ABSTRACT
BACKGROUND: Phenotyping of plant traits presents a significant bottleneck in Quantitative Trait Loci (QTL) mapping and genome-wide association studies (GWAS). Computerized phenotyping using digital images promises rapid, robust, and reproducible measurements of dimension, shape, and color traits of plant organs, including grain, leaf, and floral traits. RESULTS: We introduce GRABSEEDS, which is specifically tailored to extract a comprehensive set of features from plant images based on state-of-the-art computer vision and deep learning methods. This command-line enabled tool, which is adept at managing varying light conditions, background disturbances, and overlapping objects, uses digital images to measure plant organ characteristics accurately and efficiently. GRABSEED has advanced features including label recognition and color correction in a batch setting. CONCLUSION: GRABSEEDS streamlines the plant phenotyping process and is effective in a variety of seed, floral and leaf trait studies for association with agronomic traits and stress conditions. Source code and documentations for GRABSEEDS are available at: https://github.com/tanghaibao/jcvi/wiki/GRABSEEDS .
ABSTRACT
The life cycle of genome builds spans interlocking pillars of assembly, annotation, and comparative genomics to drive biological insights. While tools exist to address each pillar separately, there is a growing need for tools to integrate different pillars of a genome project holistically. For example, comparative approaches can provide quality control of assembly or annotation; genome assembly, in turn, can help to identify artifacts that may complicate the interpretation of genome comparisons. The JCVI library is a versatile Python-based library that offers a suite of tools that excel across these pillars. Featuring a modular design, the JCVI library provides high-level utilities for tasks such as format parsing, graphics generation, and manipulation of genome assemblies and annotations. Supporting genomics algorithms like MCscan and ALLMAPS are widely employed in building genome releases, producing publication-ready figures for quality assessment and evolutionary inference. Developed and maintained collaboratively, the JCVI library emphasizes quality and reusability.
ABSTRACT
Ixodes scapularis, the black-legged tick, is the principal vector of the Lyme disease spirochete, Borrelia burgdorferi, and is responsible for most of the â¼470,000 estimated Lyme disease cases annually in the USA. Ixodes scapularis can transmit six additional pathogens of human health significance. Because of its medical importance, I. scapularis was the first tick genome to be sequenced and annotated. However, the first assembly, I. scapularis Wikel (IscaW), was highly fragmented because of the technical challenges posed by the long, repetitive genome sequences characteristic of arthropod genomes and the lack of long-read sequencing techniques. Although I. scapularis has emerged as a model for tick research because of the availability of new tools such as embryo injection and CRISPR-Cas9-mediated gene editing yet the lack of chromosome-scale scaffolds has slowed progress in tick biology and the development of tools for their control. Here we combine diverse technologies to produce the I. scapularis Gulia-Nuss (IscGN) genome assembly and gene set. We used DNA from eggs and male and female adult ticks and took advantage of Hi-C, PacBio HiFi sequencing, and Illumina short-read sequencing technologies to produce a chromosome-level assembly. In this work, we present the predicted pseudochromosomes consisting of 13 autosomes and the sex pseudochromosomes: X and Y, and a markedly improved genome annotation compared with the existing assemblies and annotations.