PacBio single-molecule long-read sequencing provides new insights into the complexity of full-length transcripts in oriental river prawn, macrobrachium nipponense.

BACKGROUND: Oriental river prawn (Macrobrachium nipponense) is one of the most dominant species in shrimp farming in China, which is a rich source of protein and contributes to a significant impact on the quality of human life. Thus, more complete and accurate annotation of gene models are important for the breeding research of oriental river prawn. RESULTS: A full-length transcriptome of oriental river prawn muscle was obtained using the PacBio Sequel platform. Then, 37.99 Gb of subreads were sequenced, including 584,498 circular consensus sequences, among which 512,216 were full length non-chimeric sequences. After Illumina-based correction of long PacBio reads, 6,599 error-corrected isoforms were identified. Transcriptome structural analysis revealed 2,263 and 2,555 alternative splicing (AS) events and alternative polyadenylation (APA) sites, respectively. In total, 620 novel genes (NGs), 197 putative transcription factors (TFs), and 291 novel long non-coding RNAs (lncRNAs) were identified. CONCLUSIONS: In summary, this study offers novel insights into the transcriptome complexity and diversity of this prawn species, and provides valuable information for understanding the genomic structure and improving the draft genome annotation of oriental river prawn.

Integrated analysis of the miRNA and mRNA expression profiles in Leiocassis longirostris at gonadal maturation.

Leiocassis longirostris is a commercially important fish species that shows a sexually dimorphic growth pattern. A lack of molecular data from the gonads of this species has hindered research and selective breeding efforts. In this study, we conducted a comprehensive analysis of the expression profile of miRNA and mRNA to explore their regulatory roles in the gonadal maturation stage of L. longirostris. We identified 60 differentially expressed miRNAs and 20,752 differentially expressed genes by sequencing. A total of 90 miRNAs and 21 target genes involved in gonad development and sex determination were identified. Overall, the results of this study enhance our understanding of the molecular mechanisms underlying sex determination and differentiation and provide valuable genomic information for the selective breeding of L. longirostris.

Toxic metals in rice-fish co-culture systems and human health.

The threat of contamination with toxic metals (TMs) to food security and human health has become a high priority in recent decades. Hence, countless studies have investigated the safe cultivation of rice and fish, respectively, as the main food crop and protein source worldwide. For the present study, a literature search of the PubMed, Web of Science, ScienceDirect, and China National Knowledge Infrastructure databases identified 11 studies that met the inclusion criteria and provided sufficient data to assess the relationship between TM contamination of rice, fish, and shrimp products from rice-fish co-culture systems and carcinogenic risk (CR) and non-carcinogenic risk (non-CR) to humans. The result showed that consumption of Monopterus albus and rice contaminated with a single TM had a slight non-CR, which is synergistically increased by multiple TMs. Consumption of Procambarus clarkii posed no non-CR to humans. The CR of all studies ranged from 1.77 × 10-10 to 5.65 × 10-8, and less than 1 × 10-6, indicating that under current food safety guidelines, rice and fish produced by rice-fish co-culture systems pose no CR. Rice-fish co-culture systems can greatly reduce the CR and non-CR of TMs to humans.

MiRNA-seq analysis of spleen and head kidney tissue from aquacultured largemouth bass (Micropterus salmoides) in response to Aeromonas hydrophila infection.

Recently, the same fish diseases, which have been found in pond farming, have been found in the newly tested largemouth bass (Micropterus salmoides) system. Bacterial septicemia caused by Aeromonas hydrophila occurs frequently in largemouth bass culture leading to significant economic losses. To investigate the role miRNA in the largemouth bass disease resistance, twelve (2 tissues (spleen and head kidney) × 2 experimental groups (infected and control) × three biological replicates) small RNA libraries were constructed and sequenced with miRNA-seq. A total of 26 differentially expressed miRNAs, 8 upregulated and 18 downregulated, were identified in the spleen, and 19 differentially expressed miRNAs, 9 upregulated and 10 downregulated, were identified in head kidney (fold change ≥ 2 or ≤ 0.5 and P ≤ 0.05). The differentially expressed miRNAs with the largest fold change were selected for target gene prediction using GO and KEGG analysis. Six miRNAs in the spleen and 5 miRNAs in the head kidney were selected. Analysis showed that, of all the immune and metabolic pathways, the FoxO signaling pathway was enriched in both the spleen and head kidney groups. Common target genes of the pathway included AMP-activated catalytic subunit alpha 1 (prkaa1), phosphatidylinositol 3-kinase (pik3r3b), serine/threonine-protein kinase (plk2), and forkhead box protein G1 (foxg1a). MiRNAs (such as miR-126-5P, miR-126-3P) are involved in immune response and cell cycle functions as they regulate targeted genes in the FoxO pathway. These results will enhance our understanding of the molecular mechanisms underlying immune responses to bacterial septicemia and facilitate molecular-assisted selection of resistant strains of largemouth bass.

