G3: Genes|Genomes|Genetics最新文献

Having alternative infection routes is thought to help parasites circumvent host resistance, provided that these routes are associated with different host resistance loci. This study tests this postulate by examining whether alternate infection routes of the parasite Pasteuria ramosa are linked to distinct resistance loci in its crustacean host, Daphnia magna. We focus on the P. ramosa isolate P15, which can attach and penetrate the host through either the hindgut or the foregut. Using a global panel of 174 D. magna genotypes supplemented with breeding experiments, we analyzed resistance patterns for each of these infection routes. Our findings confirm our hypothesis: in D. magna, hindgut attachment is determined by the D locus, while foregut attachment is controlled by a newly identified G locus. We established a gene model for the G locus that indicated Mendelian segregation and epistatic interaction with at least one other resistance locus for P. ramosa, the C locus. Using genomic Pool-sequencing data, we localized the G locus within a known Pasteuria Resistance Complex on chromosome 4 of D. magna, whereas the D locus is on chromosome 7. Two candidate genes for the G locus, belonging to the Glycosyltransferase gene family, were identified. Our study sheds new light on host-parasite coevolution and enhances our understanding of how parasites evolve infection strategies.

Scar-less genome editing in budding yeast with elimination of the selection marker has many advantages. Some markers such as URA3 and TRP1 can be recycled through counterselection. This permits seamless genome modification with pop-in/pop-out (PIPO), in which a DNA construct first integrates in the genome and, subsequently, homologous regions recombine and excise undesired sequences. Popular approaches for creating such constructs use oligonucleotides and polymerase chain reaction (PCR). However, the use of oligonucleotides has many practical disadvantages. With the rapid reduction in price, synthesizing custom DNA sequences in specific plasmid backbones has become an appealing alternative. For designing plasmids for seamless PIPO gene tagging or deletion, there are a number of factors to consider. To create only the shortest DNA sequences necessary, avoid errors in manual design, specify the amount of homology desired, and customize restriction sites, we created the computational tool PIPOline. Using it, we tested the ratios of homology that improve pop-out efficiency when targeting the genes HTB2 or WHI5. We supply optimal PIPO plasmid sequences for tagging or deleting almost all S288C budding yeast open reading frames (ORFs). Finally, we demonstrate how the histone variant Htb2 marked with a red fluorescent protein can be used as a cell-cycle stage marker, alternative to superfolder GFP (sfGPF), reducing light toxicity. We expect PIPOline to streamline genome editing in budding yeast.

Allotopic expression refers to the artificial relocation of an organellar gene to the nucleus. Subunit 2 (Cox2) of cytochrome c oxidase, a subunit with two transmembrane domains (TMS1 and TMS2) residing in the inner mitochondrial membrane with a Nout-Cout topology, is typically encoded in the mitochondrial cox2 gene. In the yeast Saccharomyces cerevisiae, the cox2 gene can be allotopically expressed in the nucleus, yielding a functional protein that restores respiratory growth to a Δcox2 null mutant. In addition to a mitochondrial targeting sequence followed by its natural 15-residue leader peptide, the cytosol synthesized Cox2 precursor must carry one or several amino acid substitutions that decrease the mean hydrophobicity of TMS1 and facilitate its import into the matrix by the TIM23 translocase. Here, using a yeast strain that contains a COX2W56R gene construct inserted in a nuclear chromosome, we searched for genes whose overexpression could facilitate import into mitochondria of the Cox2W56R precursor and increase respiratory growth of the corresponding mutant strain. A COX2W56R expressing strain was transformed with a multicopy plasmid genomic library, and transformants exhibiting enhanced respiratory growth on non-fermentable carbon sources were selected. We identified three genes whose overexpression facilitates the internalization of the Cox2W56R subunit into mitochondria, namely: TYE7, RAS2 and COX12. TYE7 encodes a transcriptional factor, RAS2 a GTP-binding protein, and COX12 a non-core subunit of cytochrome c oxidase. We discuss potential mechanisms by which the TYE7, RAS2 and COX12 gene products could facilitate the import and assembly of the Cox2W56R subunit produced allotopically.

