BMC Genetics最新文献

Background: Genome-wide association studies (GWAS) have successfully identified genetic susceptible variants for complex diseases. However, the underlying mechanism of such association remains largely unknown. Most disease-associated genetic variants have been shown to reside in noncoding regions, leading to the hypothesis that regulation of gene expression may be the primary biological mechanism. Current methods to characterize gene expression mediating the effect of genetic variant on diseases, often analyzed one gene at a time and ignored the network structure. The impact of genetic variant can propagate to other genes along the links in the network, then to the final disease. There could be multiple pathways from the genetic variant to the final disease, with each having the chain structure since the first node is one specific SNP (Single Nucleotide Polymorphism) variant and the end is disease outcome. One key but inadequately addressed question is how to measure the between-node connection strength and rank the effects of such chain-type pathways, which can provide statistical evidence to give the priority of some pathways for potential drug development in a cost-effective manner.

Results: We first introduce the maximal correlation coefficient (MCC) to represent the between-node connection, and then integrate MCC with K shortest paths algorithm to rank and identify the potential pathways from genetic variant to disease. The pathway importance score (PIS) was further provided to quantify the importance of each pathway. We termed this method as "MCC-SP". Various simulations are conducted to illustrate MCC is a better measurement of the between-node connection strength than other quantities including Pearson correlation, Spearman correlation, distance correlation, mutual information, and maximal information coefficient. Finally, we applied MCC-SP to analyze one real dataset from the Religious Orders Study and the Memory and Aging Project, and successfully detected 2 typical pathways from APOE genotype to Alzheimer's disease (AD) through gene expression enriched in Alzheimer's disease pathway.

Conclusions: MCC-SP has powerful and robust performance in identifying the pathway(s) from the genetic variant to the disease. The source code of MCC-SP is freely available at GitHub ( https://github.com/zhuyuchen95/ADnet ).

Background: Lesion-mimic and premature aging (lmpa) mutant lmpa1 was identified from the ethyl methane sulfonate (EMS) mutant library in the bread wheat variety Keda 527 (KD527) background. To reveal the genetic basis of lmpa1 mutant, phenotypic observations and analyses of chlorophyll content and photosynthesis were carried out in lmpa1, KD527 and their F₁ and F₂ derivatives. Further, bulked segregation analysis (BSA) in combination with a 660 K SNP array were conducted on the F₂ segregation population of lmpa1/Chinese spring (CS) to locate the lmpa1 gene.

Results: Most agronomic traits of lmpa1 were similar to those of KD527 before lesion-like spots appeared. Genetic analysis indicated that the F₁ plants from the crossing of lmpa1 and KD527 exhibited the lmpa phenotype and the F₂ progenies showed a segregation of normal (wild type, WT) and lmpa, with the ratios of lmpa: WT = 124:36(χ² = 1.008 < =3.841), indicating that lmpa is a dominant mutation. The combination of BSA and the SNP array analysis of CS, lmpa1 and lmpa1/CS F₂ WT pool (50 plants) and lmpa pool (50 plants) showed that polymorphic SNPs were enriched on chromosome 5A, within a region of 30-40 Mb, indicating that the wheat premature aging gene Lmpa1 was probably located on the short arm of chromosome 5A.

Conclusions: EMS-mutagenized mutant lmpa1 deriving from elite wheat line KD527 conferred lmpa. Lmpa phenotype of lmpa1 mutant is controlled by a single dominant allele designated as Lmpa1, which affected wheat growth and development and reduced the thousand grain weight (tgw) of single plant in wheat. The gene Lmpa1 was tentatively located within the region of 30-40 Mb near to the short arm of chromosome 5A.

Background: Stenotaphrum secundatum is an important grass with a rich variety of accessions and great potential for development as an economically valuable crop. However, little is known about the genetic diversity of S. secundatum, limiting its application and development as a crop. Here, to provide a theoretical basis for further conservation, utilization, and classification of S. secundatum germplasm resources, we used phenotypic and molecular markers (single-nucleotide polymorphisms, SNPs; sequence-related amplified polymorphism, SRAP; inter-simple sequence repeat, ISSR) to analyze the genetic diversity of 49 S. secundatum accessions.

