Comparison of classification methods for detecting associations between SNPs and chick mortality

Multi-category classification methods were used to detect SNP-mortality associations in broilers. The objective was to select a subset of whole genome SNPs associated with chick mortality. This was done by categorizing mortality rates and using a filter-wrapper feature selection procedure in each of the classification methods evaluated. Different numbers of categories (2, 3, 4, 5 and 10) and three classification algorithms (naïve Bayes classifiers, Bayesian networks and neural networks) were compared, using early and late chick mortality rates in low and high hygiene environments. Evaluation of SNPs selected by each classification method was done by predicted residual sum of squares and a significance test-related metric. A naïve Bayes classifier, coupled with discretization into two or three categories generated the SNP subset with greatest predictive ability. Further, an alternative categorization scheme, which used only two extreme portions of the empirical distribution of mortality rates, was considered. This scheme selected SNPs with greater predictive ability than those chosen by the methods described previously. Use of extreme samples seems to enhance the ability of feature selection procedures to select influential SNPs in genetic association studies.     

Sequencing the genome of the Atlantic salmon (<Emphasis Type="Italic">Salmo salar</Emphasis>)

The International Collaboration to Sequence the Atlantic Salmon Genome (ICSASG) will produce a genome sequence that identifies and physically maps all genes in the Atlantic salmon genome and acts as a reference sequence for other salmonids.     

Evolution of an adenocarcinoma in response to selection by targeted kinase inhibitors

Background

Adenocarcinomas of the tongue are rare and represent the minority (20 to 25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment.

Results

In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. There were 1,078 genes that exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations, administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumors and 9 new somatic protein coding mutations. The observed mutations and amplifications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways.

Conclusions

We conclude that complete genomic characterization of a rare tumor has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.     

The evolutionary analysis of the Tnt1 retrotransposon in Nicotiana species reveals the high variability of its regulatory sequences

We studied the evolution of the tobacco Tnt1 retrotransposon by analyzing Tnt1 partial sequences containing both coding domains and U3 regulatory sequences obtained from a number of Nicotiana species. We detected three different subfamilies of Tnt1 elements, Tnt1A, Tnt1B, and Tnt1C, that differ completely in their U3 regions but share conserved flanking coding and LTR regions. U3 divergence between the three subfamilies is found in the region that contains the regulatory sequences that control the expression of the well-characterized Tnt1-94 element. This suggests that expression of the three Tnt1 subfamilies might be differently regulated. The three Tnt1 subfamilies were present in the Nicotiana genome at the time of species divergence, but have evolved independently since then in the different genomes. Each Tnt1 subfamily seems to have conserved its ability to transpose in a limited and different number of Nicotiana species. Our results illustrate the high variability of Tnt1 regulatory sequences. We propose that this high sequence variability could allow these elements to evolve regulatory mechanisms in order to optimize their coexistence with their host genome.      

Cross-adaptation and molecular modeling study of receptor mechanisms common to four taste stimuli in humans

Psychophysical cross-adaptation experiments were performed with two carbohydrates, sucrose (SUC) and fructose (FRU), and two sweeteners, acesulfame-K (MOD) and dulcin (DUL). Seven subjects were asked to match concentrations that elicited the same intensity as a sucrose reference (30 g/l). Cross-adaptation levels were calculated as the ratio of isointense concentrations measured for a given stimulus before and under adaptation. On average, cross-adaptation between SUC and FRU is low and apparently reciprocal. By contrast, cross-adaptation between SUC and MOD is clearly non-reciprocal: SUC adapts MOD significantly (24%, P < 0.005), but MOD fails to adapt SUC (2%, P < 0.79). Significant and reciprocal cross-enhancement is observed between DUL and MOD (approximately -20%, P < 0.03), and also between SUC and DUL (approximately -15%, P < 0.08). In parallel, molecular modeling of the four tastants was performed in order to look for the 12 common binding motifs that were isolated on 14 other tastants in a previous study. SUC and FRU each display 10 out of the 12 binding motifs, whereas DUL and MOD only display four and five distinct motifs respectively and do not have any motif in common. Experimental cross-adaptation levels seem to correlate well with the number of motifs that molecules have in common. FRU and SUC share a majority of binding motifs and correlatively show mutual cross-adaptation. Four motifs of MOD are found among the 10 motifs of SUC, which may explain why SUC cross-adapts MOD but not vice versa. By contrast, DUL and MOD do not share any motif and do not cross- adapt. The various molecular mechanisms that may be responsible for cross-adaptation and/or cross-enhancement are discussed in light of our results.      

Opposing effects of prostaglandin E(2)and F(2 alpha) on rat liver-associated natural killer cell activity in vitro

Strain differences in cancer incidence are proposed to be due partly to differences in immune function. As potential cancer-associated immunological regulators, the concentrations of hepatic prostaglandins E(2)(PGE(2 alpha)and F(2 alpha)(PGF(2 alpha)) were compared in 9-week-old male and female F344/N and Sprague-Dawley (SD) rats. There were no strain or gender differences in the concentrations of hepatic PGE(2). No strain difference was found in the concentration of hepatic PGF(2 alpha), but the hepatic PGF(2 alpha)concentration in female rats was two-fold that of the male rat (130 vs 60 ng/g). PGE(2)significantly inhibited hepatic natural-killer cell (NK) activity in vitro compared with untreated cells from both genders and strains (P<0.05), 25 ng PGE(2)/ml inhibited NK activity significantly more than did 10 ng PGE(2)/ml (P<0.05). In contrast, 50 ng PGF(2 alpha)/ml and 100 ng PGF(2 alpha)/ml significantly stimulated hepatic NK activity compared with untreated hepatic cells from both F344/N and SD rats. This study suggests that prostaglandins may have a negligible net effect on NK activity associated with rat liver, and may be unlikely to mediate cancer-related immune function.     

An approach to large scale identification of non-obvious structural similarities between proteins

Background

A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy.

Results

The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors.The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity.

Conclusion

Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence.

     

AFAP1 Is a Novel Downstream Mediator of TGF-β1 for CCN2 Induction in Osteoblasts

Background

CCN2 acts as an anabolic growth factor to regulate osteoblast differentiation and function. CCN2 is induced by TGF-β1 and acts as a mediator of TGF-β1 induced matrix production in osteoblasts and Src is required for CCN2 induction by TGF-β1; however, the molecular mechanisms that control CCN2 induction in osteoblasts are poorly understood. AFAP1 binds activated forms of Src and can direct the activation of Src in certain cell types, however a role for AFAP1 downstream of TGF-β1 or in osteoblats is undefined. In this study, we investigated the role of AFAP1 for CCN2 induction by TGF-β1 in primary osteoblasts.

Results

We demonstrated that AFAP1 expression in osteoblasts occurs in a biphasic pattern with maximal expression levels occurring during osteoblast proliferation (~day 3), reduced expression during matrix production/maturation (~day 14–21), an a further increase in expression during mineralization (~day 21). AFAP1 expression is induced by TGF-β1 treatment in osteoblasts during days 7, 14 and 21. In osteoblasts, AFAP1 binds to Src and is required for Src activation by TGF-β1 and CCN2 promoter activity and protein induction by TGF-β1 treatment was impaired using AFAP1 siRNA, indicating the requirement of AFAP1 for CCN2 induction by TGF-β1. We also demonstrated that TGF-β1 induction of extracellular matrix protein collagen XIIa occurs in an AFAP1 dependent fashion.

Conclusions

This study demonstrates that AFAP1 is an essential downstream signaling component of TGF-β1 for Src activation, CCN2 induction and collagen XIIa in osteoblasts.