Project description:Lingxian white goose (LXW) is a goose breed indigenous to China that is famous for its meat quality and fast growth. However, the genomic evidence underlying such excellent breeding characteristics remains poorly understood. Therefore, we performed whole-genome resequencing of 141 geese from 3 indigenous breeds to scan for selection signatures and detect genomic regions related to breed features of LXW. We identified 5 reproduction-related genes (SYNE1, ESR1, NRIP1, CCDC170, and ARMT1) in highly differentiated regions and 11 notable genes in 26 overlapping windows, some of which are responsible for meat quality (DHX15), growth traits (LDB2, SLIT2, and RBPJ), reproduction (KCNIP4), and unique immunity traits (DHX15 and SLIT2). These findings provide insights into the genetic characteristics of LXW and identify genes affecting important traits in LXW, which extends the genetic resources and basis for facilitating genetic improvement in domestic geese breeds.
Project description:BackgroundColorectal cancer (CRC) is a prevalent malignancy with diverse molecular characteristics. The NGS-based approach enhances our comprehension of genomic landscape of CRC and may guide future advancements in precision oncology for CRC patients.MethodIn this research, we conducted an analysis using Next-Generation Sequencing (NGS) on samples collected from 111 individuals who had been diagnosed with CRC. We identified somatic and germline mutations and structural variants across the tumor genomes through comprehensive genomic profiling. Furthermore, we investigated the landscape of driver mutations and their potential clinical implications.ResultsOur findings underscore the intricate heterogeneity of genetic alterations within CRC. Notably, BRAF, ARID2, KMT2C, and GNAQ were associated with CRC prognosis. Patients harboring BRAF, ARID2, or KMT2C mutations exhibited shorter progression-free survival (PFS), whereas those with BRAF, ARID2, or GNAQ mutations experienced worse overall survival (OS). We unveiled 80 co-occurring and three mutually exclusive significant gene pairs, enriched primarily in pathways such as TP53, HIPPO, RTK/RAS, NOTCH, WNT, TGF-Beta, MYC, and PI3K. Notably, co-mutations of BRAF/ALK, BRAF/NOTCH2, BRAF/CREBBP, and BRAF/FAT1 correlated with worse PFS. Furthermore, germline AR mutations were identified in 37 (33.33%) CRC patients, and carriers of these variants displayed diminished PFS and OS. Decreased AR protein expression was observed in cases with AR germline mutations. A four-gene mutation signature was established, incorporating the aforementioned prognostic genes, which emerged as an independent prognostic determinant in CRC via univariate and multivariate Cox regression analyses. Noteworthy BRAF and ARID2 protein expression decreases detected in patients with their respective mutations.ConclusionThe integration of our analyses furnishes crucial insights into CRC's molecular characteristics, drug responsiveness, and the construction of a four-gene mutation signature for predicting CRC prognosis.
Project description:Samples of 191 animals from 18 different Brazilian locally adapted swine genetic groups were genotyped using Illumina Porcine SNP60 BeadChip in order to identify selection signatures related to the monthly variation of Brazilian environmental variables. Using BayeScan software, 71 SNP markers were identified as FST outliers and 60 genotypes (58 markers) were found by Samβada software in 371 logistic models correlated with 112 environmental variables. Five markers were identified in both methods, with a Kappa value of 0.073 (95% CI: 0.011-0.134). The frequency of these markers indicated a clear north-south country division that reflects Brazilian environmental differences in temperature, solar radiation, and precipitation. Global spatial territory correlation for environmental variables corroborates this finding (average Moran's I = 0.89, range from 0.55 to 0.97). The distribution of alleles over the territory was not strongly correlated with the breed/genetic groups. These results are congruent with previous mtDNA studies and should be used to direct germplasm collection for the National gene bank.
Project description:Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in silico mutational scanning for all possible single mutations, along with 2 μs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. In sum, our findings highlight the potential of MuMi as a reliable and computationally efficient tool for predicting protein fitness landscapes, offering significant advantages over traditional methods. The methodologies and results presented in this study pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.
Project description:Several studies have uncovered a highly heterogeneous landscape of genetic differentiation across the genomes of closely related species. Specifically, genetic differentiation is often concentrated in particular genomic regions ("islands of differentiation") that might contain barrier loci contributing to reproductive isolation, whereas the rest of the genome is homogenized by introgression. Alternatively, linked selection can produce differentiation islands in allopatry without introgression. We explored the influence of introgression on the landscape of genetic differentiation in two hybridizing goose taxa: the Taiga Bean Goose (Anser fabalis) and the Tundra Bean Goose (A. serrirostris). We re-sequenced the whole genomes of 18 individuals (9 of each taxon) and, using a combination of population genomic summary statistics and demographic modeling, we reconstructed the evolutionary history of these birds. Next, we quantified the impact of introgression on the build-up and maintenance of genetic differentiation. We found evidence for a scenario of allopatric divergence (about 2.5 million years ago) followed by recent secondary contact (about 60,000 years ago). Subsequent introgression events led to high levels of gene flow, mainly from the Tundra Bean Goose into the Taiga Bean Goose. This scenario resulted in a largely undifferentiated genomic landscape (genome-wide FST = 0.033) with a few notable differentiation peaks that were scattered across chromosomes. The summary statistics indicated that some peaks might contain barrier loci while others arose in allopatry through linked selection. Finally, based on the low genetic differentiation, considerable morphological variation and incomplete reproductive isolation, we argue that the Taiga and the Tundra Bean Goose should be treated as subspecies.
