TRANSNAP: a web database providing comprehensive information on Japanese pear transcriptome

Improvement of little millet (Panicum sumatrense) using novel omics platform and genetic resource integration

MAIN CONCLUSION

This article explores possible future initiatives, such as the development of targeted breeding and integrated omics approach to boost little millet production, nutritional value, and environmental adaptation. Little millet (P. sumatrense) is a staple grain in many parts of Asia and Africa owing to its abundance in vitamins and minerals and its ability to withstand harsh agro-ecological conditions. Enhancing little millet using natural resources and novel crop improvement strategy is an effective way of boosting nutritional and food security. To understand the genetic makeup of the crop and figure out important characteristics linked to nutritional value, biotic and abiotic resistance, and production, researchers in this field are currently resorting on genomic technology. These realizations have expedited the crop's response to shifting environmental conditions by enabling the production of superior cultivars through targeted breeding. Going forward, further improvements in breeding techniques and genetics may boost the resilience, nutritional content, and production of little millet, which would benefit growers and consumers alike. The research and development on little millet improvement using novel omics platform and the integration of genetic resources are summarized in this review paper. Improved cultivars of little millet that satisfy changing farmer and consumer demands have already been developed through the use of these novel breeding strategies. This article also explores possible future initiatives, such as the development of targeted breeding, genomics, and sustainable agriculture methods. The potential for these measures to boost little millet's overall production, nutritional value, and climate adaptation will be extremely helpful in addressing nutritional security.

PPGR: a comprehensive perennial plant genomes and regulation database

Perennial woody plants hold vital ecological significance, distinguished by their unique traits. While significant progress has been made in their genomic and functional studies, a major challenge persists: the absence of a comprehensive reference platform for collection, integration and in-depth analysis of the vast amount of data. Here, we present PPGR (Resource for Perennial Plant Genomes and Regulation; https://ngdc.cncb.ac.cn/ppgr/) to address this critical gap, by collecting, integrating, analyzing and visualizing genomic, gene regulation and functional data of perennial plants. PPGR currently includes 60 species, 847 million protein-protein/TF (transcription factor)-target interactions, 9016 transcriptome samples under various environmental conditions and genetic backgrounds. Noteworthy is the focus on genes that regulate wood production, seasonal dormancy, terpene biosynthesis and leaf senescence representing a wealth of information derived from experimental data, literature mining, public databases and genomic predictions. Furthermore, PPGR incorporates a range of multi-omics search and analysis tools to facilitate browsing and application of these extensive datasets. PPGR represents a comprehensive and high-quality resource for perennial plants, substantiated by an illustrative case study that demonstrates its capacity in unraveling gene functions and shedding light on potential regulatory processes.

Rosaceae fruit transcriptome database (ROFT)-a useful genomic resource for comparing fruits of apple, peach, strawberry, and raspberry

Rosaceae is a large plant family consisting of many economically important fruit crops including peach, apple, pear, strawberry, raspberry, plum, and others. Investigations into their growth and development will promote both basic understanding and progress toward increasing fruit yield and quality. With the ever-increasing high-throughput sequencing data of Rosaceae, comparative studies are hindered by inconsistency of sample collection with regard to tissue, stage, growth conditions, and by vastly different handling of the data. Therefore, databases that enable easy access and effective utilization of directly comparable transcript data are highly desirable. Here, we describe a database for comparative analysis, ROsaceae Fruit Transcriptome database (ROFT), based on RNA-seq data generated from the same laboratory using similarly dissected and staged fruit tissues of four important Rosaceae fruit crops: apple, peach, strawberry, and red raspberry. Hence, the database is unique in allowing easy and robust comparisons among fruit gene expression across the four species. ROFT enables researchers to query orthologous genes and their expression patterns during different fruit developmental stages in the four species, identify tissue-specific and tissue-/stage-specific genes, visualize and compare ortholog expression in different fruit types, explore consensus co-expression networks, and download different data types. The database provides users access to vast amounts of RNA-seq data across the four economically important fruits, enables investigations of fruit type specification and evolution, and facilitates the selection of genes with critical roles in fruit development for further studies.

