Linkage disequilibrium and the search for complex disease genes

Genetic Diversity Analysis and Prediction of Potential Suitable Areas for the Rare and Endangered Wild Plant Henckelia longisepala

Henckelia longisepala (H. W. Li) D. J. Middleton & Mich. Möller is a rare and endangered plant species found only in Southeastern Yunnan, China, and Northern Vietnam. It is listed as a threatened species in China and recognized as a plant species with extremely small populations (PSESP), while also having high ornamental value and utilization potential. This study used ddRAD-seq technology to quantify genetic diversity and structure for 32 samples from three extant populations of H. longisepala. The H. longisepala populations were found to have low levels of genetic diversity (Ho = 0.1216, He = 0.1302, Pi = 0.1731, FIS = 0.1456), with greater genetic differentiation observed among populations (FST = 0.3225). As indicated by genetic structure and phylogenetic analyses, samples clustered into three distinct genetic groups that corresponded to geographically separate populations. MaxEnt modeling was used to identify suitable areas for H. longisepala across three time periods and two climate scenarios (SSP1-2.6, SSP5-8.5). High-suitability areas were identified in Southeastern Yunnan Province, Northern Vietnam, and Eastern Laos. Future H. longisepala distribution was predicted to remain centered in these areas, but with a decrease in the total amount of suitable habitat. The present study provides key data on H. longisepala genetic diversity, as well as a theoretical basis for the conservation, development, and utilization of its germplasm resources.

ZmARF1 positively regulates low phosphorus stress tolerance via modulating lateral root development in maize

Phosphorus (P) deficiency is one of the most critical factors for plant growth and productivity, including its inhibition of lateral root initiation. Auxin response factors (ARFs) play crucial roles in root development via auxin signaling mediated by genetic pathways. In this study, we found that the transcription factor ZmARF1 was associated with low inorganic phosphate (Pi) stress-related traits in maize. This superior root morphology and greater phosphate stress tolerance could be ascribed to the overexpression of ZmARF1. The knock out mutant zmarf1 had shorter primary roots, fewer root tip number, and lower root volume and surface area. Transcriptomic data indicate that ZmLBD1, a direct downstream target gene, is involved in lateral root development, which enhances phosphate starvation tolerance. A transcriptional activation assay revealed that ZmARF1 specifically binds to the GC-box motif in the promoter of ZmLBD1 and activates its expression. Moreover, ZmARF1 positively regulates the expression of ZmPHR1, ZmPHT1;2, and ZmPHO2, which are key transporters of Pi in maize. We propose that ZmARF1 promotes the transcription of ZmLBD1 to modulate lateral root development and Pi-starvation induced (PSI) genes to regulate phosphate mobilization and homeostasis under phosphorus starvation. In addition, ZmERF2 specifically binds to the ABRE motif of the promoter of ZmARF1 and represses its expression. Collectively, the findings of this study revealed that ZmARF1 is a pivotal factor that modulates root development and confers low-Pi stress tolerance through the transcriptional regulation of the biological function of ZmLBD1 and the expression of key Pi transport proteins.

A Deep Generative-Discriminative Learning for Multimodal Representation in Imaging Genetics

Imaging genetics, one of the foremost emerging topics in the medical imaging field, analyzes the inherent relations between neuroimaging and genetic data. As deep learning has gained widespread acceptance in many applications, pioneering studies employed deep learning frameworks for imaging genetics. However, existing approaches suffer from some limitations. First, they often adopt a simple strategy for joint learning of phenotypic and genotypic features. Second, their findings have not been extended to biomedical applications, e.g., degenerative brain disease diagnosis and cognitive score prediction. Finally, existing studies perform insufficient and inappropriate analyses from the perspective of data science and neuroscience. In this work, we propose a novel deep learning framework to simultaneously tackle the aforementioned issues. Our proposed framework learns to effectively represent the neuroimaging and the genetic data jointly, and achieves state-of-the-art performance when used for Alzheimer's disease and mild cognitive impairment identification. Furthermore, unlike the existing methods, the framework enables learning the relation between imaging phenotypes and genotypes in a nonlinear way without any prior neuroscientific knowledge. To demonstrate the validity of our proposed framework, we conducted experiments on a publicly available dataset and analyzed the results from diverse perspectives. Based on our experimental results, we believe that the proposed framework has immense potential to provide new insights and perspectives in deep learning-based imaging genetics studies.

Is BRD7 associated with spermatogenesis impairment and male infertility in humans? A case-control study in a Han Chinese population

Background

Bromodomain-containing protein 7 (BRD7), a member of the bromodomain-containing protein family, plays important roles in chromatin modification and transcriptional regulation. A recent model of Brd7-knockout mice presented azoospermia and male infertility, implying the potential role of BRD7 in spermatogenic failure in humans. This case-control study aimed to explore the association of the BRD7 gene with spermatogenic efficiency and the risk of spermatogenic defects in humans.

Results

A total of six heterozygous variants were detected in the coding and splicing regions of the BRD7 gene in patients with azoospermia. For each of four rare variants predicted to potentially damage BRD7 function, we further identified these four variants in oligozoospermia and normozoospermia as well. However, no difference in the allele and genotype frequencies of rare variants were observed between cases with spermatogenic failure and controls with normozoospermia; the sperm products of variant carriers were similar to those of noncarriers. Moreover, similar distribution of the alleles, genotypes and haplotypes of seven tag single nucleotide polymorphisms (tagSNPs) was observed between the cases with azoospermia and oligozoospermia and controls with normozoospermia; associations of tagSNP-distinguished BRD7 alleles with sperm products were not identified.

Conclusions

The lack of an association of BRD7-linked rare and common variants with spermatogenic failure implied a limited contribution of the BRD7 gene to spermatogenic efficiency and susceptibility to male infertility in humans.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12610-021-00139-3.

Association of the Sp1 binding site and -1997 promoter variations in COL1A1 with osteoporosis risk: The application of meta-analysis and bioinformatics approaches offers a new perspective for future research

As a complex disease, osteoporosis is influenced by several genetic markers. Many studies have examined the link between the Sp1 binding site +1245 G > T (rs1800012) and -1997 G > T (rs1107946) variations in the COL1A1 gene with osteoporosis risk. However, the findings of these studies have been contradictory; therefore, we performed a meta-analysis to aggregate additional information and obtain increased statistical power to more efficiently estimate this correlation. A meta-analysis was conducted with studies published between 1991-2020 that were identified by a systematic electronic search of the Scopus and Clarivate Analytics databases. Studies with bone mineral density (BMD) data and complete genotypes of the single-nucleotide variations (SNVs) for the overall and postmenopausal female population were included in this meta-analysis and analyzed using the R metaphor package. A relationship between rs1800012 and significantly decreased BMD values at the lumbar spine and femoral neck was found in individuals carrying the "ss" versus the "SS" genotype in the overall population according to a random effects model (p < 0.0001). Similar results were also found in the postmenopausal female population (p = 0.003 and 0.0002, respectively). Such findings might be an indication of increased osteoporosis risk in both studied groups in individuals with the "ss" genotype. Although no association was identified between the -1997 G > T and low BMD in the overall population, those individuals with the "GT" genotype showed a higher level of BMD than those with "GG" in the subgroup analysis (p = 0.007). To determine which transcription factor (TF) might bind to the -1997 G > T in COL1A1, 45 TFs were identified based on bioinformatics predictions. According to the GSE35958 microarray dataset, 16 of 45 TFs showed differential expression profiles in osteoporotic human mesenchymal stem cells relative to normal samples from elderly donors. By identifying candidate TFs for the -1997 G > T site, our study offers a new perspective for future research.

