Targeting conserved secreted effectors to control rice blast.

Plant pathogens usually secrete effectors to suppress the host immune response, resulting in effector-triggered susceptibility (ETS). Plants use nucleotide-binding leucine-rich repeat receptors (NLRs) to detect specific effectors and elicit effector-triggered immunity (ETI). Two recent papers (Liu et al. and Zhang et al.) have made promising progress in controlling rice blast by modulating ETS and ETI.

A sensitive one-pot ROA assay for rapid miRNA detection.

MicroRNAs (miRNAs) and short RNA fragments (18-25 nt) are crucial biomarkers in biological research and disease diagnostics. However, their accurate and rapid detection remains a challenge, largely due to their low abundance, short length, and sequence similarities. In this study, we report on a highly sensitive, one-step RNA O-circle amplification (ROA) assay for rapid and accurate miRNA detection. The ROA assay commences with the hybridization of a circular probe with the test RNA, followed by a linear rolling circle amplification (RCA) using dUTP. This amplification process is facilitated by U-nick reactions, which lead to an exponential amplification for readout. Under optimized conditions, assays can be completed within an hour, producing an amplification yield up to the microgram level, with a detection limit as low as 0.15 fmol (6 pM). Notably, the ROA assay requires only one step, and the results can be easily read visually, making it user-friendly. This ROA assay has proven effective in detecting various miRNAs and phage ssRNA. Overall, the ROA assay offers a user-friendly, rapid, and accurate solution for miRNA detection. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-024-00140-0.

BSAlign: A Library for Nucleotide Sequence Alignment.

Increasing the accuracy of the nucleotide sequence alignment is an essential issue in genomics research. Although classic dynamic programming (DP) algorithms (e.g., Smith-Waterman and Needleman-Wunsch) guarantee to produce the optimal result, their time complexity hinders the application of large-scale sequence alignment. Many optimization efforts that aim to accelerate the alignment process generally come from three perspectives: redesigning data structures [e.g., diagonal or striped Single Instruction Multiple Data (SIMD) implementations], increasing the number of parallelisms in SIMD operations (e.g., difference recurrence relation), or reducing search space (e.g., banded DP). However, no methods combine all these three aspects to build an ultra-fast algorithm. In this study, we developed a Banded Striped Aligner (BSAlign) library that delivers accurate alignment results at an ultra-fast speed by knitting a series of novel methods together to take advantage of all of the aforementioned three perspectives with highlights such as active F-loop in striped vectorization and striped move in banded DP. We applied our new acceleration design on both regular and edit distance pairwise alignment. BSAlign achieved 2-fold speed-up than other SIMD-based implementations for regular pairwise alignment, and 1.5-fold to 4-fold speed-up in edit distance-based implementations for long reads. BSAlign is implemented in C programing language and is available at https://github.com/ruanjue/bsalign.

Chloroplast and whole-genome sequencing shed light on the evolutionary history and phenotypic diversification of peanuts.

Cultivated peanut (Arachis hypogaea L.) is a widely grown oilseed crop worldwide; however, the events leading to its origin and diversification are not fully understood. Here by combining chloroplast and whole-genome sequence data from a large germplasm collection, we show that the two subspecies of A. hypogaea (hypogaea and fastigiata) likely arose from distinct allopolyploidization and domestication events. Peanut genetic clusters were then differentiated in relation to dissemination routes and breeding efforts. A combination of linkage mapping and genome-wide association studies allowed us to characterize genes and genomic regions related to main peanut morpho-agronomic traits, namely flowering pattern, inner tegument color, growth habit, pod/seed weight and oil content. Together, our findings shed light on the evolutionary history and phenotypic diversification of peanuts and might be of broad interest to plant breeders.

Low-input PacBio sequencing generates high-quality individual fly genomes and characterizes mutational processes.

Long-read sequencing, exemplified by PacBio, revolutionizes genomics, overcoming challenges like repetitive sequences. However, the high DNA requirement ( > 1 µg) is prohibitive for small organisms. We develop a low-input (100 ng), low-cost, and amplification-free library-generation method for PacBio sequencing (LILAP) using Tn5-based tagmentation and DNA circularization within one tube. We test LILAP with two Drosophila melanogaster individuals, and generate near-complete genomes, surpassing preexisting single-fly genomes. By analyzing variations in these two genomes, we characterize mutational processes: complex transpositions (transposon insertions together with extra duplications and/or deletions) prefer regions characterized by non-B DNA structures, and gene conversion of transposons occurs on both DNA and RNA levels. Concurrently, we generate two complete assemblies for the endosymbiotic bacterium Wolbachia in these flies and similarly detect transposon conversion. Thus, LILAP promises a broad PacBio sequencing adoption for not only mutational studies of flies and their symbionts but also explorations of other small organisms or precious samples.

