Heterogeneous distribution of SNPs in the human genome: microsatellites as predictors of nucleotide diversity and divergence. Genomics. 2010;95:151-159. [PMID: 20026267 DOI: 10.1016/j.ygeno.2009.12.003]

Polymorphism of ghrelin genes among four Nigerian chicken populations as tool for improvement of chickens

Research on polymorphism of ghrelin (GHRL), an acylated peptide that stimulates the release of growth hormone from the pituitary, has shown that it is associated with some essential growth genes in chicken, hence veritable in genomic selection. There is porous information on the polymorphism of GHRL genes among Nigerian chickens. The objective of this study was to determine polymorphism of ghrelin gene among four Nigerian chicken populations. Blood sample (0.5 ml) was collected from the wing vein of 102 birds for DNA extraction. Tested PCR products were sequenced following Macrogen INC. The SNPs were determined using the sequence alignment program, CLUSTAL W, implemented in MEGA software. The sequence results showed 25 SNPs. The Nigerian chickens varied in polymorphic sites from Ogun chickens (348 and 535) to Nsukka chickens (558 and 696) at the GHRL 1 and GHRL2 loci respectively. Polymorphic sites and diversity were higher among the Nsukka chicken than other populations of the Nigerian chickens. SNPs common to one geographic varied in another. The result revealed that genomic selection based on ghrelin SNPs may yield higher predictive accuracy, while Nsukka chickens could be useful for the creation of more superior lines for the global poultry industry. Since past studies have revealed that ghrelin gene stimulates the pituitary and hypothalamus for releasing growth factor (GF) hormone and have strong effect on many organs, we suggest an association study of ghrelin gene and growth traits.

Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report)

This project originated more than 15 years ago with the intent to produce a glossary of drug metabolism terms having definitions especially applicable for use by practicing medicinal chemists. A first-draft version underwent extensive beta-testing that, fortuitously, engaged international audiences in a wide range of disciplines involved in drug discovery and development. It became clear that the inclusion of information to enhance discussions among this mix of participants would be even more valuable. The present version retains a chemical structure theme while expanding tutorial comments that aim to bridge the various perspectives that may arise during interdisciplinary communications about a given term. This glossary is intended to be educational for early stage researchers, as well as useful for investigators at various levels who participate on today’s highly multidisciplinary, collaborative small molecule drug discovery teams.

Patterns of DNA variation between the autosomes, the X chromosome and the Y chromosome in Bos taurus genome

The new ARS-UCD1.2 assembly of the bovine genome has considerable improvements over the previous assembly and thus more accurate identification of patterns of genetic variation can be achieved with it. We explored differences in genetic variation between autosomes, the X chromosome, and the Y chromosome. In particular, variant densities, annotations, lengths (only for InDels), nucleotide divergence, and Tajima’s D statistics between chromosomes were considered. Whole-genome DNA sequences of 217 individuals representing different cattle breeds were examined. The analysis included the alignment to the new reference genome and variant identification. 23,655,295 SNPs and 3,758,781 InDels were detected. In contrast to autosomes, both sex chromosomes had negative values of Tajima’s D and lower nucleotide divergence. That implies a correlation between nucleotide diversity and recombination rate, which is obviously reduced for sex chromosomes. Moreover, the accumulation of nonsynonymous mutations on the Y chromosome could be associated with loss of recombination. Also, the relatively lower effective population size for sex chromosomes leads to a lower expected density of variants.

Computational Analysis of High-Risk SNPs in Human DBY Gene Responsible for Male Infertility: A Functional and Structural Impact

BACKGROUND

DEAD-box helicase 3, Y-linked (DBY) is a candidate gene of the AZF region which is involved in spermatogenesis process. Mutations in the DBY gene may disrupt the spermatogenesis and lead to infertility in men. Identification of functionally neutral mutation from the disease-causing mutation is the biggest challenge in human genetic variation analysis. Owing to the importance of DBY in male infertility, functional analysis was carried out to reveal the association between genetic mutation and phenotypic variation through various in silico approaches.