Results: Based on seven types of phenotypic data, the 49 S. secundatum accessions could be divided into three classes with great variation. We identified 1,280,873 SNPs in the 49 accessions, among which 66.22% were transition SNPs and 33.78% were transversion SNPs. Among these, C/T was the most common (19.12%) and G/C the least common (3.68%). Using 28 SRAP primers, 267 polymorphic bands were detected from the 273 bands amplified. In addition, 27 ISSR markers generated 527 amplification bands, all of which were polymorphic. Both marker types revealed a high level of genetic diversity, with ISSR markers showing a higher percentage of polymorphic loci (100%) than SRAP markers (97.8%). The genetic diversity of the accessions based on SRAP markers (h = 0.47, I = 0.66) and ISSR markers (h = 0.45, I = 0.64) supports the notion that the S. secundatum accessions are highly diverse. S. secundatum could be divided into three classes based on the evaluated molecular markers.

Conclusions: Phenotypic and molecular marker analysis using SNP, SRAP, and ISSR markers revealed great genetic variation among S. secundatum accessions, which were consistently divided into three classes. Our findings provide a theoretical basis for the genetic diversity and classification of S. secundatum. Our results indicate that SNP, SRAP and ISSR markers are reliable and effective for analyzing genetic diversity in S. secundatum. The SNPs identified in this study could be used to distinguish S. secundatum accessions.

Background: Biological pathways play an important role in the occurrence, development and recovery of complex diseases, such as cancers, which are multifactorial complex diseases that are generally caused by mutation of multiple genes or dysregulation of pathways.

Results: We propose a path-specific effect statistic (PSE) to detect the differential specific paths under two conditions (e.g. case VS. control groups, exposure Vs. nonexposure groups). In observational studies, the path-specific effect can be obtained by separately calculating the average causal effect of each directed edge through adjusting for the parent nodes of nodes in the specific path and multiplying them under each condition. Theoretical proofs and a series of simulations are conducted to validate the path-specific effect statistic. Applications are also performed to evaluate its practical performances. A series of simulation studies show that the Type I error rates of PSE with Permutation tests are more stable at the nominal level 0.05 and can accurately detect the differential specific paths when comparing with other methods. Specifically, the power reveals an increasing trends with the enlargement of path-specific effects and its effect differences under two conditions. Besides, the power of PSE is robust to the variation of parent or child node of the nodes on specific paths. Application to real data of Glioblastoma Multiforme (GBM), we successfully identified 14 positive specific pathways in mTOR pathway contributing to survival time of patients with GBM. All codes for automatic searching specific paths linking two continuous variables and adjusting set as well as PSE statistic can be found in supplementary materials.  CONCLUSION: The proposed PSE statistic can accurately detect the differential specific pathways contributing to complex disease and thus potentially provides new insights and ways to unlock the black box of disease mechanisms.

Background: The human CGGBP1 binds to GC-rich regions and interspersed repeats, maintains homeostasis of stochastic cytosine methylation and determines DNA-binding of CTCF. Interdependence between regulation of cytosine methylation and CTCF occupancy by CGGBP1 remains unknown.

Results: By analyzing methylated DNA-sequencing data obtained from CGGBP1-depleted cells, we report that some transcription factor-binding sites, including CTCF, resist stochastic changes in cytosine methylation. By analysing CTCF-binding sites we show that cytosine methylation changes at CTCF motifs caused by CGGBP1 depletion resist stochastic changes. These CTCF-binding sites are positioned at locations where the spread of cytosine methylation in cis depends on the levels of CGGBP1.

Conclusion: Our findings suggest that CTCF occupancy and functions are determined by CGGBP1-regulated cytosine methylation patterns.

