Use Of Single Nucleotide Polymorphisms Research Articles

Identification of biparental and diploid blastocysts from monopronuclear zygotes with the use of a single-nucleotide polymorphism array

To select normal fertilized diploid blastocysts in patients who had only monopronucleated (1PN) embryos for transfer. Experimental study. University-affiliated center. Couples who were undergoing intracytoplasmic sperm injection treatment and had 1PN blastocysts. In a preliminary test, limited cells of parthenogenetic human embryonic stem cells (phESCs) and normal fertilized blastocysts were analyzed with the use of a low-density single-nucleotide polymorphism (SNP) array to identify the distribution pattern and rate of heterozygosity. In the clinical application, 1PN blastocysts were analyzed with the use of the SNP array. Only diagnosed normal blastocysts were transferred. The diagnosed uniparental blastocysts were validated by imprinted gene expression. Distribution pattern and rate of heterozygosity between parthenogenesis and normal fertilization. In the pretest, phESCs exhibited distinct distribution pattern and lower rate of heterozygosity, compared with normal fertilized blastocysts after SNP analysis. In particular, homozygous hESCs showed a panhomozygosity distribution pattern, hybrid phESCs showed a partial homozygosity distribution pattern, and normal fertilized blastocysts exhibited a panheterozygosity distribution pattern with an average of 20.21% heterozygosity rate; 13.6% was found to be the minimum cutoff to predict normal fertilized samples. In the clinical application, 24 1PN blastocysts were analyzed; 10/24 showed chromosomal abnormalities, 3/24 showed panhomozygosity with 0.45%-0.8% heterozygosity, and 1/24 showed partial homozygosity with 6.54% heterozygosity. The remaining 10 blastocysts, with a panheterozygosity distribution pattern and higher genomic heterozygosity rate, were diagnosed as normal-fertilization diploid embryos; three were transferred and resulted in two healthy newborns. The low-density SNP array might serve as a cost-effective method to identify biparental origin and diploid 1PN blastocysts for transfer.

Genome-wide variability and selection signatures in Italian island cattle breeds.

In the present study, a sample of 88 animals belonging to four local (Modicana, Sarda, Sardo-Bruna and Sardo-Modicana) and one cosmopolitan (Italian Brown Swiss) cattle breeds were genotyped with a medium density SNP beadchip and compared to investigate their genetic diversity and the existence of selection signatures. A total of 43012 SNPs distributed across all 29 autosomal chromosomes were retained after data quality control. Basic population statistics, Wright fixation index and runs of homozygosity (ROH) analyses confirmed that the Italian Brown Swiss genome was shaped mainly by selection, as underlined by the low values of heterozygosity and minor allele frequency. As expected, local cattle exhibited a large within-breed genetic heterogeneity. The FST comparison revealing the largest number of significant SNPs was Sardo-Bruna vs. Sardo-Modicana, whereas the smallest was observed for Italian Brown Swiss vs. Sardo-Modicana. Modicana exhibited the largest number of detected ROHs, whereas the smallest was observed for Sardo-Modicana. Signatures of selection were detected in genomic regions that harbor genes involved in milk production traits for Italian Brown Swiss and fitness traits for local breeds. According to the results of multi-dimensional scaling and the admixture analysis the Sardo-Bruna is more similar to the Sarda than to the Italian Brown Swiss breed. Moreover, the Sardo-Modicana is genetically closer to the Modicana than to the Sarda breed. Results of the present work confirm the usefulness of single nucleotide polymorphisms in deciphering the genetic architecture of livestock breeds.

A bioinformatic pipeline for identifying informative SNP panels for parentage assignment from RADseq data.