METHODS

The present study analyzed the functional consequences of the nsSNPs in human DBY gene using SIFT, PolyPhen 2, PROVEAN, SNAP2, PMut, nsSNPAnalyzer, PhD-SNP and SNPs&GO along with stability analysis through I-Mutant2.0, MuPro and iPTREE-STAB. The conservational analysis of amino acid residues, biophysical properties and conserved domains of the DBY protein was analyzed using various computational tools. The 3D structure of the protein was generated using SPARKS-X and validated using RAMPAGE.

RESULTS

Out of 1130 SNPs reported in dbSNP, only one nsSNP (G300D) was found to have a functional effect on stability as well as the function of the DBY protein. The results showed the presence of G300 in the putative structure of DBY domain.

CONCLUSION

To the best of our knowledge, this is the first study to detect pathologically significant nsSNPs (G300D) through a computational approach in the DBY which can be useful for development in potent drug discovery studies.

Efficient genome-wide genotyping strategies and data integration in crop plants

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration. Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.

Synthetic combinations of missense polymorphic genetic changes underlying Down syndrome susceptibility

Single nucleotide polymorphisms (SNPs) are important biomolecular markers in health and disease. Down syndrome, or Trisomy 21, is the most frequently occurring chromosomal abnormality in live-born children. Here, we highlight associations between SNPs in several important enzymes involved in the one-carbon folate metabolic pathway and the elevated maternal risk of having a child with Down syndrome. Our survey highlights that the combination of SNPs may be a more reliable predictor of the Down syndrome phenotype than single SNPs alone. We also describe recent links between SNPs in p53 and its related pathway proteins and Down syndrome, as well as highlight several proteins that help to associate apoptosis and p53 signaling with the Down syndrome phenotype. In addition to a comprehensive review of the literature, we also demonstrate that several SNPs reside within the same regions as these Down syndrome-linked SNPs, and propose that these closely located nucleotide changes may provide new candidates for future exploration.

Variations at regulatory regions of the milk protein genes are associated with milk traits and coagulation properties in the Sarda sheep

Regulatory variation at the ovine casein genes could have important effects on the composition and coagulation properties of milk. Herewith, we have partially resequenced the promoters and the 3'-UTR of the four casein genes in 25 Sarda sheep. Alignment of these sequences allowed us to identify a total of 29 SNPs. This level of polymorphism (one SNP every 250 bp) is remarkably high if compared with SNP densities estimated in human genic regions (approximately one SNP per bp). The 29 SNPs identified in our resequencing experiment, plus three previously reported SNPs mapping to the lactalbumin, alpha (LALBA) and β-lactoglobulin (BLG, also known as progestagen-associated endometrial protein, PAEP) genes, were genotyped with a multiplex TaqMan Open Array Real-Time PCR assay in 760 Sarda sheep with records for milk composition and coagulation properties. Association analysis revealed the existence of significant associations of CSN1S2 and CSN3 genotypes with milk protein and casein contents. Moreover, genotypes at CSN1S1 were significantly associated with rennet coagulation time, curd firming time and curd firmness, whereas CSN2 was associated with curd firming time. These results suggest that SNPs mapping to the promoters and 3'-UTRs of ovine casein genes may exert regulatory effects on gene expression and that they could be used for improving sheep milk quality and technological traits at the population level through marker assisted selection.

Genome-wide resequencing of KRICE_CORE reveals their potential for future breeding, as well as functional and evolutionary studies in the post-genomic era

Background

Rice germplasm collections continue to grow in number and size around the world. Since maintaining and screening such massive resources remains challenging, it is important to establish practical methods to manage them. A core collection, by definition, refers to a subset of the entire population that preserves the majority of genetic diversity, enhancing the efficiency of germplasm utilization.

