Marker Allele Frequencies Research Articles

Detection of putative loci affecting milk yield in Turkish Awassi sheep using microsatellite markers.

On the basis of comparisons between bovine and ovine genome mapping information, the aim of the study was to analyze the genetic diversity of selected DNA microsatellites from the bovine genome and to investigate their correlation with the average daily milk yield in Awassi sheep. 18 informative microsatellite markers were selected from the significant QTL regions affecting milk yield identified in the bovine genome in previous studies. The selected microsatellite markers were then amplified by PCR as reciprocal amplifications on the genomic DNA of Awassi sheep, with standard daily milk yield records. Thus, in this study, 18 microsatellite markers associated with milk yield in the bovine genome were examined for both determination of genetic polymorphism within the flock and the effects of marker loci on average daily milk yield in Awassi sheep. Allele frequencies of markers were determined based on the results of fragment analysis. The analysis of variance showed that the 123bp allele at the marker locus BMS1341 on BTA2 significantly influenced the average daily milk yield of Ivesi sheep (P < 0.01). On the other hand, the BMS381 locus with a 115bp allele on BTA2, the MCM140 locus with a 185bp allele on BTA6, the BMS2721 locus with a 155bp allele, the BM1237 locus with 174 and 180bp alleles on BTA7, and finally, the BMS1967 locus with a 117bp allele, the BM4208 locus with 176 and 182bp alleles, and the INRA locus with a185 bp allele on BTA8 showed moderately significant effects on the average daily milk yield of Ivesi ewes (P < 0.05).

Designing and evaluating a cost‐effective single nucleotide polymorphism liquid array for Chinese native chickens

AbstractGenotyping plays an important role in breeding and population studies. Currently available genotyping technologies, including solid‐phase chips and sequencing, often have several limitations in their application to local chickens in China, including high costs, insufficient diversity, and poor universality. In the present study, we developed a chicken 5 K single nucleotide polymorphism (SNP) array suitable for breeding and genetic analysis using genotyping by targeted sequencing technology. The chip design was based on genomic data from 33 local breeds, and 5847 SNPs were selected for the final chip design. Among these SNPs, 3427 sites were associated with economic traits in broiler chickens. Our chip contained 25,000 high‐quality SNP markers captured from 5 K regions with highly efficient target site capture. Population analyses of the eight breeds showed high detection rates and minor allele frequencies for SNP markers on the array, enabling clear differentiation of different populations and families within populations. The genetic diversity trend obtained using the chip was consistent with the results obtained from microsatellite analyses. Additionally, the 5 K array was applied to a genome‐wide association study of broilers, resulting in the identification of several growth‐ and meat quality‐related loci. Therefore, the newly developed chip is efficient, cost‐effective, and well suited for application in local Chinese chickens, which will accelerate poultry breeding improvements and enhance conservation efforts.

Analytical screening of polymorphic variants of 20S proteasome genes when planning a study of pathogenetic effects of modification of NFKB1 post-translational processing

Aim. Formation of polymorphic variants panel of the proteasome genes 20S, potentially significant for the study as balance modifier factors of p105/p50 NFKB1.Materials and methods. Determination of genes that encode proteins of the multisubunit proteasome complex prospective for research purposes, was carried out on the basis of information retrieved from eLIBRARY and PubMed. The source of information for the formation of polymorphic variants panel of genes (SNP, single nucleotide polymorphism) was the Ensembl genomic browser, http://www.ensembl.org. The structure of genes is described by the NCBI (databases Gene, http:// www.ncbi.nlm.nih.gov/gene). The panel was filled with the minor allelic frequency in the population (MAF), the localization of SNP in the gene structure and the availability of data on the relationship with multifactorial diseases and other effects in mind. To calculate the genetic distances between populations, we used the methord of comparing the populations by frequencies of polymorphic marker alleles proposed by Ney, the obtained matrices are illustrated by the method of multidimensional scaling in space using Statistica v.8.0.Results. Discussion of the algorithm and results of analytical screening of polymorphic variants of 14 genes (PSMA1-PSMA7, PSMB1–PSMB7) encoding proteasome subunits 20S. The characteristics of the SNP panel are given, compiled with the selection criteria taken into account. According to the data on the frequencies of polymorphic gene variants, the features of global and European population gene pools (283 SNP), as well as samples from Russian populations (20 SNP) are analyzed. Based on the results of the analysis of information on the associations of selected SNPs with various diseases, a panel (42 SNPs) of 20S proteasome genes was formed, potentially significant for the study as factors modifying the p105/p50 NFKB1 balance.Conclusion. Annotation of the formed panel of SNP genes of the 20S proteasome with MAF&gt;0.1 indicates the potential role of polymorphism in the pathogenesis of diseases of various profiles. This may be of research interest to the formed panel in context of implementation of traditional approaches – the search for candidate genes based on the analysis of associations with diseases, as well as the analysis of the influence of SNP on the level of genetic expression, synthesis of gene products, NFKB1 processing and p105/p50 balance in silico and on model objects.

