Molecular Genetics and Genomics

Magnaporthe oryzae, the rice blast fungus, plays a role as a model organism for molecular plant-microbe interaction research. Studies on the pathogenic mechanism of this fungus revealed many genes involved in signaling pathways. As multi-omics data are being available, genomic-level researches have been conducted to uncover the underlying biological processes during the pathogenesis of M. oryzae. Identifying the genome-wide protein-protein interaction (PPI) network is one of the omics-level approaches, which helps to understand signaling and regulatory pathways. However, existing biological network resources of M. oryzae are not sufficient to decipher pathogenesis mechanisms due to the abundance of false positives/negatives. In this study, a reliable PPI network database of M. oryzae, MagNet, was constructed with three methods, including homology-based Interolog search, co-expression network construction, and domain-domain interaction (DDI)-based prediction. With three approaches altogether, the pan-network with 5,600,976 interactions was generated, including 217,531 highly confident interactions supported by all three methods. Experimental data on M. oryzae PPIs supported that our PPI network can predict PPIs with higher accuracy compared to the previously constructed databases. MagNet would provide integrated biological network data, which can help to understand the molecular mechanisms of the rice blast fungus. The PPI data can be accessed via https:/magnet.scnu.ac.kr.

Gene model for the ortholog of Lst8 (Lst8) in the May 2011 (WUGSC dyak_caf1/DyakCAF1) Genome Assembly (GenBank Accession: GCA_000005975.1) of Drosophila yakuba. This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.

Biological sequences are known to be not random. Thus, the comparison of in silico restriction fragment distributions of random and biological sequences may be an indicator of this non-randomness. Our analyses show that for most of the tested combinations of restriction enzyme and genome sequence the fragments per Megabase of the biological sequence deviate at least more then 10% from the corresponding random sequence. This deviation goes into both directions, i.e. clearly increased values are as common as clearly decreased values. Although there is no species- or restriction-enzyme-specific effect, a clear impact of the GC content both of the restriction site and of the genome sequence can be seen. In contrast to the random sequences, the genome sequences show distinct peaks in their fragment length distributions, hinting to repetitive elements such as transposons.

Gene-by-environment (GxE) interactions play a major role in shaping both phenotypic and molecular variation, with important implications for human health and disease. In this study, we used the Doxycycline (Dox) regulated, tetracycline-responsive (Tet-Off) promoter system to sequentially reduce or titrate gene expression levels of the essential yeast transcription factor Repressor Activator Protein 1 (RAP1) similar to a hypomorph allele series, across three distinct environments: Yeast Peptone Dextrose (YPD) media, YPD media with Heat Shock (HS), and Yeast Peptone Acetate (YPAC) media. We then performed RNA sequencing (RNA Seq) to assess global transcriptional responses to RAP1 reduction in these different growth environments. Our analysis first focused on the independent effects of varying RAP1 expression levels within and across environments. We then explored GxE interactions, revealing a subset of genes with significant consequences of reduced levels of RAP1 and environment-specific expression patterns. Notably, many genes exhibited opposite effects of RAP1 titration on gene expression when yeast were grown in YPAC media compared to YPD media and/or HS, suggesting environment-dependent regulatory architecture. This design reveals how cells integrate internal transcriptional and regulatory changes with external environmental cues, providing a deeper view of GxE architecture. Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified co-regulated gene modules, and by combining this with transcription factor motif enrichment tests, our study identified candidate regulators driving their dynamics. Our findings demonstrate that gene regulatory networks can vary dramatically depending on the environmental context an organism experiences, which can then influence the specific phenotypes produced by a particular genetic perturbation. This illustrates the complexity of genotype-environment interactions and the importance of studying gene function in multiple environments to gain a truly comprehensive understanding of a genes sometimes numerous and diverse functions.

