multiple analyses based on high‐quality SNPs revealed that the wild‐type landraces of tea plants in ND are genetically distinct from the cultivars. The analysis of molecular variance results suggested that intrapopulation variation contributed to 79% of the total genetic variation. Moreover, tea plant germplasms in ND interacted with the genetic material of landraces in Nanping and Lishui. Overall, our study provides essential insights into the genetic diversity, relationship, and conservation of ND tea germplasms and lays a molecular basis for innovative utilization and breeding improvement of tea plant germplasms.

Lifting of the 1,000 wheat exome project SNPs from Triticum aestivum cv. Chinese Spring assembly RefSeq v1.0 to RefSeq v2.1

ObjectiveThe 1,000 wheat exome project captured the single nucleotide variants in the coding regions of a diverse set of 890 wheat accessions to analyse the contribution of introgression to adaptation of wheat. However, this highly useful single nucleotide polymorphism (SNP) dataset is based on RefSeq v1.0 of the International Wheat Genome Sequencing Consortium (IWGSC) assembly of the bread wheat genome of Chinese Spring. This reference sequence has recently been updated using optical maps and long-read sequencing to produce the improved RefSeq v2.1. Our objective was to develop a reliable high-density SNP dataset positioned onto RefSeq v2.1 because it is the current standard reference sequence used by wheat researchers.ResultsThe 3,039,822 SNPs originally positioned on RefSeq v1.0 were projected to v2.1 using Liftoff with four different flanking regions, and 2,946,536 SNPs were consistently lifted to the same location irrespective of the flanking region lengths. Of these, 2,799,166 were located on the ‘+’ ve strand. The distribution of the SNPs across the 21 chromosomes on RefSeq v2.1 was similar to that of RefSeq v1.0. Among the SNPs that were based on unanchored scaffolds in RefSeq v1.0, 11,938 were projected to one of the 21 pseudomolecules in the upgraded assembly. This SNP dataset constitutes a much-needed standardized resource for the wheat research community.

Maast: genotyping thousands of microbial strains efficiently

Existing single nucleotide polymorphism (SNP) genotyping algorithms do not scale for species with thousands of sequenced strains, nor do they account for conspecific redundancy. Here we present a bioinformatics tool, Maast, which empowers population genetic meta-analysis of microbes at an unrivaled scale. Maast implements a novel algorithm to heuristically identify a minimal set of diverse conspecific genomes, then constructs a reliable SNP panel for each species, and enables rapid and accurate genotyping using a hybrid of whole-genome alignment and k-mer exact matching. We demonstrate Maast’s utility by genotyping thousands of Helicobacter pylori strains and tracking SARS-CoV-2 diversification.

High genome heterozygosity revealed vegetative propagation over the sea in Moso bamboo

BackgroundMoso bamboo (Phyllostachys edulis) is a typical East Asian bamboo that does not flower for > 60 years and propagates without seed reproduction. Thus, Moso bamboo can be propagated vegetatively, possibly resulting in highly heterozygous genetic inheritance. Recently, a draft genome of Moso bamboo was reported, followed by whole genome single nucleotide polymorphisms (SNP) analysis, which showed that the genome of Moso bamboo in China has regional characteristics. Moso bamboo in Japan is thought to have been introduced from China over the sea in 1736. However, it is unclear where and how Moso bamboo was introduced in Japan from China. Here, based on detailed analysis of heterozygosity in genome diversity, we estimate the spread of genome diversity and its pedigree of Moso bamboo.ResultsWe sequenced the whole genome of Moso bamboo in Japan and compared them with data reported previously from 15 regions of China. Only 4.1 million loci (0.37% of the analyzed genomic region) were identified as polymorphic loci. We next narrowed down the number of polymorphic loci using several filters and extracted more reliable SNPs. Among the 414,952 high-quality SNPs, 319,431 (77%) loci were identified as heterozygous common to all tested samples. The result suggested that all tested samples were clones via vegetative reproduction. Somatic mutations may accumulate in a heterozygous manner within a single clone. We examined common heterozygous loci between samples from Japan and elsewhere, from which we inferred that an individual closely related to the sample from Fujian, China, was introduced to Japan across the sea without seed reproduction. In addition, we collected 16 samples from four nearby bamboo forests in Japan and performed SNP and insertion/deletion analyses using a genotyping by sequencing (GBS) method. The results suggested that a small number of somatic mutations would spread within and between bamboo groves.ConclusionsHigh heterozygosity in the genome-wide diversity of Moso bamboo implies the vegetative propagation of Moso bamboo from China to Japan, the pedigree of Moso bamboo in Japan, and becomes a useful marker to approach the spread of genome diversity in clonal plants.

