SNP Location Research Articles

Micro-capture-C in vessel wall cell types identifies mechanisms underlying coronary artery disease susceptibility loci

Abstract Genetics is estimated to account for 50% of Coronary Artery Disease (CAD) risk. Genome-Wide Association Studies (GWAS) have revealed 100s of genomic loci which are associated with CAD (1). However, moving from GWAS signals to causal genes has proved challenging, slowing progress in developing interventions for CAD and other diseases. The greatest challenge in interpreting GWAS data is that only 10% of variants are in protein-coding regions and 90% are in "non-coding" genomic regions. Many of these non-coding variants are found in regulatory elements such as enhancers. Enhancers are distal regulatory elements that bind transcription factors and regulate genes up to 1 million base pairs away. This is achieved by DNA looping bringing enhancers into physical proximity with target genes. However, it is not possible to predict which gene(s) a given enhancer will regulate based on genomic location alone. We aimed to develop a generalisable workflow to solve CAD GWAS signals accurately and sensitively, by identifying causal enhancer SNPs and linking them mechanistically to output genes in a cell-type specific manner. We combined cell-specific epigenomic mapping with machine learning to prioritise 21,959 SNPs from 861 candidate CAD loci, in endothelial cells (HUVECs) and smooth muscle cells (HCASMCs). Micro-Capture-C (MCC) was used to resolve enhancer-promoter interactions at base-pair resolution (2). MNase footprinting determined differential transcription factor binding at specific enhancer SNPs. In HCASMCs, 20 putative enhancers containing CAD SNPs were found to interact with 32 genes, and in HUVECs 25 enhancers interacted with 48 genes. These genes were enriched for pathways including TGFb signalling, RUNX3 activity, and MAPK6/MAPK4 signalling. To prove causality at specific loci, heterozygous SNPs were identified in the individual primary cell lines. The interaction frequency at these elements was statistically compared between risk and non-risk alleles. For example, at the 9p21.3 locus, an enhancer containing a non-risk T allele was found to interact more strongly with the CDKN2B gene, compared to the risk G allele. Interestingly, this imbalance between allele interaction was potentiated by stimulation with TGFb, a key mediator in atherosclerosis. Furthermore, the transcription factor footprint at the SNP location was altered by the risk allele, indicating the mechanistic cause of the CAD-associated change in CDKN2B expression. We demonstrate a combined computational and experimental approach to identify causal non-coding variants in CAD risk loci, at scale. Among the key outputs of this study is the identification of the risk variant (rs1537373), output gene (CDKN2B), and specific cell type (HCASMC) underlying the 9p21.3 locus association with CAD risk. Using this approach to translate GWAS signals into cell-type specific outputs genes, will lead to a better understanding of the pathogenesis of CAD, and new therapeutic opportunities.

Exome-based new allele-specific PCR markers and transferability for sodicity tolerance in bread wheat (Triticum aestivum L.).

Targeted exome-based genotype by sequencing (t-GBS), a sequencing technology that tags SNPs and haplotypes in gene-rich regions was used in previous genome-wide association studies (GWAS) for sodicity tolerance in bread wheat. Thirty-nine novel SNPs including 18 haplotypes for yield and yield-components were identified. The present study aimed at developing SNP-derived markers by precisely locating new SNPs on ~180 bp allelic sequence of t-GBS, marker validation, and SNP functional characterization based on its exonic location. We identified unknown locations of significant SNPs/haplotypes by aligning allelic sequences on to IWGSC RefSeqv1.0 on respective chromosomes. Eighteen out of the target 39 SNP locations fulfilled the criteria for producing PCR markers, among which only eight produced polymorphic signals. These eight markers associated with yield, plants m-2, heads m-2, and harvest index, including a pleiotropic marker for yield, harvest index, and grains/head were validated for its amplification efficiency and phenotypic effects in focused identification germplasm strategy (FIGS) wheat set and a doubled haploid (DH) population (Scepter/IG107116). The phenotypic variation explained by these markers are in the range of 4.1-37.6 in the FIGS population. High throughput PCR-based genotyping using new markers and association with phenotypes in FIGS wheat set and DH population validated the effect of functional SNP on closely associated genes-calcineurin B-like- and dirigent protein, basic helix-loop-helix (BHLH-), plant homeodomain (PHD-) and helix-turn-helix myeloblastosis (HTH myb) type -transcription factor. Further, genome-wide SNP annotation using SnpEff tool confirmed that these SNPs are in gene regulatory regions (upstream, 3'-UTR, and intron) modifying gene expression and protein-coding. This integrated approach of marker design for t-GBS alleles, SNP functional annotation, and high-throughput genotyping of functional SNP offers translation solutions across crops and complex traits in crop improvement programs.