Аллельный полиморфизм генов, вовлеченных в продукцию IL-1β, и предрасположенность людей к развитию артериальной гипертензии

Background: The level of IL-1β in blood plasma is determined not only by pro-inflammatory stimuli, but also by allelic polymorphism of the IL1B and NLRP3 genes. Information on the associa-tion of allelic polymorphism of these genes with the risk of arterial hypertension (AH) is scarce and contradictory. The aim of the study: To assess the risk of developing hypertension in carriers of various allelic variants according to the polymorphic markers rs1143634 (c.3953C&gt;T), rs16944 (c.-511T&gt;C), rs1143627 (c.-31C&gt;T) of the IL1B gene and rs35829419 (c.2113C&gt;A) of the NLRP3 gene, as well as to study possible mechanisms for the inclusion of allelic polymorphism of these genes in the etiology and pathogenesis of AH. Materials and methods: 182 DNA samples from healthy people and 180 DNA samples from patients with hypertension (stages I-II) were used for genotyping rs1143634, rs16944, rs1143627 (PCR-RFLP analysis). 215 DNA samples from healthy individuals and 180 hypertensive patients were used to determine alleles and genotypes for rs35829419 of the NLRP3 gene (allele-specific PCR with TaqMan probes). Total RNA obtained from peripheral blood leukocytes (PBL) of 45 healthy people and 50 patients with AH (27 people taking metoprolol or bisoprolol for more than a year and 23 people without antihypertensive thera-py) for assessment of gene expression by real-time PCR was used. The content of pro-inflammatory proteins in the blood plasma of 40 healthy individuals was measured by ELISA. Results: Carriers of the TT genotype for the c.3953C&gt;T marker of the IL1B gene were found to have a 3-fold increased risk of AH (OR=3,239; 95% CI: 1,858-5,649). In healthy individuals with this genotype, the con-tent of IL-1β in blood plasma and the expression of the ICAM1 gene in PBL are higher than in het-erozygotes or homozygotes for the C allele (p=0,029 and p=0,004, respectively). Individuals with the TT genotype for the c.-31C&gt;T marker of the IL1B gene had a reduced risk of АН (OR=0,645; 95% CI: 0,481-0,866). IL1B gene expression and hsCRP levels were lower in healthy individuals with the T allele for rs1143627 (p=0,022, p=0,040, respectively). There were no differences in the distribution of allele and genotype frequencies for markers c.-511T&gt;C of the IL1B gene and c.2113C&gt;A of the NLRP3 gene in the studied groups. Conclusion: Polymorphic markers rs1143634 (c.3953C&gt;T) and rs1143627 (c.-31C&gt;T) of the IL1B gene are probably involved in the predisposi-tion of the inhabitants of Karelia to the development of arterial hypertension.

A comparison of marker-based estimators of inbreeding and inbreeding depression

BackgroundThe availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression (ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (FLH1 and FLH2), VanRaden (FVR1 and FVR2), Yang and colleagues (FYA1 and FYA2), marker homozygosity (FHOM), runs of homozygosity (FROH) and estimates based on pedigree (FPED) in comparison with estimates obtained from IBD measures (FIBD).ResultsIf the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with FIBD and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with FIBD is generally obtained by FLH1 and the best estimator of ΔID is FYA2. The estimators FVR2 and FLH2 have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with FIBD and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (FHOM) substantially overestimated ΔID. Estimates based on runs of homozygosity (FROH) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (FPED) show a lower correlation with FIBD than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations.ConclusionsWhen base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with FIBD and provide good estimates of ΔID. When base population allele frequencies are unknown, FLH1 is the marker frequency-based estimator that is most correlated with FIBD, and FYA2 provides the most accurate estimates of ΔID. Estimates from FROH are also very precise in most scenarios. The estimators FVR2 and FLH2 have the poorest performances.

