Genome‐wide Association Study and Follow‐up Analysis of Adiposity Traits in Hispanic Americans: The IRAS Family Study

We investigated candidate genomic regions associated with computed tomography (CT)–derived measures of adiposity in Hispanics from the Insulin Resistance Atherosclerosis Study Family Study (IRASFS). In 1,190 Hispanic individuals from 92 families 3 from the San Luis Valley, Colorado and San Antonio, Texas, we measured CT‐derived visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and visceral:subcutaneous ratio (VSR). A genome‐wide association study (GWAS) was completed using the Illumina HumanHap 300 BeadChip (～317K single‐nucleotide polymorphisms (SNPs)) in 229 individuals from the San Antonio site (stage 1). In total, 297 SNPs with evidence for association with VAT, SAT, or VSR, adjusting for age and sex (P < 0.001), were genotyped in the remaining 961 Hispanic samples. The entire Hispanic cohort (n = 1,190) was then tested for association, adjusting for age, sex, site of recruitment, and admixture estimates (stage 2). In stage 3, additional SNPs were genotyped in four genic regions showing evidence of association in stage 2. Several SNPs were associated in the GWAS (P < 1 × 10^?5) and were confirmed to be significantly associated in the entire Hispanic cohort (P < 0.01), including: rs7543757 for VAT, rs4754373 and rs11212913 for SAT, and rs4541696 and rs4134351 for VSR. Numerous SNPs were associated with multiple adiposity phenotypes. Targeted analysis of four genes whose SNPs were significant in stage 2 suggests candidate genes for influencing the distribution (RGS6) and amount of adiposity (NGEF). Several candidate loci, including RGS6 and NGEF, are associated with CT‐derived adipose fat measures in Hispanic Americans in a three‐stage genetic association study.     

Convergent evolution in the genetic basis of Müllerian mimicry in heliconius butterflies

The neotropical butterflies Heliconius melpomene and H. erato are Müllerian mimics that display the same warningly colored wing patterns in local populations, yet pattern diversity between geographic regions. Linkage mapping has previously shown convergent red wing phenotypes in these species are controlled by loci on homologous chromosomes. Here, AFLP bulk segregant analysis using H. melpomene crosses identified genetic markers tightly linked to two red wing-patterning loci. These markers were used to screen a H. melpomene BAC library and a tile path was assembled spanning one locus completely and part of the second. Concurrently, a similar strategy was used to identify a BAC clone tightly linked to the locus controlling the mimetic red wing phenotypes in H. erato. A methionine rich storage protein (MRSP) gene was identified within this BAC clone, and comparative genetic mapping shows red wing color loci are in homologous regions of the genome of H. erato and H. melpomene. Subtle differences in these convergent phenotypes imply they evolved independently using somewhat different developmental routes, but are nonetheless regulated by the same switch locus. Genetic mapping of MRSP in a third related species, the “tiger” patterned H. numata, has no association with wing patterning and shows no evidence for genomic translocation of wing-patterning loci.     

Right-hand-side updating for fast computing of genomic breeding values

Background

Since both the number of SNPs (single nucleotide polymorphisms) used in genomic prediction and the number of individuals used in training datasets are rapidly increasing, there is an increasing need to improve the efficiency of genomic prediction models in terms of computing time and memory (RAM) required.

Methods

In this paper, two alternative algorithms for genomic prediction are presented that replace the originally suggested residual updating algorithm, without affecting the estimates. The first alternative algorithm continues to use residual updating, but takes advantage of the characteristic that the predictor variables in the model (i.e. the SNP genotypes) take only three different values, and is therefore termed “improved residual updating”. The second alternative algorithm, here termed “right-hand-side updating” (RHS-updating), extends the idea of improved residual updating across multiple SNPs. The alternative algorithms can be implemented for a range of different genomic predictions models, including random regression BLUP (best linear unbiased prediction) and most Bayesian genomic prediction models. To test the required computing time and RAM, both alternative algorithms were implemented in a Bayesian stochastic search variable selection model.