LMTdb: A comprehensive transcriptome database for climate-resilient, nutritionally rich little millet (Panicum sumatrense)

Little millet (Panicum sumatrense) a native of Chhattisgarh, belongs to the minor millet group and is primarily known as a climate-resilient and nutritionally rich crop. However, due to the lack of enough Omic studies on the crop, the scientific community has largely remained unaware of the potential of this crop, resulting in less scope for its utilization in crop improvement programs. Looking at global warming, erratic climate change, nutritional security, and limited genetic information available, the Little Millet Transcriptome Database (LMT^db) (https://igkv.ac.in/xenom/index.aspx) was conceptualized upon completion of the transcriptome sequencing of little millet with the aim of deciphering the genetic signatures of this largely unknown crop. The database was developed with the view of providing information about the most comprehensive part of the genome, the 'Transcriptome'. The database includes transcriptome sequence information, functional annotation, microsatellite markers, DEGs, and pathway information. The database is a freely available resource that provides breeders and scientists a portal to search, browse, and query data to facilitate functional and applied Omic studies in millet crops.

Genomic and Bioinformatic Resources for Perennial Fruit Species

In the post-genomic era, data management and development of bioinformatic tools are critical for the adequate exploitation of genomics data. In this review, we address the actual situation for the subset of crops represented by the perennial fruit species. The agronomical singularity of these species compared to plant and crop model species provides significant challenges on the implementation of good practices generally not addressed in other species. Studies are usually performed over several years in non-controlled environments, usage of rootstock is common, and breeders heavily rely on vegetative propagation. A reference genome is now available for all the major species as well as many members of the economically important genera for breeding purposes. Development of pangenome for these species is beginning to gain momentum which will require a substantial effort in term of bioinformatic tool development. The available tools for genome annotation and functional analysis will also be presented.

Chromosome-scale genome assembly of Japanese pear (Pyrus pyrifolia) variety 'Nijisseiki'

We analyzed the genome sequence of a Japanese pear (Pyrus pyrifolia) to facilitate its genetics and genomics as well as breeding programs, in which a variety 'Nijisseiki' with superior flesh texture has been used as a parent for most Japanese pear cultivars. De novo assembly of long sequence reads covered 136× of the Japanese pear genome and generated 503.9 Mb contigs consisting of 114 sequences with an N50 value of 7.6 Mb. Contigs were assigned to Japanese pear genetic maps to establish 17 chromosome-scale sequences. In total, 44,876 high-confidence protein-encoding genes were predicted, 84.3% of which were supported by predicted genes and transcriptome data from Japanese pear relatives. As expected, evidence of genome-wide duplication was observed, consistent with related species. This is the first chromosome-scale genome sequence analysis reported for Japanese pear, and this resource will support breeding programs and provide new insights into the physiology and evolutionary history of Japanese pear.

An Atlas of Genomic Resources for Studying Rosaceae Fruits and Ornamentals

Rosaceae, a large plant family of more than 3,000 species, consists of many economically important fruit and ornamental crops, including peach, apple, strawberry, raspberry, cherry, and rose. These horticultural crops are not only important economic drivers in many regions of the world, but also major sources of human nutrition. Additionally, due to the diversity of fruit types in Rosaceae, this plant family offers excellent opportunities for investigations into fleshy fruit diversity, evolution, and development. With the development of high-throughput sequencing technologies and computational tools, an increasing number of high-quality genomes and transcriptomes of Rosaceae species have become available and will greatly facilitate Rosaceae research and breeding. This review summarizes major genomic resources and genome research progress in Rosaceae, highlights important databases, and suggests areas for further improvement. The availability of these big data resources will greatly accelerate research progress and enhance the agricultural productivity of Rosaceae.