Background: The major histocompatibility complex (MHC) is responsible for detecting and addressing foreign pathogens inside the body. While the general structure of MHC genes is relatively well conserved among mammalian species, it is notably different among ruminants due to a chromosomal inversion that splits MHC type II genes into two subregions (IIa, IIb). Recombination rates are reportedly high between these subregions, and a lack of linkage has been documented in domestic ruminants. However, no study has yet examined the degree of linkage between these subregions in a wild ruminant. The white-tailed deer (Odocoileus virginianus), a popular ruminant of the Cervidae family, is habitually plagued by pathogens in its natural environment (e.g. Haemonchus contortus, Elaeophora). Due to the association between MHC haplotypes and disease susceptibility, a deeper understanding of MHC polymorphism and linkage between MHC genes can further aid in this species' successful management. We sequenced MHC-DRB exon 2 (IIa) and MHC-DOB exon 2 (IIb) on the MiSeq platform from an enclosed white-tailed deer population located in Alabama.

Results: We identified 12 new MHC-DRB alleles, and resampled 7 alleles, which along with other published alleles brings the total number of documented alleles in white-tailed deer to 30 for MHC-DRB exon 2. The first examination of MHC-DOB in white-tailed deer found significantly less polymorphism (11 alleles), as was expected of a non-classical MHC gene. While MHC-DRB was found to be under positive, diversifying selection, MHC-DOB was found to be under purifying selection for white-tailed deer. We found no significant linkage disequilibrium between MHC-DRB and MHC-DOB, suggesting that these loci are unlikely to be closely linked.

Conclusions: Overall, this study identified 12 new MHC-DRB exon 2 alleles and characterized a new, non-classical, MHC II gene (MHC-DOB) for white-tailed deer. We also found a lack of significant linkage between these two loci, which supports previous findings of a chromosomal inversion within the MHC type II gene region in ruminants, and suggests that white-tailed deer may have a recombination hotspot between these MHC regions similar to that found for Bos taurus.

Background: Although the molecular function of wolframin remains unclear, the lack of this protein is known to cause stress in the endoplasmic reticulum. Some variants in the Wolfram Syndrome 1 gene (WFS1) were associated with various neuropsychiatric disorders in humans, such as aggressiveness, impulsivity and anxiety.

Results: Here we present an in silico study predicting a single nucleotide polymorphism (rs852850348) in the canine WFS1 gene which was verified by direct sequencing and was genotyped by a PCR-based technique. We found that the rs852850348 polymorphism is located in a putative microRNA (cfa-miR-8834a and cfa-miR-1838) binding site. Therefore, the molecular effect of allelic variants was studied in a luciferase reporter system that allowed assessing gene expression. We demonstrated that the variant reduced the activity of the reporter protein expression in an allele-specific manner. Additionally, we performed a behavioral experiment and investigated the association with this locus to different performance in this test. Association was found between food possessivity and the studied WFS1 gene polymorphism in the Border collie breed.

Conclusions: Based on our findings, the rs852850348 locus might contribute to the genetic risk of possessivity behavior of dogs in at least one breed and might influence the regulation of wolframin expression.

Background: Both genetic and environmental factors contribute to type 2 diabetes development. We used consomic mice established from an animal type 2 diabetes model to identify susceptibility genes that contribute to type 2 diabetes development under specific environments. We previously established consomic strains (C3H-Chr 11^NSY and C3H-Chr 14^NSY) that possess diabetogenic Chr 11 or 14 of the Nagoya-Shibata-Yasuda (NSY) mouse, an animal model of spontaneous type 2 diabetes, in the genetic background of C3H mice. To search genes contribute to type 2 diabetes under specific environment, we first investigated whether sucrose administration deteriorates type 2 diabetes-related traits in the consomic strains. We dissected loci on Chr 11 by establishing congenic strains possessing different segments of NSY-derived Chr 11 under sucrose administration.