Results

Here, we report whole-genome resequencing of the 137 rice mini core collection or Korean rice core set (KRICE_CORE) that represents 25,604 rice germplasms deposited in the Korean genebank of the Rural Development Administration (RDA). We implemented the Illumina HiSeq 2000 and 2500 platform to produce short reads and then assembled those with 9.8 depths using Nipponbare as a reference. Comparisons of the sequences with the reference genome yielded more than 15 million (M) single nucleotide polymorphisms (SNPs) and 1.3 M INDELs. Phylogenetic and population analyses using 2,046,529 high-quality SNPs successfully assigned rice accessions to the relevant rice subgroups, suggesting that these SNPs capture evolutionary signatures that have accumulated in rice subpopulations. Furthermore, genome-wide association studies (GWAS) for four exemplary agronomic traits in the KRIC_CORE manifest the utility of KRICE_CORE; that is, identifying previously defined genes or novel genetic factors that potentially regulate important phenotypes.

Conclusion

This study provides strong evidence that the size of KRICE_CORE is small but contains high genetic and functional diversity across the genome. Thus, our resequencing results will be useful for future breeding, as well as functional and evolutionary studies, in the post-genomic era.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2734-y) contains supplementary material, which is available to authorized users.

Single Nucleotide Polymorphisms as Prognostic and Predictive Factors of Adjuvant Chemotherapy in Colorectal Cancer of Stages I and II

Colorectal cancer (CRC) is a highly heterogeneous disease regarding the stage at time of diagnosis and there is special attention regarding adjuvant chemotherapy in unselected patients with stage I and stage II. The clinicohistologically based TNM staging system with emphasis on histological evaluation of primary tumor and resected regional lymph nodes remains the standard of staging, but it has restricted sensitivity resulting in false downward stage migration. Molecular characteristics might predispose tumors to a worse prognosis and identification of those enables identifying patients with high risk of disease recurrence. Suitable predictive markers also enable choosing the most appropriate therapy. The current challenge facing adjuvant chemotherapy in stages I and II CRC is choosing patients with the highest risk of disease recurrence who are going to derive most benefit without facing unnecessary adverse effects. Single nucleotide polymorphisms (SNPs) are one of the potential molecular markers that might help us identify patients with unfavorable prognostic factors regarding disease initiation and recurrence and could determine selection of an appropriate chemotherapy regimen in the adjuvant and metastatic setting. In this paper, we discuss SNPs of genes involved in the multistep processes of cancerogenesis, metastasis, and the metabolism of chemotherapy that might prove clinically significant.

Inflammatory genes and psychological factors predict induced shoulder pain phenotype

PURPOSE

The pain experience has multiple influences, but little is known about how specific biological and psychological factors interact to influence pain responses. The current study investigated the combined influences of genetic (pro-inflammatory) and psychological factors on several preclinical shoulder pain phenotypes.

METHODS

An exercise-induced shoulder injury model was used, and a priori selected genetic (IL1B, TNF/LTA region, and IL6 single nucleotide polymorphisms (SNP)) and psychological (anxiety, depression symptoms, pain catastrophizing, fear of pain, and kinesiophobia) factors were included as the predictors of interest. The phenotypes were pain intensity (5-d average and peak reported on numerical rating scale), upper extremity disability (5-d average and peak reported on the Quick Disabilities of the Arm, Shoulder and Hand instrument), and duration of shoulder pain (d).

RESULTS

After controlling for age, sex, and race, the genetic and psychological predictors were entered separately as main effects and interaction terms in regression models for each pain phenotype. Results from the recruited cohort (n = 190) indicated strong statistical evidence for the interactions between 1) TNF/LTA SNP rs2229094 and depression symptoms for average pain intensity and duration and 2) IL1B two SNP diplotype and kinesiophobia for average shoulder pain intensity. Moderate statistical evidence for prediction of additional shoulder pain phenotypes included interactions of kinesiophobia, fear of pain, or depressive symptoms with TNF/LTA rs2229094 and IL1B.

CONCLUSIONS

These findings support the combined predictive ability of specific genetic and psychological factors for shoulder pain phenotypes by revealing novel combinations that may merit further investigation in clinical cohorts to determine their involvement in the transition from acute to chronic pain conditions.