Genetic markers associated with divergent selection against the parasite Marteilia cochillia in common cockle (Cerastoderma edule) using transcriptomics and population genomics data

The common cockle (Cerastoderma edule) plays an important role in marine ecosystems and represents a valuable socioeconomic resource for coastal communities. In 2012, the cockle beds from Rı́a de Arousa (Galicia, NW Spain) were seriously decimated by the protozoan Marteilia cochillia responsible for marteiliosis. We aimed to identify single nucleotide polymorphisms (SNP) markers potentially associated with resilience to marteiliosis to be used in marker-assisted selection programs for restoring affected cockle beds and recovering their production. For this, we carried out a population genomics approach using 2b-RADseq, where 38 naive samples (before the first detection of M. cochillia in 2012) from two beds of Rı́a de Arousa were compared with 39 affected samples collected in 2018/2019 (after several years of marteiliosis occurring in the area), collected either before (15 non-exposed samples) or during (24 exposed samples) the marteiliosis outbreak. Additionally, 767 differentially expressed genes (DEG) from a previous transcriptomic study addressed during the aforementioned 2018/19 marteiliosis outbreak, were evaluated to identify SNPs showing signals of selection. Using 2b-RADseq, 9,154 SNPs were genotyped and among them, 110 consistent outliers for divergent selection were identified. This set of SNPs was able to discriminate the samples according to their marteiliosis status (naive vs affected; exposed vs non-exposed), while another 123 SNPs were identified linked to DEGs associated with the level of infection across a temporal series. Finally, combining the population genomics and transcriptomics information, we selected the 60 most reliable SNPs associated with marteiliosis resilience. These SNPs were close to or within DEGs, and many of them were related to immune response (phagocytosis and cell adhesion), defence, such as apoptosis, stress, and cellular cycle, among other functions. This set of SNPs will eventually be validated to develop a cost-effective genotyping tool for their application for obtaining cockle-resilient strains for marteiliosis.

De Novo SNP Discovery and Genotyping of Masson Pine (Pinus massoniana Lamb.) via Genotyping-by-Sequencing

Masson pine (Pinus massoniana Lamb.) is an important tree species in China, but its genomic research has been hindered due to a large genome size. Genotyping-by-sequencing (GBS) has been a powerful approach to revolutionize the field of genomic research by facilitating the discovery of thousands of single nucleotide polymorphisms (SNPs) and genotyping in non-model organisms, at relatively low cost. Here, we performed de novo SNP discovery and genotyping in 299 trees via the genotyping-by-sequencing (GBS) approach. The effort produced 9.33 × 109 sequence reads, 265,525 SNP-associated contigs, and 6,739,240 raw SNPs. Further filtering and validation of the SNP-associated contigs for reliable SNPs were performed using blasting against the Pinus tabuliformis reference genome, functional annotation, technical replicates, and custom parameter settings for the optimization. The 159,372 SNP-associated contigs were aligned and validated for SNP prediction, in which 60,038 contigs were searched with hits in the NCBI nr database. We further improved the SNP discovery and genotyping with multiple technical replicates and custom parameter settings filtering. It was found that the use of blasting, annotation, technical replicates, and specific parameter settings removed many unreliable SNPs and identified 20,055 more precise and reliable SNPs from the 10,712 filtered contigs. We further demonstrated the informativeness of the identified SNPs in the inference of some genetic diversity and structure. These findings should be useful to stimulate genomic research and genomics-assisted breeding of Masson pine.

Towards Strain-Level Complexity: Sequencing Depth Required for Comprehensive Single-Nucleotide Polymorphism Analysis of the Human Gut Microbiome.

