Genomes of historical specimens reveal multiple invasions of LTR retrotransposons in Drosophila melanogaster during the 19th century.

Transposable element invasions have a profound impact on the evolution of genomes and phenotypes. It is thus an important open question how often such TE invasions occur. To address this question, we utilize the genomes of historical specimens, sampled about 200 y ago. We found that the LTR retrotransposons Blood, Opus, and 412 spread in Drosophila melanogaster in the 19th century. These invasions constitute second waves, as degraded fragments were found for all three TEs. The composition of Opus and 412, but not of Blood, shows a pronounced geographic heterogeneity, likely due to founder effects during the invasions. Finally, we identified species from the Drosophila simulans complex as the likely origin of the TEs. We show that in total, seven TE families invaded D. melanogaster during the last 200y, thereby increasing the genome size by up to 1.2Mbp. We suggest that this high rate of TE invasions was likely triggered by human activity. Based on the analysis of strains and specimens sampled at different times, we provide a detailed timeline of TE invasions, making D. melanogaster the first organism where the invasion history of TEs during the last two centuries could be inferred.

Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds. / å¤§è§„æ¨¡å ¨åŸºå› ç»„SNPåˆ†æžæ­ç¤ºäº†é¸¡å“ç§çš„å ¨çƒç¥–å ˆã€ç§ç¾¤å‘å±•å’Œç§ç¾¤åŽ†å²çš„å¤æ‚(å’Œå¤šæ ·)çš„é—ä¼ å›¾è°±.

The worldwide chicken gene pool encompasses a remarkable, but shrinking, number of divergently selected breeds of diverse origin. This study was a large-scale genome-wide analysis of the landscape of the complex molecular architecture, genetic variability, and detailed structure among 49 populations. These populations represent a significant sample of the world's chicken breeds from Europe (Russia, Czech Republic, France, Spain, UK, etc.), Asia (China), North America (USA), and Oceania (Australia). Based on the results of breed genotyping using the Illumina 60K single nucleotide polymorphism (SNP) chip, a bioinformatic analysis was carried out. This included the calculation of heterozygosity/homozygosity statistics, inbreeding coefficients, and effective population size. It also included assessment of linkage disequilibrium and construction of phylogenetic trees. Using multidimensional scaling, principal component analysis, and ADMIXTURE-assisted global ancestry analysis, we explored the genetic structure of populations and subpopulations in each breed. An overall 49-population phylogeny analysis was also performed, and a refined evolutionary model of chicken breed formation was proposed, which included egg, meat, dual-purpose types, and ambiguous breeds. Such a large-scale survey of genetic resources in poultry farming using modern genomic methods is of great interest both from the viewpoint of a general understanding of the genetics of the domestic chicken and for the further development of genomic technologies and approaches in poultry breeding. In general, whole genome SNP genotyping of promising chicken breeds from the worldwide gene pool will promote the further development of modern genomic science as applied to poultry.

A region of suppressed recombination misleads neoavian phylogenomics.

Genomes are typically mosaics of regions with different evolutionary histories. When speciation events are closely spaced in time, recombination makes the regions sharing the same history small, and the evolutionary history changes rapidly as we move along the genome. When examining rapid radiations such as the early diversification of Neoaves 66 Mya, typically no consistent history is observed across segments exceeding kilobases of the genome. Here, we report an exception. We found that a 21-Mb region in avian genomes, mapped to chicken chromosome 4, shows an extremely strong and discordance-free signal for a history different from that of the inferred species tree. Such a strong discordance-free signal, indicative of suppressed recombination across many millions of base pairs, is not observed elsewhere in the genome for any deep avian relationships. Although long regions with suppressed recombination have been documented in recently diverged species, our results pertain to relationships dating circa 65 Mya. We provide evidence that this strong signal may be due to an ancient rearrangement that blocked recombination and remained polymorphic for several million years prior to fixation. We show that the presence of this region has misled previous phylogenomic efforts with lower taxon sampling, showing the interplay between taxon and locus sampling. We predict that similar ancient rearrangements may confound phylogenetic analyses in other clades, pointing to a need for new analytical models that incorporate the possibility of such events.

