A Solute Carrier Family 22 Member 3 Variant rs3088442 G→A Associated with Coronary Heart Disease Inhibits Lipopolysaccharide-induced Inflammatory Response

Recent genome-wide association studies have identified single-nucleotide polymorphism (SNPs) within the SLC22A3 (solute carrier family 22 member 3) gene associated with coronary heart disease (CHD) in the Caucasian population. We performed molecular analysis to investigate the potential role of SLC22A3 variants in CHD. Our study showed that the common polymorphism rs3088442 G→A, which is localized in the 3′ UTR of the SLC22A3 gene, was associated with a decreased risk of CHD in the Chinese population by a case control study. In silico analysis indicated that G→A substitution of SNP rs3088442 created a putative binding site for miR-147 in the SLC22A3 mRNA. By overexpressing miR-147 or inhibiting endogenous miR-147, we demonstrated that SNP rs3088442 G→A recruited miR-147 to inhibit SLC22A3 expression. Moreover, SLC22A3 deficiency significantly decreased LPS-induced monocytic inflammatory response by interrupting NF-κB and MAPK signaling cascades in a histamine-dependent manner. Notably, the expression of SLC22A3^A was also suppressed by LPS stimulus. Our findings might indicate a negative feedback mechanism against inflammatory response by which SLC22A3 polymorphisms decreased the risk of CHD.     

结构方程混合模型在SNP分析中的应用

采用结构方程混合模型(SEMM)对实际SNP数据进行分析,为遗传统计学提供一种新的有效的分析方法。本研究的数据是由GAW17提供的,包含697个个体的22条常染色体的上万个SNP和根据这些SNP所模拟的697个个体的性状特点。随机挑选了1号染色体上的4个SNP和3个定量性状作为研究变量,分别进行潜在类别分析和结构方程混合模型分析。根据4个SNP数据,人群被分为3个潜在类别,概率分别为0.53,0.34,0.13。潜在类别1、2和3中的因子均值Q分别为-4.029、-2.052和0,潜在类别1、2的因子均值均低于3(<0.001)。研究表明:结构方程混合模型(SEMM)综合了结构方程模型和潜在类别模型的思想,形成了自己的优势,可用于处理同时包含分类潜变量和连续潜变量的数据。     

中国野生葡萄mybA转录因子SNP特征分析

本研究以中国野生葡萄14个种为材料,对控制花色苷合成的mybA转录因子进行克隆和序列分析,获得VvmybA1和VlmybA2两个转录因子的全长基因序列,共检测到121个SNP,表现出丰富的遗传多样性。3种中性检测方法比较序列变异模式,结果表明,中国野生种葡萄VvmybA1和VlmybA2基因没有偏离中性模型,反映出基因漂移和选择性中性突变之间的平衡。不同野生种材料的mybA 基因结构存在很高的同源相似性。但是在启动子区、内含子区以及第三个外显子区存在不同程度碱基的缺失、插入和替换,而且野生种葡萄mybA基因存在一些特有序列或突变,这些突变可以作为分子标记区分不同的野生种材料。通过基因结构比对和系统进化树分析,可将野生种葡萄细分为5个类群。初步推测桦叶葡萄和变叶葡萄进化地位较为原始。     

PNPLA3基因rs738409多态性与代谢综合症在中国人群中的研究

目的:研究中国人群中PNPLA3基因rs738409位点多态性与代谢综合征之间的相关性.方法:收集了381例二型糖尿病患者和380例正常人的血液样本,使用全血提取试剂盒从781份样本中提取全基因组DNA,并利用飞行质谱技术进行目标位点的SNP分型,将分型结果与各临床指标进行统计学分析.结果:①经SNP分型结果与二型糖尿病病例-对照的关联性分析,rs738409位点多态性与二型糖尿病无显著相关性(P=0.74).②经SNP分型结果与其他临床指标的统计分析,rs738409位点多态性与高密度脂蛋白水平(P=0.029),甘油三酯水平(P=0.021),总胆固醇水平(P=0.038)及谷丙转氨酶水平(P=0.004)显著相关.结论:rs738409位点多态性与二型糖尿病的发病无显著相关性,但它通过氨基酸替换影响了与其关系紧密的基因表达,进而影响机体内各因素代谢水平的改变.     

