Crosses between laboratory strains of mice provide a powerful way of detecting quantitative trait loci for complex traits related to human disease. Hundreds of these loci have been detected, but only a small number of the underlying causative genes have been identified. The main difficulty is the extensive linkagedisequilibrium (LD) in intercross progeny and the slow process of fine-scale mapping by traditional methods. Recently, new approaches have been introduced, such as association studies with inbred lines and multigenerational crosses. These approaches are very useful for interval reduction, but generally do not provide single-gene resolution because of strong LD extending over one to several megabases. Here, we investigate the genetic structure of a natural population of micein Arizona to determine its suitability for fine-scale LD mapping and association studies. There are three main findings: (1) Arizona mice have a high level of genetic variation, which includes a large fraction of the sequence variation present in classical strains of laboratory mice; (2) they show clear evidence of local inbreeding but appear to lack stable population structure across the study area; and (3) LD decays with distance at a rate similar to human populations, which is considerably more rapid than in laboratory populations of mice. Strong associations in Arizona mice are limited primarily to markers less than 100 kb apart, which provides the possibility of fine-scale association mapping at the level of one or a few genes. Although other considerations, such as sample size requirements and marker discovery, are serious issues in the implementation of association studies, the genetic variation and LD results indicate that wildmice could provide a useful tool for identifying genes that cause variation in complex traits.
Two sets of samples—commercial egg layers and wild chicken (coded respectively LAY and ANC)—were used in this study. The commercial individuals from Lohmann Tierzucht GmbH originated from three different breeds. One commercial white egg layer breed based on White Leghorn (WL), with three separate lines, and the other two brown egg layer breeds based on White Rock (WR) and Rhode Island Red (RIR), respectively, each with two separate lines per breed. In each of these seven lines, ten individuals were sampled and genotyped. The wild chickens, comprising Red Jungle fowl (Cochin-Chinese) (G. g. gallus) and Red Jungle fowl (Burmese) (G. g. spadiceus) were sampled within the AVIANDIV project. A more detailed list of breeds is presented in Table 1. The ANC group consisted of two subspecies of Gallus gallus that are believed to stem in straight line from wild ancestors of domestic chickens. Data is pub- licly available (S1 Dataset).
The goal of the present paper is to examine the nature of the trends observed previously (e.g., [16,24]) and in particular to explore patterns of interchromosomal linkagedisequilibrium (ILD) and the presence of hybridization between wild Atlantic cod N and S types in the previously identified hybrid zone in the northwest Atlantic. First, we identify possible functional associations of clinal SNPs through alignment with the recently available Atlantic cod genome, and an exploration of SNP-gene associations. Second, we explore ILD among SNPs in three different linkage groups previously associated with clinal structure. Finally, we examine the degree of hybridization among these two latitudinal cod types using a Bayesian approach to assign individuals to discrete hybrid classes. We build on previous studies, which examined loci displaying evidence of environmentally associated selection in parallel on either side of the Atlantic in a subset of the loci (n = 40) and populations (n = 14) used in this study , and the application of these loci for fisheries management and conserva- tion [16,28]. Here, we delve further into the mechanisms driving these patterns and present evidence of previously unknown cryptic speciation and divergence in a common, heavily exploited marine fish. The implications for the management of Atlantic cod as well as the potential for cryptic diversity in other well studied and exploited marine organisms (e.g., ) suggest significant gaps in our current understanding perhaps best addressed with population genomic approaches.
The HFE genotyping was done using two commercial kits (Haemochromatosis gene mutation assay I and II, ViennaLab, Vienna, Austria). Briefly, sequences of exon 4 (for C282Y) or exon 2 (for H63D) of the HFE gene were amplified in vitro and terminally labeled with fluorescein as a reporter molecule. The amplification products were alkali-denatured, and 25 µl aliquots were selectively hybridized to allele-specific (wild type or mutant) oligonucleotide probes immobilized in two separate cavities of a microwell plate. After hybridization and stringent washes at 37°C, bound sequences were detected using a horseradish peroxidase- labeled anti-fluorescein antibody and color reaction with tetra- methylbenzidine. The methodology as well as its validation on samples of known genotype (RFLP-typed) and the application for typing have been presented elsewhere (Oberkanins et al. 1998).
