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PubMed2001

[CSNP discovery by two-dimensional gene scanning (TDGS)].

Challenges in the post-genomic era are to use genetic information in correlating individual gene variations (SNPs; single nucleotide polymorphisms, the most common form of genetic variation) with medically important parameters, such as disease susceptibility, individual responses to drugs and prognostic variables. What is missing is a high-throughput technology to identify all possible SNPs in essentially all human genes in population-based studies with high accuracy and speed in a cost-effective manner. Most tests advocated for their high throughput at low cost are actually SNP screening tests. That is, they screen samples for the presence of one or multiple previously identified SNPs. Such screening methods are only useful when all relevant SNPs in the genes of interest are known, which is presently not the case. Moreover, the usefulness of any one SNP varies enormously from population to population. Indeed, for the Korean population, where no information on possible sequence variation is available, a mutational scanning method, capable to detect all possible gene variations will be most useful. Two-Dimensional Gene Scanning (TDGS) is a high-throughput platform that enables to detect all possible SNPs in an entire gene in one gel under one set of conditions, with high sensitivity and specificity. TDGS is based on automated two-dimensional (2-D) DNA electrophoresis according to size and base pair sequence to detect DNA fragments containing all possible variations. Because the 2-D format permits the analysis of as many as 40 fragments of 250 bp on average in parallel, TDGS allows extensive multiplex PCR (megaplex PCR), i.e. up to 26 fragments in one single reaction, resulting in a significant cost reduction. TDGS tests are designed using a computer program to optimally position PCR primers around the relevant target sequences (exons). A simple automated 2-D instrument allows scanning all exons of a large gene in 8 different samples well within 3 hours. Using three different fluorophores this provides a throughput.

BRCA1 Protein↗

PubMed2006

Estimation of genetic parameters of a DH wheat population grown at different N stress levels characterized by probe genotypes.

Low market prices and environmental concerns in Europe favor lower input wheat production systems. To efficiently breed for new varieties adapted to low input management while maintaining high yield levels, our objective was to characterize the heritability and its components for yield and nitrogen traits under different nitrogen levels. Two hundred and twenty-two doubled-haploid (DH) lines from the cross between Arche (tolerant) and Récital (sensitive) were tested in France at four locations in 2000, and three in 2001, under high (N+) and low (N-) nitrogen supplies. The response of yield to the environment of four probe genotypes, the parents and two controls, were tested and used as descriptors of these environments. Grain yield (GY), its components, and grain and straw nitrogen, called nitrogen traits, were studied. A factorial regression was performed to assess the sensitivity (slope) of the DH lines to nitrogen stress and their performance to low nitrogen supply. An index based on the nitrogen nutrition index at flowering of the probe genotype Récital was the best descriptor of the environment stress. Heritabilities of yield and nitrogen traits for both nitrogen supplies were always above 0.6. When nitrogen stress increased, heritabilities decreased and genotype x nitrogen interaction variances increased. The decrease in heritability was mainly explained by a decrease in genetic variance. Genetic variation for sensitivity to nitrogen stress and performance under low nitrogen supply were shown in the population. GY decreased from 278 to 760 g/m2 per unit of nitrogen stress index increase and GY under moderate nitrogen stress varied from 340 to 613 g/m2. Those contrasted reactions revealed specific lines to include in breeding programs for improving GY under low nitrogen supply.

Breeding↗

PubMed2006

Multilevel selection 2: Estimating the genetic parameters determining inheritance and response to selection.

Interactions among individuals are universal, both in animals and in plants and in natural as well as domestic populations. Understanding the consequences of these interactions for the evolution of populations by either natural or artificial selection requires knowledge of the heritable components underlying them. Here we present statistical methodology to estimate the genetic parameters determining response to multilevel selection of traits affected by interactions among individuals in general populations. We apply these methods to obtain estimates of genetic parameters for survival days in a population of layer chickens with high mortality due to pecking behavior. We find that heritable variation is threefold greater than that obtained from classical analyses, meaning that two-thirds of the full heritable variation is hidden to classical analysis due to social interactions. As a consequence, predicted responses to multilevel selection applied to this population are threefold greater than classical predictions. This work, combined with the quantitative genetic theory for response to multilevel selection presented in an accompanying article in this issue, enables the design of selection programs to effectively reduce competitive interactions in livestock and plants and the prediction of the effects of social interactions on evolution in natural populations undergoing multilevel selection.