Risk variants of obesity associated genes demonstrate BMI raising effect in a large cohort.

Obesity is highly polygenic disease where several genetic variants have been reportedly associated with obesity in different ethnicities of the world. In the current study, we identified the obesity risk or protective association and BMI raising effect of the minor allele of adiponectin, C1Q and collagen domain containing (ADIPOQ), cholesteryl ester transfer protein (CEPT), FTO alpha-ketoglutarate dependent dioxygenase (FTO), leptin (LEP), and leptin receptor (LEPR) genes in a large cohort stratified into four BMI-based body weight categories i.e., normal weight, lean, over-weight, and obese. Based on selected candidate genetic markers, the genotyping of all study subjects was performed by PCR assays, and genotypes and allele frequencies were calculated. The minor allele frequencies (MAFs) of all genetic markers were computed for total and BMI-based body weight categories and compared with MAFs of global and South Asian (SAS) populations. Genetic associations of variants with obesity risk were calculated and BMI raising effect per copy of the minor allele were estimated. The genetic variants with higher MAFs in obese BMI group were; rs2241766 (G = 0.43), rs17817449 (G = 0.54), rs9939609 (A = 0.51), rs1421085 (C = 0.53), rs1558902 (A = 0.63), and rs1137101 (G = 0.64) respectively. All these variants were significantly associated with obesity (OR = 1.03-4.42) and showed a high BMI raising effect (β = 0.239-0.31 Kg/m2) per copy of the risk allele. In contrast, the MAFs of three variants were higher in lean-normal BMI groups; rs3764261 A = 0.38, rs9941349 T = 0.43, and rs7799039 G = 0.40-0.43). These variants showed obesity protective associations (OR = 0.68-0.76), and a BMI lowering effect per copy of the protective allele (β = -0.103-0.155 Kg/m2). The rs3764261 variant also showed significant and positive association with lean body mass (OR = 2.38, CI = 1.30-4.34). Overall, we report six genetic variants of ADIPOQ, FTO and LEPR genes as obesity-risk markers and a CETP gene variant as lean mass/obesity protective marker in studied Pakistani cohort.

Continuous Mapping Identifies Loci Associated With Weevil Resistance [Cosmopolites sordidus (Germar)] in a Triploid Banana Population.

The first step toward marker-assisted selection is linking the phenotypes to molecular markers through quantitative trait loci (QTL) analysis. While the process is straightforward in self-pollinating diploid (2x) species, QTL analysis in polyploids requires unconventional methods. In this study, we have identified markers associated with weevil Cosmopolites sordidus (Germar) resistance in bananas using 138 triploid (2n = 3x) hybrids derived from a cross between a tetraploid “Monyet” (2n = 4x) and a 2x “Kokopo” (2n = 2x) banana genotypes. The population was genotyped by Diversity Arrays Technology Sequencing (DArTSeq), resulting in 18,009 polymorphic single nucleotide polymorphisms (SNPs) between the two parents. Marker–trait association was carried out by continuous mapping where the adjusted trait means for the corm peripheral damage (PD) and total cross-section damage (TXD), both on the logit scale, were regressed on the marker allele frequencies. Forty-four SNPs that were associated with corm PD were identified on the chromosomes 5, 6, and 8, with 41 of them located on chromosome 6 and segregated in “Kokopo.” Eleven SNPs associated with corm total TXD were identified on chromosome 6 and segregated in “Monyet.” The additive effect of replacing one reference allele with the alternative allele was determined at each marker position. The PD QTL was confirmed using conventional QTL linkage analysis in the simplex markers segregating in “Kokopo” (AAAA × RA). We also identified 43 putative genes in the vicinity of the markers significantly associated with the two traits. The identified loci associated with resistance to weevil damage will be used in the efforts of developing molecular tools for marker-assisted breeding in bananas.