DPPA3 facilitates genome-wide DNA demethylation in mouse primordial germ cells.

BACKGROUND: Genome-wide DNA demethylation occurs in mammalian primordial germ cells (PGCs) as part of the epigenetic reprogramming important for gametogenesis and resetting the epigenetic information for totipotency. Dppa3 (also known as Stella or Pgc7) is highly expressed in mouse PGCs and oocytes and encodes a factor essential for female fertility. It prevents excessive DNA methylation in oocytes and ensures proper gene expression in preimplantation embryos: however, its role in PGCs is largely unexplored. In the present study, we investigated whether or not DPPA3 has an impact on CG methylation/demethylation in mouse PGCs. RESULTS: We show that DPPA3 plays a role in genome-wide demethylation in PGCs even before sex differentiation. Dppa3 knockout female PGCs show aberrant hypermethylation, most predominantly at H3K9me3-marked retrotransposons, which persists up to the fully-grown oocyte stage. DPPA3 works downstream of PRDM14, a master regulator of epigenetic reprogramming in embryonic stem cells and PGCs, and independently of TET1, an enzyme that hydroxylates 5-methylcytosine. CONCLUSIONS: The results suggest that DPPA3 facilitates DNA demethylation through a replication-coupled passive mechanism in PGCs. Our study identifies DPPA3 as a novel epigenetic reprogramming factor in mouse PGCs.

Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections.

Minimal Cut Sets (MCSs) identify sets of reactions which, when removed from a metabolic network, disable certain cellular functions. The traditional search for MCSs within genome-scale metabolic models (GSMMs) targets cellular growth, identifies reaction sets resulting in a lethal phenotype if disrupted, and retrieves a list of corresponding gene, mRNA, or enzyme targets. Using the dual link between MCSs and Elementary Flux Modes (EFMs), our logic programming-based tool aspefm was able to compute MCSs of any size from GSMMs in acceptable run times. The tool demonstrated better performance when computing large-sized MCSs than the mixed-integer linear programming methods. We applied the new MCSs methodology to a medically-relevant consortium model of two cross-feeding bacteria, Staphylococcus aureus and Pseudomonas aeruginosa. aspefm constraints were used to bias the computation of MCSs toward exchanged metabolites that could complement lethal phenotypes in individual species. We found that interspecies metabolite exchanges could play an essential role in rescuing single-species growth, for instance inosine could complement lethal reaction knock-outs in the purine synthesis, glycolysis, and pentose phosphate pathways of both bacteria. Finally, MCSs were used to derive a list of promising enzyme targets for consortium-level therapeutic applications that cannot be circumvented via interspecies metabolite exchange.

Whole-genome resequencing of Chinese indigenous sheep provides insight into the genetic basis underlying climate adaptation.

BACKGROUND: Chinese indigenous sheep are valuable resources with unique features and characteristics. They are distributed across regions with different climates in mainland China; however, few reports have analyzed the environmental adaptability of sheep based on their genome. We examined the variants and signatures of selection involved in adaptation to extreme humidity, altitude, and temperature conditions in 173 sheep genomes from 41 phenotypically and geographically representative Chinese indigenous sheep breeds to characterize the genetic basis underlying environmental adaptation in these populations. RESULTS: Based on the analysis of population structure, we inferred that Chinese indigenous sheep are divided into four groups: Kazakh (KAZ), Mongolian (MON), Tibetan (TIB), and Yunnan (YUN). We also detected a set of candidate genes that are relevant to adaptation to extreme environmental conditions, such as drought-prone regions (TBXT, TG, and HOXA1), high-altitude regions (DYSF, EPAS1, JAZF1, PDGFD, and NF1) and warm-temperature regions (TSHR, ABCD4, and TEX11). Among all these candidate genes, eight ABCD4, CNTN4, DOCK10, LOC105608545, LOC121816479, SEM3A, SVIL, and TSHR overlap between extreme environmental conditions. The TSHR gene shows a strong signature for positive selection in the warm-temperature group and harbors a single nucleotide polymorphism (SNP) missense mutation located between positions 90,600,001 and 90,650,001 on chromosome 7, which leads to a change in the protein structure of TSHR and influences its stability. CONCLUSIONS: Analysis of the signatures of selection uncovered genes that are likely related to environmental adaptation and a SNP missense mutation in the TSHR gene that affects the protein structure and stability. It also provides information on the evolution of the phylogeographic structure of Chinese indigenous sheep populations. These results provide important genetic resources for future breeding studies and new perspectives on how animals can adapt to climate change.

