Association Analysis Of Data Research Articles

Proteomics and Its Combined Analysis with Transcriptomics: Liver Fat-Lowering Effect of Taurine in High-Fat Fed Grouper (Epinephelus coioides).

In order to understand the intervention effect of taurine on liver fat deposition induced by high fat intake in the orange-spotted grouper (Epinephelus coioides), we performed proteomic analysis and association analysis with previously obtained transcriptomic data. Three isoproteic (47% crude protein) diets were designed to contain two levels of fat and were named as the 10% fat diet (10F), 15% fat diet (15F), and 15% fat with 1% taurine (15FT). The 10F diet was used as the control diet. After 8 weeks of feeding, the 15F diet exhibited comparable weight gain, feed conversion ratio, and hepatosomatic index as the 10F diet, but the former increased liver fat content vs. the latter. Feeding with the 15FT diet resulted in an improvement in weight gain and a reduction in feed conversion ratio, hepatosomatic index, and liver fat content compared with feeding the 15F diet. When comparing liver proteomic data between the 15F and 15FT groups, a total of 133 differentially expressed proteins (DEPs) were identified, of which 51 were upregulated DEPs and 82 were downregulated DEPs. Among these DEPs, cholesterol 27-hydroxylase, phosphatidate phosphatase LPIN, phosphatidylinositol phospholipase C, and 6-phosphofructo-2-kinase were further screened out and were involved in primary bile acid biosynthesis, glycerolipid metabolism, the phosphatidylinositol signaling system, and the AMPK signaling pathway as key DEPs in terms of alleviating liver fat deposition of taurine in high-fat fed fish. With the association analysis of transcriptomic and proteomic data through KEGG, three differentially expressed genes (atp1a, arf1_2, and plcd) and four DEPs (CYP27α1, LPIN, PLCD, and PTK2B) were co-enriched into five pathways related to fat metabolism including primary bile acid synthesis, bile secretion, glycerolipid metabolism, phospholipid D signaling, or/and phosphatidylinositol signaling. The results showed that dietary taurine intervention could trigger activation of bile acid biosynthesis and inhibition of triglyceride biosynthesis, thereby mediating the liver fat-lowering effects in high-fat fed orange-spotted grouper. The present study contributes some novel insight into the liver fat-lowering effects of dietary taurine in high-fat fed groupers.

The Path of Meishan Cultural Renewal and Expansion Based on Data Association Rules

Abstract Metadata and data association rules are combined in this paper to create an aggregation framework for Meishan cultural digital resources. Meishan cultural digital resources are standardized through the use of metadata standards. The accuracy of metadata is evaluated in conjunction with trustworthiness. Metadata association rules are employed to evaluate the degree of association in Meishan cultural data. Enhance the efficiency of data association analysis by enhancing the Apriori algorithm. The algorithm is applied to the association analysis of Meishan culture data, and the degree of association between different digital resources and Meishan culture is determined by combining the data. The results show that the highest correlation with Meishan culture is the digital resources of documentaries and skills, with a correlation degree of 0.9, and the lowest correlation is the book resources, with a correlation degree of 0.65. The number of nodes in the period of 1-6 and the time consumed by each dataset is in the interval of (7000,1100).

Revealing a causal relationship between gut microbiota and lung cancer: a Mendelian randomization study.