Selective deployment of multiple transcription start sites is a major regulatory feature of human transcriptomes. FANTOM CAGE data exhibit a near-universal TSS deployment parsimony which is disrupted in cancers. We have recently shown that TSS deployment is sensitive to gene function, futile upstream transcription, and cellular biosynthetic states. Patterns in FANTOM CAGE data can reveal mechanisms underlying TSS co-deployments. We propose and test the possibility that some TSSs act like epromoters and act as co-varying hubs of transcriptional activities for multiple other promoters. Using deep analysis of CAGE data implemented through neural networks we show that non-cancers implement transcription co-deployments through cores of epromoter-like TSSs which are generally proximal to their start codons. These TSSs show enhancer-like TFBSs profiles. A comparison with cancer CAGE data shows that the concentrated epromoter core is disrupted in cancers with multiple distal TSSs replacing the proximal TSS cores. We provide evidence that the core TSSs are rich in YY1 and CTCF binding sites and associated with genes coding for transcription factors. Our findings show that covariance of TSS deployment is sensitive to transcriptional resource cost and a parsimonic design of TSS co-deployments depends on proximal TSSs in non-cancers, a mechanism grossly disrupted in cancers. HighlightsO_LIHeterogeneous FANTOM CAGE data contains universal patterns of TSSs co-deployments. C_LIO_LITSS co-deployments exhibit a parsimonious "core-covariant" scheme which is disrupted in cancers. C_LIO_LICore TSSs are enriched in transcription factor binding sites and gene functions which justify biological features of the samples. C_LIO_LIThe DL pipeline we present identifies the core-covariant TSS sets in an unbiased manner. C_LI

O_LIPlants and fungi are major sources of natural products beneficial to society, making the study of distinct species essential for discovering new drugs and bioactive compounds. The medicinal mushroom "Lingzhi" or "Reishi" (Ganoderma lingzhi) is widely used in traditional medicine and extensively studied for its bioactive triterpenoids, yet it is commonly identified as Ganoderma lucidum, the type species of the genus, which lacks a type specimen. C_LIO_LIWe sequenced a G. lucidum specimen preserved in the Kew fungarium, which agreed with the original description and was collected from wood of Corylus avellana in southern England. Using this reference specimen, we compiled genomic and ITS barcoding datasets to explore the genetic and geographic variation within this species. C_LIO_LIWe showed that G. lingzhi and G. lucidum diverged more than 12 million years ago and that all seven "G. lucidum" genomes deposited in public databases belong to other species. More than 1000 barcoding sequences showed that the widely used homology-based ITS barcoding is not working in this group, which can be mitigated by a phylogenetic placement approach. The 149 sequences assigned to G. lucidum with high confidence showed a Eurasian distribution and introductions to North and South America and Africa. C_LIO_LIOur study underscores the importance of accurate species identification and provides guidance for a group of pharmaceutical and socially significant species. To further support future studies and the wider public in differentiating between G. lingzhi and G. lucidum, we propose using "False Lingzhi" as the English name for G. lucidum. C_LI Societal Impact StatementTraditional Chinese Medicine has expanded far beyond Asia, with growing markets in North America and Europe for supplements and functional foods. Lingzhi or Reishi (Ganoderma lingzhi), a well-known medicinal mushroom, is valued for its anti-inflammatory and anticancer properties. However, it is often misidentified with species that may not provide the same health benefits. This confusion poses risks to consumer safety, product regulation, and research. Here, we establish a reference using morphological and molecular tools for the most commonly misidentified species (Ganoderma lucidum) and propose the name "False Lingzhi" to distinguish it, supporting accurate identification, safer product development, and reliable research.