Intestinal bacteria strains play crucial roles in maintaining host health. Researchers have increasingly recognized the importance of strain-level analysis in metagenomic studies. Many analysis tools and several cutting-edge sequencing techniques like single cell sequencing have been proposed to decipher strains in metagenomes. However, strain-level complexity is far from being well characterized up to date. As the indicator of strain-level complexity, metagenomic single-nucleotide polymorphisms (SNPs) have been utilized to disentangle conspecific strains. Lots of SNP-based tools have been developed to identify strains in metagenomes. However, the sufficient sequencing depth for SNP and strain-level analysis remains unclear. We conducted ultra-deep sequencing of the human gut microbiome and constructed an unbiased framework to perform reliable SNP analysis. SNP profiles of the human gut metagenome by ultra-deep sequencing were obtained. SNPs identified from conventional and ultra-deep sequencing data were thoroughly compared and the relationship between SNP identification and sequencing depth were investigated. The results show that the commonly used shallow-depth sequencing is incapable to support a systematic metagenomic SNP discovery. In contrast, ultra-deep sequencing could detect more functionally important SNPs, which leads to reliable downstream analyses and novel discoveries. We also constructed a machine learning model to provide guidance for researchers to determine the optimal sequencing depth for their projects (SNPsnp, https://github.com/labomics/SNPsnp). To conclude, the SNP profiles based on ultra-deep sequencing data extend current knowledge on metagenomics and highlights the importance of evaluating sequencing depth before starting SNP analysis. This study provides new ideas and references for future strain-level investigations.

Universal probe-based intermediate primer-triggered qPCR (UPIP-qPCR) for SNP genotyping

BackgroundThe detection and identification of single nucleotide polymorphism (SNP) is essential for determining patient disease susceptibility and the delivery of medicines targeted to the individual. At present, SNP genotyping technology includes Sanger sequencing, TaqMan-probe quantitative polymerase chain reaction (qPCR), amplification-refractory mutation system (ARMS)-PCR, and Kompetitive Allele-Specific PCR (KASP). However, these technologies have some disadvantages: the high cost of development and detection, long and time consuming protocols, and high false positive rates. Focusing on these limitations, we proposed a new SNP detection method named universal probe-based intermediate primer-triggered qPCR (UPIP-qPCR). In this method, only two types of fluorescence-labeled probes were used for SNP genotyping, thus greatly reducing the cost of development and detection for SNP genotyping.ResultsIn the amplification process of UPIP-qPCR, unlabeled intermediate primers with template-specific recognition functions could trigger probe hydrolysis and specific signal release. UPIP-qPCR can be used successfully and widely for SNP genotyping. The sensitivity of UPIP-qPCR in SNP genotyping was 0.01 ng, the call rate was more than 99.1%, and the accuracy was more than 99.9%. High-throughput DNA microarrays based on intermediate primers can be used for SNP genotyping.ConclusionThis novel approach is both cost effective and highly accurate; it is a reliable SNP genotyping method that would serve the needs of the clinician in the provision of targeted medicine.

Identification of Ms2, a novel locus controlling male-fertility restoration of cytoplasmic male-sterility in onion (Allium cepa L.), and development of tightly linked molecular markers

Cytoplasmic male-sterility (CMS) has been exclusively used to produce F1 hybrid seeds of onion (Allium cepa L.). A single nuclear locus, Ms, is known to restore male-fertility of CMS in onions. Unstable male-sterile onions producing a small amount of pollen grains have been identified in a previous study. When such unstable male-sterile onions were crossed with stable male-sterile onions containing CMS-R cytoplasm, male-fertility was completely restored, although genotypes of the Ms locus were homozygous recessive. Inheritance patterns indicated that male-fertility restoration was controlled by a single locus designated as Ms2. A combined approach of bulked segregant analysis and RNA-seq was used to identify candidate genes for the Ms2 locus. High resolution melting markers were developed based on single nucleotide polymorphisms (SNPs) detected by RNA-Seq. Comparative mapping of the Ms2 locus showed that Ms2 was positioned at the end of chromosome 2 with a distance of approximately 70 cM away from the Ms locus. Although 38 contigs containing reliable SNPs were analyzed using recombinants selected from 1344 individuals, no contig showed perfect linkage to Ms2. Interestingly, transcription levels of orf725, a CMS-associated gene in onions, were significantly reduced in male-fertile individuals of segregating populations. However, no significant change in its transcription level was observed in individuals of a segregating population with male-fertility genotypes determined by the Ms locus, suggesting that male-fertility restoration mechanism of Ms2 might be different from that of the Ms locus.

Association of VEGFA polymorphisms with chronic obstructive pulmonary disease in Chinese Han and Mongolian populations.

