Natural Genetic Variation Research Articles

ARHGEF26 enhances Salmonella invasion and inflammation in cells and mice.

Salmonella hijack host machinery in order to invade cells and establish infection. While considerable work has described the role of host proteins in invasion, much less is known regarding how natural variation in these invasion-associated host proteins affects Salmonella pathogenesis. Here we leveraged a candidate cellular GWAS screen to identify natural genetic variation in the ARHGEF26 (Rho Guanine Nucleotide Exchange Factor 26) gene that renders lymphoblastoid cells susceptible to Salmonella Typhi and Typhimurium invasion. Experimental follow-up redefined ARHGEF26's role in Salmonella epithelial cell infection. Specifically, we identified complex serovar-by-host interactions whereby ARHGEF26 stimulation of S. Typhi and S. Typhimurium invasion into host cells varied in magnitude and effector-dependence based on host cell type. While ARHGEF26 regulated SopB- and SopE-mediated S. Typhi (but not S. Typhimurium) infection of HeLa cells, the largest effect of ARHGEF26 was observed with S. Typhimurium in polarized MDCK cells through a SopB- and SopE2-independent mechanism. In both cell types, knockdown of the ARHGEF26-associated protein DLG1 resulted in a similar phenotype and serovar specificity. Importantly, we show that ARHGEF26 plays a critical role in S. Typhimurium pathogenesis by contributing to bacterial burden in the enteric fever murine model, as well as inflammation in the colitis infection model. In the enteric fever model, SopB and SopE2 are required for the effects of Arhgef26 deletion on bacterial burden, and the impact of sopB and sopE2 deletion in turn required ARHGEF26. In contrast, SopB and SopE2 were not required for the impacts of Arhgef26 deletion on colitis. A role for ARHGEF26 on inflammation was also seen in cells, as knockdown reduced IL-8 production in HeLa cells. Together, these data reveal pleiotropic roles for ARHGEF26 during infection and highlight that many of the interactions that occur during infection that are thought to be well understood likely have underappreciated complexity.

High photosynthesis rate in two wild rice species is driven by leaf anatomy mediating high Rubisco activity and electron transport rate.

The importance of increasing photosynthetic efficiency for sustainable crop yield increases to feed the growing world population is well recognized. The natural genetic variation in leaf photosynthesis in crop plants is largely unexploited for increasing yield potential. The genus Oryza, including cultivated rice and wild relatives, offers tremendous genetic variability to explore photosynthetic differences and underlying biochemical, photochemical, and developmental traits. We quantified leaf photosynthesis and related physiological parameters for six cultivated and three wild rice genotypes, and identified photosynthetically efficient wild rice accessions. Fitting A/Ci curves and biochemical analyses showed that leaf photosynthesis in cultivated rice varieties IR 64 and Nipponbare was limited due to leaf nitrogen content, Rubisco activity, and electron transport rate compared with photosynthetically efficient wild rice accessions Oryza australiensis and Oryza latifolia. The selected wild rice accessions with high leaf photosynthesis per unit area had anatomical features such as larger mesophyll cells with more chloroplasts, fewer mesophyll cells between two adjacent veins, and higher mesophyll cell and chloroplast surface area exposed to intercellular space. Our results show the existence of desirable variations in Rubisco activity, electron transport rate, and leaf anatomical features that could be targeted for increasing the photosynthetic efficiency of cultivated rice varieties.

Functional convergence of growth responses to shade and warmth in Arabidopsis.

