Rhizoprionodon) exhibit life-history characteristics  that suggests that they could be fished in a sustainable manner assuming an investment in monitoring, assessment and careful management. However, obtaining species-specific landings data for sharpnose sharks is problematic because they are morphologically very similar to one another. Moreover, sharpnose sharks may also be confused with other small sharks  once they are processed . Here we present a highly streamlined molecular genetics approach based on seven species-specific PCR primers in a multiplex format that can simultaneously discriminate body parts from the seven described sharpnose shark species commonly occurring in coastal fisheries worldwide. The species-specific primers are based on nucleotide sequence differences among species in the nuclear ribosomal internal transcribed spacer 2 locus (ITS2). This approach also distinguishes sharpnose sharks from a wide range of other sharks (52 species) and can therefore assist in the regulation of coastal shark fisheries around the world.Obtaining accurate species-specific landings data is an essential step toward achieving sustainable shark fisheries. Globally distributed sharpnose sharks (genus  Shark fisheries have intensified worldwide in response to increasing demand for shark products . A major impediment managing these shark fisheries is the lack of species-specific catch data. Most shark landings are reported as an amalgam of species, in which products are sorted by broad taxonomic groups. This problem is compounded by the fact that sharks are not usually sold as whole animals, but as carcasses or processed in the form of fillets, making it difficult to identify species of origin.Rhizoprionodon is represented worldwide by seven species of small sharks Rhizoprionodon porosus (Caribbean sharpnose shark), R. lalandei (Brazilian sharpnose shark), R. terranovae (Atlantic sharpnose shark), R. oligolinx (Grey sharpnose shark), R. taylori , R. acutus (Milk shark) and R. longurio (Pacific sharpnose shark). All these sharks are range-restricted and inhabit tropical and subtropical inshore waters in either the Atlantic, Indian or Pacific oceans The genus R. lalandei and R. longurio as “Data deficient” for assessment R. porosus, which is considered to exhibit a “stable” population trend. There is some evidence for decline in some of the Atlantic species due to fisheries overexploitation Sharpnose sharks are landed in large quantities by artisanal and commercial fisheries in many locations worldwide Molecular methods have previously been used to quantify global shark fin landings, detect or reveal captures of threatened shark species and trace the geographic origin of shark parts in trade The objective of the present study was to develop a multiplex PCR assay to simultaneously identify all seven heavily exploited species of sharpnose sharks. The main goal was the obtainment of a complete set of species-specific primers for monitoring the global catch and trade on sharpnose species. This methodology was further validated through screening of market-derived samples in two independent case studies.Rhizoprionodon were specifically collected from southern and northern Brazil , Gulf of Mexico, southern USA (R. terranovae), Oman and Kuwait coast, (R. oligolinx), northern and western Australia  and western Mexico (R. longurio). Putative species-specific sharpnose primers were also tested against reference samples from 52 additional shark species (One hundred sixty six sharpnose shark fin and muscle tissue samples used for ITS2 DNA sequencing and species-specific primer testing (hereafter referred to as “reference samples”) were collected from fresh or frozen specimens caught by local fishermen and commercial boats in coastal areas of the Atlantic, Indian and Pacific Oceans . These r species . These s2, 1x PCR buffer, 200 µM dNTP’s and 1 unit of Platinum Taq DNA polymerase (Invitrogen Inc.). The reactions were performed on an iCycler (BioRad) thermal cycler. Cycling profiles consisted of initial heating at 94°C for 3 min, followed by 35 cycles at 94°C for 1 min, 55°C for 1 min, 72°C for 2 min and a 5 min extension at 72°C. Amplified segments were visualized on a 1% agarose gel stained with GelRed (Uniscience), under UV light. All products were purified with the QIAquick PCR purification kit using the manufacturer’s protocol (Qiagen Inc.).Total genomic DNA was isolated from muscle or fin clips using the DNeasy Tissue Kit (Qiagen Inc.) following the manufacturer instructions. The whole ITS2 region was amplified using the universal primers FISH5.8SF and FISH28SR Sequencing reactions were performed using the BigDye Terminator v3.1 kit , following the manufacturer’s protocol. The cycling profile comprised an initial denaturation at 95°C for 5 min, followed by 35 cycles of denaturation at 95°C for 1 min, annealing at 50°C for 30 s and extension at 60°C for 1 min. Products were gel purified using the DyeEx 2.0 Spin Kits (Qiagen Inc) and sequencing was carried out on a Applied Biosystems 3130 DNA analyzer . The final ITS2 locus sequence size retrieved from each species is shown on Rhizoprionodon species  and the genetic distances among species calculated in MEGA 4 Rhizoprionodon congeners were then further tested for their species-specificity (same cycling conditions as above) against 52 additional non-target  shark species representing a wide range of evolutionarily diverse lineages and also known to occur in fisheries . The putative SSPs that consistently amplified the correct-sized fragment for their respective target species but not any other isheries . After tRhizoprionodon species in international trade, we tested a nine-primer (nonaplex) PCR assay for its diagnostic performance. This nonaplex format consisted of the seven sharpnose SSPs plus the two shark universal primers . Other 34 meat samples comprised the following: 12 blue sharks (Prionace glauca), 11 shortfin mako sharks (Isurus oxyrhinchus), two scalloped hammerhead sharks (Sphyrna lewini), and a single sample each from silky , dusky (C. obscurus) and white shark (Carcharodon carcharias). The remaining six samples were from unidentified species likely not corresponding to the set of species-specific primers utilized. Of the 21 carcasses tested, seven were Brazilian sharpnoses, three were Caribbean sharpnoses, five were scalloped hammerheads and six were smooth hammerheads (Sphyrna zygaena). Posterior sequencing of all market-derived shark samples undoubtedly confirmed their IDs provided by SSPs (data available upon request to the authors).Of the 69 shark meat samples tested, 35 samples were genetically identified by SSPs as originating from two sharpnose species  and the large interspecific genetic divergence found in the ITS2 locus among all sharpnoses  indicateRhizoprionodon. In previous studies using the PCR-multiplex approach for species identification, the positive control was included only to prevent the complete absence of any amplification  from being interpreted as the absence of a particular species  Rhizoprionodon species with larger species-diagnostic amplicons from smaller positive control ITS2 amplicons of equivalent molecular weight , the presence of an accompanying positive control amplicon was essential, allowing undoubted species diagnosis.During standardization of the nine-primer multiplex methodology, the positive control amplicon was faintly amplified in some of the target sharpnose sharks as previously reported for other species R. lalandei and R. porosusR. terranovae. Combinations of these three species have an overlapping range in many locations in the Atlantic. The ability to identify all three species at once ensures that this one assay can be used throughout the Atlantic. Routine application of this assay to monitor fisheries may result in a clearer understanding of the distribution and degree of overlap between these similar-looking species.Our assay provides a relatively inexpensive and straightforward procedure to (1) identify products as originating from a sharpnose shark and (2) discriminate amongst sharpnose species. The assay is ready to be applied in the acquisition of catch and trade data for these species anywhere in the world. The advantage of one-tube reaction is that it enables shorter PCR cycles and good results with minor amounts of template DNA, a feature particularly functional in forensic applications Many shark populations are fished at or above a level that is sustainable and there is an urgent monitor and regulate shark fisheries. Although more data is needed to determine whether this is the case or not for several of the sharpnose species, their relatively high productivity suggests that this group of sharks could sustain a level of properly managed fishing pressure. Our assay provides an expedient and inexpensive procedure that could be used to monitor the catch of sharpnose sharks on a species-specific basis. We envision it will be most useful in developing nations that simultaneously fish several sharpnose species at once, especially in the Western Atlantic . The case studies presented here clearly addressed this issue and the genetic identification provided by our multiplex PCR approach demonstrates its utility. It could also be used in conjunction with other DNA identification methods to rapidly separate sharpnose products from similar products from juveniles of larger species, to better understand how inshore fisheries affect recruitment of larger, more vulnerable shark species.Table S1Inventory of non-target shark species tested with the sharpnose shark species-specific primers in triplex and nonaplex PCR assays. Geographic ocean basin origins of the shark test species are shown, with (n) representing the number of individuals of each species tested from each geographic region.(DOC)Click here for additional data file.