The gut microbiota has been found to be associated with the risk of lung cancer. However, its causal relationship with various types of lung cancer remains unclear. We conducted a Mendelian randomization (MR) study using the largest genome-wide association analysis of gut microbiota data to date from the MiBioGen consortium, with pooled statistics for various types of lung cancer from the Transdisciplinary Research in Cancer of the Lung, the International Lung Cancer Consortium, and FinnGen Consortium R7 release data. Inverse variance weighted, weighted model, MR-Egger regression, and weighted median were adapted to assess the causal relationship between gut microbiota and various types of lung cancer. Sensitivity analysis was used to test for the presence of pleiotropy and heterogeneity in instrumental variables. A reverse MR analysis was performed on these bacteria to determine their potential role in causing lung cancer. A reverse MR analysis was performed on these bacteria to determine their potential role in causing lung cancer. Multivariable Mendelian randomization (MVMR) was conducted to assess the direct causal impact of gut microbiota on the risk of various types of lung cancer. Using IVW as the primary analytical method, we identified a total of 40 groups of gut microbiota with potential causal associations with various subtypes of lung cancer, of which 10 were associated with lung cancer, 10 with lung adenocarcinoma, 9 with squamous cell lung cancer, and 11 groups of bacteria associated with small cell lung cancer. After performing FDR correction, we further found that there was still a significant causal relationship between Peptococcaceae and lung adenocarcinoma. Sensitivity analyses demonstrated the robustness of these results, with no heterogeneity or pleiotropy found. Our results confirm a causal relationship between specific gut microbiota and lung cancer, providing new insights into the role of gut microbiota in mediating the development of lung cancer.

Analysis of the main antioxidant enzymes in the roots of Tamarix ramosissima under NaCl stress by applying exogenous potassium (K+).

Salinization affects more than 25% of the world's arable land, and Tamarix ramosissima Ledeb (T. ramosissima), the representative of Tamarix plants, is widely grown in salinized soil. In contrast, less is known about the mechanism of potassium's antioxidative enzyme activity in preventing NaCl stress damage to plants. This study examined changes in root growth for T. ramosissima at 0h, 48h, and 168h, performed antioxidant enzyme activity assays, transcriptome sequencing, and non-targeted metabolite analysis to understand changes in their roots as well as changes in the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). Quantitative real-time PCR (qRT-PCR) was used to identify differentially expressed genes (DEGs) and differential metabolites associated with antioxidant enzyme activities. As the time increased, the results showed that compared with the 200 Mm NaCl group, the root growth of the 200 mM NaCl + 10 mM KCl group increased, the activities of SOD, POD and CAT increased the most, but the contents of hydrogen peroxide (H2O2) and Malondialdehyde (MDA) increased less. Meanwhile, 58 DEGs related to SOD, POD and CAT activities were changed during the application of exogenous K+ for 48h and 168h in T. ramosissima. Based on association analysis of transcriptomic and metabolomic data, we found coniferyl alcohol, which can act as a substrate to label catalytic POD. It is worth noting that Unigene0013825 and Unigene0014843, as POD-related genes, have positively regulated the downstream of coniferyl alcohol, and they have a significant correlation with coniferyl alcohol. In summary, 48h and 168h of exogenous K+ applied to the roots of T. ramosissima under NaCl stress can resist NaCl stress by scavenging the reactive oxygen species (ROS) generated by high salt stress by enhancing the mechanism of antioxidant enzyme activity, relieving NaCl toxicity and maintaining growth. This study provides genetic resources and a scientific theoretical basis for further breeding of salt-tolerant Tamarix plants and the molecular mechanism of K+ alleviating NaCl toxicity.

Genome-wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth-related traits in maize under plant growth-promoting bacteria inoculation.

Plant growth-promoting bacteria (PGPB) may be of use for increasing crop yield and plant resilience to biotic and abiotic stressors. Using hyperspectral reflectance data to assess growth-related traits may shed light on the underlying genetics as such data can help assess biochemical and physiological traits. This study aimed to integrate hyperspectral reflectance data with genome-wide association analyses to examine maize growth-related traits under PGPB inoculation. A total of 360 inbred maize lines with 13,826 single nucleotide polymorphisms (SNPs) were evaluated with and without PGPB inoculation; 150 hyperspectral wavelength reflectances at 386-1021 nm and 131 hyperspectral indices were used in the analysis. Plant height, stalk diameter, and shoot dry mass were measured manually. Overall, hyperspectral signatures produced similar or higher genomic heritability estimates than those of manually measured phenotypes, and they were genetically correlated with manually measured phenotypes. Furthermore, several hyperspectral reflectance values and spectral indices were identified by genome-wide association analysis as potential markers for growth-related traits under PGPB inoculation. Eight SNPs were detected, which were commonly associated with manually measured and hyperspectral phenotypes. Different genomic regions were found for plant growth and hyperspectral phenotypes between with and without PGPB inoculation. Moreover, the hyperspectral phenotypes were associated with genes previously reported as candidates for nitrogen uptake efficiency, tolerance to abiotic stressors, and kernel size. In addition, a Shiny web application was developed to explore multiphenotype genome-wide association results interactively. Taken together, our results demonstrate the usefulness of hyperspectral-based phenotyping for studying maize growth-related traits in response to PGPB inoculation.