A Comparison of Three Circular Mitochondrial Genomes of Fagus sylvatica from Germany and Poland Reveals Low Variation and Complete Identity of the Gene Space

Similar to chloroplast loci, mitochondrial markers are frequently used for genotyping, phylogenetic studies, and population genetics, as they are easily amplified due to their multiple copies per cell. In a recent study, it was revealed that the chloroplast offers little variation for this purpose in central European populations of beech. Thus, it was the aim of this study to elucidate, if mitochondrial sequences might offer an alternative, or whether they are similarly conserved in central Europe. For this purpose, a circular mitochondrial genome sequence from the more than 300-year-old beech reference individual Bhaga from the German National Park Kellerwald-Edersee was assembled using long and short reads and compared to an individual from the Jamy Nature Reserve in Poland and a recently published mitochondrial genome from eastern Germany. The mitochondrial genome of Bhaga was 504,730 bp, while the mitochondrial genomes of the other two individuals were 15 bases shorter, due to seven indel locations, with four having more bases in Bhaga and three locations having one base less in Bhaga. In addition, 19 SNP locations were found, none of which were inside genes. In these SNP locations, 17 bases were different in Bhaga, as compared to the other two genomes, while 2 SNP locations had the same base in Bhaga and the Polish individual. While these figures are slightly higher than for the chloroplast genome, the comparison confirms the low degree of genetic divergence in organelle DNA of beech in central Europe, suggesting the colonisation from a common gene pool after the Weichsel Glaciation. The mitochondrial genome might have limited use for population studies in central Europe, but once mitochondrial genomes from glacial refugia become available, it might be suitable to pinpoint the origin of migration for the re-colonising beech population.

A unified local objective function for optimally selecting SNPs on arrays for agricultural genomics applications.

Over the years, ad-hoc procedures were used for designing SNP arrays, but the procedures and strategies varied considerably case by case. Recently, a multiple-objective, local optimization (MOLO) algorithm was proposed to select SNPs for SNP arrays, which maximizes the adjusted SNP information (E score) under multiple constraints, e.g. on MAF, uniformness of SNP locations (U score), the inclusion of obligatory SNPs and the number and size of gaps. In the MOLO, each chromosome is split into equally spaced segments and local optima are selected as the SNPs having the highest adjusted E score within each segment, conditional on the presence of obligatory SNPs. The computation of the adjusted E score, however, is empirical, and it does not scale well between the uniformness of SNP locations and SNP informativeness. In addition, the MOLO objective function does not accommodate the selection of uniformly distributed SNPs. In the present study, we proposed a unified local function for optimally selecting SNPs, as an amendment to the MOLO algorithm. This new local function takes scalable weights between the uniformness and informativeness of SNPs, which allows the selection of SNPs under varied scenarios. The results showed that the weighting between the U and the E scores led to a higher imputation concordance rate than the U score or E score alone. The results from the evaluation of six commercial bovine SNP chips further confirmed this conclusion.

A New Method of Gene Information Vectorization and its Application in Similarity Search

With the development of the Human Genome Project, more and more biological sequence data are generated, and the analysis and processing of these sequence data have promoted the development of bioinformatics. Sequence similarity analysis is the basis of bioinformatics, through which we can use the information of known sequences to study the structure, function and evolutionary relationship of unknown new sequences. This paper performs data compression and retrieval on the genome database based on the dbSNP information of DNA. According to the rule of determining a protein by three bases, the amino acid characters are determined, and the redundant information is removed by using the dbSNP information. It is the first time to propose the construction of a new compressed form of biological sequence structure, which can reflect the strong correlation between the SNP location information and SNP in each sample in the genome. Finally, this paper constructs a complete biological sequence approximate neighbor query system, which can not only greatly reduce the storage and computing overhead, but also improve the query efficiency under the condition of ensuring the retrieval accuracy. The accuracy and scalability of this method are verified by experiments on a large data set of gene database.