Genomic prediction in a numerically small breed population using prioritized genetic markers from whole‐genome sequence data

AbstractThe objective of this study was to investigate the accuracy of genomic prediction of body weight and eating quality traits in a numerically small sheep population (Dorper sheep). Prediction was based on a large multi‐breed/admixed reference population and using (a) 50k or 500k single nucleotide polymorphism (SNP) genotypes, (b) imputed whole‐genome sequencing data (~31 million), (c) selected SNPs from whole genome sequence data and (d) 50k SNP genotypes plus selected SNPs from whole‐genome sequence data. Furthermore, the impact of using a breed‐adjusted genomic relationship matrix on accuracy of genomic breeding value was assessed. The selection of genetic variants was based on an association study performed on imputed whole‐genome sequence data in an independent population, which was chosen either randomly from the base population or according to higher genetic proximity to the target population. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of genomic prediction was assessed according to the correlation between genomic breeding value and corrected phenotypes divided by the square root of trait heritability. The accuracy of genomic prediction was between 0.20 and 0.30 across different traits based on common 50k SNP genotypes, which improved on average by 0.06 (absolute value) on average based on using prioritized genetic markers from whole‐genome sequence data. Using prioritized genetic markers from a genetically more related GWAS population resulted in slightly higher prediction accuracy (0.02 absolute value) compared to genetic markers derived from a random GWAS population. Using high‐density SNP genotypes or imputed whole‐genome sequence data in GBLUP showed almost no improvement in genomic prediction accuracy however, accounting for different marker allele frequencies in reference population according to a breed‐adjusted GRM resulted to on average 0.024 (absolute value) increase in accuracy of genomic prediction.

Identification of Prospective Soybean Accessions for the Creation of a Genebank Core Collection Based on High Density DNA Marker Data

Genebanks typically collect and conserve as many existing genetic variations as possible. However, a smaller core population that is representative of the whole collection but maintains as much diversity as possible is more practical for in-depth phenotypic characterization, genetic studies, and plant breeding. Here we describe genotype-based core collection development from USDA soybean germplasm collection, which contains 20,095 accessions that had been genotyped using 50,000 single nucleotide polymorphism DNA markers. Analysis using trimmed marker data and Core Hunter 3 software identified 382 accessions with maximum genetic distances from each other. Population structure analysis of the selected accessions indicated that the software favored admixed individuals instead of those with pure ancestor population genotypes. Allele frequencies of most markers are largely conserved in the core population, which indicates successful maintenance of alleles in the core population. Phenotypic variations for branch number and yield were largely similar to the original population, but slightly different for seed weight and maturity, where very high seed weight and high-latitude maturity groups were less prominent in the core collection. The resulting core population can be used as a base population for any institutions interested in utilizing worldwide soybean genetic diversity for breeding and genetic studies.

Allele frequency data for 23 aSTR for different ethnic groups from Republic of Zimbabwe.

In order to determine the population allele frequencies of autosomal STR markers of forensic interest in the Zimbabwean population, we analyzed a sample of 478 individuals from 19 different ethnic groups using the PowerPlex® Fusion 6C Kit (Promega Corp, Madison, Wisconsin). The data obtained were compared among the different Zimbabwean ethnic groups as well as with several African populations to establish whether significant differences exist among them. No significant differences were found among the ethnic groups in Zimbabwe. Statistically significant differences were observed between allele frequencies in Zimbabwe and some other African populations, although FST with neighboring Bantu populations from South and Southeast regions were low (below 0.005 in most single locus comparisons).

Estimation of Cry3Bb1 resistance allele frequency in field populations of western corn rootworm using a genetic marker.

Following the discovery of western corn rootworm (WCR; Diabrotica virgifera virgifera) populations resistant to the Bacillus thuringiensis (Bt) protein Cry3Bb1, resistance was genetically mapped to a single locus on WCR chromosome 8 and linked SNP markers were shown to correlate with the frequency of resistance among field-collected populations from the US Corn Belt. The purpose of this paper is to further investigate the relationship between one of these resistance-linked markers and the causal resistance locus. Using data from laboratory bioassays and field experiments, we show that one allele of the resistance-linked marker increased in frequency in response to selection, but was not perfectly linked to the causal resistance allele. By coupling the response to selection data with a genetic model of the linkage between the marker and the causal allele, we developed a model that allowed marker allele frequencies to be mapped to causal allele frequencies. We then used this model to estimate the resistance allele frequency distribution in the US Corn Belt based on collections from 40 populations. These estimates suggest that chromosome 8 Cry3Bb1 resistance allele frequency was generally low (<10%) for 65% of the landscape, though an estimated 13% of landscape has relatively high (>25%) resistance allele frequency.