5 recombination (Sved, 2009). The model derivation assumed that the population was isolated, mating was random, and the population size remained constant over time. These assumptions are likely to be violated in most natural and selective breeding populations. Moreover, nonlinear regression models generally assume that errors are independent, have homogeneous variance, and are normally distributed. These assumptions are violated, due to the nature of LD data, which is dependent on the distance between markers and is more variable at short distances than at long distances. Consequently, some alternatives have been proposed for modeling LD decay. Instead of using a fixed value of unity for the intercept, Corbin et al. (2010) introduced a new parameter to estimate the intercept in the equation proposed by Sved (1971); this new parameter may provide a better fit to the LD at short distances. LOESS regression is also a good option for describing the LD decay, because it allows the functional form between dependent and independent variables to be determined by the data without requiring strong assumptions (Andersen, 2009).
structure of LD in the maize genome. Fine scale coverage was only 2.3 SNP/gene on average, but this was enough to give us a rough picture of the structure of LD in maize at the whole genome level. Our results demonstrate that LD decline is variable across the chromosomes and not continual within a chromosome. More markers may have smoothed some of the discontinuity within a chromosome, but it also reflects the known complex genome structure of maize. Minimum allelic frequency is another factor that affects estimation of the extent of LD. Within the global decay distance of maize LD (5–10 kb), mean r 2 increases with the increase of MAF, and a similar phenomenon was also observed in other species . Khatkar et al.,  proposed that SNP pairs with similar allelic frequencies may increase estimates of r 2 . In this study, removing SNPs with very low MAFs also lead to lower numbers of SNPs available for study, which can also lead to bias of LD estimates. A small sample size (e.g. n = 25) can also lead to the biased estimation for LD. However, there are no significant differences for the mean r 2 when sample sizes are over 50, especially when the given extent interval of LD is less than 2 kb (Figure 7). However, a recent study in cattle demonstrated that a sample of 400 or more was required for reliable estimation if using D 9 to measure LD . Decay of LD is also greatly affected by the sequence diversity present in the samples used. The LD decay is more rapid in tropical and subtropical lines than in temperate lines when sample numbers are equivalent (Figure 8), because there is more sequence diversity in tropical and subtropical than temperate lines (Table 8).
Table 1 shows that all groups are in Hardy–Weinberg equi- librium for the HLA-A, -B and -DRB1 loci except for the LIGH database and the Asian group where the number of observed heterozygotes is smaller than expected. This fact possibly occurs because the LIGH database is composed of donors from different parts of Paraná State or living in cities with high con- centrations of people sharing the same ancestral background (Asian) that determine regional differences in the popula- tion. Additionally, the condition of strictly random marriages, which is fundamental to the accuracy of the Hardy–Weinberg equilibrium, may not occur.
Alpha Minimal Essential Medium (a-MEM), Dubecco’s Mod- ified Eagle’s Medium (DMEM), fetal calf serum, trypsin/EDTA solution, phosphate-buffered saline (PBS), penicillin-streptomycin, and Superscript III first-strand synthesis kit were purchased from Life Technologies (Carlsbad, CA). Okadaic acid, alizarin red, sodium orthovanadate, TRAP staining kit, ascorbic acid, and b- glycerol phosphate were from Sigma-Aldrich (St. Louis, MO). Protease inhibitor and NBT/BCIP tablets were from Roche Applied Sciences (Indianapolis, IN). Polymerases were purchased from Roche Applied Sciences, and Fermentas (Hanover, MD). AquaBlock EIA/WIB solution was from East Coast Biologicals (North Berwick, ME), and the BCA protein assay kit was obtained from Pierce Biotechnologies (Rockford, IL). Immobilon-FL was from Millipore Corporation (Billerico, MA). RANKL and m-CSF were purchased from R&D systems (Minneapolis, MN). Produc- tion and use of recombinant BMP2 has been described . Antibodies were obtained from the following vendors: anti-Akt1 (AbCam, Cambridge, United Kingdom), anti-Akt, anti-phospho- Akt (Ser 473 ), and anti-Akt2 (Cell Signaling Technology, Beverly, MA), anti-a-tubulin, Sigma Aldrich (St. Louis, MO), anti-Runx2 (Santa Cruz Biotechnology, Santa Cruz, CA). Goat-anti-rabbit IgG-IR800 and goat anti-mouse IgG-IR680 were from Rockland Immunochemical (Gilbertsville, PA). Other chemicals and re- agents were purchased from commercial suppliers.