Analysis of the Antioxidant Mechanism of Tamarix ramosissima Roots under NaCl Stress Based on Physiology, Transcriptomic and Metabolomic.

There is a serious problem with soil salinization that affects the growth and development of plants. Tamarix ramosissima Ledeb (T. ramosissima), as a halophyte, is widely used for afforestation in salinized soils. At present, there are few reports on the antioxidant mechanism of T. ramosissima under NaCl stress. In this study, we learned about the superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities, and hydrogen peroxide (H2O2) and malondialdehyde (MDA) content changes in T. ramosissima. We also mined the relevant metabolic pathways in the antioxidant mechanism, candidate key genes, and their related differential metabolites and verified them using quantitative real-time PCR (qRT-PCR). The results show that the SOD, POD, and CAT activities, and the H2O2 and MDA content reached the highest values in the roots of T. ramosissima. Simultaneously, 92 differentially expressed genes (DEGs) related to antioxidant enzyme activities changed during 48 and 168 h of NaCl stress, and these DEGs were mainly upregulated in 168 h. Based on the association analysis of transcriptomic and metabolomic data, we found Unigene0089358 and Unigene0007782 as genes related to key enzymes in the flavonoid biosynthesis pathway. They were located in the upstream positive regulation at 48 and 168 h under NaCl stress, and their respective related metabolites (phloretin and pinocembrin) were involved in resistance to NaCl stress, and they were significantly correlated with their respective metabolites. In conclusion, at 48 and 168 h under NaCl stress, the roots of T. ramosissima resist NaCl stress by enhancing enzymatic and nonenzymatic antioxidant mechanisms, scavenging ROS generated by high-salt stress, alleviating NaCl toxicity, and maintaining the growth of T. ramosissima. This study provides genetic resources and a scientific theoretical basis for further breeding of salt-tolerant Tamarix plants and the molecular mechanism of antioxidants to alleviate NaCl toxicity.

Analysis on the desert adaptability of indigenous sheep in the southern edge of Taklimakan Desert

The southern margin of the Taklimakan Desert is characterized by low rainfall, heavy sandstorms, sparse vegetation and harsh ecological environment. The indigenous sheep in this area are rich in resources, with the advantages of perennial estrus and good resistance to stress in most sheep. Exploring the molecular markers of livestock adaptability in this environment will provide the molecular basis for breeding research to cope with extreme future changes in the desert environment. In this study, we analyzed the population genetic structure and linkage imbalance of five sheep breeds with three different agricultural geographic characteristics using four complementary genomic selection signals: fixation index (FST), cross-population extended haplotype homozygosity (xp-EHH), Rsb (extended haplotype homozygosity between-populations) and iHS (integrated haplotype homozygosity score). We used Illumina Ovine SNP 50K Genotyping BeadChip Array, and gene annotation and enrichment analysis were performed on selected regions of the obtained genome. The ovary of Qira Black sheep (Follicular phase, Luteal phase, 30th day of pregnancy, 45th day of pregnancy) was collected, and the differentially expressed genes were screened by transcriptomic sequencing. Genome-wide selective sweep results and transcriptome data were combined for association analysis to obtain candidate genes associated with perennial estrus and stable reproduction. In order to verify the significance of the results, 15 resulting genes were randomly selected for fluorescence quantitative analysis. The results showed that Dolang sheep and Qira Black sheep evolved from Kazak sheep. Linkage disequilibrium analysis showed that the decay rate of sheep breeds in the Taklimakan Desert was higher than that in Yili grassland. The signals of FST, xp-EHH, Rsb and iHS detected 526, 332, 308 and 408 genes, respectively, under the threshold of 1% and 17 overlapping genes under the threshold of 5%. A total of 29 genes were detected in association analysis of whole-genome and transcriptome data. This study reveals the genetic mechanism of perennial estrus and environmental adaptability of indigenous sheep breeds in the Taklimakan Desert. It provides a theoretical basis for the conservation and exploitation of genetic resources of indigenous sheep breeds in extreme desert environment. This provides a new perspective for the quick adaptation of sheep and other mammals to extreme environments and future climate changes.

