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At least 55 records · Page 3

Description of a novel extremophile green algae, Chlamydomonas pacifica , and its potential as a biotechnology host

We present the comprehensive characterization of a newly identified microalga, Chlamydomonas pacifica , originally isolated from a soil sample in San Diego, CA, USA. This species showcases remarkable biological versatility, including a broad pH range tolerance (6–11.5), high thermal tolerance (up to 42 °C), and salinity resilience (up to 2 % NaCl). Its amenability to genetic manipulation and sexual reproduction via mating, particularly between the two opposing strains CC-5697 & CC-5699, now publicly available through the Chlamydomonas Resource Center, underscores its potential as a biotechnological chassis. The biological assessment of C. pacifica revealed versatile metabolic capabilities, including diverse nitrogen assimilation capability, motility and phototaxis. Genomic and transcriptomic analyses identified 17,829 genes within a 121 Mb genome, featuring a GC content of 61 %. The codon usage of C. pacifica closely mirrors that of C. reinhardtii , indicating a conserved genetic architecture that supports a trend in codon preference with minor variations. Phylogenetic analyses position C. pacifica within the core-Reinhardtinia clade yet distinct from known Volvocales species. The lipidomic data revealed an abundance of triacylglycerols (TAGs), promising for biofuel applications and lipids for health-related benefits. Our investigation lays the groundwork for exploiting C. pacifica in biotechnological applications, from biofuel generation to synthesizing biodegradable plastics, positioning it as a versatile host for future bioengineering endeavors.

Alkali tolerant↗

BrainXcan identifies brain features associated with behavioral and psychiatric traits using large-scale genetic and imaging data

Advances in brain MRI have enabled many discoveries in neuroscience. Case-control comparisons of brain MRI features have highlighted potential causes of psychiatric and behavioral disorders. However, due to the cost and difficulty of collecting MRI data, most studies have small sample sizes, limiting their reliability. Furthermore, reverse causality complicates interpretation because many observed brain differences are the result rather than the cause of the disease. Here we propose a method (BrainXcan) that leverages the power of large-scale genomewide association studies (GWAS) and reference brain MRI data to discover new mechanisms of disease etiology and validate existing ones. BrainXcan tests the association with genetic predictors of brain MRI-derived features and complex traits to pinpoint relevant brain-wide and region-specific features. Requiring only genetic data, BrainXcan allows us to test a host of hypotheses on mental illness, across many MRI modalities, using public data resources. For example, our method shows that reduced axonal density across the brain is associated with schizophrenia risk, consistent with the disconnectivity hypothesis. We also find that the hippocampus volume is associated with schizophrenia risk, highlighting the potential of our approach. Taken together, our results show the promise of BrainXcan to provide insights into the biology of GWAS traits.

Association study↗

Genetics of gene expression in the aging human brain reveal TDP-43 proteinopathy pathophysiology

Genetic variants that control distant gene expression are highly relevant for disease mechanisms but remain poorly charaterized. Here, leveraging the modular structure of gene coexpression in the aging human brain, we performed genome-wide association studies of gene coexpression modules and identified TMEM106B and RBFOX1 as module quantitative trait loci (modQTLs). The TMEM106B modQTL is a known risk locus of neurodegenerative TDP-43 proteinopathy and has a large-scale dominant transcriptomic effect including lysosomal and splicing dysregulation, recapitulating TDP-43 pathophysiology. Further, a locus in another TDP-43 proteinopathy risk gene, GRN, shows similar transcriptomic effects. TMEM106B and APOE/amyloid-ß converge on altered myelination/lysosomal gene expression, and jointly promote limbic-predominant age-related TDP-43 encephalopathy neuropathological change. Thus, genetic architecture of distant gene expression in the aging human brain elucidates TDP-43 proteinopathy pathophysiology.