consequence of gene duplication subsequent to the diver- gence of humans from rodents (Merritt et al. 1990). Indi- viduals containing three AGP genes have been reported (Dente et al. 1987; Merritt and Board 1988; Nakamura et al. 2000). These three gene arrays (AGP1-AGP2-AGP2 or AGP1-AGP1-AGP2) represent polymorphisms in the pop- ulations studied and are the result of further crossover events that must have occurred relatively recently since there were no changes in the duplicated genes studied. In the Caucasian population studied here linkage disequilib- rium was observed between the presence of an intense 6.9 kb HindIII fragment (1-2-2’ and hence multiple AGP1 or AGP2 genes) and the TaqI RFLP. The simplest explanation for the origin of the TaqI polymorphism would be a point mutation that caused the loss of the TaqI site in the region between the AGP1 and AGP2 genes. However, if one con- siders that unequal crossing over events generated three member AGP gene arrays (Dente et al. 1987; Merritt and Board 1988; Merritt et al. 1990; Nakamura et al. 2000) it is possible that a crossover event could cause the loss of a TaqI site. In this study individuals who may be homozy- gous for the presence of a third AGP gene would be indis- tinguishable from heterozygotes since increased intensity of the 6.9 kb band relative to the 4.5 kb was used as the ba- sis for scoring. Interestingly, however, Family M, (Figure 3.) was informative for both the TaqI polymorphism and the presence of an extra AGP gene and those individuals that were heterozygous for the TaqI polymorphism were also heterozygous for an extra AGP gene. Furthermore, in the population studied there were no T2T2 individuals sug- gesting that there were no individuals homozygous for an extra AGP gene. Further sequence analysis of the AGP lo- cus from the individuals studied would be required to con- firm the genetic basis for observed linkage between the TaqI polymorphism and the presence of multiple AGP genes and to determine if the particular duplicated gene was AGP1 or AGP2.
The gut microbiota profoundly affects the biology of its host. The composition of the micro- biota is dynamic and is affected by both host genetic and many environmental effects. The gut microbiota of laboratory mice has been studied extensively, which has uncovered many of the effects that the microbiota can have. This work has also shown that the environments of different research institutions can affect the mouse microbiota. There has been relatively limited study of the microbiota of wildmice, but this has shown that it typically differs from that of laboratory mice (and that maintaining wild caught micein the laboratory can quite quickly alter the microbiota). There is also inter-individual variation in the microbiota of wildmice, with this principally explained by geographical location. In this study we have charac- terised the gut (both the caecum and rectum) microbiota of wild caught Mus musculus domesticus at three UK sites and have investigated how the microbiota varies depending on host location and host characteristics. We find that the microbiota of these mice are generally consistent with those described from other wildmice. The rectal and caecal micro- biotas of individual mice are generally more similar to each other, than they are to the micro- biota of other individuals. We found significant differences in the diversity of the microbiotas among mice from different sample sites. There were significant correlations of microbiota diversity and body weight, a measure of age, body-mass index, serum concentration of lep- tin, and virus, nematode and mite infection.
Hardy-Weinberg equilibrium (HWE) was determined in both cases and controls (23) and genotype and allelic frequencies were also determined in cases and controls. Prior to statistical analysis, BMI and triglyceride data were normalized by natural log transformation. The general linear method was used to adjust for age and gender when as- sessing the effects of SNPs on obesity parameters and lipid levels. The results of association analysis for the SNPs and obesity parameters indicated that the additive model best fitted the data. Data are reported as means ± SD. Bonfer- roni’s adjustment was performed to correct for multiple tests on multiple markers (α = 0.05/30). Statistical analysis was performed using the SPSS version 16 software.
there are converging biological, clinical, and genetic evidences implicating DRD2 as a viable candidate gene for genetic susceptibility for schizophrenia, especially its neighboring sin- gle-nucleotide polymorphism (SNP) rs1800497 (Taq1A). The rs1800497 SNP was considered a silent mutation located 10 kb from DRD2 gene, in the 3’ untranslated region. However recently the identification of a novel gene in the neighboring forward-strand region of DRD2 gene, named ANKK1 gene, showed that the rs1800497 SNP is located in exon 8 of the ANKK1 gene 13 . This polymorphism actually causes an amino
Evidences have indicated that the size of human population increased in the Upper Pleistocene . Populations that have grown are expected to have an excess of low-frequency alleles and thus low pairwise difference between sequences, which will lead to the reduction of common statistics used to detect from neutrality, e.g. Tajima’s D, . Therefore, it is inappropriate to detect natural selection, e.g. conservative to detect balancing selection, under the model of constant population size . In this study, we identified significant deviation of Tajima’s D from neutrality under models incorporating different human population growth parameters. Another two pieces of evidences, strong linkagedisequilibrium and lower genetic differentiation among human ethnical populations also support the existence of a balancing selection, because population subdivision, another competing hypothesis, could also lead to significantly high Tajima’s D for divergent haplotypes existing in different geographical regions [14,19]. However, the nucleotide diversity is low in the region, which is not usually observed in the genes under balancing selection (Figure 3). Perhaps, the intron 5 region is highly conservative during evolution for its essential function and does not allow accumulation of new mutations. For example, the nucleotide diversity of ACE2 gene, subject to balancing selection, is even lower than that found in this intron .