Study on the operating condition diagnosis method of hydropower station equipment based on fuzzy clustering analysis

The current operation status diagnosis of hydropower station equipment is mainly based on the independent analysis of the equipment, ignoring the correlation between the equipment, resulting in a large diagnostic error. In order to improve the above problems, a diagnosis method based on fuzzy clustering analysis is studied. This paper deals with association analysis and error data discrimination of equipment state data in operation collection of hydropower station, and selects operation data preliminarily. Using gravitational search algorithm for fuzzy c-means algorithm of the initial fuzzy membership degree matrix, improved fuzzy clustering algorithm is used to analyze the running status data clustering at a time. After using the encoder to extract data, secondary cluster, the abnormal data and equipment state match, the final diagnosis results are obtained. In the case verification experiment, the diagnostic accuracy rate of the method is as high as 94.83%, and the diagnostic efficiency is higher and the real-time performance is better.

Effects of Different Chemicals on Sexual Regulation in Persimmon (Diospyros kaki Thunb.) Flowers

Research on crop sexuality is important for establishing systems for germplasm innovation and cultivating improved varieties. In this study, androecious persimmon trees were treated with various concentrations of ethrel (100, 500, and 1,000 mg/L) and zeatin (1, 5, and 10 mg/L) to investigate the morphological, physiological, and molecular characteristics of persimmon. Ethrel at 1,000 mg/L and zeatin at 10 mg/L both significantly reduced the stamen length and pollen grain diameter in androecious trees. Ethrel treatment also led to reduced stamen development with degenerated cellular contents; zeatin treatment promoted the development of arrested pistils via maintaining relatively normal mitochondrial morphology. Both treatments altered carbohydrate, amino acid, and endogenous phytohormone contents, as well as genes associated with hormone production and floral organ development. Thereafter, we explored the combined effects of four chemicals, including ethrel and zeatin, as well as zebularine and 5-azacytidine, both of which are DNA methylation inhibitors, on androecious persimmon flower development. Morphological comparisons showed that stamen length, pollen viability, and pollen grain diameter were significantly inhibited after combined treatment. Large numbers of genes involving in carbohydrate metabolic, mitogen-activated protein kinase (MAPK) signaling, and ribosome pathways, and metabolites including uridine monophosphate (UMP) and cyclamic acid were identified in response to the treatment, indicating complex regulatory mechanisms. An association analysis of transcriptomic and metabolomic data indicated that ribosomal genes have distinct effects on UMP and cyclamic acid metabolites, explaining how male floral buds of androecious persimmon trees respond to these exogenous chemicals. These findings extend the knowledge concerning sexual differentiation in persimmon; they also provide a theoretical basis for molecular breeding, high-yield cultivation, and quality improvement in persimmon.