Yang, Hyun-Sik↗

A genome-wide association study of suicide attempts in the million veterans program identifies evidence of pan-ancestry and ancestry-specific risk loci

In this study, to identify pan-ancestry and ancestry-specific loci associated with attempting suicide among veterans, we conducted a genome-wide association study (GWAS) of suicide attempts within a large, multi-ancestry cohort of U.S. veterans enrolled in the Million Veterans Program (MVP). Cases were defined as veterans with a documented history of suicide attempts in the electronic health record (EHR; N = 14,089) and controls were defined as veterans with no documented history of suicidal thoughts or behaviors in the EHR ( N = 395,064). GWAS was performed separately in each ancestry group, controlling for sex, age and genetic substructure. Pan-ancestry risk loci were identified through meta-analysis and included two genome-wide significant loci on chromosomes 20 ( p = 3.64 × 10 -9 ) and 1 ( p = 3.69 × 10 -8 ). A strong pan-ancestry signal at the Dopamine Receptor D2 locus ( p = 1.77 × 10 -7 ) was also identified and subsequently replicated in a large, independent international civilian cohort ( p = 7.97 × 10 -4 ). Additionally, ancestry-specific genome-wide significant loci were also detected in African-Americans, European-Americans, Asian-Americans, and Hispanic-Americans. Pathway analyses suggested over-representation of many biological pathways with high clinical significance, including oxytocin signaling, glutamatergic synapse, cortisol synthesis and secretion, dopaminergic synapse, and circadian rhythm. These findings confirm that the genetic architecture underlying suicide attempt risk is complex and includes both pan-ancestry and ancestry-specific risk loci. Moreover, pathway analyses suggested many commonly impacted biological pathways that could inform development of improved therapeutics for suicide prevention.

60 APPLIED LIFE SCIENCES↗

Mutational signatures in tumours induced by high and low energy radiation in Trp53 deficient mice

Lonising radiation (IR) is a recognised carcinogen responsible for cancer development in patients previously treated using radiotherapy, and in individuals exposed as a result of accidents at nuclear energy plants. However, the mutational signatures induced by distinct types and doses of radiation are unknown. Here, we analyse the genetic architecture of mammary tumours, lymphomas and sarcomas induced by high ( 56 Fe-ions) or low (gamma) energy radiation in mice carrying Trp53 loss of function alleles. In mammary tumours, high-energy radiation is associated with induction of focal structural variants, leading to genomic instability and Met amplification. Gamma-radiation is linked to large-scale structural variants and a point mutation signature associated with oxidative stress. The genomic architecture of carcinomas, sarcomas and lymphomas arising in the same animals are significantly different. Our study illustrates the complex interactions between radiation quality, germline Trp53 deficiency and tissue/cell of origin in shaping the genomic landscape of IR-induced tumours.

Science & Technology - Other Topics↗

Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees

There is overwhelming evidence that forest trees are locally adapted to climate. Thus, genecological models based on population phenotypes have been used to measure local adaptation, infer genetic maladaptation to climate, and guide assisted migration. However, instead of phenotypes, there is increasing interest in using genomic data for gene resource management. We used whole-genome resequencing and common-garden experiments to understand the genetic architecture of adaptive traits in black cottonwood. We studied the potential of using genome-wide association studies (GWAS) and genomic prediction to detect causal loci, identify climate-adapted phenotypes, and inform gene resource management. We analyzed population structure by partitioning phenotypic and genomic (single-nucleotide polymorphism) variation among 840 genotypes collected from 91 stands along 16 rivers. Most phenotypic variation (60 to 81%) occurred among populations and was strongly associated with climate. Population phenotypes were predicted well using genomic data (e.g., predictive abilityr> 0.9) but almost as well using climate or geography (r> 0.8). In contrast, genomic prediction within populations was poor (r< 0.2). We identified many GWAS associations among populations, but most appeared to be spurious based on pooled within-population analyses. Hierarchical partitioning of linkage disequilibrium and haplotype sharing suggested that within-population genomic prediction and GWAS were poor because allele frequencies of causal loci and linked markers differed among populations. Given the urgent need to conserve natural populations and ecosystems, our results suggest that climate variables alone can be used to predict population phenotypes, delineate seed zones and deployment zones, and guide assisted migration.

Science & Technology - Other Topics↗

Linkage mapping evidence for a syntenic QTL associated with flowering time in perennial C 4 rhizomatous grasses Miscanthus and switchgrass

Flowering in perennial species is directed via complex signalling pathways that adjust to developmental regulations and environmental cues. Synchronized flowering in certain environments is a prerequisite to commercial seed production, and so the elucidation of the genetic architecture of flowering time in Miscanthus and switchgrass could aid breeding in these underdeveloped species. In this context, we assessed a mapping population in Miscanthus and two ecologically diverse switchgrass mapping populations over 3 years from planting. Multiple flowering time quantitative trait loci (QTL) were identified in both species. Remarkably, the most significant Miscanthus and switchgrass QTL proved to be syntenic, located on linkage groups 4 and 2, with logarithm of odds scores of 17.05 and 21.8 respectively. These QTL regions contained three flowering time transcription factors: Squamosa Promoter-binding protein-Like, MADS-box SEPELLATA2 and gibberellin-responsive bHLH137. The former is emerging as a key component of the age-related flowering time pathway.