Models, Genetic↗

PubMed2006

Bioinformatics research on the SARS coronavirus (SARS_CoV) in China.

Severe acute respiratory syndrome (SARS) first appeared in 2002 in China, which fastly affected about 8000 patients over 29 countries and caused 774 fatalities. As its pathogen was identified as a new kind of coronavirus (SARS_CoV), its genome was quickly sequenced on several isolates. Studies on its functional genomics were performed by combinatorial application of all the available bioinformatics tools and the development of new programs. In this way, it was found that the four proteins were absolutely responsible for nosogenesis of SARS, i.e. spike (S) protein; small envelop (E) protein; membrane (M) protein; and nucleocaspid (N) protein. Molecular evolution studies have revealed that SARS must be originated from wild animals, and it was demonstrated that the major genetic variations in some critical genes, particularly the Spike gene, was essential for the transition from animal-to-human transmission to human-to-human transmission. Theoretical models, either Logistic model or SIR model, were developed to describe the transmission of SARS. The recorded difference of SARS spreading in Beijing and Hong Kong was also reasonably analyzed according to these models. The whole process of fruitful bioinformatics studies, along with other related scientific investigations have set up an unprecedented paradigm for human of how to battle against sudden-breaking and catastrophic epidemics.

China↗

PubMed2004

In silico search for single nucleotide polymorphisms in genes important in vitamin E homeostasis.

Large inter-individual variation exists in the response to vitamin E supplementation, and this may influence the outcome of human studies. It is our hypothesis that genetic heterogeneity is an important determinant of vitamin E homeostasis. Therefore we have performed an in silico search for single nucleotide polymorphisms (SNPs) associated with genes involved in vitamin E homeostasis. Based on function, the following genes were considered as candidates for vitamin E heterogeneity: c-tocopherol transfer protein (TTPA), tocopherol associated protein (TAP), lipoprotein lipase (LPL), multidrug resistance protein 2 (MDR-2), pregnane X receptor (PXR) and members of the cytochrome P450 family (CYP). Searches for coding SNPs were initiated from web based programs of the National Center for Biotechnology Information (NCBI). SNP frequencies were calculated by dividing the number of annotated coding SNPs by the number of base pairs in the open reading frame. Genes for TTPA, TAP and CYP3A5 had calculated SNP frequencies between 503 and 837 base pairs per coding SNP (bp/cSNP) and so are not highly polymorphic. In contrast, cSNP frequencies in LPL, MRP2, PXR, CYP3A4 and CYP4F2 were in the range of 100 bp/cSNP and so are highly polymorphic. Thus proteins involved in specific vitamin E binding are not highly polymorphic, may not influence inter-individual variation and so may not be good candidates for population studies. Proteins involved in drug/lipid metabolism which indirectly influence vitamin E status are highly polymorphic, are likely to influence inter-individual variation and so are good candidates for population studies. We suggest that future studies are aimed at addressing the role of such SNPs in vitamin E homeostasis.

ATP Binding Cassette Transporter, Subfamily B↗

PubMed2002

Genetic basis of variation in carotid artery plaque in the San Antonio Family Heart Study.

BACKGROUND AND PURPOSE: In contrast to the commonly used quantitative marker of subclinical atherosclerosis, namely intima-media thickness, we investigated the extent to which the presence or absence of carotid artery plaque (CAP) was under genetic control. METHODS: The study population consisted of 750 individuals distributed across 29 randomly ascertained extended Mexican American pedigrees who participated in the second examination cycle of the San Antonio Family Heart Study. Extracranial focal CAP was identified by B-mode ultrasound bilaterally in the internal carotid artery or the carotid bulb. Using a variance decomposition approach implemented in the SOLAR computer program, we performed genetic analysis on the discrete trait CAP (ie, liability to disease) using a threshold model. Covariates considered in the analysis included age, sex, diabetes, current smoking status, lipid levels, and markers of hypertension and obesity. RESULTS: Fifty-one of 461 women and fifty-seven of 289 men with a mean age of 42.1 years had evidence of a plaque in the right and/or left carotid artery. The age- and sex-adjusted heritability (h(2)+/-SE) for CAP was significant (h(2)=0.28+/-0.15, P=0.01). Furthermore, after adjustment for additional covariates that contributed significantly to the model (P<0.05; diabetes, hypertension, body mass index, waist circumference, and smoking status), heritability remained significant (h(2)=0.23+/-0.15, P=0.03). CONCLUSIONS: Our data indicate that after established cardiovascular risk factors are controlled for, the variation of the discrete trait CAP is under appreciable additive genetic influences.