Differentiating between Hyperdiploidy and Pseudo-Hyperdiploidy in B-Lymphoblastic Leukemia Utilizing Low-Coverage Mate-Pair Sequencing

Purpose: B-cell acute lymphoblastic leukemia/lymphoma (B-ALL/LBL) represents the most common childhood malignancy. Classification of recurrent genetic abnormalities in B-ALL/LBL is essential for risk stratification and patient management. Observed in approximately 5% of B-ALL/LBL cases, hypodiploidy is considered a poor prognostic finding and can be further characterized as near-haploidy (24-31 chromosomes), low hypodiploidy (32-39 chromosomes) and high hypodiploidy (40-43 chromosomes). Importantly, masked hypodiploid clones that have undergone endoreduplication can be mischaracterized as hyperdiploidy, a favorable prognostic finding in B-ALL/LBL. These "doubled" hypodiploid clones are termed pseudo-hyperdiploid and their accurate detection is critical. Mate-pair sequencing (MPseq) is a next-generation sequencing (NGS) technology designed to sequence larger DNA fragments (2000-5000bp) than paired-end sequencing. This allows for the detection of large genetic rearrangements (e.g. translocations, inversions, etc.) and copy number variants (CNVs) at a high resolution with low base coverage. It has demonstrated particular clinical utility for genetic characterization of hematologic malignancies. To expand the role of MPseq in the evaluation of hematologic neoplasms, we aimed to improve the analysis of MPseq results to allow for the detection of copy-neutral loss of heterozygosity (cnLOH) that would enable the differentiation between hyperdiploid and pseudo-hyperdiploid clones. Methods: A new algorithm was applied that statistically analyzes common SNP locations in MPseq data in order to detect both cnLOH regions, and provides global heterozygosity levels at a resolution that allows for the detection of hypodiploidy. This method accounts for the low base-coverage of MPseq data (<10x) in order to provide the highest possible accuracy and precision without increasing cost by requiring changes to the input or sequencing requirements. The algorithm was applied to 17 B-ALL samples classified by conventional chromosome analysis, FISH, and/or chromosomal microarray as either pseudo-hyperdiploidy (n=8) or hyperdiploidy (n=9). The cases were sequenced using MPseq with 101bp read lengths across a range of base coverages (1-10x; 30-135 million fragments) and tumor percentages (50-100%). Results: We demonstrate the method's ability to differentiate between hyperdiploidy and pseudo-hyperdiploidy in all cases without any changes to the MPseq input or sequencing requirements. We detected an average of 11.5 whole-chromosome cnLOH (range 8-20) in the pseudo-hyperdiploidy cases, compared to an average of 0.67 whole-chromosome cnLOH (range 0-2) in the hyperdiploidy cases. Additionally, the method allows for the detection of cnLOH regions across the genome. For example, we observed a recurrent cnLOH of chromosome 9 in the hyperdiploid subtype (3/9 hyperdiploid cases), which is a recurrent abnormality in the disease. The method provides an easy to read visual output that compares favorably to the output of chromosomal microarray, increasing its utility for clinical application. Conclusions: This advancement in the analysis of low-coverage sequencing data makes MPseq available for the genetic characterization of B-ALL/LBL, where hypodiploidy is a primary cytogenetic abnormality and is sometimes missed by conventional cytogenetic techniques. Additionally, the algorithm allows for the detection of cnLOH regions across the genome, which is important across many disease types for diagnosis, prognosis, and the detection of potential therapeutic targets. The addition of the algorithm to the MPseq analysis pipeline makes it a more complete genetic characterization tool and brings it closer to its promise as a potential single assay replacement for conventional cytogenetic techniques. Disclosures No relevant conflicts of interest to declare.

Disease genetics: SNP location helps predict disease aetiology.

Disease genetics: SNP location helps predict disease aetiology.

