BMC Genomics最新文献

Background: Cryptolaemus montrouzieri (Coccinellidae) is widely utilized as biological control agents in modern agriculture. A comprehensive understanding of its food preference can help guide mass rearing and safety management during field application of pest control. Although some studies have paid attentions to the impacts of prey shift on C. montrouzieri, little is known regarding the role of post-transcriptional regulations in its acclimation to unnatural preys.

Results: We performed a genome-wide investigation on alternative splicing dynamics in C. montrouzieri in response to the predation transition from natural prey to unnatural ones. When feeding on undesired diets, 402-764 genes were differentially alternative spliced in C. montrouzieri. It is noteworthy that the majority of these genes (> 87%) were not differentially expressed, and these differentially spliced genes regulated distinct biological processes from differentially expressed genes, such as organ development and morphogenesis, locomotory behavior, and homeostasis processes. These suggested the functionally nonredendant role of alternative splicing in modulating physiological and metabolic responses of C. montrouzieri to the shift to undesired preys. In addition, the individuals feeding on aphids were subject to a lower level of changes in splicing than other alternative diets, which might be because of the similar chemical and microbial compositions. Our study further suggested a putative coupling of alternative splicing and nonsense-mediated decay (AS-NMD), which may play an important role in fine-tuning the protein repertoire of C. montrouzieri, and promoting its acclimation to predation changes.

Conclusion: These findings highlight the key role of alternative splicing in modulating the acclimation of ladybirds to prey shift and provide new genetic clues for the future application of ladybirds in biocontrol.

Drought stress poses a critical threat to global crop yields and sustainable agriculture. The GASA genes are recognized for their pivotal role in stress tolerance and plant growth, but little is known about how they function in sunflowers. The investigation aimed to identify and elucidate the role of HaGASA genes in conferring sunflowers with drought tolerance. Twenty-seven different HaGASA gene family members were found in this study that were inconsistently located across eleven sunflower chromosomes. Phylogeny analysis revealed that the sunflower HaGASA genes were divided into five subgroups by comparing GASA genes with those from Arabidopsis, peanut, and soybean, with members within each subgroup displaying similar conserved motifs and gene structures. In-silico evaluation of cis-regulatory elements indicated the existence of specific elements associated with stress-responsiveness being the most abundant, followed by hormone, light, and growth-responsive elements. Transcriptomic data from the NCBI database was utilized to assess the HaGASA genes expression profile in different sunflower varieties under drought conditions. The HaGASA genes expression across ten sunflower genotypes under drought stress, revealed 14 differentially expressed HaGASA genes, implying their active role in the plant's stress response. The expression in different organs revealed that HaGASA2, HaGASA11, HaGASA17, HaGASA19, HaGASA21 and HaGASA26 displayed maximum expression in the stem. Our findings implicate HaGASA genes in mediating sunflower growth maintenance and adaptation to abiotic stress, particularly drought. The findings, taken together, provided a basic understanding of the structure and potential functions of HaGASA genes, setting the framework for further functional investigations into their roles in drought stress mitigation and crop improvement strategies.

Background: Archaea and Bacteria are distinct domains of life that are adapted to a variety of ecological niches. Several genome-based methods have been developed for their accurate classification, yet many aspects of the specific genomic features that determine these differences are not fully understood. In this study, we used publicly available whole-genome sequences from bacteria ( $N=2546$ ) and archaea ( $N=109$ ). From these, a set of genomic features (nucleotide frequencies and proportions, coding sequences (CDS), non-coding, ribosomal and transfer RNA genes (ncRNA, rRNA, tRNA), Chargaff's, topological entropy and Shannon's entropy scores) was extracted and used as input data to develop machine learning models for the classification of archaea and bacteria.

