G3 Genes|Genomes|Genetics

The field of genetics of bird migration advances, driven by exponential refinements of sequencing and tracking technologies. In willow warblers (Phylloscopus trochilus), a complex repeat-rich region named MARB (Migration Associated Repeat Block) has recently been found to correlate with the routes taken by individual birds from Europe to their African wintering grounds. However, the genomic location of this region remains unknown. Here, we characterized MARB using a combination of approaches to understand how it evolved. We describe the region using long-read genome assemblies of two willow warbler subspecies (P. t. trochilus and P. t. acredula), two related species, the common chiffchaff (P. collybita) and the greenish warbler (P. trochiloides), and whole genome sequencing data from 76 willow warblers. Finally, we applied karyotyping and fluorescent in situ hybridization techniques on willow warbler spermatocytes to cytogenetically locate MARB. Due to the many repeats, we cannot order scaffolds in silico, but probe hybridization on the karyotype shows that MARB constitutes a single locus (~27.5 Mb) spanning most of the 11th largest chromosome in the willow warbler genome. Interestingly, the MARB regions of all species share several characteristics such as relatively high GC content (50%), a high density of specific repeat families and notably, more than 800 olfactory receptor sequences. Regions homologous to MARB may exist in several migrant bird genomes, though currently unassembled due to their complexity. Resolving these in species with similar migratory polymorphisms to willow warblers will be essential to determine whether MARB influences migratory behaviour across species.

Many taxa have evolved heteromorphic sex chromosomes like the XY system found in mammals. In additional to the sex determination gene which directs development of the gonad into an ovary or testis, sex chromosomes can have drastically different gene content, leading to substantial genetic differences between genetic males and females beyond their gonad identity. Studying the effects of these genetic differences is challenging, as the sex chromosomes and sex determination gene are inherited together, so the effects of genetic differences between the X and Y cannot be easily isolated from the hormonal differences produced by the ovary and testis. The threespine stickleback fish has a heteromorphic XY sex chromosome system and a wide range of well documented sex differences in morphology and behaviors, including complex mating behaviors and male-only parental care. Through genetic manipulation of amhy, the newly identified sex determination gene in threespine stickleback, we are able to generate gonadal males and females with either the XX or XY sex chromosome complement and analyze the separate effects of gonadal sex and sex chromosome complement on sexually dimorphic gene expression. We find that sex chromosomes have a larger effect on gene expression than gonadal sex in somatic tissues, while gonadal sex has a larger effect on expression in the gonads. We also find that the X and Y chromosomes are enriched for genes which show differential expression between females and males. Our findings demonstrate the significant biological impact of sex chromosomes outside of primary sex determination and showcase the utility of the threespine stickleback for studying the genetic basis of sex differences.

At a mere 20 cells, the Caenorhabditis elegans intestine regulates metabolism, energy homeostasis, host defense, yolk production, and genetic aging, all while dynamically responding to its environment. How the intestine develops to carry out these disparate functions is unknown, and how cells differ along the length of the intestine is unclear. To address these questions, we performed single-cell RNA sequencing (scRNA-seq) on FACS-enriched intestinal cells from mixed-stage C. elegans embryos. The resulting single-cell transcriptomes of 974 cells organized into 13 clusters, suggesting a diversity of cell types and states. We used two post hoc approaches to ascribe identities to each cluster. First, genes with known developmental timing in early-, mid-, and late-stages were used to place clusters in time, and smiFISH microscopy was used to fine-tune the assignments. Second, the eight late-stage clusters were assessed for their region of origin. To assign these clusters to anatomical regions, we identified marker genes for each cluster and assessed their expression along the anterior-to-posterior length of the intestine using smiFISH microscopy. Genes associated with growth and cell division were expressed in early stages, whereas genes associated with immune responses and metabolism were expressed later. Genes associated with biotic responses and RNA metabolism were the most likely to vary across the intestines anterior-posterior axis. Finally, perturbation of anterior-localized intestinal transcripts more robustly affected intestinal function compared to central or posterior-localized genes. Overall, this research illustrates the intrinsic heterogeneity across the 20 cells of the embryonic intestine and sets the stage for future works aimed at understanding cell-specific intestinal responses to diet and the environment. ARTICLE SUMMARYWe investigate how the Caenorhabditis elegans intestine develops specialized functions on a spatiotemporal scale. We used single-cell RNA-sequencing to analyze embryonic intestinal cells and identify 13 distinct clusters. Combining gene expression analysis with microscopy, we assigned clusters to developmental stages and anatomical regions. Clusters associated with early intestine development express genes linked to growth and cell division, while later-stage clusters express genes involved in metabolism and immune responses. Genes varied across the intestines anterior-to-posterior axis, and disrupting anterior-specific genes produced stronger functional effects. These findings reveal previously unrecognized intestinal diversity and provide insight into how intestinal cells specialize during development.