Abstract 3413: A genetic analysis of splicing in neuroblastoma identifies opposing functions for FUBP1 splice variants in MYC regulation

Abstract Neuroblastoma, a tumor of the peripheral neural crest, is the most common cancer of infancy and the most common extracranial solid tumor of childhood. Large scale sequencing efforts have identified recurrent mutations in only a handful of genes in a minority of patients, but these efforts have so far focused on the exome, limiting identification of mutations leading to changes in alternative splicing. Regulation of alternative splicing is a critical and tightly regulated cellular function involving a complex interplay between cis-acting sequences on the pre-mRNA transcript and accessory trans-acting splicing factors. To elucidate genetic control of splicing, we used a splicing quantitative trait loci (sQTL) analysis in a backcrossed mouse model of neuroblastoma. We utilized Affymetrix Exon Arrays to profile mRNA expression at the exon level for superior cervical ganglia and cerebella (n=102) which we coupled with genotypes at 350 SNP and microsattlelite locations. With whole-genome sequencing data available for the inbred parental strains, our approach provided us with localized sequences for each individual mouse. In addition to identifying novel candidate trans-acting splicing factors, these sQTL identify novel candidate intronic regulatory sequences critical for splicing and reveal strain-specific splicing events leading to functional consequences in neuroblastoma. Among these, we show that a subtle splicing event within FUBP1 modulates levels of the MYC oncoprotein in human neuroblastoma-derived cell lines and correlates with outcome in children with neuroblastoma. Citation Format: Justin Chen, Christopher S. Hackett, Shile Zhang, Young K. Song, Annette Molinaro, David A. Quigley, Allan Balmain, William C. Gustafson, Terry A. Van Dyke, Pui-Yan Kwok, Javed Khan, William A. Weiss. A genetic analysis of splicing in neuroblastoma identifies opposing functions for FUBP1 splice variants in MYC regulation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3413. doi:10.1158/1538-7445.AM2014-3413

Genome-wide association studies identify the loci for 5 exterior traits in a Large White × Minzhu pig population.

As one of the main breeding selection criteria, external appearance has special economic importance in the hog industry. In this study, an Illumina Porcine SNP60 BeadChip was used to conduct a genome-wide association study (GWAS) in 605 pigs of the F2 generation derived from a Large White × Minzhu intercross. Traits under study were abdominal circumference (AC), body height (BH), body length (BL), cannon bone circumference (CBC), chest depth (CD), chest width (CW), rump circumference (RC), rump width (RW), scapula width (SW), and waist width (WW). A total of 138 SNPs (the most significant being MARC0033464) on chromosome 7 were found to be associated with BH, BL, CBC, and RC (P-value = 4.15E-6). One SNP on chromosome 1 was found to be associated with CD at genome-wide significance levels. The percentage phenotypic variance of these significant SNPs ranged from 0.1–25.48%. Moreover, a conditional analysis revealed that the significant SNPs were derived from a single quantitative trait locus (QTL) and indicated additional chromosome-wide significant association for 25 SNPs on SSC4 (BL, CBC) and 9 SNPs on SSC7 (RC). Linkage analysis revealed two complete linkage disequilibrium haplotype blocks that contained seven and four SNPs, respectively. In block 1, the most significant SNP, MARC0033464, was present. Annotations from pig reference genome suggested six genes (GRM4, HMGA1, NUDT3, RPS10, SPDEF and PACSIN1) in block 1 (495 kb), and one gene (SCUBE3) in block 3 (124 kb). Functional analysis indicated that HMGA1 and SCUBE3 genes are the potential genes controlling BH, BL, and RC in pigs, with an application in breeding programs. We screened several candidate intervals and genes based on SNP location and gene function, and predicted their function using bioinformatics analyses.

MrsFAST-Ultra: a compact, SNP-aware mapper for high performance sequencing applications

High throughput sequencing (HTS) platforms generate unprecedented amounts of data that introduce challenges for processing and downstream analysis. While tools that report the ‘best’ mapping location of each read provide a fast way to process HTS data, they are not suitable for many types of downstream analysis such as structural variation detection, where it is important to report multiple mapping loci for each read. For this purpose we introduce mrsFAST-Ultra, a fast, cache oblivious, SNP-aware aligner that can handle the multi-mapping of HTS reads very efficiently. mrsFAST-Ultra improves mrsFAST, our first cache oblivious read aligner capable of handling multi-mapping reads, through new and compact index structures that reduce not only the overall memory usage but also the number of CPU operations per alignment. In fact the size of the index generated by mrsFAST-Ultra is 10 times smaller than that of mrsFAST. As importantly, mrsFAST-Ultra introduces new features such as being able to (i) obtain the best mapping loci for each read, and (ii) return all reads that have at most n mapping loci (within an error threshold), together with these loci, for any user specified n. Furthermore, mrsFAST-Ultra is SNP-aware, i.e. it can map reads to reference genome while discounting the mismatches that occur at common SNP locations provided by db-SNP; this significantly increases the number of reads that can be mapped to the reference genome. Notice that all of the above features are implemented within the index structure and are not simple post-processing steps and thus are performed highly efficiently. Finally, mrsFAST-Ultra utilizes multiple available cores and processors and can be tuned for various memory settings. Our results show that mrsFAST-Ultra is roughly five times faster than its predecessor mrsFAST. In comparison to newly enhanced popular tools such as Bowtie2, it is more sensitive (it can report 10 times or more mappings per read) and much faster (six times or more) in the multi-mapping mode. Furthermore, mrsFAST-Ultra has an index size of 2GB for the entire human reference genome, which is roughly half of that of Bowtie2. mrsFAST-Ultra is open source and it can be accessed at http://mrsfast.sourceforge.net.

