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11 pages, 1523 KiB

Open AccessArticle

Marfan Syndrome Variability: Investigation of the Roles of Sarcolipin and Calcium as Potential Transregulator of FBN1 Expression

by Louise Benarroch, Mélodie Aubart, Marie-Sylvie Gross, Marie-Paule Jacob, Pauline Arnaud, Nadine Hanna, Guillaume Jondeau and Catherine Boileau

Genes 2018, 9(9), 421; https://doi.org/10.3390/genes9090421 - 21 Aug 2018

Cited by 7 | Viewed by 3252

Abstract

Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder that displays a great clinical variability. Previous work in our laboratory showed that fibrillin-1 (FBN1) messenger RNA (mRNA) expression is a surrogate endpoint for MFS severity. Therefore, an expression quantitative trait [...] Read more.

Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder that displays a great clinical variability. Previous work in our laboratory showed that fibrillin-1 (FBN1) messenger RNA (mRNA) expression is a surrogate endpoint for MFS severity. Therefore, an expression quantitative trait loci (eQTL) analysis was performed to identify trans-acting regulators of FBN1 expression, and a significant signal reached genome-wide significant threshold on chromosome 11. This signal delineated a region comprising one expressed gene, SLN (encoding sarcolipin), and a single pseudogene, SNX7-ps1 (CTD-2651C21.3). We first investigated the region and then looked for association between the genes in the region and FBN1 expression. For the first time, we showed that the SLN gene is weakly expressed in skin fibroblasts. There is no direct correlation between SLN and FBN1 gene expression. We showed that calcium influx modulates FBN1 gene expression. Finally, SLN gene expression is highly correlated to that of the neighboring SNX7-ps1. We were able to confirm the impact of calcium influx on FBN1 gene expression but we could not conclude regarding the role of sarcolipin and/or the eQTL locus in this regulation. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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19 pages, 4281 KiB

Open AccessArticle

Whole Exome Sequencing Identifies New Host Genomic Susceptibility Factors in Empyema Caused by Streptococcus pneumoniae in Children: A Pilot Study

by Antonio Salas, Jacobo Pardo-Seco, Ruth Barral-Arca, Miriam Cebey-López, Alberto Gómez-Carballa, Irene Rivero-Calle, Sara Pischedda, María-José Currás-Tuala, Jorge Amigo, José Gómez-Rial, Federico Martinón-Torres and On behalf of GENDRES Network

Genes 2018, 9(5), 240; https://doi.org/10.3390/genes9050240 - 03 May 2018

Cited by 8 | Viewed by 5236

Abstract

Pneumonia is the leading cause of death amongst infectious diseases. Streptococcus pneumoniae is responsible for about 25% of pneumonia cases worldwide, and it is a major cause of childhood mortality. We carried out a whole exome sequencing (WES) study in eight patients with [...] Read more.

Pneumonia is the leading cause of death amongst infectious diseases. Streptococcus pneumoniae is responsible for about 25% of pneumonia cases worldwide, and it is a major cause of childhood mortality. We carried out a whole exome sequencing (WES) study in eight patients with complicated cases of pneumococcal pneumonia (empyema). An initial assessment of statistical association of WES variation with pneumonia was carried out using data from the 1000 Genomes Project (1000G) for the Iberian Peninsula (IBS) as reference controls. Pseudo-replication statistical analyses were carried out using different European control groups. Association tests pointed to single nucleotide polymorphism (SNP) rs201967957 (gene MEIS1; chromosome 2; p-value_IBS = 3.71 × 10⁻¹³) and rs576099063 (gene TSPAN15; chromosome 10; p-value_IBS = 2.36 × 10⁻⁸) as the best candidate variants associated to pneumococcal pneumonia. A burden gene test of pathogenicity signaled four genes, namely, OR9G9, MUC6, MUC3A and APOB, which carry significantly increased pathogenic variation when compared to controls. By analyzing various transcriptomic data repositories, we found strong supportive evidence for the role of MEIS1, TSPAN15 and APOBR (encoding the receptor of the APOB protein) in pneumonia in mouse and human models. Furthermore, the association of the olfactory receptor gene OR9G9 has recently been related to some viral infectious diseases, while the role of mucin genes (MUC6 and MUC3A), encoding mucin glycoproteins, are well-known factors related to chronic obstructive airway disease. WES emerges as a promising technique to disentangle the genetic basis of host genome susceptibility to infectious respiratory diseases. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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13 pages, 2790 KiB