What is the central question of this study? Vascular endothelial growth factor A (VEGFA) is an important growth factor involved in changes in the bronchial microvascular and airway inflammation in chronic obstructive pulmonary disease (COPD) progression. What is the association of single nucleotide polymorphisms (SNPs) in VEGFA with the risk of COPD in the Chinese Han and Mongolian populations? What is the main finding and its importance? The effect of five SNPs in the VEGFA gene was analysed and compared between the Chinese Han and Mongolian populations. A contribution of risk alleles rs833068, rs833070 and rs3024997 to COPD was detected in the Chinese Mongolian population only. The study provided data from different populations to validate the role of VEGFA polymorphisms in COPD and provided reliable SNPs to predict the risk of COPD. We attempted to define the associations between single nucleotide polymorphisms (SNPs) in the vascular endothelial growth factor A (VEGFA) gene and chronic obstructive pulmonary disease (COPD) in Chinese Han and Mongolian cohorts. Five SNPs were genotyped in cohorts of 684 COPD patients (350 Mongolian and 334 Han) and 784 healthy controls (350 Mongolian and 434 Han) using SNPscan multiplexPCR. SNP frequencies, genetic models and haplotypes were analysed using the chi-square test. The associations of SNPs with COPD and linkage disequilibrium were analysed using logistic regression and HaploView, respectively. We found that only rs833068G>A, rs833070T>C and rs3024997G>A were significantly associated with the risk of COPD in the Mongolian population (rs833068: P<0.001, rs833070: P<0.001, rs3024997: P=0.002). In the analysis of genotype distributions, the A/A and G/A genotypes in rs833068 (A/A: odds ratio (OR) = 0.313, P<0.001; G/A: OR=0.724, P<0.001) and rs3024997 (A/A: OR=0.513, P=0.008; G/A: OR=0.671, P=0.008) and the C/C and T/C genotypes in rs833070 (C/C: OR=0.435, P=0.007; T/C: OR=0.593, P=0.007) were associated with protection against COPD in the Mongolian population. The haplotype frequencies of GCCAT and GTCGC were significantly different between the patients and controls (GCCAT: P=0.001; GTCGC: P<0.001) in the Mongolian population. Our findings indicate that five SNPs in the VEGFA gene play divergent roles in the Han and Mongolian populations. rs833068A, rs833070C and rs3024997A were observed to be associated with the risk of COPD in the Mongolian population.

Genome-Wide Association Study Reveals Candidate Genes for Flowering Time in Cowpea (Vigna unguiculata [L.] Walp.).

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 368 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8–12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.

Potential of preimplantation genomic selection using the blastomere separation technique in bovine in vitro fertilized embryos.

Preimplantation genomic selection combined with an in vitro embryo production system is expected as a means of accelerating genetic improvement in cattle. While micromanipulation-based biopsy approaches are often used to collect embryonic cells for genetic testing, they require expensive equipment and sophisticated skills, hindering the adoption of this system. In the present study, to develop a simple method for preimplantation genomic selection using the blastomere separation (BS) technique in bovine in vitro fertilized embryos, we examined the accuracy of single nucleotide polymorphism (SNP) genotyping and optimal cryopreservation method in demi-blastocysts produced by the BS technique. We demonstrated reliable SNP genotyping using DNA derived from demi-blastocysts. We indicated a suitable equilibrium time in vitrification solution for demi-blastocysts and succeeded obtaining pregnancies by the transfer of vitrified demi-blastocysts. In conclusion, our findings suggest that the BS technique provides a simple method for preimplantation genomic selection in bovine in vitro fertilized embryos.

Development of Kompetitive Allele Specific PCR markers for identification of persimmon varieties using genotyping-by-sequencing

Persimmon ( Diospyros kaki Thunb.) is the most widely cultivated species of the genus Diospyros . In this study, genetic diversity and variations in persimmon genotypes were investigated using single nucleotide polymorphism (SNP) markers identified by genotyping-by-sequencing (GBS) analysis. Ninety-five persimmon accessions grown in the Pear Research Institute, National Institute Horticultural and Herbal Science, were sequenced using the Illumina Hiseq2500 platform and polymorphic SNPs were detected to develop molecular markers. These reliable SNPs were analyzed using the Kompetitive Allele Specific PCR (KASP) assay to discriminate among persimmon genotypes. GBS generated a total of 447,495,724 trimmed reads, of which 89.7% were raw reads. After demultiplexing and sequence quality trimming, 108,876,644 clean reads were mapped to the reference transcriptome. An average of 1,146,070 genotype reads were mapped. Filtering of raw SNPs in each sample led to selection of a total of 1,725,401 high-quality SNPs. The number of homozygous and heterozygous SNPs ranged from 1,933 to 6,834 and from 846 to 5,927, respectively. Of the 49 SNPs selected for development of an identification system for persimmons, 15 SNPs were used in the KASP assay to analyze 32 persimmon accessions. These KASP markers discriminated among all accessions. How to cite: Ma KB, Yang SJ, Jo YS, et al. Development of Kompetitive Allele Specific PCR markers for identification of persimmon varieties using genotyping-by-sequencing. Electron J Biotechnol 2021;49. https://doi.org/10.1016/j.ejbt.2020.11.003

An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies.

