I Am Your Father: Investigating the Genetic Mating System in the Antarctic Sea Spider Nymphon australe.

Over the past few years, single nucleotide polymorphisms (SNPs) have been proposed as the next generation of markers for the identification of loci associated with complex diseases and for pharmacogenetic applications (Lander and Schork 1994; Lander 1996; Risch and Merikangas 1996; Kruglyak 1997; Schafer and Hawkins 1998). SNPs are frequently present in the genome with a density of at least one common (>20% allele frequency) SNP per kilobase pair (Lai et al. 1998; Sachidanandam et al. 2001). They are mostly biallelic ( 1.6 million SNPs in the public databases (Sachidanandam et al. 2001). In this article, I will attempt to summarize what we know about SNPs and identify some of the challenges that await us in the application of SNPs in research and medicine. The first questions most people would ask are, how many SNPs are there in the human genome and have we identified most of the SNPs? The frequently cited rate of 1 SNP/kb suggests that there are 3 million common SNPs in the human genome. However, recent data have indicated that the number of SNPs in the human genome is potentially much more than 3 million. The first indication came from the comparison of the Celera SNP database with the public data. Celera Genomics claimed to contain over 3.5 million putative SNPs in their database. However, only 400,000 of their SNPs were redundant when compared to the publicly available 1.6 million. The second line of evidence came from our own experiments. We have isolated >1000 SNPs in a 20megabase region by re-sequencing eight individuals (not the same DNA source as the TSC SNPs). The overlap between our SNPs (∼1,000) and the TSC SNPs in this region is ∼5% (instead of the expected 50% if the total number of common SNP is around 3 million). These results suggest that there are potentially 10 million or more common SNPs in the human population. A theoretical modeling experiment has also predicted that there are more than 10 million SNPs in the genome (Kruglyak and Nickerson 2001). There are two important implications in the usage of SNPs as a genetic tool if there are indeed over 10 million SNPs in the human genome. The first implication is that the SNP(s) you are looking for might not be discovered yet. The second implication is the need to select a representative set of SNPs out of the 1.6 million to cover the genome. The first problem is a difficult one since it is impossible to know whether the SNP(s) of interest is present in the current databases. There are two potential solutions. The first solution is to design experiments that combine SNP discovery and genotyping (Brenner et al. 2000). However, this approach has not been demonstrated for whole genome SNP scan and could be costly even if it is technically feasible. The second solution, which is suitable for both implications mentioned above, is the development of a comprehensive whole genome SNP marker set that has a high likelihood of detecting the SNP(s) of interest by linkage disequilibrium or association (see section below on marker set development) (Jorde 2000). So how do we design a marker set that covers the genome as completely as possible? There are many suggestions and computer models using linkage disequilibrium (LD) as a guide and striking a balance between number of markers and information content (Kruglyak 1999; Jorde 2000). A number of recent studies have indicated that an average spacing of 30 kb provides a good balance (i.e., 100,000 SNPs for whole genome) (Collins 1999; Huttley et al. 1999; Goddard et al. 2000; Jorde 2000). In addiE-MAIL ehl21107@GlaxoWellcome.com; FAX (919) 315-0113. Article and publication are at www.genome.org/cgi/ doi/10.1101/gr.192301. Insight/Outlook

SNPs, Haplotypes, and Cancer: Applications in Molecular Epidemiology

This study was conducted to estimate the extent of linkage disequilibrium (LD) and effective population size using whole genomic single nucleotide polymorphisms (SNP) genotyped by DNA chip in Hanwoo. Using the blood samples of 35 young bulls born from 2005 to 2008 and their progenies (N=253) in a Hanwoo nucleus population collected from Hanwoo Improvement Center, 51,582 SNPs were genotyped using Bovine SNP50 chips. A total of 40,851 SNPs were used in this study after elimination of SNPs with a missing genotyping rate of over 10 percent and monomorphic SNPs (10,730 SNPs). The total autosomal genome length, measured as the sum of the longest syntenic pairs of SNPs by chromosome, was 2,541.6 Mb (Mega base pairs). The average distances of all adjacent pairs by each BTA ranged from 0.55 to 0.74 cM. Decay of LD showed an exponential trend with physical distance. The means of LD (r2) among syntenic SNP pairs were 0.136 at a range of 0-0.1 Mb in physical distance and 0.06 at a range of 0.1-0.2 Mb. When these results were used for Luo’s formula, about 2,000 phenotypic records were found to be required to achieve power > 0.9 to detect 5% QTL in the population of Hanwoo. As a result of estimating effective population size by generation in Hanwoo, the estimated effective population size for the current status was 84 heads and the estimate of effective population size for 50 generations of ancestors was 1,150 heads. The average decreasing rates of effective population size by generation were 9.0% at about five generations and 17.3% at the current generation. The main cause of the rapid decrease in effective population size was considered to be the intensive use of a few prominent sires since the application of artificial insemination technology in Korea. To increase and/or sustain the effective population size, the selection of various proven bulls and mating systems that consider genetic diversity are needed.