Rhodnius prolixus is a primary insect vector of Trypanosoma cruzi, the causative agent of Chagas disease, a neglected parasitosis endemic in Latin American countries. It has been estimated that Chagas disease affects 7-8 million people worldwide and is responsible for approximately 1000 deaths per year. Genetic and molecular studies in this species remain challenging due to its life cycle and feeding habits, thus hindering the development of new strategies to control their populations and reduce the diffusion of Chagas disease. Recently, two stable cell lines - RPE/LULS53 and RPE/LULS57 - were derived from Rhodnius embryos, which represent promising new tools to investigate the genetics of this insect vector. Here, we describe their gene expression landscapes through transcriptomic approaches. We show that 8,968 expressed genes are shared between the two cell lines, whereas 391 and 1,088 genes are uniquely expressed in RPE/LULS53 and RPE/LULS57, respectively. Although key components of primary developmental, immune and redox signaling pathways are expressed in both cell lines, some genes such as Frizzled-10-a-like and catalase show marked differences in expression. Our results strongly suggest that RPE/LULS53 and RPE/LULS57 likely represent two different cell phenotypes. Consistent with this, gene ontology analysis reveals that RPE/LULS53 is enriched for animal organ morphogenesis and stress response, while RPE/LULS57 for DNA-directed RNA polymerase activity, among others. Despite these differences, both cell lines express comparable levels of transcripts from resident transposable elements, including the highly abundant Mariner and LINE/I elements, as well as horizontally transferred transposons. Our findings shed light on the nature of the RPE/LULS53 and RPE/LULS57 embryo-derived cell lines and provide valuable transcriptomic resources for future genetic and functional studies in Rhodnius and other triatomine insect vectors. Author summaryRhodnius prolixus is a blood-feeding insect and a major vector of Chagas disease, a parasitosis endemic in Latin America and affecting millions of people worldwide. In the absence of effective drugs and vaccines, the control of the insect population represents a promising strategy to reduce the diffusion of the disease. Yet, genetic and functional studies in Rhodnius are extremely challenging due to its feeding habit and life cycle. To overcome these limitations, researchers have previously developed two stable cell lines derived from Rhodnius embryos. In this study, we provide the first characterization of the genes expressed in these cell lines. We found that, while the two cell lines share many expressed genes, each of them also has distinct gene expression patterns pointing to two different cell types with specialized functions. These differences likely affect the way they respond to stress and regulate biological processes. Our findings provide an important resource for researchers studying Rhodnius prolixus and other insect vectors, helping advance our understanding of the genetic and molecular mechanisms that control the insect development and mediate the interactions between insect vectors and the parasites they transmit

The transformation of the free nuclear syncytium into cellular endosperm tissue with starch and protein accumulation is a well-established phenomenon, at least in the fruits of cereals of the Triticeae tribe. The present article demonstrates that there is considerable diversity inherent in this type of caryopsis morphogenesis. By examining various taxa (species, varieties, and cultivars) of wheat, oats, and some wild grasses, this research reveals significant deviations in endosperm morphogenesis from the typical state. A new developmental pattern of endosperm was identified, characterized by several distinctive features such as incomplete cellularization of the syncytium and starch accumulation within the acellular endosperm domains and the endosperm cavity. A large number of plastids were observed in the syncytium stage, which served as the basis for the later amyloplast stage. The acellular endosperm domains and the cavity domain exhibited connections at specific discontinuities in the modified aleurone layer surrounding the cavity. The peripheral parts of the caryopsis received fewer assimilates necessary for starch synthesis, which was attributed to their increased distance from the transfer system and a likely reduction in the efficiency of assimilate transport through the apoplast in these areas. The starch cavity volume constituted a few percent of the overall caryopsis volume, which could serve as a foundation for potential breeding improvements to enhance starch yields across different varieties.

CRISPR-Cas genome editing toolkits have expanded the scope of genetic studies in various emerging model organisms. However, their applications are limited mainly to knockout experiments due to technical difficulties in establishing knock-in strains, which enable in vivo molecular tagging-based experiments. Here, we investigated knock-in strategies in the harlequin ladybug Harmonia axyridis, a model insect for evolutionary developmental biology, which shows more than 200 color pattern variations within a species. We tested several knock-in strategies using synthetic DNA templates. We found that ssDNA templates generated founder knock-in strains efficiently (2.5-11%), whereas the 5 regions of ssDNA templates were frequently deleted when the insert length exceeded [~]40 bases. To overcome this limitation, we designed several 3 extended DNA templates. Fast-annealed 3-extended double-stranded DNA templates, which were designed for tagging endogenous proteins with epitope tags, showed high founder generation efficiency (9.9-20.9%) and accuracy (30.8-85.7%). This strategy is also applicable to the two-spotted cricket Gryllus bimaculatus, suggesting that the fast-annealed 3-extended dsDNA template is a versatile DNA template for generating knock-in strains in emerging model insects for developmental genetic studies. Summary statementFast-annealed 3-extended dsDNA templates facilitate efficient CRISPR-Cas9-mediated knock-in in emerging model insects.