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

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.

Interest in quantifying linkage disequilibrium (LD, non-random associations of alleles at different loci) has skyrocketed in recent years as researchers have focused on use of LD in genome-wide association studies (GWAS), for studying historical demography, and for estimating effective population size (Ne). The most widely used LD metric is r2 = the squared correlation of alleles at a pair of loci. Despite a half century of efforts, developing an unbiased expectation of r2 as a function of the many factors that can affect it (physical linkage, genetic drift, selection, migration, mutation, mating systems) remains elusive. Furthermore, even when all of these other factors are absent, empirical estimates of r2 are upwardly biased by sampling a finite number (S) of individuals, and that must be accounted for if one wants to focus on the desired signal of LD. Previous approaches to estimate [Formula] have been shown to be biased to greater or lesser degrees. The purpose of this short paper is to demonstrate that a simple and apparently exact expression for [Formula] does exist for the special case where sampling error is the only factor contributing to r2, in which case [Formula] = 1/(S - 1). When other factors contribute heavily to LD, [Formula] shrinks toward 0 as empirical r2 [->] 1. However, for estimating contemporary Ne with unlinked markers, empirical r2 will generally be small and 1/(S - 1) will provide a robust estimate of [Formula].

Animals sleep more when they are sick. In C. elegans, stress-induced sleep (SIS) follows cellular injury such as exposure to ultraviolet (UV) light. The genetic regulators of SIS remain incompletely defined. Using a worm-picking robot, multi-well WorMotel imaging, and association analysis we performed a semi-automated screen of 941 whole-genome-sequenced Million Mutation Project (MMP) strains. We quantified behavioral activity and quiescence before and after ultraviolet (UV) radiation. We applied the Sequence Kernel Association Test (SKAT) to this behavioral data to prioritize 6,663 genes and observed significant enrichment of known SIS genetic regulators. Based on these results, we conducted a candidate validation screen for additional genes regulating SIS. We identified three genes (strd-1, egl-8, cla-1), mutations in which reproducibly influence SIS. Further exploration of these genes holds potential for enhancing our understanding of the molecular basis of SIS. These findings establish a pipeline for automated behavioral phenotyping coupled with gene-based association to accelerate studies of C. elegans neurogenetics.

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.

Pennycress (Thlaspi arvense L.) is an intermediate winter oilseed crop that has only recently been domesticated for agronomic use. Improving agronomic traits requires sources of genetic variation, and mutagenesis is frequently used to help overcome the limitations of natural populations. We investigate the impact of Ethyl methanesulfonate (EMS) on genetically effective cells (GECs) to characterize the intra-individual genetic variation of EMS mutagenesis in pennycress. We identified that pennycress contains at least 4 GECs which, when treated with EMS, create unique mutations across different branches within the same individual plant. We then propagated the M2 plants for whole genome sequencing, providing extensive characterization of the EMS mutation profile and developing a gene index as a resource for future reverse genetic screenings. Article SummaryPennycress is an emerging winter oil seed crop in the American Midwest. Domestication efforts have advanced rapidly through a combination of genetic techniques. One of the most successful methods has been the use of a mutant gene index, a large collection of pennycress seed where new genetic variation has been created through Ethyl methanesulfonate (EMS). EMS mutations are not uniform however, and a single treated seed can have wide genetic variation within the resulting plant. We investigate the role of genetically effective cells on EMS variation, and present the full EMS population as a resource for further pennycress domestication efforts.

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

One feature key to the versatility of zebrafish as an animal model for biomedical research is the breadth of genetic tools available, including for transgenesis. While the Tol2 transposase system remains the gold standard, its efficiency can be highly variable. Here, we explored the potential of a complementary transgenesis system, Cp36, a large serine recombinase identified from Clostridium perfringens previously found to efficiently integrate target cargo into the human genome without a preinstalled attB site. We generated Cp36-based plasmid constructs for zebrafish transgenesis and compared their performance to matched Tol2 plasmids across multiple experimental contexts, including transient expression, germline transmission, and multi-transgene expression. Cp36 integrates small [~]3.5kb cargo into the zebrafish genome and transmits to the next generation as efficiently as Tol2, but Cp36 performance declines substantially for larger [~]7.5kb constructs. Both Cp36 and Tol2 have comparable efficiency in transiently expressing a second construct regardless of the transposase/recombinase used to integrate the first construct, indicating compatibility with sequential transgenesis strategies. In summary, we demonstrate that Cp36 functions as a new alternative transgenesis method in zebrafish.