Identification of Potential Genes for Benign Prostatic Hyperplasia and Prostate Cancer Susceptibility in Four X-chromosome Regions with High Frequency of Microvariant Alleles

BACKGROUND

The X-chromosome has been suggested to play a role in prostate cancer (PrCa) since epidemiological studies have provided evidence for an X-linked mode of inheritance for PrCa based on the higher relative risk among men who report an affected brother(s) as compared to those reporting an affected father. The aim of this study was to examine the potential association between the forensic STR markers located at four regions Xp22.31, Xq11.2-12, Xq26.2, and Xq28 and the risk of BPH and PrCa to confirm the impact of ChrX in the PrCa incidence. This may be helpful in the incorporation of STRs genetic variation in the early detection of men population at risk of developing PrCa.

METHODS

DNA samples from 92 patients and 156 healthy controls collected from two medical centers in Riyadh, Saudi Arabia were analyzed for four regions located at X-chromosome using the Investigator® Argus X-12 QS Kit.

RESULTS

The results demonstrated that microvariant alleles of (DXS7132, DXS10146, HPRTB, DXS10134, and DXS10135) are overrepresented in the BPH group (p < 0.00001). Allele 28 of DXS10135 and allele 15 of DXS7423 could have a protective effect, OR 0.229 (95%CI, 0.066-0.79); and OR 0.439 (95%CI, 0.208-0.925). On the other hand, patients carrying allele 23 of DXS10079 and allele 26 of DXS10148 presented an increased risk to PrCa OR 4.714 (95%CI, 3.604-6.166).

CONCLUSION

The results are in concordance with the involvement of the X chromosome in PrCa and BPH development. STR allele studies may add further information from the definition of a genetic profile of PrCa resistance or susceptibility. As TBL1, AR, LDOC1, and RPL10 genes are located at regions Xp22.31, Xq11.2-12, Xq26.2, and Xq28, respectively, these genes could play an essential role in PrCa or BPH.

Molecular-Assisted Distinctness and Uniformity Testing Using SLAF-Sequencing Approach in Soybean

Distinctness, uniformity and stability (DUS) testing of cultivars through morphological descriptors is an important and compulsory part of soybean breeding. Molecular markers are usually more effective and accurate in describing the genetic features for the identification and purity assessment of cultivars. In the present study, we assessed the distinctness and uniformity of five soybean cultivars using both single nucleotide polymorphism (SNP) markers developed by specific-locus amplified fragment sequencing (SLAF-seq) technology, and simple sequence repeat (SSR) markers. The phylogenetic tree and principal component analysis (PCA) from both the SLAF-seq and SSR methods showed a clear distinction among cultivars Zhonghuang 18, Zhonghuang 68 and Zhonghuang 35, while no clear distinction was observed between cultivars Zhonghuang 13 and Hedou 13. Using the SLAF-seq method, we determined the proportion of homozygous loci for the five soybean cultivars. The heterozygosity of each individual plant was estimated for the assessment of cultivar purity and the purity levels of the five soybean cultivars ranged from 91.89% to 93.96%. To further validate the applicability of the SLAF-seq approach for distinctness testing, we used the SNP information of 150 soybean cultivars with different origins. The cultivars were also distinguished clearly. Taken together, SLAF-seq can be used as an accurate and reliable method in the assessment of the distinctness and uniformity of soybean cultivars.

On the Extent of Linkage Disequilibrium in the Genome of Farm Animals

Given the importance of linkage disequilibrium (LD) in gene mapping and evolutionary inferences, I characterize in this review the pattern of LD and discuss the influence of human intervention during domestication, breed establishment, and subsequent genetic improvement on shaping the genome of livestock species. To this end, I summarize data on the profile of LD based on array genotypes vs. sequencing data in cattle and chicken, two major livestock species, and compare to the human case. This comparison provides insights into the real dimension of the pairwise allelic correlation and haplo-block structuring. The dependency of LD on allelic frequency is pictured and a recently introduced metric for moderating it is outlined. In the context of the contact farm animals had with human, the impact of genetic forces including admixture, mutation, recombination rate, selection, and effective population size on LD is discussed. The review further highlights the interplay of LD with runs of homozygosity and concludes with the operational implications of the widely used association and selection mapping studies in relation to LD.

Genomic selection for non-key traits in radiata pine when the documented pedigree is corrected using DNA marker information

Background

Non-key traits (NKTs) in radiata pine (Pinus radiata D. Don) refer to traits other than growth, wood density and stiffness, but still of interest to breeders. Branch-cluster frequency, stem straightness, external resin bleeding and internal checking are examples of such traits and are targeted for improvement in radiata pine research programmes. Genomic selection can be conducted before the performance of selection candidates is available so that generation intervals can be reduced. Radiata pine is a species with a long generation interval, which if reduced could significantly increase genetic gain per unit of time. The aim of this study was to evaluate the accuracy and predictive ability of genomic selection and its efficiency over traditional forward selection in radiata pine for the following NKTs: branch-cluster frequency, stem straightness, internal checking, and external resin bleeding.

Results

Nine hundred and eighty-eight individuals were genotyped using exome capture genotyping by sequencing (GBS) and 67,168 single nucleotide polymorphisms (SNPs) used to develop genomic estimated breeding values (GEBVs) with genomic best linear unbiased prediction (GBLUP). The documented pedigree was corrected using a subset of 704 SNPs. The percentage of trio parentage confirmed was about 49% and about 50% of parents were re-assigned. The accuracy of GEBVs was 0.55–0.75 when using the documented pedigree and 0.61–0.80 when using the SNP-corrected pedigree. A higher percentage of additive genetic variance was explained and a higher predictive ability was observed when using the SNP-corrected pedigree than using the documented pedigree. With the documented pedigree, genomic selection was similar to traditional forward selection when assuming a generation interval of 17 years, but worse than traditional forward selection when assuming a generation interval of 14 years. After the pedigree was corrected, genomic selection led to 37–115% and 13–77% additional genetic gain over traditional forward selection when generation intervals of 17 years and 14 years were assumed, respectively.