Results: The classification accuracy ranged from 0.993 (Random Forest) to 0.998 (Neural Networks). Over the four models, only 11 examples were misclassified, especially those belonging to the minority class (Archaea). From variable importance, tRNA topological and Shannon's entropy, nucleotide frequencies in tRNA, rRNA and ncRNA, CDS, tRNA and rRNA Chargaff's scores have emerged as the top discriminating factors. In particular, tRNA entropy (both topological and Shannon's) was the most important genomic feature for classification, pointing at the complex interactions between the genetic code, tRNAs and the translational machinery.

Conclusions: tRNA, rRNA and ncRNA genes emerged as the key genomic elements that underpin the classification of archaea and bacteria. In particular, higher nucleotide diversity was found in tRNA from bacteria compared to archaea. The analysis of the few classification errors reflects the complex phylogenetic relationships between bacteria, archaea and eukaryotes.

Background: In the domain of forensic science, the application of kinship identification and mixture deconvolution techniques are of critical importance, providing robust scientific evidence for the resolution of complex cases. Microhaplotypes, as the emerging class of genetic markers, have been widely studied in forensics due to their high polymorphisms and excellent stability.

Results and discussion: In this research, a novel and high-efficient panel integrating 33 microhaplotype loci along with a sex-determining locus was developed by the next generation sequencing technology. In addition, we also assessed its forensic utility and delved into its capacity for kinship analysis and mixture deconvolution. The average effective number of alleles (Ae) of the 33 microhaplotype loci in the Guizhou Han population was 6.06, and the Ae values of 30 loci were greater than 5. The cumulative power of discrimination and cumulative power of exclusion values of the novel panel in the Guizhou Han population were 1-5.6 × 10^- 43 and 1-1.6 × 10^- 15, respectively. In the simulated kinship analysis, the panel could effectively distinguish between parent-child, full-sibling, half-sibling, grandfather-grandson, aunt-nephew and unrelated individuals, but uncertainty rates clearly increased when distinguishing between first cousins and unrelated individuals. For the mixtures, the novel panel had demonstrated excellent performance in estimating the number of contributors of mixtures with 1 to 5 contributors in combination with the machine learning methods.

Conclusions: In summary, we have developed a small and high-efficient panel for forensic genetics, which could provide novel insights into forensic complex kinships testing and mixture deconvolution.

Background: Microsatellites are increasingly realized to have biological significance in human genome and health in past decades, the assembled complete reference sequence of human genome T2T-CHM13 brought great help for a comprehensive study of short tandem repeats in the human genome.

Results: Microsatellites density landscapes of all 24 chromosomes were built here for the first complete reference sequence of human genome T2T-CHM13. These landscapes showed that short tandem repeats (STRs) are prone to aggregate characteristically to form a large number of STRs density peaks. We classified 8,823 High Microsatellites Density Peaks (HMDPs), 35,257 Middle Microsatellites Density Peaks (MMDPs) and 199, 649 Low Microsatellites Density Peaks (LMDPs) on the 24 chromosomes; and also classified the motif types of every microsatellites density peak. These STRs density aggregation peaks are mainly composing of a single motif, and AT is the most dominant motif, followed by AATGG and CCATT motifs. And 514 genomic regions were characterized by microsatellite density feature in the full T2T-CHM13 genome.

Conclusions: These landscape maps exhibited that microsatellites aggregate in many genomic positions to form a large number of microsatellite density peaks with composing of mainly single motif type in the complete reference genome, indicating that the local microsatellites density varies enormously along the every chromosome of T2T-CHM13.

Background: The R2R3-MYB transcription factors in plants participate in various physiological and biochemical processes and responds to various external stimuli. Prunus sibirica (known as Siberian apricot) is a drupe tree species that produces extremely high nutritional value kernels. However, it is susceptiblility to frost damage during the flowering period, results in a marked reduction in kernel yield.