The PTM profiling of CTCF reveals the regulation of 3D chromatin structure by O-GlcNAcylation.

CCCTC-binding factor (CTCF), a ubiquitously expressed and highly conserved protein, is known to play a critical role in chromatin structure. Post-translational modifications (PTMs) diversify the functions of protein to regulate numerous cellular processes. However, the effects of PTMs on the genome-wide binding of CTCF and the organization of three-dimensional (3D) chromatin structure have not been fully understood. In this study, we uncovered the PTM profiling of CTCF and demonstrated that CTCF can be O-GlcNAcylated and arginine methylated. Functionally, we demonstrated that O-GlcNAcylation inhibits CTCF binding to chromatin. Meanwhile, deficiency of CTCF O-GlcNAcylation results in the disruption of loop domains and the alteration of chromatin loops associated with cellular development. Furthermore, the deficiency of CTCF O-GlcNAcylation increases the expression of developmental genes and negatively regulates maintenance and establishment of stem cell pluripotency. In conclusion, these results provide key insights into the role of PTMs for the 3D chromatin structure.

Detection and classification of the integrative conjugative elements of Lactococcus lactis.

Lactococcus lactis is widely applied by the dairy industry for the fermentation of milk into products such as cheese. Adaptation of L. lactis to the dairy environment often depends on functions encoded by mobile genetic elements (MGEs) such as plasmids. Other L. lactis MGEs that contribute to industrially relevant traits like antimicrobial production and carbohydrate utilization capacities belong to the integrative conjugative elements (ICE). Here we investigate the prevalence of ICEs in L. lactis using an automated search engine that detects colocalized, ICE-associated core-functions (involved in conjugation or mobilization) in lactococcal genomes. This approach enabled the detection of 36 candidate-ICEs in 69 L. lactis genomes. By phylogenetic analysis of conserved protein functions encoded in all lactococcal ICEs, these 36 ICEs could be classified in three main ICE-families that encompass 7 distinguishable ICE-integrases and are characterized by apparent modular-exchangeability and plasticity. Finally, we demonstrate that phylogenetic analysis of the conjugation-associated VirB4 ATPase function differentiates ICE- and plasmid-derived conjugation systems, indicating that conjugal transfer of lactococcal ICEs and plasmids involves genetically distinct machineries. Our genomic analysis and sequence-based classification of lactococcal ICEs creates a comprehensive overview of the conserved functional repertoires encoded by this family of MGEs in L. lactis, which can facilitate the future exploitation of the functional traits they encode by ICE mobilization to appropriate starter culture strains.

Accuracy of Genomic prediction for fleece traits in Inner Mongolia Cashmere goats.

