PGD: a machine learning-based photosynthetic-related gene detection approach.

BACKGROUND: The primary determinant of crop yield is photosynthetic capacity, which is under the control of photosynthesis-related genes. Therefore, the mining of genes involved in photosynthesis is important for the study of photosynthesis. MapMan Mercator 4 is a powerful annotation tool for assigning genes into proper functional categories; however, in maize, the functions of approximately 22.15% (9520) of genes remain unclear and are labeled "not assigned", which may include photosynthesis-related genes that have not yet been identified. The fast-increasing usage of the machine learning approach in solving biological problems provides us with a new chance to identify novel photosynthetic genes from functional "not assigned" genes in maize. RESULTS: In this study, we proved the ensemble learning model using a voting eliminates the preferences of single machine learning models. Based on this evaluation, we implemented an ensemble based ML(Machine Learning) methods using a majority voting scheme and observed that including RNA-seq data from multiple photosynthetic mutants rather than only a single mutant could increase prediction accuracy. And we call this approach "A Machine Learning-based Photosynthetic-related Gene Detection approach (PGD)". Finally, we predicted 716 photosynthesis-related genes from the "not assigned" category of maize MapMan annotation. The protein localization prediction (TargetP) and expression trends of these genes from maize leaf sections indicated that the prediction was reliable and robust. And we put this approach online base on google colab. CONCLUSIONS: This study reveals a new approach for mining novel genes related to a specific functional category and provides candidate genes for researchers to experimentally define their biological functions.

Effects of chronic exposure to the fungicide vinclozolin on gut microbiota community in an aquatic turtle.

Environmental issues associated with the widespread use of agricultural chemicals are being seriously concerned. Of them, toxicological impacts of fungicides in aquatic organisms are often overlooked. Here, soft-shelled turtle (Pelodiscus sinensis) hatchlings were exposed to different concentrations of vinclozolin (0, 5, 50, 500 and 5000 µg/L) for 60 days to investigate the impact of fungicide exposure on their gut microbial composition and diversity. Vinclozolin exposure significantly affected the composition of the gut microbiota in hatchling turtles. Unexpectedly, gut bacterial diversity and richness of vinclozolin-exposed turtles (but not for the 5000 µg/L-exposed group) were relatively higher than control ones. At the phylum level, the abundance of Firmicutes was decreased, while that of Proteobacteria was increased in high-concentration groups. At the genus level, some bacterial genera including Cellulosilyticum, Romboutsia and Clostridium_sensu_stricto, were significantly changed after vinclozolin exposure; and some uniquely observed in high-concentration groups. Gene function predictions showed that genes related to amino acid metabolism were less abundant, while those related to energy metabolism more abundant in high-concentration groups. The prevalence of some pathogens inevitably affected gut health status of vinclozolin-exposed turtles. Such gut microbiota dysbiosis might be potentially linked with hepatic metabolite changes induced by vinclozolin exposure.

ERP Responses to Violations in the Hierarchical Structure of Functional Categories in Japanese Verb Conjugation.

An event-related potential experiment was conducted in order to investigate readers' response to violations in the hierarchical structure of functional categories in Japanese, an agglutinative language where functional heads like Negation (Neg) as well as Tense (Tns) are realized as suffixes. A left-lateralized negativity followed by a P600 was elicited for the anomaly of attaching a Neg morpheme outside a Tns-marking suffix (i.e., syntactic violation of the form *[[V - Tns] - Neg]), while only P600 was observed for the anomalous form with a purely morphological/morpho-phonological violation, i.e., a Neg morpheme attached to ren'yo form instead of Neg-selecting form. The findings suggest that the syntactic structure involving Tns and Neg in Japanese, realized within a word as a sequence of suffixes, is processed in a similar manner to the syntactic structures that are phrasally realized in well-studied European languages like English.

Examining the Functional Category in Chinese-English Code-Switching: Evidence from the Eye-Movements.

To investigate the grammatical constraints of code-switching (CS hereafter) under the disputes of the constraint-based account versus the constraint-free account, the effects of functional category on CS have long been investigated in the existing studies. Thus, the present study, by asking 47 participants to take part in an eye-movement experiment, examined the potential effects of functional category on Chinese-English CS. We found that differential switch costs at varying code-switched conditions as well as robust switch effects that last from the early to the late stage. The findings could tentatively give rise to the theoretical predictions of the minimalist program, a representative of the constraint-free account rather than the functional head constraint, a typical representative of the constraint-based account. Moreover, such switch effects might initiate from the early to the very late stage in terms of time-course of CS processing.

Representation of Functional Category in the Monkey Prefrontal Cortex and Its Rule-Dependent Use for Behavioral Selection.