Results

Compared to the original algorithm, the improved residual updating algorithm reduced CPU time by 35.3 to 43.3%, without changing memory requirements. The RHS-updating algorithm reduced CPU time by 74.5 to 93.0% and memory requirements by 13.1 to 66.4% compared to the original algorithm.

Conclusions

The presented RHS-updating algorithm provides an interesting alternative to reduce both computing time and memory requirements for a range of genomic prediction models.     

Gene Expression Profiling as a Tool for Positional Cloning of Genes-Shortcut or the Longest Way Round

The identification of quantitative trait loci, QTL, in arthritis animal models is a straight forward process. However, to identify the underlying genes is a great challenge. One strategy frequently used, is to combine QTL analysis with genomic/proteomic screens. This has resulted in a number of publications where carefully performed genomic analyses present likely candidate genes for their respective QTL´s. However, seldom the findings are reconnected to the QTL controlled phenotypes. In this review, we use our own data as an illustrative example that “very likely candidate genes” identified by genomic/proteomics is not necessarily the same as true QTL underlying genes.     

Susceptibility loci revealed for bovine respiratory disease complex in pre-weaned holstein calves

Background

Bovine respiratory disease complex (BRDC) is an infectious disease of cattle that is caused by a combination of viral and/or bacterial pathogens. Selection for cattle with reduced susceptibility to respiratory disease would provide a permanent tool for reducing the prevalence of BRDC. The objective of this study was to identify BRDC susceptibility loci in pre-weaned Holstein calves as a prerequisite to using genetic improvement as a tool for decreasing the prevalence of BRDC. High density SNP genotyping with the Illumina BovineHD BeadChip was conducted on 1257 male and 757 female Holstein calves from California (CA), and 767 calves identified as female from New Mexico (NM). Of these, 1382 were classified as BRDC cases, and 1396 were classified as controls, with all phenotypes assigned using the McGuirk health scoring system. During the acquisition of blood for DNA isolation, two deep pharyngeal and one mid-nasal diagnostic swab were obtained from each calf for the identification of bacterial and viral pathogens. Genome-wide association analyses were conducted using four analytical approaches (EIGENSTRAT, EMMAX-GRM, GBLUP and FvR). The most strongly associated SNPs from each individual analysis were ranked and evaluated for concordance. The heritability of susceptibility to BRDC in pre-weaned Holstein calves was estimated.

Results

The four statistical approaches produced highly concordant results for 373 top ranked SNPs that defined 126 chromosomal regions for the CA population. Similarly, in NM, 370 SNPs defined 138 genomic regions that were identified by all four approaches. When the two populations were combined (i.e., CA + NM) and analyzed, 324 SNPs defined 116 genomic regions that were associated with BRDC across all analytical methods. Heritability estimates for BRDC were 21% for both CA and NM as individual populations, but declined to 13% when the populations were combined.

Conclusions

Four analytical approaches utilizing both single and multi-marker association methods revealed common genomic regions associated with BRDC susceptibility that can be further characterized and used for genomic selection. Moderate heritability estimates were observed for BRDC susceptibility in pre-weaned Holstein calves, thereby supporting the application of genomic selection to reduce the prevalence of BRDC in U.S. Holsteins.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1164) contains supplementary material, which is available to authorized users.     

Polymorphic Admixture Typing in Human Ethnic Populations

A panel of 257 RFLP loci was selected on the basis of high heterozygosity in Caucasian DNA surveys and equivalent spacing throughout the human genome. Probes from each locus were used in a Southern blot survey of allele frequency distribution for four human ethnic groups: Caucasian, African American, Asian (Chinese), and American Indian (Cheyenne). Nearly all RFLP loci were polymorphic in each group, albeit with a broad range of differing allele frequencies (δ). The distribution of frequency differences (δ values) was used for three purposes: (1) to provide estimates for genetic distance (differentiation) among these ethnic groups, (2) to revisit with a large data set the proportion of human genetic variation attributable to differentiation within ethnic groups, and (3) to identify loci with high δ values between recently admixed populations of use in mapping by admixture linkage disequilibrium (MALD). Although most markers display significant allele frequency differences between ethnic groups, the overall genetic distances between ethnic groups were small (.066–.098), and <10% of the measured overall molecular genetic diversity in these human samples can be attributed to “racial” differentiation. The median δ values for pairwise comparisons between groups fell between .15 and .20, permitting identification of highly informative RFLP loci for MALD disease association studies.     