Adolescent↗

PubMed2002

Inversion of oceanic constituents in case I and II waters with genetic programming algorithms.

A stochastic inverse technique based on agenetic programming (GP) algorithm was developed toinvert oceanic constituents from simulated data for case I and case II water applications. The simulations were carried out with the Ordre Successifs Ocean Atmosphere (OSOA) radiative transfer model. They include the effects of oceanic substances such as algal-related chlorophyll, nonchlorophyllous suspended matter, and dissolved organic matter. The synthetic data set also takes into account the directional effects of particles through a variation of their phase function that makes the simulated data realistic. It is shown that GP can be successfully applied to the inverse problem with acceptable stability in the presence of realistic noise in the data. GP is compared with neural network methodology for case I waters; GP exhibits similar retrieval accuracy, which is greater than for traditional techniques such as band ratio algorithms. The application of GP to real satellite data [a Sea-viewing Wide Field-of-view Sensor (SeaWiFS)] was also carried out for case I waters as a validation. Good agreement was obtained when GP results were compared with the SeaWiFS empirical algorithm. For case II waters the accuracy of GP is less than 33%, which remains satisfactory, at the present time, for remote-sensing purposes.

Journal Article↗

PubMed2005

Molecular mapping of a quantitative trait locus for aluminum tolerance in wheat cultivar Atlas 66.

Genetic improvement of aluminum (Al) tolerance is one of the cost-effective solutions to improve wheat (Triticum aestivum) productivity in acidic soils. The objectives of the present study were to identify quantitative trait loci (QTL) for Al-tolerance and associated PCR-based markers for marker-assisted breeding utilizing cultivar Atlas 66. A population of recombinant inbred lines (RILs) from the cross Atlas 66/Century was screened for Al-tolerance by measuring root-growth rate during Al treatment in hydroponics and root response to hematoxylin stain of Al treatment. After 797 pairs of SSR primers were screened for polymorphisms between the parents, 131 pairs were selected for bulk segregant analysis (BSA). A QTL analysis based on SSR markers revealed one QTL on the distal region of chromosome arm 4DL where a malate transporter gene was mapped. This major QTL accounted for nearly 50% of the phenotypic variation for Al-tolerance. The SSR markers Xgdm125 and Xwmc331 were the flanking markers for the QTL and have the potential to be used for high-throughput, marker-assisted selection in wheat-breeding programs.

Aluminum↗

PubMed1995

Convergent evolution within the V3 loop domain of human immunodeficiency virus type 1 in association with disease progression.

Phylogenetic analysis was used to study in vivo genetic variation of the V3 region of human immunodeficiency virus type 1 in relation to disease progression in six infants with vertically acquired human immunodeficiency virus type 1 infection. Nucleotide sequences from each infant formed a monophyletic group with similar average branch lengths separating the sets of sequences. In contrast to the star-shaped phylogeny characteristic of interinfant viral evolution, the shape of the phylogeny formed by sequences from the infants who developed AIDS tended to be linear. A computer program, DISTRATE, was written to analyze changes in DNA distance values over time. For the six infants, the rate of divergence from the initial variant was inversely correlated with CD4 cell counts averaged over the first 11 to 15 months of life (r = -0.87, P = 0.024). To uncover evolutionary relationships that might be dictated by protein structure and function, tree-building methods were applied to inferred amino acid sequences. Trees constructed from the full-length protein fragment (92 amino acids) showed that viruses from each infant formed a monophyletic group. Unexpectedly, V3 loop protein sequences (35 amino acids) that were found at later time points from the two infants who developed AIDS clustered together. Furthermore, these sequences uniquely shared amino acids that have been shown to confer a T-cell line tropic phenotype. The evolutionary pattern suggests that viruses from these infants with AIDS acquired similar and possibly more virulent phenotypes.