Ribosome biogenesis is a highly coordinated pathway that involves the assembly of ribosomal RNAs (rRNAs) with ribosomal proteins (r-proteins) to generate functional ribosomal subunits (r-subunits). The Saccharomyces cerevisiae (yeast) large 60S r-subunit consists of three rRNA molecules and 46 r-proteins. The contributions of nearly all r-proteins of the yeast large r-subunit have been characterized; however, a few non-essential proteins remain poorly understood. Although non-essential, human eL22 has been identified as a key player in p53 regulation during ribosomal stress and as a highly mutated target in cancers. Despite this function, the role of eL22 in ribosome maturation is still ill-defined. In this study, we characterized yeast eL22 r-protein. Our results show that eL22 assembles into intermediate nucleolar pre-60S ribosomal particles. Loss of eL22 impairs cell growth and reduces 60S r-subunit accumulation, phenotypes that are exacerbated at low temperatures. Analysis of pre-rRNA processing by pulse-chase labeling, northern blot hybridization, and primer extension reveals a defect in 27S pre-rRNA maturation, specifically at the level of 27SB pre-rRNA processing. Consequently, nuclear export of eL22-deficient pre-60S particles is mildly impaired. Furthermore, we identify genetic interactions between eL22 and neighboring r-proteins, eL38 and eL31. We conclude that eL22 assembly is required for optimal pre-60S maturation during middle nucleolar stages, particularly at low temperatures, a function likely supported by the cooperative action of other r-proteins associated with common elements of 25S rRNA. HighlightsO_LIWe have studied the role of r-protein eL22 in yeast ribosome assembly. C_LIO_LIeL22 is required for 60S ribosomal subunit production. C_LIO_LIThe absence of eL22 is critical at low temperatures. C_LIO_LIeL22 is important for 27SB pre-rRNA processing and nuclear export of pre-ribosomes. C_LIO_LIeL22 functionally interacts with r-proteins eL38 and eL31 in domain III of 25S rRNA. C_LI

We recently reported the identification of endogenous viral elements (EVEs) originating from the Caulimoviridae family within the alfalfa (Medicago sativa L.) genome. Our subsequent identification of ubiquitous rhabdoviral elements in infected and healthy alfalfa tissues by high throughput sequencing prompted us to suggest that the alfalfa genome might be populated with integrated rhabdoviruses as well. Bioinformatics analysis using 26 publicly available alfalfa genomes proved the suggestion accurate. We found multiple non-retroviral segments of the Rhabdoviridae family belonging to the genera Betanucleorhabdovirus and Betacytorhabdovirus that appeared to be stable constituents of the host genome. In that capacity they could potentially acquire functional roles in alfalfas development and response to environmental stresses. We believe this study reveals the first documented case of rhabdoviruses integrated into the alfalfa genome.

In this study, the critical gap in understanding how fonio responds to contrasting pedoclimatic conditions, both within and outside its traditional production areas was addressed. A multi-environment trial was carried out to identify high-yielding genotypes with either broad stability or specific adaptation, thereby enabling targeted varietal recommendations to support the expansion of fonio cultivation into new areas. Randomized complete block design was used in six environments with eleven genotypes to evaluate flowering and maturity times, and grain yield. The Additive Main effect and Multiplicative Interaction and the Genotype main effect and Genotype x Environment interaction biplots revealed a significant effect of the genotype-by-environment interactions on traits, with genotypes B12 and G31 identified as high-yielding, while genotypes M5 and M14 were revealed as early-flowering and maturing. Genotypes M14 and M15 were adapted to all environments and early maturing. Boukoumbe, known as the fonio production area in Benin, was the most desirable for earliness, while Ina was the most ideal for grain yield, proving that fonio could be cultivated in Sudanian and Sudano-Guinean areas. Factor analysis revealed precipitation, C:N ratio, soil pH and texture as the main environmental variables influencing the grain yield in fonio. Our findings contributed to selecting stable, adapted genotypes.

Genetically identical cells grown in the same environment show variation in gene expression known as expression noise. Expression noise can be heritable and impact fitness, making it subject to natural selection. Increasing expression noise for the Saccharomyces cerevisiae TDH3 gene was shown to be beneficial in glucose-based media when mean TDH3 expression was far from the fitness optimum but deleterious when it was close to this optimum. Here, we show that growth on different carbon sources alters the effects of new mutations on TDH3 expression noise and examine the fitness effects of changing expression noise. In galactose-based media, we observed the same relationship between expression noise and fitness seen in glucose-based media, but in glycerol- and ethanol-based media, we observed the opposite relationship or no significant relationship, respectively. Using simulations of single-cell organisms, we found that these differences were most likely explained by environment-specific relationships between gene expression and fitness. We also found that, far from the optimum, the fitness effects of noise were greatest when expression was highly heritable between mother and daughter cells. The empirical observations and simulations reported in this study show how environments influence both the production of expression noise and its impacts on fitness.

