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Biallelic loss-of-function variants in C19orf44 lead to retinal degeneration.

BACKGROUND: Inherited retinal diseases (IRDs) are a group of disorders often resulting in progressive vision loss, ultimately leading to blindness. A significant portion of their genetic causes remain unresolved, partly due to undiscovered disease-associated genes or variants. This study aimed to identify novel genetic links to IRDs. METHODS: All patients underwent comprehensive ophthalmological evaluation, including retinal imaging (fundus autofluorescence and macular optical coherence tomography) and electroretinogram testing. Whole exome sequencing and whole genome sequencing were performed on patients with clinically unsolved IRD, and data were analysed using an in-house pipeline to identify causal variants. Subsequently, Sanger sequencing was performed to confirm identified variants. RESULTS: Three unrelated patients from Europe, Middle East and East Asia were identified with unique late-onset retinal degeneration (Stargardt-like phenotype) associated with biallelic loss-of-function (LoF) variants in C19orf44 (HGNC: 26141), a gene of unknown function. The homozygous variant NM_032207.2:c.549_550del;p.Ser185Profs*2 was identified in two unrelated patients (European and Middle Eastern). Moreover, an East Asian patient had likely compound heterozygous LoF variants (NM_032207.2:c.1168C>T;p.Gln390*/c.976_977del;p.Leu326Lysfs*15). CONCLUSIONS: Our findings establish C19orf44 as a novel disease-causing gene for IRD with Stargardt-like phenotype, expanding the genetic landscape of retinal degeneration.

Humans↗

SpRY-mediated screens facilitate functional dissection of non-coding sequences at single-base resolution.

CRISPR mutagenesis screens conducted with SpCas9 and other nucleases have identified certain cis-regulatory elements and genetic variants but at a limited resolution due to the absence of protospacer adjacent motif (PAM) sequences. Here, leveraging the broad targeting scope of the near-PAMless SpRY variant, we have demonstrated that saturated SpRY mutagenesis and base editing screens can faithfully identify functional regulatory elements and essential genetic variants for target gene expression at single-base resolution. We further extended this methodology to investigate a genome-wide association study (GWAS) locus at 10q22.1 associated with a red blood cell trait, where we identified potential enhancers regulating HK1 gene expression, despite not all of these enhancers exhibiting typical chromatin signatures. More importantly, our saturated base editing screens pinpoint multiple causal variants within this locus that would otherwise be missed by Bayesian statistical fine-mapping. Our approach is generally applicable to functional interrogation of all non-coding genomic elements while complementing other high-coverage CRISPR screens.

Humans↗

Multi-ancestry multi-trait analysis reveals shared genetics across major psychiatric disorders and Alzheimer's disease.

The clinical overlap between major psychiatric disorders (MPDs) and Alzheimer's disease (AD) implicates complex shared etiology. Previous studies demonstrated that both diseases are genetically complex and highly heritable, suggesting that more endeavors are necessary to be made from the very bottom to understand their genetic basis. With the advance of post-genomic analysis, multi-ancestry meta-analysis allows the generalizability of the genetic architecture across different populations to uncover ancestry-specific variants, while multi-trait analysis enables the discovery of the co-colocalized risk genomic regions across diseases. Therefore, in this study, we leveraged published GWAS summary statistics from European, East Asian, Hispanic and African American populations to report schizophrenia, major depressive disorders, and Alzheimer's disease risk loci and further fine-mapping to credible sets with >95% PP inclusion of the causal variant. We distilled 2871 potential traits from publicly available and found 134 traits significantly genetically correlated with both MPDs and AD using batch LD score regression. We then prioritized the identified loci from multi-ancestry results for cross-trait colocalization analysis to assess shared genetic etiology and further nominated 2 colocalized loci across both conditions, including rs2532240 and rs6504163. In the end, we finalized our analysis by validation and functional inference of the underlying susceptibility genes as well as putative mechanisms using evidence from multiple resources, including FIVEx, Open Targets, and scQTLbase.

Humans↗

A variant of the HTRA1 gene increases susceptibility to age-related macular degeneration.