54 ENVIRONMENTAL SCIENCES↗

Genomic approaches to accelerate American chestnut restoration

More than a century after two introduced pathogens killed billions of American chestnut trees, introgression of resistance alleles from Chinese chestnuts has contributed to the recovery of self-sustaining populations. However, progress has been slow because of the complex genetic architecture of resistance. To better understand blight resistance, we compared reference genomes, gene expression responses, and stem metabolite profiles of the resistant Chinese and susceptible American chestnut species. To accelerate resistance breeding, we conducted large-scale phenotyping and genotyping in hybrids of these species. Simulation and inoculation experiments suggest that significant resistance gains are possible through selectively breeding trees with an average of 70 to 85% American chestnut ancestry. In conclusion, the resources developed in this work are foundational for breeding to create diverse restoration populations with sufficient disease resistance and competitive growth.

Westbrook, Jared W. [The American Chestnut Foundat↗

rBahadur: efficient simulation of structured high-dimensional genotype data with applications to assortative mating

Existing methods for generating synthetic genotype data are ill-suited for replicating the effects of assortative mating (AM). We propose rb_dplr, a novel and computationally efficient algorithm for generating high-dimensional binary random variates that effectively recapitulates AM-induced genetic architectures using the Bahadur order-2 approximation of the multivariate Bernoulli distribution. The rBahadur R library is available through the Comprehensive R Archive Network at https://CRAN.R-project.org/package=rBahadur.

59 BASIC BIOLOGICAL SCIENCES↗

COMPILE: a GWAS computational pipeline for gene discovery in complex genomes

Abstract Background Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity. Results COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer ( Ostrinia nubilalis ). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity. Conclusions The relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing Non-Food Grade Brassica Biofuel Feedstock Cultivars with High Yield, Oil Content, and Oil Quality that are Suitable for Low Input Production Dryland Systems (Final Report)

The U.S. uses a substantial amount of fossil fuel as an energy source for a wide range for functions including home heating, agriculture and transportation. In the transportation sector, diesel and jet fuel are consumed at a rapid rate, and alternative liquid energy is being investigated globally and nationally to reduce our dependence on fossil fuel and reduce the impact of our carbon footprint on global climate change. Non-food Brassica crops have the potential of producing high oil yield (over 250 gal acre-1) and have oil quality highly desirable for use as biodiesel or bio jet fuel. Developing oilseed feedstock Brassica cultivars with higher seed and oil yield, with high oil quality and with resistance to pathogens, that can be grown with few chemical inputs will helping break our dependence on fossil fuels and reduce importation of fossil fuels. While some oilseed Brassicas have been grown on a small scale for many years in the Pacific Northwest (PNW), adoption has been limited, and the potential of the crops have not been realized or even fully investigated. This report summarizes the results of a study to develop superior non-food grade winter (B. napus) and spring (B. napus and B. juncea) oilseed cultivars suitable for a range of PNW, and other US environments with high resistance to the biotic and abiotic stresses suitable for high-quality biofuel feedstocks. In conducting this work, genome-wide association selection was used to dissect the genetic architecture of industrial Brassica oilseed germplasm for yield, quality, and resistance to biotic and abiotic stresses. A genome-wide bioinformatics approach was used to identify putative PRR (pattern recognition receptor) - type resistance genes that confer durable resistance to blackleg. A novel transgenic approach was developed to generate resistant non-food oilseed lines using PPR genes Br1033 and Br8486. These genes were inserted into regionally adapted oilseed cultivars.