BackgroundChimeric antigen receptor (CAR)-T cell therapies efficacy in solid tumors remains limited, largely due to the profoundly immunosuppressive tumor microenvironment (TME) which drives CAR-T cells to dysfunction and poor persistence. A comprehensive understanding of the dynamic interplay between CAR-T cells and the TME is therefore critical for the rational design of more effective CAR-T strategies for solid cancers. MethodsHere, we performed single-cell RNA sequencing of tumor samples from immunocompetent mice treated with stroma-targeting EDA-CAR-T cells, profiling CAR-T cell states and TME programs at the peak of antitumor response and during subsequent tumor progression. ResultsOur analysis revealed a marked temporal remodeling of EDA-CAR-T cells within the TME, where early antitumor efficacy is associated with concurrent expansion of cytotoxic effector CD8 CAR-T cells and activation of memory CD4 CAR-T subsets. Moreover, EDA-CAR-T cells effectively engaged the myeloid compartment, resulting in strengthened communication networks involving T cell activation. However, by tumor progression, EDA-CAR-T cells suffered a widespread transcriptional reprogramming towards dysfunction, characterized by loss of effector programs alongside induction of exhaustion and immunoregulatory pathways within the TME, including PD-L1/PD-L2 and TGF{beta} signaling, which impairs sustained immune responses. Notably, early CAR-T cell activation led to increased susceptibility to TME-mediated immunosuppression, revealing EDA-CAR-T-specific soluble galectin-mediated cell-to-cell interaction networks. ConclusionsTogether, this works offers a high-resolution view of CAR-T cell dynamics within the solid TME, uncovering cellular and molecular mechanisms of rapid functional decline and identifying regulatory pathways within the TME that can be exploited to improve CAR-T cell therapy efficacy in solid tumors. KEY MESSAGES OF THE ARTICLEO_ST_ABSWhat is already known on this topicC_ST_ABSThe determinants of CAR-T cell therapeutic efficacy in solid tumors remain poorly defined, largely due to the complexity of the immunosuppressive tumor microenvironment. In this effort, it is necessary to perform comprehensive and detailed mechanistic studies that capture CAR-T cell dynamics within the solid tumor microenvironment to understand treatment failure. What this study addsWe performed single-cell profiling of stroma-targeting EDA-CAR-T cells, revealing their dynamic reprogramming toward dysfunction within the solid tumor microenvironment. We dissected CAR-T cell states and their cell-to-cell interactions with the tumor microenvironment across response and tumor progression and identified mechanisms linking CAR-T cell functionality and therapeutic failure. How this study might affect research, practice or policyThis study provides comprehensive mechanistic insights from an immunocompetent model that can be leveraged to identify shared determinants of CAR-T cell functionality in solid tumors and potentially guide the rational development of improved CAR-T cell therapies.

