PhylteR: Efficient Identification of Outlier Sequences in Phylogenomic Datasets.

In phylogenomics, incongruences between gene trees, resulting from both artifactual and biological reasons, can decrease the signal-to-noise ratio and complicate species tree inference. The amount of data handled today in classical phylogenomic analyses precludes manual error detection and removal. However, a simple and efficient way to automate the identification of outliers from a collection of gene trees is still missing. Here, we present PhylteR, a method that allows rapid and accurate detection of outlier sequences in phylogenomic datasets, i.e. species from individual gene trees that do not follow the general trend. PhylteR relies on DISTATIS, an extension of multidimensional scaling to 3 dimensions to compare multiple distance matrices at once. In PhylteR, these distance matrices extracted from individual gene phylogenies represent evolutionary distances between species according to each gene. On simulated datasets, we show that PhylteR identifies outliers with more sensitivity and precision than a comparable existing method. We also show that PhylteR is not sensitive to ILS-induced incongruences, which is a desirable feature. On a biological dataset of 14,463 genes for 53 species previously assembled for Carnivora phylogenomics, we show (i) that PhylteR identifies as outliers sequences that can be considered as such by other means, and (ii) that the removal of these sequences improves the concordance between the gene trees and the species tree. Thanks to the generation of numerous graphical outputs, PhylteR also allows for the rapid and easy visual characterization of the dataset at hand, thus aiding in the precise identification of errors. PhylteR is distributed as an R package on CRAN and as containerized versions (docker and singularity).

Genetic diversity and epidemic histories of rice yellow mottle virus in Ghana.

Rice yellow mottle virus (RYMV) has persisted as a major biotic constraint to rice production in Africa. However, no data on RYMV epidemics were available in Ghana, although it is an intensive rice-producing country. Surveys were performed from 2010 to 2020 in eleven rice-growing regions of Ghana. Symptom observations and serological detections confirmed that RYMV is circulating in most of these regions. Coat protein gene and complete genome sequencings revealed that RYMV in Ghana almost exclusively belongs to the strain S2, one of the strains covering the largest area in West Africa. We also detected the presence of the S1ca strain which is being reported for the first time outside its area of origin. These results suggested a complex epidemiological history of RYMV in Ghana and a recent expansion of S1ca to West Africa. Phylogeographic analyses reconstructed at least five independent RYMV introductions in Ghana for the last 40 years, probably due to rice cultivation intensification in West Africa leading to a better circulation of RYMV. In addition to identifying some routes of RYMV dispersion in Ghana, this study contributes to the epidemiological surveillance of RYMV and helps to design disease management strategies, especially through breeding for rice disease resistance.

GeMo: a web-based platform for the visualization and curation of genome ancestry mosaics.

In silico chromosome painting is a technique by which contributions of distinct genetic groups are represented along chromosomes of hybrid individuals. This type of analysis is used to study the mechanisms by which these individuals were formed. Such techniques are well adapted to identify genetic groups contributing to these individuals as well as hybridization events. It can also be used to follow chromosomal recombinations that occurred naturally or were generated by selective breeding. Here, we present GeMo, a novel interactive web-based and user-oriented interface to visualize in a linear-based fashion results of in silico chromosome painting. To facilitate data input generation, a script to execute analytical commands is provided and an interactive data curation mode is supported to ensure consistency of the automated procedure. GeMo contains preloaded datasets from published studies on crop domestication but can be applied to other purposes, such as breeding programs Although only applied so far on plants, GeMo can handle data from animals as well. Database URL: https://gemo.southgreen.fr/.

An atypical class of non-coding small RNAs is produced in rice leaves upon bacterial infection.

Non-coding small RNAs (sRNA) act as mediators of gene silencing and regulate plant growth, development and stress responses. Early insights into plant sRNAs established a role in antiviral defense and they are now extensively studied across plant-microbe interactions. Here, sRNA sequencing discovered a class of sRNA in rice (Oryza sativa) specifically associated with foliar diseases caused by Xanthomonas oryzae bacteria. Xanthomonas-induced small RNAs (xisRNAs) loci were distinctively upregulated in response to diverse virulent strains at an early stage of infection producing a single duplex of 20-22 nt sRNAs. xisRNAs production was dependent on the Type III secretion system, a major bacterial virulence factor for host colonization. xisRNA loci overlap with annotated transcripts sequences, with about half of them encoding protein kinase domain proteins. A number of the corresponding rice cis-genes have documented functions in immune signaling and xisRNA loci predominantly coincide with the coding sequence of a conserved kinase motif. xisRNAs exhibit features of small interfering RNAs and their biosynthesis depend on canonical components OsDCL1 and OsHEN1. xisRNA induction possibly mediates post-transcriptional gene silencing but they do not broadly suppress cis-genes expression on the basis of mRNA-seq data. Overall, our results identify a group of unusual sRNAs with a potential role in plant-microbe interactions.

Genotyping by sequencing can reveal the complex mosaic genomes in gene pools resulting from reticulate evolution: a case study in diploid and polyploid citrus.

BACKGROUND AND AIMS: Reticulate evolution, coupled with reproductive features limiting further interspecific recombinations, results in admixed mosaics of large genomic fragments from the ancestral taxa. Whole-genome sequencing (WGS) data are powerful tools to decipher such complex genomes but still too costly to be used for large populations. The aim of this work was to develop an approach to infer phylogenomic structures in diploid, triploid and tetraploid individuals from sequencing data in reduced genome complexity libraries. The approach was applied to the cultivated Citrus gene pool resulting from reticulate evolution involving four ancestral taxa, C. maxima, C. medica, C. micrantha and C. reticulata. METHODS: A genotyping by sequencing library was established with the restriction enzyme ApeKI applying one base (A) selection. Diagnostic single nucleotide polymorphisms (DSNPs) for the four ancestral taxa were mined in 29 representative varieties. A generic pipeline based on a maximum likelihood analysis of the number of read data was established to infer ancestral contributions along the genome of diploid, triploid and tetraploid individuals. The pipeline was applied to 48 diploid, four triploid and one tetraploid citrus accessions. KEY RESULTS: Among 43 598 mined SNPs, we identified a set of 15 946 DSNPs covering the whole genome with a distribution similar to that of gene sequences. The set efficiently inferred the phylogenomic karyotype of the 53 analysed accessions, providing patterns for common accessions very close to that previously established using WGS data. The complex phylogenomic karyotypes of 21 cultivated citrus, including bergamot, triploid and tetraploid limes, were revealed for the first time. CONCLUSIONS: The pipeline, available online, efficiently inferred the phylogenomic structures of diploid, triploid and tetraploid citrus. It will be useful for any species whose reproductive behaviour resulted in an interspecific mosaic of large genomic fragments. It can also be used for the first generations of interspecific breeding schemes.