Sugar pine, Pinus lambertiana Douglas, is a keystone species of montane forests from Baja California to southern Oregon. Like other North American white pines, populations of sugar pine have been greatly reduced by the disease white pine blister rust (WPBR) caused by a fungal pathogen, Cronartium ribicola, that was introduced into North America early in the twentieth century. Major gene resistance to WPBR segregating in natural populations has been documented in sugar pine. Indeed, the dominant resistance gene in this species, Cr1, was genetically mapped, although not precisely. Genomic single nucleotide polymorphisms (SNPs) placed in a large scaffold were reported to be associated with the allele for this major gene resistance (Cr1R). Forest restoration efforts often include sugar pine seed derived from the rare resistant individuals (typically Cr1R/Cr1r) identified through an expensive 2-year phenotypic testing program. To validate and geographically characterize the variation in this association and investigate its potential to expedite genetic improvement in forest restoration, we developed a simple PCR-based, diploid genotyping of DNA from needle tissue. By applying this to range-wide samples of susceptible and resistant (Cr1R) trees, we show that the SNPs exhibit a strong, though not complete, association with Cr1R. Paralleling earlier studies of the geographic distribution of Cr1R and the inferred demographic history of sugar pine, the resistance-associated SNPs are marginally more common in southern populations, as is the frequency of Cr1R. Although the strength of the association of the SNPs with Cr1R and thus, their predictive value, also varies with geography, the potential value of this new tool in quickly and efficiently identifying candidate WPBR-resistant seed trees is clear.

Association between genomic single nucleotide polymorphisms and susceptibility of Talaromyces marneffei.

BackgroundGastric cancer exhibits familial clustering, and gastric cancer familial relatives (GCF) tend to present with corpus-predominant gastritis and precancerous lesions as SPEM or IM after H. pylori infection. The study determined whether the children of gastric cancer patients (GCA) had genomic single nucleotide polymorphisms (SNPs) predisposed to the gastric precancerous lesions as spasmolytic polypeptide-expressing metaplasia (SPEM) or intestinal metaplasia (IM).ResultsThere were 389 family relatives of 193 non-cardiac GCA and 173 duodenal ulcer patients (DU), received blood sampling for DNA collection. The differences of the risk alleles of SNPs in the ITGA5, ITGB1, IL-10, COX-2, RUNX3, and TFF2 genes were compared between 195 children of GCA and 143 DU. The children of GCA had higher allele frequencies of ITGA5-1160 T-carrier (P = 0.006, OR[95% CI] = 2.2[1.2-4]), ITGB1-1949 A-carrier (P = 0.047; OR[95% CI] = 2.8[1.4-5.3]), ITGB1 + 31804 C-carrier (P = 0.013; OR[95% CI] = 4.7[1.7-13.0]), IL-10-592 AA (P = 0.014; OR[95% CI] = 2.3[1.4-4.0]) and COX-2-1195 G-carrier (P = 0.019; OR[95% CI] = 1.7[0.9-3.2]) than DU. The combined genotype with ITGA5-1160/ITGB1-1949/ITGB1 + 31804 as T/A/C carriers and COX-2-1195/IL-10-592 as G-carrier/AA was more prevalent in the children of GCA than in DU (P < 1×10−4), and predisposed with a 5.3-fold risk of getting SPEM in the H. pylori-infected children of GCA (P = 0.016). Such risk of getting SPEM increased to 112 folds, if combined with RUNX3 + 492/TFF2-308 as A-carrier/CC in this limited study scale (P = 1×10−4).ConclusionsThe SNPs of ITGA5-1160/ITGB1-1949/ ITGB1 + 31804 as T/A/C carriers and COX-2-1195/IL-10-592 as G-carrier/AA, or more specific to combine RUNX3 + 492/TFF2-308 as A-carrier/CC shall be host factor predisposing to gastric cancer during H. pylori infection, and serve as marker to identify high-risk subjects for H. pylori eradication.Electronic supplementary materialThe online version of this article (doi:10.1186/s12929-015-0121-7) contains supplementary material, which is available to authorized users.

