Pooled DNA Samples Research Articles

High-Throughput Sequencing-The Key to Rapid Biodiversity Assessment of Marine Metazoa?

The applications of traditional morphological and molecular methods for species identification are greatly restricted by processing speed and on a regional or greater scale are generally considered unfeasible. In this context, high-throughput sequencing, or metagenetics, has been proposed as an efficient tool to document biodiversity. Here we evaluated the effectiveness of 454 pyrosequencing in marine metazoan community analysis using the 18S rDNA: V1-V2 region. Multiplex pyrosequencing of the V1-V2 region was used to analyze two pooled samples of DNA, one comprising 118 and the other 37 morphologically identified species, and one natural sample taken directly from a North Sea zooplankton community. A DNA reference library comprising all species represented in the pooled samples was created by Sanger sequencing, and this was then used to determine the optimal similarity threshold for species delineation. The optimal threshold was found at 99% species similarity, with 85% identification success. Pyrosequencing was able to identify between fewer species: 67% and 78% of the species in the two pooled samples. Also, a large number of sequences for three species that were not included in the pooled samples were amplified by pyrosequencing, suggesting preferential amplification of some genotypes and the sensitivity of this approach to even low levels of contamination. Conversely, metagenetic analysis of the natural zooplankton sample identified many more species (particularly gelatinous zooplankton and meroplankton) than morphological analysis of a formalin-fixed sample from the same sampling site, suggesting an increased level of taxonomic resolution with pyrosequencing. The study demonstrated that, based on the V1-V2 region, 454 sequencing does not provide accurate species differentiation and reliable taxonomic classification, as it is required in most biodiversity monitoring. The analysis of artificially prepared samples indicated that species detection in pyrosequencing datasets is complicated by potential PCR-based biases and that the V1-V2 marker is poorly resolved for some taxa.

Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis.

BackgroundInterest in the potential of DNA methylation in peripheral blood as a biomarker of cancer risk is increasing. We aimed to assess whether epigenome-wide DNA methylation measured in peripheral blood samples obtained before onset of the disease is associated with increased risk of breast cancer. We report on three independent prospective nested case-control studies from the European Prospective Investigation into Cancer and Nutrition (EPIC-Italy; n = 162 matched case-control pairs), the Norwegian Women and Cancer study (NOWAC; n = 168 matched pairs), and the Breakthrough Generations Study (BGS; n = 548 matched pairs). We used the Illumina 450k array to measure methylation in the EPIC and NOWAC cohorts. Whole-genome bisulphite sequencing (WGBS) was performed on the BGS cohort using pooled DNA samples, combined to reach 50× coverage across ~16 million CpG sites in the genome including 450k array CpG sites. Mean β values over all probes were calculated as a measurement for epigenome-wide methylation.ResultsIn EPIC, we found that high epigenome-wide methylation was associated with lower risk of breast cancer (odds ratio (OR) per 1 SD = 0.61, 95 % confidence interval (CI) 0.47–0.80; −0.2 % average difference in epigenome-wide methylation for cases and controls). Specifically, this was observed in gene bodies (OR = 0.51, 95 % CI 0.38–0.69) but not in gene promoters (OR = 0.92, 95 % CI 0.64–1.32). The association was not replicated in NOWAC (OR = 1.03 95 % CI 0.81–1.30). The reasons for heterogeneity across studies are unclear. However, data from the BGS cohort was consistent with epigenome-wide hypomethylation in breast cancer cases across the overlapping 450k probe sites (difference in average epigenome-wide methylation in case and control DNA pools = −0.2 %).ConclusionsWe conclude that epigenome-wide hypomethylation of DNA from pre-diagnostic blood samples may be predictive of breast cancer risk and may thus be useful as a clinical biomarker.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0104-2) contains supplementary material, which is available to authorized users.

