Development and optimization of Lysis gene E as a counter-selection marker with high selection stringency

Seamless modification of bacteria chromosome is widely performed both in theoretical and in practical research, for this purpose, excellent counter-selection marker genes with high selection stringency are needed. Lysis gene E from bacteriophage PhiX174 was developed and optimized as a counter-selection marker in this paper. Lysis gene E was firstly constructed under the control of pL promoter. At 42 °C, Lysis gene E could effectively kill Escherichia coli. Seamless modification using E as a counter-selection marker also successfully conducted. It also works in another Gram-negative strain Serratia marcescens under the control of Arac/PBAD regulatory system. Through combining lysis gene E and kil, the selection stringency frequency of pL-kil-sd-E cassette in E. coli arrived at 4.9×10−8 and 3.2×10−8 at two test loci, which is very close to the best counter-selection system, inducible toxins system. Under the control of Arac/PBAD, selection stringency of PBAD-kil-sd-E in S. marcescens arrived at the level of 10−7 at four test loci. By introducing araC gene harboring plasmid pKDsg-ack, 5- to 18- fold improvement of selection stringency was observed at these loci, and a surprising low selection stringency frequency 4.9×10−9 was obtained at marR-1 locus, the lowest selection stringency frequency for counter-selection reported so far. Similarly, at araB locus of E. coli selection stringency frequency of PBAD-kil-sd-E was improved to 3×10−9 after introducing plasmid pKDsg-ack. In conclusion, we have developed and optimized a newly universal counter-selection marker based on lysis gene E. The best selection stringency of this new marker exceeds the inducible toxins system several fold.

DeepLINK: Deep learning inference using knockoffs with applications to genomics

We propose a deep learning–based knockoffs inference framework, DeepLINK, that guarantees the false discovery rate (FDR) control in high-dimensional settings. DeepLINK is applicable to a broad class of covariate distributions described by the possibly nonlinear latent factor models. It consists of two major parts: an autoencoder network for the knockoff variable construction and a multilayer perceptron network for feature selection with the FDR control. The empirical performance of DeepLINK is investigated through extensive simulation studies, where it is shown to achieve FDR control in feature selection with both high selection power and high prediction accuracy. We also apply DeepLINK to three real data applications to demonstrate its practical utility.

Interplay between extreme drift and selection intensities favors the fixation of beneficial mutations in selfing maize populations

Population and quantitative genetic models provide useful approximations to predict long-term selection responses sustaining phenotypic shifts, and underlying multilocus adaptive dynamics. Valid across a broad range of parameters, their use for understanding the adaptive dynamics of small selfing populations undergoing strong selection intensity (thereafter High Drift-High selection regime, HDHS) remains to be explored. Saclay Divergent Selection Experiments (DSEs) on maize flowering time provide an interesting example of populations evolving under HDHS, with significant selection responses over 20 generations in two directions. We combined experimental data from Saclay DSEs, forward individual-based simulations, and theoretical predictions to dissect the evolutionary mechanisms at play in the observed selection responses. We asked two main questions: How do mutations arise, spread, and reach fixation in populations evolving under HDHS? How does the interplay between drift and selection influence observed phenotypic shifts? We showed that the long-lasting response to selection in small populations is due to the rapid fixation of mutations occurring during the generations of selection. Among fixed mutations, we also found a clear signal of enrichment for beneficial mutations revealing a limited cost of selection. Both environmental stochasticity and variation in selection coefficients likely contributed to exacerbate mutational effects, thereby facilitating selection grasp and fixation of small-effect mutations. Together our results highlight that despite a small number of polymorphic loci expected under HDHS, adaptive variation is continuously fueled by a vast mutational target. We discuss our results in the context of breeding and long-term survival of small selfing populations.