Genotype-phenotype association tests are typically adjusted for population stratification using principal components that are estimated genome-wide. This lacks resolution when analysing populations with fine structure and/or individuals with fine levels of admixture. This can affect power and precision, and is a particularly relevant consideration when control individuals are recruited using geographic selection criteria. Such is the case in France where we have recently created reference panels of individuals anchored to different geographic regions. To make correct comparisons against case groups, who would likely be gathered from large urban areas, new methods are needed. We present SURFBAT (a SURrogate Family Based Association Test) which performs an approximation of the transmission-disequilibrium test. Our method hinges on the application of genotype imputation algorithms to match similar haplotypes between the case and control groups. This permits us to approximate local ancestry informed posterior probabilities of un-transmitted parental alleles of each case individual. This is achieved by assuming haplotypes from the imputation panel are well matched for ancestry with the case individuals. When the first haplotype of an individual from the imputation panel matches that of a case individual, it is assumed that the second haplotype of the same individual can be used as a locally ancestry matched control haplotype and to approximately impute un-transmitted parental alleles. SURFBAT provides an association test that is inherently robust to fine-scale population stratification and opens up the possibility of efficiently using large imputation reference panels as control groups for association testing. In contrast to other methods for association testing that incorporate local-ancestry inference, SURFBAT does not require a set of ancestry groups to be defined, nor for local ancestry to be explicitly estimated. We demonstrate the interest of our tool on simulated datasets, as well as on a real-data example for a group of case individuals affected by Brugada syndrome.

Analyzing human genomic data from biobanks and large-scale genetic evaluations often requires fitting models with a sample size exceeding the number of DNA markers used (n > p). For instance, developing Polygenic Scores (PGS) for humans and genomic prediction for genetic evaluations of agricultural species may require fitting models involving a few thousand SNPs using data with hundreds of thousands of samples. In such cases, computations based on sufficient statistics are more efficient than those based on individual genotype-phenotype data. Additionally, software that admits sufficient statistics as inputs can be used to analyze data from multiple sources jointly without the need to share individual genotype-phenotype data. Therefore, we developed functionality within the BGLR R-package that generates posterior samples for Bayesian shrinkage and variable selection models from sufficient statistics. In this article, we present an overview of the new methods incorporated in the BGLR R-package, demonstrate the use of the new software through simple examples, provide several computational benchmarks, and present a real-data example using data from the UK-Biobank, All of Us, and the HCHS/SOL cohort demonstrating how a joint analysis from multiple cohorts can be implemented without sharing individual genotype-phenotype data, and how a combined analysis can improve the prediction accuracy of PGS for Hispanics--a group severely underrepresented in GWAS data.

With the rise of high-throughput sequencing technologies, a holistic view of genetic variation within populations-through population genomics studies-appears feasible, although it remains an ongoing effort. Genetic variation arises from a diverse range of evolutionary forces, with mutation and recombination being key drivers in shaping genomes. Studying genetic variation within a population represents a crucial first step in understanding the relationship between genotype and phenotype and the evolutionary history of species. In this context, the budding yeast Saccharomyces cerevisiae has been at the forefront of population genomic studies. In addition, it has a complex history that involves adaptation to a wide range of wild and human-related ecological niches. Although to date more than 3,000 diverse isolates have been sequenced, there is currently a lack of a resource bringing together sequencing data and associated metadata for all sequenced isolates. To perform a comprehensive analysis of the population structure of S. cerevisiae, we collected genome sequencing data from 3,034 natural isolates and processed the data uniformly. We determined ploidy levels, identified single nucleotide polymorphisms (SNPs), small insertion-deletions (InDels), copy number variations (CNVs), and aneuploidies across the population, creating a publicly accessible resource for the yeast research community. Interestingly, we showed that this population captures ∼93% of the species diversity. Using neighbor-joining and Bayesian methods, we redefined the populations, revealing clustering patterns primarily based on ecological origin. This work represents a valuable resource for the community and efforts have been made to make it evolvable and integrable to future yeast population studies.

Peppermint, Mentha × piperita L., is a hexaploid (2n = 6x = 72) and the predominant cultivar of commercial mint oil production in the US. This cultivar is threatened because of high susceptibility to the fungal disease verticillium wilt, caused by Verticillium dahliae. This report details the first draft polyploid chromosome-level genome assembly for this mint species. The "Mitcham" genome resource will broaden comparative studies of disease resistance, essential oil biosynthesis, and hybridization events within the genus Mentha. It will also be a valuable contribution to the body of phylogenetic studies involving Mentha and other genera that contain species with varying ploidy levels.

The popularity of genomic selection as an efficient and cost-effective approach to estimate breeding values continues to increase, due in part to the significant saving in phenotyping. Ridge regression is one of the most popular methods used for genomic prediction; however, its efficiency (in terms of prediction performance) depends on the appropriate tunning of the penalization parameter. In this paper we propose a novel, more efficient method to select the optimal penalization parameter for Ridge regression. We compared the proposed method with the conventional method to select the penalization parameter in 14 real data sets and we found that in 13 of these, the proposed method outperformed the conventional method and across data sets the gains in prediction accuracy in terms of Pearson's correlation was of 56.15%, with not-gains observed in terms of normalized mean square error. Finally, our results show evidence of the potential of the proposed method, and we encourage its adoption to improve the selection of candidate lines in the context of plant breeding.