Evaluation of Group Genetic Ancestry of Populations from Philadelphia and Dakar in the Context of Sex-Biased Admixture in the Americas

Background

Population history can be reflected in group genetic ancestry, where genomic variation captured by the mitochondrial DNA (mtDNA) and non-recombining portion of the Y chromosome (NRY) can separate female- and male-specific admixture processes. Genetic ancestry may influence genetic association studies due to differences in individual admixture within recently admixed populations like African Americans.

Principal Findings

We evaluated the genetic ancestry of Senegalese as well as European Americans and African Americans from Philadelphia. Senegalese mtDNA consisted of ∼12% U haplotypes (U6 and U5b1b haplotypes, common in North Africa) while the NRY haplotypes belonged solely to haplogroup E. In Philadelphia, we observed varying degrees of admixture. While African Americans have 9–10% mtDNAs and ∼31% NRYs of European origin, these results are not mirrored in the mtDNA/NRY pools of European Americans: they have less than 7% mtDNAs and less than 2% NRYs from non-European sources. Additionally, there is <2% Native American contribution to Philadelphian African American ancestry and the admixture from combined mtDNA/NRY estimates is consistent with the admixture derived from autosomal genetic data. To further dissect these estimates, we have analyzed our samples in the context of different demographic groups in the Americas.

Conclusions

We found that sex-biased admixture in African-derived populations is present throughout the Americas, with continual influence of European males, while Native American females contribute mainly to populations of the Caribbean and South America. The high non-European female contribution to the pool of European-derived populations is consistently characteristic of Iberian colonization. These data suggest that genomic data correlate well with historical records of colonization in the Americas.     

Amplification Biases and Consistent Recovery of Loci in a Double-Digest RAD-seq Protocol

A growing variety of “genotype-by-sequencing” (GBS) methods use restriction enzymes and high throughput DNA sequencing to generate data for a subset of genomic loci, allowing the simultaneous discovery and genotyping of thousands of polymorphisms in a set of multiplexed samples. We evaluated a “double-digest” restriction-site associated DNA sequencing (ddRAD-seq) protocol by 1) comparing results for a zebra finch (Taeniopygia guttata) sample with in silico predictions from the zebra finch reference genome; 2) assessing data quality for a population sample of indigobirds (Vidua spp.); and 3) testing for consistent recovery of loci across multiple samples and sequencing runs. Comparison with in silico predictions revealed that 1) over 90% of predicted, single-copy loci in our targeted size range (178–328 bp) were recovered; 2) short restriction fragments (38–178 bp) were carried through the size selection step and sequenced at appreciable depth, generating unexpected but nonetheless useful data; 3) amplification bias favored shorter, GC-rich fragments, contributing to among locus variation in sequencing depth that was strongly correlated across samples; 4) our use of restriction enzymes with a GC-rich recognition sequence resulted in an up to four-fold overrepresentation of GC-rich portions of the genome; and 5) star activity (i.e., non-specific cutting) resulted in thousands of “extra” loci sequenced at low depth. Results for three species of indigobirds show that a common set of thousands of loci can be consistently recovered across both individual samples and sequencing runs. In a run with 46 samples, we genotyped 5,996 loci in all individuals and 9,833 loci in 42 or more individuals, resulting in <1% missing data for the larger data set. We compare our approach to similar methods and discuss the range of factors (fragment library preparation, natural genetic variation, bioinformatics) influencing the recovery of a consistent set of loci among samples.     

Shared genetic loci between depression and cardiometabolic traits

Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402–776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.     