Age-related macular degeneration (AMD) is the most common cause of irreversible vision loss in the developed world and has a strong genetic predisposition. A locus at human chromosome 10q26 affects the risk of AMD, but the precise gene(s) have not been identified. We genotyped 581 AMD cases and 309 normal controls in a Caucasian cohort in Utah. We demonstrate that a single-nucleotide polymorphism, rs11200638, in the promoter region of HTRA1 is the most likely causal variant for AMD at 10q26 and is estimated to confer a population attributable risk of 49.3%. The HTRA1 gene encodes a secreted serine protease. Preliminary analysis of lymphocytes and retinal pigment epithelium from four AMD patients revealed that the risk allele was associated with elevated expression levels of HTRA1 mRNA and protein. We also found that drusen in the eyes of AMD patients were strongly immunolabeled with HTRA1 antibody. Together, these findings support a key role for HTRA1 in AMD susceptibility and identify a potential new pathway for AMD pathogenesis.

Aged↗

Adolescent depression as a systemic multimorbidity catalyst: integrated genetic and metabolic pathway analysis.

BACKGROUND: Although adolescent depression has been linked to individual chronic conditions, its broader role in shaping multimorbidity risk remains understudied. METHODS: A total of 87,562 UK Biobank participants were included, of whom 18,851 had documented adolescent depression. Cox proportional hazards models were applied to evaluate associations between adolescent depression and 24 chronic diseases, followed by stratified analyses by sex and age. Two-sample Mendelian randomization (MR) was then conducted to infer causality for diseases showing significant associations. Genomic colocalization analyses were performed using relevant GWAS data to identify shared causal variants. Mediation analyses were performed to detect possible mediating factors, including the frailty index, KDM biological age acceleration, allostatic load and 30 circulating biomarkers. RESULTS: Adolescent depression was associated with elevated risk for 12 chronic diseases, with strongest associations for hypothyroidism (HR = 1.29 [1.18-1.42]), diabetes (HR = 1.25 [1.13-1.38]) and chronic obstructive pulmonary disease (COPD) (HR = 1.74 [1.50-2.01]). Risks were notably higher among females and younger adults. MR confirmed likely causal relationships for hypothyroidism (OR = 1.45 [1.03-2.05]), diabetes (OR = 1.01 [1.01-1.02]) and COPD (OR = 1.04 [1.02-1.06]). Genomic colocalization revealed a shared genetic signal at the CDSN/PSORS1C1 locus between adolescent depression and hypothyroidism. Mediation analyses revealed disease-specific pathways: creatinine for hypothyroidism, testosterone for diabetes, KDM biological ageing for COPD and frailty index across all three conditions. CONCLUSIONS: Adolescent depression confers systemic vulnerability through genetic and metabolic mechanisms, with amplified risks in females and individuals aged ≤55 years. These findings support early, integrated interventions to mitigate long-term multimorbidity.

Humans↗

Pervasive context-dependent effects in the genetic architecture of complex and quantitative traits revealed by a powerful multiparent mapping population in yeast.

The genetic dissection of complex traits remains a major challenge in basic and biomedical research, but is essential for understanding the molecular pathways that shape phenotypic variation and for developing predictive models of trait and disease susceptibility. Here, we leverage a novel multiparent mapping population of budding yeast, CYClones, comprising 9,344 haploid strains derived from eight genetically diverse founders (~270,000 SNVs, ~ 1 per 44 bp, capturing 56% of common variants and 32% of all variants with a minor allele frequency greater than 0.005 in the global population), to identify quantitative trait loci (QTL) and systematically investigate the genetic architecture of growth rates across ten environmental conditions. In total, we identified 349 QTL (ranging from 18 to 49 QTL per growth condition) that explained between 60% and 100% of narrow sense heritability across traits. The high power and resolution of CYClones revealed that growth traits exhibited distinct, condition-specific genetic architectures with extensive allelic heterogeneity, where a QTL was the result of multiple tightly linked causal variants. We also observed pleiotropy among QTL with complex, trait-dependent allele effects that are also consistent with allelic heterogeneity. Genetic complexity varied widely, with some traits showing nearly Mendelian architectures, while others were highly polygenic. Introgressed loci played a prominent role in the landscape of growth rate QTL, including a QTL localized to a 2.4 kb interval in the PCA1 cadmium transporter that explains 72% of variation in cadmium resistance and is largely driven by an introgression, and a non-additive interaction between the GAL3 regulator and introgressed GAL1/7/10 alleles, extending a previously described three-locus GAL-pathway incompatibility to a four-locus interaction. In both cadmium and galactose conditions, we show that allelic variation at a small number of loci stratifies the population into regulatory or physiological subgroups, each with distinct genetic architectures, a specific manifestation of epistasis we term allele-dependent stratification. Collectively, our results provide novel insights into the genetics of growth rates in budding yeast, the architectural features of genetic complexity, and demonstrate that CYClones is a powerful platform for revealing the molecular basis of complex trait variation.