Conclusion

It was concluded that genomic selection with a pedigree corrected by SNP information was an efficient way of improving non-key traits in radiata pine breeding.

Genomic selection for non-key traits in radiata pine when the documented pedigree is corrected using DNA marker information

BACKGROUND

Non-key traits (NKTs) in radiata pine (Pinus radiata D. Don) refer to traits other than growth, wood density and stiffness, but still of interest to breeders. Branch-cluster frequency, stem straightness, external resin bleeding and internal checking are examples of such traits and are targeted for improvement in radiata pine research programmes. Genomic selection can be conducted before the performance of selection candidates is available so that generation intervals can be reduced. Radiata pine is a species with a long generation interval, which if reduced could significantly increase genetic gain per unit of time. The aim of this study was to evaluate the accuracy and predictive ability of genomic selection and its efficiency over traditional forward selection in radiata pine for the following NKTs: branch-cluster frequency, stem straightness, internal checking, and external resin bleeding.

RESULTS

Nine hundred and eighty-eight individuals were genotyped using exome capture genotyping by sequencing (GBS) and 67,168 single nucleotide polymorphisms (SNPs) used to develop genomic estimated breeding values (GEBVs) with genomic best linear unbiased prediction (GBLUP). The documented pedigree was corrected using a subset of 704 SNPs. The percentage of trio parentage confirmed was about 49% and about 50% of parents were re-assigned. The accuracy of GEBVs was 0.55-0.75 when using the documented pedigree and 0.61-0.80 when using the SNP-corrected pedigree. A higher percentage of additive genetic variance was explained and a higher predictive ability was observed when using the SNP-corrected pedigree than using the documented pedigree. With the documented pedigree, genomic selection was similar to traditional forward selection when assuming a generation interval of 17 years, but worse than traditional forward selection when assuming a generation interval of 14 years. After the pedigree was corrected, genomic selection led to 37-115% and 13-77% additional genetic gain over traditional forward selection when generation intervals of 17 years and 14 years were assumed, respectively.

CONCLUSION

It was concluded that genomic selection with a pedigree corrected by SNP information was an efficient way of improving non-key traits in radiata pine breeding.

Measuring consistency among gene set analysis methods: A systematic study

Gene set analysis is a quantitative approach for generating biological insight from gene expression datasets. The abundance of gene set analysis methods speaks to their popularity, but raises the question of the extent to which results are affected by the choice of method. Our systematic analysis of 13 popular methods using 6 different datasets, from both DNA microarray and RNA-Seq origin, shows that this choice matters a great deal. We observed that the overall number of gene sets reported by each method differed by up to 2 orders of magnitude, and there was a bias toward reporting large gene sets with some methods. Furthermore, there was substantial disagreement between the 20 most statistically significant gene sets reported by the methods. This was also observed when expanding to the 100 most statistically significant reported gene sets. For different datasets of the same phenotype/condition, the top 20 and top 100 most significant results also showed little to no agreement even when using the same method. GAGE, PAGE, and ORA were the only methods able to achieve relatively high reproducibility when comparing the 20 and 100 most statistically significant gene sets. Biological validation on a juvenile idiopathic arthritis (JIA) dataset showed wide variation in terms of the relevance of the top 20 and top 100 most significant gene sets to known biology of the disease, where GAGE predicted the most relevant gene sets, followed by GSEA, ORA, and PAGE.

Association score testing for rare variants and binary traits in family data with shared controls

Genome-wide association studies have been an important approach used to localize trait loci, with primary focus on common variants. The multiple rare variant-common disease hypothesis may explain the missing heritability remaining after accounting for identified common variants. Advances of sequencing technologies with their decreasing costs, coupled with methodological advances in the context of association studies in large samples, now make the study of rare variants at a genome-wide scale feasible. The resurgence of family-based association designs because of their advantage in studying rare variants has also stimulated more methods development, mainly based on linear mixed models (LMMs). Other tests such as score tests can have advantages over the LMMs, but to date have mainly been proposed for single-marker association tests. In this article, we extend several score tests (χcorrected2, WQLS, and SKAT) to the multiple variant association framework. We evaluate and compare their statistical performances relative with the LMM. Moreover, we show that three tests can be cast as the difference between marker allele frequencies (AFs) estimated in each of the group of affected and unaffected subjects. We show that these tests are flexible, as they can be based on related, unrelated or both related and unrelated subjects. They also make feasible an increasingly common design that only sequences a subset of affected subjects (related or unrelated) and uses for comparison publicly available AFs estimated in a group of healthy subjects. Finally, we show the great impact of linkage disequilibrium on the performance of all these tests.

HLA-B*58:01 and rs9263726 have a linkage, but not absolute linkage disequilibrium in Han Chinese population

HLA-B*58:01 has been demonstrated to be associated with allopurinol-induced severe cutaneous adverse reactions. Since HLA-B*58:01 is too complicated to be identified, it is necessary to select an appropriate surrogate biomarker. In Japan, the rs9263726 allele was considered as a surrogate biomarker for HLA-B*58:01, but this was not the case with the Australian cohort. Due to the conflict results, in this study, we aim to demonstrate whether the rs9263726 allele is a surrogate biomarker for HLA-B*58:01 in Han Chinese population. A total of 353 samples (200 cases from the south and 153 cases from the north) were selected to detect HLA-B*58:01 and rs9263726 allele. The HLA-B*58:01 was identified by sequencing-based method, and the rs9263726 allele was identified by Taqman SNP Genotyping Assays. The results showed that the two alleles had a linkage, but not absolute linkage disequilibrium in Han Chinese population.

Genetic Architecture of Dietary Fiber and Oligosaccharide Content in a Middle American Panel of Edible Dry Bean

Common bean ( L.) is the most consumed edible grain legume worldwide and contains a wide range of nutrients for human health including dietary fiber. Diets high in beans are associated with lower rates of chronic diseases such as obesity and type 2 diabetes, and the content of dietary fibers varies among different market classes of dry bean. In this study, we evaluated the dietary fiber content in a Middle American diversity panel (MDP) of common bean and evaluated the genetic architecture of the various dietary fiber components. The dietary fiber components included insoluble and soluble dietary fibers as well as the antinutritional raffinose family of oligosaccharides (RFOs; raffinose, stachyose, and verbascose). All variables measured differed among market classes and entries. Colored bean seeds had higher levels of insoluble dietary fibers with the black market class showing also the highest raffinose and stachyose content. Cultivars and lines released since 1997 had higher insoluble dietary fibers and RFO content in race Durango. Higher levels of RFOs were also observed in cultivars with type II growth habit that was a recent breeding target in Durango race germplasm. Candidate genes for dietary fiber traits, especially homologs to two main genes in the RFO biosynthesis pathway, were identified. The knowledge of diversity of dietary fibers in the MDP accompanied with the identification of candidate genes could effectively improve dietary fiber components in common bean.