Single nucleotide polymorphisms (SNPs) are highly abundant, amendable to high-throughput genotyping, and useful for a number of breeding and genetics applications in crops. SNP frequencies vary depending on the species and populations under study, and therefore target SNPs need to be carefully selected to be informative for each application. While multiple SNP genotyping systems are available for rice (Oryza sativa L. and its relatives), they vary in their informativeness, cost, marker density, speed, flexibility, and data quality. In this study, we report the development and performance of the Cornell-IR LD Rice Array (C7AIR), a second-generation SNP array containing 7,098 markers that improves upon the previously released C6AIR. The C7AIR is designed to detect genome-wide polymorphisms within and between subpopulations of O. sativa, as well as O. glaberrima, O. rufipogon and O. nivara. The C7AIR combines top-performing SNPs from several previous rice arrays, including 4,007 SNPs from the C6AIR, 2,056 SNPs from the High Density Rice Array (HDRA), 910 SNPs from the 384-SNP GoldenGate sets, 189 SNPs from the 44K array selected to add information content for elite U.S. tropical japonica rice varieties, and 8 trait-specific SNPs. To demonstrate its utility, we carried out a genome-wide association analysis for plant height, employing the C7AIR across a diversity panel of 189 rice accessions and identified 20 QTLs contributing to plant height. The C7AIR SNP chip has so far been used for genotyping >10,000 rice samples. It successfully differentiates the five subpopulations of Oryza sativa, identifies introgressions from wild and exotic relatives, and is useful for quantitative trait loci (QTL) and association mapping in diverse materials. Moreover, data from the C7AIR provides valuable information that can be used to select informative and reliable SNP markers for conversion to lower-cost genotyping platforms for genomic selection and other downstream applications in breeding.

Indirect predictions with a large number of genotyped animals using the algorithm for proven and young.

Reliable single-nucleotide polymorphisms (SNP) effects from genomic best linear unbiased prediction BLUP (GBLUP) and single-step GBLUP (ssGBLUP) are needed to calculate indirect predictions (IP) for young genotyped animals and animals not included in official evaluations. Obtaining reliable SNP effects and IP requires a minimum number of animals and when a large number of genotyped animals are available, the algorithm for proven and young (APY) may be needed. Thus, the objectives of this study were to evaluate IP with an increasingly larger number of genotyped animals and to determine the minimum number of animals needed to compute reliable SNP effects and IP. Genotypes and phenotypes for birth weight, weaning weight, and postweaning gain were provided by the American Angus Association. The number of animals with phenotypes was more than 3.8 million. Genotyped animals were assigned to three cumulative year-classes: born until 2013 (N = 114,937), born until 2014 (N = 183,847), and born until 2015 (N = 280,506). A three-trait model was fitted using the APY algorithm with 19,021 core animals under two scenarios: 1) core 2013 (random sample of animals born until 2013) used for all year-classes and 2) core 2014 (random sample of animals born until 2014) used for year-class 2014 and core 2015 (random sample of animals born until 2015) used for year-class 2015. GBLUP used phenotypes from genotyped animals only, whereas ssGBLUP used all available phenotypes. SNP effects were predicted using genomic estimated breeding values (GEBV) from either all genotyped animals or only core animals. The correlations between GEBV from GBLUP and IP obtained using SNP effects from core 2013 were ≥0.99 for animals born in 2013 but as low as 0.07 for animals born in 2014 and 2015. Conversely, the correlations between GEBV from ssGBLUP and IP were ≥0.99 for animals born in all years. IP predictive abilities computed with GEBV from ssGBLUP and SNP predictions based on only core animals were as high as those based on all genotyped animals. The correlations between GEBV and IP from ssGBLUP were ≥0.76, ≥0.90, and ≥0.98 when SNP effects were computed using 2k, 5k, and 15k core animals. Suitable IP based on GEBV from GBLUP can be obtained when SNP predictions are based on an appropriate number of core animals, but a considerable decline in IP accuracy can occur in subsequent years. Conversely, IP from ssGBLUP based on large numbers of phenotypes from non-genotyped animals have persistent accuracy over time.