DNA methylation levels are highly correlated between pooled samples and averaged values when analysed using the Infinium HumanMethylation450 BeadChip array

BackgroundDNA methylation is a heritable and stable epigenetic mark implicated in complex human traits. Epigenome-wide association studies (EWAS) using array-based technology are becoming widely used to identify differentially methylated sites associated with complex diseases. EWAS studies require large sample sizes to detect small effects, which increases project costs. In the present study we propose to pool DNA samples in methylation array studies as an affordable and accurate alternative to individual samples studies, in order to reduce economic costs or when low amounts of DNA are available. For this study, 20 individual DNA samples and 4 pooled DNA samples were analysed using the Illumina Infinium HumanMethylation450 BeadChip array to evaluate the efficiency of the pooling approach in EWAS studies. Statistical power calculations were also performed to discover the minimum sample size needed for the pooling strategy in EWAS.ResultsA total of 485,577 CpG sites across the whole genome were assessed. Comparison of methylation levels of all CpG sites between individual samples and their related pooled samples revealed highly significant correlations (rho > 0.99, p-val < 10−16). These results remained similar when assessing the 101 most differentially methylated CpG sites (rho > 0.98, p-val < 10−16). Also, it was calculated that n = 43 is the minimum sample size required to achieve a 95 % statistical power and a 10−06 significance level in EWAS, when using a DNA pool strategy.ConclusionsDNA pooling strategies seems to accurately provide estimations of averaged DNA methylation state using array based EWAS studies. This type of approach can be applied to the assessment of disease phenotypes, reducing the amount of DNA required and the cost of large-scale epigenetic analyses.

Lack of association between NCAM1 and early onset schizophrenia in a family based study in Shandong peninsula of China.

The neural cell adhesion molecule (NCAM1) gene plays important roles in cellular migration, synaptic integrity and neurodevelopment. Multiple NCAM1 proteins are differentially altered in schizophrenia (SZ). A whole genome association study was first carried out on Affymetrix genome-wide human single-nucleotide polymorphism (SNP) Array 6.0 and two pooled DNA samples consisting of 89 early onset SZ (EOS) cases and 1,000 controls. Association between rs10891495 and EOS was detected (χ(2) = 2 3.66, P = 1.15E-06). The position of this SNP is just within the NCAM1 gene. Since several previous studies reported that NCAM1 was a candidate gene for SZ, we further performed a family based association study and genotyped six SNPs (rs10891495, rs1245133, rs1821693, rs686050, rs12794326, rs674246) within NCAM1 gene in 100 EOS nuclear families. We found no evidence for association with SZ status either for SNP or for haplotype. Therefore, the NCAM1 gene is unlikely to play a major role in the etiology of early-onset SZ in the Chinese population.

Machine learning approach for pooled DNA sample calibration.

BackgroundDespite ongoing reduction in genotyping costs, genomic studies involving large numbers of species with low economic value (such as Black Tiger prawns) remain cost prohibitive. In this scenario DNA pooling is an attractive option to reduce genotyping costs. However, genotyping of pooled samples comprising DNA from many individuals is challenging due to the presence of errors that exceed the allele frequency quantisation size and therefore cannot be simply corrected by clustering techniques. The solution to the calibration problem is a correction to the allele frequency to mitigate errors incurred in the measurement process. We highlight the limitations of the existing calibration solutions such as the fact they impose assumptions on the variation between allele frequencies 0, 0.5, and 1.0, and address a limited set of error types. We propose a novel machine learning method to address the limitations identified.ResultsThe approach is tested on SNPs genotyped with the Sequenom iPLEX platform and compared to existing state of the art calibration methods. The new method is capable of reducing the mean square error in allele frequency to half that achievable with existing approaches. Furthermore for the first time we demonstrate the importance of carefully considering the choice of training data when using calibration approaches built from pooled data.ConclusionThis paper demonstrates that improvements in pooled allele frequency estimates result if the genotyping platform is characterised at allele frequencies other than the homozygous and heterozygous cases. Techniques capable of incorporating such information are described along with aspects of implementation.

Quantitative high resolution melting: two methods to determine SNP allele frequencies from pooled samples.