MultiGWAS: An integrative tool for Genome Wide Association Studies in tetraploid organisms

The genome‐wide association studies (GWASs) are essential to determine the genetic bases of either ecological or economic phenotypic variation across individuals within populations of the model and nonmodel organisms. For this research question, the GWAS replication testing different parameters and models to validate the results'' reproducibility is common. However, straightforward methodologies that manage both replication and tetraploid data are still missing. To solve this problem, we designed the MultiGWAS, a tool that does GWAS for diploid and tetraploid organisms by executing in parallel four software packages, two designed for polyploid data (GWASpoly and SHEsis) and two designed for diploid data (GAPIT and TASSEL). MultiGWAS has several advantages. It runs either in the command line or in a graphical interface; it manages different genotype formats, including VCF. Moreover, it allows control for population structure, relatedness, and several quality control checks on genotype data. Besides, MultiGWAS can test for additive and dominant gene action models, and, through a proprietary scoring function, select the best model to report its associations. Finally, it generates several reports that facilitate identifying false associations from both the significant and the best‐ranked association Single Nucleotide Polymorphisms (SNPs) among the four software packages. We tested MultiGWAS with public tetraploid potato data for tuber shape and several simulated data under both additive and dominant models. These tests demonstrated that MultiGWAS is better at detecting reliable associations than using each of the four software packages individually. Moreover, the parallel analysis of polyploid and diploid software that only offers MultiGWAS demonstrates its utility in understanding the best genetic model behind the SNP association in tetraploid organisms. Therefore, MultiGWAS probed to be an excellent alternative for wrapping GWAS replication in diploid and tetraploid organisms in a single analysis environment.     

Y chromosome haplotype distribution of brown bears (Ursus arctos) in Northern Europe provides insight into population history and recovery

High‐resolution, male‐inherited Y‐chromosomal markers are a useful tool for population genetic analyses of wildlife species, but to date have only been applied in this context to relatively few species besides humans. Using nine Y‐chromosomal STRs and three Y‐chromosomal single nucleotide polymorphism markers (Y‐SNPs), we studied whether male gene flow was important for the recent recovery of the brown bear (Ursus arctos) in Northern Europe, where the species declined dramatically in numbers and geographical distribution during the last centuries but is expanding now. We found 36 haplotypes in 443 male extant brown bears from Sweden, Norway, Finland and northwestern Russia. In 14 individuals from southern Norway from 1780 to 1920, we found two Y chromosome haplotypes present in the extant population as well as four Y chromosome haplotypes not present among the modern samples. Our results suggested major differences in genetic connectivity, diversity and structure between the eastern and the western populations in Northern Europe. In the west, our results indicated that the recovered population originated from only four male lineages, displaying pronounced spatial structuring suggestive of large‐scale population size increase under limited male gene flow within the western subpopulation. In the east, we found a contrasting pattern, with high haplotype diversity and admixture. This first population genetic analysis of male brown bears shows conclusively that male gene flow was not the main force of population recovery.     

Construction of a virtual Mycobacterium tuberculosis consensus genome and its application to data from a next generation sequencer

Background

Although Mycobacterium tuberculosis isolates are consisted of several different lineages and the epidemiology analyses are usually assessed relative to a particular reference genome, M. tuberculosis H37Rv, which might introduce some biased results. Those analyses are essentially based genome sequence information of M. tuberculosis and could be performed in sillico in theory, with whole genome sequence (WGS) data available in the databases and obtained by next generation sequencers (NGSs). As an approach to establish higher resolution methods for such analyses, whole genome sequences of the M. tuberculosis complexes (MTBCs) strains available on databases were aligned to construct virtual reference genome sequences called the consensus sequence (CS), and evaluated its feasibility in in sillico epidemiological analyses.