In order to verify the presence of a founder chromo- some, we analyzed the distribution of alleles at DXS548 lo- cus, a polymorphic marker located 150 Kb centromeric from the CGG repeats, that co-segregates, in the majority of the cases, without recombination with the fragile-Xlocus (Fu et al., 1991; Dreesen et al., 1994). In addition to all the previously described DXS548 alleles, we detected a new allele which we called “allele 10” (17 CA), following the terminology recommended by Macpherson et al. (1994) (Figure 2). The frequencies of DXS548 alleles in our sam- ple show a slightly higher genetic diversity than in other populations, which probably reflects Spain’s more hetero- geneous genetic background, as it has been previously re- ported for other loci (Bertrantpetit and Cavalli-Sforza, 1991; Cavalli-Sforza and Piazza, 1993; Chillon et al., 1994; Milá et al., 1994; Milá, 1997). In the non-fragile Xchromo- somes, we observed that the most frequent DXS548 allele was allele 7 (20 CA, 47%), followed by allele 6 (21 AC, 23%) (Table 1). Table 2 shows the DXS548/ (CGG)n- FRAXA haplotypes in the non-fragile X chromosomes, compared to fragile X. Similar to previous work in south European countries and black African populations, allele 2 at the DXS548 locus was present in 52% of non-related fragile-X-positive subjects, whereas it was very uncommon (9%) in non-related fragile-X-negative mentally retarded subjects. Therefore, a statistically significant linkage dis- equilibrium between the fragile Xchromosomes and allele 2 at the DXS548 locus was demonstrated (X 2 = 19.4; p = 0.002; df = 3). No disequilibrium with regard to the nor- mal (CGG)n repeats was detected. These results are consis- tent with the idea of at least one founder chromosome for the fragile Xsyndrome in our population, corresponding to one of the original predisposing chromosome in Indo-Euro- pean populations that could derive from an ancient African founder, as postulated by Chiurazzi et al. (1996c).
Kidney samples were quickly frozen in liquid nitrogen. Total RNA was isolated by TRIzol Reagent (Invitrogen, California, USA) methodology. First-strand cDNAs were synthesized using MML-V reverse transcriptase (Promega, Madison, USA). Real-time PCR was performed using TaqMan PCR assays as followed: IL-1b (Mm00434228_m1), IL-4 (Mm00445259_m1), IL-10 (Mm00439616_m1), Bcl-2 (Mm00477631_m1) and Bad (Mm00432042_m1) plus the housekeeper gene hypoxanthine guanine phosphoribosyltransferase (HPRT) (Mm00446968_m1) (Applied Biosystem, California, USA). Real-time PCR was per- formed for GATA-3, T-bet, MCP-1, HO-1, B1R and B2R expression using SYBR Green assay (Applied Biosystem). In this case, another specific SYBR Green HPRT was used. Sequences of oligonucleotides are depicted in Table 1. Cycling conditions were: 10 minutes at 95 uC followed by 45 cycles of 30 seconds at 95uC, 30 seconds at 58 uC and 30 seconds at 72uC. Relative quantification of mRNA levels was performed using the comparative threshold cycle method (described in detail in User Bulletin 2; PerkinElmer, Applied Biosystems, Branchburg, NJ, 1997). Briefly, the target gene amount was normalized to the endogenous reference (HPRT) and then compared against a calibrator (sample with the lowest expression, namely, sham-operated animals), using the formula 2 2DDCT . Hence, all data were expressed as an n-fold difference in relation to the expression of matched controls (sham). Analyses were performed with the Sequence Detection Software 1.9 (SDS).
Combining the information from both populations, four genomic regions harbored coincident QTLs for grain yield. The coincident genomic region at bin 1.09, spanned a physical position from 223.1 to 289.6 Mbp for MP1 and 217.0 - 284.1 Mbp for MP2, with QTLs showing constant effect across water stress and control conditions. In this region, Almeida et al. (2013) identified a meta-QTL (276.0 - 285.3 Mbp) integrating three QTLs for GY under water stress and one QTL for well-watered using three maize subtropical bi-parental populations. A candidate gene at position 285.3 Mbp was associated with ABA metabolites in the silk organ in a panel of 350 maize lines, the significant SNP PZB01403.4 was located inside the predicted gene GRMZM2G124260, which encodes the enzyme aldehyde oxidase (ZmAO3) (Setter et al. 2011). ZmAO3 is closely related to rice and Arabidopsis aldehyde oxidases that are involved in metabolic pathway of abscisic acid (ABA) (Ibdah et al. 2009; Setter et al. 2011). ABA is a central regulator of diverse responses of plants to environmental stresses, integrating the molecular signals after stress perception (Tran et al. 2007). Water deficiency increases ABA concentration in reproductive tissues negatively influencing the seed development. The exogenous ABA application decreases the growth of the seed and cell division in endosperm in the first days after pollination before the starch synthesis stage (Setter and Parra 2010).
