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Auto Tag: Triticum

April 21, 2020  |  

Blast Fungal Genomes Show Frequent Chromosomal Changes, Gene Gains and Losses, and Effector Gene Turnover.

Pyricularia is a fungal genus comprising several pathogenic species causing the blast disease in monocots. Pyricularia oryzae, the best-known species, infects rice, wheat, finger millet, and other crops. As past comparative and population genomics studies mainly focused on isolates of P. oryzae, the genomes of the other Pyricularia species have not been well explored. In this study, we obtained a chromosomal-level genome assembly of the finger millet isolate P. oryzae MZ5-1-6 and also highly contiguous assemblies of Pyricularia sp. LS, P. grisea, and P. pennisetigena. The differences in the genomic content of repetitive DNA sequences could largely explain the variation in genome size among these new genomes. Moreover, we found extensive gene gains and losses and structural changes among Pyricularia genomes, including a large interchromosomal translocation. We searched for homologs of known blast effectors across fungal taxa and found that most avirulence effectors are specific to Pyricularia, whereas many other effectors share homologs with distant fungal taxa. In particular, we discovered a novel effector family with metalloprotease activity, distinct from the well-known AVR-Pita family. We predicted 751 gene families containing putative effectors in 7 Pyricularia genomes and found that 60 of them showed differential expression in the P. oryzae MZ5-1-6 transcriptomes obtained under experimental conditions mimicking the pathogen infection process. In summary, this study increased our understanding of the structural, functional, and evolutionary genomics of the blast pathogen and identified new potential effector genes, providing useful data for developing crops with durable resistance. © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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April 21, 2020  |  

Hybrid sequencing reveals insight into heat sensing and signaling of bread wheat.

Wheat (Triticum aestivum L.), a globally important crop, is challenged by increasing temperatures (heat stress, HS). However its polyploid nature, the incompleteness of its genome sequences and annotation, the lack of comprehensive HS-responsive transcriptomes and the unexplored heat sensing and signaling of wheat hinder our full understanding of its adaptations to HS. The recently released genome sequences of wheat, as well as emerging single-molecular sequencing technologies, provide an opportunity to thoroughly investigate the molecular mechanisms of the wheat response to HS. We generated a high-resolution spatio-temporal transcriptome map of wheat flag leaves and filling grain under HS at 0 min, 5 min, 10 min, 30 min, 1 h and 4 h by combining full-length single-molecular sequencing and Illumina short reads sequencing. This hybrid sequencing newly discovered 4947 loci and 70 285 transcripts, generating the comprehensive and dynamic list of HS-responsive full-length transcripts and complementing the recently released wheat reference genome. Large-scale analysis revealed a global landscape of heat adaptations, uncovering unexpected rapid heat sensing and signaling, significant changes of more than half of HS-responsive genes within 30 min, heat shock factor-dependent and -independent heat signaling, and metabolic alterations in early HS-responses. Integrated analysis also demonstrated the differential responses and partitioned functions between organs and subgenomes, and suggested a differential pattern of transcriptional and alternative splicing regulation in the HS response. This study provided comprehensive data for dissecting molecular mechanisms of early HS responses in wheat and highlighted the genomic plasticity and evolutionary divergence of polyploidy wheat. © 2019 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

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April 21, 2020  |  

A Pathovar of Xanthomonas oryzae Infecting Wild Grasses Provides Insight Into the Evolution of Pathogenicity in Rice Agroecosystems

Xanthomonas oryzae (Xo) are critical rice pathogens. Virulent lineages from Africa and Asia and less virulent strains from the US have been well characterized. X. campestris pv. leersiae (Xcl), first described in 1957, causes bacterial streak on the perennial grass, Leersia hexandra, and is a close relative of Xo. L. hexandra, a member of the Poaceae, is highly similar to rice phylogenetically, is globally ubiquitous around rice paddies, and is a reservoir of pathogenic Xo. We used long read, single molecule, real time (SMRT) genome sequences of five strains of Xcl from Burkina Faso, China, Mali and Uganda to determine the genetic relatedness of this organism with Xo. Novel Transcription Activator-Like Effectors (TALEs) were discovered in all five strains of Xcl. Predicted TALE target sequences were identified in the L. perrieri genome and compared to rice susceptibility gene homologs. Pathogenicity screening on L. hexandra and diverse rice cultivars confirmed that Xcl are able to colonize rice and produce weak but not progressive symptoms. Overall, based on average nucleotide identity, type III effector repertoires and disease phenotype, we propose to rename Xcl to X. oryzae pv. leersiae (Xol) and use this parallel system to improve understanding of the evolution of bacterial pathogenicity in rice agroecosystems.