The Rise and Fall and Rise of Linkage Analysis as a Technique for Finding and Characterizing Inherited Influences on Disease Expression

For many years, family-based studies using linkage analysis represented the primary approach for identifying disease genes. This strategy is responsible for the identification of the greatest number of genes proven to cause human disease. However, technical advancements in next generation sequencing and high throughput genotyping, coupled with the apparent simplicity of association testing, led to the rejection of family-based studies and of linkage analysis. At present, genetic association methods, using case-control comparisons, have become the exclusive approach for detecting disease-related genes, particularly those underlying common, complex diseases. In this chapter, we present a historical overview of linkage analysis, including a description of how the approach works, as well as its strengths and weaknesses. We discuss how the transition from family-based studies to population comparison association studies led to a critical loss of information with respect to genetic etiology and inheritance, and we present historical and contemporary examples of linkage analysis "success stories" in identifying genes contributing to the development of human disease. Currently, linkage analysis is re-emerging as a useful approach for identifying disease genes, determining genetic parameters, and resolving genetic heterogeneity. We posit that the combination of linkage analysis, association testing, and high throughput sequencing provides a powerful approach for identifying disease-causing genes.

First description and evaluation of SNPs in the ADH and ALDH genes in a population of alcoholics in Central-West Brazil

Worldwide, different studies have reported an association of alcohol-use disorder (AUD) with different types of Single Nucleotide Polymorphisms (SNPs) in the genes for aldehyde dehydrogenase (ALDH) and alcohol dehydrogenase (ADH). In Brazil, there is little information about the occurrence of these SNPs in the AUD population and an absence of studies characterizing the population in the Central-West Region of Brazil. Actually, in Brazil, there are more than 4 million people with AUD. Despite the major health hazards of AUD, information on alcohol consumption and its consequences are not well understood. Therefore, it is extremely important to characterize these SNPs for the better understanding of AUD as a genetic disease in the Brazilian population. The present study, unlike other studies in other countries, is done with a subject population that shows a significant amount of racial homogenization. We evaluated the presence of SNPs in the ADH (ADH1B, ADH1C, and ADH4) and ALDH (ALDH2) genes in alcohol users of Goiânia, State of Goiás - Brazil, and then we established a possible relationship with AUD by allelic and genotypic study. This study was conducted with a population of people with AUD (n = 99) from Goiás Alcohol Dependence Recovery Center (GO CEREA) and Psychosocial Care Center for Alcohol and Drugs (CAPS AD), and with a population of people without AUD as controls (n = 100). DNA was extracted from whole-blood samples and the genotyping was performed using TaqMan^® SNP genotyping assays. For characterization and evaluation of SNPs in the population, genotype frequency, allele frequency, haplotype frequency, Hardy-Weinberg equilibrium, and linkage disequilibrium were analyzed. Statistical analyses were calculated by GENEPOP 4.5 and Haploview software. The allele 1 was considered as "wild" (or *1) and allele 2 as mutant (or *2). Significant differences were found for ADH1B*, ADH4*2, and ALDH2*2 SNPs when the genotype and allele frequencies were analyzed. In addition, four haplotypes were observed between ADH1B*2 and ADH1C*2 through linkage disequilibrium analysis. The genetic variants may be associated with protection against AUD in the population studied.

Genetic diversity, linkage disequilibrium, and association mapping analyses of Gossypium barbadense L. germplasm

Limited polymorphism and narrow genetic base, due to genetic bottleneck through historic domestication, highlight a need for comprehensive characterization and utilization of existing genetic diversity in cotton germplasm collections. In this study, 288 worldwide Gossypium barbadense L. cotton germplasm accessions were evaluated in two diverse environments (Uzbekistan and USA). These accessions were assessed for genetic diversity, population structure, linkage disequilibrium (LD), and LD-based association mapping (AM) of fiber quality traits using 108 genome-wide simple sequence repeat (SSR) markers. Analyses revealed structured population characteristics and a high level of intra-variability (67.2%) and moderate interpopulation differentiation (32.8%). Eight percent and 4.3% of markers revealed LD in the genome of the G. barbadense at critical values of r2 ≥ 0.1 and r2 ≥ 0.2, respectively. The LD decay was on average 24.8 cM at the threshold of r2 ≥ 0.05. LD retained on average distance of 3.36 cM at the threshold of r2 ≥ 0.1. Based on the phenotypic evaluations in the two diverse environments, 100 marker loci revealed a strong association with major fiber quality traits using mixed linear model (MLM) based association mapping approach. Fourteen marker loci were found to be consistent with previously identified quantitative trait loci (QTLs), and 86 were found to be new unreported marker loci. Our results provide insights into the breeding history and genetic relationship of G. barbadense germplasm and should be helpful for the improvement of cotton cultivars using molecular breeding and omics-based technologies.

Exploiting Linkage Disequilibrium for Ultrahigh-Dimensional Genome-Wide Data with an Integrated Statistical Approach

Genome-wide data with millions of single-nucleotide polymorphisms (SNPs) can be highly correlated due to linkage disequilibrium (LD). The ultrahigh dimensionality of big data brings unprecedented challenges to statistical modeling such as noise accumulation, the curse of dimensionality, computational burden, spurious correlations, and a processing and storing bottleneck. The traditional statistical approaches lose their power due to [Formula: see text] (n is the number of observations and p is the number of SNPs) and the complex correlation structure among SNPs. In this article, we propose an integrated distance correlation ridge regression (DCRR) approach to accommodate the ultrahigh dimensionality, joint polygenic effects of multiple loci, and the complex LD structures. Initially, a distance correlation (DC) screening approach is used to extensively remove noise, after which LD structure is addressed using a ridge penalized multiple logistic regression (LRR) model. The false discovery rate, true positive discovery rate, and computational cost were simultaneously assessed through a large number of simulations. A binary trait of Arabidopsis thaliana, the hypersensitive response to the bacterial elicitor AvrRpm1, was analyzed in 84 inbred lines (28 susceptibilities and 56 resistances) with 216,130 SNPs. Compared to previous SNP discovery methods implemented on the same data set, the DCRR approach successfully detected the causative SNP while dramatically reducing spurious associations and computational time.

