Linked region detection using high-density SNP genotype data via the minimum recombinant model of pedigree haplotype inference

<p>Abstract</p> <p>Background</p> <p>With the rapid development of high-throughput genotyping technologies, efficient methods for identifying linked regions using high-density SNP genotype data have become more and more important. Recently, a deterministic method that works very well on SNP genotyping data has been developed (Lin et al. Bioinformatics 2008, 24(1): 86–93). However, that program can only work on a limited number of family structures. In particular, the results (if any) will be poor when the genotype data for the whole chromosome of one of the parents in a nuclear family is missing.</p> <p>Results</p> <p>We have developed a software package (LIden) for identifying linked regions using high-density SNP genotype data. We focus on handling the case where the genotype data for the whole chromosome of one of the parents in a nuclear family is missing. We use the minimum recombinant model for haplotype inference in pedigrees. Several local optimization algorithms are used to infer the haplotype of each individual and determine the linked regions based on the inferred haplotype data. We have developed a more flexible method to combine nuclear families to further refine (reduce the length of) the linked regions.</p> <p>Conclusion</p> <p>Our new package (LIden) is efficient software for linked region detection using high-density SNP genotype data. LIden can handle some important cases where the existing programs do not work well. In particular, the new package can handle many cases where the genotype data of one of the two parents is missing for the entire chromosome. The running time of the program is <it>O</it>(<it>mn</it>), where <it>m </it>is the number of members in the family and <it>n </it>is the number of SNP sites in the chromosome. LIden is specifically suitable for handling big sized families. This research also demonstrates another practical use of the minimum recombinant model for haplotype inference in pedigrees.</p> <p>The software package can be downloaded at <url>http://www.cs.cityu.edu.hk/~lwang/software/Link</url>.</p

Quality at the Tail

Practical applications employing deep learning must guarantee inference quality. However, we found that the inference quality of state-of-the-art and state-of-the-practice in practical applications has a long tail distribution. In the real world, many tasks have strict requirements for the quality of deep learning inference, such as safety-critical and mission-critical tasks. The fluctuation of inference quality seriously affects its practical applications, and the quality at the tail may lead to severe consequences. State-of-the-art and state-of-the-practice with outstanding inference quality designed and trained under loose constraints still have poor inference quality under constraints with practical application significance. On the one hand, the neural network models must be deployed on complex systems with limited resources. On the other hand, safety-critical and mission-critical tasks need to meet more metric constraints while ensuring high inference quality. We coin a new term, ``tail quality,'' to characterize this essential requirement and challenge. We also propose a new metric, ``X-Critical-Quality,'' to measure the inference quality under certain constraints. This article reveals factors contributing to the failure of using state-of-the-art and state-of-the-practice algorithms and systems in real scenarios. Therefore, we call for establishing innovative methodologies and tools to tackle this enormous challenge.Comment: 9 pages, 4 figure

Cerebroprotective Effects of Dimeric Copper(II) Bis(o-acetoxybenzoate) on Ischemia-reperfusion Injury in Gerbils

The cerebroprotective effects of copper aspirinate [dimeric copper(II) bis(o-acetoxybenzoate)] were investigated in gerbils subjected to 10-min global cerebral ischemia followed b 60-min reperfusion. The results showed that intragastric copper aspirinate (7.5, 15.0 and 30.0 mg Kg−1) markedly promoted the recovery of the electroencephalogram amplitude, attenuated the increase of lipid peroxide content and the decrease of superoxide dismutase activity in the cortex during ischemia-reperfusion injury. It suggested that copper aspirinate possesses potential neuroprotective properties, the mechanism of which might be related to an increase of the activity of endogenous superoxide dismutase

Promoter-sharing by different genes in human genome – CPNE1 and RBM12 gene pair as an example

<p>Abstract</p> <p>Background</p> <p>Regulation of gene expression plays important role in cellular functions. Co-regulation of different genes may indicate functional connection or even physical interaction between gene products. Thus analysis on genomic structures that may affect gene expression regulation could shed light on the functions of genes.</p> <p>Results</p> <p>In a whole genome analysis of alternative splicing events, we found that two distinct genes, <it>copine I </it>(<it>CPNE1</it>) and <it>RNA binding motif protein 12 </it>(<it>RBM12</it>), share the most 5' exons and therefore the promoter region in human. Further analysis identified many gene pairs in human genome that share the same promoters and 5' exons but have totally different coding sequences. Analysis of genomic and expressed sequences, either cDNAs or expressed sequence tags (ESTs) for <it>CPNE1 </it>and <it>RBM12</it>, confirmed the conservation of this phenomenon during evolutionary courses. The co-expression of the two genes initiated from the same promoter is confirmed by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) in different tissues in both human and mouse. High degrees of sequence conservation among multiple species in the 5'UTR region common to <it>CPNE1 </it>and <it>RBM12 </it>were also identified.</p> <p>Conclusion</p> <p>Promoter and 5'UTR sharing between <it>CPNE1 </it>and <it>RBM12 </it>is observed in human, mouse and zebrafish. Conservation of this genomic structure in evolutionary courses indicates potential functional interaction between the two genes. More than 20 other gene pairs in human genome were found to have the similar genomic structure in a genome-wide analysis, and it may represent a unique pattern of genomic arrangement that may affect expression regulation of the corresponding genes.</p