Stripe rust and leaf rust, caused by Puccinia striiformis f. sp. tritici and P. triticina, respectively, are the most destructive wheat diseases in the southern Great Plains. Green Hammer is a hard red winter wheat (HRWW) cultivar released by Oklahoma State University in 2018 and has demonstrated a stable adult plant resistance to stripe rust and race-specific seedling resistance to leaf rust. To identify and map rust resistance loci, 109 doubled haploid (DH) lines derived from the cross between Green Hammer and another HRWW cultivar, Lonerider, were developed. Lonerider showed adult plant resistance to stripe rust but was susceptible to multiple P. triticina races. The DH lines were evaluated for stripe rust at the adult plant stage in greenhouse and field environments across Oklahoma, Kansas, and Washington, and for leaf rust at the seedling stage against seven U.S. P. triticina races and at the adult plant stage in Oklahoma and Texas. Genotyping-by-sequencing generated 6,078 polymorphic single-nucleotide polymorphisms used for genetic mapping. Quantitative trait loci (QTL) analysis identified 14 stripe rust and 8 leaf rust resistance QTL. For stripe rust, a major QTL in Green Hammer, QYr.osughln-2AS, was identified in the proximity of the 2NvS translocation. Three other major stripe rust resistance QTL were identified in Lonerider on chromosomes 2AL (two QTL) and 2BS (one QTL). For leaf rust, QLr.osughln-1DS and QLr.osughln-2DS.1 were the two major QTL identified in Green Hammer and most likely correspond to the all-stage resistance genes Lr21 and Lr39, respectively. In this study, we identified previously characterized genes as well as unknown genes that can be utilized in wheat breeding programs to enhance resistance to leaf rust and stripe rust.

Genomic prediction models that account genotype-by-environment (GxE) have the potential to accelerate the rate of genetic gain for yield and agronomic performance, yet relatively few studies have applied GxE prediction in public soft red winter wheat (Triticum aestivum) breeding programs. In this study, we extended a reaction norm-based genomic prediction framework by integrating weather-based environmental covariates to more effectively capture genotype- environment interactions. Key agronomic traits, including seed yield, plant height, test weight, and heading date, were evaluated across 33 environments (location-year) using over 3,200 breeding lines from the North Carolina State University small grains breeding program. Multiple genomic prediction models were compared using several cross-validation (CV) schemes representing common breeding scenarios. Across traits, the reaction norm M5 model, which incorporates both GxE and genotype-by-environmental covariate interactions (GxO), achieved the highest prediction accuracy (PA) in CV2 (predicting incomplete field trials) and CV1 for yield and test weight (predicting new lines). The highest PA was observed for test weight under CV2 (0.54) and for yield under CV1 (0.41). Under CV0 (predicting new environments), the M3 model incorporating GxE produced highest PA across traits, with the greatest accuracy for plant height (0.45), although differences among M2, M3, and M4 were small. Prediction under CV00 (predicting new lines in new environments) remained more challenging, with PA values 0.10 - 0.20 across traits. Overall, our results demonstrate that integrating environmental covariates into genomic prediction models can improve predictive performance across diverse wheat-growing environments in North Carolina, supporting their utility for applied breeding efforts. CORE IDEASO_LIIntegrating genotype-by-environment (GxE) interactions with environmental covariates improves prediction accuracy across environments. C_LIO_LIModel performance varies by prediction scenario, with different approaches performing best for new lines, incomplete trials, or new environments. C_LIO_LIPrediction of new lines in new environments remains challenging. C_LI PLAIN LANGUAGE SUMMARYThis study explores how adding environmental information to genomic prediction models can improve prediction accuracy in a public winter wheat breeding program. Using data from multi-environment trials conducted across diverse conditions in North Carolina, we evaluated statistical models that capture how different wheat lines respond to changing environments. By incorporating weather data, we improved the ability to predict performance across locations and years. These findings provide practical insights for refining selection strategies and accelerating genetic gain in wheat breeding.