Quantitative Trait Loci↗

Association of a rare thyroglobulin gene microsatellite variant with autoimmune thyroid disease.

Genetic and environmental factors contribute to the development of Graves' disease and Hashimoto's thyroiditis. These diseases, although clinically distinct, share many immunological and histological features. Susceptibility genes for autoimmune thyroid disease (AITD) have been investigated, although only the human leukocyte antigen and cytotoxic T lymphocyte-associated antigen-4 gene regions have been consistently associated with disease. Recent data, however, have shown linkage and association of chromosome 8q24 (containing the thyroglobulin gene) to AITD. Therefore, we performed a case-control association study on patients with AITD and controls using previously associated markers (D8S284 and Tgms2). No differences in allele frequencies were observed between AITD cases and controls for D8S284. Compared with the three common alleles (frequencies >10%), the rare alleles of Tgms2 were increased (chi(2)= 10.6; P = 0.001) at Tgms2. This group included the 336-bp allele (increased in cases vs. controls: chi(2)= 24.97; P < 0.001), which has previously been reported to be associated with AITD. The rarity of this allele in the United Kingdom, however, precluded analysis in our family dataset. Although these findings may represent a random chance event, in view of previous reports of linkage and association of this gene region to AITD, this may be an example of a rare causal variant of a complex disease.

Adolescent↗

Dissecting the shared genetic architecture between migraine subtypes and cardiovascular diseases: a multi-layered genomic analysis.

BACKGROUND: Epidemiological studies have linked migraine to an increased risk of cardiovascular disease (CVD); however, the shared genetic basis and putative causal relationships between migraine subtypes and cardiovascular traits remain poorly understood. METHODS: Leveraging large-scale GWAS summary statistics for migraine phenotypes (overall migraine, migraine with aura [MA], and migraine without aura [MO]) from FinnGen R12, along with seven cardiovascular diseases from publicly available consortia, we conducted a multi-layered genetic analysis. This integrative framework encompassed genetic correlation [linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL)], cross-trait meta-analysis (CPASSOC and PLACO), Bayesian colocalization, summary-data-based Mendelian randomization (SMR) using GTEx v8 eQTL data, and bidirectional two-sample Mendelian randomization (MR). RESULTS: Significant genetic correlations were identified between migraine and multiple cardiovascular traits, with hypertension and coronary artery disease (CAD) showing the most robust associations. MA exhibited broader genetic overlap with cardiovascular diseases than MO, including a notably stronger correlation with ischemic stroke, whereas MO demonstrated a stronger correlation with hypertension. Cross-trait meta-analysis identified 160 pleiotropic loci across 17 of 21 trait pairs. Colocalization analysis confirmed 32 loci harboring shared causal variants, mapped to 13 candidate genes, of which 7 (PHACTR1, LRP1, SOX7, ABO, FHOD3, MEI1, XKR6) were further validated by SMR as exhibiting tissue-specific regulatory effects. Among these, PHACTR1 displayed the broadest pleiotropic profile across migraine phenotypes and vascular diseases. After MR-PRESSO outlier removal, bidirectional MR identified 10 MR-supported associations, two of which (genetic liability to hypertension on overall migraine, and CAD on MA) survived Bonferroni correction, all free of detectable horizontal pleiotropy. Genetic liability to hypertension was associated with increased migraine risk (OR&#x2009;=&#x2009;1.90, 95% CI 1.25-2.90, P&#x2009;=&#x2009;2.64&#x2009;&#xd7;&#x2009;10&#x207b;&#xb3;), atherosclerotic diseases showed subtype-specific effects (inverse for MO, positive for MA), and, in the reverse direction, migraine was associated with increased ischemic stroke risk. CONCLUSIONS: This study provides a comprehensive and systematic characterization of the shared genetic architecture between migraine subtypes and cardiovascular diseases. By identifying pleiotropic genes and bidirectional putative causal relationships with subtype-specific patterns, our findings carry implications for the development of targeted therapeutics and subtype-specific cardiovascular risk stratification.