Open AccessArticle

MHC-Dependent Mate Selection within 872 Spousal Pairs of European Ancestry from the Health and Retirement Study

by Zhen Qiao, Joseph E. Powell and David M. Evans

Genes 2018, 9(1), 53; https://doi.org/10.3390/genes9010053 - 22 Jan 2018

Cited by 13 | Viewed by 5163

Abstract

Disassortative mating refers to the phenomenon in which individuals with dissimilar genotypes and/or phenotypes mate with one another more frequently than would be expected by chance. Although the existence of disassortative mating is well established in plant and animal species, the only documented [...] Read more.

Disassortative mating refers to the phenomenon in which individuals with dissimilar genotypes and/or phenotypes mate with one another more frequently than would be expected by chance. Although the existence of disassortative mating is well established in plant and animal species, the only documented example of negative assortment in humans involves dissimilarity at the major histocompatibility complex (MHC) locus. Previous studies investigating mating patterns at the MHC have been hampered by limited sample size and contradictory findings. Inspired by the sparse and conflicting evidence, we investigated the role that the MHC region played in human mate selection using genome-wide association data from 872 European American spouses from the Health and Retirement Study (HRS). First, we treated the MHC region as a whole, and investigated genomic similarity between spouses using three levels of genomic variation: single-nucleotide polymorphisms (SNPs), classical human leukocyte antigen (HLA) alleles (both four-digit and two-digit classifications), and amino acid polymorphisms. The extent of MHC dissimilarity between spouses was assessed using a permutation approach. Second, we investigated fine scale mating patterns by testing for deviations from random mating at individual SNPs, HLA genes, and amino acids in HLA molecules. Third, we assessed how extreme the spousal relatedness at the MHC region was compared to the rest of the genome, to distinguish the MHC-specific effects from genome-wide effects. We show that neither the MHC region, nor any single SNPs, classic HLA alleles, or amino acid polymorphisms within the MHC region, were significantly dissimilar between spouses relative to non-spouse pairs. However, dissimilarity in the MHC region was extreme relative to the rest of genome for both spousal and non-spouse pairs. Despite the long-standing controversy, our analyses did not support a significant role of MHC dissimilarity in human mate choice. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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11 pages, 1478 KiB

Open AccessArticle

Using Y-Chromosomal Haplogroups in Genetic Association Studies and Suggested Implications

by A. Mesut Erzurumluoglu, Denis Baird, Tom G. Richardson, Nicholas J. Timpson and Santiago Rodriguez

Genes 2018, 9(1), 45; https://doi.org/10.3390/genes9010045 - 22 Jan 2018

Cited by 5 | Viewed by 7633

Abstract

Y-chromosomal (Y-DNA) haplogroups are more widely used in population genetics than in genetic epidemiology, although associations between Y-DNA haplogroups and several traits, including cardiometabolic traits, have been reported. In apparently homogeneous populations defined by principal component analyses, there is still Y-DNA haplogroup variation [...] Read more.