Acquired Immunodeficiency Syndrome↗

PubMed2004

LDDist: a Perl module for calculating LogDet pair-wise distances for protein and nucleotide sequences.

LDDist is a Perl module implemented in C++ that allows the user to calculate LogDet pair-wise genetic distances for amino acid as well as nucleotide sequence data. It can handle site-to-site rate variation by treating a proportion of the sites as invariant and/or by assigning sites to different, presumably homogenous, rate categories. The rate-class assignments and invariant proportion can be set explicitly, or estimated by the program; the latter using either of two different capture-recapture methods. The assignment to rate categories in lieu of a phylogeny can be done using Shannon-Wiener index as a crude token for relative rate.

Algorithms↗

PubMed2026

Targeted population genomics uncovers demographic history and genetic divergence in north American wild cranberry.

Wild populations of North American cranberry (Vaccinium macrocarpon Aiton) are reservoirs of genetic variation that may contribute to the improvement of breeding-relevant traits. However, the extent to which wild genetic variation is geographically structured and represented in elite germplasm remains unclear. We analysed 179 wild cranberry accessions from the upper Midwest and Eastern North America to estimate nucleotide diversity (π), population structure, and loci associated with genetic differentiation and environmental variables using a genome-informed targeted genotyping panel. Additionally, 14 demographic scenarios were evaluated using site-frequency-spectrum-based inference to identify historical events that could explain current genetic diversity. We observed extremely low nucleotide diversity within the targeted panel (π = 5 × 10-6). Rare allele distributions strongly influenced π and Tajima's D values, suggesting constrained diversity in the genomic regions assayed that is not captured by heterozygosity-based estimates alone. However, we interpreted these results as conservative lower bounds on genome-wide neutral diversity because the targeted panel is enriched for genic and conserved regions. A clear separation between the Midwest and East populations was observed, with inbreeding coefficients ranging from -0.13 to 0.15. Furthermore, site frequency spectrum inference from the targeted panel supported a demographic scenario consistent with a significant population reduction ≈15-14 thousand years ago (kya), followed by a divergence between the two regions ≈12 kya, and an asymmetric gene flow ≈1.3 kya. We detected 254 candidate loci showing regional allele-frequency differentiation. Several of these loci colocalized with candidate genes linked to stress response, development, and metabolic processes. To evaluate the representation of geographically differentiated wild alleles in a breeding context, we analysed Rutgers breeding materials (n = 484) and found that this panel is enriched for common alleles in Eastern wild populations. These findings indicate regionally structured allele-frequency variation in wild cranberry, with potential relevance to environmental response and breeding. This study extends prior wild cranberry population-genetic research by providing targeted-panel estimates of diversity, comparisons of demographic models, and breeding insights on geographically differentiated alleles, while highlighting the importance of conserving wild cranberry germplasm for use in modern breeding programs.

Journal Article↗

PubMed2006

Simultaneous estimation of mixing rates and genetic drift under successive sampling of genetic markers with application to the mud crab (Scylla paramamosain) in Japan.

In stock enhancement programs, it is important to assess mixing rates of released individuals in stocks. For this purpose, genetic stock identification has been applied. The allele frequencies in a composite population are expressed as a mixture of the allele frequencies in the natural and released populations. The estimation of mixing rates is possible, under successive sampling from the composite population, on the basis of temporal changes in allele frequencies. The allele frequencies in the natural population may be estimated from those of the composite population in the preceding year. However, it should be noted that these frequencies can vary between generations due to genetic drift. In this article, we develop a new method for simultaneous estimation of mixing rates and genetic drift in a stock enhancement program. Numerical simulation shows that our procedure estimates the mixing rate with little bias. Although the genetic drift is underestimated when the amount of information is small, reduction of the bias is possible by analyzing multiple unlinked loci. The method was applied to real data on mud crab stocking, and the result showed a yearly variation in the mixing rate.