Identification of Genetic Loci Associated with Quality Traits in Almond via Association Mapping

To design an appropriate association study, we need to understand population structure and the structure of linkage disequilibrium within and among populations as well as in different regions of the genome in an organism. In this study, we have used a total of 98 almond accessions, from five continents located and maintained at the Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA; Spain), and 40 microsatellite markers. Population structure analysis performed in 'Structure' grouped the accessions into two principal groups; the Mediterranean (Western-Europe) and the non-Mediterranean, with K = 3, being the best fit for our data. There was a strong subpopulation structure with linkage disequilibrium decaying with increasing genetic distance resulting in lower levels of linkage disequilibrium between more distant markers. A significant impact of population structure on linkage disequilibrium in the almond cultivar groups was observed. The mean r2 value for all intra-chromosomal loci pairs was 0.040, whereas, the r2 for the inter-chromosomal loci pairs was 0.036. For analysis of association between the markers and phenotypic traits, five models comprising both general linear models and mixed linear models were selected to test the marker trait associations. The mixed linear model (MLM) approach using co-ancestry values from population structure and kinship estimates (K model) as covariates identified a maximum of 16 significant associations for chemical traits and 12 for physical traits. This study reports for the first time the use of association mapping for determining marker-locus trait associations in a world-wide almond germplasm collection. It is likely that association mapping will have the most immediate and largest impact on the tier of crops such as almond with the greatest economic value.

Development of Vibrio spp. infection resistance related SNP markers using multiplex SNaPshot genotyping method in the clam Meretrix meretrix

The clam Meretrix meretrix is a commercially important mollusc species in the coastal areas of South and Southeast Asia. In the present study, large-scale SNPs were genotyped by the Multiplex SNaPshot genotyping method among the stocks of M. meretrix with different Vibrio spp. infection resistance profile. Firstly, the AUTOSNP software was applied to mine SNPs from M. meretrix transcriptome, and 323 SNP loci (including 120 indels) located on 64 contigs were selected based on Uniprot-GO associations. Then, 38 polymorphic SNP loci located on 15 contigs were genotyped successfully in the clam stocks with different resistance to Vibrio parahaemolyticus infection (11-R and 11-S groups). Pearson's Chi-square test was applied to compare the allele and genotype frequency distributions of the SNPs between the different stocks, and seven SNP markers located on three contigs were found to be associated with V. parahaemolyticus infection resistance trait. Haplotype-association analysis showed that six haplotypes had significantly different frequency distributions in 11-S and 11-R (P < 0.05). With selective genotyping between 09-R and 09-C populations, which had different resistance to Vibrio harveyi infection, four out of the seven selected SNPs had significantly different distributions (P < 0.05) and therefore they were considered to be associated with Vibrio spp. infection resistance. Sequence alignments and annotations indicated that the contigs containing the associated SNPs had high similarity to the immune related genes. All these results would be useful for the future marker-assisted selection of M. meretrix strains with high Vibrio spp. infection resistance.

Comparative analysis of disease-linked single nucleotide polymorphic markers from Brassica rapa for their applicability to Brassica oleracea

Numerous studies using single nucleotide polymorphisms (SNPs) have been conducted in humans, and other animals, and in major crops, including rice, soybean, and Chinese cabbage. However, the number of SNP studies in cabbage is limited. In this present study, we evaluated whether 7,645 SNPs previously identified as molecular markers linked to disease resistance in the Brassica rapa genome could be applied to B. oleracea. In a BLAST analysis using the SNP sequences of B. rapa and B. oleracea genomic sequence data registered in the NCBI database, 256 genes for which SNPs had been identified in B. rapa were found in B. oleracea. These genes were classified into three functional groups: molecular function (64 genes), biological process (96 genes), and cellular component (96 genes). A total of 693 SNP markers, including 145 SNP markers [BRH—developed from the B. rapa genome for high-resolution melt (HRM) analysis], 425 SNP markers (BRP—based on the B. rapa genome that could be applied to B. oleracea), and 123 new SNP markers (BRS—derived from BRP and designed for HRM analysis), were investigated for their ability to amplify sequences from cabbage genomic DNA. In total, 425 of the SNP markers (BRP-based on B. rapa genome), selected from 7,645 SNPs, were successfully applied to B. oleracea. Using PCR, 108 of 145 BRH (74.5%), 415 of 425 BRP (97.6%), and 118 of 123 BRS (95.9%) showed amplification, suggesting that it is possible to apply SNP markers developed based on the B. rapa genome to B. oleracea. These results provide valuable information that can be utilized in cabbage genetics and breeding programs using molecular markers derived from other Brassica species.

Population structure and genetic diversity characterization of a sunflower association mapping population using SSR and SNP markers

BACKGROUND

Argentina has a long tradition of sunflower breeding, and its germplasm is a valuable genetic resource worldwide. However, knowledge of the genetic constitution and variability levels of the Argentinean germplasm is still scarce, rendering the global map of cultivated sunflower diversity incomplete. In this study, 42 microsatellite loci and 384 single nucleotide polymorphisms (SNPs) were used to characterize the first association mapping population used for quantitative trait loci mapping in sunflower, along with a selection of allied open-pollinated and composite populations from the germplasm bank of the National Institute of Agricultural Technology of Argentina. The ability of different kinds of markers to assess genetic diversity and population structure was also evaluated.

RESULTS

The analysis of polymorphism in the set of sunflower accessions studied here showed that both the microsatellites and SNP markers were informative for germplasm characterization, although to different extents. In general, the estimates of genetic variability were moderate. The average genetic diversity, as quantified by the expected heterozygosity, was 0.52 for SSR loci and 0.29 for SNPs. Within SSR markers, those derived from non-coding regions were able to capture higher levels of diversity than EST-SSR. A significant correlation was found between SSR and SNP- based genetic distances among accessions. Bayesian and multivariate methods were used to infer population structure. Evidence for the existence of three different genetic groups was found consistently across data sets (i.e., SSR, SNP and SSR + SNP), with the maintainer/restorer status being the most prevalent characteristic associated with group delimitation.

CONCLUSION

The present study constitutes the first report comparing the performance of SSR and SNP markers for population genetics analysis in cultivated sunflower. We show that the SSR and SNP panels examined here, either used separately or in conjunction, allowed consistent estimations of genetic diversity and population structure in sunflower breeding materials. The generated knowledge about the levels of diversity and population structure of sunflower germplasm is an important contribution to this crop breeding and conservation.

Assortative mating drives linkage disequilibrium between sperm and egg recognition protein loci in the sea urchin Strongylocentrotus purpuratus

Sperm and eggs have interacting proteins on their surfaces that influence their compatibility during fertilization. These proteins are often polymorphic within species, producing variation in gamete affinities. We first demonstrate the fitness consequences of various sperm bindin protein (Bindin) variants in the sea urchin Strongylocentrotus purpuratus, and assortative mating between males and females based on their sperm Bindin genotype. This empirical finding of assortative mating based on sperm Bindin genotype could arise by linkage disequilibrium (LD) between interacting sperm and egg recognition loci. We then examine sequence variation in eight exons of the sea urchin egg receptor for sperm Bindin (EBR1). We find little evidence of LD among the eight exons of EBR1, yet strong evidence for LD between sperm Bindin and EBR1 overall, and varying degrees of LD between sperm Bindin among the eight exons. We reject the alternate hypotheses of LD driven by shared evolutionary histories, population structure, or close physical linkage between these interacting loci on the genome. The most parsimonious explanation for this pattern of LD is that it represents selection driven by assortative mating based on interactions among these sperm and egg loci. These findings indicate the importance of ongoing sexual selection in the maintenance of protein polymorphisms and LD, and more generally highlight how LD can be used as an indication of current mate choice, as opposed to historic selection.