The development of high-throughput sequencing technologies is dramatically increasing the use of single nucleotide polymorphisms (SNPs) across the field of genetics, but most parentage studies of wild populations still rely on microsatellites. We developed a bioinformatic pipeline for identifying SNP panels that are informative for parentage analysis from restriction site-associated DNA sequencing (RADseq) data. This pipeline includes options for analysis with or without a reference genome, and provides methods to maximize genotyping accuracy and select sets of unlinked loci that have high statistical power. We test this pipeline on small populations of Mexican gray wolf and bighorn sheep, for which parentage analyses are expected to be challenging due to low genetic diversity and the presence of many closely related individuals. We compare the results of parentage analysis across SNP panels generated with or without the use of a reference genome, and between SNPs and microsatellites. For Mexican gray wolf, we conducted parentage analyses for 30 pups from a single cohort where samples were available from 64% of possible mothers and 53% of possible fathers, and the accuracy of parentage assignments could be estimated because true identities of parents were known a priori based on field data. For bighorn sheep, we conducted maternity analyses for 39 lambs from five cohorts where 77% of possible mothers were sampled, but true identities of parents were unknown. Analyses with and without a reference genome produced SNP panels with ≥95% parentage assignment accuracy for Mexican gray wolf, outperforming microsatellites at 78% accuracy. Maternity assignments were completely consistent across all SNP panels for the bighorn sheep, and were 74.4% consistent with assignments from microsatellites. Accuracy and consistency of parentage analysis were not reduced when using as few as 284 SNPs for Mexican gray wolf and 142 SNPs for bighorn sheep, indicating our pipeline can be used to develop SNP genotyping assays for parentage analysis with relatively small numbers of loci.

AA9int: SNP interaction pattern search using non-hierarchical additive model set.

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. Supplementary data are available at Bioinformatics online.

Increasing the discrimination power of ancestry- and identity-informative SNP loci within the ForenSeq™ DNA Signature Prep Kit

The use of single nucleotide polymorphisms (SNPs) in forensic genetics has been limited to challenged samples with low template and/or degraded DNA. The recent introduction of massively parallel sequencing (MPS) technologies has expanded the potential applications of these markers and increased the discrimination power of well-established loci by considering variation in the flanking regions of target loci. The ForenSeq Signature Preparation Kit contains 165 SNP amplicons for ancestry- (aiSNPs), identity- (iiSNPs), and phenotype-inference (piSNPs). In this study, 714 individuals from four major populations (African American, AFA; East Asian, ASN; US Caucasian, CAU; and Southwest US Hispanic, HIS) previously reported by Churchill et al. [Forensic Sci Int Genet. 30 (2017) 81–92; DOI: https://doi.org/10.1016/j.fsigen.2017.06.004] were assessed using STRait Razor v2s to determine the level of diversity in the flanking regions of these amplicons. The results show that nearly 70% of loci showed some level of flanking region variation with 22 iiSNPs and 8 aiSNPs categorized as microhaplotypes in this study. The heterozygosities of these microhaplotypes approached, and in one instance surpassed, those of some core STR loci. Also, the impact of the flanking region on other forensic parameters (e.g., power of exclusion and power of discrimination) was examined. Sixteen of the 94 iiSNPs had an effective allele number greater than 2.00 across the four populations. To assess what effect the flanking region information had on the ancestry inference, genotype probabilities and likelihood ratios were determined. Additionally, concordance with the ForenSeq UAS and Nextera Rapid Capture was evaluated, and patterns of heterozygote imbalance were identified. Pairwise comparison of the iiSNP diplotypes determined the probability of detecting a mixture (i.e., observing ≥ 3 haplotypes) using these loci alone was 0.9952. The improvement in random match probabilities for the full regions over the target iiSNPs was found to be significant. When combining the iiSNPs with the autosomal STRs, the combined match probabilities ranged from 6.40 × 10−73 (ASN) to 1.02 × 10-79 (AFA).

Use of Single-Nucleotide Polymorphisms and Mammographic Density Plus Classic Risk Factors for Breast Cancer Risk Prediction