Shade and warmth promote the growth of the stem, but the degree of mechanistic convergence and functional association between these responses is not clear. We analysed the quantitative impact of mutations and natural genetic variation on the hypocotyl growth responses of Arabidopsis thaliana to shade and warmth, the relationship between the abundance of PHYTOCHROME INTERACTING FACTOR 4 (PIF4) and growth stimulation by shade or warmth, the effects of both cues on the transcriptome and the consequences of warm temperature on carbon balance. Growth responses to shade and warmth showed strong genetic linkage and similar dependence on PIF4 levels. Temperature increased growth and phototropism even within a range where damage by extreme high temperatures is unlikely to occur in nature. Both cues enhanced the expression of growth-related genes and reduced the expression of photosynthetic genes. However, only warmth enhanced the expression of genes involved in responses to heat. Warm temperatures substantially increased the amount of light required to compensate for the daily carbon dioxide balance. We propose that the main ecological function of hypocotyl growth responses to warmth is to increase the access of shaded photosynthetic organs to light, which implies functional convergence with shade avoidance.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments.

Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that “all genes affect every complex trait” complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.

The foraging gene affects alcohol sensitivity, metabolism and memory in Drosophila

The genetic basis of alcohol use disorder (AUD) is complex. Understanding how natural genetic variation contributes to alcohol phenotypes can help us identify and understand the genetic basis of AUD. Recently, a single nucleotide polymorphism in the human foraging (for) gene ortholog, Protein Kinase cGMP-Dependent 1 (PRKG1), was found to be associated with stress-induced risk for alcohol abuse. However, the mechanistic role that PRKG1 plays in AUD is not well understood. We use natural variation in the Drosophila for gene to describe how variation of cGMP-dependent protein kinase (PKG) activity modifies ethanol-induced phenotypes. We found that variation in for affects ethanol-induced increases in locomotion and memory of the appetitive properties of ethanol intoxication. Further, these differences may stem from the ability to metabolize ethanol. Together, this data suggests that natural variation in PKG modulates cue reactivity for alcohol, and thus could influence alcohol cravings by differentially modulating metabolic and behavioral sensitivities to alcohol.

Natural genetic variation drives microbiome selection in the Caenorhabditis elegans gut

Host genetic landscapes can shape microbiome assembly in the animal gut by contributing to the establishment of distinct physiological environments. However, the genetic determinants contributing to the stability and variation of these microbiome types remain largely undefined. Here, we use the free-living nematode Caenorhabditis elegans to identify natural genetic variation among wild strains of C.elegans that drives assembly of distinct microbiomes. To achieve this, we first established a diverse model microbiome that represents the strain-level phylogenetic diversity naturally encountered by C.elegans in the wild. Using this community, we show that C.elegans utilizes immune, xenobiotic, and metabolic signaling pathways to favor the assembly of different microbiome types. Variations in these pathways were associated with enrichment for specific commensals, including the Alphaproteobacteria Ochrobactrum. Using RNAi and mutant strains, we showed that host selection for Ochrobactrum is mediated specifically by host insulin signaling pathways. Ochrobactrum recruitment is blunted in the absence of DAF-2/IGFR and modulated by the competitive action of insulin signaling transcription factors DAF-16/FOXO and PQM-1/SALL2. Further, the ability of C.elegans to enrich for Ochrobactrum as adults is correlated with faster animal growth rates and larger body size at the end of development. These results highlight a new role for the highly conserved insulin signaling pathways in the regulation of gut microbiome composition in C.elegans.

A Tandem Mass Tags (TMTs) labeling approach highlights differences between the shoot proteome of two Arabidopsis thaliana ecotypes, Col-0 and Ws.

Arabidopsis has become a powerful model to study morphogenesis, plant growth, development but also plant response to environmental conditions. Over 1000 Arabidopsis genomes are available and show natural genetic variations. Among them, the main reference accessions Wassilewskija (Ws) and Columbia (Col-0), originally growing at contrasted altitudes and temperatures, are widely studied, but data contributing to their molecular phenotyping are still scarce. A global quantitative proteomics approach using isobaric stable isotope labeling (Tandem Mass Tags, TMT) was performed on Ws and Col-0. Plants have been hydroponically grown at 16 h/8 h (light/dark cycle) at 23°C day/19°C night for three weeks. A TMT labeling of the proteins extracted from their shoots has been performed and showed a differential pattern of protein abundance between them. These results have allowed identifying several proteins families possibly involved in the differential responses observed for Ws and Col-0 during plant development and upon environmental changes. In particular, Ws and Col-0 mainly differ in photosynthesis, cell wall-related proteins, plant defense/stress, ROS scavenging enzymes/redox homeostasis and DNA/RNA binding/transcription/translation/protein folding.

