Rapid genomic evolution in Brassica rapa with bumblebee selection in experimental evolution

Insect pollinators shape rapid phenotypic evolution of traits related to floral attractiveness and plant reproductive success. However, the underlying genomic changes and their impact on standing genetic variation remain largely unknown despite their importance in predicting adaptive responses in nature or in crop’s artificial selection. Here, based on a previous, nine generation experimental evolution study with fast cycling Brassica rapa plants adapting to bumblebees, we document genomic evolution associated to the adaptive process. We performed a genomic scan of the allele frequency changes along the genome and estimated the nucleotide diversity and genomic variance changes. We detected signature of selection associated with rapid changes in allelic frequencies on multiple loci. During experimental evolution, we detected an increase in overall genomic variance, whereas for loci under selection, a reduced variance was apparent in both replicates suggesting a parallel evolution. Our study highlights the polygenic nature of short-term pollinator adaptation and the importance of a such genetic architecture in the maintenance of genomic variance during strong natural selection by biotic factors.

Identification of immune subtypes of Ph-neg B-ALL with ferroptosis related genes and the potential implementation of Sorafenib

Background The clinical outcome of Philadelphia chromosome-negative B cell acute lymphoblastic leukemia (Ph-neg B-ALL) varies considerably from one person to another after clinical treatment due to lack of targeted therapies and leukemia’s heterogeneity. Ferroptosis is a recently discovered programmed cell death strongly correlated with cancers. Nevertheless, few related studies have reported its significance in acute lymphoblastic leukemia. Methods Herein, we collected clinical data of 80 Ph-neg B-ALL patients diagnosed in our center and performed RNA-seq with their initial bone marrow fluid samples. Throughout unsupervised machine learning K-means clustering with 24 ferroptosis related genes (FRGs), the clustered patients were parted into three variant risk groups and were performed with bioinformatics analysis. Results As a result, we discovered significant heterogeneity of both immune microenvironment and genomic variance. Furthermore, the immune check point inhibitors response and potential implementation of Sorafenib in Ph-neg B-ALL was also analyzed in our cohort. Lastly, one prognostic model based on 8 FRGs was developed to evaluate the risk of Ph-neg B-ALL patients. Conclusion Jointly, our study proved the crucial role of ferroptosis in Ph-neg B-ALL and Sorafenib is likely to improve the survival of high-risk Ph-neg B-ALL patients.

Novel Genomic Regions Associated with Intramuscular Fatty Acid Composition in Rabbits

Intramuscular fat (IMF) content and its composition affect the quality of meat. Selection for IMF generated a correlated response on its fatty acid composition. The increase of IMF content is associated with an increase of its saturated (SFA) and monounsaturated (MUFA) fatty acids, and consequently a decrease of polyunsaturated fatty acids (PUFA). We carried out a genome wide association study (GWAS) for IMF composition on two rabbit lines divergently selected for IMF content, using a Bayes B procedure. Association analyses were performed using 475 individuals and 90,235 Single Nucleotide Polymorphisms (SNPs). The main objectives were to identify genomic regions associated with the IMF composition and to generate a list of candidate genes. Genomic regions associated with the intramuscular fatty acid composition were spread across different rabbit chromosomes (OCU). An important region at 34.0–37.9 Mb on OCU1 was associated with C14:0, C16:0, SFA, and C18:2n6, explaining 3.5%, 11.2%, 11.3%, and 3.2% of the genomic variance, respectively. Another relevant genomic region was found to be associated at 46.0–48.9 Mb on OCU18, explaining up to 8% of the genomic variance of MUFA/SFA. The associated regions harbor several genes related to lipid metabolism, such as SCD, PLIN2, and ERLIN1. The main genomic regions associated with the fatty acids were not previously associated with IMF content in rabbits. Nonetheless, MTMR2 is the only gene that was associated with both the IMF content and composition in rabbits. Our study highlighted the polygenic nature of the fatty acids in rabbits and elucidated its genetic background.

Mutations of SARS-CoV-2 nsp14 exhibit strong association with increased genome-wide mutation load

SARS-CoV-2 is a betacoronavirus responsible for COVID-19, a pandemic with global impact that first emerged in late 2019. Since then, the viral genome has shown considerable variance as the disease spread across the world, in part due to the zoonotic origins of the virus and the human host adaptation process. As a virus with an RNA genome that codes for its own genomic replication proteins, mutations in these proteins can significantly impact the variance rate of the genome, affecting both the survival and infection rate of the virus, and attempts at combating the disease. In this study, we analyzed the mutation densities of viral isolates carrying frequently observed mutations for four proteins in the RNA synthesis complex over time in comparison to wildtype isolates. Our observations suggest mutations in nsp14, an error-correcting exonuclease protein, have the strongest association with increased mutation load without selective pressure and across the genome, compared to nsp7, nsp8 and nsp12, which form the core polymerase complex. We propose nsp14 as a priority research target for understanding genomic variance rate in SARS-CoV-2 isolates and nsp14 mutations as potential predictors for high mutability strains.