Humans↗

High-resolution, genotype-free mapping of genetic variation with CRI-SPA-Map.

Genetic variation within species shapes phenotypes, but identifying the specific genes and variants that cause phenotypic differences is costly and challenging. Here, we introduce CRI-SPA-Map, a genetic mapping strategy combining CRISPR-Cas9 genome engineering, selective ploidy ablation (SPA), and high-throughput phenotyping for precise genetic mapping with or without genotyping in the yeast Saccharomyces cerevisiae. In CRI-SPA-Map, a donor strain carrying SPA machinery is mated to a genetically different recipient strain harboring a genome-integrated selectable cassette. In the resulting diploid, CRISPR-Cas9 cuts the cassette for replacement with DNA from the homologous donor chromosome. Donor chromosomes are then removed using SPA to yield haploid recombinant strains. To establish CRI-SPA-Map, we mated a W303 SPA strain to 92 strains from the BY4742 yeast knockout collection that carry gene deletion cassettes on the left arm of chromosome XIV and created 1,451 recombinant isolates. Whole-genome sequencing verified that deletion cassette replacement introduced short donor DNA tracts of variable length, resulting in a finely recombined mapping population. Using only the known location of the gene deletions, which marks where donor DNA is introduced, we identified a 6.5 kb-region shaping yeast growth. Further dissection of this region pinpointed two causal variants in two genes, MKT1 and SAL1. Engineering these variants alone and in combination revealed gene-by-environment interactions at both genes, as well as epistatic interactions between them that were in turn dependent on the environment. CRI-SPA-Map is a cost-effective strategy for creating high-resolution recombinant panels of yeast strains for identifying the genetic basis of phenotypic variation.

Journal Article↗

Interleukin-1 receptor antagonist haplotype associated with prostate cancer risk.

IL1-RN is an important anti-inflammatory cytokine that modulate the inflammation response by binding to IL1 receptors, and as a consequence inhibits the action of proinflammatory cytokines IL1alpha and IL1beta. In this study, we hypothesise that sequence variants in the IL1-RN gene are associated with prostate cancer risk. The study population, a population-based case-control study in Sweden, consisted of 1383 prostate cancer case patients and 779 control subjects. We first selected 18 sequence variants covering the IL1-RN gene and genotyped these single-nucleotide polymorphisms (SNPs) in 96 control subjects. Gene-specific haplotypes of IL1-RN were constructed and four haplotype-tagging single-nucleotide polymorphisms (htSNPs) were identified (rs878972, rs315934, rs3087263 and rs315951) that could uniquely describe >95% of the haplotypes. All study subjects were genotyped for the four htSNPs. No significant difference in genotype frequencies between cases and controls were observed for any of the four SNPs based on a multiplicative genetic model. Overall there was no significant difference in haplotype frequencies between cases and controls; however, the prevalence of the most common haplotype (ATGC) was significantly higher among cases (38.7%) compared to controls (33.5%) (haplotype-specific P = 0.009). Evaluation of the prostate cancer risk associated with carrying the 'ATGC' haplotype revealed that homozygous carriers were at significantly increased risk (odds ratio (OR) = 1.6, 95% confidence interval (CI) = 1.2-2.2), compared to noncarriers, while no significant association was found among subjects heterozygous for the haplotype (OR = 1.0, 95% CI = 0.8-1.2). Restricting analyses to advanced prostate cancer strengthened the association between the 'ATGC' haplotype and disease risk (OR for homozygous carriers vs noncarriers 1.8, 95% CI = 1.3-2.5). In conclusion, the results from this study support the hypothesis that inflammation has a role of in the development of prostate cancer, but further studies are needed to identify the causal variants in this region and to elucidate the biological mechanism for this association.

Aged↗

Association between estrogen receptor alpha gene variation and cardiovascular disease.