BackgroundThe advent of next-generation sequencing has brought about an explosion of single nucleotide polymorphism (SNP) data in non-model organisms; however, profiling these SNPs across multiple natural populations still requires substantial time and resources.ResultsHere, we introduce two cost-efficient quantitative High Resolution Melting (qHRM) methods for measuring allele frequencies at known SNP loci in pooled DNA samples: the “peaks” method, which can be applied to large numbers of SNPs, and the “curves” method, which is more labor intensive but also slightly more accurate. Using the reef-building coral Acropora millepora, we show that both qHRM methods can recover the allele proportions from mixtures prepared using two or more individuals of known genotype. We further demonstrate advantages of each method over previously published methods; specifically, the “peaks” method can be rapidly scaled to screen several hundred SNPs at once, whereas the “curves” method is better suited for smaller numbers of SNPs.ConclusionsCompared to genotyping individual samples, these methods can save considerable effort and genotyping costs when relatively few candidate SNPs must be profiled across a large number of populations. One of the main applications of this method could be validation of SNPs of interest identified in population genomic studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0222-z) contains supplementary material, which is available to authorized users.

Deep resequencing of 131 Crohn's disease associated genes in pooled DNA confirmed three reported variants and identified eight novel variants

ObjectiveGenome wide association studies (GWAS) and meta-analyses for Crohn's disease (CD) have not fully explained the heritability of CD, suggesting that additional loci are yet to be found and that...

Coupling Spore Traps and Quantitative PCR Assays for Detection of the Downy Mildew Pathogens of Spinach (Peronospora effusa) and Beet (P. schachtii).

Downy mildew of spinach (Spinacia oleracea), caused by Peronospora effusa, is a production constraint on production worldwide, including in California, where the majority of U.S. spinach is grown. The aim of this study was to develop a real-time quantitative polymerase chain reaction (qPCR) assay for detection of airborne inoculum of P. effusa in California. Among oomycete ribosomal DNA (rDNA) sequences examined for assay development, the highest nucleotide sequence identity was observed between rDNA sequences of P. effusa and P. schachtii, the cause of downy mildew on sugar beet and Swiss chard in the leaf beet group (Beta vulgaris subsp. vulgaris). Single-nucleotide polymorphisms were detected between P. effusa and P. schachtii in the 18S rDNA regions for design of P. effusa- and P. schachtii-specific TaqMan probes and reverse primers. An allele-specific probe and primer amplification method was applied to determine the frequency of both P. effusa and P. schachtii rDNA target sequences in pooled DNA samples, enabling quantification of rDNA of P. effusa from impaction spore trap samples collected from spinach production fields. The rDNA copy numbers of P. effusa were, on average, ≈3,300-fold higher from trap samples collected near an infected field compared with those levels recorded at a site without a nearby spinach field. In combination with disease-conducive weather forecasting, application of the assays may be helpful to time fungicide applications for disease management.

High frequency of multiple paternity in a solitary population of olive ridley sea turtles in Honduras

Females of all seven living species of sea turtles are known to be polyandrous and show multiple paternity. The frequency of multiple paternity varies among species, and among populations of the same species. In the olive ridley sea turtle (Lepidochelys olivacea), multiple paternity levels correlate with the abundance of individuals in the mating system, being much higher in arribada rookeries than in solitary nesting sites. We used two highly polymorphic microsatellite markers (Cm84 and Or1) to assess the level of multiple paternity in an olive ridley solitary population nesting in the Gulf of Fonseca, Honduras. We found evidence of multiple paternity in 6 out of 8 clutches (75%), with a minimum number of two fathers in four clutches, and a minimum of three in the remaining two clutches. This high level of multiple paternity in a small solitary population suggests that some of the females nesting in Honduras may be coming from proximal Nicaraguan arribada nesting beaches. Historical evidences and recent satellite telemetry data support this hypothesis. In addition, we show that multiple paternity studies can be effectively performed in the absence of maternal samples, and that pooled DNA samples can be used with results comparable to individual hatchling sampling in multiple paternity analyses.

MotorPlex provides accurate variant detection across large muscle genes both in single myopathic patients and in pools of DNA samples.