PEMT, PCYT1A, and PTDSS2 were positively correlated and PCYT2 was negatively correlated with percent fat mass and body mass index (BMI). Among the polymorphisms in these genes, SNP rs4646404 in PEMT showed the strongest association (p = 3.07E-06) with waist-to-hip ratio (WHR) adjusted for BMI. The WHR-associated intronic SNP rs4646343 in the PEMT gene showed the strongest association with its expression in adipose. Allele “C” of this SNP was associated with higher WHR (p = 2.47E-05) and with higher expression (p = 4.10E-04). Our study shows that the expression of PEMT gene is high in obese insulin-resistant subjects. Intronic cis-regulatory polymorphisms may increase the genetic risk of obesity by modulating PEMT expression.Recent studies have identified links between phospholipid composition and altered cellular functions in animal models of obesity, but the involvement of phospholipid biosynthesis genes in human obesity are not well understood. We analyzed the transcript of four phospholipid biosynthesis genes in adipose and muscle from 170 subjects. We examined publicly available genome-wide association data from the GIANT and MAGIC cohorts to investigate the association of SNPs in these genes with obesity and glucose homeostasis traits, respectively. Trait-associated SNPs were genotyped to evaluate their roles in regulating expression in adipose. In adipose tissue, expression of  Compared to wild-type mice, PEMT-deficient mice (Pemt -/-) are resistant to diet-induced hypertrophy of adipocytes in white adipose tissue and are also protected against high fat diet-induced obesity and insulin resistance PCYT2) gene is involved in synthesis of PE from diacylglycerol. Interestingly, mice deficient in PCYT2 (Pcyt2+/−) are obese and insulin resistant Interestingly, mRNA and protein levels of phosphatidylethanolamine N-methyltransferase (cis- regulatory polymorphisms (eSNPs) may increase susceptibility to obesity and insulin resistance by modulating expression of these genes. To test our hypothesis, we analyzed expression of four major genes  involved in ER membrane phospholipid biosynthesis/remodeling in adipose and muscle from 170 individuals with a broad range of insulin sensitivity (SI) and body mass index (BMI) values. We investigated the association of SNPs in these genes with obesity and glycemic traits in publicly available data from large genome-wide association studies. Finally, we evaluated the role of obesity-associated SNPs in these genes in regulating expression in adipose tissue.Given these considerations, we hypothesized that adipose and muscle tissue expression of genes in the ER phospholipid biosynthesis pathway will be associated with obesity and insulin resistance in humans, and 2. Detailed characteristics of the subjects in this study are described elsewhere Gene expression and effects of genotype on gene expression were studied in adipose and muscle tissue from 170 Caucasian or African American subjects recruited by advertisement. Subjects were in good general health, between 19–60 years of age, and had a body mass index (BMI) between 19 and 45 kg/mvastus lateralis muscle of all subjects were obtained under fasting conditions, and insulin sensitivity of non-diabetic subjects were evaluated by an insulin modified frequently sampled intravenous glucose tolerance test (FSIVGT). Body fat was determined by dual X-ray absorptiometry (DXA) scans (Hologic QDR-4500). Biopsy samples were quick frozen in liquid nitrogen and stored at −80°C for further use. The adipocyte fraction (AF) was separated from the stromal-vascular fraction (SVF) after collagenase digestion of freshly collected adipose biopsy samples, as described earlier Genomic DNA was isolated from blood samples using a Puregene DNA extraction kit . Needle biopsies of abdominal subcutaneous adipose tissue and Insulin was measured by the UAMS Clinical Research Center core laboratory using an immuno-chemiluminometric assay . Assays with <10% CV were used for the analysis. Plasma glucose was measured by using a glucose oxidase method at LabCorp, Inc. .Total RNA was isolated from whole adipose and adipocyte fractions using the RNAeasy Lipid Tissue Mini kit (Qiagen). Total RNA from the SVF of adipose was isolated using an RNAqueous kit . RNA from muscle biopsies was isolated using an Ultrasoec RNA kit . The quantity and quality of the isolated total RNA samples were determined by ultraviolet spectrophotometry  and electrophoresis , respectively.Figure S1). Choline-phosphate cytidylyltransferase A (PCYT1A) and ethanolamine-phosphate cytidylyltransferase 2 (PCYT2) genes are involved in synthesis of PC and PE, respectively, from diacylglycerol. Phosphatidylethanolamine N-methyltransferase (PEMT) catalyzes the conversion of PE to PC by a sequential methylation reaction PTDSS2) converts PE to phosphatidylserine (PS). Thus, we analyzed expression of these genes in tissues relevant to obesity and related metabolic phenotypes.A recent study by Fu et al in animal models identified an increase in the cellular PC/PE ratio as a mechanism proximal to the ER stress induction in obesity table S1 for details). We have successfully generated expression data in adipose tissue of 155 subjects and in muscle of 160 subjects from our cohort.Total RNA (1 µg) was reverse transcribed using a Qiagen QuantiTect reverse transcription kit (Qiagen) following the manufacturer's protocol, which includes a DNase digestion step to remove genomic DNA contamination. Transcripts were measured by quantitative real-time PCR using Power SYBR green chemistry  and normalized either to the expression of human ribosomal protein, large P0 (RPLP0 or 36B4) gene (for adipose and AF), or to 18S ribosomal RNA (for muscle and SVF), similar to our published studies http://www.broadinstitute.org/collaboration/giant/) consortium http://www.magicinvestigators.org) To investigate whether the SNPs in genes in phospholipid remodeling were associated with obesity and glucose homeostasis traits, we examined publicly accessible data from large genome-wide association (GWA) studies in Caucasian subjects. We used meta-analyses of association data for BMI and WHR adjusted for BMI from the GIANT . We further expanded our search to ±500 kb to identify any associations within the putative PCYT1A, PCYT2, or PTDSS2 SNPs with metabolic phenotypes in the GIANT and MAGIC data sets (at the p≤0.0004 level). However, nine SNPs in PEMT showed significant associations (see Results). Thus, genotype vs. expression association was tested only for these SNPs in PEMT. Linkage disequilibrium between SNPs was evaluated by HaploView software http://hapmap.ncbi.nlm.nih.gov/). Three SNPs were selected to tag (r2>0.8) nine SNPs within ±2 Kb of the PEMT gene that were associated with WHR (adjusted for BMI). A coding non-synonymous SNP (rs7946) that showed a marginal association with WHR was also genotyped.Resent studies have shown that complex trait-associated SNPs are enriched for regulatory SNPs (eSNPs) table S2.Genomic DNA isolated from total blood samples of individuals from our expression cohort was used for genotyping. Four SNPs were genotyped by Pyrosequencing  using a modification of the manufacturer's protocol including a biotinylated universal primer. Details of genotyping assays are given in I) of non-diabetic subjects I) with gene expression were calculated after controlling for age, gender, and self-identified ethnicity I are strongly correlated, additional adjustments for BMI were also included to evaluate correlations between gene expression and SI. Pre-computed p-values from the GIANT and MAGIC meta-analyses were used and queried using a Microsoft Access database to evaluate the association between SNPs in the four phospholipid remodeling genes and obesity and glucose homeostasis traits, respectively. Genotypic effects on gene expression were analyzed by one-way analysis of variance (ANOVA). Associations between genotype and gene expression were further evaluated by univariate analysis of variance using a general linear model (GLM) procedure, which includes age as a covariate and genotype, gender, and self-identified ethnicity as fixed factors a priori hypothesis and the high correlation among tested traits.We used the MINMOD Millennium program to analyze FSIVGT data to determine insulin sensitivity , PEMT  and PTDSS2  in adipose showed significant positive correlations, while PCYT2  was negatively correlated with percent of fat mass (PFAT) and BMI in 142 non-diabetic subjects  but not by cells in the stromal vascular fraction  than in stromal vascular fractions of adipose tissue.Expression of subjects Table 2.I) was negatively correlated with expression of PEMT  and positively correlated with PCYT2  in adipose. However, correlations of PEMT and PCYT2 expression with SI were only marginally significant after adjustment for BMI  in skeletal muscle compared to subcutaneous