CONTEXT: Estrogen and related hormone therapies activate estrogen receptors, which in turn regulate genes for several cardiovascular disease (CVD) risk factors. Relatively little is known, however, about the impact of genetic variation in estrogen receptor alpha (ESR1) on CVD risk. OBJECTIVE: To investigate whether the ESR1 c.454-397T>C polymorphism is associated with CVD risk. DESIGN, SETTING, AND PARTICIPANTS: Prospective study of 1739 unrelated men and women from the population-based offspring cohort of the Framingham Heart Study, who were followed up from 1971 to 1998. MAIN OUTCOME MEASURES: Total atherosclerotic CVD events, defined as recognized or unrecognized myocardial infarction (MI), angina pectoris, coronary insufficiency, intermittent claudication, coronary heart disease death, or atherothrombotic stroke (n = 178); major atherosclerotic CVD, defined as recognized acute MI, coronary insufficiency, coronary heart disease death, or atherothrombotic stroke (n = 83); and recognized acute MI (n = 59). RESULTS: Twenty percent of participants (n = 352) were homozygous for the ESR1 c.454-397C allele. After adjustment for covariates (age, sex, body mass index, hypertension, diabetes mellitus, total cholesterol, high-density lipoprotein cholesterol, and cigarette smoking), the CC genotype was significantly associated with major atherosclerotic CVD, with an odds ratio of 2.0 (95% confidence interval [CI], 1.3-3.2; P =.004) compared with individuals with the CT or TT genotypes. Participants with the CC genotype had 3.0-fold greater odds of MI (95% CI, 1.7-5.2; P<.001) compared with those with the CT or TT genotype. The results remained significant when analyses were restricted to men; too few women had events to study them separately. CONCLUSIONS: Individuals with the common ESR1 c.454-397CC genotype have a substantial increase in risk of MI. Whether ESR1 c.454-397T>C is causally related to MI risk or in linkage disequilibrium with 1 or more causal variants remains to be determined. These findings support the importance of estrogen receptors in CVD susceptibility, especially in men. Estrogen receptor variation also has potential to explain recent conflicting data regarding the effects of hormone therapy on CVD susceptibility in women.

Cardiovascular Diseases↗

Genetic association between the PRKCH gene encoding protein kinase Ceta isozyme and rheumatoid arthritis in the Japanese population.

OBJECTIVE: Analyses of families with rheumatoid arthritis (RA) have suggested the presence of a putative susceptibility locus on chromosome 14q21-23. This large population-based genetic association study was undertaken to examine this region. METHODS: A 2-stage case-control association study of 950 unrelated Japanese patients with RA and 950 healthy controls was performed using >400 gene-based common single-nucleotide polymorphisms (SNPs). RESULTS: Multiple SNPs in the PRKCH gene encoding the eta isozyme of protein kinase C (PKCeta) showed significant single-locus disease associations, the most significant being SNP c.427+8134C>T (odds ratio 0.72, 95% confidence interval 0.62-0.83, P = 5.9 x 10(-5)). Each RA-associated SNP was consistently mapped to 3 distinct regions of strong linkage disequilibrium (i.e., linkage disequilibrium or haplotype blocks) in the PRKCH gene locus, suggesting that multiple causal variants influence disease susceptibility. Significant SNPs included a novel common missense polymorphism of the PRKCH gene, V374I (rs2230500), which lies within the ATP-binding site that is highly conserved among PKC superfamily members. In circulating lymphocytes, PRKCH messenger RNA was expressed at higher levels in resting T cells (CD4(+) or CD8(+)) than in B cells (CD19(+)) or monocytes (CD14(+)) and was significantly down-regulated through immune responses. CONCLUSION: Our results provide evidence of the involvement of PRKCH as a susceptibility gene for RA in the Japanese population. Dysregulation of PKCeta signal transduction pathway(s) may confer increased risk of RA through aberrant T cell-mediated autoimmune responses.

Adult↗

A Novel PTPN2 Isoform Differentially Regulates Immune Response.