Single nucleotide polymorphisms (SNPs) are becoming the dominant form of molecular marker for genetic and genomic analysis. The advances in second generation DNA sequencing provide opportunities to identify very large numbers of SNPs in a range of species. However, SNP identification remains a challenge for large and polyploid genomes due to their size and complexity. We have developed a pipeline for the robust identification of SNPs in large and complex genomes using Illumina second generation DNA sequence data and demonstrated this by the discovery of SNPs in the hexaploid wheat genome. We have developed a SNP discovery pipeline called SGSautoSNP (Second-Generation Sequencing AutoSNP) and applied this to discover more than 800,000 SNPs between four hexaploid wheat cultivars across chromosomes 7A, 7B and 7D. All SNPs are presented for download and viewing within a public GBrowse database. Validation suggests an accuracy of greater than 93% of SNPs represent polymorphisms between wheat cultivars and hence are valuable for detailed diversity analysis, marker assisted selection and genotyping by sequencing. The pipeline produces output in GFF3, VCF, Flapjack or Illumina Infinium design format for further genotyping diverse populations. As well as providing an unprecedented resource for wheat diversity analysis, the method establishes a foundation for high resolution SNP discovery in other large and complex genomes.

Phylogenomic structure of Bacillus anthracis isolates in the Northern Cape Province, South Africa revealed novel single nucleotide polymorphisms

IntroductionDevelopmental delay and dysmorphic features affect 1 – 3 % of paediatric population. In the last few years molecular cytogenetic high resolution techniques (comparative genomic hybridization arrays and single-nucleotide polymorphism arrays) have been proven to be a first-tier choice for clinical diagnostics of developmental delay and dysmorphic features.Methods and resultsIn the present article we describe the clinical advantages of molecular cytogenetic approach (comparative genomic hybridization arrays and single nucleotide polymorphism arrays) in the diagnostic procedure of two children with developmental delay, dysmorphic features and additional morphological phenotypes. Additionally, we demonstrate the necessity of fluorescent in situ hybridization utilisation to identify the localisation and underlying mechanism of detected chromosomal rearrangement.ConclusionsTwo types of chromosomal abnormalities were identified and confirmed using different molecular genetic approaches. Comparative genomic hybridization arrays and single nucleotide polymorphism arrays are hereby presented as important methods to identify chromosomal imbalances in patients with developmental delay and dysmorphic features. We emphasize the importance of molecular genetic testing in patients’ parents for the demonstration of the origin and clinical importance of the aberrations prior determined in the patients. The results obtained using molecular cytogenetic high resolution techniques methods are the cornerstone for proper genetic counselling to the affected families.

Combined comparative genomic hybridization and single-nucleotide polymorphism array detects cryptic chromosomal lesions in both myelodysplastic syndromes and cytopenias of undetermined significance

A genetic diversity analysis and identification of plant germplasms and varieties are important and necessary for plant breeding. Deoxyribonucleotide (DNA) fingerprints based on genomic molecular markers play an important role in accurate germplasm identification. In this study, Specific-Locus Amplified Fragment Sequencing (SLAF-seq) was conducted for a sugarcane population with 103 cultivated and wild accessions. In total, 105,325 genomic single nucleotide polymorphisms (SNPs) were called successfully to analyze population components and genetic diversity. The genetic diversity of the population was complex and clustered into two major subpopulations. A principal component analysis (PCA) showed that these accessions could not be completely classified based on geographical origin. After filtration, screening, and comparison, 192 uniformly-distributed SNP loci were selected for the 32 chromosomes of sugarcane. An SNP complex genotyping detection system was established using the SNaPshot typing method and used for the precise genotyping and identification of 180 sugarcane germplasm samples. According to the stability and polymorphism of the SNPs, 32 high-quality SNP markers were obtained and successfully used to construct the first SNP fingerprinting and quick response codes (QR codes) for sugarcane. The results provide new insights for genotyping, classifying, and identifying germplasm and resources for sugarcane breeding

Development and validation of a SNP panel for parentage assignment in rainbow trout