HiTE: a fast and accurate dynamic boundary adjustment approach for full-length transposable element detection and annotation.

Recent advancements in genome assembly have greatly improved the prospects for comprehensive annotation of Transposable Elements (TEs). However, existing methods for TE annotation using genome assemblies suffer from limited accuracy and robustness, requiring extensive manual editing. In addition, the currently available gold-standard TE databases are not comprehensive, even for extensively studied species, highlighting the critical need for an automated TE detection method to supplement existing repositories. In this study, we introduce HiTE, a fast and accurate dynamic boundary adjustment approach designed to detect full-length TEs. The experimental results demonstrate that HiTE outperforms RepeatModeler2, the state-of-the-art tool, across various species. Furthermore, HiTE has identified numerous novel transposons with well-defined structures containing protein-coding domains, some of which are directly inserted within crucial genes, leading to direct alterations in gene expression. A Nextflow version of HiTE is also available, with enhanced parallelism, reproducibility, and portability.

Overcoming the High Error Rate of Composite DNA Letters-Based Digital Storage through Soft-Decision Decoding.

Composite DNA letters, by merging all four DNA nucleotides in specified ratios, offer a pathway to substantially increase the logical density of DNA digital storage (DDS) systems. However, these letters are susceptible to nucleotide errors and sampling bias, leading to a high letter error rate, which complicates precise data retrieval and augments reading expenses. To address this, Derrick-cp is introduced as an innovative soft-decision decoding algorithm tailored for DDS utilizing composite letters. Derrick-cp capitalizes on the distinctive error sensitivities among letters to accurately predict and rectify letter errors, thus enhancing the error-correcting performance of Reed-Solomon codes beyond traditional hard-decision decoding limits. Through comparative analyses in the existing dataset and simulated experiments, Derrick-cp's superiority is validated, notably halving the sequencing depth requirement and slashing costs by up to 22% against conventional hard-decision strategies. This advancement signals Derrick-cp's significant role in elevating both the precision and cost-efficiency of composite letter-based DDS.

An effective strategy for assembling the sex-limited chromosome.

BACKGROUND: Most currently available reference genomes lack the sequence map of sex-limited (such as Y and W) chromosomes, which results in incomplete assemblies that hinder further research on sex chromosomes. Recent advancements in long-read sequencing and population sequencing have provided the opportunity to assemble sex-limited chromosomes without the traditional complicated experimental efforts. FINDINGS: We introduce the first computational method, Sorting long Reads of Y or other sex-limited chromosome (SRY), which achieves improved assembly results compared to flow sorting. Specifically, SRY outperforms in the heterochromatic region and demonstrates comparable performance in other regions. Furthermore, SRY enhances the capabilities of the hybrid assembly software, resulting in improved continuity and accuracy. CONCLUSIONS: Our method enables true complete genome assembly and facilitates downstream research of sex-limited chromosomes.

NextDenovo: an efficient error correction and accurate assembly tool for noisy long reads.

Long-read sequencing data, particularly those derived from the Oxford Nanopore sequencing platform, tend to exhibit high error rates. Here, we present NextDenovo, an efficient error correction and assembly tool for noisy long reads, which achieves a high level of accuracy in genome assembly. We apply NextDenovo to assemble 35 diverse human genomes from around the world using Nanopore long-read data. These genomes allow us to identify the landscape of segmental duplication and gene copy number variation in modern human populations. The use of NextDenovo should pave the way for population-scale long-read assembly using Nanopore long-read data.

KSNP: a fast de Bruijn graph-based haplotyping tool approaching data-in time cost.

Long reads that cover more variants per read raise opportunities for accurate haplotype construction, whereas the genotype errors of single nucleotide polymorphisms pose great computational challenges for haplotyping tools. Here we introduce KSNP, an efficient haplotype construction tool based on the de Bruijn graph (DBG). KSNP leverages the ability of DBG in handling high-throughput erroneous reads to tackle the challenges. Compared to other notable tools in this field, KSNP achieves at least 5-fold speedup while producing comparable haplotype results. The time required for assembling human haplotypes is reduced to nearly the data-in time.