Extensive genome-wide autozygosity in the population isolates of Daghestan

Isolated populations are valuable resources for mapping disease genes, as inbreeding increases genome-wide homozygosity and enhances the ability to map disease alleles on a genetically uniform background within a relatively homogenous environment. The populations of Daghestan are thought to have resided in the Caucasus Mountains for hundreds of generations and are characterized by a high prevalence of certain complex diseases. To explore the extent to which their unique population history led to increased levels of inbreeding, we genotyped >550 000 autosomal single-nucleotide polymorphisms (SNPs) in a set of 14 population isolates speaking Nakh-Daghestanian (ND) languages. The ND-speaking populations showed greatly elevated coefficients of inbreeding, very high numbers and long lengths of Runs of Homozygosity, and elevated linkage disequilibrium compared with surrounding groups from the Caucasus, the Near East, Europe, Central and South Asia. These results are consistent with the hypothesis that most ND-speaking groups descend from a common ancestral population that fragmented into a series of genetic isolates in the Daghestanian highlands. They have subsequently maintained a long-term small effective population size as a result of constant inbreeding and very low levels of gene flow. Given these findings, Daghestanian population isolates are likely to be useful for mapping genes associated with complex diseases.

Case-only exome sequencing and complex disease susceptibility gene discovery: study design considerations

Whole exome sequencing (WES) provides an unprecedented opportunity to identify the potential aetiological role of rare functional variants in human complex diseases. Large-scale collaborations have generated germline WES data on patients with a number of diseases, especially cancer, but less often on healthy controls under the same sequencing procedures. These data can be a valuable resource for identifying new disease susceptibility loci if study designs are appropriately applied. This review describes suggested strategies and technical considerations when focusing on case-only study designs that use WES data in complex disease scenarios. These include variant filtering based on frequency and functionality, gene prioritisation, interrogation of different data types and targeted sequencing validation. We propose that if case-only WES designs were applied in an appropriate manner, new susceptibility genes containing rare variants for human complex diseases can be detected.

Edge biomarkers for classification and prediction of phenotypes

In general, a disease manifests not from malfunction of individual molecules but from failure of the relevant system or network, which can be considered as a set of interactions or edges among molecules. Thus, instead of individual molecules, networks or edges are stable forms to reliably characterize complex diseases. This paper reviews both traditional node biomarkers and edge biomarkers, which have been newly proposed. These biomarkers are classified in terms of their contained information. In particular, we show that edge and network biomarkers provide novel ways of stably and reliably diagnosing the disease state of a sample. First, we categorize the biomarkers based on the information used in the learning and prediction steps. We then briefly introduce conventional node biomarkers, or molecular biomarkers without network information, and their computational approaches. The main focus of this paper is edge and network biomarkers, which exploit network information to improve the accuracy of diagnosis and prognosis. Moreover, by extracting both network and dynamic information from the data, we can develop dynamical network and edge biomarkers. These biomarkers not only diagnose the immediate pre-disease state but also detect the critical molecules or networks by which the biological system progresses from the healthy to the disease state. The identified critical molecules can be used as drug targets, and the critical state indicates the critical point of disease control. The paper also discusses representative biomarker-based methods.

Genome-wide linkage disequilibrium in nine-spined stickleback populations

Variation in the extent and magnitude of genome-wide linkage disequilibrium (LD) among populations residing in different habitats has seldom been studied in wild vertebrates. We used a total of 109 microsatellite markers to quantify the level and patterns of genome-wide LD in 13 Fennoscandian nine-spined stickleback (Pungitius pungitius) populations from four (viz. marine, lake, pond, and river) different habitat types. In general, high magnitude (D' > 0.5) of LD was found both in freshwater and marine populations, and the magnitude of LD was significantly greater in inland freshwater than in marine populations. Interestingly, three coastal freshwater populations located in close geographic proximity to the marine populations exhibited similar LD patterns and genetic diversity as their marine neighbors. The greater levels of LD in inland freshwater compared with marine and costal freshwater populations can be explained in terms of their contrasting demographic histories: founder events, long-term isolation, small effective sizes, and population bottlenecks are factors likely to have contributed to the high levels of LD in the inland freshwater populations. In general, these findings shed new light on the patterns and extent of variation in genome-wide LD, as well as the ecological and evolutionary factors driving them.

Using haplotypes for the prediction of allelic identity to fine-map QTL: characterization and properties

BACKGROUND

Numerous methods have been developed over the last decade to predict allelic identity at unobserved loci between pairs of chromosome segments along the genome. These loci are often unobserved positions tested for the presence of quantitative trait loci (QTL). The main objective of this study was to understand from a theoretical standpoint the relation between linkage disequilibrium (LD) and allelic identity prediction when using haplotypes for fine mapping of QTL. In addition, six allelic identity predictors (AIP) were also compared in this study to determine which one performed best in theory and application.

RESULTS

A criterion based on a simple measure of matrix distance was used to study the relation between LD and allelic identity prediction when using haplotypes. The consistency of this criterion with the accuracy of QTL localization, another criterion commonly used to compare AIP, was evaluated on a set of real chromosomes. For this set of chromosomes, the criterion was consistent with the mapping accuracy of a simulated QTL with either low or high effect. As measured by the matrix distance, the best AIP for QTL mapping were those that best captured LD between a tested position and a QTL. Moreover the matrix distance between a tested position and a QTL was shown to decrease for some AIP when LD increased. However, the matrix distance for AIP with continuous predictions in the [0,1] interval was algebraically proven to decrease less rapidly up to a lower bound with increasing LD in the simplest situations, than the discrete predictor based on identity by state between haplotypes (IBS hap), for which there was no lower bound. The expected LD between haplotypes at a tested position and alleles at a QTL is a quantity that increases naturally when the tested position gets closer to the QTL. This behavior was demonstrated with pig and unrelated human chromosomes.

CONCLUSIONS

When the density of markers is high, and therefore LD between adjacent loci can be assumed to be high, the discrete predictor IBS hap is recommended since it predicts allele identity correctly when taking LD into account.