0035 Enrichment of RAI1 genetic aberrations associated with sleep disturbances in SMS, in Autism Spectrum Disorder

Abstract Introduction Autism Spectrum Disorder (ASD) comprises a complex of neurodevelopmental disorders primarily characterized by deficits in verbal communication, impaired social interactions and repetitive behaviors. The profound clinical heterogeneity of ASD poses challenges in diagnosis and treatment. Genetic studies have pointed to hundreds of presumptive causative or susceptibility variants in ASD, making it difficult to find common underlying pathogenic mechanisms and suggesting that multiple different genetic etiologies for ASDs influence a continuum of traits. Smith–Magenis syndrome is a rare genetic disorder that results from an interstitial deletion of 17p11.2 and, in rare cases, from a retinoic acid induced 1 (RAI1) gene variant. The prevalence is estimated to be 1/15,000–25,000. Haploinsufficiency of RAI1 is the primary cause of the neurobehavioral and metabolic phenotype in SMS. Individuals with SMS present with a distinct pattern of mild to moderate intellectual disability, delayed speech and language skills, distinctive craniofacial and skeletal abnormalities, behavioral disturbances, and, almost uniformly, significant sleep disturbances. Alterations in RAI1 copy number has been also linked to a number of neurodevelopmental disorders including ASD. Methods We conducted a large-scale association analysis of the ASD MSSNG whole genome sequencing data to elucidate the prevalence of RAI1 SNVs and CNVs in the ASD population. We accessed the MSSNG database hosting over 11,000 genomes (6080 probands) and queried both SNVs and CNVs. Results Specifically, we focused on the prevalence of the classic deletions, microdeletions of (exon 3) and of the causative variants. We report a single case of a classic deletion (17p11.2 critical region), and an additional 3 cases of microdeletions in exon 3. Moreover, we report 2 frameshift mutations and one splicing variant. Given that the frequency of SMS is 1 in 15000 in the general population, we observe a 2.5x enrichment of the major deletion (1 in 6080 samples) and a >5x enrichment of the frameshift variants (2 in 6080 samples). In a set of 6080 probands we also observed 54 unique missense variants in 84 individuals within exon 3 of RAI1 gene. Conclusion Both ASD patients and SMS patients suffer from sleep disturbances. In this population of individuals with ASD, we report here an enrichment of variants known to cause SMS. We estimate the enrichment to be at least 2.5-fold and potentially higher than 10-fold enrichment, considering the types of variants observed in the population. Currently, the prevailing theory is that there is an underlying circadian pathophysiology causing sleep disturbances in SMS associated with RAI1 haploinsufficiency, as these patients exhibit low overall melatonin concentrations and abnormal timing of peak plasma melatonin concentrations. This abnormal inverted circadian rhythm is estimated to occur in 95% of individuals with SMS. The sleep disturbance seen in individuals with SMS may be also the underlying mechanism in at least a subset of individuals with ASD, especially in those individuals with consequential variants in the RAI1 gene Further studies will help delineate the role of RAI1 variants in sleep physiology. Support (If Any)

Association analysis and functional annotation of imputed sequence data within genomic regions influencing resistance to gastro-intestinal parasites detected by an LDLA approach in a nucleus flock of Sarda dairy sheep

BackgroundGastroinestinal nematodes (GIN) are one of the major health problem in grazing sheep. Although genetic variability of the resistance to GIN has been documented, traditional selection is hampered by the difficulty of recording phenotypes, usually fecal egg count (FEC). To identify causative mutations or markers in linkage disequilibrium (LD) to be used for selection, the detection of quantitative trait loci (QTL) for FEC based on linkage disequilibrium-linkage analysis (LDLA) was performed on 4097 ewes (from 181 sires) all genotyped with the OvineSNP50 Beadchip. Identified QTL regions (QTLR) were imputed from whole-genome sequences of 56 target animals of the population. An association analysis and a functional annotation of imputed polymorphisms in the identified QTLR were performed to pinpoint functional variants with potential impact on candidate genes identified from ontological classification or differentially expressed in previous studies.ResultsAfter clustering close significant locations, ten QTLR were defined on nine Ovis aries chromosomes (OAR) by LDLA. The ratio between the ANOVA estimators of the QTL variance and the total phenotypic variance ranged from 0.0087 to 0.0176. QTL on OAR4, 12, 19, and 20 were the most significant. The combination of association analysis and functional annotation of sequence data did not highlight any putative causative mutations. None of the most significant SNPs showed a functional effect on genes’ transcript. However, in the most significant QTLR, we identified genes that contained polymorphisms with a high or moderate impact, were differentially expressed in previous studies, contributed to enrich the most represented GO process (regulation of immune system process, defense response). Among these, the most likely candidate genes were: TNFRSF1B and SELE on OAR12, IL5RA on OAR19, IL17A, IL17F, TRIM26, TRIM38, TNFRSF21, LOC101118999, VEGFA, and TNF on OAR20.ConclusionsThis study performed on a large experimental population provides a list of candidate genes and polymorphisms which could be used in further validation studies. The expected advancements in the quality of the annotation of the ovine genome and the use of experimental designs based on sequence data and phenotypes from multiple breeds that show different LD extents and gametic phases may help to identify causative mutations.