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April 21, 2020  |  

A hybrid de novo genome assembly of the honeybee, Apis mellifera, with chromosome-length scaffolds.

The ability to generate long sequencing reads and access long-range linkage information is revolutionizing the quality and completeness of genome assemblies. Here we use a hybrid approach that combines data from four genome sequencing and mapping technologies to generate a new genome assembly of the honeybee Apis mellifera. We first generated contigs based on PacBio sequencing libraries, which were then merged with linked-read 10x Chromium data followed by scaffolding using a BioNano optical genome map and a Hi-C chromatin interaction map, complemented by a genetic linkage map.Each of the assembly steps reduced the number of gaps and incorporated a substantial amount of additional sequence into scaffolds. The new assembly (Amel_HAv3) is significantly more contiguous and complete than the previous one (Amel_4.5), based mainly on Sanger sequencing reads. N50 of contigs is 120-fold higher (5.381 Mbp compared to 0.053 Mbp) and we anchor >?98% of the sequence to chromosomes. All of the 16 chromosomes are represented as single scaffolds with an average of three sequence gaps per chromosome. The improvements are largely due to the inclusion of repetitive sequence that was unplaced in previous assemblies. In particular, our assembly is highly contiguous across centromeres and telomeres and includes hundreds of AvaI and AluI repeats associated with these features.The improved assembly will be of utility for refining gene models, studying genome function, mapping functional genetic variation, identification of structural variants, and comparative genomics.

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April 21, 2020  |  

Genome sequencing and comparison of five Tilletia species to identify candidate genes for the detection of regulated species infecting wheat

Tilletia species cause diseases on grass hosts with some causing bunt diseases on wheat (Triticum). Two of the four species infecting wheat have restricted distributions globally and are subject to quarantine regulations to prevent their spread to new areas. Tilletia indica causes Karnal bunt and is regulated by many countries while the non-regulated T. walkeri is morphologically similar and very closely related phylogenetically, but infects ryegrass (Lolium) and not wheat. Tilletia controversa causes dwarf bunt of wheat (DB) and is also regulated by some countries, while the closely related but non-regulated species, T. caries and T. laevis, both cause common bunt of wheat (CB). Historically, diagnostic methods have relied on cryptic morphology to differentiate these species in subsamples from grain shipments. Of the DNA-based methods published so far, most have focused on sequence variation among tested strains at a single gene locus. To facilitate the development of additional molecular assays for diagnostics, we generated whole genome data for multiple strains of the two regulated wheat pathogens and their closest relatives. Depending on the species, the genomes were assembled into 907 to 4633 scaffolds ranging from 24?Mb to 30?Mb with 7842 to 9952 gene models predicted. Phylogenomic analyses confirmed the placement of Tilletia in the Exobasidiomycetes and showed that T. indica and T. walkeri were in one clade whereas T. controversa, T. caries and T. laevis grouped in a separate clade. Single copy and species-specific genes were identified by orthologous group analysis. Unique species-specific genes were identified and evaluated as suitable markers to differentiate the quarantine and non-quarantine species. After further analyses and manual inspection, primers and probes for the optimum candidate genes were designed and tested in silico, for validation in future wet-lab studies.

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April 21, 2020  |  

External memory BWT and LCP computation for sequence collections with applications

Background: Sequencing technologies produce larger and larger collections of biosequences that have to be stored in compressed indices supporting fast search operations. Many compressed indices are based on the Bur- rows–Wheeler Transform (BWT) and the longest common prefix (LCP) array. Because of the sheer size of the input it is important to build these data structures in external memory and time using in the best possible way the available RAM. Results: We propose a space-efficient algorithm to compute the BWT and LCP array for a collection of sequences in the external or semi-external memory setting. Our algorithm splits the input collection into subcollections sufficiently small that it can compute their BWT in RAM using an optimal linear time algorithm. Next, it merges the partial BWTs in external or semi-external memory and in the process it also computes the LCP values. Our algorithm can be modi- fied to output two additional arrays that, combined with the BWT and LCP array, provide simple, scan-based, external memory algorithms for three well known problems in bioinformatics: the computation of maximal repeats, the all pairs suffix–prefix overlaps, and the construction of succinct de Bruijn graphs. Conclusions: We prove that our algorithm performs O(nmaxlcp) sequential I/Os, where n is the total length of the collection and maxlcp is the maximum LCP value. The experimental results show that our algorithm is only slightly slower than the state of the art for short sequences but it is up to 40 times faster for longer sequences or when the available RAM is at least equal to the size of the input.

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