09 BIOMASS FUELS↗

Inhibition of ethylene involved in resistance to E. turcicum in an exotic-derived double haploid maize population

Northern corn leaf blight (NCLB) is an economically important disease of maize. While the genetic architecture of NCLB has been well characterized, the pathogen is known to overcome currently deployed resistance genes, and the role of hormones in resistance to NCLB is an area of active research. The objectives of the study were (i) to identify significant markers associated with resistance to NCLB, (ii) to identify metabolic pathways associated with NCLB resistance, and (iii) to examine role of ethylene in resistance to NCLB. We screened 252 lines from the exotic-derived double haploid BGEM maize population for resistance to NCLB in both field and greenhouse environments. We used a genome wide association study (GWAS) and stepwise regression to identify four markers associated with resistance, followed by a pathway association study tool (PAST) to identify important metabolic pathways associated with disease severity and incubation period. The ethylene synthesis pathway was significant for disease severity and incubation period. We conducted a greenhouse assay in which we inhibited ethylene to examine the role of ethylene in resistance to NCLB. We observed a significant increase in incubation period and a significant decrease in disease severity between plants treated with the ethylene inhibitor and mock-treated plants. Our study confirms the potential of the BGEM population as a source of novel alleles for resistance. We also confirm the role of ethylene in resistance to NCLB and contribute to the growing body of literature on ethylene and disease resistance in monocots.

59 BASIC BIOLOGICAL SCIENCES↗

Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic control of root architectural plasticity in maize

Root phenotypes regulate soil resource acquisition; however, their genetic control and phenotypic plasticity are poorly understood. We hypothesized that the responses of root architectural phenes to water deficit (stress plasticity) and different environments (environmental plasticity) are under genetic control and that these loci are distinct. Root architectural phenes were phenotyped in the field using a large maize association panel with and without water deficit stress for three seasons in Arizona and without water deficit stress for four seasons in South Africa. All root phenes were plastic and varied in their plastic response. We identified candidate genes associated with stress and environmental plasticity and candidate genes associated with phenes in well-watered conditions in South Africa and in well-watered and water-stress conditions in Arizona. Few candidate genes for plasticity overlapped with those for phenes expressed under each condition. Our results suggest that phenotypic plasticity is highly quantitative, and plasticity loci are distinct from loci that control phene expression in stress and non-stress, which poses a challenge for breeding programs. To make these loci more accessible to the wider research community, we developed a public online resource that will allow for further experimental validation towards understanding the genetic control underlying phenotypic plasticity.

59 BASIC BIOLOGICAL SCIENCES↗

Unveiling shared genetic regulators of plant architectural and biomass yield traits in the Sorghum Association Panel

Abstract Sorghum is emerging as an ideal genetic model for designing high-biomass bioenergy crops. Biomass yield, a complex trait influenced by various plant architectural characteristics, is typically regulated by numerous genes. This study aimed to dissect the genetic regulators underlying 14 plant architectural traits and 10 biomass yield traits in the Sorghum Association Panel across two growing seasons. We identified 321 associated loci through genome-wide association studies (GWAS), involving 234 264 single nucleotide polymorphisms (SNPs). These loci include genes with known associations to biomass traits, such as maturity, dwarfing (Dw), and leafbladeless1, as well as several uncharacterized loci not previously linked to these traits. We also identified 22 pleiotropic loci associated with variation in multiple phenotypes. Three of these loci, located on chromosomes 3 (S03_15463061), 6 (S06_42790178; Dw2), and 9 (S09_57005346; Dw1), exerted significant and consistent effects on multiple traits across both growing seasons. Additionally, we identified three genomic hotspots on chromosomes 6, 7, and 9, each containing multiple SNPs associated with variation in plant architecture and biomass yield traits. Chromosome-wise correlation analyses revealed multiple blocks of positively associated SNPs located near or within the same genomic regions. Finally, genome-wide correlation-based network analysis showed that loci associated with flowering, plant height, leaf traits, plant density, and tiller number per plant were highly interconnected with other genetic loci influencing plant architectural and biomass yield traits. The pyramiding of favorable alleles related to these traits holds promise for enhancing the future development of bioenergy sorghum crops.