adipose, and the other three genes tested in muscle showed similar levels of expression compared to adipose. Expression of these genes in muscle showed no significant correlation with expression in adipose tissue from the same subjects. Expression of these phospholipid remodeling genes in muscle was not correlated with obesity measures  with SI.Average expression of measures . HoweverPTDSS2, PEMT, and PCYT1A genes. None of these SNPs showed significant association at a genome-wide significance threshold (p<5.0×10−8). However, at our overall significance threshold (p ≤0.0004), 9 SNPs in PEMT showed significant associations with WHR adjusted for BMI . Further expansion of this search identified a locus in chromosome 17 significantly associated with WHR (adjusted for BMI). SNP rs4646404, located in an intron of PEMT, showed the strongest association  within ±500 Kb of the gene . None of the SNPs within ±2 Kb of these genes showed any evidence for association with BMI in the GIANT meta-analysis dataset at the p≤0.00004 threshold. A similar search in meta-analysis data from the MAGIC consortium also identified no SNPs significantly associated with glucose homeostasis traits . No SNP association data were available for the ±2 kb region around the PCYT2 gene. However, no SNP reached significance in an expanded search within ±500 kb region of this gene.Interrogation of the meta-analysis data from the GIANT consortium identified 115 SNPs within ±2 kb of the cis-regulators in adipose tissue. In our cohort (N = 154), intronic SNP rs4646343 showed the strongest genotypic association (p = 9.16×10−4) with expression of PEMT transcript (and−4) in a non-diabetic Caucasian subset (N = 101) of our cohort. The SNP rs4646404 that showed the strongest association with WHR in the GIANT dataset was marginally associated (p = 0.024–0.09) with PEMT expression in adipose. We noticed that for all of these SNPs, alleles linked to increased WHR were associated with increased expression of PEMT.We further investigated if the WHR-associated SNPs (within ±2 kb of PEMT gene) are PEMT) and downregulation of the PCYT2 gene, involved in PE biosynthesis, in the adipose tissue of obese subjects. Although we have not measured tissue phospholipid levels, the transcriptional profile of four genes indicates a possible increase in PC/PE ratio in adipose and may be a mechanism behind the perturbation of ER homeostasis and induction of ER stress. In our study, induction of PEMT in obesity was limited to adipocytes, and was not seen in muscle or cells in the SVF of adipose. Thus, similar to rodent models Studies by our laboratory and others have shown the induction of chronic ER stress in adipose tissue of obese subjects We attempted to elucidate the function of four phospholipid biosynthesis genes in obesity and related traits by combining phenotype, gene expression in tissues important for obesity, and genotype data in a metabolically well-characterized cohort. Integration of publicly available genome-wide association (GWA) findings with our study significantly expedited our search to identify functional polymorphisms that increase susceptibility to obesity by modulating expression at the transcript level. However, a notable limitation of our study is that we used only adipose and muscle samples. As noted previously, phospholipid remodeling in hepatic ER was the focus of a rodent model study −6) loci using a fixed effect meta-analysis of WHR from 77,167 subjects from 32 studies, employing study-specific linear regression adjusted for BMI and age, stratified by gender, and using an additive genetic model PEMT polymorphism with WHR adjusted for BMI in the GIANT consortium dataset. The strongest association p-value (p = 3.07×0−6) for WHR within ±500 Kb of the PEMT gene is below the threshold and thus was not reported by GIANT consortium. Prioritizing genes that are causally involved with susceptibility to obesity may thus be helpful in identifying additional genetic susceptibility loci from GWA studies.Although dietary and lifestyle risk factors play important roles, the contribution of genetic susceptibility to obesity is well established. Recent GWA studies have identified several susceptibility loci for obesity PEMT expression in adipose was a more significant predictor of percent of fat mass compared to BMI. Polymorphisms in PEMT are not associated with BMI, but were associated with WHR adjusted for BMI, indicating this gene's role in body fat distribution rather than overall adiposity. These polymorphisms were also associated with transcript-level expression of PEMT in adipose tissue. Analysis of publicly available adipose tissue eQTL data also confirmed this association  and Phosphatidylethanolamine (PE) biosynthesis and remodeling. .(PDF)Click here for additional data file.Figure S2Linkage Disequilibrium among SNPs in PEMT gene. Top graph also indicates association of PEMT SNPs with WHR (adjusted for BMI) in Caucasian subjects from the GIANT consortium.(PDF)Click here for additional data file.Figure S3SNPs in PEMT gene region (±500 Kb) are associated with waist-to-hip ratio (WHR) adjusted for BMI. Data represents a meta-analysis of 77158 Caucasian subjects from the GIANT consortium.(PDF)Click here for additional data file.Figure S4Association of PEMT expression with local SNP genotype in MuTHER consortium-TwinUK data set. A) Expression of PEMT (Illumina expression probe ILMN_1745806) in adipose is associated with local regulatory SNPs and association peaks within the intron of PEMT. Association of 540 SNPs within ±500 Kb of PEMT gene is shown . B) WHR associated intronic SNP rs4646343 is an adipose tissue specific cis-regulator for PEMT and not for any other gene within ±500 Kb. A, adipose; L, transformed lymphocyte; S, skin fibroblast.(PDF)Click here for additional data file.Table S1Primer sequences for quantitative real time PCR (qRT-PCR) assays.(PDF)Click here for additional data file.Table S2Primer sequences for genotyping by pyrosequencing.(PDF)Click here for additional data file.


Epidermal growth factor receptor monoclonal antibody was approved for treatment of metastatic colorectal cancer patients carrying KRAS wild type DNA. However, recent studies showed that patients with KRAS G13D mutation may benefit from EGFR antibody therapy. In this study we tried to explore whether the abundance of KRAS mutation could affect the efficacy of EGFR antibody therapy. We firstly established a PNA-PCR method which could calculate the percentage of KRAS mutation in total DNA and proved its ability on 47 colorectal cancer samples bearing KRAS mutations. Then we analyzed the correlation between the abundance of KRAS mutations and efficacy of EGFR antibody therapy in another 35 metastatic colorectal cancer patients. We proved that PNA-PCR assay could calculate the abundance of KRAS mutation and the percentage of mutant DNA in tumor cells varied a lot (10.8%∼98.3%) on the 47 colorectal cancer patients. The efficacy of EGFR antibody correlated with the abundance of KRAS mutations: in the KRAS mutation less than 30% group, the disease control rate was 44.4% (4/9); the disease control rate of 30∼80% group was 5.6% (1/18) and the >80% group was 12.5% (1/8) (P = 0.038). In summary, our study showed that PNA-PCR method could easily detect the percentage of KRAS mutation in tumor cells and colorectal cancer patients with low abundance of KRAS mutation might benefit from EGFR antibody therapy. Epidermal growth factor receptor (EGFR) monoclonal antibody was approved for treatment of metastatic colorectal cancer patients without KRAS mutations. KRAS mutations are described to occur in approximately 40% of colorectal cancer and most of them (90%) occur in codon 12 and 13 However, recent studies showed that KRAS G13D mutation and codon 12 mutations are actually not created equal in predicting clinical outcomes of anti-EGFR therapy in metastatic colorectal cancer (mCRC) patients Since tumor had great heterogeneity, different tumor tissues may also have variable abundance of KRAS mutant tumor cells. Since every screening method had its detection sensitivity, when the tumor KRAS mutation’s proportion reduced to a certain extent, this tumor sample might be recognized as KRAS wild type. As more and more highly sensitive screening methods are established, more tumor specimens will be classified as KRAS mutant ones In our former study, we established a PNA-PCR (peptide nucleic acids-PCR) method which could suppress the amplification of KRAS wild type DNA. In this study, we first modified this PNA-PCR method to make sure that it could totally suppress amplification of KRAS wild-type DNA and confirmed its suppression ability on 47 tumor samples bearing KRAS mutations. Then we quantified and calculated the proportion of KRAS mutant DNA in tumor tissues and found that the proportion varied a lot. Finally, we compared the relationship between KRAS