Single-nucleotide polymorphisms (SNPs) have demonstrated an association with breast cancer susceptibility, but there is limited evidence on how to incorporate them into current breast cancer risk prediction models. To determine whether a panel of 18 SNPs (SNP18) may be used to predict breast cancer in combination with classic risk factors and mammographic density. This cohort study enrolled a subcohort of 9363 women, aged 46 to 73 years, without a previous breast cancer diagnosis from the larger prospective cohort of the PROCAS study (Predicting Risk of Cancer at Screening) specifically to evaluate breast cancer risk-assessment methods. Enrollment took place from October 2009 through June 2015 from multiple population-based screening centers in Greater Manchester, England. Follow-up continued through January 5, 2017. Genotyping of 18 SNPs, visual-assessment percentage mammographic density, and classic risk assessed by the Tyrer-Cuzick risk model from a self-completed questionnaire at cohort entry. The predictive ability of SNP18 for breast cancer diagnosis (invasive and ductal carcinoma in situ) was assessed using logistic regression odds ratios per interquartile range of the predicted risk. A total of 9363 women were enrolled in this study (mean [range] age, 59 [46-73] years). Of these, 466 were found to have breast cancer (271 prevalent; 195 incident). SNP18 was similarly predictive when unadjusted or adjusted for mammographic density and classic factors (odds ratios per interquartile range, respectively, 1.56; 95% CI, 1.38-1.77 and 1.53; 95% CI, 1.35-1.74), with observed risks being very close to expected (adjusted observed-to-expected odds ratio, 0.98; 95% CI, 0.69-1.28). A combined risk assessment indicated 18% of the subcohort to be at 5% or greater 10-year risk, compared with 30% of all cancers, 35% of interval-detected cancers, and 42% of stage 2+ cancers. In contrast, 33% of the subcohort were at less than 2% risk but accounted for only 18%, 17%, and 15% of the total, interval, and stage 2+ breast cancers, respectively. SNP18 added substantial information to risk assessment based on the Tyrer-Cuzick model and mammographic density. A combined risk is likely to aid risk-stratified screening and prevention strategies.

Use of single nucleotide polymorphisms identifies backcrossing and species misidentifications among three San Francisco estuary osmerids

Two threatened osmerid species native to the San Francisco Estuary (SFE)—Delta Smelt (Hypomesus transpacificus) and Longfin Smelt (Spirinchus thaleichthys)—are subject to broad human influence, including significant habitat alteration and the presence of the introduced osmerid, Wakasagi (Hypomesus nipponensis). The identification of these closely related species and their hybrids is difficult in field collected specimens which are subject to damage through handling and may be difficult to identify morphologically, especially when young. In addition, it is known that these three species hybridize, but the extent and effect of hybridization is difficult to quantify and monitor. We developed assays for 24 species-specific single nucleotide polymorphisms (SNPs) that identify whether a sample is a pure species (Delta Smelt, Longfin Smelt, or Wakasagi), a first generation (F1) hybrid, or a backcross. We used this SNP panel to genetically identify wild osmerids collected in Yolo Bypass from 2010 to 2016 and detected nine Delta Smelt × Wakasagi F1 hybrids and two Wakasagi × (Delta Smelt × Wakasagi) backcross hybrids; all assayed hybrids had Wakasagi as the maternal parent. The backcrossing into Wakasagi suggests that hybridization may only occur in one direction and thus preclude introgression to Delta Smelt. We also found substantial morphological field misidentifications (32.7%) in the Yolo Bypass samples resulting in more Wakasagi and fewer Delta Smelt than previously recorded when based on morphology. The SNP panel described in this study constitutes a valuable resource for monitoring hybridization in the SFE and assigning species identifications with accuracy and efficiency.

The redesigned Forensic Research/Reference on Genetics-knowledge base, FROG-kb

The Forensic Resource/Reference on Genetics-knowledge base (FROG-kb) web site <https://frog.med.yale.edu/FrogKB/> was introduced in 2011 and in the five years since the previous publication ongoing research into how the database can better serve forensics has resulted in extensive redesign of the database interface and functionality. Originally designed as a prototype to support forensic use of single nucleotide polymorphisms (SNPs), FROG-kb provides a freely accessible web interface that facilitates forensic practice and can be useful for teaching and research. Based on knowledge gained through its use, the web interface has been redesigned for easier navigation through the multiple components. The site also has functional enhancements, extensive new documentation, and new reference panels of SNPs with new curated data. FROG-kb focuses on single nucleotide polymorphisms (SNPs) and provides reference population data for several published panels of individual identification SNPs (IISNPs) and several published panels of ancestry inference SNPs (AISNPs). For each of the various marker panels with reference population data, FROG-kb calculates random match probabilities (RMP) and relative likelihoods of ancestry for a user-entered genotype profile (either completely or partially specified). Example genotype profiles are available and the User’s Manual presents interpretation guidelines for the calculations. The extensive documentation along with ongoing updates makes FROG-kb a comprehensive tool in facilitating use of SNPs in forensic practice and education. An overview of the new FROG-kb with examples and material explaining the results of its use are presented here.