Genome-wide association studies implicate the PTPN2 gene locus (18p11.21) in risk for several autoimmune diseases, including inflammatory bowel disease. Through genetic fine mapping, we identified the single-nucleotide polymorphism rs80262450 in the PTPN2 gene as the putative causal variant. Analysis of GTEx tissue samples and genetically engineered myeloid cell lines carrying risk and nonrisk alleles of rs80262450 demonstrated increased expression of the PTPN2 splice isoform 4 (PTPN2.4), suggesting that the rs80262450 enhances disease susceptibility by favoring production of PTPN2.4. Furthermore, we found that PTPN2.4 contains a nuclear export sequence (NES) that leads to its retention in the cytoplasm. Differential localization of PTPN2.4 isoform results in a distinct protein binding profile revealed by mass-spectrometry analysis, and its overexpression increased TNF-&#x3b1;. PTPN2.4 knockdown reduced pro-inflammatory cytokines in human macrophages. Mutations within the NES motif abolished the unique localization and function of PTPN2.4. Lastly, increased expression of PTPN2.4 was found in Crohn's disease tissues, demonstrating its involvement in the disease. Together, we identified the pathogenic isoform PTPN2.4 as a novel driver of intestinal inflammation and a potential target to attenuate inflammation in IBD.

Humans↗

Two-Stage sampling designs for gene association studies.

We consider two-stage case-control designs for testing associations between single nucleotide polymorphisms (SNPs) and disease, in which a subsample of subjects is used to select a panel of "tagging" SNPs that will be considered in the main study. We propose a pseudolikelihood [Pepe and Flemming, 1991: JASA 86:108-113] that combines the information from both the main study and the substudy to test the association with any polymorphism in the original set. SNP-tagging [Chapman et al., 2003: Hum Hered 56:18-31] and haplotype-tagging [Stram et al., 2003a; Hum Hered 55:27-36] approaches are compared. We show that the cost-efficiency of such a design for estimating the relative risk associated with the causal polymorphism can be considerably better than for a single-stage design, even if the causal polymorphism is not included in the tag-SNP set. We also consider the optimal selection of cases and controls in such designs and the relative efficiency for estimating the location of a causal variant in linkage disequilibrium mapping. Nevertheless, as the cost of high-volume genotyping plummets and haplotype tagging information from the International HapMap project [Gibbs et al., 2003; Nature 426:789-796] rapidly accumulates in public databases, such two-stage designs may soon become unnecessary.

Case-Control Studies↗

Accounting for haplotype uncertainty in matched association studies: a comparison of simple and flexible techniques.

Population-based case-control studies measuring associations between haplotypes of single nucleotide polymorphisms (SNPs) are increasingly popular, in part because haplotypes of a few "tagging" SNPs may serve as surrogates for variation in relatively large sections of the genome. Due to current technological limitations, haplotypes in cases and controls must be inferred from unphased genotypic data. Using individual-specific inferred haplotypes as covariates in standard epidemiologic analyses (e.g., conditional logistic regression) is an attractive analysis strategy, as it allows adjustment for nongenetic covariates, provides omnibus and haplotype-specific tests of association, and can estimate haplotype and haplotype x environment interaction effects. In principle, some adjustment for the uncertainty in inferred haplotypes should be made. Via simulation, we compare the performance (bias and mean squared error of haplotype and haplotype x environment interaction effect estimates) of several analytic strategies using inferred haplotypes in the context of matched case-control data. These strategies include using only the most likely haplotype assignment, the expectation substitution approach described by Stram et al. ([2003b] Hum. Hered. 55:179-190) and others, and an improper version of multiple imputation. For relatively uncomplicated haplotype structures and moderate haplotype relative risks (</=2), all methods performed comparably well (small bias with appropriately-sized confidence intervals). For larger relative risks, the most likely haplotype and multiple imputation strategies showed noticeable bias towards the null; the expectation substitution strategy still performed well. When there was more uncertainty in the inferred haplotypes, the most likely and multiple imputation strategies showed even more bias towards the null, while the expectation substitution method had slightly smaller than nominal confidence intervals for larger relative risks (>/=5). An application to progesterone-receptor haplotypes and endometrial cancer further illustrates that the performance of all these methods depends on how well the observed haplotypes "tag" the unobserved causal variant.

Algorithms↗

A QTL affecting daily feed intake maps to Chromosome 2 in pigs.