Natural Genetic Diversity in the Potato Resistance Gene RB Confers Suppression Avoidance from Phytophthora Effector IPI-O4.

RB is a potato gene that provides resistance to a broad spectrum of genotypes of the late blight pathogen Phytophthora infestans. RB belongs to the CC-NB-LRR (coiled-coil, nucleotide-binding, leucine-rich repeat) class of resistance (R) genes, a major component of the plant immune system. The RB protein detects the presence of class I and II IPI-O effectors from P. infestans to initiate a hypersensitive resistance response, but this activity is suppressed in the presence of the Class III effector IPI-O4. Using natural genetic variation of RB within potato wild relatives, we identified two amino acids in the CC domain that alter interactions needed for suppression of resistance by IPI-O4. We have found that separate modification of these amino acids in RB can diminish or expand the resistance capability of this protein against P. infestans in both Nicotiana benthamiana and potato. Our results demonstrate that increased knowledge of the molecular mechanisms that determine resistance activation and R protein suppression by effectors can be utilized to tailor-engineer genes with the potential to provide increased durability.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Gene-based mapping of trehalose biosynthetic pathway genes reveals association with source- and sink-related yield traits in a spring wheat panel.

Trehalose 6‐phosphate (T6P) signalling regulates carbon use and allocation and is a target to improve crop yields. However, the specific contributions of trehalose phosphate synthase (TPS) and trehalose phosphate phosphatase (TPP) genes to source‐ and sink‐related traits remain largely unknown. We used enrichment capture sequencing on TPS and TPP genes to estimate and partition the genetic variation of yield‐related traits in a spring wheat (Triticum aestivum) breeding panel specifically built to capture the diversity across the 75,000 CIMMYT wheat cultivar collection. Twelve phenotypes were correlated to variation in TPS and TPP genes including plant height and biomass (source), spikelets per spike, spike growth and grain filling traits (sink) which showed indications of both positive and negative gene selection. Individual genes explained proportions of heritability for biomass and grain‐related traits. Three TPS1 homologues were particularly significant for trait variation. Epistatic interactions were found within and between the TPS and TPP gene families for both plant height and grain‐related traits. Gene‐based prediction improved predictive ability for grain weight when gene effects were combined with the whole‐genome markers. Our study has generated a wealth of information on natural variation of TPS and TPP genes related to yield potential which confirms the role for T6P in resource allocation and in affecting traits such as grain number and size confirming other studies which now opens up the possibility of harnessing natural genetic variation more widely to better understand the contribution of native genes to yield traits for incorporation into breeding programmes.

Detection of genetic variation and activity analysis of the promoter region of the cattle tRNA-modified gene TRDMT1.

The tRNA modification gene in eukaryotes is relatively conservative. As an important modification gene, the TRDMT1 gene plays an important role in maintaining tRNA structural maintenance and reducing mistranslation of protein translation by methylation of specific tRNA subpopulations. Mouse and zebrafish TRDMT1 knockout experiments indicate that it may mediate growth and development through tRNA modification. However, there are no systematic reports on the function of tRNA-modified genes in livestock. In this study, Qinchuan cattle DNA pool sequencing technology was used. A GC mutation in the bp position upstream of the TRDMT1 translation initiator codon was found. At this locus, the dual-luciferase assay indicated that different genotypes cause differences in transcriptional activity (). Our experiment detected a natural genetic variation of a tRNA modification gene TRDMT1, which may provide potential natural molecular materials for the study of tRNA modification.

A complex genetic architecture in zebrafish relatives Danio quagga and D. kyathit underlies development of stripes and spots.