Animals↗

PubMed2004

Steroid sulfatase gene variation and DHEA responsiveness to resistance exercise in MERET.

Genetic influences and endurance exercise have been shown to alter circulating concentrations of dehydroepiandrosterone (DHEA) and its sulfated conjugate, DHEAS. We hypothesized that acute resistance exercise (RE) and training (RET) would increase DHEA steroids, and the magnitude of the increase would be influenced by a steroid sulfatase (STS) gene variation. Fasting blood samples were collected before and after the first (S1) and last (S30) session of a 10-wk RET program in 62 men and 58 women [age: 21.0 yr (2.4)]. Acute RE increased both DHEA [+2.8 (0.4), S1; +1.6 ng/ml (0.4), S30; P < 0.001] and DHEAS [+154 (24), S1; +166 ng/ml (15), S30; P < 0.001] and decreased DHEAS:DHEA [-27 (8), S1; -15 (7), S30; P < 0.01]. RET reduced resting DHEAS (-122 ng/ml, P < 0.01) and decreased DHEA response to RE (-50%, P < 0.05). Subjects with an STS "G" allele (n = 36) had greater acute changes in DHEA [+4.4 (0.7) vs. +2.0 ng/ml (0.5), S1; +3.2 (0.6) vs. +1.0 ng/ml (0.4), S30; P < 0.01] and DHEAS:DHEA [-37 (11) vs. 5 (7), S30, P < 0.05] than those subjects with only an "A" allele (n = 84). The observed increase in DHEA and DHEAS and decrease in DHEAS:DHEA suggest RE-induced STS activation which is influenced by the STS polymorphism.

Adult↗

PubMed2003

Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions.

MOTIVATION: Polymorphisms in human genes are being described in remarkable numbers. Determining which polymorphisms and which environmental factors are associated with common, complex diseases has become a daunting task. This is partly because the effect of any single genetic variation will likely be dependent on other genetic variations (gene-gene interaction or epistasis) and environmental factors (gene-environment interaction). Detecting and characterizing interactions among multiple factors is both a statistical and a computational challenge. To address this problem, we have developed a multifactor dimensionality reduction (MDR) method for collapsing high-dimensional genetic data into a single dimension thus permitting interactions to be detected in relatively small sample sizes. In this paper, we describe the MDR approach and an MDR software package. RESULTS: We developed a program that integrates MDR with a cross-validation strategy for estimating the classification and prediction error of multifactor models. The software can be used to analyze interactions among 2-15 genetic and/or environmental factors. The dataset may contain up to 500 total variables and a maximum of 4000 study subjects. AVAILABILITY: Information on obtaining the executable code, example data, example analysis, and documentation is available upon request. SUPPLEMENTARY INFORMATION: All supplementary information can be found at http://phg.mc.vanderbilt.edu/Software/MDR.

Algorithms↗

PubMed2026

Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups.

The early 20th-century discovery of heterosis and the establishment of heterotic groups transformed maize (Zea mays L.) into a keystone of global agriculture. However, maize breeding faces two significant challenges: the gradual decline of general combining ability (GCA) variance within heterotic groups and the impracticality of testing all possible single crosses in the early stages of a breeding program. Here, we developed genomic best linear unbiased prediction (GBLUP)-based multikernel models, using additive and two alternative nonadditive genomic relationship matrices, to estimate the variance components associated with the general combining ability of Stiff Stalk (SS) and Non-Stiff Stalk (NSS) heterotic groups and the specific combining ability arising from their crosses. We further applied these models to predict the performance of untested single-cross combinations under varying levels of parental information. We showed that the SS and NSS groups retained significant GCA variance across traits in both early- and late-maturity groups. The SS group, in contrast, exhibited no detectable GCA variance in grain yield for the intermediate-flowering subset of hybrids, highlighting a limitation for future genetic improvement. Furthermore, our results showed that GBLUP-based multikernel models effectively identified superior hybrids when parental information was available. In the absence of this information, however, these models underperformed compared to covariance-based approaches. Both nonadditive matrices yielded similar results, indicating that they capture comparable genetic relationship patterns despite their distinct formulations. Overall, this study sheds light on the future use of US maize commercial germplasm and demonstrates how GBLUP-based multikernel models can improve the efficiency of hybrid breeding programs.