Results: In this study, the MYB gene family of P. sibirica (PsMYB) was systematically analyzed, and 116 R2R3-MYB genes that were distributed unevenly over eight chromosomes were ultimately screened. Phylogenetic analysis divided these 116 genes into 30 subgroups. We discovered that 37 PsMYBs had cold stress-responsive promoters, and six PsMYBs were annotated to be associated with cold response. Intraspecific homology analysis identified segmental duplication as the primary gene amplification mechanism, and homology analysis of the PsMYB genes with those of five other species revealed phylogenetic relationships with Rosaceae species. Protein interaction studies revealed collaborative regulation of the PsMYB proteins with Arabidopsis protein, and transcriptome analysis identified PsMYB genes that were highly expressed at low temperatures. Additionally, the expression levels of 22 PsMYBs in different tissue parts of P. sibirica and under different low-temperature stress conditions were evaluated using quantitative real-time PCR, with the results verifying that PsMYBs are specifically expressed in different plant parts and may be involved in the growth and development of P. sibirica species. Genes upregulated after exposure to low-temperature stress and likely involved in cold response were identified.

Conclusion: This study lays a foundation for understanding the molecular biology of PsMYBs in P. sibirica and provides a theoretical basis for the future study of transgenic lines with cold resistance during the flowering period of this tree.

Background: Assembly of metagenomic samples can provide essential information about the mobility potential and taxonomic origin of antibiotic resistance genes (ARGs) and inform interventions to prevent further spread of resistant bacteria. However, similar to other conserved regions, such as ribosomal RNA genes and mobile genetic elements, almost identical ARGs typically occur in multiple genomic contexts across different species, representing a considerable challenge for the assembly process. Usually, this results in many fragmented contigs of unclear origin, complicating the risk assessment of ARG detections. To systematically investigate the impact of this issue on detection, quantification and contextualization of ARGs, we evaluated the performance of different assembly approaches, including genomic-, metagenomic- and transcriptomic-specialized assemblers. We quantified recovery and accuracy rates of each tool for ARGs both from in silico spiked metagenomic samples as well as real samples sequenced using both long- and short-read sequencing technologies.

Results: The results revealed that none of the investigated tools can accurately capture genomic contexts present in samples of high complexity. The transcriptomic assembler Trinity showed a better performance in terms of reconstructing longer and fewer contigs matching unique genomic contexts, which can be beneficial for deciphering the taxonomic origin of ARGs. The currently commonly used metagenomic assembly tools metaSPAdes and MEGAHIT were able to identify the ARG repertoire but failed to fully recover the diversity of genomic contexts present in a sample. On top of that, in a complex scenario MEGAHIT produced very short contigs, which can lead to considerable underestimation of the resistome in a given sample.

Conclusions: Our study shows that metaSPAdes and Trinity would be the preferable tools in terms of accuracy to recover correct genomic contexts around ARGs in metagenomic samples characterized by uneven coverages. Overall, the inability of assemblers to reconstruct long ARG-containing contigs has impacts on ARG quantification, suggesting that directly mapping reads to an ARG database should be performed as a complementary strategy to get accurate ARG abundance and diversity measures.

Background: Austroasiatic (AA)-speaking populations in northern Thailand are of significant interest due to their status as indigenous descendants and their location at the crossroads of AA prehistoric distribution across Southern China, the Indian Subcontinent, and Mainland Southeast Asia. However, the complexity of ethnic identification can result in inaccuracies regarding the origin and migration history of these populations. To address this, we have conducted a genome-wide SNP analysis of 89 individuals from two Lavue and three Lwa-endonym populations. We then combined our outcomes with previously published data to elucidate the genetic diversity and clustering of AA groups in northern Thailand.

Results: Our findings align with existing linguistic classifications, revealing different genetic compositions among the three branches of the Mon-Khmer subfamily within the AA family: Monic, Khmuic, and Palaungic. Although the term "Lua" ethnicity is confusingly used to identify ethnic groups belonging to both Khmuic and Palaungic branches, our genomic data indicate that the Khmuic-speaking Lua living on the eastern side of the region are relatively distant from the Palaungic-speaking Lavue and Lwa populations living on the western side. The Lavue populations, primarily inhabiting mountainous areas, exhibit a genetic makeup unique to the AA family, with a close genetic relationship to the Karenic subgroup of the Sino-Tibetan language family. Conversely, the Lwa and Blang populations, residing in lowland river valleys, display genetic signatures resulting from admixture with Tai-Kadai-speaking ethnic groups.