mutation abundance and the efficiency of cetuximab in another 35 metastatic colorectal cancer patients.PNA-PCR method was established before in our laboratory Colon carcinoma cell lines SW480 and SW116  were used in this study. Cell line SW480 contains a homozygous KRAS codon 12 mutation (GGT→GTT) and SW116 harbors wild-type KRAS gene. A total of 47 colorectal cancer patients’ FFPE specimens whose KRAS status was proved to be mutant on either KRAS codon 12 or codon 13 were obtained from the Drum Tower Hospital from November 2008 to December 2010. Another 35 colorectal cancer patients with KRAS mutation were collected from Jiangsu Cancer Hospital from 2006 to 2010. Different from patients above, all of these 35 patients received cetuximab treatment. Informed written consent was obtained from all patients before treatment started. All treatment decisions were made by the treating physicians prior to design of the study. The study was approved by the institutional ethics committee of hospitals  before this study was conducted.After manual macrodissection of FFPE tissues, the hematoxylin and eosin-stained sections of FFPE tissue were reviewed by three experienced pathologists to evaluate the abundance of tumor cells. The detailed evaluation method has been described before 5′-CCTACGCCACCAGCTCC-3′. The forward primer sequence was 5′-GCCTGCTGAAAATGACTGAATATAA-3′ and the reverse primer was 5′-biotin-CGTCAAGGCACTCTTGCCTAC-3′. Thermocycling was performed in an Mx3000P (Stratagene) real-time PCR instruction and the cycling conditions were as follows:98°C for 30 s and then 40 cycles of 98°C for 10 s, 72°C for 10 s, 62°C for 20 s and 72°C for 20 s. Pyrosequencing was performed in Pyrosequencing PSQ96 HS System (Biotage AB). The sequence of pyrosequencing primer was 5′-TGTGGTAGTTGGAGCT-3′. Nucleotide dispensation order was cyclic TACG from 5′ to 3′.PNA-PCR and pyrosequencing conditions have been described previously except for PCR master mix 2 . There were 28 patients who received cetuximab alone. There were 4 patients who received 5-Fu treatment plus cetuximab treatment after failure of 5-Fu therapy. Another 3 patients received irinotecan, 5-Fu and cetuximab therapy after disease progress of irinotecan plus 5-Fu therapy.We retrospectively analyzed 35 patients with histologically confirmed mCRC with KRAS mutation from 2006 to 2010. All tumors were colorectal adenocarcinomas. Patients gave informed written consent and were treated with cetuximab or ceruximab-based regimens. Cetuximab was administered as a single agent or in combination with chemotherapy-based regimens with the same dose until disease progression. Cetuximab was administrated at a dose of 250 mg/mThe clinical response was assessed every 2 months by computer tomography (CT) scan of the chest and abdomen and/or magnetic response scan (MR). The Response Evaluation Criteria in Solid Tumor (RECIST) version 1.0 were adopted for clinical evaluation. According to RECIST version 1.0, complete response (CR) was defined as disappearance of all target lesions; partial response (PR) was at least a 30% decrease in the sum of the longest diameters (SLD) of target lesions taking as reference the baseline SLD; progressive disease (PD) was at least a 20% increase in the SLD of target lesions, taking as reference the smallest SLD recorded since the treatment started; stable disease (SD) was neither sufficient decrease in SLD to qualify for PR nor sufficient increase in SLD to qualify for PD. Two oncologists and radiologists verified the clinical response for all patients in a blinded manner.Patients with CR, PR and SD were defined as patients with disease control and the diseased control rate was calculated as the number of disease control patient/the number of all patients. Chi-square test was carried out to compare the disease control rate of different groups in the 35 colorectal patients. The Chi-square was carried out by SPSS 16.0. A p value of <0.05 was considered statistically significant.We found that when we added 100 ng KRAS wild-type DNA in the PNA-PCR assay, the PNA could suppress the amplification of wild-type DNA. However, this suppression was not complete and stable after repeated tests . HoweverIn order to make sure the stability of the assay, we decreased the amount of wild-type DNA to 10 ng added in the assay and found that PNA could completely and stably suppress the amplification of wild-type DNA even in the absence of KRAS mutant DNA . Therefore, in the following experiment, we controlled the DNA added in the assay no more than 10 ng.A total of 47 colorectal cancer patients were confirmed to carry KRAS mutation by COLD-PCR/Sanger sequencing Before detecting the percentage of mutant DNA of tumor tissue, we analyzed the standard curve of the PNA-PCR assay and found the regression line was linear  in the range of 0.02 to 10 ng of KRAS mutant DNA , which mNo more than 10 ng DNA from FFPE tissue (2 ul) was added to PNA-PCR assay and regular PCR assay (without PNA) respectively . One sample’s total DNA and KRAS mutant DNA could be read by standard curve. The DNA amount in regular PCR assay was total DNA as all kinds of DNA could be equally amplified and the DNA amount in PNA-PCR assay was KRAS mutant DNA as the wild-type one didn’t amplify in this assay. The percentage of KRAS mutant DNA was calculated as amount of KRAS mutant DNA/amount of total DNA. The percentage of KRAS mutant DNA in tumor cells was calculated as percentage of KRAS mutant DNA in total DNA/percentage of tumor cells in tumor tissue. The percentage of mutant DNA in tumor cells varied from 10.8% to 98.3% . In totaPatient’s characteristics and percentage of KRAS mutation in tumor cells have been listed in The present study proved that PNA-PCR method could quantify and calculate the KRAS mutation’s abundance of tumor cells. As far as we know, we firstly showed that low abundance of KRAS mutation (<30%) might also benefit from anti-EGFR treatment in metastatic colorectal cancer patients. Since previous studies only focused on whether the mutation was positive, our study revealed a new research concept of EGFR antibody therapy.In this study, there were 7 patients treated by both cetuximab and chemotherapy. However, all these 7 patients received cetuximab after failure of original chemotherapy. Therefore, we tended to believe that patients’ response to therapy mainly contributed to cetuximab. Although there were studies proved that patients with KRAS G13D mutation showed a strong trend to a more favorable outcome comparing to codon 12 mutations, we failed to observe this in our study potentially because of the limited number patients of this study.Our results indicated that the percentage of KRAS mutant DNA in tumor cells varied from 10.8% to 98.3% and this distribution was continuous. As we expected, patients bearing low abundance (<30%) of KRAS mutation had higher disease control rate to cetuximab than other groups . If we excluded a disease control patient who carried a G13D mutation in >80% group, the trend that low abundance had higher disease control rate was more obvious.Although direct Sanger sequencing was regarded as a classic method for screening KRAS mutations, more and more high sensitivity methods such as COLD-PCR, ARMS, mutant-enriched PCR, competitive amplification of differentially melting amplicons (CADMA) Why did tumor with low abundance of KRAS mutation tend to response to EGFR antibody therapy? One potential explanation was that tumor cells had great heterogeneity. When the KRAS mutant tumor cells were minority, most of KRAS wild-type tumor cells could also be killed by EGFR antibody treatment and in this process cancer patients could show a relatively long time of stable disease or even partial response. However, as therapy continues, more and more KRAS wild-type tumor are wiped out, the abundance of KRAS mutation becomes higher and patients tend to have a progression disease and become resistant to EGFR antibody therapy.Nature found that 60% of patients who developed resistance to EGFR antibody treatment showed acquisition of secondary KRAS mutations These could also explain why EGFR antibody treatment is initially effective to most KRAS wild-type cancer patients and then losts its efficiency as therapy continues. A recent article published in More importantly, Misale et al also found that KRAS mutant alleles could be detected in the blood of anti-EGFR treatment patients as early as 10 months before radiographic documentation of disease progression Although some researchers had paid attentions to distinguish low and high abundance of EGFR mutation recently In summary, our study demonstrated that PNA-PCR method could easily detect the percentage of KRAS mutation in tumor cells. Colorectal cancer patients with low abundance of KRAS mutation might benefit from EGFR antibody therapy and further research is needed on a larger number patients.