The fleece traits are important economic traits of goats. With the reduction of sequencing and genotyping cost and the improvement of related technologies, genomic selection for goats has become possible. The research collect pedigree, phenotype and genotype information of 2299 Inner Mongolia Cashmere goats (IMCGs) individuals. We estimate fixed effects, and compare the estimates of variance components, heritability and genomic predictive ability of fleece traits in IMCGs when using the pedigree based Best Linear Unbiased Prediction (ABLUP), Genomic BLUP (GBLUP) or single-step GBLUP (ssGBLUP). The fleece traits considered are cashmere production (CP), cashmere diameter (CD), cashmere length (CL) and fiber length (FL). It was found that year of production, sex, herd and individual ages had highly significant effects on the four fleece traits (P < 0.01). All of these factors should be considered when the genetic parameters of fleece traits in IMCGs are evaluated. The heritabilities of FL, CL, CP and CD with ABLUP, GBLUP and ssGBLUP methods were 0.26 ~ 0.31, 0.05 ~ 0.08, 0.15 ~ 0.20 and 0.22 ~ 0.28, respectively. Therefore, it can be inferred that the genetic progress of CL is relatively slow. The predictive ability of fleece traits in IMCGs with GBLUP (56.18% to 69.06%) and ssGBLUP methods (66.82% to 73.70%) was significantly higher than that of ABLUP (36.73% to 41.25%). For the ssGBLUP method is significantly (29% ~ 33%) higher than that with ABLUP, and which is slightly (4% ~ 14%) higher than that of GBLUP. The ssGBLUP will be as an superiors method for using genomic selection of fleece traits in Inner Mongolia Cashmere goats.

Genomic evidence for human-mediated introgressive hybridization and selection in the developed breed.

BACKGROUND: The pig (Sus Scrofa) is one of the oldest domesticated livestock species that has undergone extensive improvement through modern breeding. European breeds have advantages in lean meat development and highly-productive body type, whereas Asian breeds possess extraordinary fat deposition and reproductive performance. Consequently, Eurasian breeds have been extensively used to develop modern commercial breeds for fast-growing and high prolificacy. However, limited by the sequencing technology, the genome architecture of some nascent developed breeds and the human-mediated impact on their genomes are still unknown. RESULTS: Through whole-genome analysis of 178 individuals from an Asian locally developed pig breed, Beijing Black pig, and its two ancestors from two different continents, we found the pervasive inconsistent gene trees and species trees across the genome of Beijing Black pig, which suggests its introgressive hybrid origin. Interestingly, we discovered that this developed breed has more genetic relationships with European pigs and an unexpected introgression from Asian pigs to this breed, which indicated that human-mediated introgression could form the porcine genome architecture in a completely different type compared to native introgression. We identified 554 genomic regions occupied 63.30 Mb with signals of introgression from the Asian ancestry to Beijing Black pig, and the genes in these regions enriched in pathways associated with meat quality, fertility, and disease-resistant. Additionally, a proportion of 7.77% of genomic regions were recognized as regions that have been under selection. Moreover, combined with the results of a genome-wide association study for meat quality traits in the 1537 Beijing Black pig population, two important candidate genes related to meat quality traits were identified. DNAJC6 is related to intramuscular fat content and fat deposition, and RUFY4 is related to meat pH and tenderness. CONCLUSIONS: Our research provides insight for analyzing the origins of nascent developed breeds and genome-wide selection remaining in the developed breeds mediated by humans during modern breeding.

Conserved switch genes that arose via whole-genome duplication regulate a cannibalistic nematode morph.

Experimental genetics in a nematode reveals a key role for developmental plasticity in the evolution of nutritional diversity.

The scales, mechanisms, and dynamics of the genome architecture.

Even when split into several chromosomes, DNA molecules that make up our genome are too long to fit into the cell nuclei unless massively folded. Such folding must accommodate the need for timely access to selected parts of the genome by transcription factors, RNA polymerases, and DNA replication machinery. Here, we review our current understanding of the genome folding inside the interphase nuclei. We consider the resulting genome architecture at three scales with a particular focus on the intermediate (meso) scale and summarize the insights gained from recent experimental observations and diverse computational models.

Genetic conflicts in budding yeast: The 2µ plasmid as a model selfish element.