Vertebrate pigmentation is a fundamentally important, multifaceted phenotype. Zebrafish, Danio rerio, has been a valuable model for understanding genetics and development of pigment pattern formation due to its genetic and experimental tractability, advantages that are shared across several Danio species having a striking array of pigment patterns. Here, we use the sister species D. quagga and D. kyathit, with stripes and spots, respectively, to understand how natural genetic variation impacts phenotypes at cellular and organismal levels. We first show that D. quagga and D. kyathit phenotypes resemble those of wild-type D. rerio and several single locus mutants of D. rerio, respectively, in a morphospace defined by pattern variation along dorsoventral and anteroposterior axes. We then identify differences in patterning at the cellular level between D. quagga and D. kyathit by repeated daily imaging during pattern development and quantitative comparisons of adult phenotypes, revealing that patterns are similar initially but diverge ontogenetically. To assess the genetic architecture of these differences, we employ reduced-representation sequencing of second-generation hybrids. Despite the similarity of D. quagga to D. rerio, and D. kyathit to some D. rerio mutants, our analyses reveal a complex genetic basis for differences between D. quagga and D. kyathit, with several quantitative trait loci contributing to variation in overall pattern and cellular phenotypes, epistatic interactions between loci, and abundant segregating variation within species. Our findings provide a window into the evolutionary genetics of pattern-forming mechanisms in Danio and highlight the complexity of differences that can arise even between sister species. Further studies of natural genetic diversity underlying pattern variation in D. quagga and D. kyathit should provide insights complementary to those from zebrafish mutant phenotypes and more distant species comparisons.

Nitrogen Use Efficiency in Sorghum: Exploring Native Variability for Traits Under Variable N-Regimes.

Exploring the natural genetic variability and its exploitation for improved Nitrogen Use Efficiency (NUE) in sorghum is one of the primary goals in the modern crop improvement programs. The integrated strategies include high-throughput phenotyping, next generation sequencing (NGS)-based genotyping technologies, and a priori selected candidate gene studies that help understand the detailed physiological and molecular mechanisms underpinning this complex trait. A set of sixty diverse sorghum genotypes was evaluated for different vegetative, reproductive, and yield traits related to NUE in the field (under three N regimes) for two seasons. Significant variations for different yield and related traits under 0 and 50% N confirmed the availability of native genetic variability in sorghum under low N regimes. Sorghum genotypes with distinct genetic background had interestingly similar NUE associated traits. The Genotyping-By-Sequencing based SNPs (>89 K) were used to study the population structure, and phylogenetic groupings identified three distinct groups. The information of grain N and stalk N content of the individuals covered on the phylogenetic groups indicated randomness in the distribution for adaptation under variable N regimes. This study identified promising sorghum genotypes with consistent performance under varying environments, with buffer capacity for yield under low N conditions. We also report better performing genotypes for varied production use—grain, stover, and dual-purpose sorghum having differential adaptation response to NUE traits. Expression profiling of NUE associated genes in shoot and root tissues of contrasting lines (PVK801 and HDW703) grown in varying N conditions revealed interesting outcomes. Root tissues of contrasting lines exhibited differential expression profiles for transporter genes [ammonium transporter (SbAMT), nitrate transporters (SbNRT)]; primary assimilatory (glutamine synthetase (SbGS), glutamate synthase (SbGOGAT[NADH], SbGOGAT[Fd]), assimilatory genes [nitrite reductase (SbNiR[NADH]3)]; and amino acid biosynthesis associated gene [glutamate dehydrogenase (SbGDH)]. Identification and expression profiling of contrasting sorghum genotypes in varying N dosages will provide new information to understand the response of NUE genes toward adaptation to the differential N regimes in sorghum. High NUE genotypes identified from this study could be potential candidates for in-depth molecular analysis and contribute toward the development of N efficient sorghum cultivars.