A biocompatible open-surface droplet manipulation platform for detection of multi-nucleotide polymorphism

We present a novel and simple method to manipulate droplets applicable to an open-surface microfluidic platform. The platform comprised a control module for pneumatic droplets and a superhydrophobic polydimethylsiloxane (PDMS) membrane. With pneumatic suction to cause deflection of the flexible PDMS-based superhydrophobic membrane, the sample and reagent droplets on the membrane become transported and mixed. A facile one-step laser micromachining technique serves to fabricate a superhydrophobic surface; a contact angle of 150° and a hysteresis angle of 4° were achieved without chemical modification. Relative to previous open-surface microfluidic systems, this platform is capable of simultaneous and precise delivery of droplets in two-dimensional (2D) manipulation. Droplets were manipulated with suction, which avoided interference from an external driving energy (e.g. heat, light, electricity) to affect the bio-sample inside the droplets. Two common bio-samples, namely protein and DNA, verified the performance of the platform. Based on the experimental results, operations on protein can be implemented without adsorption on the surface of the platform. Another striking result is the visual screening for multi-nucleotide polymorphism with hybridization-mediated growth of gold-nanoparticle (AuNP) probes. The detection results are observable with the naked eye, without the aid of advanced instruments. The entire procedure only takes 5 min from the addition of the sample and reagent to obtaining the results, which is much quicker than the traditional method. The total sample volume consumed in each operation is only 10 μL, which is significantly less than what is required in a large system. According to this approach, the proposed platform is suitable for biological and chemical applications.

Unraveling the genetics of atherosclerosis: implications for diagnosis and treatment

The hereditary aspect of atherosclerosis has been known for some time in clinical medicine. Over the past three decades, a great deal of research has focused on defining the genetic component of this disease with the hopes that detailed knowledge of the genes and gene variants will lead to improvements in the diagnosis and treatment. This article reviews the different approaches for studying the genetics of atherosclerosis and the potential for using the results in clinical practice.

The architecture of risk for type 2 diabetes: understanding Asia in the context of global findings

The prevalence of Type 2 diabetes is rising rapidly in both developed and developing countries. Asia is developing as the epicentre of the escalating pandemic, reflecting rapid transitions in demography, migration, diet, and lifestyle patterns. The effective management of Type 2 diabetes in Asia may be complicated by differences in prevalence, risk factor profiles, genetic risk allele frequencies, and gene-environment interactions between different Asian countries, and between Asian and other continental populations. To reduce the worldwide burden of T2D, it will be important to understand the architecture of T2D susceptibility both within and between populations. This review will provide an overview of known genetic and nongenetic risk factors for T2D, placing the results from Asian studies in the context of broader global research. Given recent evidence from large-scale genetic studies of T2D, we place special emphasis on emerging knowledge about the genetic architecture of T2D and the potential contribution of genetic effects to population differences in risk.

Polymorphisms in genes involved in folate metabolism modify the association of dietary and circulating folate and vitamin B-6 with cervical neoplasia

High folate intake has been suggested as an important factor in cancer prevention; however, previous studies on the relation among folate intake, serum folate, and plasma homocysteine (hcy) are controversial. We conducted a hospital-based, case-control study in Brazil investigating associations between dietary and circulating vitamins B-6 and B-12 and folate, hcy, genotypes of folate-metabolizing enzyme methylenetetrahydrofolate reductase (MTHFR C677T, A1298C), 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR A2756G), methionine synthase reductase (MTRR A66G), and reduced folate carrier (RFC1 G80A) and risk of cervical intraepithelial neoplasia (CIN) grades 1 (CIN1), 2 (CIN2), and 3 (CIN3). The study was composed by 453 controls, 140 CIN1, 126 CIN2, and 231 CIN3. We investigated the joint effects of genetic variants of folate-related genes using genetic risk scores (GRSs) by summing the number of risk alleles for CIN1 and CIN2+ (CIN2 and CIN3 cases). The OR (95% CI) for CIN1 and CIN2+ per each risk allele were 1.29 (1.01, 1.65) and 1.22 (1.01, 1.46), respectively. An association between folate intake and CIN2+ was observed only after stratification according to GRS: crude OR (95% CI) for lower folate intake and GRS ≥ 4 was 1.67 (0.92, 3.04) (P-trend < 0.001) compared with higher folate intake (above the median) and GRS ≤ 3. The CIN2+ risk of lower serum vitamin B-6 and GRS ≥ 4 was 2.14 (0.92, 5.02) (P-trend = 0.05) and lower serum folate (below the median) and GRS ≥ 4 was 0.49 (0.20, 1.17) (P-trend = 0.05) after adjustment for confounding variables and human papillomavirus infection. Our data suggest that polymorphisms in genes related to folate metabolism modify the association of dietary and circulating folate and vitamin B-6 with cervical neoplasia.

Network biomarkers reveal dysfunctional gene regulations during disease progression

Extensive studies have been conducted on gene biomarkers by exploring the increasingly accumulated gene expression and sequence data generated from high-throughput technology. Here, we briefly report on the state-of-the-art research and application of biomarkers from single genes (i.e. gene biomarkers) to gene sets (i.e. group or set biomarkers), gene networks (i.e. network biomarkers) and dynamical gene networks (i.e. dynamical network biomarkers). In particular, differential and dynamical network biomarkers are used as representative examples to demonstrate their effectiveness in both detecting early signals for complex diseases and revealing essential mechanisms on disease initiation and progression at a network level.

A multidisciplinary approach providing new insight into fruit flesh browning physiology in apple (Malus x domestica Borkh.)

In terms of the quality of minimally processed fruit, flesh browning is fundamentally important in the development of an aesthetically unpleasant appearance, with consequent off-flavours. The development of browning depends on the enzymatic action of the polyphenol oxidase (PPO). In the 'Golden Delicious' apple genome ten PPO genes were initially identified and located on three main chromosomes (2, 5 and 10). Of these genes, one element in particular, here called Md-PPO, located on chromosome 10, was further investigated and genetically mapped in two apple progenies ('Fuji x Pink Lady' and 'Golden Delicious x Braeburn'). Both linkage maps, made up of 481 and 608 markers respectively, were then employed to find QTL regions associated with fruit flesh browning, allowing the detection of 25 QTLs related to several browning parameters. These were distributed over six linkage groups with LOD values spanning from 3.08 to 4.99 and showed a rate of phenotypic variance from 26.1 to 38.6%. Anchoring of these intervals to the apple genome led to the identification of several genes involved in polyphenol synthesis and cell wall metabolism. Finally, the expression profile of two specific candidate genes, up and downstream of the polyphenolic pathway, namely phenylalanine ammonia lyase (PAL) and polyphenol oxidase (PPO), provided insight into flesh browning physiology. Md-PPO was further analyzed and two haplotypes were characterised and associated with fruit flesh browning in apple.