Y-chromosomal (Y-DNA) haplogroups are more widely used in population genetics than in genetic epidemiology, although associations between Y-DNA haplogroups and several traits, including cardiometabolic traits, have been reported. In apparently homogeneous populations defined by principal component analyses, there is still Y-DNA haplogroup variation which will result from population history. Therefore, hidden stratification and/or differential phenotypic effects by Y-DNA haplogroups could exist. To test this, we hypothesised that stratifying individuals according to their Y-DNA haplogroups before testing for associations between autosomal single nucleotide polymorphisms (SNPs) and phenotypes will yield difference in association. For proof of concept, we derived Y-DNA haplogroups from 6537 males from two epidemiological cohorts, Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 5080; 816 Y-DNA SNPs) and the 1958 Birth Cohort (n = 1457; 1849 Y-DNA SNPs), and studied the robust associations between 32 SNPs and body mass index (BMI), including SNPs in or near Fat Mass and Obesity-associated protein (FTO) which yield the strongest effects. Overall, no association was replicated in both cohorts when Y-DNA haplogroups were considered and this suggests that, for BMI at least, there is little evidence of differences in phenotype or SNP association by Y-DNA structure. Further studies using other traits, phenome-wide association studies (PheWAS), other haplogroups and/or autosomal SNPs are required to test the generalisability and utility of this approach. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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18 pages, 2273 KiB

Open AccessArticle

Copy Number Variation in SOX6 Contributes to Chicken Muscle Development

by Shudai Lin, Xiran Lin, Zihao Zhang, Mingya Jiang, Yousheng Rao, Qinghua Nie and Xiquan Zhang

Genes 2018, 9(1), 42; https://doi.org/10.3390/genes9010042 - 17 Jan 2018

Cited by 22 | Viewed by 4844

Abstract

Copy number variations (CNVs), which cover many functional genes, are associated with complex diseases, phenotypic diversity and traits that are economically important to raising chickens. The sex-determining region Y-box 6 (Sox6) plays a key role in fast-twitch muscle fiber differentiation of [...] Read more.

Copy number variations (CNVs), which cover many functional genes, are associated with complex diseases, phenotypic diversity and traits that are economically important to raising chickens. The sex-determining region Y-box 6 (Sox6) plays a key role in fast-twitch muscle fiber differentiation of zebrafish and mice, but it is still unknown whether SOX6 plays a role in chicken skeletal muscle development. We identified two copy number polymorphisms (CNPs) which were significantly related to different traits on the genome level in chickens by AccuCopy^® and CNVplex^® analyses. Notably, five white recessive rock (CN = 1, CN = 3) variant individuals and two Xinghua (CN = 3) variant individuals contain a CNP13 (chromosome5: 10,500,294–10,675,531) which overlaps with SOX6. There is a disordered region in SOX6 proteins 265–579 aa coded by a partial CNV overlapping region. A quantitative real-time polymerase chain reaction showed that the expression level of SOX6 mRNA was positively associated with CNV and highly expressed during the skeletal muscle cell differentiation in chickens. After the knockdown of the SOX6, the expression levels of IGFIR1, MYF6, SOX9, SHOX and CCND1 were significantly down-regulated. All of them directly linked to muscle development. These results suggest that the number of CNVs in the CNP13 is positively associated with the expression level of SOX6, which promotes the proliferation and differentiation of skeletal muscle cells by up-regulating the expression levels of the muscle-growth-related genes in chickens as in other animal species. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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1317 KiB

Open AccessArticle

Identification of the Ovine Keratin-Associated Protein 26-1 Gene and Its Association with Variation in Wool Traits

by Shaobin Li, Huitong Zhou, Hua Gong, Fangfang Zhao, Jiang Hu, Yuzhu Luo and Jon G. H. Hickford

Genes 2017, 8(9), 225; https://doi.org/10.3390/genes8090225 - 13 Sep 2017

Cited by 29 | Viewed by 3887

Abstract

Keratin-associated proteins (KAPs) are structural components of wool and hair fibres, and are believed to play a role in defining the physico-mechanical properties of the wool fibre. In this study, the putative ovine homologue of the human KAP26-1 gene (KRTAP26-1) was [...] Read more.