Integrative analysis identifies the quality advantage and corresponding regulatory mechanism of paddy field-cultured crayfish (Procambarus clarkii).

Procambarus clarkii is the dominant economic variety of crayfish in China, and paddy field shrimp cultivation is an organic mode of traditional rice-fish cultivation, with paddy field shrimp being the country's prevailing aquatic product. However, little has been reported on the differences in meat quality and digestive ability between paddy field and pond fish. In this study, the muscle composition and digestive function regulation of P. clarkii in ponds and paddies were studied to explore the influence of paddy field culture on P. clarkii quality. The results showed that the muscle composition of paddy field shrimp was significantly changed, with increased protein and decreased lipid levels. Through the study of the hepatopancreas and intestinal microbial diversity of P. clarkii, we hypothesized that rice farming may cause changes in its bacterial spectrum, stimulate the digestive functions of its intestines and hepatopancreas, cause differential expression of multi-substance metabolic pathways, and ultimately result in the substances' deposition in its muscles. This study revealed the impact of rice cultivation on P. clarkii from the perspective of meta-metabolism, and it demonstrated the advantages of paddy field shrimp cultivation.Key points• We explored the influence of paddy field culture on P. clarkii quality.• Muscle composition of paddy field shrimp was significantly changed, with increased protein and decreased lipid levels in paddy field.• Rice farming caused changes in its bacterial spectrum and stimulated the digestive functions of hepatopancreas.

Accurately estimating the length distributions of genomic micro-satellites by tumor purity deconvolution.

BACKGROUND: Genomic micro-satellites are the genomic regions that consist of short and repetitive DNA motifs. Estimating the length distribution and state of a micro-satellite region is an important computational step in cancer sequencing data pipelines, which is suggested to facilitate the downstream analysis and clinical decision supporting. Although several state-of-the-art approaches have been proposed to identify micro-satellite instability (MSI) events, they are limited in dealing with regions longer than one read length. Moreover, based on our best knowledge, all of these approaches imply a hypothesis that the tumor purity of the sequenced samples is sufficiently high, which is inconsistent with the reality, leading the inferred length distribution to dilute the data signal and introducing the false positive errors. RESULTS: In this article, we proposed a computational approach, named ELMSI, which detected MSI events based on the next generation sequencing technology. ELMSI can estimate the specific length distributions and states of micro-satellite regions from a mixed tumor sample paired with a control one. It first estimated the purity of the tumor sample based on the read counts of the filtered SNVs loci. Then, the algorithm identified the length distributions and the states of short micro-satellites by adding the Maximum Likelihood Estimation (MLE) step to the existing algorithm. After that, ELMSI continued to infer the length distributions of long micro-satellites by incorporating a simplified Expectation Maximization (EM) algorithm with central limit theorem, and then used statistical tests to output the states of these micro-satellites. Based on our experimental results, ELMSI was able to handle micro-satellites with lengths ranging from shorter than one read length to 10kbps. CONCLUSIONS: To verify the reliability of our algorithm, we first compared the ability of classifying the shorter micro-satellites from the mixed samples with the existing algorithm MSIsensor. Meanwhile, we varied the number of micro-satellite regions, the read length and the sequencing coverage to separately test the performance of ELMSI on estimating the longer ones from the mixed samples. ELMSI performed well on mixed samples, and thus ELMSI was of great value for improving the recognition effect of micro-satellite regions and supporting clinical decision supporting. The source codes have been uploaded and maintained at https://github.com/YixuanWang1120/ELMSI for academic use only.