PBIF is typically validated by comparing its quantification results with those obtained via arterial sampling. However, for PBIF to be employed in actual clinical research studies, its ability to faithfully capture the whole spectrum of results must be assessed. The present study validated a PBIF for [18F]FMPEP-d2, and then to quantify CB1 receptors in alcoholic patients (n = 18) and chronic daily cannabis smokers (n = 29). Both groups were scanned at baseline and after 2–4 weeks of monitored drug abstinence.The PBIF was first created and validated with data from 42 healthy volunteers. This PBIF was used to assess the retest variability of [VT) was 13.3±3.8 mL/cm3 for full sampling and 13.2±3.8 mL/cm3 for PBIF; R2 = 0.8765, p<0.0001) and test-retest results were comparable to those obtained with full sampling . PBIF accurately replicated the alcoholism study, showing a widespread ∼20% reduction of CB1 receptors in alcoholic subjects, without significant change after abstinence. However, a small PBIF-VT bias of −9% was unexpectedly observed in cannabis smokers. This bias led to substantial errors, including a VT decrease in regions that had shown no downregulation in the full input function. Simulated data showed that the original findings could only have been replicated with a PBIF bias between −6% and +4%.PBIF yielded accurate results in the 42 healthy subjects (average Logan-distribution volume (Despite being initially well validated in healthy subjects, PBIF may misrepresent clinical protocol results and be a source of variability between different studies and institutions. Kinetic modeling for positron emission tomography (PET) studies often requires that tracer radioactivity concentration be measured in arterial blood. Different approaches have been tried to avoid arterial cannulation, including image-derived input function (IDIF) and population-based input function (PBIF). IDIF, which theoretically allows estimation of an individualized, non-invasive input function, measures blood tracer concentration directly from dynamic images using an anatomical blood pool, such as the heart. However, in practice, IDIF is plagued by many shortcomings. For instance, limited spatial and temporal resolution of PET cameras makes reliable estimation of radioactivity concentration in the vessels and its rapid variations over time difficult; in addition, PET cameras cannot distinguish the parent compound from its radiometabolites PBIF modeling is based on the individual scaling of a tracer-specific input function of standard shape, and may be a more reliable alternative than IDIF. PBIF is not affected by problems linked to image quality and resolution, and radiometabolite correction can be inherently taken into account by using an average time-activity curve of parent concentrations. Moreover, because PBIF is derived from averaged values over a population, it generally shows little or no systematic error, as estimation errors of individual input functions would be normally distributed around the mean. While this may pose a problem in personalized diagnostic settings, research studies typically compare population means; thus, a larger standard deviation may be acceptable if properly accounted for.18F]-FDG Historically, PBIF was validated primarily for [18F]FMPEP-d2, a radioligand targeting cannabinoid CB1 receptors 18F]FMPEP-d2 concentrations can be accurately measured in plasma, and this allows accurate estimation of brain distribution volume (VT) 18F]FMPEP-d2VT values in healthy volunteers 1 receptors in the brain of alcoholic subjects Our laboratory developed [1 receptors were re-analyzed. The first study (retest study) involved 8 healthy subjects (5 men and 3 women) who underwent a test-retest scan 1 receptors in 18 male patients with alcohol dependence 1 receptors were imaged with PET and [18F]FMPEP-d2 at two time points: within 1 week of admission, and again after 2–4 weeks of abstinence. The third study (cannabis study) assessed CB1 receptors alteration in 30 males who were daily chronic cannabis smokers Data from three previous publications involving imaging of cannabinoid CBRadioactivity was measured in brain with an Advance PET camera  over 120 minutes. The input function was measured from radial artery plasma sampling. Arterial samples were drawn at 15 seconds intervals until 2 minutes, and then at increasingly longer intervals until the end of the scan, as previously described 18F]FMPEP-d2 input functions from all healthy subjects in our database were used. This comprised all healthy subjects in the three previous publications described above To generate the PBIF, FMPEP-d2 was found in cannabis smokers compared with healthy subjects . Compared to the original paper which included 30 cannabis smokers VT was about 20% lower in neocortical and limbic regions, but not in other brain regions  VT increased specifically in those brain regions that had shown decreased VT at baseline .The Logan model with full arterial input function obtained results similar to those found with 2TCM VT obtained with PBIF showed however a small bias of about −9% as compared to the Logan-VT obtained with the full input function  , and the group×region interaction was statistically highly significant   showed no physiological change between baseline and abstinence conditions.The Logan-<0.0001) . Because0000001) . Howevere matter . After aVT values, we created simulated sets of VT values whose means equal the target bias and the coefficient of variation is constant and equal to that of the real PBIF-VT values. The simulated data showed that significant deviations from the original findings of the study appeared with a bias lower than −6% or higher than +4%. Negative bias resulted in false positive findings in a number of brain regions. With a −6% bias, basal ganglia  appeared to be significantly downregulated, a finding that is inconsistent not only with our previous kinetic modeling study 1 receptors to chronic agonist-induced downregulation VT bias would have occurred in the other direction (i.e. +9%), the decrease would not have been statistically significant in any of the individual brain regions ; furthermore, no significant recovery of receptor downregulation after abstinence would have been observed .Because the bias of −9% was sufficient to cause substantial errors in the interpretation of the regional data from the cannabis study, we created datasets with different degrees of simulated bias (1 percent unit increments from −8% to +9%) to find the tolerable range of bias that would allow the exact replication of the results. In practice, starting from the actual PBIF-This study assessed whether PBIF can reliably replicate actual clinical protocols by comparing PBIF results to those obtained with a full input function.VT is derived by combining individual rate constants, which are sensitive to the shape of the input function. PBIF cannot accurately reproduce the shape of the individual input functions, especially during the early rapid phase. In contrast, the Logan graphical plot relies on the AUC of the input function Before analyzing PBIF data, we first replicated the previous studies using a Logan plot and the full arterial input function. This was necessary to have data that were directly comparable to those acquired using the Logan plot and the PBIF. In fact, compartmental modeling is not well suited to PBIF, because 18F]FMPEP-d2 gave reliable results. Moreover, the PBIF obtained from healthy subjects also closely replicated results from the alcohol study, showing a widespread decrease in VT in patients with alcohol dependence, both in terms of magnitude and statistical significance of change. After 2–4 weeks of abstinence, kinetic modeling with both full input and PBIF showed a similar persistent downregulation of CB1 receptors.In a large number of healthy subjects, both at baseline and in a test-retest setting, PBIF for -DOPA PBIF still correctly discriminated between healthy subjects and patients with Parkinson’s disease, it predicted quantitative severity ratings less accurately. Striatal Ki correlated significantly with the Unified Parkinson’s Disease Rating Score using the reference input function, but this correlation was lost when PBIF was employed.A 1994 study by Takikawa and colleagues provides a rare example where the performance of PBIF was tested against the full input in both healthy subjects and patients, and results were correlated with clinical findings In summary, care should be taken when using alternative techniques to measure input function. Despite initially good validation in healthy subjects, errors may unexpectedly arise in actual clinical protocols. These errors, in turn, may lead to a misinterpretation of results and be a source of variability between different studies and institutions. Indeed, these erroneous results may have important consequences for understanding basic pathophysiology or pharmacological effectiveness of drugs. Discrepant results are unfortunately not rare in molecular imaging studies Figure S1Scatter plots of 2TCM/Logan with full input, 2TCM/Logan with PBIF and Logan with full input/Logan with PBIF. Values for the test scans are reported in the left column and those of the retest scans in right column. For each one of the test-retest subjects, a single VT value (whole-brain region) has been used. A strong correlation exists between all datasets.(EPS)Click here for additional data file.Table S1Correlation coefficients for the area-under-the-curve of the plasma time-activity curve (AUC) using the measured radioligand concentrations.(DOCX)Click here for additional data file.