Extensive and coordinated control of allele-specific expression by both transcription and translation in Candida albicans.

Though sequence differences between alleles are often limited to a few polymorphisms, these differences can cause large and widespread allelic variation at the expression level. Such allele-specific expression (ASE) has been extensively explored at the level of transcription but not translation. Here we measured ASE in the diploid yeast Candida albicans at both the transcriptional and translational levels using RNA-seq and ribosome profiling, respectively. Since C. albicans is an obligate diploid, our analysis isolates ASE arising from cis elements in a natural, nonhybrid organism, where allelic effects reflect evolutionary forces. Importantly, we find that ASE arising from translation is of a similar magnitude as transcriptional ASE, both in terms of the number of genes affected and the magnitude of the bias. We further observe coordination between ASE at the levels of transcription and translation for single genes. Specifically, reinforcing relationships—where transcription and translation favor the same allele—are more frequent than expected by chance, consistent with selective pressure tuning ASE at multiple regulatory steps. Finally, we parameterize alleles based on a range of properties and find that SNP location and predicted mRNA-structure stability are associated with translational ASE in cis. Since this analysis probes more than 4000 allelic pairs spanning a broad range of variations, our data provide a genome-wide view into the relative impact of cis elements that regulate translation.

Genome-wide selective sweep analysis on Large White and Tong-cheng pigs

The production performance of pigs has been significantly improved due to long-term artificial selection, and the specific variation characterizations (selection signatures) emerged from the selected genome regions. Different types of breeds are subjected to different selection intensities and had different selection signatures. Selective sweep analysis is one of major methods to detect the selection signatures. In this study, based on the 60K BeadChip genotyping data of both commercial Large White (n=45) and local Tongcheng pigs (n=45), genetic differentiation coefficient Fst was applied to detect the selection signatures. Using gPLINK software to set quality control standards, a total of 34 304 SNPs were selected for statistical analysis. Fst values between two breeds were estimated with Genepop package and the average Fst value was 0.3209. Setting Fst>0.7036 (1% of total number of Fst values) as selection threshold, 344 SNPs were obtained and SNP location annotation indicated that there were 79 candidate genes (Sus scrofa Build 9). Furthermore, network analysis was performed using Ingenuity Pathway Analysis and the preliminary results suggested that most genes were involved in growth, reproduction, and immune response, such as NCOA6, ERBB4, RUNX2, and APOB genes. The findings from this study will contribute to further identification of candidate genes and causal mutations implying for meat production and disease resistance in pig.

Rapid molecular diagnosis of spinal muscular atrophy

Rapid molecular diagnosis of spinal muscular atrophy

Abstract 3888: Ionizing radiation destabilizes inverted ALU repeats linked to LOH