A hybrid correcting method considering heterozygous variations by a comprehensive probabilistic model.

BACKGROUND: The emergence of the third generation sequencing technology, featuring longer read lengths, has demonstrated great advancement compared to the next generation sequencing technology and greatly promoted the biological research. However, the third generation sequencing data has a high level of the sequencing error rates, which inevitably affects the downstream analysis. Although the issue of sequencing error has been improving these years, large amounts of data were produced at high sequencing errors, and huge waste will be caused if they are discarded. Thus, the error correction for the third generation sequencing data is especially important. The existing error correction methods have poor performances at heterozygous sites, which are ubiquitous in diploid and polyploidy organisms. Therefore, it is a lack of error correction algorithms for the heterozygous loci, especially at low coverages. RESULTS: In this article, we propose a error correction method, named QIHC. QIHC is a hybrid correction method, which needs both the next generation and third generation sequencing data. QIHC greatly enhances the sensitivity of identifying the heterozygous sites from sequencing errors, which leads to a high accuracy on error correction. To achieve this, QIHC established a set of probabilistic models based on Bayesian classifier, to estimate the heterozygosity of a site and makes a judgment by calculating the posterior probabilities. The proposed method is consisted of three modules, which respectively generates a pseudo reference sequence, obtains the read alignments, estimates the heterozygosity the sites and corrects the read harboring them. The last module is the core module of QIHC, which is designed to fit for the calculations of multiple cases at a heterozygous site. The other two modules enable the reads mapping to the pseudo reference sequence which somehow overcomes the inefficiency of multiple mappings that adopt by the existing error correction methods. CONCLUSIONS: To verify the performance of our method, we selected Canu and Jabba to compare with QIHC in several aspects. As a hybrid correction method, we first conducted a groups of experiments under different coverages of the next-generation sequencing data. QIHC is far ahead of Jabba on accuracy. Meanwhile, we varied the coverages of the third generation sequencing data and compared performances again among Canu, Jabba and QIHC. QIHC outperforms the other two methods on accuracy of both correcting the sequencing errors and identifying the heterozygous sites, especially at low coverage. We carried out a comparison analysis between Canu and QIHC on the different error rates of the third generation sequencing data. QIHC still performs better. Therefore, QIHC is superior to the existing error correction methods when heterozygous sites exist.

An Efficient Algorithm for Sensitively Detecting Circular RNA from RNA-seq Data.

Circular RNA (circRNA) is an important member of non-coding RNA family. Numerous computational methods for detecting circRNAs from RNA-seq data have been developed in the past few years, but there are dramatic differences among the algorithms regarding the balancing of the sensitivity and precision of the detection and filtering strategies. To further improve the sensitivity, while maintaining an acceptable precision of circRNA detection, a novel and efficient de novo detection algorithm, CIRCPlus, is proposed in this paper. CIRCPlus accurately locates circRNA candidates by identifying a set of back-spliced junction reads by comparing the local similar sequence of each pair of spanning junction reads. This strategy, thus, utilizes the important information provided by unbalanced spanning reads, which facilitates the detection especially when the expression levels of circRNA are unapparent. The performance of CIRCPlus was tested and compared to the existing de novo methods on the real datasets as well as a series of simulation datasets with different configurations. The experiment results demonstrated that the sensitivities of CIRCPlus were able to reach 90% in common simulation settings, while CIRCPlus held balanced sensitivity and reliability on the real datasets according to an objective assessment criteria based on RNase R-treated samples. The software tool is available for academic uses only.

Synstable Fusion: A Network-Based Algorithm for Estimating Driver Genes in Fusion Structures.