Results: In C3H-Chr 11^NSY mice, sucrose administration for 10 weeks deteriorated hyperglycemia, insulin resistance, and impaired insulin secretion, which is comparable to NSY mice with sucrose. In C3H-Chr 14^NSY mice, sucrose administration induced glucose intolerance, but not insulin resistance and impaired insulin secretion. To dissect the gene(s) existing on Chr 11 for sucrose-induced type 2 diabetes, we constructed four novel congenic strains (R1, R2, R3, and R4) with different segments of NSY-derived Chr 11 in C3H mice. R2 mice showed marked glucose intolerance and impaired insulin secretion comparable to C3H-Chr 11^NSY mice. R3 and R4 mice also showed impaired insulin secretion. R4 mice showed significant decreases in white adipose tissue, which is in the opposite direction from parental C3H-Chr 11^NSY and NSY mice. None of the four congenic strains showed insulin resistance.

Conclusions: Genes on mouse Chr 11 could explain glucose intolerance, impaired insulin secretion, insulin resistance in NSY mice under sucrose administration. Congenic mapping with high sucrose environment localized susceptibility genes for type 2 diabetes associated with impaired insulin secretion in the middle segment (26.0-63.4 Mb) of Chr 11. Gene(s) that decrease white adipose tissue were mapped to the distal segment of Chr 11. The identification of diabetogenic gene on Chr 11 in the future study will facilitate precision medicine in type 2 diabetes by controlling specific environments in targeted subjects with susceptible genotypes.

Background: Bacterial fruit blotch (BFB), a disease caused by Acidovorax citrulli, results in significant economic losses in melon. The causal QTLs and genes for resistance to this disease have yet to be identified. Resistance (R)-genes play vital roles in resistance to plant diseases. Since the complete genome sequence of melon is available and genome-wide identification of R-genes has been performed for this important crop, comprehensive expression profiling may lead to the identification of putative candidate genes that function in the response to BFB.

Results: We identified melon accessions that are resistant and susceptible to BFB through repeated bioassays and characterized all 70 R-genes in melon, including their gene structures, chromosomal locations, domain organizations, motif distributions, and syntenic relationships. Several disease resistance-related domains were identified, including NBS, TIR, LRR, CC, RLK, and DUF domains, and the genes were categorized based on the domains of their encoded proteins. In addition, we profiled the expression patterns of the genes in melon accessions with contrasting levels of BFB resistance at 12 h, 1 d, 3 d, and 6 d after inoculation with A. citrulli. Six R-genes exhibited consistent expression patterns (MELO3C023441, MELO3C016529, MELO3C022157, MELO3C022146, MELO3C025518, and MELO3C004303), with higher expression levels in the resistant vs. susceptible accession.

Conclusion: We identified six putative candidate R-genes against BFB in melon. Upon functional validation, these genes could be targeted for manipulation via breeding and biotechnological approaches to improve BFB resistance in melon in the future.

Background: The HTR1B gene encodes the 5-hydroxytryptamine (5-HT1B) receptor, which is involved in a variety of brain activities and mental disorders. The regulatory effects of non-coding regions on genomic DNA are one of many reasons for the cause of genetic-related diseases. Post-transcriptional regulation that depends on the function of 3' regulatory regions plays a particularly important role. This study investigated the effects, on reporter gene expression, of several haplotypes of the HTR1B gene (rs6297, rs3827804, rs140792648, rs9361234, rs76194807, rs58138557, and rs13212041) and truncated fragments in order to analyze the function of the 3' region of HTR1B.

Results: We found that the haplotype, A-G-Del-C-T-Ins-A, enhanced the expression level compared to the main haplotype; A-G-Del-C-G-Ins-A; G-G-Del-C-G-Ins-G decreased the expression level. Two alleles, rs76194807T and rs6297G, exhibited different relative luciferase intensities compared to their counterparts at each locus. We also found that + 2440 ~ + 2769 bp and + 1953 ~ + 2311 bp regions both had negative effects on gene expression.

Conclusions: The 3' region of HTR1B has a regulatory effect on gene expression, which is likely closely associated with the interpretation of HTR1B-related disorders. In addition, the HTR1B 3' region includes several effector binding sites that induce an inhibitory effect on gene expression.