Evaluation of Reference Genes and Expression Level of Genes Potentially Involved in the Mode of Action of Cry1Ac and Cry1F in a Susceptible Reference Strain of Chrysodeixis includens

Soybean looper (SBL), Chrysodeixis includens (Walker), is one of the major lepidopteran pests of soybean in the American continent. SBL control relies mostly on the use of insecticides and genetically modified crops expressing Bacillus thuringiensis (Bt) insecticidal Cry proteins. Due to the high selection pressure exerted by these control measures, resistance has developed to different insecticides and Bt proteins. Nevertheless, studies on the mechanistic background are still scarce. Here, the susceptibility of the laboratory SBL-Benzon strain to the Bt proteins Cry1Ac and Cry1F was determined in diet overlay assays and revealed a greater activity of Cry1Ac than Cry1F, thus confirming results obtained for other sensitive SBL strains. A reference gene study across larval stages with four candidate genes revealed that RPL10 and EF1 were the most stable genes for normalization of gene expression data obtained by RT-qPCR. Finally, the basal expression levels of eight potential Bt protein receptor genes in six larval instars were analyzed, including ATP-binding cassette (ABC) transporters, alkaline phosphatase, aminopeptidases, and cadherin. The results presented here provide fundamental knowledge to support future SBL resistance studies.

The evaluation of genomic diversity and selection signals in the autochthonous Slovak Spotted cattle

The aim of this study was to evaluate the effective population size based on linkage disequilibrium and the trend of inbreeding derived from runs of homozygosity (ROH) in the Slovak Spotted cattle. The ROH segments longer than 4 Mb were then analysed to identify selection signals. Eighty-five individuals were genotyped using the ICBF International Dairy and Beef chip (dams of sires) and Illumina BovineSNP50 BeadChip (sires). The ROH segments > 1 Mb occurred most often in the autosomal genome with an average number of 16.75 ± 7.23. The ROH segments > 16 Mb covering 0.41% of the genome pointed to the long-term effort of breeders to reduce inbreeding in the population of Slovak Spotted cattle. However, the average observed heterozygosity indicated a decrease in overall diversity in the current population. The decrease of heterozygosity per generation also confirmed the estimates of historical and recent effective population size (a decrease of 6.88 animals per generation). The predicted current effective population size was 58 animals. Twenty-one regions across 12 different autosomes were fixed due to the high selection pressure. Within these genomic regions were identified various genes associated with reproduction (SLC9C1, PTPN12), milk production (IGF1, ABCG2), beef production (IFRD1, PTPN4), developmental processes (FMNL2, GLI2), immune system (CD96, CSK) and coat colour (KIT). These selection signals detected in the genome of Slovak Spotted cattle confirm the constant effort of breeders to preserve the dual-purpose nature of this breed.

Glycan-based shaping of the microbiota during primate evolution

Genes encoding glycosyltransferases can be under relatively high selection pressure, likely due to the involvement of the glycans synthesized in host-microbe interactions. Here, we used mice as an experimental model system to investigate whether loss of α−1,3-galactosyltransferase gene (GGTA1) function and Galα1-3Galβ1-4GlcNAcβ1-R (αGal) glycan expression affects host-microbiota interactions, as might have occurred during primate evolution. We found that Ggta1 deletion shaped the composition of the gut microbiota. This occurred via an immunoglobulin (Ig)-dependent mechanism, associated with targeting of αGal-expressing bacteria by IgA. Systemic infection with an Ig-shaped microbiota inoculum elicited a less severe form of sepsis compared to infection with non-Ig-shaped microbiota. This suggests that in the absence of host αGal, antibodies can shape the microbiota towards lower pathogenicity. Given the fitness cost imposed by bacterial sepsis, we infer that the observed reduction in microbiota pathogenicity upon Ggta1 deletion in mice may have contributed to increase the frequency of GGTA1 loss-of-function mutations in ancestral primates that gave rise to humans.

Evolution of Knockdown Resistance Haplotypes in Response to Pyrethroid Selection in Aedes aegypti

This study describes the evolution of knockdown resistance (kdr) haplotypes in Aedes aegypti in response to pyrethroid insecticide use over the course of 18 years in Iquitos, Peru. Based on the duration and intensiveness of sampling (~10,000 samples), this is the most thorough study of kdr population genetics in Ae. aegypti to date within a city. We provide evidence for the direct connection between programmatic citywide pyrethroid spraying and the increase in frequency of specific kdr haplotypes by identifying two evolutionary events in the population. The relatively high selection coefficients, even under infrequent insecticide pressure, emphasizes how quickly populations can evolve. The observed rapid increase in frequency of resistance alleles might have been aided by the incomplete dominance of resistance-conferring alleles over corresponding susceptibility alleles. In addition to dramatic temporal shifts, spatial suppression experiments reveal that genetic heterogeneity existed not only at the citywide scale, but also on a very fine scale within the city.