Gene fusion structure is a class of common somatic mutational events in cancer genomes, which are often formed by chromosomal mutations. Identifying the driver gene(s) in a fusion structure is important for many downstream analyses and it contributes to clinical practices. Existing computational approaches have prioritized the importance of oncogenes by incorporating prior knowledge from gene networks. However, different methods sometimes suffer different weaknesses when handling gene fusion data due to multiple issues such as fusion gene representation, network integration, and the effectiveness of the evaluation algorithms. In this paper, Synstable Fusion (SYN), an algorithm for computationally evaluating the fusion genes, is proposed. This algorithm uses network-based strategy by incorporating gene networks as prior information, but estimates the driver genes according to the destructiveness hypothesis. This hypothesis balances the two popular evaluation strategies in the existing studies, thereby providing more comprehensive results. A machine learning framework is introduced to integrate multiple networks and further solve the conflicting results from different networks. In addition, a synchronous stability model is established to reduce the computational complexity of the evaluation algorithm. To evaluate the proposed algorithm, we conduct a series of experiments on both artificial and real datasets. The results demonstrate that the proposed algorithm performs well on different configurations and is robust when altering the internal parameter settings.

An improved burden-test pipeline for identifying associations from rare germline and somatic variants.

BACKGROUND: Identifying rare germline and somatic variants associated with cancer progression is an important research topic in cancer genomics. Although many approaches are proposed for rare variant association study, they are not fit for cancer sequencing data due to multiple issues, such as overly relying on pre-selection, losing sight of interacting hotspots, etc. RESULTS: In this article, we propose an improved pipeline to identify germline variant and somatic mutation interactions influencing cancer susceptibility from pair-wise cancer sequencing data. The proposed pipeline, RareProb-C performs an algorithmic selection on the given variants by incorporating the variant allelic frequencies. The interactions among the variants are considered within the regions which are limited by a four-gamete test. Then it filters singular cases according to the posterior probability at each site. Finally, it outputs the selected candidates that pass a collapse test. CONCLUSIONS: We apply RareProb-C on a series of carefully constructed simulation cases and it outperforms six existing genetic model-free approaches. We also test RareProb-C on 429 TCGA ovarian cancer cases, and RareProb-C successfully identifies the known highlighted variants which are considered increasing disease susceptibilities.

Effects of different temperatures on Leiocassis longirostris gill structure and intestinal microbial composition.

Fish are poikilothermic vertebrates and their physiological activities are affected by water temperature. In recent years, extreme weather has occurred frequently, and temperature changes have adversely affected the growth of farmed fish. To explore the changes in gill tissue structure caused by changing the water temperature and the relationship between the intestinal microbiota and the Leiocassis longirostris host adaptation mechanism, gill tissue sections and intestinal microbial 16S rRNA amplicon sequencing were conducted under different temperature stress (low temperature 4 °C, normal temperature 26 °C and high temperature 32 °C). The results showed that heat stress and cold stress caused injury and swelling, terminal congestion, cell vacuolation, and necrosis of the gill tissue of L. longirostris. For intestinal microbiota, the abundances of Pseudomonadota and Bacillota increased at the cold stress, while the abundances of Fusobacteriota and Bacteroidota increased at the heat stress. The number of opportunistic bacteria, mainly Aeromonas and Acinetobacter, was the highest under cold stress. In addition, the richness of the intestinal microbiota decreased significantly at heat and cold stresses, while evenness increased. Prediction of intestinal microbiota function showed that most common functions, such as metabolism of cofactors and vitamins, energy metabolism and replication and repair, were decreased significantly at heat stress and cold stress, and phylogenetic relationship analysis revealed significant differences among the groups. In conclusion, the change of temperature altered the gill tissue structure, and affected the structure and homeostasis of the intestinal microbiota, thus affecting the survival time of L. longirostris, and cold stress had a greater effect than heat stress.

A probabilistic method for identifying rare variants underlying complex traits.

BACKGROUND: Identifying the genetic variants that contribute to disease susceptibilities is important both for developing methodologies and for studying complex diseases in molecular biology. It has been demonstrated that the spectrum of minor allelic frequencies (MAFs) of risk genetic variants ranges from common to rare. Although association studies are shifting to incorporate rare variants (RVs) affecting complex traits, existing approaches do not show a high degree of success, and more efforts should be considered. RESULTS: In this article, we focus on detecting associations between multiple rare variants and traits. Similar to RareCover, a widely used approach, we assume that variants located close to each other tend to have similar impacts on traits. Therefore, we introduce elevated regions and background regions, where the elevated regions are considered to have a higher chance of harboring causal variants. We propose a hidden Markov random field (HMRF) model to select a set of rare variants that potentially underlie the phenotype, and then, a statistical test is applied. Thus, the association analysis can be achieved without pre-selection by experts. In our model, each variant has two hidden states that represent the causal/non-causal status and the region status. In addition, two Bayesian processes are used to compare and estimate the genotype, phenotype and model parameters. We compare our approach to the three current methods using different types of datasets, and though these are simulation experiments, our approach has higher statistical power than the other methods. The software package, RareProb and the simulation datasets are available at: http://www.engr.uconn.edu/~jiw09003.