Astrocytic homeostatic programs, many of which are regulated by the circadian clock, are disrupted early in neurodegenerative disease. The core clock transcription factor (TF) BMAL1 is required for normal astrocyte function, but its role during disease remains unclear. This is partly because methods for identifying cell type-specific TF binding sites are limited. Here, we developed MACS-Calling Cards (MACS-CC), a strategy for mapping astrocyte-specific TF occupancy in vivo. We used MACS-CC to define BMAL1 binding in the Cln3{Delta}ex7/8 mouse model of CLN3 disease, a fatal neurodegenerative disorder marked by early astrocyte dysfunction and circadian disruption. BMAL1 binding was extensively redistributed in Cln3{Delta}ex7/8 astrocytes: wild-type-specific binding sites enriched near glial differentiation genes, whereas Cln3{Delta}ex7/8-specific sites lacked functional enrichment. Consistent with these changes, Cln3{Delta}ex7/8 astrocytes decreased expression of mature astrocyte markers. To define mechanisms underlying BMAL1 retargeting, we tested whether altered chromatin accessibility explained the changes in BMAL1 binding. Although chromatin accessibility was broadly remodeled, differential accessibility did not predict BMAL1 redistribution. Instead, motif analysis suggested that loss of cooperative TF interactions drives BMAL1 retargeting. These findings demonstrate that MACS-CC enables astrocyte-specific TF occupancy mapping and reveals mechanisms behind early rewiring of circadian regulatory programs within a model of a neurodegenerative disease. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/721783v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1ada239org.highwire.dtl.DTLVardef@7564a3org.highwire.dtl.DTLVardef@122222forg.highwire.dtl.DTLVardef@1f2729c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Seaweed cultivation has recently gained increased attention in North-West Europe as a sustainable source of biomass for biobased products. However, yields need to increase to make the seaweed sector economically viable. To achieve this, higher yielding varieties can be bred but this requires variation for yield and yield-related traits among genotypes. To reliably select high-yielding genotypes, an understanding is required of how both within-farm and between-farm environmental differences affect phenotypes and how to identify simple and reliable proxies for yield. In this study we evaluated growth of nine Saccharina latissima genotypes on two farms, 12 km apart, within the same season. We observed a threefold difference in yield among genotypes, demonstrating the potential for improvement through selection and breeding. Blade thickness and blade size-related traits were strongly correlated with yield, highlighting their potential to serve as rapid and non-destructive proxies for yield, thereby accelerating selection. Furthermore, we demonstrated the importance of adequate replication in farm trials to improve genotype performance estimation by correcting for within-farm spatial variation. Moreover, phenotypic variation was most explained by the genotype and environment, highlighting the importance of both genotype and site selection. Although genotype by environment interactions (GxE) were significant, its contributions were small, indicating stable genotype ranking across farms. Overall, these results are promising for breeding improved S. latissima as it indicates that genotype performance is consistent across close by locations and that local S. latissima populations harbour substantial phenotypic variation that can be used to breed for increased yield. Highlights- Local genetic resources harbour substantial variation in yield and morphology for breeding. - Minor GxE allows for breeding across farms. - Blade thickness and blade size related traits are good predictors of yield. - Correction for on-farm spatial variation improves genotype performance estimation.

Phenomic prediction (PP) is a breeding value prediction method using near infrared spectroscopy (NIRS). Spectra pre-processing is a key step in the analysis pipeline of PP and generally involves chemometrics methods. However, there is still little understanding in the genetics community of what pre-processing does and why it increases performances. Consequently, the choice of pre-processing is done either arbitrarily or through a search of the optimal set of methods and associated parameters. In this study, we propose a PCA-based pre-processing method where genetic values of spectra are estimated on a set of principal components instead of individual wavelengths. This way, estimations are based on a few informative and orthogonal features of spectra instead of many correlated, uninformative wavelengths. We tested this new pre-processing method on five data sets representing four plant species (maize, rice, sorghum and grapevine). Results show that it performs as good, or better than the best classical chemometric pre-processing methods in almost all cases. Combining PCA-based and classical chemometric pre-processing methods maximizes predictive ability. Moreover, this pre-processing method opens up possibilities of better understanding and selecting parts of the spectral information that are relevant for the prediction of breeding values. Indeed, components representing together about 1% of spectral variability were found to be responsible for most of PP predictive ability. Plain language summaryCultivated plants are the result of a breeding process during which their genetic values are used to select those to breed. Estimation of breeding values requires heavy experimental means and is time consuming. Phenomic prediction is a low cost and high throughput genetic value estimation method that is increasingly being used. It often uses near infrared spectroscopy measurements as predictors of genetic values that are easy to collect and thus routinely used in many species. However, near infrared spectra generally require pre-processing before being used in prediction. Currently used pre-processing methods arise from the chemometrics community, and still deserve a better in-depth appropriation by geneticists. In this study, we propose a new pre-processing approach that performs as good as or better than the best chemometric pre-processing generally used, reduces computation time, and allows for a better understanding of what parts of spectral information are relevant for prediction. Core IdeasO_LIWorking on principal components of spectra instead of wavelengths increases predictive ability of phenomic prediction and performs as good as or better than classical chemometrics pre-processing C_LIO_LIWorking on principal components of spectra requires less optimization of parameters than chemometrics pre-processing C_LIO_LIAbout 1% of spectral variance is responsible for most of the predictive power of phenomic prediction C_LIO_LIWorking on principal components of spectra pre-processed with classical chemometrics pre-processing can increase predictive ability even more C_LIO_LIPCA-based methods are valuable to optimize predictive ability of phenomic prediction and could be used more widely in the quantitative genetics field C_LI