In quantitative genetics, candidate SNPs are identified through genotype-phenotype associations inferred with genome-wide association studies (GWAS). In this study, we explore an alternative approach to detect genetic variants with non-neutral effects by tracking temporal trends in allele frequency in a winter wheat (Triticum aestivum L.) breeding population over an eight-year period, from which signals of selection may be inferred. Selection signatures were inferred with a generalized linear model, where we modeled trends in allele frequency as a function of time (crossing year). These signatures of selection were used to prioritize variants. Associations between phenotypic performance and individual load of prioritized variants were then investigated. Furthermore, we assessed whether incorporating selection information into a genomic best linear unbiased prediction (GBLUP) model improves model performance in terms of quality of fit and prediction ability. Our findings indicate that the inferred signals of selection are effective in identifying non-neutral variants. Variants under strong negative selection were associated with a decrease in protein content adjusted for grain yield (p-value < 0.01), while genetic variants that had been under moderate to high levels of positive selection were associated with increased grain yield (p-value < 0.01). However, incorporating selection information did not improve prediction accuracy. In conclusion, temporal trends in allele frequency can be used to detect non-neutral variants. The proposed approach may hence complement traditional quantitative genetic methods for detecting non-neutral genetic variation. This approach may allow breeders to detect non-neutral variants earlier in the breeding cycle, without resorting to phenotypic data.

Organismal survival depends on coordinated responses to oxidative stress and DNA damage. Using Caenorhabditis elegans, we investigate mul-1, a robust transcriptional target of ionizing radiation and reactive oxygen species. Although annotated as a mucin, MUL-1 is a small ShKT domain-containing protein belonging to an invertebrate expanded family of cysteine-rich proteins. mul-1 is selectively induced by oxidative stress, including IR, hydrogen peroxide (H2O2), Pseudomonas aeruginosa infection, or loss of the peroxiredoxin PRDX-2, via the p38 MAPK-ATF-7 pathway in intestinal cells. Loss of mul-1 and its paralogs increases ROS accumulation, oxidative stress sensitivity, and CEP-1/p53 dependent germ cell apoptosis. Combined deletion of mul-1 paralogs causes constitutive apoptosis, reduced fecundity, and compensatory activation of DAF-16/Foxo and SKN-1/Nrf2 stress response pathways. Together with genetic analysis of SYSM-1, these findings suggest MUL-1-like ShKT proteins buffer oxidative stress.

The nematode Caenorhabditis elegans was the first metazoan to have its genome completely sequenced and assembled. Since that time, researchers have continuously updated the reference genome and manually curated its approximately 20,000 genes. The closely related species, Caenorhabditis briggsae, has served as a comparative model because of its similar morphology, mode of reproduction, and patterns of intra-species genetic variation. However, the genomic resources for C. briggsae lag behind C. elegans, hindering comparative genomics studies between the species. Decades of experimentation have been performed in the AF16 reference strain genetic background, so we obtained high-coverage long-read sequencing and high-throughput chromosome conformation capture data to create an updated reference genome for an isogenic derivative of AF16, named CGC2. The CGC2 genome is vastly improved relative to the existing AF16 assemblies, with no unplaced sequence, no gaps, and telomere-to-telomere contiguity. To provide genomic resources for CGC2, we exploited deep RNA-seq libraries from all developmental stages to predict protein-coding gene annotations comparable in accuracy and completeness to the existing AF16 gene models. We also performed lift-over of 108 validated insertion-deletion variants to the updated coordinate system of the CGC2 genome to facilitate future mappings of mutations. In summary, we present an updated reference genome for the canonical AF16 reference strain with improved genomic resources to enable high-quality intra- and inter-species comparative studies.