Serum proteomics screening intercellular adhesion molecule-2 improves intermediate-risk stratification in acute myeloid leukemia.

The clinical risk classification of acute myelocytic leukemia (AML) is largely based on cytogenetic and molecular genetic detection. However, the optimal treatment for intermediate-risk AML patients remains uncertain. Further refinement and improvement of prognostic stratification are therefore necessary. The aim of this study was to identify serum protein biomarkers to refine risk stratification in AML patients. This study is a retrospective study. Label-free proteomics was used to identify the differential abundance of serum proteins in AML patients. Transcriptomic data were combined to identify key altered markers that could indicate the risk rank of AML patients. The survival status was assessed by Kaplan-Meier and multivariate Cox regression analyses. We delineated serum protein expression in a population of AML patients. Many biological processes were influenced by the identified differentially expressed proteins. Association analysis of transcriptome data showed that intercellular adhesion molecule-2 (ICAM2) had a higher survival prediction value in the intermediate-risk AML group. ICAM2 was detrimental for intermediate-risk AML, regardless of whether patients received bone marrow transplantation. ICAM2 well distinguishes the intermediate group of patients, whose probability of survival is comparable to that of patients with the ELN-2017 according to the reference classification. In addition, newly established stratified clinical features were associated with leukemia stem cell scores. The inclusion of ICAM2 expression into the AML risk classification according to ELN-2017 was a good way to transfer patients from three to two groups. Thus, providing more information for clinical decision-making to improve intermediate-risk stratification in AML patients.

Association analysis in food sampling inspection data

At present, China exists a problem that the cost of food sampling inspection is too high. This paper attempts to reduce the number of sampling inspection items in the same food category, reduce the cost of food sampling inspection, and improve the work efficiency through the association analysis of national sampling inspection data. And this paper applies Apriori algorithm to analyse the association rules, which is based on the unqualified pastry sampling inspection data in the 2019 national food sampling inspection database. Finally, we obtain 10 strong association rules through experiments. The results show that this association analysis can reduce the workload of food sampling inspection effectively.

OmicsOne: associate omics data with phenotypes in one-click

BackgroundThe rapid advancements of high throughput “omics” technologies have brought a massive amount of data to process during and after experiments. Multi-omic analysis facilitates a deeper interrogation of a dataset and the discovery of interesting genes, proteins, lipids, glycans, metabolites, or pathways related to the corresponding phenotypes in a study. Many individual software tools have been developed for data analysis and visualization. However, it still lacks an efficient way to investigate the phenotypes with multiple omics data. Here, we present OmicsOne as an interactive web-based framework for rapid phenotype association analysis of multi-omic data by integrating quality control, statistical analysis, and interactive data visualization on ‘one-click’.Materials and methodsOmicsOne was applied on the previously published proteomic and glycoproteomic data sets of high-grade serous ovarian carcinoma (HGSOC) and the published proteome data set of lung squamous cell carcinoma (LSCC) to confirm its performance. The data was analyzed through six main functional modules implemented in OmicsOne: (1) phenotype profiling, (2) data preprocessing and quality control, (3) knowledge annotation, (4) phenotype associated features discovery, (5) correlation and regression model analysis for phenotype association analysis on individual features, and (6) enrichment analysis for phenotype association analysis on interested feature sets.ResultsWe developed an integrated software solution, OmicsOne, for the phenotype association analysis on multi-omics data sets. The application of OmicsOne on the public data set of ovarian cancer data showed that the software could confirm the previous observations consistently and discover new evidence for HNRNPU and a glycopeptide of HYOU1 as potential biomarkers for HGSOC data sets. The performance of OmicsOne was further demonstrated in the Tumor and NAT comparison study on the proteome data set of LSCC.ConclusionsOmicsOne can effectively simplify data analysis and reveal the significant associations between phenotypes and potential biomarkers, including genes, proteins, and glycopeptides, in minutes to assist users to understand aberrant biological processes.