Population and subspecies diversity at mouse centromere satellites

BackgroundMammalian centromeres are satellite-rich chromatin domains that execute conserved roles in kinetochore assembly and chromosome segregation. Centromere satellites evolve rapidly between species, but little is known about population-level diversity across these loci.ResultsWe developed a k-mer based method to quantify centromere copy number and sequence variation from whole genome sequencing data. We applied this method to diverse inbred and wild house mouse (Mus musculus) genomes to profile diversity across the core centromere (minor) satellite and the pericentromeric (major) satellite repeat. We show that minor satellite copy number varies more than 10-fold among inbred mouse strains, whereas major satellite copy numbers span a 3-fold range. In contrast to widely held assumptions about the homogeneity of mouse centromere repeats, we uncover marked satellite sequence heterogeneity within single genomes, with diversity levels across the minor satellite exceeding those at the major satellite. Analyses in wild-caught mice implicate subspecies and population origin as significant determinants of variation in satellite copy number and satellite heterogeneity. Intriguingly, we also find that wild-caught mice harbor dramatically reduced minor satellite copy number and elevated satellite sequence heterogeneity compared to inbred strains, suggesting that inbreeding may reshape centromere architecture in pronounced ways.ConclusionTaken together, our results highlight the power of k-mer based approaches for probing variation across repetitive regions, provide an initial portrait of centromere variation across Mus musculus, and lay the groundwork for future functional studies on the consequences of natural genetic variation at these essential chromatin domains.

Integrative analysis of liver-specific non-coding regulatory SNPs associated with the risk of coronary artery disease

Genetic factors underlying coronary artery disease (CAD) have been widely studied using genome-wide association studies (GWASs). However, the functional understanding of the CAD loci has been limited by the fact that a majority of GWAS variants are located within non-coding regions with no functional role. High cholesterol and dysregulation of the liver metabolism such as non-alcoholic fatty liver disease confer an increased risk of CAD. Here, we studied the function of non-coding single-nucleotide polymorphisms in CAD GWAS loci located within liver-specific enhancer elements by identifying their potential target genes using liver cis-eQTL analysis and promoter Capture Hi-C in HepG2 cells. Altogether, 734 target genes were identified of which 121 exhibited correlations to liver-related traits. To identify potentially causal regulatory SNPs, the allele-specific enhancer activity was analyzed by (1) sequence-based computational predictions, (2) quantification of allele-specific transcription factor binding, and (3) STARR-seq massively parallel reporter assay. Altogether, our analysis identified 1,277 unique SNPs that display allele-specific regulatory activity. Among these, susceptibility enhancers near important cholesterol homeostasis genes (APOB, APOC1, APOE, and LIPA) were identified, suggesting that altered gene regulatory activity could represent another way by which genetic variation regulates serum lipoprotein levels. Using CRISPR-based perturbation, we demonstrate how the deletion/activation of a single enhancer leads to changes in the expression of many target genes located in a shared chromatin interaction domain. Our integrative genomics approach represents a comprehensive effort in identifying putative causal regulatory regions and target genes that could predispose to clinical manifestation of CAD by affecting liver function.

Genome-wide association study on metabolite accumulation in a wild barley NAM population reveals natural variation in sugar metabolism.