Population structure and genetic diversity of coffee progenies derived from Catuaí and Híbrido de Timor revealed by genome-wide SNP marker

The use of single nucleotide polymorphism (SNP) molecular markers has provided advances in selection methodologies used in breeding programs of different crops, reducing cost and time of cultivar release. Despite the great economic and social importance of Coffea arabica, studies with SNP markers are scarce and a small number of SNP are available for this species, when compared with other crops of agronomic importance. Thus, the objective of this study was to identify and validate SNP molecular markers for the species Coffea arabica and to introduce these markers to genetic breeding by means of an accurate analysis of the diversity and genetic structure of breeding populations of this species. After quality filtering, 11,187 SNP markers were selected from the coffee population obtained from crosses between the genotypes Catuai and Hibrido de Timor. A great number of markers were distributed in the 11 chromosomes, within transcribed regions, and were used to estimate the genetic dissimilarity among the individuals of the breeding population. Dendrogram analysis and a Bayesian approach demonstrated the formation of two groups and the discrimination of all genotypes evaluated. The expressive number of SNP molecular markers distributed throughout C. arabica genome was efficient to discriminate all the accessions evaluated in the experiment, clustering them according to their genealogies. This work identified mixtures within the progenies. The genotyping data also provided detailed information about the parental genotypes and led to the identification of new candidate parents to be introduced to the breeding program. The study discussed population structure and its consequence in obtaining improved varieties of C. arabica.

Clinical and genetic factors associated with kidney tubular dysfunction in a real-life single centre cohort of HIV-positive patients

BackgroundTenofovir (TDF) is one of the most widely used antiretroviral drug. Despite the high degree of tolerability a small percentage of patients experienced alteration in tubular function during TDF use. Intracellular TDF disposition is regulated by ATP-binding cassette (ABC) drug efflux transporters and, a reduced transport activity may be implicated in accumulation of TDF into the cells. The aim of our study was to assess the major determinants of TDF associated tubular dysfunction (KTD) in a real-life setting including the usefulness of single-nucleotide polymorphisms (SNPs) mapping into ABCC2, ABCC4 and ABCC10 genes.MethodsWe retrospectively analyzed all HIV positive patients who were followed at the Infectious Diseases Unit, DIBIC Luigi Sacco, University of Milan from April 2013 to June 2016. All patients treated with TDF who underwent a genotypization for the functional variants mapping in ABCC2 rs717620 (−24 C > T), ABCC4 rs1751034 (3463 A > G) and ABCC10 rs2125739 (T > C) were evaluated. KTD was defined as the presence of urine phosphate wasting and/or proteinuria at 24 h urine analysis.ResultsOne hundred fifty-eight patients were genotyped, of which 42 (26.6%) experienced signs of KTD. No statistical significant differences were observed among patients with or without KTD regarding age, gender, ethnicity and comorbidities (hypertension and diabetes). The percentage of patients with KTD was higher among those with “GG” genotype at rs1751034 of ABCC4 compared to patients without KTD [6 (14.3%) vs 4 (3.5%), p = 0.01]. No statistical significant differences were observed regarding the distribution of ABCC2 and ABCC10 SNPs. Carriers of “G” allele in homozygous status at rs1751034 of ABCC4 showed a significant association with KTD (Odds Ratio 4.67, 95% CI 1.25–17.46, p = 0.02) in bivariate analysis, but this association was lost in multivariable analysis. A significant association between bone diseases and KTD was observed (Odds Ratio 3.178, 95%CI 1.529–6.603, p = 0.002).ConclusionsAccording to our results ABCC4 rs1751034 could be a genetic determinant of KTD; however validation studies are needed for therapy personalization. Noteworthy, a strong association between bone disease and KTD was also observed.

Joint Estimation of Relatedness Coefficients and Allele Frequencies from Ancient Samples.