Novel directions in data pre-processing and genome-wide association study (GWAS) methodologies to overcome ongoing challenges

Abstract A genome-wide association study (GWAS) is a standard population-based technique for identifying the heritable genetic basis of complex diseases by discovering correlations between trait variations and allele frequencies of genetic markers. This article aims to help fill gaps in data pre-processing and GWAS methodologies by reviewing novel techniques and methodologies. Data pre-processing performed prior to a GWAS presents challenges in Hardy-Weinberg (H–W) estimation, genotyping and accounting for factors such as sample structure. Recent developments towards overcoming these challenges are presented: the likelihood ratio test for H–W estimation, sequencing for genotyping, and techniques for dealing with sample structure. Traditional statistical methods cannot provide a way to insightfully interpret the data generated from high-throughput techniques; therefore, novel directions in GWAS methodologies are reviewed using efficient statistical methods, which are flexible techniques for performing genetic association analysis when factors such as non-random sampling or population structure occur. Despite the development of these methods, genotyping costs and an increased capacity for large dataset analysis have motivated researchers to examine tissue-specific signals. This review discusses how prospective and retrospective association analyses can be used to consider binary traits, address non-random ascertainment, and increase the capacity for large dataset analysis. Importantly, for disease susceptibility, rare variants can represent a large portion of genetic markers, and this article reviews some association methods for rare variant detection. In conclusion, the recent developments in GWAS data preparation and methodologies reviewed in this article can overcome most current challenges in the field and will also address future challenges.

Seascape Genomics of the Sugar Kelp Saccharina latissima along the North Eastern Atlantic Latitudinal Gradient.

Temperature is one of the most important range-limiting factors for many seaweeds. Driven by the recent climatic changes, rapid northward shifts of species’ distribution ranges can potentially modify the phylogeographic signature of Last Glacial Maximum. We explored this question in detail in the cold-tolerant kelp species Saccharina latissima, using microsatellites and double digest restriction site-associated DNA sequencing ( ddRAD-seq) derived single nucleotide polymorphisms (SNPs) to analyze the genetic diversity and structure in 11 sites spanning the entire European Atlantic latitudinal range of this species. In addition, we checked for statistical correlation between genetic marker allele frequencies and three environmental proxies (sea surface temperature, salinity, and water turbidity). Our findings revealed that genetic diversity was significantly higher for the northernmost locality (Spitsbergen) compared to the southern ones (Northern Iberia), which we discuss in light of the current state of knowledge on phylogeography of S. latissima and the potential influence of the recent climatic changes on the population structure of this species. Seven SNPs and 12 microsatellite alleles were found to be significantly associated with at least one of the three environmental variables. We speculate on the putative adaptive functions of the genes associated with the outlier markers and the importance of these markers for successful conservation and aquaculture strategies for S. latissima in this age of rapid global change.

A pseudolikelihood approach for assessing genetic association in case-control studies with unmeasured population structure.

The case-control study design is one of the main tools for detecting associations between genetic markers and diseases. It is well known that population substructure can lead to spurious association between disease status and a genetic marker if the prevalence of disease and the marker allele frequency vary across subpopulations. In this paper, we propose a novel statistical method to estimate the association in case-control studies with unmeasured population substructure. The proposed method takes two steps. First, the information on genomic markers and disease status is used to infer the population substructure; second, the association between the disease and the test marker adjusting for the population substructure is modeled and estimated parametrically through polytomous logistic regression. The performance of the proposed method, relative to the existing methods, on bias, coverage probability and computational time, is assessed through simulations. The method is applied to an end-stage renal disease study in African Americans population.

Polygenic Risk Score for the Non-Invasive Prediction of Surgical Endometriosis [OP04-3D