A ferrofluid-based homogeneous assay for highly sensitive and selective detection of single-nucleotide polymorphisms

A simple and low-cost colorimetric assay utilizing ferrofluidic nanoparticulate probes (FNPs) and a ligase for single-nucleotide polymorphism genotyping is described. Excellent sensitivity and selectivity were accomplished through the engagement of the FNPs and a ligase chain reaction.

Frequency of hybridization between Ostrinia nubilalis E-and Z-pheromone races in regions of sympatry within the United States

Female European corn borer, Ostrinia nubilalis, produce and males respond to sex pheromone blends with either E- or Z-Δ11-tetradecenyl acetate as the major component. E- and Z-race populations are sympatric in the Eastern United States, Southeastern Canada, and the Mediterranean region of Europe. The E- and Z-pheromone races of O. nubilalis are models for incipient species formation, but hybridization frequencies within natural populations remain obscure due to lack of a high-throughput phenotyping method. Lassance et al. previously identified a pheromone gland-expressed fatty-acyl reductase gene (pgfar) that controls the ratio of Δ11-tetradecenyl acetate stereoisomers. We identified three single nucleotide polymorphism (SNP) markers within pgfar that are differentially fixed between E- and Z-race females, and that are ≥98.2% correlated with female pheromone ratios measured by gas chromatography. Genotypic data from locations in the United States demonstrated that pgfar-z alleles were fixed within historically allopatric Z-pheromone race populations in the Midwest, and that hybrid frequency ranged from 0.00 to 0.42 within 11 sympatric sites where the two races co-occur in the Eastern United States (mean hybridization frequency or heterozygosity (H O) = 0.226 ± 0.279). Estimates of hybridization between the E- and Z-races are important for understanding the dynamics involved in maintaining race integrity, and are consistent with previous estimates of low levels of genetic divergence between E- and Z-races and the presence of weak prezygotic mating barriers. This work describes the development of new single nucleotide polymorphism (SNP) markers within the pheromone gland expressed fatty acyl reductase (pgfar) gene of Ostrinia nubilalis. These SNPs were shown to segregate based upon female pheromone production, and thus provide the first description of an assay for genetic determination of O. nubilalis pheromone strain from field-collected samples. These assays were applied to estimate hybridization within field populations, and represent valuable tools for future population genetic studies of this species.

The evidence for association of ATP2B2 polymorphisms with autism in Chinese Han population

Background

Autism is a neurodevelopmental disorder with a high estimated heritability. ATP2B2, located on human chromosome 3p25.3, encodes the plasma membrane calcium-transporting ATPase 2 which extrudes Ca²⁺ from cytosol into extracellular space. Recent studies reported association between ATP2B2 and autism in samples from Autism Genetic Resource Exchange (AGRE) and Italy. In this study, we investigated whether ATP2B2 polymorphisms were associated with autism in Chinese Han population.

Methods

We performed a family based association study between five SNPs (rs35678 in exon, rs241509, rs3774180, rs3774179, and rs2278556 in introns) in ATP2B2 and autism in 427 autism trios of Han Chinese descent. All SNPs were genotyped using the Sequenom genotyping platform. The family-based association test (FBAT) program was used to perform association test for SNPs and haplotype analyses.

Results

This study demonstrated a preferential transmission of T allele of rs3774179 to affected offsprings under an additive model (T>C, Z = 2.482, p = 0.013). While C allele of rs3774179 showed an undertransmission from parents to affected children under an additive and a dominant model, respectively (Z = −2.482, p = 0.013; Z = −2.591, p = 0.0096). Haplotype analyses revealed that three haplotypes were significantly associated with autism. The haplotype C-C (rs3774180–rs3774179) showed a significant undertransmission from parents to affected offsprings both in specific and global haplotype FBAT (Z = −2.037, p = 0.042; Global p = 0.03). As for the haplotype constructed by rs3774179 and rs2278556, C-A might be a protective haplotype (Z = −2.206, p = 0.027; Global p = 0.04), while T-A demonstrated an excess transmission from parents to affected offsprings (Z = 2.143, p = 0.032). These results were still significant after using the permutation method to obtain empirical p values.

Conclusions

Our research suggested that ATP2B2 might play a role in the etiology of autism in Chinese Han population.

Assessing the genetic landscape of a contact zone: the case of European hare in northeastern Greece

The European hare populations of the Balkan Peninsula comprise two divergent phylogenetic lineages with discrete geographical distribution slightly overlapping in the area of northeastern Greece and Bulgaria. Here we elucidate their contact zone, by defining the spatial distributional pattern of the two highly divergent groups, detecting individuals of hybrid origin, and identifying genetic barriers present in the area of their co-existence. Specimens from northeastern Greece were assayed for lineage assignment and population genetic inference based on a 511 bp fragment of mitochondrial DNA control region and allelic data from 10 microsatellite loci. Bayesian analyses on original and simulated genotypes were performed allowing for the contact zone delineation. Our results indicate high genetic diversity in both nuclear and mitochondrial DNA, strong population structure and non random spatial distribution of the differentiated gene pools. The information provided by the two types of molecular markers yielded consistent results. This study comprises a fine scale analysis of the contact zone between the two evolutionary lineages of European brown hares in northeastern Greece. Specific questions on the spatial patterns where addressed for the first time. Furthermore, hypotheses regarding the presence of hybrids were also tested. As a result, interpretive power to the diversity patterns observed today in the Balkans was added and previously overlooked aspects of the species biology were highlighted.

Association mapping in sunflower for Sclerotinia Head Rot resistance

BACKGROUND

Sclerotinia Head Rot (SHR) is one of the most damaging diseases of sunflower in Europe, Argentina, and USA, causing average yield reductions of 10 to 20 %, but leading to total production loss under favorable environmental conditions for the pathogen. Association Mapping (AM) is a promising choice for Quantitative Trait Locus (QTL) mapping, as it detects relationships between phenotypic variation and gene polymorphisms in existing germplasm without development of mapping populations. This article reports the identification of QTL for resistance to SHR based on candidate gene AM.

RESULTS

A collection of 94 sunflower inbred lines were tested for SHR under field conditions using assisted inoculation with the fungal pathogen Sclerotinia sclerotiorum. Given that no biological mechanisms or biochemical pathways have been clearly identified for SHR, 43 candidate genes were selected based on previous transcript profiling studies in sunflower and Brassica napus infected with S. sclerotiorum. Associations among SHR incidence and haplotype polymorphisms in 16 candidate genes were tested using Mixed Linear Models (MLM) that account for population structure and kinship relationships. This approach allowed detection of a significant association between the candidate gene HaRIC_B and SHR incidence (P < 0.01), accounting for a SHR incidence reduction of about 20 %.

CONCLUSIONS

These results suggest that AM will be useful in dissecting other complex traits in sunflower, thus providing a valuable tool to assist in crop breeding.