FeatureCorr: An R package to study feature correlations aided with data transformation for sequencing and microarray data

<h2>Abstract</h2> FeatureCorr is an R package that aids in association and network analysis of data obtained from preliminary bioinformatic analysis of next-generation sequencing(NGS) or microarray experiments. These experiments are widely used for various applications like mutation and expression profiles, detection of epigenetic changes in the genomic DNA, etc. FeatureCorr enables users in cleaning and preprocessing data to minimize batch effects and for background noise removal. FeatureCorr can help in the analysis of feature correlation in different ways: Correlation of one Feature vs multiple Features, pairwise correlation of multiple features against multiple features, and in-depth correlation and distributions of two features.

Screening of candidate genes related to low-dose ionizing radiation based on transcriptome-proteome correlation research techniques

Objective: To identify the related genes of low-dose ionizing radiation on basis of association analysis of transcriptome and proteome data, and provide new clues for the molecular mechanism of low-dose radiation (LDR) effect. Methods: In March 2018, healthy human peripheral blood was used as materials for transcriptome sequencing and proteome analysis after exposure to radiation at 150 mGy (treatment group) and no radiation (control group) , with three samples in each group. The total RNA and protein were extracted and then correlation analysis of transcriptomic and proteomic were performed to determine LDR effect-related genes, and after that, the biological process and molecular function were analyzed. Results: A total of 486 genes and 266 proteins were identified differentially expressed between treatment group and control group, respectively. Twelve genes and related proteins were found correlated (P<0.05) . The overall correlation between quantitative protein and gene was low (rs=0.0034) , the differential gene with the same change trend was positively correlated with protein expression (rs=0.6786) , and the differential gene with the opposite change trend was negatively correlated with protein expression (rs=-0.1000) . Seven differentially expressed genes (DEGs) showed the same trend as proteins, among which FBXO7 and SNCA were up-regulated as well as ORM1, ORM2, HIST1H4J, HBZ and LYZ were down-regulated. Five DEGs showed the opposite trend as proteins, including SLC4A1, BCAM, C4B_2, KEL, TGM2 up-regulated in transcription level and down-regulated in protein expression level. These DEGs were involved in various biological processes such as immune system regulation, signal transduction, enzyme activity regulation, transmembrane transport, defense, transcription and DNA repair, which indicated their important roles in response to LDR in human peripheral blood. Conclusion: Twelve candidate genes related to LDR effect and their corresponding expressed proteins are screened by the correlation research of transcriptome and proteome data, which provides new clues for the further study of the mechanism of LDR effect.

The genetics of vigour-related traits in chickpea (Cicer arietinum L.): insights from genomic data.

QTL controlling vigour and related traits were identified in a chickpea RIL population and validated in diverse sets of germplasm. Robust KASP markers were developed for marker-assisted selection. To understand the genetic constitution of vigour in chickpea (Cicer arietinum L.), genomic data from a bi-parental population and multiple diversity panels were used to identify QTL, sequence-level haplotypes and genetic markers associated with vigour-related traits in Australian environments. Using 182 Recombinant Inbred Lines (RILs) derived from a cross between two desi varieties, Rupali and Genesis836, vigour QTL independent of flowering time were identified on chromosomes (Ca) 1, 3 and 4 with genotypic variance explained (GVE) ranging from 7.1 to 28.8%. Haplotype analysis, association analysis and graphical genotyping of whole-genome re-sequencing data of two diversity panels consisting of Australian and Indian genotypes and an ICRISAT Chickpea Reference Set revealed a deletion in the FTa1-FTa2-FTc gene cluster of Ca3 significantly associated with vigour and flowering time. Across the RIL population and diversity panels, the impact of the deletion was consistent for vigour but not flowering time. Vigour-related QTL on Ca4 co-located with a QTL for seed size in Rupali/Genesis836 (GVE = 61.3%). Using SNPs from this region, we developed and validated gene-based KASP markers across different panels. Two markers were developed for a gene on Ca1, myo -inositol monophosphatase (CaIMP), previously proposed to control seed size, seed germination and seedling growth in chickpea. While associated with vigour in the diversity panels, neither the markers nor broader haplotype linked to CaIMP was polymorphic in Rupali/Genesis836. Importantly, vigour appears to be controlled by different sets of QTL across time and with components which are independent from phenology.