Fatty acids (FA) play an integral role in brain function and alterations have been implicated in a variety of complex neurological disorders. Several recent genomic studies have highlighted genetic variability in the fatty acid desaturase (FADS1/2/3) gene cluster as an important contributor to FA alterations in serum lipids as well as measures of FA desaturase index estimated by ratios of relevant FAs. The contribution to alterations of FAs within the brain by local synthesis is still a matter of debate. Thus, the impact of genetic variants in FADS genes on gene expression and brain FA levels is an important avenue to investigate.Analyses were performed on brain tissue from prefrontal cortex Brodmann area 47 (BA47) of 61 male subjects of French Canadian ancestry ranging in age from young adulthood to middle age (18–58 years old), with the exception of one teenager (15 years old). Haplotype tagging SNPs were selected using the publicly available HapMap genotyping dataset in conjunction with Haploview. DNA sequencing was performed by the Sanger method and gene expression was measured by quantitative real-time PCR. FAs in brain tissue were analysed by gas chromatography. Variants in the FADS1 gene region were sequenced and analyzed for their influence on both FADS gene expression and FAs in brain tissue.Our results suggest an association of the minor haplotype with alteration in estimated fatty acid desaturase activity. Analysis of the impact of DNA variants on expression and alternative transcripts of FADS1 and FADS2, however, showed no differences. Furthermore, there was a significant interaction between haplotype and age on certain brain FA levels.This study suggests that genetic variability in the FADS genes cluster, previously shown to be implicated in alterations in peripheral FA levels, may also affect FA composition in brain tissue, but not likely by local synthesis. To what extent the adult human brain relies on transport from peripheral circulation via receptor mediated uptake, passive diffusion, or local synthesis of the various n6 and n3 polyunsaturated fatty acids (FA) under physiological or pathological conditions is still a matter of some debate. Highly unsaturated FA, such as the major n6-FA arachidonic acid (AA) and major n3-FA docosahexanoic acid (DHA) are synthesised from their respective shorter chain FA linoleic acid (LA) and α-linolenic acid (ALA) through several precursors by a series of carbon chain elongation and desaturation steps, followed by a final β-oxidation step for DHA  gene cluster as having an impact on unsaturated FA composition at peripheral locations, such as in serum, plasma, and erythrocyte membranes. Determinants of FA levels in the periphery are likely a consequence of several interacting factors including intake and gene expression levels. As of yet, it is unknown whether genetic sequence variation in FADS genes contribute to alterations in gene expression of the desaturase enzymes in relation to alterations in FA levels in humans, or importantly, in human brain tissue. Integrated measures of genetic variant, gene expression, enzyme activity, and total FA levels are elemental to elucidate contributing factors to brain lipid levels. Thus, the objective of this study was to examine the relationship between genetic variation within FADS genes, the expression of FADS genes and, using relevant desaturase FA product/precursor ratios as a proxy of desaturation index, estimated FADS activity.www.douglas.qc.ca/suicide). Approval for this study was granted by the Douglas Hospital Institutional Review Board in accordance with the 1964 Declaration of Helsinki, and written informed consent was obtained from each participating family. Cause of death was ascertained by the Quebec Coroner’s Office in Montreal. The sample consisted of a mix of subjects who died by natural or accidental causes  and subjects who died by suicide with  or without a history of MDD . All deaths were sudden and without prolonged agonal state, and none of the samples analyzed in this study came from individuals with a neuropathological illness. BA 47 was chosen for this study given importance of the prefrontal cortex in brain function and cognition, that LC-FA are found in high concentration in prefrontal cortex grey matter, and the previous associations of FADS variants with cognitive function. All subjects were males of French Canadian ancestry ranging in age from young adulthood to middle age (18–58 years old), with the exception of one teenager (15 years old).Brain tissue from Brodmann area 47 (BA47) was obtained from the Quebec Suicide Brain Bank , producing 3 distinct bands of 526 bp (T/T), 371+155 bp (C/T), 526+371+155 bp (C/C) (Haplotype tagging SNP (htSNPs) were selected using publicly available HapMap genotyping data set from Utah residents with ancestry from Northern and Western Europe  in conjunction with Haploview (version 4.2). bp (C/C) . The resRNA was extracted from brain using the Qiagen RNeasy lipid kit including DNase I incubation to remove contaminating genomic sequences. RNA quality was assessed by bioanalyser and RNA integrity number greater than 5 were deemed satisfactory. To quantify expression of refseq mRNA and to investigate presence of FADS AT expression, primers were designed using Primer3 to produce an approximately 200 bp amplicon for analysis by SYBR green quantitative real time PCR ABI 7900 Fast HT for different transcripts of FADS1 and FADS2  were analysed as previously described. The variables analysed included relationships between measures of desaturase enzyme activity (AA/DGLA: D5D and DGLA/LA: D6D indices), quantities of n6 and n3 fatty acids , gene expression of FADS1uc010rlm.1, FADS1uc001nsh.2, FADS2uc001nsl.1/uc001nsk.2, FADS2uc001nsk.2, and genetic variation in the FADS1 gene and the 2 reconstructed haplotypes (GCG haplotype was excluded as it only contained 2 subjects). Groups were not significantly different for post-mortem interval (PMI), RNA integrity number (RIN), or brain tissue pH  and ther2 = 0.432, Spearman rho = 0.848 p = 7.5×10–15, The haplotype and SNP frequencies were similar to those obtained from the HapMap CEU dataset and did not deviate significantly from Hardy-Weinberg equilibrium  and 2. FTo rule out compensatory up-regulation in known alternative transcript expression between haplotypes, which has been recently implicated in FADS2 function in primates For SNP analysis, as shown with rs174555, the alterations in D6D and D5D indices were observed in an allele dosage dependent manner, though after multiple testing correction, only homozygous genotypes were significantly different  nor were there differences in analytical measures by psychiatric disorder (data not shown). Although, perhaps with increased sample size an association might be more readily detected. As age was found to be correlated with several measures including D6D , LA  and AA , D5D index , LA , DGLA , and AA . No significant interaction effects were seen for age on n3 FA measures or FADS gene expression (data not shown).There was no association of psychiatric diagnosis of subjects with or without MDD and haplotype  was associated with increased expression of FADS1. Interestingly, in this study, there were no alterations in measures of gene expression for any of the FADS transcripts quantified, nor was there any observable relationship between desaturase gene expression and desaturase index. Only two previous studies have assessed the relationship between FADS gene expression and FA levels in human brain tissue. In one study, Liu et al. investigated the relationship between FADS2 expression and index of FADS2 activity (represented by AA/LA ratio) in the orbitofrontal cortex in a sample of 20 schizophrenics and 20 controls. While there was no relationship between FADS2 expression for either AA level, or for DGLA/LA ratio, these authors reported a significant correlation between expression and AA/LA ratio in controls. McNamara and colleagues also investigated the relationship between brain FA content and FADS1 and FADS2 expression during aging in the orbitofrontal cortex. In a sample of 30 subjects ranging from 29–80 years of age, they detected a positive correlation between FADS1 expression and AA/DGLA ratio, as well as between FADS2 and AA/LA ratio. While there was no relationship between age and FADS expression, there was a significant positive correlation between age and LA level, and a significant negative correlation between age and AA level. The lack of difference in expression of FADS gene transcripts does not preclude small-scale fine-tuning of brain FA or transport of endogenously synthesised FA from other brain regions. However, the relatively large effect of genotype and the similarity to associations reported in human peripheral circulation suggest that the important variables contributing to prefrontal cortex brain FA levels might more largely depend on uptake from peripheral circulation, due to liver synthesis levels, with likely age-related differences in brain receptor-mediated uptake. Furthermore, it is not possible to dismiss a change in conversion of FA, especially AA, into downstream eicosanoids, such as prostaglandins, which are known to be biologically active inflammatory mediators and have important implications in brain function. Notably, expression of prostaglandin synthase genes have recently been identified to vary with age and psychiatric disorder in post-mortem human prefrontal cortex and this could be of interest for follow up investigations. in vivo. A limitation of this study is the subject sample is composed only of males, thus no potential gender differences could be ascertained. Also, the fatty acids analysed were from total lipids and potential differences in lipid classes such as phospholipid profiles cannot be differentiated. An additional limitation is the necessity of extrapolation of metabolic states from post mortem tissue due to the lack of peripheral FA measures with the relatively small sample size for a SNP study. However, to date this is the largest sample size to combine gene sequence variants and gene expression measures in relation to brain FA levels. Of special importance, the group of Rapoport et al. have recently published a method using positron emission tomography to evaluate AA and DHA metabolism, suggesting the utility of employing this technique to examine how human brain AA/DHA signalling and metabolism are influenced by diet, aging, disease and genetics, which raises exciting possibilities to clarify many of the questions unresolved in relation to adult human brain FA function In this study, the minor haplotype variant of the FADS1 gene was associated with an increase in DGLA level in human brain tissue. DGLA has been suggested to be an anti-inflammatory FA. The mechanisms governing brain FA composition are vastly complex and in adult humans much remains to be resolved. This study suggests that genetic variability in the FADS genes cluster may also affect FA composition in brain tissue in a manner similar to changes previously shown in peripheral FA levels. This study also proposes that the lack of change in gene expression may reflect the dependence of uptake of preformed FA preferentially over local chain desaturation of precursor FA.Figure S1Haplotype block structure of FADS1 and FADS2 gene region. According to CEU HapMap dataset  spanning an 80 kb region including the intergenic region between FADS1 and 2.(TIF)Click here for additional data file.Figure S2Example of BglI restriction enzyme digest. Validation of rs174555 amplicon with BglI digestion produces distinct fragments of 526, 371, and 155 bp. Lane 1∶25 bp ladder lane 2 : C/C 371+155 bp lane 3 : C/T 526+371+155 bp lane 4 : T/T 526 bp.(TIF)Click here for additional data file.Figure S3Correlation between FADS1 expression values normalised to GAPDH or β-actin. Expression of FADS1 is comparable irrespective of endogenous control or chemistry used. β-actin was also evaluated using SYBR green chemistry but was determined to be less reliable than GAPDH. .(TIF)Click here for additional data file.Figure S4Desaturase activity index by SNP genotype. FADS desaturase activity is similar across SNPs tested. Following correction for multiple testing, rs174546 and rs174555 homozygous minor were significantly different compared to homozygous major (See (TIF)Click here for additional data file.Figure S5FADS expression by SNP genotype. FADS expression is similar across all SNPs tested. No differences were observed in expression levels (See (TIF)Click here for additional data file.Table S1Sample sizes after outlier removal by genotype for measures investigated in this study.(XLSX)Click here for additional data file.