Transfer of genetic therapy across human populations: molecular targets for increasing patient coverage in repeat expansion diseases

Allele-specific gene therapy aims to silence expression of mutant alleles through targeting of disease-linked single-nucleotide polymorphisms (SNPs). However, SNP linkage to disease varies between populations, making such molecular therapies applicable only to a subset of patients. Moreover, not all SNPs have the molecular features necessary for potent gene silencing. Here we provide knowledge to allow the maximisation of patient coverage by building a comprehensive understanding of SNPs ranked according to their predicted suitability toward allele-specific silencing in 14 repeat expansion diseases: amyotrophic lateral sclerosis and frontotemporal dementia, dentatorubral-pallidoluysian atrophy, myotonic dystrophy 1, myotonic dystrophy 2, Huntington's disease and several spinocerebellar ataxias. Our systematic analysis of DNA sequence variation shows that most annotated SNPs are not suitable for potent allele-specific silencing across populations because of suboptimal sequence features and low variability (>97% in HD). We suggest maximising patient coverage by selecting SNPs with high heterozygosity across populations, and preferentially targeting SNPs that lead to purine:purine mismatches in wild-type alleles to obtain potent allele-specific silencing. We therefore provide fundamental knowledge on strategies for optimising patient coverage of therapeutics for microsatellite expansion disorders by linking analysis of population genetic variation to the selection of molecular targets.

Increased substitution rates surrounding low-complexity regions within primate proteins

Previous studies have found that DNA-flanking low-complexity regions (LCRs) have an increased substitution rate. Here, the substitution rate was confirmed to increase in the vicinity of LCRs in several primate species, including humans. This effect was also found among human sequences from the 1000 Genomes Project. A strong correlation was found between average substitution rate per site and distance from the LCR, as well as the proportion of genes with gaps in the alignment at each site and distance from the LCR. Along with substitution rates, d_N/d_S ratios were also determined for each site, and the proportion of sites undergoing negative selection was found to have a negative relationship with distance from the LCR.

DNA clustering and genome complexity

Early global measures of genome complexity (power spectra, the analysis of fluctuations in DNA walks or compositional segmentation) uncovered a high degree of complexity in eukaryotic genome sequences. The main evolutionary mechanisms leading to increases in genome complexity (i.e. gene duplication and transposon proliferation) can all potentially produce increases in DNA clustering. To quantify such clustering and provide a genome-wide description of the formed clusters, we developed GenomeCluster, an algorithm able to detect clusters of whatever genome element identified by chromosome coordinates. We obtained a detailed description of clusters for ten categories of human genome elements, including functional (genes, exons, introns), regulatory (CpG islands, TFBSs, enhancers), variant (SNPs) and repeat (Alus, LINE1) elements, as well as DNase hypersensitivity sites. For each category, we located their clusters in the human genome, then quantifying cluster length and composition, and estimated the clustering level as the proportion of clustered genome elements. In average, we found a 27% of elements in clusters, although a considerable variation occurs among different categories. Genes form the lowest number of clusters, but these are the longest ones, both in bp and the average number of components, while the shortest clusters are formed by SNPs. Functional and regulatory elements (genes, CpG islands, TFBSs, enhancers) show the highest clustering level, as compared to DNase sites, repeats (Alus, LINE1) or SNPs. Many of the genome elements we analyzed are known to be composed of clusters of low-level entities. In addition, we found here that the clusters generated by GenomeCluster can be in turn clustered into high-level super-clusters. The observation of 'clusters-within-clusters' parallels the 'domains within domains' phenomenon previously detected through global statistical methods in eukaryotic sequences, and reveals a complex human genome landscape dominated by hierarchical clustering.

“Targeting” renal cell carcinoma patients with “targeted” agents: Are we there yet?

The rapid approval of several novel agents, targeting the vascular endothelial growth factor or mammalian target of rapamycin pathways (sunitinib, pazopanib, sorafenib, axitinib, bevacizumab, everolimus, temsirolimus) has given to metastatic renal cell carcinoma (mRCC) patients and their treating physicians many new and effective therapeutic options. The treatment paradigm for these patients is rapidly evolving, with future studies needed to define the optimal sequencing of these new agents. Despite progresses, no validated biomarkers able to predict clinical outcome or useful to guide patient selection for treatment are currently available. Recent studies have suggested that some biomarkers, including cytokines, circulating proangiogenic factors, markers of hypoxia or targets of signaling pathways are potentially promising prognostic or predictive factors in mRCC. We present an overview of the most recent developments in identifying biomarkers for targeted therapies in advanced RCC.