Mutations in ~100 genes cause muscle diseases with complex and often unexplained genotype/phenotype correlations. Next-generation sequencing studies identify a greater-than-expected number of genetic variations in the human genome. This suggests that existing clinical monogenic testing systematically miss very relevant information.We have created a core panel of genes that cause all known forms of nonsyndromic muscle disorders (MotorPlex). It comprises 93 loci, among which are the largest and most complex human genes, such as TTN, RYR1, NEB and DMD. MotorPlex captures at least 99.2% of 2,544 exons with a very accurate and uniform coverage. This quality is highlighted by the discovery of 20-30% more variations in comparison with whole exome sequencing. The coverage homogeneity has also made feasible to apply a cost-effective pooled sequencing strategy while maintaining optimal sensitivity and specificity.We studied 177 unresolved cases of myopathies for which the best candidate genes were previously excluded. We have identified known pathogenic variants in 52 patients and potential causative ones in further 56 patients. We have also discovered 23 patients showing multiple true disease-associated variants suggesting complex inheritance. Moreover, we frequently detected other nonsynonymous variants of unknown significance in the largest muscle genes. Cost-effective combinatorial pools of DNA samples were similarly accurate (97-99%).MotorPlex is a very robust platform that overcomes for power, costs, speed, sensitivity and specificity the gene-by-gene strategy. The applicability of pooling makes this tool affordable for the screening of genetic variability of muscle genes also in a larger population. We consider that our strategy can have much broader applications.Electronic supplementary materialThe online version of this article (doi:10.1186/s40478-014-0100-3) contains supplementary material, which is available to authorized users.

Quantitative analysis of low-density SNP data for parentage assignment and estimation of family contributions to pooled samples.

BackgroundWhile much attention has focused on the development of high-density single nucleotide polymorphism (SNP) assays, the costs of developing and running low-density assays have fallen dramatically. This makes it feasible to develop and apply SNP assays for agricultural species beyond the major livestock species. Although low-cost low-density assays may not have the accuracy of the high-density assays widely used in human and livestock species, we show that when combined with statistical analysis approaches that use quantitative instead of discrete genotypes, their utility may be improved. The data used in this study are from a 63-SNP marker Sequenom® iPLEX Platinum panel for the Black Tiger shrimp, for which high-density SNP assays are not currently available.ResultsFor quantitative genotypes that could be estimated, in 5% of cases the most likely genotype for an individual at a SNP had a probability of less than 0.99. Matrix formulations of maximum likelihood equations for parentage assignment were developed for the quantitative genotypes and also for discrete genotypes perturbed by an assumed error term. Assignment rates that were based on maximum likelihood with quantitative genotypes were similar to those based on maximum likelihood with perturbed genotypes but, for more than 50% of cases, the two methods resulted in individuals being assigned to different families. Treating genotypes as quantitative values allows the same analysis framework to be used for pooled samples of DNA from multiple individuals. Resulting correlations between allele frequency estimates from pooled DNA and individual samples were consistently greater than 0.90, and as high as 0.97 for some pools. Estimates of family contributions to the pools based on quantitative genotypes in pooled DNA had a correlation of 0.85 with estimates of contributions from DNA-derived pedigree.ConclusionsEven with low numbers of SNPs of variable quality, parentage testing and family assignment from pooled samples are sufficiently accurate to provide useful information for a breeding program. Treating genotypes as quantitative values is an alternative to perturbing genotypes using an assumed error distribution, but can produce very different results. An understanding of the distribution of the error is required for SNP genotyping platforms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-014-0051-y) contains supplementary material, which is available to authorized users.

Screening and characterization of sex-linked DNA markers and marker-assisted selection in the Nile tilapia (Oreochromis niloticus)

The Nile tilapia is a cultured teleost fish in which males grow faster and larger than females, and mono-sex culturing could avoid unwanted reproduction during grow-out. Sex control in tilapia is an important issue in aquaculture. In the present study, randomly amplified polymorphic DNA (RAPD) and amplified fragment length polymorphism (AFLP) fingerprinting were used to screen pooled and individual DNA samples from XX, XY, and YY fish for sex-linked markers. Four sex-linked markers (Marker-1 from RAPD and Markers-2, -3, and -4 from AFLP) were obtained and mapped to LG23, a small chromosome, by sequence analysis and fluorescence in situ hybridization (FISH). In addition, a total of 32 pairs of primers were designed based on the sequences of scaffolds 7, 29, and 101 on LG23, and these were used to screen genetic differences between X and Y by PCR. One of these (Marker-5) produced a detectable difference between XX, XY, and YY individuals. Eight pairs of primers based on the sequence characterized amplified region (SCAR) were designed and successfully converted to SCAR markers, which were used to sex progeny from different crosses of known genotypes for validation. Subsequently, Markers-4 and -5 were used to sex eight populations of Nile tilapia collected from different fish farms in China, which gave concordance rates that ranged from 76 to 100%. Based on the recombination rate derived from the progeny of XX (♀) × XY (♂), Markers-1, -2, -3, -4, and -5 were estimated to be around 5, 3, 5, 2 and 0 cM away from the sex-determining locus (SD), respectively. Marker-5, which mapped close to the SD reported previously (Eshel et al., 2012), was used for selective breeding of genetic male tilapia (GMT). • Five sex-linked markers were isolated from Nile tilapia. • Markers were located on LG23, about 5, 3, 5, 2 and 0 cM away from SD. • PCR-based genetic sex identification and MAS-GMT were established. • In the strain studied, sex is primarily determined by a locus in LG23.

