Solar influenced late Holocene temperature changes on the northern Tibetan Plateau

Considerable efforts have been made to extend temperature records beyond the instrumental period through proxy reconstructions, in order to further understand the mechanisms of past climate variability. Yet, the global coverage of existing temperature records is still limited, especially for some key regions like the Tibetan Plateau and for earlier times including the Medieval Warm Period (MWP). Here we present decadally-resolved, alkenone-based, temperature records from two lakes on the northern Tibetan Plateau. Characterized by marked temperature variability, our records provide evidence that temperatures during the MWP were slightly higher than the modern period in this region. Further, our temperature reconstructions, within age uncertainty, can be well correlated with solar irradiance changes, suggesting a possible link between solar forcing and natural climate variability, at least on the northern Tibetan Plateau. © 2013 The Author(s).published_or_final_versio

On the flexibility of the design of Multiple Try Metropolis schemes

The Multiple Try Metropolis (MTM) method is a generalization of the classical Metropolis-Hastings algorithm in which the next state of the chain is chosen among a set of samples, according to normalized weights. In the literature, several extensions have been proposed. In this work, we show and remark upon the flexibility of the design of MTM-type methods, fulfilling the detailed balance condition. We discuss several possibilities and show different numerical results

Radial Growth of Qilian Juniper on the Northeast Tibetan Plateau and Potential Climate Associations

There is controversy regarding the limiting climatic factor for tree radial growth at the alpine treeline on the northeastern Tibetan Plateau. In this study, we collected 594 increment cores from 331 trees, grouped within four altitude belts spanning the range 3550 to 4020 m.a.s.l. on a single hillside. We have developed four equivalent ring-width chronologies and shown that there are no significant differences in their growth-climate responses during 1956 to 2011 or in their longer-term growth patterns during the period AD 1110–2011. The main climate influence on radial growth is shown to be precipitation variability. Missing ring analysis shows that tree radial growth at the uppermost treeline location is more sensitive to climate variation than that at other elevations, and poor tree radial growth is particularly linked to the occurrence of serious drought events. Hence water limitation, rather than temperature stress, plays the pivotal role in controlling the radial growth of Sabina przewalskii Kom. at the treeline in this region. This finding contradicts any generalisation that tree-ring chronologies from high-elevation treeline environments are mostly indicators of temperature changes

Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood

The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain (“fuzzy”) genotypes, like those resulting from AFLP scores, can be handled by adding an extra layer to the model. We describe the model and the estimation algorithm. We apply it to a data set of accurate human single nucleotide polymorphism (SNP) and to a data set of fuzzy tomato AFLP scores

Haplotype inference in crossbred populations without pedigree information

<p>Abstract</p> <p>Background</p> <p>Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called <it>crossbreeding </it>and <it>hybridization </it>in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.</p> <p>Results</p> <p>We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.</p> <p>Conclusion</p> <p>Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.</p

Prevalence of genetic polymorphisms in the promoter region of the alpha-1 antitrypsin (SERPINA1) gene in chronic liver disease: a case control study

Contains fulltext : 89639.pdf (publisher's version ) (Open Access)BACKGROUND: Alpha-1 antitrypsin (A1AT) deficiency, caused by the Z allele (p.E342K) and S allele (p.E264V) in the SERPINA1 gene, can induce liver and pulmonary disease. Different mechanisms appear to be responsible for the pathogenesis of these divergent disease expressions. The c.-1973T >C polymorphism located in the SERPINA1 promoter region is found more frequent in A1AT deficiency patients with liver disease compared to patients with pulmonary disease, but data are lacking regarding contribution to the development of liver diseases caused by other aetiologies. AIM: To study the prevalence of c.-1973T >C, Z allele and S allele in a cohort of patients with liver disease of various aetiologies compared with healthy controls and to evaluate its effect on disease progression. METHODS: A total of 297 patients with liver disease from various aetiologies and 297 age and gender matched healthy controls were included. The c.-1973T >C polymorphism and Z and S alleles of the SERPINA1 gene were analyzed by real-time PCR. RESULTS: c.-1973T >C was similarly distributed between patients with liver disease of various origins and healthy controls. Furthermore, the distribution of c.-1973T >C was independent from aetiology subgroup. In patients with liver disease mean ages at of onset of liver disease were 44.4, 42.3 and 40.7 years for the c.-1973 T/T, T/C and C/C genotype respectively (NS). S allele heterozygosity was increased in patients with drug induced liver injury (DILI), (OR 4.3; 95%CI 1.1-17.2). CONCLUSION: In our study, c.-1973T >C polymorphism was not a risk factor for liver disease of various aetiologies. In addition, S allele heterozygosity might contribute to the development of DILI

Genetic variations in APPL2 are associated with overweight and obesity in a Chinese population with normal glucose tolerance