BigDataBench: a Big Data Benchmark Suite from Internet Services

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purposes mentioned above. This paper presents our joint research efforts on this issue with several industrial partners. Our big data benchmark suite BigDataBench not only covers broad application scenarios, but also includes diverse and representative data sets. BigDataBench is publicly available from http://prof.ict.ac.cn/BigDataBench . Also, we comprehensively characterize 19 big data workloads included in BigDataBench with varying data inputs. On a typical state-of-practice processor, Intel Xeon E5645, we have the following observations: First, in comparison with the traditional benchmarks: including PARSEC, HPCC, and SPECCPU, big data applications have very low operation intensity; Second, the volume of data input has non-negligible impact on micro-architecture characteristics, which may impose challenges for simulation-based big data architecture research; Last but not least, corroborating the observations in CloudSuite and DCBench (which use smaller data inputs), we find that the numbers of L1 instruction cache misses per 1000 instructions of the big data applications are higher than in the traditional benchmarks; also, we find that L3 caches are effective for the big data applications, corroborating the observation in DCBench.Comment: 12 pages, 6 figures, The 20th IEEE International Symposium On High Performance Computer Architecture (HPCA-2014), February 15-19, 2014, Orlando, Florida, US

Suppression of methane uptake by precipitation pulses and long-term nitrogen addition in a semi-arid meadow steppe in northeast China

In the context of global change, the frequency of precipitation pulses is expected to decrease while nitrogen (N) addition is expected to increase, which will have a crucial effect on soil C cycling processes as well as methane (CH4) fluxes. The interactive effects of precipitation pulses and N addition on ecosystem CH4 fluxes, however, remain largely unknown in grassland. In this study, a series of precipitation pulses (0, 5, 10, 20, and 50 mm) and long-term N addition (0 and 10 g N m-2 yr-1, 10 years) was simulated to investigate their effects on CH4 fluxes in a semi-arid grassland. The results showed that large precipitation pulses (10 mm, 20 mm, and 50 mm) had a negative pulsing effect on CH4 fluxes and relatively decreased the peak CH4 fluxes by 203-362% compared with 0 mm precipitation pulse. The large precipitation pulses significantly inhibited CH4 absorption and decreased the cumulative CH4 fluxes by 68-88%, but small precipitation pulses (5 mm) did not significantly alter it. For the first time, we found that precipitation pulse size increased cumulative CH4 fluxes quadratically in both control and N addition treatments. The increased soil moisture caused by precipitation pulses inhibited CH4 absorption by suppressing CH4 uptake and promoting CH4 release. Nitrogen addition significantly decreased the absorption of CH4 by increasing NH4+-N content and NO3–-N content and increased the production of CH4 by increasing aboveground biomass, ultimately suppressing CH4 uptake. Surprisingly, precipitation pulses and N addition did not interact to affect CH4 uptake because precipitation pulses and N addition had an offset effect on pH and affected CH4 fluxes through different pathways. In summary, precipitation pulses and N addition were able to suppress the absorption of CH4 from the atmosphere by soil, reducing the CH4 sink capacity of grassland ecosystems

EFIN: predicting the functional impact of nonsynonymous single nucleotide polymorphisms in human genome

Background Predicting the functional impact of amino acid substitutions (AAS) caused by nonsynonymous single nucleotide polymorphisms (nsSNPs) is becoming increasingly important as more and more novel variants are being discovered. Bioinformatics analysis is essential to predict potentially causal or contributing AAS to human diseases for further analysis, as for each genome, thousands of rare or private AAS exist and only a very small number of which are related to an underlying disease. Existing algorithms in this field still have high false prediction rate and novel development is needed to take full advantage of vast amount of genomic data. Results Here we report a novel algorithm that features two innovative changes: 1. making better use of sequence conservation information by grouping the homologous protein sequences into six blocks according to evolutionary distances to human and evaluating sequence conservation in each block independently, and 2. including as many such homologous sequences as possible in analyses. Random forests are used to evaluate sequence conservation in each block and to predict potential impact of an AAS on protein function. Testing of this algorithm on a comprehensive dataset showed significant improvement on prediction accuracy upon currently widely-used programs. The algorithm and a web-based application tool implementing it, EFIN (Evaluation of Functional Impact of Nonsynonymous SNPs) were made freely available (http://paed.hku.hk/efin/) to the public. Conclusions Grouping homologous sequences into different blocks according to evolutionary distance of the species to human and evaluating sequence conservation in each group independently significantly improved prediction accuracy. This approach may help us better understand the roles of genetic variants in human disease and health.published_or_final_versio