Whole genome duplication is a common mutation in eukaryotes with far-reaching phenotypic effects. The resulting morphological, physiological, and fitness consequences and how they affect the survival probability of newly polyploid lineages are intensively studied, but very little is known about the effect of genome doubling on the short-term evolvability of populations. Understanding the effect of polyploidization on the adaptive potential of populations is of crucial importance to predict the future of polyploid populations. In this paper, I investigate the immediate consequences of genome doubling on the genetic variance of populations. To do so, I performed numerical iterations and simulations of how the genetic variance of a quantitative trait changes after polyploidization, under different genetic architectures (additivity, dominance, and epistasis). I found that genetic variance generally decreases after genome doubling. Non-additive gene actions can make autotetraploid populations genetically more diverse than their diploid progenitors in rare cases, notably with overdominance and directional epistasis. By collecting estimates from the agronomic literature, I found that both dominance and epistatic variance contribute to the genetic variance of polyploid populations. These results bring new insights into the adaptive potential of newly formed tetraploid populations, and call for further experimental investigations of how polyploidization is associated with a short-term decrease in evolvability.

Genomic erosion as a manifestation of small effective population size (Ne) and consanguinity subverts long-term perpetuation of threatened species by compromising their adaptive potential; however, the integration of genomics remains limited in applied conservation efforts to guide priorities. This study combines non-invasive sampling, double-digest Restriction site-associated DNA sequencing (ddRAD), and population-genomic analyses to assess genetic health in two vulture assemblages-mixed wild enclosure and captive breeding cohorts. Both the geographical locations exhibit signs of populations in distress: low genetic diversity and abundant intermediate-length runs of homozygosity (RoH), consistent with long-term reduced Ne plus recent demographic isolation. Our demographic model runs favoured ancient migration (AM) topology characterised by an ephemeral window of gene flow, taken over by a prolonged population separation period. The mutation quantification results from approximately 59,000 outgroup-polarised SNPs reveal higher additive burden and more homozygous-derived sites in BKN. However, this was later traced to low-impact and non-coding variants rather than a surge in the loss-of-function (LoF) alleles. The data support a genomic profile that carries an elevated risk from polygenic/aggregate deleterious burden in BKN despite a scarcity of high-impact mutations. By highlighting the disconnect between genetic resilience and demographic recovery, our results accentuate the need to incorporate genomics-informed inbreeding and monitoring programs, while also focusing on reducing anthropogenic mortality with genetic augmentation.

An expectation of a hypothesis that proposes cell-to-cell signalling pathways are redundant due to the redundancy of pathway terminal transcription factors (TFs) was tested by screening 35 signalling ligands (SLs) for rescue of a decapentaplegic (dpp) hypomorphic wing growth phenotype. The screen identified three examples of partial rescue: Hedgehog (HH), Semphorin 1a (SEMA1A) and Wnt ortholog 2 (WNT2). HH overexpression with dppGAL4 may increase the expression of DPP activity from the hypomorphic dpp alleles. However, SEMA1A and WNT2 did not phenocopy ectopic expression of HH or DPP and neither SEMA1A nor WNT2 were required for wing growth suggesting substitution of DPP for partial restoration of wing growth. The WNT2 rescue was dependent on the Frizzled 4 (FZ4) WNT receptor excluding the possibility that WNT2 weakly binds the DPP receptor. Although examples of phenotypic nonspecificity of SL function were identified, this is an expectation, and not direct proof, of the hypothesis of TF redundancy. Screen Report SummaryAn expectation of a hypothesis proposing that cell-to-cell signalling pathways are redundant due to the redundancy of the pathway terminal transcription factors was tested by screening for replacement of one signalling ligand (DPP; SLa) with another SLb for wing growth. Three non-DPP SLs were identified in the screen of 35SLs: HH, SEMA1A and WNT2. Genetic analysis of Sema1a and Wnt2 suggests functional complementation of dpp for wing growth suggesting that SEMA1A and WNT2 partially replace DPP for wing growth. Therefore, an expectation of the hypothesis is met.