A two-dimensional pooling strategy for rare variant detection on next-generation sequencing platforms.

We describe a method for pooling and sequencing DNA from a large number of individual samples while preserving information regarding sample identity. DNA from 576 individuals was arranged into four 12 row by 12 column matrices and then pooled by row and by column resulting in 96 total pools with 12 individuals in each pool. Pooling of DNA was carried out in a two-dimensional fashion, such that DNA from each individual is present in exactly one row pool and exactly one column pool. By considering the variants observed in the rows and columns of a matrix we are able to trace rare variants back to the specific individuals that carry them. The pooled DNA samples were enriched over a 250 kb region previously identified by GWAS to significantly predispose individuals to lung cancer. All 96 pools (12 row and 12 column pools from 4 matrices) were barcoded and sequenced on an Illumina HiSeq 2000 instrument with an average depth of coverage greater than 4,000×. Verification based on Ion PGM sequencing confirmed the presence of 91.4% of confidently classified SNVs assayed. In this way, each individual sample is sequenced in multiple pools providing more accurate variant calling than a single pool or a multiplexed approach. This provides a powerful method for rare variant detection in regions of interest at a reduced cost to the researcher.

Numerical analysis of intensity signals resulting from genotyping pooled DNA samples in beef cattle and broiler chicken1

Pooled genomic DNA has been proposed as a cost-effective approach in genomewide association studies (GWAS). However, algorithms for genotype calling of biallelic SNP are not adequate with pooled DNA samples because they assume the presence of 2 fluorescent signals, 1 for each allele, and operate under the expectation that at most 2 copies of the variant allele can be found for any given SNP and DNA sample. We adapt analytical methodology from 2-channel gene expression microarray technology to SNP genotyping of pooled DNA samples. Using 5 datasets from beef cattle and broiler chicken of varying degrees of complexity in terms of design and phenotype, continuous and dichotomous, we show that both differential hybridization (M = green minus red intensity signal) and abundance (A = average of red and green intensities) provide useful information in the prediction of SNP allele frequencies. This is predominantly true when making inference about extreme SNP that are either nearly fixed or highly polymorphic. We propose the use of model-based clustering via mixtures of bivariate normal distributions as an optimal framework to capture the relationship between hybridization intensity and allele frequency from pooled DNA samples. The range of M and A values observed here are in agreement with those reported within the context of gene expression microarray and also with those from SNP array data within the context of analytical methodology for the identification of copy number variants. In particular, we confirm that highly polymorphic SNP yield a strong signal from both channels (red and green) while lowly or nonpolymorphic SNP yield a strong signal from 1 channel only. We further confirm that when the SNP allele frequencies are known, either because the individuals in the pools or from a closely related population are themselves genotyped, a multiple regression model with linear and quadratic components can be developed with high prediction accuracy. We conclude that when these approaches are applied to the estimation of allele frequencies, the resulting estimates allow for the development of cost-effective and reliable GWAS.