Study on the Adaptive Regulation of Light on the Stress Response of Mandarin Fish (Siniperca chuatsi) with Re-Feeding after Starvation.

Light influences the stress response to environmental stimuli and feeding behaviors of Siniperca chuatsi and, thus, is an important regulator of normal growth and development. In this study, we first explored the important role of light on the digestive and stress capacity of S. chuatsi by studying the changes in physiological and biochemical indicators of S. chuatsi, taking the re-feeding after starvation as the constant environmental stimulus and the light intensity as the adjustable environmental stimulus. The activity of protease and lipase was generally higher in the stomach tissues than in the intestinal tissues, especially lipase, which was higher in stomach tissues under all light conditions, and the protease and lipase activity peaked in the stomach tissues of S. chuatsi at a light intensity of 18.44 ± 3.00 lx and in intestinal tissues at 11.15 ± 2.01 lx, respectively, indicating that greater light intensity increased the digestive capacity of stomach tissues, whereas lower light intensity facilitated the digestive capacity of intestinal tissues. The tissues of the gill, stomach, and intestine had relatively high activity of stress-related enzymes, whereas the tissues of the brain, kidney, liver, and plasma samples had relatively low activity of enzymes. Collectively, the results show that light intensity at 11.15 ± 2.01 lx promoted digestive capacity in the intestine and enhanced the anti-stress ability of S. chuatsi in response to stress induced by re-feeding after starvation. These findings should prove useful for artificial breeding of S. chuatsi.

Integrated analysis of how gender and body weight affect the intestinal microbial diversity of Gymnocypris chilianensis.

Intestinal microorganisms that living in the mucosa and contents of the gastrointestinal tract of animals, have close links with their hosts over a long evolutionary history. The community structure of the fish intestinal microbiota is associated with food, living environment, and the growth stage. To screen for potential probiotics that can be used for regulating breeding behaviors, this study focused on the diversity of fish intestinal microorganisms. This study aimed to investigate the effects of sex and body weight on the intestinal microbial diversity of Gymnocypris chilianensis in the wild. The results showed that the significant high diversity and richness of intestinal microbiota were fould in heavier individuals, and males. The dominant bacterial phyla of G. chilianensis were Proteobacteria, Firmicutes, and Bacteroidetes. In addition, the abundance of Firmicutes varied significantly among different body weights. The genus profile revealed that small individuals were dominated by Weissella, while females were dominated by Aeromonas, and both large individuals and males were dominated by other genera. Phylogenetic relationships and UPGMA clustering analysis showed significant differences among the groups. In general, the two main factors that have an effect on the intestinal microbiota diversity of wild G. chilianensis are sex and body weight.

Single-nuclei RNA-seq reveals skin cell responses to Aeromonas hydrophila infection in Chinese longsnout catfish Leiocassis longirostris.

As the primary natural barrier that protects against adverse environmental conditions, the skin plays a crucial role in the innate immune response of fish, particularly in relation to bacterial infections. However, due to the diverse functionality and intricate anatomical and cellular composition of the skin, deciphering the immune response of the host is a challenging task. In this study, single nuclei RNA-sequencing (snRNA-seq) was performed on skin biopsies obtained from Chinese longsnout catfish (Leiocassis longirostris), comparing Aeromonas hydrophila-infected subjects to healthy control subjects. A total of 19,581 single nuclei cells were sequenced using 10x Genomics (10,400 in the control group and 9,181 in the treated group). Based on expressed unique transcriptional profiles, 33 cell clusters were identified and classified into 12 cell types including keratinocyte (KC), fibroblast (FB), endothelial cells (EC), secretory cells (SC), immune cells, smooth muscle cells (SMC), and other cells such as pericyte (PC), brush cell (BC), red blood cell (RBC), neuroendocrine cell (NDC), neuron cells (NC), and melanocyte (MC). Among these, three clusters of KCs, namely, KC1, KC2, and KC5 exhibited significant expansion after A. hydrophila infection. Analysis of pathway enrichment revealed that KC1 was primarily involved in environmental signal transduction, KC2 was primarily involved in endocrine function, and KC5 was primarily involved in metabolism. Finally, our findings suggest that neutrophils may play a crucial role in combating A. hydrophila infections. In summary, this study not only provides the first detailed comprehensive map of all cell types present in the skin of teleost fish but also sheds light on the immune response mechanism of the skin following A. hydrophila infection in Chinese longsnout catfish.