Mapping the Human Reference Genome’s Missing Sequence by Three-Way Admixture in Latino Genomes

A principal obstacle to completing maps and analyses of the human genome involves the genome’s “inaccessible” regions: sequences (often euchromatic and containing genes) that are isolated from the rest of the euchromatic genome by heterochromatin and other repeat-rich sequence. We describe a way to localize these sequences by using ancestry linkage disequilibrium in populations that derive ancestry from at least three continents, as is the case for Latinos. We used this approach to map the genomic locations of almost 20 megabases of sequence unlocalized or missing from the current human genome reference (NCBI Genome GRCh37)—a substantial fraction of the human genome’s remaining unmapped sequence. We show that the genomic locations of most sequences that originated from fosmids and larger clones can be admixture mapped in this way, by using publicly available whole-genome sequence data. Genome assembly efforts and future builds of the human genome reference will be strongly informed by this localization of genes and other euchromatic sequences that are embedded within highly repetitive pericentromeric regions.     

Nucleotide Polymorphism and Within-Gene Recombination in Daphnia magna and D. pulex, Two Cyclical Parthenogens

Theory predicts that partially asexual organisms may make the “best of both worlds”: for the most part, they avoid the costs of sexual reproduction, while still benefiting from an enhanced efficiency of selection compared to obligately asexual organisms. There is, however, little empirical data on partially asexual organisms to test this prediction. Here we examine patterns of nucleotide diversity at eight nuclear loci in continentwide samples of two species of cyclically parthenogenetic Daphnia to assess the effect of partial asexual reproduction on effective population size and amount of recombination. Both species have high nucleotide diversities and show abundant evidence for recombination, yielding large estimates of effective population sizes (300,000–600,000). This suggests that selection will act efficiently even on mutations with small selection coefficients. Divergence between the two species is less than one-tenth of previous estimates, which were derived using a mitochondrial molecular clock. As the two species investigated are among the most distantly related species of the genus, this suggests that the genus Daphnia may be considerably younger than previously thought. Daphnia has recently received increased attention because it is being developed as a model organism for ecological and evolutionary genomics. Our results confirm the attractiveness of Daphnia as a model organism, because the high nucleotide diversity and low linkage disequilibrium suggest that fine-scale mapping of genes affecting phenotypes through association studies should be feasible.     

Native American Admixture in the Quebec Founder Population

For years, studies of founder populations and genetic isolates represented the mainstream of genetic mapping in the effort to target genetic defects causing Mendelian disorders. The genetic homogeneity of such populations as well as relatively homogeneous environmental exposures were also seen as primary advantages in studies of genetic susceptibility loci that underlie complex diseases. European colonization of the St-Lawrence Valley by a small number of settlers, mainly from France, resulted in a founder effect reflected by the appearance of a number of population-specific disease-causing mutations in Quebec. The purported genetic homogeneity of this population was recently challenged by genealogical and genetic analyses. We studied one of the contributing factors to genetic heterogeneity, early Native American admixture that was never investigated in this population before. Consistent admixture estimates, in the order of one per cent, were obtained from genome-wide autosomal data using the ADMIXTURE and HAPMIX software, as well as with the fastIBD software evaluating the degree of the identity-by-descent between Quebec individuals and Native American populations. These genomic results correlated well with the genealogical estimates. Correlations are imperfect most likely because of incomplete records of Native founders’ origin in genealogical data. Although the overall degree of admixture is modest, it contributed to the enrichment of the population diversity and to its demographic stratification. Because admixture greatly varies among regions of Quebec and among individuals, it could have significantly affected the homogeneity of the population, which is of importance in mapping studies, especially when rare genetic susceptibility variants are in play.     

Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10^-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3.     