Discovery of rare mutations in extensively pooled DNA samples using multiple target enrichment

Chemical mutagenesis is routinely used to create large numbers of rare mutations in plant and animal populations, which can be subsequently subjected to selection for beneficial traits and phenotypes that enable the characterization of gene functions. Several next-generation sequencing (NGS)-based target enrichment methods have been developed for the detection of mutations in target DNA regions. However, most of these methods aim to sequence a large number of target regions from a small number of individuals. Here, we demonstrate an effective and affordable strategy for the discovery of rare mutations in a large sodium azide-induced mutant rice population (F2). The integration of multiplex, semi-nested PCR combined with NGS library construction allowed for the amplification of multiple target DNA fragments for sequencing. The 8 × 8 × 8 tridimensional DNA sample pooling strategy enabled us to obtain DNA sequences of 512 individuals while only sequencing 24 samples. A stepwise filtering procedure was then elaborated to eliminate most of the false positives expected to arise through sequencing error, and the application of a simple Student's t-test against position-prone error allowed for the discovery of 16 mutations from 36 enriched targeted DNA fragments of 1024 mutagenized rice plants, all without any false calls.

Knockdown resistance allele frequencies in North American head louse (Anoplura: Pediculidae) populations.

The study examines the extent and frequency of a knockdown-type resistance allele (kdr type) in North American populations of human head lice. Lice were collected from 32 locations in Canada and the United States. DNA was extracted from individual lice and used to determine their zygosity using the serial invasive signal amplification technique to detect the kdr-type T917I (TI) mutation, which is most responsible for nerve insensitivity that results in the kdr phenotype and permethrin resistance. Previously sampled sites were resampled to determine if the frequency of the TI mutation was changing. The TI frequency was also reevaluated using a quantitative sequencing method on pooled DNA samples from selected sites to validate this population genotyping method. Genotyping substantiated that TI occurs at high levels in North American lice (88.4%). Overall, the TI frequency in U.S. lice was 84.4% from 1999 to 2009, increased to 99.6% from 2007 to 2009, and was 97.1% in Canadian lice in 2008. Genotyping results using the serial invasive signal amplification reaction (99.54%) and quantitative sequencing (99.45%) techniques were highly correlated. Thus, the frequencies of TI in North American head louse populations were found to be uniformly high, which may be due to the high selection pressure from the intensive and widespread use of the pyrethrins- or pyrethroid-based pediculicides over many years, and is likely a main cause of increased pediculosis and failure of pyrethrins- or permethrin-based products in Canada and the United States. Alternative approaches to treatment of head lice infestations are critically needed.

Linkage disequilibrium and haplotype distribution of the bovine LHX4 gene in relation to growth

LIM homeobox transcription factor 4 (LHX4) is a LIM homeodomain transcription factor involved in pituitary gland and nervous system development. The aim of this study was to examine the association of the LHX4 polymorphisms with growth traits in beef cattle breed. A total of 7 single nucleotide polymorphyisms (SNPs) have been identified in the coding region and noncoding region of the bovine LHX4 by sequencing pooled DNA samples (Pool-Seq) and PCR-single strand conformation polymorphism (PCR-SSCP) methods. The linkage disequilibrium was assessed in 871 individuals representing four main cattle breeds from China. The SNPs 2–5 and 7–8 were found to be in complete linkage disequilibrium, respectively. The result of haplotype analysis of 13 SNPs showed that 31 haplotypes were found in four Chinese cattle breeds, and 20 genotypes were only found in Nanyang cattle. The statistical analyses indicated that the SNP1–5, and 6 are associated with the body weight at 18, and 6months of age in Nanyang cattle population (P<0.05), but no significant associations between their twenty combined genotypes. Our results provide evidence that some polymorphisms in LHX4 are associated with growth traits at certain ages, and may be used as candidates for marker-assisted selection and management in cattle.

MotorPlex provides accurate variant detection across large muscle genes both in single myopathic patients and in pools of DNA samples

