Vegetable Breeding, Genetics and Genomics, 2nd Volume

Topic Information

Dear Colleagues,

In recent years, vegetable breeding has been driven by genomics and next-generation sequencing tools. NGS has advanced breeding to the next level, as orphan crops, or understudied vegetable and fruit crops, are currently being sequenced to generate gold-standard genome sequences, deep sequencing of germplasm collections and breeding populations. These resources were used to perform genomic-assisted selections, to identify deleterious alleles and targets for genome editing, and, most importantly, to identify lines with the highest breeding value based on genomic predictions. For this Topic, we invite papers addressing the development and use of whole-genome sequencing, SNP, or structural variants, genome-wide association studies, genomic predictions, QTL analysis, methods for analysis, review articles related to this topic, and methods to purge deleterious alleles from the crops, with special reference being made to vegetable crops.

Prof. Dr. Umesh K. Reddy
Prof. Dr. Padma Nimmakayala
Dr. Georgia Ntatsi
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Agriculture agriculture	3.3	4.9	2011	19.2 Days	CHF 2600	Submit
Agronomy agronomy	3.3	6.2	2011	17.6 Days	CHF 2600	Submit
Crops crops	-	-	2021	22.1 Days	CHF 1000	Submit
Genes genes	2.8	5.2	2010	14.9 Days	CHF 2600	Submit
Plants plants	4.0	6.5	2012	18.9 Days	CHF 2700	Submit
DNA dna	-	-	2021	23.3 Days	CHF 1000	Submit

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All Agriculture Agronomy Crops Genes Plants DNA

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Open AccessArticle

Transcriptome and Metabolome Analysis of Low-Pressure Regulation in Saussurea involucrata Leaves

by Xinyu Quan, Fenggui Fan, Hanbo Cao, Na Tang, Changgen Xu and Changhe Wang

Genes 2025, 16(3), 328; https://doi.org/10.3390/genes16030328 - 11 Mar 2025

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Abstract

Saussurea involucrata, an endangered medicinal plant, thrives in high mountain regions at altitudes ranging from 3500 to 5000 m. Being a plant that grows at high altitudes means it possesses unique physiological mechanisms and stress-responsive genes that regulate and adapt to the [...] Read more.

Saussurea involucrata, an endangered medicinal plant, thrives in high mountain regions at altitudes ranging from 3500 to 5000 m. Being a plant that grows at high altitudes means it possesses unique physiological mechanisms and stress-responsive genes that regulate and adapt to the high-altitude environment. While many cold-resistant genes have been cloned and their mechanisms studied, the genes and molecular mechanisms involved in adaptation to hypobaric hypoxia remain largely unexplored. This study conducted transcriptomic and metabolomic analyses on the leaves of S. involucrata under normal atmosphere (101 kPa) and low pressure (60 kPa). A total of 2383 differentially expressed genes (DEGs) and 336 differentially accumulated metabolites (DAMs) were identified utilizing RNA-seq and UPLS-MS techniques. The results indicated that S. involucrata exhibits responses to hypobaric hypoxia environments by engaging in DNA repair, membrane transport, hypoxic response, reproductive processes, and various metabolic activities associated with nutrient uptake and the effective utilization of chemical components. It is worth noting that under low-pressure treatment, flavonoids are predominantly negatively regulated, whereas terpenoids are primarily positively regulated. These findings identify key genes and metabolites in S. involucrata that respond to hypobaric hypoxia treatment, providing a theoretical basis for the development of its medicinal value and for low-altitude cultivation. Full article

(This article belongs to the Topic Vegetable Breeding, Genetics and Genomics, 2nd Volume)

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Open AccessArticle

Genome-Wide Identification and Expression Analysis of the SPL Gene Family in Solanum melongena (Eggplant)

by Hefen Cheng, Zhiliang Li, Baojuan Sun, Wei Zhao, Songyuan Zhang, Tao Li, Qian You and Dinggang Zhou

Agronomy 2025, 15(2), 471; https://doi.org/10.3390/agronomy15020471 - 14 Feb 2025

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Abstract

The SPL (SQUAMOSA promoter-binding protein-like) transcription factor gene family plays a crucial role in the growth of plants, including fruit development. Although the SPL gene family has been widely studied in many plants, it remains unexplored in eggplant, an important Solanaceae vegetable crop. [...] Read more.

The SPL (SQUAMOSA promoter-binding protein-like) transcription factor gene family plays a crucial role in the growth of plants, including fruit development. Although the SPL gene family has been widely studied in many plants, it remains unexplored in eggplant, an important Solanaceae vegetable crop. In this study, we performed a genome-wide analysis and identified 11 SmSPL genes with 10 motifs in the eggplant genome, which were assigned to five groups based on the amino acid sequences and the gene structure of the SBP domain. In addition, the expression patterns of 11 SmSPL genes were analyzed in different tissue types and at four different fruit development stages in eggplant. The results showed that all SmSPL genes were expressed differently in various tissues, suggesting that they may play different roles in the regulation of the development of different organs. Specifically, the expression level of SmSPL_5 was increased at the fruit expansion stage and showed the highest expression levels at 16 and 24 days after pollination, suggesting that it may be involved in regulating fruit development at both the fruit expansion and commercial fruit stages. Overall, this study provides an important basis for further exploring the function of the SmSPL gene family in eggplant. Full article

(This article belongs to the Topic Vegetable Breeding, Genetics and Genomics, 2nd Volume)

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Open AccessArticle

Genotype-Driven Phenotype Prediction in Onion Breeding: Machine Learning Models for Enhanced Bulb Weight Selection

by Junhwa Choi, Sunghyun Cho, Subin Choi, Myunghee Jung, Yu-jin Lim, Eunchae Lee, Jaewon Lim, Han Yong Park and Younhee Shin

Agriculture 2024, 14(12), 2239; https://doi.org/10.3390/agriculture14122239 - 6 Dec 2024

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Abstract

Onions (Allium cepa L.) are a globally significant horticultural crop, ranking second only to tomatoes in terms of cultivation and consumption. However, due to the crop’s complex genome structure, lengthy growth cycle, self-incompatibility, and susceptibility to disease, onion breeding is challenging. To [...] Read more.

Onions (Allium cepa L.) are a globally significant horticultural crop, ranking second only to tomatoes in terms of cultivation and consumption. However, due to the crop’s complex genome structure, lengthy growth cycle, self-incompatibility, and susceptibility to disease, onion breeding is challenging. To address these issues, we implemented digital breeding techniques utilizing genomic data from 98 elite onion lines. We identified 51,499 high-quality variants and employed these data to construct a genomic estimated breeding value (GEBV) model and apply machine learning methods for bulb weight prediction. Validation with 260 new individuals revealed that the machine learning model achieved an accuracy of 83.2% and required only thirty-nine SNPs. Subsequent in silico crossbreeding simulations indicated that offspring from the top 5% of elite lines exhibited the highest bulb weights, aligning with traditional phenotypic selection methods. This approach demonstrates that early-stage selection based on genotypic information followed by crossbreeding can achieve economically viable breeding results. This methodology is not restricted to bulb weight and can be applied to various horticultural traits, significantly improving the efficiency of onion breeding through advanced digital technologies. The integration of genomic data, machine learning, and computer simulations provides a powerful framework for data-driven breeding strategies, accelerating the development of superior onion varieties to meet global demand. Full article

(This article belongs to the Topic Vegetable Breeding, Genetics and Genomics, 2nd Volume)

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