Humans, monkeys, and other animals are considered to have the cognitive ability to use functional categories--that is, stimulus groups based on functional equivalence independent of physical properties. To investigate the underlying neural mechanisms of the use of functional categories, we recorded single-unit activity in the prefrontal cortex of monkeys performing a behavioral task in which the rule-dependent usage of functional category was needed to select an appropriate response. We found a neural correlate of functional categories on the single-neuron level and found that category information is coded independently of other task-relevant information such as rule and contingency information. Analysis of the time course of the information activation suggested that contingency information used for action selection is derived by integrating incoming category information with rule information maintained throughout a session. Such neural computation can be considered as the neural background of flexible behavioral control based on category and rule.

Enrichment of SNPs in Functional Categories Reveals Genes Affecting Complex Traits.

Genome-wide association studies (GWAS) have indicated potential to identify heritability of common complex phenotypes, but traditional approaches have limited ability to detect hiding signals because single SNP has weak effect size accounting for only a small fraction of overall phenotypic variations. To improve the power of GWAS, methods have been developed to identify truly associated genes by jointly testing effects of all SNPs. However, equally considering all SNPs within a gene might dilute strong signals of SNPs in real functional categories. Here, we observed a consistent pattern on enrichment of significant SNPs in eight functional categories across six phenotypes, with the highest enrichment in coding and both UTR regions while the lowest enrichment in the intron. Based on the pattern of SNP enrichment in functional categories, we developed a new approach for detecting gene associations on traits (DGAT) by selecting the most significant functional category and then using SNPs within it to assess gene associations. The method was found to be robust in type I error rate on simulated data, and to have mostly higher power in detecting associated genes for three different diseases than other methods. Further analysis indicated ability of the DGAT to detect novel genes. The DGAT is available by http://sparks-lab.org/server/DGAT.

Multiple Factors Drive Replicating Strand Composition Bias in Bacterial Genomes.

Composition bias from Chargaff's second parity rule (PR2) has long been found in sequenced genomes, and is believed to relate strongly with the replication process in microbial genomes. However, some disagreement on the underlying reason for strand composition bias remains. We performed an integrative analysis of various genomic features that might influence composition bias using a large-scale dataset of 1111 genomes. Our results indicate (1) the bias was stronger in obligate intracellular bacteria than in other free-living species (p-value=0.0305); (2) Fusobacteria and Firmicutes had the highest average bias among the 24 microbial phyla analyzed; (3) the strength of selected codon usage bias and generation times were not observably related to strand composition bias (p-value=0.3247); (4) significant negative relationships were found between GC content, genome size, rearrangement frequency, Clusters of Orthologous Groups (COG) functional subcategories A, C, I, Q, and composition bias (p-values<1.0×10(-8)); (5) gene density and COG functional subcategories D, F, J, L, and V were positively related with composition bias (p-value<2.2×10(-16)); and (6) gene density made the most important contribution to composition bias, indicating transcriptional bias was associated strongly with strand composition bias. Therefore, strand composition bias was found to be influenced by multiple factors with varying weights.

Parallel functional category deficits in clauses and nominal phrases: The case of English agrammatism.

Individuals with agrammatic aphasia exhibit restricted patterns of impairment of functional morphemes, however, syntactic characterization of the impairment is controversial. Previous studies have focused on functional morphology in clauses only. This study extends the empirical domain by testing functional morphemes in English nominal phrases in aphasia and comparing patients' impairment to their impairment of functional morphemes in English clauses. In the linguistics literature, it is assumed that clauses and nominal phrases are structurally parallel but exhibit inflectional differences. The results of the present study indicated that aphasic speakers evinced similar impairment patterns in clauses and nominal phrases. These findings are consistent with the Distributed Morphology Hypothesis (DMH), suggesting that the source of functional morphology deficits among agrammatics relates to difficulty implementing rules that convert inflectional features into morphemes. Our findings, however, are inconsistent with the Tree Pruning Hypothesis (TPH), which suggests that patients have difficulty building complex hierarchical structures.

Gut microbiota composition alteration analysis and functional categorization in children with growth hormone deficiency.

Objective: To study changes in the composition and functions of the gut microbiota (GM) in children with growth hormone deficiency (GHD) using high-throughput sequencing. Methods: Thirty-three children with GHD diagnosed in Longgang District Maternity and Child Health Hospital were included in the disease group and 24 healthy children of the same age comprised the control group. Total DNA was extracted and amplified from stool samples obtained from all subjects. High-throughput sequencing was used to analyze the GM composition and functions. Results: The GM from the two groups of children showed significant differences in α-diversity (P < 0.05). In comparison with the control group, the abundance of the phylum Bacteroidetes was significantly higher (45.96% vs. 65.71%) while the Firmicutes count was significantly lower (47.09% vs. 25.20%). At the genus level, the abundance of Prevotella in the disease group was significantly higher (3.16% vs. 20.67%) and that of Lachnospiracea incertae sedis, Clostridium XlVa, and Megamonas was lower (6.576% vs. 1.75%; 4.51% vs. 0.80%; 5.08% vs. 2.02%, respectively). GM functions, including those involved in membrane_transport, energy_metabolism, poorly_characterized, metabolism_of_cofactors_and_vitamins, glycan_biosynthesis_and_metabolism, transcription, folding,_sorting,_and_degradation, were significantly altered in the disease group. The abundance of various GM components was correlated with endocrine hormone levels. Conclusion: Significant alterations in the GM are seen in children with growth hormone deficiency, which may affect both energy metabolism and the levels of endocrine hormones, potentially leading to growth restriction.