Mutations in ~100 genes cause muscle diseases with complex and often unexplained genotype/phenotype correlations. Next-generation sequencing studies identify a greater-than-expected number of genetic variations in the human genome. This suggests that existing clinical monogenic testing systematically miss very relevant information. We have created a core panel of genes that cause all known forms of nonsyndromic muscle disorders (MotorPlex). It comprises 93 loci, among which are the largest and most complex human genes, such as TTN, RYR1, NEB and DMD. MotorPlex captures at least 99.2% of 2,544 exons with a very accurate and uniform coverage. This quality is highlighted by the discovery of 20-30% more variations in comparison with whole exome sequencing. The coverage homogeneity has also made feasible to apply a cost-effective pooled sequencing strategy while maintaining optimal sensitivity and specificity. We studied 177 unresolved cases of myopathies for which the best candidate genes were previously excluded. We have identified known pathogenic variants in 52 patients and potential causative ones in further 56 patients. We have also discovered 23 patients showing multiple true disease-associated variants suggesting complex inheritance. Moreover, we frequently detected other nonsynonymous variants of unknown significance in the largest muscle genes. Cost-effective combinatorial pools of DNA samples were similarly accurate (97-99%). MotorPlex is a very robust platform that overcomes for power, costs, speed, sensitivity and specificity the gene-by-gene strategy. The applicability of pooling makes this tool affordable for the screening of genetic variability of muscle genes also in a larger population. We consider that our strategy can have much broader applications.

Novel candidate genes putatively involved in stress fracture predisposition detected by whole-exome sequencing.

While genetic factors in all likelihood contribute to stress fracture (SF) pathogenesis, a few studies focusing on candidate genes have previously been reported. The objective of this study is to gain better understanding on the genetic basis of SF in a gene-naive manner. Exome sequence capture followed by massive parallel sequencing of two pooled DNA samples from Israeli combat soldiers was employed: cases with high grade SF and ethnically matched healthy controls. The resulting sequence variants were individually verified using the Sequenom™ platform and the contribution of the genetic alterations was validated in a second cohort of cases and controls. In the discovery set that included DNA pool of cases (n = 34) and controls (n = 60), a total of 1174 variants with >600 reads/variant/DNA pool were identified, and 146 (in 127 genes) of these exhibited statistically significant (P < 0·05) different rates between SF cases and controls after multiple comparisons correction. Subsequent validation of these 146 sequence variants individually in a total of 136 SF cases and 127 controls using the Sequenom™ platform validated 20/146 variants. Of these, three missense mutations (rs7426114, rs4073918, rs3752135 in the NEB, SLC6A18 and SIGLEC12 genes, respectively) and three synonymous mutations (rs2071856, rs2515941, rs716745 in the ELFN2, GRK4, LRRC55 genes) displayed significant different rates in SF cases compared with controls. Exome sequencing seemingly unravelled novel candidate genes as involved in SF pathogenesis and predisposition.

Expression, SNP Identification, Linkage Disequilibrium, and Haplotype Association Analysis of the Growth Suppressor Gene ZBED6 in Qinchuan Beef Cattle

Zinc finger, BED-type containing 6 (ZBED6) is a novel transcription factor that was identified and shown to act as a repressor of IGF2 transcription in skeletal muscle myogenesis and development. The aims of this study were to determine ZBED6 expression level and examine the association of the ZBED6 polymorphism with growth traits in Qinchuan beef cattle. The bovine ZBED6 mRNA was detected in eight tissues by quantitative real-time PCR (qPCR), being highly expressed in skeletal muscle. Three single nucleotide polymorphisms (SNPs) were identified the bovine ZBED6 by sequencing pooled DNA samples (Pool-Seq) and forced polymerase chain reaction-restriction fragment length polymorphism (forced PCR-RFLP) methods. In this study, we reported one mutation in the promoter and two missense mutations in the coding regions within the bovine ZBED6 gene, and the haplotype variability and extent of linkage disequilibrium (LD) in 817 individuals from the Qinchuan (QC) and Chinese Holstein (CH). We also investigated haplotype structure and linkage disequilibrium coefficients for three SNPs of ZBED6 in the study populations. The result of haplotype analysis of three SNPs showed that eight different haplotypes were identified in two breeds. The wild-type haplotype (Hap 1: GCA) and mutant-type haplotype (Hap 8: AGG) shared by two populations accounted for 29.8%, 57.5%, and 8.6%, 0% of all haplotypes observed in QC and CH, respectively. The statistical analyses indicated that three SNPs, 23 combined genotypes, and 8 haplotypes were significantly associated with different growth traits in the QC cattle population (P < 0.05 or P < 0.01). The mutant-type variants and mutant haplotype were superior for growth traits; the heterozygote diplotype was associated with higher growth traits compared to the wild-type homozygote. The results of this study suggest that the ZBED6 gene possibly is a strong candidate gene that affects growth traits in QC beef cattle breeding program.