Toxic Metals in a Paddy Field System: A Review.

The threat of toxic metals to food security and human health has become a high-priority issue in recent decades. As the world's main food crop source, the safe cultivation of rice has been the focus of much research, particularly the restoration of toxic metals in paddy fields. Therefore, in this paper, we focus on the effects of toxic metals on rice, as well as the removal or repair methods of toxic metals in paddy fields. We also provide a detailed discussion of the sources and monitoring methods of toxic metals pollution, the current toxic metal removal, and remediation methods in paddy fields. Finally, several important research issues related to toxic metals in paddy field systems are proposed for future work. The review has an important guiding role for the future of heavy metal remediation in paddy fields, safe production of rice, green ecological fish culture, and human food security and health.

Studies on the molecular level changes and potential resistance mechanism of Coreius guichenoti under temperature stimulation.

In this study, we used transcriptome and proteome technology to analyze molecular level changes in tissues of Coreius guichenoti cultured at high temperature (HT) and low temperature (LT). We also screened for specific anti-stress genes and proteins and evaluated the relationships between them. We identified 201,803 unigenes and 10,623 proteins. Compared with the normal temperature (NT), 408 genes and 1,204 proteins were up- or down-regulated in brain tissues, respectively, at HT, and the numbers were 8 and 149 at LT. In gill tissues, the numbers were 101 and 1,745 at HT and 27 and 511 at LT. In gill tissues at both temperatures, the degree of down-regulation (average, HT 204.67-fold, LT 443.13-fold) was much greater than that of up-regulation (average, HT 28.69-fold, LT 17.68-fold). The protein expression in brain (average, up 52.67-fold, down 13.54-fold) and gill (average, up 73.02-fold, down 12.92-fold) tissues increased more at HT than at LT. The protein expression in brain (up 3.77-fold, down 4.79-fold) tissues decreased more at LT than at HT, whereas the protein expression in gill (up 8.64-fold, down 4.35-fold) tissues was up-regulated more at LT than at HT. At HT, brain tissues were mainly enriched in pathways related to metabolism and DNA repair; at LT, they were mainly enriched in cancer-related pathways. At both temperatures, gill tissues were mainly enriched in pathways related to cell proliferation, apoptosis, immunity, and inflammation. Additionally, Kyoto Encyclopedia of Genes and Genomes pathway analysis showed more differentially expressed proteins in gill tissues than in brain tissues at HT and LT, and temperature stimulation led to the strengthening of metabolic pathways in both tissues. Of the 96 genes we identified as potentially being highly related to temperature stress (59 from transcriptome and 38 from proteome data), we detected heat shock protein 70 in both the transcriptome and proteome. Our results improved our understanding of the differential relationship between gene expression and protein expression in C. guichenoti. Identifying important temperature stress genes will help lay a foundation for cultivating C. guichenoti, and even other fish species, that are resistant to HT or LT.

Integrated analysis about the effects of heat stress on physiological responses and energy metabolism in Gymnocypris chilianensis.