BackgroundOutbreaks of the coral predator Crown-of-Thorns Starfish (CoTS) pose a severe threat to coral reefs in the Indo-Pacific Ocean. In 2018, the South China Sea (SCS) experienced significant CoTS outbreaks, leading to extensive coral mortality across the Xisha, Zhongsha, Dongsha, and Nansha Islands, severely impacting the coral reef ecosystem.ResultsTo explore the origins of these outbreaks, we conducted a comprehensive genomic analysis using data from genomic single nucleotide polymorphism sites (SNPs) and mitochondrial haplotypes. Our analysis reveals that CoTS populations in the SCS, which exhibit moderate genetic diversity and may have undergone positive selection or population expansion. There was limited genetic differentiation among CoTS populations from XS, ZS, and NS groups. Especially between the XS and ZS groups, there was almost no genetic differentiation. The populations from XS, ZS, and NS groups have strong genetic connections with populations in Vietnam and the Philippines. There was high gene flow from Vietnam to the Xisha Islands and from the Philippines to the Nansha Islands, suggesting that the CoTS populations in these regions primarily originate from these neighboring countries.ConclusionThe comprehensive analyses of SNP and mitochondrial genomes have provided valuable insights into the population genetics of CoTS. This research has generated significant genomic resources and facilitated important studies on the genetics of the CoTS species. By identifying potential source populations and understanding the genetic basis of their spread, managers can develop more effective conservation strategies to protect vulnerable coral reef ecosystems in the SCS.

Metabolomic analysis in colorectal cancer (CRC) is an emerging research area with both prognostic and therapeutic targeting potential. We aimed to identify metabolomic pathway activity prognostic for CRC recurrence and overall survival and cross-reference such metabolomic data with prognostic genomic single-nucleotide polymorphisms (SNPs). A systematic search of PubMed, Embase and Cochrane Library was performed for studies reporting prognostic metabolomic pathway activity in CRC in keeping with PRISMA guidelines. The QUADOMICS tool was used to assess study quality. MetaboAnalyst software (version4.0) was used to map metabolites that were associated with recurrence and survival in CRC to recognise metabolic pathways and identify genomic SNPs associated with CRC prognosis, referencing the following databases: Human Metabolome Database (HMDB), the Small Molecule Pathway Database (SMPDB), PubChem and Kyoto Encyclopaedia of Genes and Genomes (KEGG) Pathway Database. Nine studies met the inclusion criteria, reporting on 1117 patients. Increased metabolic activity in the urea cycle (p = 0.002, FDR = 0.198), ammonia recycling (p = 0.004, FDR = 0.359) and glycine and serine metabolism (p = 0.004, FDR = 0.374) was prognostic of CRC recurrence. Increased activity in aspartate metabolism (p < 0.001, FDR = 0.079) and ammonia recycling (p = 0.004, FDR = 0.345) was prognostic of survival. Eight resulting SNPs were prognostic for CRC recurrence (rs2194980, rs1392880, rs2567397, rs715, rs169712, rs2300701, rs313408, rs7018169) and three for survival (rs2194980, rs169712, rs12106698) of which two overlapped with recurrence (rs2194980, rs169712). With a caveat on study heterogeneity, specific metabolites and metabolic pathway activity appear evident in the setting of poor prognostic colorectal cancers and such metabolic signatures are associated with specific genomic SNPs.

Tumor heterogeneity significantly increases the difficulty of tumor treatment. The same drugs and treatment methods have different effects on different tumor subtypes. Therefore, tumor heterogeneity is one of the main sources of poor prognosis, recurrence and metastasis. At present, there have been some computational methods to study tumor heterogeneity from the level of genome, transcriptome, and histology, but these methods still have certain limitations. In this study, we proposed an epistasis and heterogeneity analysis method based on genomic single nucleotide polymorphism (SNP) data. First of all, a maximum correlation and maximum consistence criteria was designed based on Bayesian network score K2 and information entropy for evaluating genomic epistasis. As the number of SNPs increases, the epistasis combination space increases sharply, resulting in a combination explosion phenomenon. Therefore, we next use an improved genetic algorithm to search the SNP epistatic combination space for identifying potential feasible epistasis solutions. Multiple epistasis solutions represent different pathogenic gene combinations, which may lead to different tumor subtypes, that is, heterogeneity. Finally, the XGBoost classifier is trained with feature SNPs selected that constitute multiple sets of epistatic solutions to verify that considering tumor heterogeneity is beneficial to improve the accuracy of tumor subtype prediction. In order to demonstrate the effectiveness of our method, the power of multiple epistatic recognition and the accuracy of tumor subtype classification measures are evaluated. Extensive simulation results show that our method has better power and prediction accuracy than previous methods.