GRK5 intronic (CA)n polymorphisms associated with type 2 diabetes in Chinese Hainan Island

A genome-wide association study had showed G-protein-coupled receptor kinase 5 (GRK5) rs10886471 was related to the risk of type 2 diabetes mellitus (T2DM) through upregulated GRK5 mRNA expression. Rs10886471 is located in the intron region of GRK5. However, the mechanism by which intronic SNP affects gene expression remains unclear, whether the effect on gene expression depends on the intronic short tandem repeat (STR) (CA)n splicing regulator or not. Here we investigated the STR (CA)n polymorphism in rs10886471 and further discussed its role in the T2DM risk of Chinese Hainan Island individuals. A total of 1164 subjects were recruited and classified into a normal fasting glucose (NFG) group, an impaired fasting glucose (IFG) group, an impaired glucose tolerance (IGT) group, and a T2DM group. STR (CA)n polymorphisms were detected through polymerase chain reaction and sequencing. Five intronic (CA)n alleles, (CA)15 to (CA)19, were identified in GRK5 rs10886471. Only the (CA)16 allele was significantly associated with increased prediabetes and T2DM risk [odds ratio (OR)>1, P<0.05]. Conversely, multiple alleles without any (CA)16 protected against prediabetes and T2DM (0<OR<1, P<0.05). In summary, rs10886471 acts as both an SNP and an STR. The rs10886471 intronic SNP causes GRK5 overexpression the subsequent risk of T2DM may be due to the rs10886471 intronic STR (CA)n splicing enhancer. Further studies should focus on verifying these finding using a large sample size and analyzing the splicing mechanism of intronic (CA)n in rs10886471.

Increased polymorphism near low-complexity sequences across the genomes of Plasmodium falciparum isolates

Low-complexity regions (LCRs) within proteins sequences are often considered to evolve neutrally even though recent studies reported evidence for selection acting on some of them. Because of their widespread distribution among eukaryotes genomes and the potential deleterious effect of expansion/contraction of some of them in humans, low-complexity sequences are of major interest and numerous studies have attempted to describe their dynamic between genomes as well as the factors correlated to their variation and to assess their selective value. However, due to the scarcity of individual genomes within a species, most of the analyses so far have been performed at the species level with the implicit assumption that the variation both in composition and size within species is too small relative to the between-species divergence to affect the conclusions of the analysis. Here we used the available genomes of 14 Plasmodium falciparum isolates to assess the relationship between low-complexity sequence variation and factors such as nucleotide polymorphism across strains, sequence composition, and protein expression. We report that more than half of the 7,711 low-complexity sequences found within aligned coding sequences are variable in size among strains. Across strains, we observed an increasing density of polymorphic sites toward the LCR boundaries. This observation strongly suggests the joint effects of lowered selective constraints on low-complexity sequences and a mutagenic effect of these simple sequences.

Bases adjacent to mononucleotide repeats show an increased single nucleotide polymorphism frequency in the human genome

Mononucleotide repeats (MNRs) are abundant in eukaryotic genomes and exhibit a high degree of length variability due to insertion and deletion events. However, the relationship between these repeats and mutation rates in surrounding sequences has not been systematically investigated. We have analyzed the frequency of single nucleotide polymorphisms (SNPs) at positions close to and within MNRs in the human genome. Overall, we find a 2- to 4-fold increase in the SNP frequency at positions immediately adjacent to the boundaries of MNRs, relative to that at more distant bases. This relationship exhibits a strong asymmetry between 3' and 5' ends of repeat tracts and is dependent upon the repeat motif, length and orientation of surrounding repeats. Our analysis suggests that the incorporation or exclusion of bases adjacent to the boundary of the repeat through substitutions, in which these nucleotides mutate towards or away from the base present within the repeat, respectively, may be another mechanism by which MNRs expand and contract in the human genome.