All experimental protocols were reviewed and approved by the IACUC committee at Memorial Sloan-Kettering Cancer Center. Male C57BL/6J and RAG mice based on the same genetic background (B6.129S7-Rag1tm1Mom/J) were purchased from Jackson Laboratories (Bar Harbor, Maine) and maintained in a temperature and light controlled environment. Previous studies have shown that a diet high in fat (60% Kcal from fat) in these animals reliably results in moderate obesity as compared to animals fed a normal chow or low fat diet and that this model is a useful analog to diet induced (rather than genetic) obesity in humans . Therefore, in order to induce diet-induced obesity (DIO), wild-type and RAG mice were maintained on a high fat diet (60% kcal from fat; W.F Fisher & Son, Inc., NJ) beginning at 6 weeks of age ad libitum for 8–10 weeks. Age-matched control male wild-type or RAG mice were maintained on a normal chow diet (13% kcal from fat; Purina PicoLab Rodent Diet 20, W.F Fisher & Son) for the same period of time. At the conclusion of the experiment, animals were weighed using a digital scale (Sartorius, Bradford, MA), and a 12-hour fasting blood draw was performed from the retro-orbital sinus. Serum glucose, cholesterol, and triglyceride levels were analyzed using standard assays (ALX laboratories (New York, NY).
To identify candidate genes for expansion volume and other popcorn quality traits, we based our analysis on kernel physiochemical characteristics affecting expansion volume, such as kernel size, shape, and density as well as kernel moisture, starch, protein, and fatty acid contents. The endosperm is the most important kernel component af- fecting popping, while starch is the major polymer involved in popcorn expansion. Popcorn kernels contain both vitre- ous (horny or hard) and opaque (floury or soft) endosperm. During popping, starch granules in the vitreous endosperm are highly expanded and responsible for flake formation, whereas starch granules in the opaque endosperm appear to undergo little change. Acting as a pressure vessel during heating, the pericarp gives popcorn its distinct popping ability. The pericarp is the primary source of fiber in the popcorn kernel, while the germ (embryo) is the primary source of lipids. Other than fracturing the pericarp, popping does not substantially alter either the germ or pericarp. In general, small- to medium kernel size (lower 100-kernel weight) and greater kernel sphericity, kernel density, ratio of vitreous to opaque endosperm, and linoleic acid, oleic acid, and a-zein protein levels are associated with greater expansion volume. Pericarp damage and thickness also greatly affect expansion volume (Sweley et al., 2013).
Six isozyme systems (ACP, G6PDH, IDH, PGI, PGM and SKDH) codifying for seven polymorphic loci (Acp-2, G6pdh-1, Idh-1, Pgi-2, Pgm-1, Pgm-2 and Skdh-1) were investigated for inheritance and gametic disequilibriumin Cecropia pachystachya Trec. Mendelian inheritance was confirmed for all available loci. Significant segregation deviations from expected ratio 1:1 were detected only in one family from heterozygous tree. Linkagedisequilibrium was examined for 21 pairs of allozyme loci. No linkagedisequilibrium was detected in the pairs of loci studied. These loci can be used in subsequent mating system, genetic diversity and structure studies of C. pachystachya.
Fig. 4: modulation of TNF-α results in decreased expression of CCR5 by CD8+ cells in T. cruzi-infected mice. C3H/He mice were infected with 100 blood trypomastigotes of the Colombian strain of T. cruzi. After 14 days post of infection (dpi) the animals were treated with 10 µg of anti-human TNF-α blocking antibody (black bars) or vehicle (striped bars), every 48 h during 14 days. The animals were anesthetized, blood was collected at 32 dpi. Representative flow-cytometry plot shows decreased CCR5 expression in PBMC of anti-TNF-α-treated infected mice (A). The mean fluorescence intensity (MFI) confirms this finding (B). Vertical lines represent the standard deviations of the means of the re- sults obtained from five mice. Asterisks indicate p < 0.05, anti-TNF-α-treated (black bars) in relation to vehicle-injected controls (striped bars). Representative flow-cytometry plots (C) of PBMC lymphocytes (gate R1) showing CD4 + and CD8 + cells among CCR5 + lymphocytes (gate R1