Project description:Understanding plant-microbe interactions with the possibility to modulate the plant's microbiome is essential to design new strategies for a more productive and sustainable agriculture and to maintain natural ecosystems. Therefore, a key question is how to design bacterial consortia that will yield the desired host phenotype. This work was designed to identify the potential genomic features involved in the interaction between Micromonospora and known host plants. Seventy-four Micromonospora genomes representing diverse environments were used to generate a database of all potentially plant-related genes using a novel bioinformatic pipeline that combined screening for microbial-plant related features and comparison with available plant host proteomes. The strains were recovered in three clusters, highly correlated with several environments: plant-associated, soil/rhizosphere, and marine/mangrove. Irrespective of their isolation source, most strains shared genes coding for commonly screened plant growth promotion features, while differences in plant colonization related traits were observed. When Arabidopsis thaliana plants were inoculated with representative Micromonospora strains selected from the three environments, significant differences were in found in the corresponding plant phenotypes. Our results indicate that the identified genomic signatures help select those strains with the highest probability to successfully colonize the plant and contribute to its wellbeing. These results also suggest that plant growth promotion markers alone are not good indicators for the selection of beneficial bacteria to improve crop production and the recovery of ecosystems.
Project description:The classification of genetic variants represents a major challenge in the post-genome era by virtue of their extraordinary number and the complexities associated with ascribing a clinical impact, especially for disorders exhibiting exceptional phenotypic, genetic, and allelic heterogeneity. To address this challenge for hearing loss, we have developed the Deafness Variation Database (DVD), a comprehensive, open-access resource that integrates all available genetic, genomic, and clinical data together with expert curation to generate a single classification for each variant in 152 genes implicated in syndromic and non-syndromic deafness. We evaluate 876,139 variants and classify them as pathogenic or likely pathogenic (more than 8,100 variants), benign or likely benign (more than 172,000 variants), or of uncertain significance (more than 695,000 variants); 1,270 variants are re-categorized based on expert curation and in 300 instances, the change is of medical significance and impacts clinical care. We show that more than 96% of coding variants are rare and novel and that pathogenicity is driven by minor allele frequency thresholds, variant effect, and protein domain. The mutational landscape we define shows complex gene-specific variability, making an understanding of these nuances foundational for improved accuracy in variant interpretation in order to enhance clinical decision making and improve our understanding of deafness biology.
Project description:Pediatric bithalamic gliomas encompass several histomolecular tumoral types from benign to malignant and underlines the central role of a comprehensive neuropathological review, including immunohistochemistry, genetic, and epigenetic analyses, to achieve an accurate diagnosis.
Project description:Mitochondrial (MT) dysfunction is a hallmark of aging and has been associated with most aging-related diseases as well as immunological processes. However, little is known about aging, lifestyle and genetic factors influencing mitochondrial DNA (mtDNA) abundance. In this study, mtDNA abundance was estimated from the weighted intensities of probes mapping to the MT genome in 295,150 participants from the UK Biobank. We found that the abundance of mtDNA was significantly elevated in women compared to men, was negatively correlated with advanced age, higher smoking exposure, greater body-mass index, higher frailty index as well as elevated red and white blood cell count and lower mortality. In addition, several biochemistry markers in blood-related to cholesterol metabolism, ion homeostasis and kidney function were found to be significantly associated with mtDNA abundance. By performing a genome-wide association study, we identified 50 independent regions genome-wide significantly associated with mtDNA abundance which harbour multiple genes involved in the immune system, cancer as well as mitochondrial function. Using mixed effects models, we estimated the SNP-heritability of mtDNA abundance to be around 8%. To investigate the consequence of altered mtDNA abundance, we performed a phenome-wide association study and found that mtDNA abundance is involved in risk for leukaemia, hematologic diseases as well as hypertension. Thus, estimating mtDNA abundance from genotyping arrays has the potential to provide novel insights into age- and disease-relevant processes, particularly those related to immunity and established mitochondrial functions.
Project description:IntroductionCultivated peanut (Arachis hypogaea L.) is an important oil crop for human nutrition and is cultivated in >100 countries. However, the present knowledge of its genomic diversity, evolution, and loci related to the seed traits is limited.ObjectivesOur study intended to (1) uncover the population structure and the demographic history of peanuts, (2) identify signatures of selection that occurred during peanut improvement breeding, and (3) detect and verify the functions of candidate genes associated with seed traits.MethodsWe explored the population relationship and the evolution of peanuts using a largescale single nucleotide polymorphism dataset generated from the genome-wide resequencing of 203 cultivated peanuts. Genetic diversity and genomic scan analyses were applied to identify selective loci for genomic-selection breeding. Genome-wide association studies, transgenic experiments, and RNA-seq were employed to identify the candidate genes associated with seed traits.ResultsOur study revealed that the 203 resequenced accessions were divided into four genetic groups, consistent with their botanical classification. Moreover, the var. peruviana and var. fastigiata subpopulations have diverged to a greater extent than the others, and var. peruviana may be the earliest variant in the evolution from tetraploid ancestors. A recent dramatic expansion in the effective population size of the cultivated peanuts ca. 300-500 years ago was also noted. Selective sweeps underlying quantitative trait loci and genes of seed size, plant architecture, and disease resistance coincide with the major goals of improved peanut breeding compared with the landrace and cultivar populations. Genome-wide association testing with functional analysis led to the identification of two genes involved in seed weight and seed length regulation.ConclusionOur study provides valuable information for understanding the genomic diversity and the evolution of peanuts and serves as a genomic basis for improving peanut cultivars.