Metabolites play a key role in plants as they are routing plant developmental processes and are involved in biotic and abiotic stress responses. Their analysis can offer important information on the underlying processes. Regarding plant breeding, metabolite concentrations can be used as biomarkers instead of or in addition to genetic markers to predict important phenotypic traits (metabolic prediction). In this study, we applied a genome-wide association study (GWAS) in a wild barley nested association mapping (NAM) population to identify metabolic quantitative trait loci (mQTL). A set of approximately 130 metabolites, measured at early and late sampling dates, was analysed. For four metabolites from the early and six metabolites from the late sampling date significant mQTL (grouped as 19 mQTL for the early and 25 mQTL for the late sampling date) were found. Interestingly, all of those metabolites could be classified as sugars. Sugars are known to be involved in signalling, plant growth and plant development. Sugar-related genes, encoding mainly sugar transporters, have been identified as candidate genes for most of the mQTL. Moreover, several of them co-localized with known flowering time genes like Ppd-H1, HvELF3, Vrn-H1, Vrn-H2 and Vrn-H3, hinting on the known role of sugars in flowering. Furthermore, numerous disease resistance-related genes were detected, pointing to the signalling function of sugars in plant resistance. An mQTL on chromosome 1H in the region of 13 Mbp to 20 Mbp stood out, that alone explained up to 65% of the phenotypic variation of a single metabolite. Analysis of family-specific effects within the diverse NAM population showed the available natural genetic variation regarding sugar metabolites due to different wild alleles. The study represents a step towards a better understanding of the genetic components of metabolite accumulation, especially sugars, thereby linking them to biological functions in barley.

Assessment of Genetic Variability and Traits Association in Pigeonpea [Cajanus cajan (L.) Millsp.] Germplasm

Background: Pigeon pea is an important dietary protein source for humans but the production was constrained by various biotic and abiotic factors. Breeding strategies were followed to improve yield and developing high yielding varieties but at the same time utilization of genetic resources have declined. Pigeon pea is native to India with huge natural genetic variability in the local germplasm and its wild relatives. So it is necessary to identify and select breeding material from germplasm with considerable genetic and morphological variability to utilize in breeding programmes. As an initial study, 200 pre-breeding lines developed were evaluated for morphological variability patterns.Methods: A total of two hundred lines selected from F4 generation of pigeon pea developed at ICAR-NBPGR were evaluated in Randomized Block design (RBD) during 2014-2015 kharif season under Indo-Swiss collaboration in Biotechnology at Agricultural College and Research Institute, Madurai (TNAU). The accessions found to be superior in seed yield than the local check APK1were forwarded to the next generation (2015-2016) for assessment of genetic variability, heritability, genetic advance and association studies.Result: Qualitative traits were evaluated and variation in leaflet shape, stem colour, pattern of streaks and base seed colour were observed. All tested lines expressed greater variability for most of the traits. Maximum coefficient of variation was observed for number of pods per plant followed by number of primary branches per plant. Selection of traits with moderate heritability coupled with high genetic advance like number of pods per plant, number of primary branches per plant could help in crop improvement program. Seed yield was positively correlated with number of seeds per pod, number of pods per plant and hundred seed weight. Potential genetic stocks and donors for high yield were selected based on hundred seed weight and seeds per pod. The accessions superior in number of pods and seed yield than check were forwarded to next generation for assessment. The identified trait-specific accessions will help in future breeding program.

Natural genetic variation determines microglia heterogeneity in wild-derived mouse models of Alzheimer’s disease

SUMMARYGenetic and genome-wide association studies suggest a central role for microglia in Alzheimer’s disease (AD). However, single-cell RNA sequencing (scRNA-seq) of microglia in mice, a key preclinical model, has shown mixed results regarding translatability to human studies. To address this, scRNA-seq of microglia from C57BL/6J (B6) and wild-derived strains (WSB/EiJ, CAST/EiJ, and PWK/PhJ) with and without APP/PS1 demonstrates that genetic diversity significantly alters features and dynamics of microglia in baseline neuroimmune functions and in response to amyloidosis. Results show significant variation in the abundance of microglial subtypes or states, including numbers of previously identified disease-associated and interferon-responding microglia, across the strains. For each subtype, significant differences in the expression of many genes are observed in wild-derived strains relative to B6, including 19 genes previously associated with human AD including Apoe, Trem2, and Sorl1. This resource is critical in the development of appropriately targeted therapeutics for AD and other neurological diseases.