The temperature of the rivers in the Qilian Mountains, China varies widely from day to night, and Gymnocypris chilianensis living in these rivers may experience a change of 10 °C to 20 °C within a day. To explore the mechanisms underlying G. chilianensis responses to heat stress, we conducted an acute temperature stress experiment. In response to heat stress, levels of antioxidant enzymes (SOD\CAT\MDA) first increased and then decreased with time, but T-AOC levels only decreased. The activities of key glycolytic enzymes HK and PFK in the liver also first increased and then decreased and transaminase (AST/ALT) activity increased significantly. We obtained 5350 significantly different genes through transcriptome sequencing with enrichment pathways including primarily glycine, serine and threonine metabolism, cysteine and methionine metabolism, tryptophan metabolism, fructose and mannose metabolism, steroid hormone biosynthesis, and fatty acid degradation. A total of 457 differential metabolites were identified in the liver under thermal stress, most of which are involved in biochemical pathways of amino acid metabolism. Biosynthesis of amino acids indicated that G. chilianensis maintained physiological homeostasis by enhancing glucose metabolism and regulating lipid and amino acid metabolism pathways under thermal stress. We also randomly selected 12 key response genes for validation using qRT-PCR. This is the first study describing the mechanisms underlying responses to thermal stress in G. chilianensis, and may also provide reference data for the study of environmental mutations in indigenous fish in the Qinghai-Tibet Plateau and Qilian Mountains.

Genetic diversity of two color morphs of Northern snakehead (Channa argus) unveiled by the mitochondrial DNA D-loop region.

To analyze the genetic background of 'white' type Northern snakehead (Channa argus), and provide atheoretical basis for breeding of C. argus, the investigation of genetic diversity and population structure were investigated based on the complete sequences of mitochondrial DNA D-loop region for three cultured 'white' type C. argus populations, and four 'bicolor' type C. argus populations were used to compare with them; 28 mutation loci and 30 haplotypes were found in the D-loop sequence of all individuals with a total length of 907 bp. The highest haplotype diversity (Hd ) and nucleotide diversity (Pi ) in the 'white' type C. argus populations were 0.505 and 0.00057, respectively, which lower than those in the 'bicolor' type C. argus populations (Hd = 0.911, Pi = 0.00326). Population differentiation values (F ST) show that the four 'bicolor' type C. argus populations had obvious genetic differentiation (Fst: 0.21902-0.49428. p < 0.01), but not in the three 'white' type C. argus populations (Fst: -0.00571 to 0.07261. p > 0.05). The phylogenetic tree and Median Joining (MJ) network showed that the genetic distance among 'white' type C. argus populations is very close. Therefore, much attention should be paid to protecting population genetic diversity and avoiding inbreeding in the breeding of 'white' type C. argus.

A machine learning framework for genotyping the structural variations with copy number variant.

BACKGROUND: Genotyping of structural variation is an important computational problem in next generation sequence data analysis. However, in cancer genomes, the copy number variant(CNV) often coexists with other types of structural variations which significantly reduces the accuracy of the existing genotype methods. The bias on sequencing coverage and variant allelic frequency can be observed on a CNV region, which leads to the genotyping approaches that misinterpret the heterozygote as a homozygote. Furthermore, other data signals such as split mapped read, abnormal read will also be misjudged because of the CNV. Therefore, genotyping the structural variations with CNV is a complicated computational problem which should consider multiple features and their interactions. METHODS: Here we proposed a computational method for genotyping indels in the CNV region, which introduced a machine learning framework to comprehensively incorporate a set of data features and their interactions. We extracted fifteen kinds of classification features as input and different from the traditional genotyping problem, here the structure of variant may fall into types of normal homozygote, homozygous variant, heterozygous variant without CNV, heterozygous variant with a CNV on the mutated haplotype, and heterozygous variant with a CNV on the wild haplotype. The Multiclass Relevance Vector Machine (M-RVM) was used as a machine learning framework combined with the distribution characteristics of the features. RESULTS: We applied the proposed method to both simulated and real data, and compared it with the existing popular softwares include Gindel, Facets, GATK, and also compared with other machine learning cores: Support Vector Machine, Lanrange-SVM with OVO multiple classification, Naïve Bayes and BP Neural Network. The results demonstrated that the proposed method outperforms others on accuracy, stability and efficiency. CONCLUSION: This work shows that the genotyping of structural variations on the CNV region cannot be solved as a traditional genotyping problem. More features should be used to efficiently complete the five-category task. According to the result, the proposed method can be a practical algorithm to correct genotype structural variations with CNV on the next generation sequence data. The source codes have been uploaded at https://github.com/TrinaZ/Mixgenotype for academic usage only.