INTRODUCTION: Endometriosis commonly causes infertility, dysmenorrhea, dyspareunia, dyschezia, chronic pelvic pain, and other gynecologic symptoms. Unfortunately, history, physical exam, pelvic ultrasound, and even the “gold standard” of laparoscopic visualization/histology have limitations with regard to diagnostic sensitivity and specificity. The objective of this study is development of a predictive DNA test for endometriosis. METHODS: Using IRB approved protocols, endometriosis associated markers were discovered using genome wide association studies (GWAS) involving 5,571 women with surgically confirmed endometriosis and 21,971 controls and whole exome sequencing (WES) of 2,904 affected women. Allele frequencies for WES markers were compared to published data [55,860 non-Finnish European in gnomAD database (Broad Institute)]. An additive prediction model was created using 71 GWAS markers combined into a single risk term using logistic regression and 550 low-frequency exome variants individually weighted using observed odds ratios. The predictive algorithm was validated using independent cohorts (1,458 Caucasian endometriosis patients and 758 population controls). RESULTS: The mean polygenic risk score was 1.2 in population controls and 2.9 in endometriosis patients (p&lt;10-16). The calculated Area Under the Curve (AUC) of predictor was excellent (0.88), even though endometriosis was not excluded in population controls (10% may have endometriosis). CONCLUSION: Predictive DNA testing may help to reduce the under-diagnosis and delayed diagnosis documented for endometriosis today. Blood, saliva, or other cell/tissue samples can be tested using this assay. DNA tests also have the potential to provide insights regarding molecular pathways involved, likely treatment responses, malignant potential, and other disease characteristics unavailable from histology.

CG/CA genotypes represent novel markers in the NPHS2 gene region associated with nephrotic syndrome

Nephrotic syndrome (NS) is considered as a primary disease of the kidney that represents a heterogeneous group of glomerular disorders occurring mainly in children. It is generally divided into steroid-sensitive and steroid-resistant forms, depending upon the patient's response to steroid therapy. Among the genes involved, the NPHS2 gene has been reported as the causative gene in steroid resistant form of nephrotic syndrome. In the present study, heterozygosity rate, allelic frequency and linkage of rs2274625 and rs3829795 markers were investigated in the NPHS2 gene region. To determine the SNP alleles, tetra-primer ARMS PCR was used. After genotyping rs2274625 and rs3829795 polymorphic markers in 120 unrelated individuals and nine trios families, the data were analysed using various computer programs such as UCSC Genome Browser, dbSNP and SNPper. Based on the statistical analysis of the results, for rs2274625 marker, allele frequency for C and T alleles was 97% and 3%, respectively. For rs3829795 marker allele frequency for G and A alleles was 55% and 45%, respectively. The values of heterozygosity index for the examined markers were 5% for rs2274625 and 45/8% for rs3829795. Consequently, two informative haplotypes, CG/CA, were identified in the NPHS2 gene region through combination of these two markers. These haplotypes can serve as appropriate tools for the identification of heterozygous carriers and linkage analysis of nephrotic syndrome disease in the Iranian families with an affected child.

On rare variants in principal component analysis of population stratification

BackgroundPopulation stratification is a known confounder of genome-wide association studies, as it can lead to false positive results. Principal component analysis (PCA) method is widely applied in the analysis of population structure with common variants. However, it is still unclear about the analysis performance when rare variants are used.ResultsWe derive a mathematical expectation of the genetic relationship matrix. Variance and covariance elements of the expected matrix depend explicitly on allele frequencies of the genetic markers used in the PCA analysis. We show that inter-population variance is solely contained in K principal components (PCs) and mostly in the largest K-1 PCs, where K is the number of populations in the samples. We propose FPC, ratio of the inter-population variance to the intra-population variance in the K population informative PCs, and d2, sum of squared distances among populations, as measures of population divergence. We show analytically that when allele frequencies become small, the ratio FPC abates, the population distance d2 decreases, and portion of variance explained by the K PCs diminishes. The results are validated in the analysis of the 1000 Genomes Project data. The ratio FPC is 93.85, population distance d2 is 444.38, and variance explained by the largest five PCs is 17.09% when using with common variants with allele frequencies between 0.4 and 0.5. However, the ratio, distance and percentage decrease to 1.83, 17.83 and 0.74%, respectively, with rare variants of frequencies between 0.0001 and 0.01.ConclusionsThe PCA of population stratification performs worse with rare variants than with common ones. It is necessary to restrict the selection to only the common variants when analyzing population stratification with sequencing data.