Here, we develop and test a method to address whether DNA samples sequenced from a group of fossil hominin bone or tooth fragments originate from the same individual or from closely related individuals. Our method assumes low amounts of retrievable DNA, significant levels of sequencing error, and contamination from one or more present-day humans. We develop and implement a maximum likelihood method that estimates levels of contamination, sequencing error rates, and pairwise relatedness coefficients in a set of individuals. We assume that there is no reference panel for the ancient population to provide allele and haplotype frequencies. Our approach makes use of single nucleotide polymorphisms (SNPs) and does not make assumptions about the underlying demographic model. By artificially mating genomes from the 1000 Genomes Project, we determine the numbers of individuals at a given genomic coverage that are required to detect different levels of genetic relatedness with confidence.

Chinese Sesame Cultivars, DNA Fingerprinting, and Two‐dimensional Barcodes Using Single Nucleotide Polymorphisms, Insertions or Deletions, and Simple Sequence Repeat Markers

Sesame (Sesamum indicum L.) is one of the most important oilseed crops. Accurate and efficient means to identify each variety of sesame are needed for improvement of the sesame production market. In this study, three kinds of molecular markers were used for DNA fingerprinting of 151 sesame cultivars released in China since 1960: single nucleotide polymorphisms (SNPs), insertions or deletions (InDels), and simple sequence repeats (SSRs). The 140 polymorphic markers used (47 SNPs, 47 InDels, and 46 SSRs) revealed a narrow range of genetic variation among the 151 Chinese sesame cultivars. Clustering analysis classified them into three main groups, which were consistent with the cultivars’ geographical distribution. Three of the 151 cultivars (AH03, AH04, and AH05 from the Anhui Province) were considered synonymous cultivars because of their high genetic similarity coefficients ( &gt; 98%). Overall, 15 SNPs, 14 InDels, and 9 SSRs were sufficient to distinguish all sesame cultivars and the DNA fingerprints generated from these markers allowed establishing two‐dimensional graphical barcodes to accurately and rapidly identify sesame cultivars. Thus, we have provided a useful protocol for the identification and authentication of various sesame cultivars and revealed the usefulness of SNPs, InDels, and SSRs in cultivar identification and intellectual property protection; the fingerprinting codes obtained for the 151 sesame cultivars should be useful in sesame breeding and marketing seed.

Genotyping-by-sequencing provides the discriminating power to investigate the subspecies of Daucus carota (Apiaceae).

BackgroundThe majority of the subspecies of Daucus carota have not yet been discriminated clearly by various molecular or morphological methods and hence their phylogeny and classification remains unresolved. Recent studies using 94 nuclear orthologs and morphological characters, and studies employing other molecular approaches were unable to distinguish clearly many of the subspecies. Fertile intercrosses among traditionally recognized subspecies are well documented. We here explore the utility of single nucleotide polymorphisms (SNPs) generated by genotyping-by-sequencing (GBS) to serve as an effective molecular method to discriminate the subspecies of the D. carota complex.ResultsWe used GBS to obtain SNPs covering all nine Daucus carota chromosomes from 162 accessions of Daucus and two related genera. To study Daucus phylogeny, we scored a total of 10,814 or 38,920 SNPs with a maximum of 10 or 30% missing data, respectively. To investigate the subspecies of D. carota, we employed two data sets including 150 accessions: (i) rate of missing data 10% with a total of 18,565 SNPs, and (ii) rate of missing data 30%, totaling 43,713 SNPs. Consistent with prior results, the topology of both data sets separated species with 2n = 18 chromosome from all other species. Our results place all cultivated carrots (D. carota subsp. sativus) in a single clade. The wild members of D. carota from central Asia were on a clade with eastern members of subsp. sativus. The other subspecies of D. carota were in four clades associated with geographic groups: (1) the Balkan Peninsula and the Middle East, (2) North America and Europe, (3) North Africa exclusive of Morocco, and (4) the Iberian Peninsula and Morocco. Daucus carota subsp. maximus was discriminated, but neither it, nor subsp. gummifer (defined in a broad sense) are monophyletic.ConclusionsOur study suggests that (1) the morphotypes identified as D. carota subspecies gummifer (as currently broadly circumscribed), all confined to areas near the Atlantic Ocean and the western Mediterranean Sea, have separate origins from sympatric members of other subspecies of D. carota, (2) D. carota subsp. maximus, on two clades with some accessions of subsp. carota, can be distinguished from each other but only with poor morphological support, (3) D. carota subsp. capillifolius, well distinguished morphologically, is an apospecies relative to North African populations of D. carota subsp. carota, (4) the eastern cultivated carrots have origins closer to wild carrots from central Asia than to western cultivated carrots, and (5) large SNP data sets are suitable for species-level phylogenetic studies in Daucus.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-016-0806-x) contains supplementary material, which is available to authorized users.