Antagonistic coevolution, arising from genetic conflict, can drive rapid evolution and biological innovation. Conflict can arise both between organisms and within genomes. This review focuses on budding yeasts as a model system for exploring intra- and inter-genomic genetic conflict, highlighting in particular the 2-micron (2µ) plasmid as a model selfish element. The 2µ is found widely in laboratory strains and industrial isolates of Saccharomyces cerevisiae and has long been known to cause host fitness defects. Nevertheless, the plasmid is frequently ignored in the context of genetic, fitness, and evolution studies. Here, I make a case for further exploring the evolutionary impact of the 2µ plasmid as well as other selfish elements of budding yeasts, discuss recent advances, and, finally, future directions for the field.

BEERS2: RNA-Seq simulation through high fidelity in silico modeling.

Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully length messenger RNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in polymerase chain reaction (PCR) amplification, barcode read errors and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.

TIP aquaporins in Cyperus esculentus: genome-wide identification, expression profiles, subcellular localizations, and interaction patterns.

BACKGROUND: Tonoplast intrinsic proteins (TIPs), which typically mediate water transport across vacuolar membranes, play an essential role in plant growth, development, and stress responses. However, their characterization in tigernut (Cyperus esculentus L.), an oil-bearing tuber plant of the Cyperaceae family, is still in the infancy. RESULTS: In this study, a first genome-wide characterization of the TIP subfamily was conducted in tigernut, resulting in ten members representing five previously defined phylogenetic groups, i.e., TIP1-5. Although the gene amounts are equal to that present in two model plants Arabidopsis and rice, the group composition and/or evolution pattern were shown to be different. Except for CeTIP1;3 that has no counterpart in both Arabidopsis and rice, complex orthologous relationships of 1:1, 1:2, 1:3, 2:1, and 2:2 were observed. Expansion of the CeTIP subfamily was contributed by whole-genome duplication (WGD), transposed, and dispersed duplications. In contrast to the recent WGD-derivation of CeTIP3;1/-3;2, synteny analyses indicated that TIP4 and - 5 are old WGD repeats of TIP2, appearing sometime before monocot-eudicot divergence. Expression analysis revealed that CeTIP genes exhibit diverse expression profiles and are subjected to developmental and diurnal fluctuation regulation. Moreover, when transiently overexpressed in tobacco leaves, CeTIP1;1 was shown to locate in the vacuolar membrane and function in homo/heteromultimer, whereas CeTIP2;1 is located in the cell membrane and only function in heteromultimer. Interestingly, CeTIP1;1 could mediate the tonoplast-localization of CeTIP2;1 via protein interaction, implying complex regulatory patterns. CONCLUSIONS: Our findings provide a global view of CeTIP genes, which provide valuable information for further functional analysis and genetic improvement through manipulating key members in tigernut.

TMBstable: a variant caller controls performance variation across heterogeneous sequencing samples.

In cancer genomics, variant calling has advanced, but traditional mean accuracy evaluations are inadequate for biomarkers like tumor mutation burden, which vary significantly across samples, affecting immunotherapy patient selection and threshold settings. In this study, we introduce TMBstable, an innovative method that dynamically selects optimal variant calling strategies for specific genomic regions using a meta-learning framework, distinguishing it from traditional callers with uniform sample-wide strategies. The process begins with segmenting the sample into windows and extracting meta-features for clustering, followed by using a pre-trained meta-model to select suitable algorithms for each cluster, thereby addressing strategy-sample mismatches, reducing performance fluctuations and ensuring consistent performance across various samples. We evaluated TMBstable using both simulated and real non-small cell lung cancer and nasopharyngeal carcinoma samples, comparing it with advanced callers. The assessment, focusing on stability measures, such as the variance and coefficient of variation in false positive rate, false negative rate, precision and recall, involved 300 simulated and 106 real tumor samples. Benchmark results showed TMBstable's superior stability with the lowest variance and coefficient of variation across performance metrics, highlighting its effectiveness in analyzing the counting-based biomarker. The TMBstable algorithm can be accessed at https://github.com/hello-json/TMBstable for academic usage only.