331 Efficient quality control methods for genomic and pedigree data used in routine genomic evaluation

Abstract Quality control and consistency tests on genotypes and historical pedigree data are applied in a routine genomic evaluation and academic research. The quality control takes more time to finish as more genotypes become available, and this step is a bottleneck in a pipeline of routine evaluation. For the efficient quality control, we have developed several algorithms and a computer program to support for large-scale, biallelic, single nucleotide polymorphisms (SNPs). The program is designed to detect unsatisfactory genomic markers and individuals in terms of call rate, marker allele frequencies, duplicate samples, and Mendelian inconsistency in the large genomic data with the pedigree including millions of individuals. Duplicated genotypes can be detected using a set of markers. An SNP genotype is packed into a 2-bit representation in memory that enables bitwise operations with parallel computing to efficiently perform the quality control. The software optionally checks the inconsistency of pedigree information. We compared QCF90 with preGSf90, a preceding program, in terms of memory usage and computing time using a data set including 200,000 genotyped individuals, 50,000 SNP markers per individual, and 216,500 pedigree individuals. In total running time, QCF90 was approximately 6 times faster than PREGSF90 (307 s vs 2075 s) while the memory usage was 30 times less (2 GB vs 75 GB) using only 1 thread. The QCF90 program performed better in speed as more threads were used. A check for genomic duplications took 159 s with 16 threads when 5,000 genotypes were compared with 200,000 genotypes using 2500 SNP markers. The new tool is useful in the routine genomic evaluation and the academic research in which both the genotypes and the pedigree information are used. The QCF90 executable is available at http://nce.ads.uga.edu with a user manual.

Analysis of 55 Kidd ancestry SNPs in Qatari population using ForenSeq Universal software & STRUCTURE software

SNPs are good predictors of ethnicity and serval panels have been published [1]. The ForenSeq Signature kit (Illumina) offers coverage of 230 different markers including 55 ancestry SNPs (AISNPs). The ForenSeq Universal Analysis Software (UAS) brings the capability to analyse the sequencing data, represent results and accomplish statistical estimates of biogeographic ancestry. The ancestry prediction results in UAS are based on Principal Component Analysis (PCA) collected on several reference populations comprised in the 1000 Genomes project. This set does not include Qatari population. The data was analysed using STRUCTURE software. These data serves as an addition to the existing Middle Eastern population data for the 55 AISNPs. The Qatari population has been a melting pot of various populations and this forensic study was the first of its kind to generate new data on the genetics of Qatari population. The 55-ancestry marker allele frequency data for 150 samples were analysed and compared to 139 world populations using STRUCTURE software. FROG-kb analysis led to all Qatari samples being correctly assigned to Middle Eastern populations showing that the Illumina software needs to be enhanced by adding more databases from the Middle East. In conclusion, the results have clearly demonstrated the potential use of MPS methods to study the genetics of Qatari population.

Mosquitoes as a feasible sentinel group for anti-malarial resistance surveillance by Next Generation Sequencing of Plasmodium falciparum

BackgroundPlasmodium falciparum drug resistance surveillance is key to successful disease control and eradication. Contemporary methods that only allow determination of prevalence of resistance are expensive, time consuming and require ethical considerations. A newer method involving Next Generation Sequencing (NGS) permits obtaining frequency of resistance while allowing to detect minority variants in mixed infections. Here, NGS was tested for P. falciparum resistance marker detection in mosquito samples as a feasible and suitable alternative for molecular resistance surveillance. Anopheles funestus were collected in southern Mozambique using CDC light traps and manual collections. DNA was extracted from either whole mosquito, head-thorax and abdomen separately or pools of five mosquitoes. These samples were screened for P. falciparum and if positive for k13, pfcrt, pfmdr1, pfdhps and pfdhfr mutations related to anti-malarial drug resistance with Sanger sequencing and NGS.ResultsAmong the 846 samples screened for P. falciparum, 122 were positive by 18S ssrDNA qPCR with an infection rate of 23.6%. No mutations were observed for k13 and pfcrt72-76 and almost zero for pfmdr86, but quintuple pfdhfr/pfdhps mutations were near fixation and about half of the isolates contained the pfmdr184F polymorphism. Similar allele frequencies of resistance markers were estimated with NGS in comparison with the prevalence of markers obtained with the gold standard Sanger sequencing.ConclusionsPooled deep sequencing of P. falciparum isolates extracted from mosquitoes is a promising, efficient and cost-effective method to quantify allele frequencies at population level which allows to detect known and unknown markers of resistance in single and mixed infections in a timelier manner. Using mosquitoes as sentinel group and focusing on allele frequency opposed to prevalence, permits active surveillance across a more homogeneous geographical range.