Genome Wide Association Study Identifies New Loci Associated with Undesired Coat Color Phenotypes in Saanen Goats

This paper reports a quantitative genetics and genomic analysis of undesirable coat color patterns in goats. Two undesirable coat colors have routinely been recorded for the past 15 years in French Saanen goats. One fifth of Saanen females have been phenotyped “pink” (8.0%) or “pink neck” (11.5%) and consequently have not been included in the breeding program as elite animals. Heritability of the binary “pink” and “pink neck” phenotype, estimated from 103,443 females was 0.26 for “pink” and 0.21 for “pink neck”. Genome wide association studies (using haplotypes or single SNPs) were implemented using a daughter design of 810 Saanen goats sired by 9 Artificial Insemination bucks genotyped with the goatSNP50 chip. A highly significant signal (-log10pvalue = 10.2) was associated with the “pink neck” phenotype on chromosome 11, suggesting the presence of a major gene. Highly significant signals for the “pink” phenotype were found on chromosomes 5 and 13 (-log10p values of 7.2 and, 7.7 respectively). The most significant SNP on chromosome 13 was in the ASIP gene region, well known for its association with coat color phenotypes. Nine significant signals were also found for both traits. The highest signal for each trait was detected by both single SNP and haplotype approaches, whereas the smaller signals were not consistently detected by the two methods. Altogether these results demonstrated a strong genetic control of the “pink” and “pink neck” phenotypes in French Saanen goats suggesting that SNP information could be used to identify and remove undesired colored animals from the breeding program.     

Modular Skeletal Evolution in Sticklebacks Is Controlled by Additive and Clustered Quantitative Trait Loci

Understanding the genetic architecture of evolutionary change remains a long-standing goal in biology. In vertebrates, skeletal evolution has contributed greatly to adaptation in body form and function in response to changing ecological variables like diet and predation. Here we use genome-wide linkage mapping in threespine stickleback fish to investigate the genetic architecture of evolved changes in many armor and trophic traits. We identify >100 quantitative trait loci (QTL) controlling the pattern of serially repeating skeletal elements, including gill rakers, teeth, branchial bones, jaws, median fin spines, and vertebrae. We use this large collection of QTL to address long-standing questions about the anatomical specificity, genetic dominance, and genomic clustering of loci controlling skeletal differences in evolving populations. We find that most QTL (76%) that influence serially repeating skeletal elements have anatomically regional effects. In addition, most QTL (71%) have at least partially additive effects, regardless of whether the QTL controls evolved loss or gain of skeletal elements. Finally, many QTL with high LOD scores cluster on chromosomes 4, 20, and 21. These results identify a modular system that can control highly specific aspects of skeletal form. Because of the general additivity and genomic clustering of major QTL, concerted changes in both protective armor and trophic traits may occur when sticklebacks inherit either marine or freshwater alleles at linked or possible “supergene” regions of the stickleback genome. Further study of these regions will help identify the molecular basis of both modular and coordinated changes in the vertebrate skeleton.     

Skin pigmentation,biogeographical ancestry and admixture mapping

Ancestry informative markers (AIMs) are genetic loci showing alleles with large frequency differences between populations. AIMs can be used to estimate biogeographical ancestry at the level of the population, subgroup (e.g. cases and controls) and individual. Ancestry estimates at both the subgroup and individual level can be directly instructive regarding the genetics of the phenotypes that differ qualitatively or in frequency between populations. These estimates can provide a compelling foundation for the use of admixture mapping (AM) methods to identify the genes underlying these traits. We present details of a panel of 34 AIMs and demonstrate how such studies can proceed, by using skin pigmentation as a model phenotype. We have genotyped these markers in two population samples with primarily African ancestry, viz. African Americans from Washington D.C. and an African Caribbean sample from Britain, and in a sample of European Americans from Pennsylvania. In the two African population samples, we observed significant correlations between estimates of individual ancestry and skin pigmentation as measured by reflectometry (R(2)=0.21, P<0.0001 for the African-American sample and R(2)=0.16, P<0.0001 for the British African-Caribbean sample). These correlations confirm the validity of the ancestry estimates and also indicate the high level of population structure related to admixture, a level that characterizes these populations and that is detectable by using other tests to identify genetic structure. We have also applied two methods of admixture mapping to test for the effects of three candidate genes (TYR, OCA2, MC1R) on pigmentation. We show that TYR and OCA2 have measurable effects on skin pigmentation differences between the west African and west European parental populations. This work indicates that it is possible to estimate the individual ancestry of a person based on DNA analysis with a reasonable number of well-defined genetic markers. The implications and applications of ancestry estimates in biomedical research are discussed.