Use of single nucleotide polymorphism (SNP) arrays and next generation sequencing (NGS) to study the incidence, type and origin of aneuploidy in the human preimplantation embryo

To perform a thorough investigation using a combination of the most advanced technologies available in an effort to decipher the aneuploidy ‘code’ in the human preimplantation embryo. Quantitative assessment and genotyping were undertaken concurrently for human blastocysts using SNP arrays and NGS. Single trophectoderm biopsies were obtained from blastocysts of couples undergoing in vitro fertilization (IVF) with preimplantation genetic diagnosis (PGD) for single gene disorders (SGD) and aneuploidy screening. Karyomapping SNP array (Illumina, USA) was used for PGD of SGD while, NGS via the VeriSeq PGS assay (Illumina) was utilized for comprehensive chromosome screening. Fisher’s exact test (GraphPad Software, USA) was used for statistical analysis. In total, over 19,000 chromosomes were screened in 417 embryos from 75 couples [maternal age: 34.1±0.5 years (mean ± SE)]. At least one chromosomal abnormality was detected in 49.2% (205/417) of the embryos assessed, with 48.3% of the embryos exhibiting only abnormalities of meiotic origin, 40% having only mitotic abnormalities and the remainder of the embryos presenting both types of abnormalities. Notably, maternal meiosis was associated with an equal number of events leading to gain vs. loss of chromosomal material (74 gains vs. 75 losses) and prevailed over paternal meiosis which consisted of events mainly involving loss of chromosomal material (27 losses vs. 1 gain) with almost half of the losses (40.7%) being partial. Of the overall number of aneuploidies detected, 15.7% were determined to be partial with the size of segments gained or lost ranging from 7.8 to 145.6 megabases. Incidences of maternally-derived meiotic errors and overall mitotic errors detected are presented in the table below in relation to maternal age: The incidence of maternal meiotic abnormalities was associated with increasing age, consistent with the higher rates of implantation failure and miscarriage experienced by older women. Mitotic errors, potentially producing mosaicism, were also common. Interestingly, aneuploidy of male meiotic origin was characterized by a predominance of monosomies compared with that of female origin, suggesting a sex-specific difference in the mechanism underlying segregation errors.Tabled 1No. of embryos with meiotic or mitotic errors vs. overall No. of embryos per maternal age groupMaternal Age GroupMaternal Meiotic ErrorsOverall Mitotic Errors< 3445/257 (17.5%)a,b63/257 (24.5%)35-3956/131 (42.7%)a,c34/131 (26.0%)> 4022/29 (75.9%)b,c9/29 (31.0%)Meiotic errors: a difference statistically significant at P<0.0001; b difference statistically significant at P<0.0001; c difference statistically significant at P<0.01.Mitotic errors: No difference detected between the different age groups (P>0.05). Open table in a new tab

Relative frequency of 4 major strain types of Mycobacterium avium ssp. paratuberculosis in Canadian dairy herds using a novel single nucleotide polymorphism-based polymerase chain reaction.