The performance of a single cross is determined by the average additive effects of the parents, as well as the interactions between them. These quantities can be estimated using an appropriate genetic design, allowing for the estimation of general (GCA) and specific (SCA) combining abilities. The prediction of GCA for new parents and the total genetic value of unrealized crosses can be made when genome-wide marker information is available. Several studies in crops such as maize and rice have demonstrated the potential of genomic-assisted prediction of single-cross performance in economically important crops. However, no study to date has explored its relevance in perennial ryegrass, an obligate allogamous species that is bred in genetically heterogeneous families. In this study, we aimed to estimate genetic parameters and assess the ability of genomic models to predict the performance of F2 families in terms of dry matter yield and nutritive quality traits. We used data from a large partial diallel involving 104 parents from two distinct subpopulations, as inferred by admixture analysis. F2 families were evaluated in multiple environments and under two nitrogen availability conditions. Genotyping-by-sequencing of the parent plants produced 42,145 variants after quality control, which were used to estimate genomic relationships based on identity-by-state. Variance component estimation revealed limited GCA and SCA interactions with the environment, and particularly with nitrogen management. The predictive abilities of two parental models exceeded 0.60 and often surpassed 0.70 for most traits. However, incorporating non-additive effects into the model did not improve predictive ability. We leveraged the genetic diversity among parents to map genomic regions associated with all recorded traits. Genome-wide association studies (GWAS) by genomic best linear unbiased prediction (GBLUP) identified six quantitative trait loci (QTL) regions, with 45 candidate genes within the linkage disequilibrium range, estimated at approximately 92 kb. Our results demonstrate that genomic prediction of single crosses can be performed with high accuracy, especially when both parents are also progenitors of families in the training set.

Maximum utilization of existing genetic variability in a breeding program depends on the efficient classification of the inbred lines into heterotic groups, particularly under stress conditions. This study applied practical breeding approaches to determine the mode of genetic inheritance for Striga resistance and proposes a weighted heterotic grouping method based on the general combining ability of multiple traits (WHGCAMT) and compares its effectiveness with other existing methods in classifying the inbred lines into heterotic groups in Striga-infested and optimum environments. Using Diallel design IV, 300 crosses were generated from 21 inbred lines and 4 standard testers. The crosses, along with six checks, were evaluated in an 18 x 17 alpha lattice design with two replications at two locations, in both artificial Striga-infested and Striga-free environments. The inbred lines were genotyped using DArTtag SNP markers. Phenotypic and genotypic data were analyzed using R. Analysis of variance revealed significant mean squares for hybrid, general combining ability (GCA), specific combining ability (SCA) and their interactions with environment. Significant positive and negative GCA and SCA effects were detected for grain yield and other measured traits. However, a larger proportion of additive gene action than non-additive gene action was observed for grain yield and most measured traits. The analysis of molecular variance also showed substantial genetic differences within and between clusters. Except for HSCA, the mean grain yield between the inter-group and intra-group hybrids was significant for each method. Pairwise comparison of the inter- and intra-group hybrids of all the methods showed significant differences between the WHGCAMT and all other methods in most cases. WHGCAMT consistently produced higher-yielding inter-group hybrids and lower-yielding intra-group hybrids, achieving breeding efficiency improvements of 55.8%, 4.3%, 15.7%, and 11.4% over the HSCA, HSGCA, HGCAMT and molecular marker methods, respectively, under Striga infestation. Thus, WHGCAMT offers more precise, reliable and biologically meaningful heterotic groups among early-maturing maize inbred lines.

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.

In sunflower (Helianthus annuus L.), the composition of fatty acids in the seeds, primarily oleic, linoleic, stearic and palmitic acid, is of utmost importance for oil quality. Despite this, the genetic basis of this trait and its interaction with the environment is poorly understood. Understanding this interaction is critical to improvement of sunflower within the context of climate change. In this work, we incorporated fatty acid composition measurements from the sunflower SAM population and eight environments across an extensive geographic cline into GWAS. The SAM panel consists of 287 varieties representing approximately 90% of sunflower diversity, for which 2.2 million high-quality SNPs with a MAF > 5% are available. For increased power, multivariate GWAS was performed with four different inputs: (i) mean fatty acid composition within each environment, (ii) mean fatty acid composition within each environment omitting high oleic varieties, (iii) trait stability within environments quantified by standard errors among replicate samples ( stability) and (iv) Eberhart and Russells {beta} which quantifies trait stabilities across environments ({beta} stability). All four analyses yielded highly significantly associated SNPs. We found that high oleic varieties exhibited high {beta} trait stability, resulting in substantial overlap in markers between analyses (i) and (iv), with signals being fairly consistent between environments in analysis (i). For analyses (ii) and (iii), significant markers tended to vary between trials. For significant SNPs across all analyses, 147 candidate genes were identified, including promising candidates such as 15 fatty acid metabolism genes, 6 heat shock proteins and 22 transcription factors. Lastly, a large introgression consisting of two flanking inverted sequences on Chromosome 5 was found to coincide with stability in the Georgia trial, suggesting a role in FA composition stability under high heat conditions.