Development and applications of genome-scale metabolic network models.

The genome-scale metabolic network model is an effective tool for characterizing the gene-protein-response relationship in the entire metabolic pathway of an organism. By combining various algorithms, the genome-scale metabolic network model can effectively simulate the influence of a specific environment on the physiological state of cells, optimize the culture conditions of strains, and predict the targets of genetic modification to achieve targeted modification of strains. In this review, we summarize the whole process of model building, sort out the various tools that may be involved in the model building process, and explain the role of various algorithms in model analysis. In addition, we also summarized the application of GSMM in network characteristics, cell phenotypes, metabolic engineering, etc. Finally, we discuss the current challenges facing GSMM.

Statistical sampling of missing environmental variables improves biophysical genomic prediction in wheat.

KEY MESSAGE: The integration of genomic prediction with crop growth models enabled the estimation of missing environmental variables which improved the prediction accuracy of grain yield. Since the invention of whole-genome prediction (WGP) more than two decades ago, breeding programmes have established extensive reference populations that are cultivated under diverse environmental conditions. The introduction of the CGM-WGP model, which integrates crop growth models (CGM) with WGP, has expanded the applications of WGP to the prediction of unphenotyped traits in untested environments, including future climates. However, CGMs require multiple seasonal environmental records, unlike WGP, which makes CGM-WGP less accurate when applied to historical reference populations that lack crucial environmental inputs. Here, we investigated the ability of CGM-WGP to approximate missing environmental variables to improve prediction accuracy. Two environmental variables in a wheat CGM, initial soil water content (InitlSoilWCont) and initial nitrate profile, were sampled from different normal distributions separately or jointly in each iteration within the CGM-WGP algorithm. Our results showed that sampling InitlSoilWCont alone gave the best results and improved the prediction accuracy of grain number by 0.07, yield by 0.06 and protein content by 0.03. When using the sampled InitlSoilWCont values as an input for the traditional CGM, the average narrow-sense heritability of the genotype-specific parameters (GSPs) improved by 0.05, with GNSlope, PreAnthRes, and VernSen showing the greatest improvements. Moreover, the root mean square of errors for grain number and yield was reduced by about 7% for CGM and 31% for CGM-WGP when using the sampled InitlSoilWCont values. Our results demonstrate the advantage of sampling missing environmental variables in CGM-WGP to improve prediction accuracy and increase the size of the reference population by enabling the utilisation of historical data that are missing environmental records.

LKRSDH-dependent histone modifications of insulin-like peptide sites contribute to age-related circadian rhythm changes.

To understand aging impact on the circadian rhythm, we screened for factors influencing circadian changes during aging. Our findings reveal that LKRSDH mutation significantly reduces rhythmicity in aged flies. RNA-seq identifies a significant increase in insulin-like peptides (dilps) in LKRSDH mutants due to the combined effects of H3R17me2 and H3K27me3 on transcription. Genetic evidence suggests that LKRSDH regulates age-related circadian rhythm changes through art4 and dilps. ChIP-seq analyzes whole genome changes in H3R17me2 and H3K27me3 histone modifications in young and old flies with LKRSDH mutation and controls. The results reveal a correlation between H3R17me2 and H3K27me3, underscoring the role of LKRSDH in regulating gene expression and modification levels during aging. Overall, our study demonstrates that LKRSDH-dependent histone modifications at dilps sites contribute to age-related circadian rhythm changes. This data offers insights and a foundational reference for aging research by unveiling the relationship between LKRSDH and H3R17me2/H3K27me3 histone modifications in aging.

Measuring, visualizing, and diagnosing reference bias with biastools.

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios: when the donor's variants are known and reads are simulated; when donor variants are known and reads are real; and when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.