Joint association and classification analysis of multi-view data.

Multi-view data, which is matched sets of measurements on the same subjects, have become increasingly common with advances in multi-omics technology. Often, it is of interest to find associations between the views that are related to the intrinsic class memberships. Existing association methods cannot directly incorporate class information, while existing classification methods do not take into account between-views associations. In this work, we propose a framework for Joint Association and Classification Analysis of multi-view data (JACA). Our goal is not to merely improve the misclassification rates, but to provide a latent representation of high-dimensional data that is both relevant for the subtype discrimination and coherent across the views. We motivate the methodology by establishing a connection between canonical correlation analysis and discriminant analysis. We also establish the estimation consistency of JACA in high-dimensional settings. A distinct advantage of JACA is that it can be applied to the multi-view data with block-missing structure, that is to cases where a subset of views or class labels is missing for some subjects. The application of JACA to quantify the associations between RNAseq and miRNA views with respect to consensus molecular subtypes in colorectal cancer data from The Cancer Genome Atlas project leads to improved misclassification rates and stronger found associations compared to existingmethods.

Conceptual review on the conventional and genome-wide association analysis towards developing salinity tolerance in rice

Salinity is the major abiotic stress which predominantly affects the productivity of rice worldwide. Conventional breeding programs to develop stress-tolerant varieties showed only marginal success. Marker-assisted selection can improve the efficiency of salinity tolerance as they are growth stage and environment independent. However, physiological response due to ionic and osmotic stresses caused by salt accumulation in the soil hinders plant growth and development. Genetic engineering strategy was adopted to tailor the selection and incorporation of candidate salt-tolerant genes in rice. Understanding the genomics of salinity tolerance remains a complex phenomenon since several genes and pathways control them. Genome-wide association studies revealing the information of SNP's variants and functional effects appear to be a future for breeding salinity-tolerant rice. Therefore, this review provides scientific insights into the mechanisms and approaches to enhance salinity tolerance, genome-wide association analysis, and the CRISPR/Cas technology as an efficient tool for genome modifications. Genome-wide association analysis showed the presence of major QTL region SalTol in chromosome 1, containing potential salt tolerant responsive genes in indica varieties. The distribution of SNP and InDels was highest in the Chromosome 1 of Godawee, Pokkali, and Nona Bokra. The SNP and InDels density was not consistent among the varieties. Genome-wide association analysis of SNPs and InDels data highlighted the importance of genomic variants in regulating the salinity tolerance that could be useful for future crop improvements.

Bibliometrics and visualization analysis of China's Service Quality Development Trend

From the aspect of bibliometrics and social network analysis, this paper studies the content characteristics and network evolution of service quality in China, form visual analysis charts and summarizes the research hotspots and development trends. Taking CNKI database as the data source, data mining and association analysis of sample data were carried out by means of manual judgment, keyword co-occurrence, bibliometric software BICOMB and Pajek. 872 related literatures were retrieved from 1999 to 2019, and the tendency of the number of published papers in each year was close to the inverted U type. This study expands the application fields of bibliometrics and social network software, and analyzes the development trend of service quality. The theoretical and practical research on service quality has achieved rapid development in the past 20 years. The library service quality and service quality satisfaction have always gotten a high level of attention, and the characteristics of network platforms for service quality have gradually become apparent because of the development of the Internet and computer technology.