<p>Abstract</p> <p>Background</p> <p>APPL1 and APPL2 are two adaptor proteins, which can mediate adiponectin signaling via binding to N terminus of adiponectin receptors in muscle cells. Genes encoding adiponectin and adiponectin receptors contribute to insulin resistance and the risk of obesity, and genetic variants of <it>APPL1 </it>are associated with body fat distribution. However, the association between genetic variations of <it>APPL2 </it>and metabolic traits remains unknown. In the current study, we aimed to test the impacts of <it>APPL2 </it>genetic variants on obesity in a Chinese population with normal glucose tolerance.</p> <p>Methods</p> <p>We genotyped six single nucleotide polymorphisms (SNPs) in <it>APPL2 </it>in 1,808 non-diabetic subjects. Overweight and obesity were defined by body mass index (BMI). Obesity-related anthropometric parameters were measured, including height, weight, waist circumference, hip circumference. BMI and waist-hip ratio (WHR) were calculated.</p> <p>Results</p> <p>We found significant evidence of association with overweight/obesity for rs2272495 and rs1107756. rs2272495 C allele and rs1107756 T allele both conferred a higher risk of being overweight and obese (OR 1.218, 95% CI 1.047-1.416, <it>p </it>= 0.011 for rs2272495; OR 1.166, 95% CI 1.014-1.341, <it>p </it>= 0.031 for rs1107756). After adjusting multiple comparisons, only the effect of rs2272495 on overweight/obesity remained to be significant (empirical <it>p </it>= 0.043). Moreover, we investigated the effects of these SNPs on obesity-related quantitative traits in all participants. rs2272495 was associated with BMI (<it>p </it>= 0.015), waist circumference (<it>p </it>= 0.006), hip circumference (<it>p </it>= 0.025) as well as WHR (<it>p </it>= 0.047) under a recessive model. Similar associations were found for rs1107756 except for WHR.</p> <p>Conclusion</p> <p>This study suggests that genetic variations in <it>APPL2 </it>are associated with overweight and obesity in Chinese population with normal glucose tolerance.</p

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

Lack of association between genetic polymorphisms within DUSP12 - ATF6 locus and glucose metabolism related traits in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Genome-wide linkage studies in multiple ethnic populations found chromosome 1q21-q25 was the strongest and most replicable linkage signal in the human chromosome. Studies in Pima Indian, Caucasians and African Americans identified several SNPs in <it>DUSP12 </it>and <it>ATF6</it>, located in chromosome 1q21-q23, were associated with type 2 diabetes.</p> <p>Methods</p> <p>We selected 19 single nucleotide polymorphisms (SNPs) that could tag 98% of the SNPs with minor allele frequencies over 0.1 within <it>DUSP12-ATF6 </it>region. These SNPs were genotyped in a total of 3,700 Chinese Han subjects comprising 1,892 type 2 diabetes patients and 1,808 controls with normal glucose regulation.</p> <p>Results</p> <p>None of the SNPs and haplotypes showed significant association to type 2 diabetes in our samples. No association between the SNPs and quantitative traits was observed either.</p> <p>Conclusions</p> <p>Our data suggests common SNPs within <it>DUSP12</it>-<it>ATF6 </it>locus may not play a major role in glucose metabolism in the Chinese.</p

Genome structure of cotton revealed by a genome-wide SSR genetic map constructed from a BC1 population between gossypium hirsutum and G. barbadense

<p>Abstract</p> <p>Background</p> <p>Cotton, with a large genome, is an important crop throughout the world. A high-density genetic linkage map is the prerequisite for cotton genetics and breeding. A genetic map based on simple polymerase chain reaction markers will be efficient for marker-assisted breeding in cotton, and markers from transcribed sequences have more chance to target genes related to traits. To construct a genome-wide, functional marker-based genetic linkage map in cotton, we isolated and mapped expressed sequence tag-simple sequence repeats (EST-SSRs) from cotton ESTs derived from the A₁, D₅, (AD)₁, and (AD)₂genome.</p> <p>Results</p> <p>A total of 3177 new EST-SSRs developed in our laboratory and other newly released SSRs were used to enrich our interspecific BC₁genetic linkage map. A total of 547 loci and 911 loci were obtained from our EST-SSRs and the newly released SSRs, respectively. The 1458 loci together with our previously published data were used to construct an updated genetic linkage map. The final map included 2316 loci on the 26 cotton chromosomes, 4418.9 cM in total length and 1.91 cM in average distance between adjacent markers. To our knowledge, this map is one of the three most dense linkage maps in cotton. Twenty-one segregation distortion regions (SDRs) were found in this map; three segregation distorted chromosomes, Chr02, Chr16, and Chr18, were identified with 99.9% of distorted markers segregating toward the heterozygous allele. Functional analysis of SSR sequences showed that 1633 loci of this map (70.6%) were transcribed loci and 1332 loci (57.5%) were translated loci.</p> <p>Conclusions</p> <p>This map lays groundwork for further genetic analyses of important quantitative traits, marker-assisted selection, and genome organization architecture in cotton as well as for comparative genomics between cotton and other species. The segregation distorted chromosomes can be a guide to identify segregation distortion loci in cotton. The annotation of SSR sequences identified frequent and rare gene ontology items on each chromosome, which is helpful to discover functions of cotton chromosomes.</p