Johne's disease is a worldwide concern, as it causes huge economic losses. The etiological agent, Mycobacterium avium ssp. paratuberculosis (MAP), has limited genetic diversity, impeding efforts to understand transmission and distribution of strain types. Whole-genome sequencing was previously performed on a representative set of MAP isolates from Canadian dairy herds and 9 divergent clades were identified. Four clades were of particular interest, as they were either MAP types rarely reported in North America, or they represented a substantial proportion of isolates recovered from dairy farms in Canada. One clade included type I/III isolates, whereas the remaining clades included type II isolates. Variant sites in the MAP genome are often separated by thousands of base pairs, limiting use of single nucleotide polymorphism (SNP)-based genotyping on a single genomic region. Therefore, a SNP-PCR assay was developed to facilitate interrogation of 5 SNP in 2 distant regions of the genome, linking them together in a single PCR reaction for subsequent Sanger sequencing. This high-throughput assay enabled discrimination of 602 MAP isolates from 264 herds (from all 10 provinces). More than 1 isolate was cultured from 133 herds, 14 of which included multiple subtypes. A previously identified dominant type included 87% of isolates, whereas the Bison type was more widespread than previously reported. The latter type and isolates from a second clade of interest were overrepresented in Québec and Saskatchewan, respectively. In conclusion, the distribution and relative frequency of MAP subtypes within Canadian dairy herds were assessed using a novel SNP-based typing assay. These findings will contribute to understanding the clinical relevance and transmission dynamics of MAP in this population and elsewhere.

High density genome wide genotyping-by-sequencing and association identifies common and low frequency SNPs, and novel candidate genes influencing cow milk traits.

High-throughput sequencing technologies have increased the ability to detect sequence variations for complex trait improvement. A high throughput genome wide genotyping-by-sequencing (GBS) method was used to generate 515,787 single nucleotide polymorphisms (SNPs), from which 76,355 SNPs with call rates >85% and minor allele frequency ≥1.5% were used in genome wide association study (GWAS) of 44 milk traits in 1,246 Canadian Holstein cows. GWAS was accomplished with a mixed linear model procedure implementing the additive and dominant models. A strong signal within the centromeric region of bovine chromosome 14 was associated with test day fat percentage. Several SNPs were associated with eicosapentaenoic acid, docosapentaenoic acid, arachidonic acid, CLA:9c11t and gamma linolenic acid. Most of the significant SNPs for 44 traits studied are novel and located in intergenic regions or introns of genes. Novel potential candidate genes for milk traits or mammary gland functions include ERCC6, TONSL, NPAS2, ACER3, ITGB4, GGT6, ACOX3, MECR, ADAM12, ACHE, LRRC14, FUK, NPRL3, EVL, SLCO3A1, PSMA4, FTO, ADCK5, PP1R16A and TEP1. Our study further demonstrates the utility of the GBS approach for identifying population-specific SNPs for use in improvement of complex dairy traits.

Genome-wide discovery of single nucleotide polymorphisms (SNPs) and single nucleotide variants (SNVs) in deep-sea mussels: Potential use in population genomics and cross-species application

The present study aimed to generate genome-wide single nucleotide polymorphisms (SNPs) for the deep-sea mussel Bathymodiolus platifrons via a combination of genome survey sequencing and the type IIB endonuclease restriction-site associated DNA (2b-RAD) sequencing, assess the potential use of SNPs in detecting fine-sale population genetic structure and signatures of divergent selection, as well as their cross-species application in other bathymodioline mussels. Genome survey sequencing was conducted for one individual of B. platifrons. De novo assembly resulted in 781,720 sequences with a scaffold N50 of 2.9kb. Using these sequences as a reference, 9307 genome-wide SNPs were identified by 2b-RAD for 28 B. platifrons individuals collected from a seep and a vent population. Among these SNPs, nine outliers showed significant evidence for divergent selection, and their positions in the genes or scaffolds were identified. The FST estimated based on the putative neutral SNPs was low (0.0126) indicating the two B. platifrons populations having a high genetic connectivity. However, the permutation test detected significant differences (P<0.00001), indicating the two populations having clearly detectable genetic differentiation. The Bayesian clustering analyses and principle component analyses (PCA) performed based on either the putative neutral or outlier SNPs also showed that these two populations were genetically differentiated. In addition, 2b-RAD was also conducted to detect 10,199, 6429, and 3811 single nucleotide variants (SNVs) respectively in the bathymodioline mussels Bathymodiolus japonicus, Bathymodiolus aduloides and Idas sp. with different phylogenetic distances from B. platifrons. Overall, our study has demonstrated the feasibility and effectiveness of combining genome survey sequencing and 2b-RAD to rapidly generate genomic resources for use in fine-scale population genetic studies, and various cross-species applications.