Abstract Ionizing radiation is a potent inducer of Loss of Heterozygosity (LOH), driven primarily by DNA double strand breaks. Such a process impacts both tumorigenesis through deletion of linked tumor suppressor genes and, similarly, the potential development of radiation resistant tumor clones during radiation therapy. The human mucoepidermoid cell line, H292, was exposed to either 4 or 8 Gy and surviving clones developed from two rounds of cloning analyzed for LOH using polymorphic microsatellite markers. A high level of LOH was observed within individual clones extending from 11q21 to 11q24 (6/49 after 4 Gy and 8/50 after 8Gy). More detailed analysis using a SNP screen on selected LOH positive clones indicated a sharp telomeric termination of LOH adjacent to a common SNP location. The telomeric extent of LOH observed co-mapped to a region of elevated recombination instability documented previously using linkage analysis. Further, SNP analysis showed a region of approximately 1 Mbp LOH that included the region of recombination instability identified through linkage analysis, in some clones isolated either with or without irradiation. The consistency of the telomeric boundary of LOH observed in the irradiated clones permitted a targeted analysis of DNA double strand breaks at this location, using LM-PCR, both before and after 4Gy irradiation of the same cell line. Using a six primer set screen covering a 9 kbp region at the telomeric extent of radiation-induced LOH, a single primer set showed an elevation in DNA breaks from 2-8h after irradiation. The timing and discrete distribution of such breaks indicated that these were not directly induced by the radiation itself. Cells that were unirradiated were not affected. Further inspection of the location demonstrating selective radiation-linked fragmentation showed the presence of an ALU inverted repeat, separated by approximately 1kbp, where the DNA breaks determined by LM-PCR were clustered within the 5’ ALU. Others have shown previously that inverted ALU repeats separated by <20bp are recombinationally unstable and are underrepresented within the human genome. It is proposed that, within the H292 cell line, otherwise stable ALU inverted repeats are capable of forming a transient hairpin conformation, perhaps facilitated by their own transcription via RNA polymerase III, which is unstable within a genome undergoing DNA damage and repair. The combination of such inverted ALU repeats and genotoxic exposure, such as during radiation therapy, may therefore destabilize specific regions of the genome and contribute to the development of aberrant cell clones. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3888. doi:10.1158/1538-7445.AM2011-3888

Analyses of porcine public SNPs in coding-gene regions by re-sequencing and phenotypic association studies

The Porcine SNP database has a huge number of SNPs, but these SNPs are mostly found by computer data-mining procedures and have not been well characterized. We re-sequenced 1,439 porcine public SNPs from four commercial pig breeds and one Korean domestic breed (Korean Native pig, KNP) by using two DNA pools from eight unrelated animals in each breed. These SNPs were from 419 protein-coding genes covering the 18 autosomes, and the re-sequencing in breeds confirmed 690 public SNPs (47.9%) and 226 novel mutations (173 SNPs and 53 insertions/deletions). Thus, totally, 916 variations were found from our study. Of the 916 variations, 148 SNPs (16.2%) were found across all the five breeds, and 199 SNPs (21.7%) were breed specific polymorphisms. According to the SNP locations in the gene sequences, these 916 variations were categorized into 802 non-coding SNPs (785 in intron, 17 in 3'-UTR) and 114 coding SNPs (86 synonymous SNPs, 28 non-synonymous SNPs). The nucleotide substitution analyses for these SNPs revealed that 70.2% were from transitions, 20.0% from transversions, and the remaining 5.79% were deletions or insertions. Subsequently, we genotyped 261 SNPs from 180 genes in an experimental KNP × Landrace F2 cross by the Sequenom MassARRAY system. A total of 33 traits including growth, carcass composition and meat quality were analyzed for the phenotypic association tests using the 132 SNPs in 108 genes with minor allele frequency (MAF)>0.2. The association results showed that five marker-trait combinations were significant at the 5% experiment-wise level (ADCK4 for rear leg, MYH3 for rear leg, Hunter B, Loin weight and Shearforce) and four at the 10% experiment-wise level (DHX38 for average daily gain at live weight, LGALS9 for crude lipid, NGEF for front leg and LIFR for pH at 24 h). In addition, 49 SNPs in 44 genes showing significant association with the traits were detected at the 1% comparison-wise level. A large number of genes that function as enzymes, transcription factors or signalling molecules were considered as genetic markers for pig growth (RNF103, TSPAN31, DHX38, ABCF1, ABCC10, SCD5, KIAA0999 and FKBP10), muscling (HSPA5, PTPRM, NUP88, ADCK4, PLOD1, DLX1 and GRM8), fatness (PTGIS, IDH3B, RYR2 and NOL4) and meat quality traits (DUSP4, LIFR, NGEF, EWSR1, ACTN2, PLXND1, DLX3, LGALS9, ENO3, EPRS, TRIM29, EHMT2, RBM42, SESN2 and RAB4B). The SNPs or genes reported here may be beneficial to future marker assisted selection breeding in pigs.

Common variants near MC4R are associated with fat mass, weight and risk of obesity

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.