Salmo salar) strains and their wild progenitor populations in an effort to detect potential signals of domestication selection by typing of 261 SNPs and 70 microsatellite loci. By combining information from four different neutrality tests, in total ten genomic regions showed signs of directional selection based on multiple sources of evidence. Most of the identified candidate regions were rather small ranging from zero to a few centimorgans (cM) in the female Atlantic salmon linkage map. We also evaluated how adaptation from standing variation affects adjacent SNP and microsatellite variation along the chromosomes and, by using forward simulations with strong selection, we were able to generate genetic differentiation patterns comparable to the observed data. This study highlights the significance of standing genetic variation during the early stages of adaptation and represents a useful step towards identifying functional variants involved in domestication of Atlantic salmon.Domesticated animals provide a unique opportunity to identify genomic targets of artificial selection to the captive environment. Here, we screened three independent domesticated/captive Atlantic salmon ( Over the last decade, advances in genomic technologies together with developments in methods of statistical analyses have resulted in considerable progress in the systematic detection of genomic regions influenced by artificial selection –5. TheseSalmo salar L.) represents a useful model for studying the genetic basis of recent, ongoing domestication since reared salmon strains have experienced intense artificial selection for only a short period of time (5–12 generations), and there are still many wild populations available for comparative purposes, including progenitor populations. The traits that have been targets of selective breeding in reared Atlantic salmon strains include higher growth rate, delayed sexual maturity, bacterial resistance, flesh colour, and fat content. The selection response of many of these traits has been as high as 10% per generation [Atlantic salmon , Ume/Vindelälven Rivers , and the Saint John River , in an attempt to identify genomic regions affected by domestication/captive breeding. A short description of the history of each reared strain and sampling details are provided below.Artificial rearing of juvenile salmon for ranching from the Burrishoole river began in 1960 and recruitment from the wild population continued until 1964. Apart from the addition of a small number of wild fish in the reared broodstock between 1970 and 1975, the breeding strain has been effectively closed since that time; the hatchery born fish were distinguished from their wild counterparts by the absence of a previously-clipped adipose fin. Assuming a generation time of 5 years for the wild fish, wild and reared (ranched) Burrishoole salmon have experienced different selection pressures for approximately 8 generations during the early freshwater phase (from fertilization to smoltification). Today, the Burrishoole-ranched strain is composed of three almost distinct coexisting cohorts with little overlap between year classes . BurrishThe wild River Umeälven salmon were extirpated by power plant dam construction in the early 1950s but River Vindelälven (a tributary of Umeälven) continued to support wild salmon. The present hatchery stock of River Umeälven originates from the wild Vindelälven population and since 1971, all hatchery (ranched) smolts have had their adipose fin removed. Since 1974 all salmon without adipose fins (hatchery fish) or with intact adipose fins  have been recorded at the fish trap below the Norrfors hydroelectric dam and only salmon of wild origin are released above the dam to continue their upstream spawning migration to the Vindelälven. As a result, wild and captive (ranched) Ume/Vindelälven salmon have experienced different selection pressures for approximately 5-6 generations during the early freshwater phase (from fertilization until smoltification) assuming a generation time of 5-6 years. River Ume/Vindelälven wild samples consisted of 16 returning individuals in 2006, while the samples from the reared (ranched) strain were obtained in 2009 (16 1+ old juveniles).The Saint John reared strain used for farming was founded in 1990 from wild Saint John River salmon, and in contrast to IRL and SWE populations, by 2006 it has experienced four generations of selection for higher growth and reduced early maturation . As a reIn total, 320 SNP developed by Moen et al.  were genμL volumes including 10–100 ng of genomic DNA and 0.033–0.3 μM of locus specific primers, the forward primer being labelled with one of four fluorescent dyes , and 1 × QIAGEN multiplex PCR master mix. The thermal cycling conditions used were as follows: 15 min initial activation step at 95°C followed by 35 cycles of denaturation at 94°C for 30 s, annealing at 55–60°C for 90 s and extension at 72°C for 60 s and ending with a final extension at 60°C for 10–30 min. Amplifications were performed using an Applied Biosystems 2720, a PTC-100, or a PTC-200 (Bio-Rad) thermal cycler. The PCR products from separate multiplex reactions were pooled (1–2.5 μL) and made up to the final volume of 120 μL of distilled water, mixed with GS600LIZ size standard (Applied Biosystems), and formamide for electrophoresis on an ABI 3130 × l automated sequencer. Detailed multiplex amplification information, including specific primer concentrations, annealing temperatures, and post-PCR pooling procedures, are available on request.A total of 70 variable number tandem repeat markers were also included in this study. They included two MHC linked mini- and microsatellite loci, 21 EST-derived microsatellite loci , 36, andFST estimates [FST estimates between pairwise comparisons was tested by permutation of individuals between samples using FSTAT 2.9.3 [Diversity indices were estimated using the program FSTAT 2.9.3 . Deviatistimates . The sigAT 2.9.3 .FST for each locus in the sample, and coalescent simulations based on a symmetrical island model are used to generate data sets with the mean FST similar to the empirical distribution. To calculate approximate P values for each locus, 100,000 independent loci were generated and the simulated distribution of FST between two populations was then compared to the observed FST values, conditional on heterozygosity, to identify potential outliers as implemented in the software FDIST2. Sample sizes used to calculate FST from coalescent simulations were set to 16 individuals, corresponding to the empirical data. Two different tests aimed at detection of loci subject to directional selection during domestication/captive breeding were used. Both approaches rely on the rationale that directional selection increases genetic differentiation between populations and reduces variability at linked loci. However, because both of the tests are based on different assumptions, identification of outlier loci simultaneously with both approaches provides additional support for the candidate status of a particular locus . The firFST is modelled using a logistic regression model implementing a locus effect and a population effect, relaxing the assumption of symmetrical island model by allowing for population structure asymmetries. The estimation of the model parameters was automatically adjusted on the basis of short pilot runs (10 pilot runs with 5000 iterations each). We used a burn-in of 50,000 iterations and the total chain length of 500,000 iterations  to identify loci under selection. Altogether, three independent runs were performed for each wild and domesticated/captive population pair. Bayescan estimates the posterior probability that a locus is under selection by calculating a Bayes factor, which is given by the ratio of posterior model probabilities of two models , given the data. For example, a Bayes factor of two indicates that the data favor one model over the other at odds of two to one. According to Jeffreys' interpretation, Bayes factor between 3 and 10 (log10 = 0.5–1) is considered “substantial evidence” to favour one model over the other and corresponds to a posterior probability between 0.76–0.91. A Bayes factor between 10 and 32 (log10 = 1–1.5) is considered “strong evidence” of different statistical support for the two models and corresponds to a posterior probability between 0.91–0.97. However, this probability cannot be compared directly to the P value from FDIST2, since Bayescan explicitly takes all loci into account in the analyses. The second method to detect footprints of selection also identifies loci that exhibit extreme differentiation compared to the rest of the genome using the Bayesian likelihood method implemented via reversible jump Markov Chain Monte Carlo . Using tFST) or large differences in genetic diversity (lnRH) [FST and mean absolute lnRH for pairs of markers along specific chromosomes and by using permutations evaluated whether the empirical pattern differs from random expectations . We subsequently identified locus pairs that exhibited elevated differentiation (FST) or large differences in genetic diversity (lnRH), against the permutation-derived 95% significance threshold. Absolute lnRH was used as a parameter for quantifying