Keratin-associated proteins (KAPs) are structural components of wool and hair fibres, and are believed to play a role in defining the physico-mechanical properties of the wool fibre. In this study, the putative ovine homologue of the human KAP26-1 gene (KRTAP26-1) was sequenced and four variants (named A–D) were identified. The sequences shared some identity with each other and with other KRTAPs, but they had the greatest similarity with the human KRTAP26-1 sequence. This suggests they represent different variants of ovine KRTAP26-1. The association of these KRTAP26-1 variants with wool traits was investigated in the 383 Merino-Southdown cross sheep. The presence of B was associated (p < 0.05) with an increase in mean fibre diameter (MFD), mean fibre curvature, and prickle factor (PF). The presence of C was found to be associated (p < 0.05) with an increase in wool yield (Yield) and mean staple length (MSL), and a decrease in MFD, fibre diameter standard deviation (FDSD), and PF. The results suggest that sheep with C have, on average, higher wool quality. These results may be useful in the future development of breeding programs based on decreasing wool MFD and FDSD, or on increasing wool MSL. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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Review

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15 pages, 1908 KiB

Open AccessFeature PaperReview

Unravelling the Roles of Susceptibility Loci for Autoimmune Diseases in the Post-GWAS Era

by Jody Ye, Kathleen M. Gillespie and Santiago Rodriguez

Genes 2018, 9(8), 377; https://doi.org/10.3390/genes9080377 - 27 Jul 2018

Cited by 29 | Viewed by 5013

Abstract

Although genome-wide association studies (GWAS) have identified several hundred loci associated with autoimmune diseases, their mechanistic insights are still poorly understood. The human genome is more complex than single nucleotide polymorphisms (SNPs) that are interrogated by GWAS arrays. Apart from SNPs, it also [...] Read more.

Although genome-wide association studies (GWAS) have identified several hundred loci associated with autoimmune diseases, their mechanistic insights are still poorly understood. The human genome is more complex than single nucleotide polymorphisms (SNPs) that are interrogated by GWAS arrays. Apart from SNPs, it also comprises genetic variations such as insertions-deletions, copy number variations, and somatic mosaicism. Although previous studies suggest that common copy number variations do not play a major role in autoimmune disease risk, it is possible that certain rare genetic variations with large effect sizes are relevant to autoimmunity. In addition, other layers of regulations such as gene-gene interactions, epigenetic-determinants, gene and environmental interactions also contribute to the heritability of autoimmune diseases. This review focuses on discussing why studying these elements may allow us to gain a more comprehensive understanding of the aetiology of complex autoimmune traits. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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21 pages, 810 KiB

Open AccessReview

Another Round of “Clue” to Uncover the Mystery of Complex Traits

by Shefali Setia Verma and Marylyn D. Ritchie

Genes 2018, 9(2), 61; https://doi.org/10.3390/genes9020061 - 25 Jan 2018

Cited by 7 | Viewed by 5920

Abstract

A plethora of genetic association analyses have identified several genetic risk loci. Technological and statistical advancements have now led to the identification of not only common genetic variants, but also low-frequency variants, structural variants, and environmental factors, as well as multi-omics variations that [...] Read more.

A plethora of genetic association analyses have identified several genetic risk loci. Technological and statistical advancements have now led to the identification of not only common genetic variants, but also low-frequency variants, structural variants, and environmental factors, as well as multi-omics variations that affect the phenotypic variance of complex traits in a population, thus referred to as complex trait architecture. The concept of heritability, or the proportion of phenotypic variance due to genetic inheritance, has been studied for several decades, but its application is mainly in addressing the narrow sense heritability (or additive genetic component) from Genome-Wide Association Studies (GWAS). In this commentary, we reflect on our perspective on the complexity of understanding heritability for human traits in comparison to model organisms, highlighting another round of clues beyond GWAS and an alternative approach, investigating these clues comprehensively to help in elucidating the genetic architecture of complex traits. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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896 KiB

Open AccessReview

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

by Akira Ishikawa

Genes 2017, 8(12), 347; https://doi.org/10.3390/genes8120347 - 27 Nov 2017

Cited by 13 | Viewed by 5127

Abstract

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for [...] Read more.

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example. Full article

(This article belongs to the Special Issue Complex Genetic Loci)

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