SNP heritability: What are we estimating?

The SNP heritability has become a central concept in the study of complex traits. Estimation of based on genomic variance components in a linear mixed model using restricted maximum likelihood has been widely adopted as the method of choice were individual level data are available. Empirical results have suggested that this approach is not robust if the population of interest departs from the assumed statistical model. Prolonged debate of the appropriate model choice has yielded a number of approaches to account for frequency- and linkage disequilibrium dependent genetic architectures. Here we analytically resolve the question of how these estimates relate to of the population from which samples are drawn. In particular, we show that the correct model for the purpose of inference about does not require knowledge of the true genetic architecture of a trait. More generally, our results provide a complete perspective of these class of estimators of , highlighting practical shortcomings of current practise. We illustrate our theoretical results using simulations and data from UK Biobank.

Mutations of SARS-CoV-2 nsp14 exhibit strong association with increased genome-wide mutation load

SARS-CoV-2 is a betacoronavirus responsible for human cases of COVID-19, a pandemic with global impact that first emerged in late 2019. Since then, the viral genome has shown considerable variance as the disease spread across the world, in part due to the zoonotic origins of the virus and the human host adaptation process. As a virus with an RNA genome that codes for its own genomic replication proteins, mutations in these proteins can significantly impact the variance rate of the genome, affecting both the survival and infection rate of the virus, and attempts at combating the disease. In this study, we analyzed the mutation densities of viral isolates carrying frequently observed mutations for four proteins in the RNA synthesis complex over time in comparison to wildtype isolates. Our observations suggest mutations in nsp14, an error-correcting exonuclease protein, have the strongest association with increased mutation load in both regions without selective pressure and across the genome, compared to nsp7, 8, and 12, which form the core polymerase complex. We propose nsp14 as a priority research target for understanding genomic variance rate in SARS-CoV-2 isolates, and nsp14 mutations as potential predictors for high mutability strains.

Genomic variance of the 2019-nCoV coronavirus

There is rising global concern for the recently emerged novel Coronavirus (2019-nCov). Full genomic sequences have been released by the worldwide scientific community in the last few weeks in order to understand the evolutionary origin and molecular characteristics of this virus. Taking advantage of all the genomic information currently available, we constructed a phylogenetic tree including also representatives of other coronaviridae, such as Bat coronavirus (BCoV) and SARS. We confirm high sequence similarity (>99%) between all sequenced 2019-nCoVs genomes available, with the closest BCoV sequence sharing 96.2% sequence identity, confirming the notion of a zoonotic origin of 2019-nCoV. Despite the low heterogeneity of the 2019-nCoV genomes, we could identify at least two hyper-variable genomic hotspots, one of which is responsible for a Serine/Leucine variation in the viral ORF8-encoded protein. Finally, we perform a full proteomic comparison with other coronaviridae, identifying key aminoacidic differences to be considered for antiviral strategies deriving from previous anti-coronavirus approaches.

Transcriptomic basis for salt tolerance and disease resistance of silverleaf sunflower revealed by Iso-seq and RNA-seq

Background Silverleaf sunflower, Helianthus argophyllus , is one of the most important wild species that have been usually used for the improvement of cultivated sunflower. Although a reference genome is now available for the cultivated species, H. annuus , its effect in helping understanding the mechanisms underlying the traits of H. argophyllus is limited by the substantial genomic variance between these two species.Results In this study, we generated a high-quality reference transcriptome of H. argophyllus using Iso-seq strategy. This assembly contains 50,153 unique genes covering more than 91% of the whole genes. Among them, we find 205 genes that are absent in the cultivated species and 475 fusion genes containing components of coding or non-coding sequences from the genome of H. annuus . It is interesting that in line with the strong disease resistance observed for H. argophyllus , these H. argophyllus -specific genes are predominantly related to functions of resistance. We have also profiled the gene expressions in leaf and root under normal or salt stressed conditions and, as a result, find distinct transcriptomic responses to salt stress in leaf and root. Particularly, genes involved in several critical processes including the synthesis and metabolism of glutamate and carbohydrate transport are reversely regulated in leaf and root.Conclusions Overall, this study provided insights into the genomic mechanisms underlying the disease resistance and salt tolerance of silverleaf sunflower and the transcriptome assembly and the genes identified in this study can serve as a complement data resources for future research and breeding programs of sunflowers.