the difference in genetic diversity (lnRH) between populations, as very short-term directional selection can either reduce or increase the genetic variation of a particular locus depending on the frequency of the allele linked to an advantageous mutation. For example, short-term directional selection initially increases the diversity when the positively selected (or linked) allele is at low frequency, while it reduces the variation when the positively selected (or linked) allele is at high frequency in the population. Loss of diversity measured as lnRH has been commonly used to identify outliers in microsatellite datasets but this statistic can also be applied to SNPs markers [As a complementary approach to the outlier tests described above, we evaluated whether there is a tendency for adjacent loci to exhibit high differentiation (y (lnRH)  between  markers  as lnRH  markers .q value to evaluate the proportion of putative outliers that are likely to be false positives ; FDRs  [P values derived from (i) coalescent simulations (FDIST2 test), (ii) from expected normal distributions (lnRH test), and (iii) from permutation tests aimed at detecting clustering of loci with extreme FST and lnRH values. A bootstrap method was used for estimating the overall proportion of true null hypotheses as a more conservative approach compared to the smoother method as suggested by Storey and Tibshirani [To control for the multiple testing problem that arises when large numbers of markers are tested against the neutral null hypothesis, we employed the false discovery rate (FDR) methodology  implemen values)  were calbshirani .de novo mutations, as it is more likely that initial adaptation to an artificial environment occurs from standing variation. As a result, selection on preexisting genetic variation is expected to lead to immediate evolutionary response, fixation of more alleles of small effect and importantly, generally weaker footprints of selection compared to strong selective sweeps [To evaluate whether the observed patterns of genetic variation were compatible with the effect of strong directional selection, we used an individual-based forward-time simulation environment, simuPOP 1.0.2 , to exple sweeps . FST from Ne = t/(2FST). We then constructed a simple single population split model applying the derived population genetic parameters for each population pair . We subsequently applied forward simulations using the empirical genotype data from wild population and genetic linkage map information to simulate the effect of selection along specific chromosomes on identified outlier loci. We first created an ancestral wild population by using empirical genotype data from the wild progenitor population  by multiplication of existing genotypes and subsequent random mating for three generations. After the split of the ancestral population, we simulated positive selection on the minor allele in a single candidate region per population pair. We assumed that the fitness of three genotypes AA, Aa, and aa in captive environment is 1, 0.7 and 0.4 , while there is no selection acting in the wild populations. Note that we are aware of only one-published single locus selection coefficient for Atlantic salmon  [FST estimator [FST was visualized by creating box plots using SPSS 14.0.Given that the time since foundation of captive/domesticated strains are known and assuming equal population sizes and complete isolation (drift only) after the split, we calculated the effective population size using the estimated onicida)  but seleonicida) –50. We sstimator , by sampU test, all P values < 0.001). Contrary to earlier population genetic studies on natural and farmed Atlantic salmon populations [P values > 0.05; P values < 0.05; θ, between reared strain/wild population pairs was rather low, ranging from ~0.01 in SWE and IRL to 0.039 in CAN but nevertheless, was highly significant . When comparing wild population and reared strain pairs across different type of markers, the mean genetic differentiation estimates were rather similar , indicating that both types of markers are generally affected by a similar kind of evolutionary forces across the genome. Hardy-Weinberg disequilibrium was detected in 35 of 1370 loci by population tests at the 1% significance level before correction for multiple tests (data not shown). Approximately 14 of them are expected to emerge simply because of the large number of tests performed. As expected, SNPs and microsatellites showed different levels of genetic variation  identified nine outlier loci  with substantial evidence (Bayes factor > 3 corresponding to log10(BF) > 0.5) of directional selection according to Jeffreys' interpretation [Altogether, eleven loci were identified as outliers in three wild-reared comparisons (three each in SWE and CAN and five in IRL) at the 99%  g FDIST2 . Those eretation   or alternatively, show large differences in genetic diversity (lnRH) between wild-reared population pairs. Altogether, seven adjacent locus pairs  exhibited evidence for clustering of markers  with high genetic differentiation (FST) along the chromosome . As expected, a considerable proportion of the loci that fall to the tails of the distribution are probably false positives, that is, they emerge because of the large number of tests performed  for the four previously-used neutrality tests: FDIST2, lnRH, clustering of adjacent loci with high erformed . As a reerformed . Among tWe also evaluated whether strong directional selection over a very short period of time from standing variation also affects adjacent genetic markers along the chromosome, using the empirical genotype data from wild population as a source for subsequent forward simulations. We selected three linkage groups/chromosomes that contained previously-identified outlier loci  with the closest adjacent marker 0 cM (CAN), 7.8 cM (IRL), and 33.6 cM (SWE) apart. Overall, strong selection on the minor allele resulted in high differentiation between wild population and reared strain pairs at selected markers, comparable with the empirical data . The hitIn recent years, there has been a considerably increased interest in searching for signatures of natural or artificial selection, both in model and nonmodel organisms –56. In tP < 0.012). Interestingly, the same two genes also showed significant gene expression differences between domesticated- and wild-rainbow trout (Oncorhynchus mykiss) [By combining information from four different neutrality tests, in total, ten genomic regions showed signs of directional selection based on multiple sources of evidence . When se mykiss) . These fWe found that several of our candidate regions overlap with Atlantic salmon QTLs identified for various ecologically and economically important traits in earlier studies. For example, linkage groups 6 (Chrom. 12), 7 (Chrom. 24), and 11 (Chrom. 3) have been shown to harbour QTLs for body weight , 59, conOncorhynchus mykiss) and brook charr , differentially expressed genes between reared strains and wild populations have been shown to belong primarily to similar biological functions such as energy metabolism of lipids and protein synthesis, but the specific genes involved in these biological functions were found to be different [Oncorhynchus kisutch). Our study provides little support for the hypothesis of independent parallel genetic changes at the DNA level in Atlantic salmon from different population pairs as none of the identified candidate regions overlapped in the three wild-population/reared strain pairs. This is in contrast with earlier studies at the gene expression level that have demonstrated the presence of parallel differences in transcription of genes between independent domesticated- and wild-Atlantic salmon . Howeverifferent , 65. Theifferent  who founifferent  who showvice versa; even if polymorphism exists in all strains, when the allele that is linked to the positively selected site is already at high frequency in a particular population, selection does not necessarily induce a strong increase in the level of genetic differentiation and reduction in diversity. It is also possible that several other factors contribute to the population-specific signatures of selection, such as (i) different selective regimes in farmed versus ranched strains, (ii) different selective regimes between separate ranched strains, or, (iii) allele frequency differences between populations/strains. In fact, it is possible that all of these factors contribute to the lack of overlap of outliers because (i) farmed strains experience strong intentional selection for growth, disease resistance, delayed maturity, and other commercially important traits while ranched strains experience inadvertent selection in captivity as well as natural selection at sea , 67;  in order to obtain more comprehensive understanding about molecular mechanisms of adaptation. Species with domesticated/captive strains are likely to remain popular models in this context, providing unique opportunities to identify molecular targets of artificial selection. In conclusion, our results together with other recent studies , 80, 81 Marker and genetic map information of studied SNP and microsatellite loci.Click here for additional data file.