Results

The consensus sequence (CS) was successfully constructed and utilized to perform phylogenetic analysis, evaluation of read mapping efficacy, which is crucial for detecting single nucleotide polymorphisms (SNPs), and various MTBC typing methods virtually including spoligotyping, VNTR, Long sequence polymorphism and Beijing typing. SNPs detected based on CS, in comparison with H37Rv, were utilized in concatemer-based phylogenetic analysis to determine their reliability relative to a phylogenetic tree based on whole genome alignment as the gold standard. Statistical comparison of phylogenic trees based on CS with that of H37Rv indicated the former showed always better results that that of later. SNP detection and concatenation with CS was advantageous because the frequency of crucial SNPs distinguishing among strain lineages was higher than those of H37Rv. The number of SNPs detected was lower with the consensus than with the H37Rv sequence, resulting in a significant reduction in computational time. Performance of each virtual typing was satisfactory and accorded with those published when those are available.

Conclusions

These results indicated that virtual CS constructed from genome sequence data is an ideal approach as a reference for MTBC studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1368-9) contains supplementary material, which is available to authorized users.     

SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance

Background

Soybean cyst nematode (SCN) is the most economically devastating pathogen of soybean. Two resistance loci, Rhg1 and Rhg4 primarily contribute resistance to SCN race 3 in soybean. Peking and PI 88788 are the two major sources of SCN resistance with Peking requiring both Rhg1 and Rhg4 alleles and PI 88788 only the Rhg1 allele. Although simple sequence repeat (SSR) markers have been reported for both loci, they are linked markers and limited to be applied in breeding programs due to accuracy, throughput and cost of detection methods. The objectives of this study were to develop robust functional marker assays for high-throughput selection of SCN resistance and to differentiate the sources of resistance.

Results

Based on the genomic DNA sequences of 27 soybean lines with known SCN phenotypes, we have developed Kompetitive Allele Specific PCR (KASP) assays for two Single nucleotide polymorphisms (SNPs) from Glyma08g11490 for the selection of the Rhg4 resistance allele. Moreover, the genomic DNA of Glyma18g02590 at the Rhg1 locus from 11 soybean lines and cDNA of Forrest, Essex, Williams 82 and PI 88788 were fully sequenced. Pairwise sequence alignment revealed seven SNPs/insertion/deletions (InDels), five in the 6th exon and two in the last exon. Using the same 27 soybean lines, we identified one SNP that can be used to select the Rhg1 resistance allele and another SNP that can be employed to differentiate Peking and PI 88788-type resistance. These SNP markers have been validated and a strong correlation was observed between the SNP genotypes and reactions to SCN race 3 using a panel of 153 soybean lines, as well as a bi-parental population, F₅–derived recombinant inbred lines (RILs) from G00-3213 x LG04-6000.

Conclusions

Three functional SNP markers (two for Rhg1 locus and one for Rhg4 locus) were identified that could provide genotype information for the selection of SCN resistance and differentiate Peking from PI 88788 source for most germplasm lines. The robust KASP SNP marker assays were developed. In most contexts, use of one or two of these markers is sufficient for high-throughput marker-assisted selection of plants that will exhibit SCN resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1531-3) contains supplementary material, which is available to authorized users.     

Recent artificial selection in U.S. Jersey cattle impacts autozygosity levels of specific genomic regions

Background

Genome signatures of artificial selection in U.S. Jersey cattle were identified by examining changes in haplotype homozygosity for a resource population of animals born between 1953 and 2007. Genetic merit of this population changed dramatically during this period for a number of traits, especially milk yield. The intense selection underlying these changes was achieved through extensive use of artificial insemination (AI), which also increased consanguinity of the population to a few superior Jersey bulls. As a result, allele frequencies are shifted for many contemporary animals, and in numerous cases to a homozygous state for specific genomic regions. The goal of this study was to identify those selection signatures that occurred after extensive use of AI since the 1960, using analyses of shared haplotype segments or Runs of Homozygosity. When combined with animal birth year information, signatures of selection associated with economically important traits were identified and compared to results from an extended haplotype homozygosity analysis.

Results

Overall, our results reveal that more recent selection increased autozygosity across the entire genome, but some specific regions increased more than others. A genome-wide scan identified more than 15 regions with a substantial change in autozygosity. Haplotypes found to be associated with increased milk, fat and protein yield in U.S. Jersey cattle also consistently increased in frequency.

Conclusions

The analyses used in this study was able to detect directional selection over the last few decades when individual production records for Jersey animals were available.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1500-x) contains supplementary material, which is available to authorized users.