Our understanding of the molecular genetic basis of several key performance traits in pigs has been significantly advanced through the quantitative trait loci (QTL) mapping approach. However, in contrast to growth and fatness traits, the genetic basis of feed intake traits has rarely been investigated through QTL mapping. Since feed intake is an important component of efficient pig production, the identification of QTL affecting feed intake may lead to the identification of genetic markers that can be used in selection programs. In this study a QTL analysis for feed intake, feeding behavior, and growth traits was performed in an F2 population derived from a cross between Chinese Meishan and European Large White pigs. A QTL with a significant effect on daily feed intake (DFI) was identified on Sus scrofa Chromosome 2 (SSC2). A number of suggestive QTL with effects on daily gain, feed conversion, and feeding behavior traits were also located. The significant QTL lies close to a previously identified mutation in the insulin-like growth factor 2 gene (IGF2) that affects carcass composition traits, although the IGF2 mutation is not segregating in the populations analyzed in the current study. Therefore, a distinct causal variant may exist on the P arm of SSC2 with an effect on feed intake.

Animals↗

Complete nucleotide sequence and genomic structure of the human NRAMP1 gene region on chromosome region 2q35.

Several lines of independent evidence suggest that human Natural Resistance Associated Macrophage Protein 1 gene (NRAMP1) is an important regulator of susceptibility to infectious diseases caused by certain intracellular pathogens. Here, we report the nucleotide sequence of 32198 bp of genomic DNA overlapping NRAMP1 on chromosomal region 2q35. The NRAMP1 gene spans 13604 bp. The gene and its 5' genomic region are highly enriched for DNA repeat sequences. A second gene was identified in the immediate vicinity of NRAMP1 and was tentatively named Nuclear LIM Interactor-Interacting Factor (NLI-IF) by analogy to its closest ortholog. The human NLI-IF gene begins 4721 bp downstream of the NRAMP1 stop codon and is composed of seven exons varying in size from 57 bp to 1644 bp. The gene gives rise to a 2655-bp mRNA transcript that contains a 783-bp open reading frame. The predicted molecular weight of the 261-amino acid NLI-IF protein is 29.2 kDa. Several putative gene regulatory elements were identified in the 5' upstream region of NLI-IF, including consensus binding sequences for Sp1, AP-2, NF-kappa B, and PU 1. The NLI-IF amino acid sequence has homology to proteins that have a high degree of homology with the NLI-interacting factor from Gallus gallus and are found in divergent species ranging from yeast to plants. NLI-IF is part of a human gene family encoding four related proteins of unknown function. Northern blot analysis of 15 different human tissues revealed a 2.6-kb NLI-IF mRNA that was ubiquitously expressed, but at varying levels. A second transcript with estimated size of 7 kb was expressed only in the placenta. Our data provide new sequence information about the NRAMP1 gene region that will be useful in the search for genetic variants causally involved in altered susceptibility to infectious diseases.

Amino Acid Sequence↗

Estimation of single nucleotide polymorphism allele frequency in DNA pools by using Pyrosequencing.

Positional cloning of genes underlying complex diseases, such as type 2 diabetes mellitus (T2DM), typically follows a two-tiered process in which a chromosomal region is first identified by genome-wide linkage scanning, followed by association analyses using densely spaced single nucleotide polymorphic markers to identify the causal variant(s). The success of genome-wide single nucleotide polymorphism (SNP) detection has resulted in a vast number of potential markers available for use in the construction of such dense SNP maps. However, the cost of genotyping large numbers of SNPs in appropriately sized samples is nearly prohibitive. We have explored pooled DNA genotyping as a means of identifying differences in allele frequency between pools of individuals with T2DM and unaffected controls by using Pyrosequencing technology. We found that allele frequencies in pooled DNA were strongly correlated with those in individuals (r=0.99, P<0.0001) across a wide range of allele frequencies (0.02-0.50). We further investigated the sensitivity of this method to detect allele frequency differences between contrived pools, also over a wide range of allele frequencies. We found that Pyrosequencing was able to detect an allele frequency difference of less than 2% between pools, indicating that this method may be sensitive enough for use in association studies involving complex diseases where a small difference in allele frequency between cases and controls is expected.

Base Sequence↗