Identification and validation of SNPs in the phytoene synthase 2 (psy2) gene associated with yellow color of the root in cassava (Manihot esculenta Crantz) accessions of the Brazilian Amazon

The biofortification of cassava (Manihot esculenta Crantz) roots is one of the actual goals of genetic breeding, with the development of roots richer in carotenoids. In order to evaluate the natural genetic variation of cassava, this study analyzed 78 accessions from the Brazilian Amazon to verify the presence of single nucleotide polymorphism (SNP) molecular markers in the phytoene synthase 2 (psy2) gene associated with root color. From the sequencing of 294 bp containing part of the intron 2 and the exon 3 of the psy2 gene, three SNPs located in the coding region and the existence of eight haplotypes were identified. The c.1434G > C (SNP1) and c.1485C > A (SNP3) variations were found in yellow and cream root accessions and nucleotide polymorphism resulted in amino acid substitution. SNP2 (c.1462T > C) was identified in accessions with white roots and its allelic variation did not result in amino acid substitution. Four haplotypes that presented SNP3 were widely distributed in the states of Para, Amapa, Rondonia and Amazonas. All accessions of yellow or cream root that presented the SNP3 were in heterozygosity, confirming the dominance of the SNP, except for one accession, that could be used in genetic breeding. The effect of mutations on the structure and function of PSY2 was in silico evaluated by molecular dynamics and it was indicated that the aminoacid substitutions affected the active site of the protein depending on the distance. The results were compatible with the phenotype detected experimentally.

Identification of genetic variation for salt tolerance in Brassica napus using genome-wide association mapping.

Soil salinity negatively impacts rapeseed (Brassica napus) crop production. In particular, high soil salinity is known to hinder seedling growth and establishment. Identifying natural genetic variation for high salt tolerance in Brassica napus seedlings is an effective way to breed for improved productivity under salt stress. To identify genetic variants involved in differential response to salt stress, we evaluated a diverse association panel of 228 Brasica napus accessions for four seedling traits under salt stress to establish stress susceptibility index (SSI) and stress tolerance index (STI) values, and performed genome-wide association studies (GWAS) using 201,817 high-quality single nucleotide polymorphic (SNP) markers. Our GWAS identified 142 significant SNP markers strongly associated with salt tolerance distributed across all rapeseed chromosomes, with 78 SNPs in the C genome and 64 SNPs in the A genome, and our analyses subsequently pinpointed both favorable alleles and elite cultivars. We identified 117 possible candidate genes associated with these SNPs: 95/117 were orthologous with Arabidopsis thaliana genes encoding transcription factors, aquaporins, and binding proteins. The expression level of ten candidate genes was validated by quantitative real-time PCR (qRT-PCR), and these genes were found to be differentially expressed between salt-tolerant and salt-susceptible lines under salt stress conditions. Our results provide new genetic resources and information for improving salt tolerance in rapeseed genotypes at the seed germination and seedling stages via genomic or marker-assisted selection, and for future functional characterization of putative gene candidates.

Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus.

As whole genome sequencing is becoming more accessible and affordable for clinical microbiological diagnostics, the reliability of genotypic antimicrobial resistance (AMR) prediction from sequencing data is an important issue to address. Computational AMR prediction can be performed at multiple levels. The first-level approach, such as simple AMR search relies heavily on the quality of the information fed into the database. However, AMR due to mutations are often undetected, since this is not included in the database or poorly documented. Using co-trimoxazole (trimethoprim-sulfamethoxazole) resistance in Staphylococcus aureus, we compared single-level and multi-level analysis to investigate the strengths and weaknesses of both approaches. The results revealed that a single mutation in the AMR gene on the nucleotide level may produce false positive results, which could have been detected if protein sequence analysis would have been performed. For AMR predictions based on chromosomal mutations, such as the folP gene of S. aureus, natural genetic variations should be taken into account to differentiate between variants linked to genetic lineage (MLST) and not over-estimate the potential resistant variants. Our study showed that careful analysis of the whole genome data and additional criterion such as lineage-independent mutations may be useful for identification of mutations leading to phenotypic resistance. Furthermore, the creation of reliable database for point mutations is needed to fully automatized AMR prediction.