Accurate Differentiation of Green Beans of Arabica and Robusta Coffee Using Nanofluidic Array of Single Nucleotide Polymorphism (SNP) Markers.

Green (unroasted) coffee is one of the most traded agricultural commodities in the world. The Arabica (Coffea arabica L.) and Robusta (Coffea canephora Pierre ex A. Froehner) species are the two main types of coffees for commercial production. In general, Arabica coffee is known to have better quality in terms of sensory characteristics; thus, it has a higher market value than Robusta coffee. Accurate differentiation of green beans of the two species is, therefore, of commercial interest in the coffee industry. Using the newly developed single nucleotide polymorphism (SNP) markers, we analyzed a total of 80 single green bean samples, representing 20 Arabica cultivars and four Robusta accessions. Reliable SNP fingerprints were generated for all tested samples. Unambiguous differentiation between Robusta and Arabica coffees was achieved using multivariate analysis and assignment test. The SNP marker panel and the genotyping protocol are sufficiently robust to detect admixture of green coffee in a high-throughput fashion. Moreover, the multilocus SNP approach can differentiate every single bean within Robusta and 55% of Arabica samples. This advantage, together with the single-bean sensitivity, suggests a significant potential for practical application of this technology in the coffee industry.

Genomic diversity affects the accuracy of bacterial single-nucleotide polymorphism-calling pipelines.

BackgroundAccurately identifying single-nucleotide polymorphisms (SNPs) from bacterial sequencing data is an essential requirement for using genomics to track transmission and predict important phenotypes such as antimicrobial resistance. However, most previous performance evaluations of SNP calling have been restricted to eukaryotic (human) data. Additionally, bacterial SNP calling requires choosing an appropriate reference genome to align reads to, which, together with the bioinformatic pipeline, affects the accuracy and completeness of a set of SNP calls obtained. This study evaluates the performance of 209 SNP-calling pipelines using a combination of simulated data from 254 strains of 10 clinically common bacteria and real data from environmentally sourced and genomically diverse isolates within the genera Citrobacter, Enterobacter, Escherichia, and Klebsiella.ResultsWe evaluated the performance of 209 SNP-calling pipelines, aligning reads to genomes of the same or a divergent strain. Irrespective of pipeline, a principal determinant of reliable SNP calling was reference genome selection. Across multiple taxa, there was a strong inverse relationship between pipeline sensitivity and precision, and the Mash distance (a proxy for average nucleotide divergence) between reads and reference genome. The effect was especially pronounced for diverse, recombinogenic bacteria such as Escherichia coli but less dominant for clonal species such as Mycobacterium tuberculosis.ConclusionsThe accuracy of SNP calling for a given species is compromised by increasing intra-species diversity. When reads were aligned to the same genome from which they were sequenced, among the highest-performing pipelines was Novoalign/GATK. By contrast, when reads were aligned to particularly divergent genomes, the highest-performing pipelines often used the aligners NextGenMap or SMALT, and/or the variant callers LoFreq, mpileup, or Strelka.

Museum specimens provide reliable SNP data for population genomic analysis of a widely distributed but threatened cockatoo species.

Natural history museums harbour a plethora of biological specimens which are of potential use in population and conservation genetic studies. Although technical advancements in museum genomics have enabled genome-wide markers to be generated from aged museum specimens, the suitability of these data for robust biological inference is not well characterized. The aim of this study was to test the utility of museum specimens in population and conservation genomics by assessing the biological and technical validity of single nucleotide polymorphism (SNP) data derived from such samples. To achieve this, we generated thousands of SNPs from 47 red-tailed black cockatoo (Calyptorhychus banksii) traditional museum samples (i.e. samples that were not collected with the primary intent of DNA analysis) and 113 fresh tissue samples (cryopreserved liver/muscle) using a restriction site-associated DNA marker approach (DArTseq™ ). Thousands of SNPs were successfully generated from most of the traditional museum samples (with a mean age of 44years, ranging from 5 to 123years), although 38% did not provide useful data. These SNPs exhibited higher error rates and contained significantly more missing data compared with SNPs from fresh tissue samples, likely due to considerable DNA fragmentation. However, based on simulation results, the level of genotyping error had a negligible effect on inference of population structure in this species. We did identify a bias towards low diversity SNPs in older samples that appears to compromise temporal inferences of genetic diversity. This study demonstrates the utility of a RADseq-based method to produce reliable genome-wide SNP data from traditional museum specimens.