Conclusion: Utilizing genome-wide SNP markers, our findings indicate genetic heterogeneity among the Lua, Lavue, and Lwa ethnic groups. The intricate interplay of genetics, cultural heritage, and historical influences has shaped these ethnic communities. Our study underscores the importance of accurate ethnic classifications, emphasizing the use of self-identified endonyms, names created and used by the ethnic groups themselves. This approach respects the AA communities in northern Thailand and acknowledges their significant contributions to advancing our understanding of genetic anthropology.

Background: Transcription factors (TFs) bind to different parts of the genome in different types of cells, but it is usually assumed that the inherent DNA-binding preferences of a TF are invariant to cell type. Yet, there are several known examples of TFs that switch their DNA-binding preferences in different cell types, and yet more examples of other mechanisms, such as steric hindrance or cooperative binding, that may result in a "DNA signature" of differential binding.

Results: To survey this phenomenon systematically, we developed a deep learning method we call SigTFB (Signatures of TF Binding) to detect and quantify cell-type specificity in a TF's known genomic binding sites. We used ENCODE ChIP-seq data to conduct a wide scale investigation of 169 distinct TFs in up to 14 distinct cell types. SigTFB detected statistically significant DNA binding signatures in approximately two-thirds of TFs, far more than might have been expected from the relatively sparse evidence in prior literature. We found that the presence or absence of a cell-type specific DNA binding signature is distinct from, and indeed largely uncorrelated to, the degree of overlap between ChIP-seq peaks in different cell types, and tended to arise by two mechanisms: using established motifs in different frequencies, and by selective inclusion of motifs for distint TFs.

Conclusions: While recent results have highlighted cell state features such as chromatin accessibility and gene expression in predicting TF binding, our results emphasize that, for some TFs, the DNA sequences of the binding sites contain substantial cell-type specific motifs.

Background: MYB transcription factors regulate anthocyanin biosynthesis across numerous plant species. However, comprehensive genome-wide investigations regarding the R2R3-MYB gene family and its involvement in regulating anthocyanin biosynthesis in the red and white fruit color morphs of Fragaria pentaphylla remain scarce.

Results: A total of 101 FpR2R3-MYB genes were identified from the F. pentaphylla genome and were divided into 34 subgroups based on phylogenetic analysis. Gene structure (exon/intron) and protein motifs were particularly conserved among the FpR2R3-MYB genes, especially members within the same subgroup. The FpR2R3-MYB genes were distributed over seven F. pentaphylla chromosomes. Analysis of gene duplication events revealed five pairs of tandem duplication genes and 16 pairs of segmental duplication genes, suggesting that segmental duplications are the major pattern for expansion of the FpR2R3-MYB gene family expansion in F. pentaphylla. Cis-regulatory elements of the FpR2R3-MYB promoters were involved in cellular development, phytohormones, environmental stress and photoresponse. Based on the analysis of the FpR2R3-MYB gene family and transcriptome sequencing (RNA-seq) data, FpMYB9 was identified as a key transcription factor involved in the regulation of anthocyanin synthesis in F. pentaphylla fruits. The expression of FpMYB9 increases significantly during the ripening stage of red fruits, as confirmed by reverse transcription quantitative real-time PCR. In addition, subcellular localization experiments further confirmed the nuclear presence of FpMYB9, supporting its role as a transcription factor involved in anthocyanin biosynthesis.

Conclusion: Our results showed that the FpR2R3-MYB genes are highly conserved and play important roles in the anthocyanin biosynthesis in F. pentaphylla fruits. Our results also provide a compelling basis for further understanding of the regulatory mechanism underlying the role of FpMYB9 in anthocyanin formation in F. pentaphylla fruits.