Skeletal muscle as a treatment target for older adults with diabetes mellitus: The importance of a multimodal intervention based on functional category.

Although the lifespan of people with diabetes has increased in many countries, the age-related increase in comorbidities (sarcopenia, frailty and disabilities) and diabetic complications has become a major issue. Diabetes accelerates the aging of skeletal muscles and blood vessels through mechanisms, such as increased oxidative stress, chronic inflammation, insulin resistance, mitochondrial dysfunction, genetic polymorphism (fat mass and obesity-associated genes) and accumulation of advanced glycation end-products. Diabetes is associated with early onset, and progression of muscle weakness and sarcopenia, thus resulting in diminished daily life function. The type and duration of diabetes, insulin section/resistance, hyperglycemia, diabetic neuropathy, malnutrition and low physical activity might affect muscular loss and weakness. To prevent the decline in daily activities in older adults with diabetes, resistance training or multicomponent exercise should be recommended. To maintain muscle function, optimal energy and sufficient protein intake are necessary. Although no specific drug enhances muscle mass and function, antidiabetic drugs that increase insulin sensitivity or secretion could be candidates for improvement of sarcopenia. The goals of glycemic control for older patients are determined based on three functional categories through an assessment of cognitive function and activities of daily living, and the presence or absence of medications that pose a hypoglycemic risk. As these functional categories are associated with muscle weakness, frailty and mortality risk, providing multimodal interventions (exercise, nutrition, social network or support and optimal medical treatment) is important, starting at the category II stage for maintenance or improvement in daily life functions. Geriatr Gerontol Int 2022; 22: 110-120.

Inference-based accuracy of metagenome prediction tools varies across sample types and functional categories.

BACKGROUND: Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition. In this study, we evaluated the performance of three commonly used metagenome prediction tools (PICRUSt, PICRUSt2, and Tax4Fun) by comparing the significance of the differential abundance of predicted functional gene profiles to those from shotgun metagenome sequencing across different environments. RESULTS: We selected 7 datasets of human, non-human animal, and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between predicted gene compositions and gene relative abundance measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the abundance of genes were permuted across samples. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of metagenome prediction tools. As an alternative, we compared the performance of genes predicted with PICRUSt, PICRUSt2, and Tax4Fun to sequenced metagenome genes in inference models associated with metadata within each dataset. With this approach, we found reasonable performance for human datasets, with the metagenome prediction tools performing better for inference on genes related to "housekeeping" functions. However, their performance degraded sharply outside of human datasets when used for inference. CONCLUSION: We conclude that the utility of PICRUSt, PICRUSt2, and Tax4Fun for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted. Video abstract.

Distinct Gut Microbiota Composition and Functional Category in Children With Cerebral Palsy and Epilepsy.

Cerebral palsy (CP) and epilepsy are two interactive neurological diseases, and their clinical treatment can cause severe side-effects in children's development, especially when it involves long-term administration of antiepileptic drugs. Accumulating studies on the gut-brain axis indicated that the gut microbiota (GM), which participates in various neurological diseases, would provide a harmless therapeutic target for the treatment of CP and epilepsy. To explore the GM characteristics in children with both CP and epilepsy (CPE), we collected fecal samples from 25 CPE patients (CPE group) and 21 healthy children (Healthy group) for 16S rDNA sequencing. In this study, we discovered significantly higher microbial diversity in the CPE group compared to healthy group (P < 0.001). After selecting the top 15 most abundant genera in each group, we found significantly enriched Bifidobacterium, Streptococcus, Akkermansia, Enterococcus, Prevotella, Veillonella, Rothia, and Clostridium IV in the CPE group, and noticeably reduced Bacteroides, Faecalibacterium, Blautia, Ruminococcus, Roseburia, Anaerostipes, and Parasutterella. A GM co-occurrence network was also constructed, and negative correlations were discovered between Bacteroides and Lactobacillus (r = -0.768, P < 0.001, FDR < 0.001), as well as Intestinibacter and Bifidobacterium (r = -0.726, P < 0.001, FDR < 0.001). After KEGG annotation and functional enrichment, 24 functional categories exhibited different enrichment levels between the CPE and Healthy groups. The functions, associated with xenobiotics metabolism, immune system diseases, and neurodegenerative diseases, were enriched in the CPE group. Conversely, the functional categories related to the biosynthesis of secondary metabolites were reduced. Furthermore, the neurodegenerative diseases were mainly attributed to Streptococcus, while an increased risk of immune system diseases was associated with enriched Akkermansia in the CPE patients. Generally, this study characterized the GM in CPE patients, illustrated the microbial co-occurrence relationships, and detected the functional distributions of the bacteria.