Development and evaluation of a high-throughput single nucleotide polymorphism multiplex assay for assigning pedigrees in common carp

Accurate pedigree information is critical when managing animal breeding programmes and ensure the highest rate of genetic gain. The abundance of available genomic data and the development of high-throughput genotyping platforms have facilitated the use of single nucleotide polymorphisms (SNPs) as the best DNA markers for genomic selection studies. Furthermore, the superior qualities of SNPs compared with those of microsatellite markers allow standardization between laboratories, which is crucial for developing an international set of markers for use in traceability studies. The objective of this study was to develop a high-throughput SNP array to assign common carp pedigrees accurately. A 48-SNP array was developed based on the Fluidigm genotyping platform, and a phylogenetic analysis was performed to distinguish different pedigrees. A likelihood-based approach was used to infer parental pairs, and the pair with the highest LOD score (log of the ratio of the likelihood given parentage to likelihood given non-parentage) was assigned. The SNP genotypes of the offspring and candidate parents tested were collected, and 94% of the offspring were assigned to the most-likely parent pair, which was consistent with the actual pedigree records. Using this SNP assay will allow implementation of offspring testing at large commercial farms where improved accuracy of pedigree assignments and genetic evaluations will increase genetic gains in the common carp aquaculture industry.

A comparison of DMET Plus microarray and genome-wide technologies by assessing population substructure.

The capacity of the Affymetrix drug metabolism enzymes and transporters (DMET) Plus pharmacogenomics genotyping chip to estimate population substructure and cryptic relatedness was evaluated. The results were compared with estimates using genome-wide HapMap data for the same individuals. For 301 unrelated individuals, spanning three continental populations and one admixed population, genotypic data were collected using the Affymetrix DMET Plus microarray. Genome-wide data on these individuals were obtained from HapMap release 3. Population substructure was assessed using Eigenstrat and ADMIXTURE software for both platforms. Cryptic relatedness was explored by inbreeding coefficient estimation. Nonparametric tests were used to determine correlations of the analytical results of the two genotyping platforms. Principal components analysis identified population substructure for both datasets, with 15.8 and 16.6% of the total variance explained in the first two principal components for DMET Plus and HapMap data, respectively. ADMIXTURE results correctly identified four subpopulations within each dataset. Nonparametric rank correlations indicated significant associations between analyses with an average ρ=0.7272 (P<10) across the three continental populations and ρ=0.4888 for the admixed population. Concordance correlation coefficients (average ρc=0.9693 across all four subpopulations) strongly indicate concordance between ADMIXTURE results. Inbreeding coefficients were slightly inflated (16 individuals>0.15) using DMET Plus data and no cryptic relatedness was indicated using HapMap data. The inflated inbreeding estimation could be because of the limited number of markers provided by DMET as a random sample of 1832 markers from HapMap also yielded inflated estimates of cryptic relatedness (39 individuals>0.15). Furthermore, use of single nucleotide polymorphisms located in genes involved in metabolism and transport may have different allele frequencies in subpopulations than single nucleotide polymorphisms sampled from the whole genome. The DMET Plus pharmacogenomics genotyping chip is effective in quantifying population substructure across the three continental populations and inferring the presence of an admixed population. On the basis of our results, these microarrays offer sufficient depth for covariate adjustment of population substructure in genomic association studies.

A Simple Algorithm for Population Classification.

A single-nucleotide polymorphism (SNP) is a variation in the DNA sequence that occurs when a single nucleotide in the genome differs across members of the same species. Variations in the DNA sequences of humans are associated with human diseases. This makes SNPs as a key to open up the door of personalized medicine. SNP(s) can also be used for human identification and forensic applications. Compared to short tandem repeat (STR) loci, SNPs have much lower statistical testing power for individual recognition due to the fact that there are only 3 possible genotypes for each SNP marker, but it may provide sufficient information to identify the population to which a certain samples may belong. In this report, using eight SNP markers for 641 samples, we performed a standard statistical classification procedure and found that 86% of the samples could be classified accurately under a two-population model. This study suggests the potential use of SNP(s) in population classification with a small number (n ≤ 8) of genetic markers for forensic screening, biodiversity and disaster victim controlling.