Singh, Anuradha (ORCID:0000000197149095)↗

Phenome‐to‐genome insights for evaluating root system architecture in field studies of maize

Abstract Understanding the genetic basis of root system architecture (RSA) in crops requires innovative approaches that enable both high‐throughput and precise phenotyping in field conditions. In this study, we evaluated multiple phenotyping and analytical frameworks for quantifying RSA in mature, field‐grown maize in three field experiments. We used forward and reverse genetic approaches to evaluate >1700 maize root crowns, including a diversity panel, a biparental mapping population, and maize mutant and wild‐type alleles at two known RSA genes,DEEPER ROOTING 1(DRO1) andRootless1(Rt1). We show the utility of increasing the dimensionality of traditional two‐dimensional (2D) techniques, referred to as the “2D multi‐view” method, to improve the capture of whole root system information for mapping genetic variation influencing RSA. Comparison of univariate and multivariate genome‐wide association study (GWAS) approaches revealed that multivariate traits were effective at dissecting complex RSA phenotypes and identifying pleiotropic quantitative trait loci (QTLs). Overall, three‐dimensional (3D) root models generated from X‐ray computed tomography and digital phenotyping captured a larger proportion of RSA trait variations compared to other methods of root phenotyping, as evidenced by both genome‐wide and single‐gene analyses. Among the individual root traits, root pulling force emerged as a highly heritable estimate of RSA that identified the largest number of shared QTLs with 3D phenotypes. Our study shows that integrating complementary phenotyping technologies helps to provide a more comprehensive understanding of the genetic architecture of RSA in field‐grown maize.

Genetics & Heredity↗

Integration of high-density genetic mapping with transcriptome analysis uncovers numerous agronomic QTL and reveals candidate genes for the control of tillering in sorghum

Phenotypes such as branching, photoperiod sensitivity, and height were modified during plant domestication and crop improvement. Here, we perform quantitative trait locus (QTL) mapping of these and other agronomic traits in a recombinant inbred line (RIL) population derived from an interspecific cross between Sorghum propinquum and Sorghum bicolor inbred Tx7000. Using low-coverage Illumina sequencing and a bin-mapping approach, we generated ~1920 bin markers spanning ~875 cM. Phenotyping data were collected and analyzed from two field locations and one greenhouse experiment for six agronomic traits, thereby identifying a total of 30 QTL. Many of these QTL were penetrant across environments and co-mapped with major QTL identified in other studies. Other QTL uncovered new genomic regions associated with these traits, and some of these were environment-specific in their action. To further dissect the genetic underpinnings of tillering, we complemented QTL analysis with transcriptomics, identifying 6189 genes that were differentially expressed during tiller bud elongation. We identified genes such as Dormancy Associated Protein 1 (DRM1) in addition to various transcription factors that are differentially expressed in comparisons of dormant to elongating tiller buds and lie within tillering QTL, suggesting that these genes are key regulators of tiller elongation in sorghum. Our study demonstrates the usefulness of this RIL population in detecting domestication and improvement-associated genes in sorghum, thus providing a valuable resource for genetic investigation and improvement to the sorghum community.

59 BASIC BIOLOGICAL SCIENCES↗

A genetic link between leaf carbon isotope composition and whole-plant water use efficiency in the C 4 grass Setaria

Genetic selection for whole-plant water use efficiency (yield per transpiration; WUE plant ) in any crop-breeding programme requires high-throughput phenotyping of component traits of WUE plant such as intrinsic water use efficiency (WUE i ; CO 2 assimilation rate per stomatal conductance). Measuring WUE i by gas exchange measurements is laborious and time consuming and may not reflect an integrated WUE i over the life of the leaf. Alternatively, leaf carbon stable isotope composition (δ 13 C leaf ) has been suggested as a potential time-ntegrated proxy for WUE i that may provide a tool to screen for WUE plant . However, a genetic link between δ 13 C leaf and WUE plant in a C 4 species has not been well established. Thus, to confirm if there is a genetic relationship in a C 4 plant between δ 13 C leaf and WUE plant under well watered and water-limited growth conditions, a high-throughput phenotyping facility was used to measure WUE plant in a recombinant inbred line (RIL) population created between the C 4 grasses Setaria viridis and S. italica . Three quantitative trait loci (QTL) for δ 13 C leaf were found and co-localized with transpiration, biomass accumulation, and WUE plant . Additionally, WUE plant for each of the δ 13 C leaf QTL allele classes was negatively correlated with δ 13 C leaf , as would be predicted when WUE i influences WUE plant . These findings demonstrate that δ 13 C leaf is genetically linked to WUE plant , likely to be through their relationship with WUE i , and can be used as a high-throughput proxy to screen for WUE plant in these C 4 species.

59 BASIC BIOLOGICAL SCIENCES↗