Zea mays↗

PubMed2026

SNPannotator: automated functional annotation of genetic variants and linked proxies.

SUMMARY: Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with complex traits and diseases. However, explaining the mechanisms underlying phenotypic variation remains challenging. Here, we introduce SNPannotator, an automated post-GWAS analysis software package designed to streamline the interpretation of GWAS findings. Our pipeline implements a multi-step process that identifies proxy variants in high linkage disequilibrium (LD) with associated lead variants, then queries comprehensive resources (including Ensembl, the GTEx Portal, the eQTL Catalog, and STRING DB) for genomic position, deleteriousness, regulatory annotations, clinical significance, trait associations, expression (eQTLs) and splicing quantitative trait loci (sQTLs), and functional enrichment analyses and compiles the results into user-friendly reports. This package is implemented in the R programming language and includes auxiliary functions for variant lookup and LD exploration. SNPannotator provides a practical framework for efficiently deriving biologically meaningful insights from GWAS data and for assisting researchers in prioritizing candidate variants for functional validation. AVAILABILITY AND IMPLEMENTATION: The SNPannotator package is available from the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/SNPannotator. The development version and tutorial is available on GitHub (https://github.com/omicslaboratory/SNPannotator). The online version of the package is available at https://omicslab.org/snpannotator.

Software↗

PubMed1998

Human genome diversity.

Human genome diversity studies analyse genetic variation among individuals and between populations in order to understand the origins and evolution of anatomically modern humans (Homo sapiens sapiens). The availability of thousands of DNA polymorphisms (genetic markers) brings analytic power to these studies. Human genome diversity studies have clearly shown that the large part of genetic variability is due to differences among individuals within populations rather than to differences between populations, effectively discrediting a genetic basis of the concept of 'race'. Evidence from paleontology, archaeology and genetic diversity studies is quite consistent with an African origin of modern humans more than 100,000 years ago. The evidence favors migrations out of African as the source of the original peopling of Asia, Australia, Europe and Oceania. An international program for the scientific analysis of human genome diversity and of human evolution has been developed. The Human Genome Diversity Project (HGDP) aims to collect and preserve biologic samples from hundreds of populations throughout the world, make DNA from these samples available to scientists and distribute to the scientific community the results of DNA typing with hundreds of genetic markers.

Evolution, Molecular↗

PubMed2004

Population genetic structure of Anopheles gambiae mosquitoes on Lake Victoria islands, west Kenya.

BACKGROUND: Understanding the genetic structure of island Anopheles gambiae populations is important for the current tactics in mosquito control and for the proposed strategy using genetically-modified mosquitoes (GMM). Genetically-isolated mosquito populations on islands are a potential site for testing GMM. The objective of this study was to determine the genetic structure of A. gambiae populations on the islands in Lake Victoria, western Kenya. METHODS: The genetic diversity and the population genetic structures of 13 A. gambiae populations from five islands on Lake Victoria and six villages from the surrounding mainland area in the Suba District were examined using six microsatellite markers. The distance range of sampling sites varied between 2.5 and 35.1 km. RESULTS: A similar level of genetic diversity between island mosquito populations and adjacent mainland populations was found. The average number of alleles per locus was 7.3 for the island populations and 6.8 for the mainland populations. The average observed heterozygosity was 0.32 and 0.28 for the island and mainland populations, respectively. A low but statistically significant genetic structure was detected among the island populations (FST = 0.019) and between the island and mainland populations (FST = 0.003). A total of 12 private alleles were found, and nine of them were from the island populations. CONCLUSION: A level of genetic differentiation between the island and mainland populations was found. Large extent of gene flow between the island and mainland mosquito populations may result from wind- or human-assisted dispersal. Should the islands on Lake Victoria be used as a trial site for the release program of GMM, mosquito dispersal between the islands and between the island and the mainland should be vigorously monitored.

Alleles↗