CottonGVD: A Comprehensive Genomic Variation Database for Cultivated Cottons

Multi-genome comprehensive identification of SSR/SV and development of molecular markers database to serve Sorghum bicolor (L.) breeding

BACKGROUND

As an important food and cash crop, identification of DNA molecular markers is of great significance for molecular marker-assisted breeding of Sorghum (Sorghum bicolor (L.) moench). Although some sorghum-related mutation databases have been published, the special SSR and SV databases still need to be constructed and updated.

RESULTS

In this study, the quality of 18 different sorghum genomes was evaluated, and two genomes were assembled at chromosome level. Through the identification and comparative analysis of SSR loci in these genomes, the distribution characteristics of SSR in the above sorghum genomes were initially revealed. At the same time, five representative reference genomes were selected to identify the structural variation of sorghum. Finally, a convenient SSR/SV database of sorghum was constructed by integrating the above results ( http://www.sorghum.top:8079/ ; http://43.154.129.150:8079/ ; http://47.106.184.91:8079/ ). Users can query the information of related sites and primer pairs.

CONCLUSIONS

Anyway, our research provides convenience for sorghum researchers and will play an active role in sorghum molecular marker-assisted breeding.

A comprehensive overview of cotton genomics, biotechnology and molecular biological studies

Cotton is an irreplaceable economic crop currently domesticated in the human world for its extremely elongated fiber cells specialized in seed epidermis, which makes it of high research and application value. To date, numerous research on cotton has navigated various aspects, from multi-genome assembly, genome editing, mechanism of fiber development, metabolite biosynthesis, and analysis to genetic breeding. Genomic and 3D genomic studies reveal the origin of cotton species and the spatiotemporal asymmetric chromatin structure in fibers. Mature multiple genome editing systems, such as CRISPR/Cas9, Cas12 (Cpf1) and cytidine base editing (CBE), have been widely used in the study of candidate genes affecting fiber development. Based on this, the cotton fiber cell development network has been preliminarily drawn. Among them, the MYB-bHLH-WDR (MBW) transcription factor complex and IAA and BR signaling pathway regulate the initiation; various plant hormones, including ethylene, mediated regulatory network and membrane protein overlap fine-regulate elongation. Multistage transcription factors targeting CesA 4, 7, and 8 specifically dominate the whole process of secondary cell wall thickening. And fluorescently labeled cytoskeletal proteins can observe real-time dynamic changes in fiber development. Furthermore, research on the synthesis of cotton secondary metabolite gossypol, resistance to diseases and insect pests, plant architecture regulation, and seed oil utilization are all conducive to finding more high-quality breeding-related genes and subsequently facilitating the cultivation of better cotton varieties. This review summarizes the paramount research achievements in cotton molecular biology over the last few decades from the above aspects, thereby enabling us to conduct a status review on the current studies of cotton and provide strong theoretical support for the future direction.

TeaPVs: a comprehensive genomic variation database for tea plant (Camellia sinensis)

Genome variation not only plays an important role in plant phenotypic modeling and adaptive evolution, but also enhances population genetic diversity and regulates gene expression. The tea tree (Camellia sinensis) has a large genome (~ 3.0 Gb), making the identification of genome-wide variants time-consuming and expensive. With the continuous publication of a large number of different types of population sequencing data, there is a lack of an open platform to integrate these data and identify variants in the tea plant genome.To integrate the genetic variation confidence in the tea plant population genome, 238 whole-genome resequencing, 213 transcriptome sequencing, and 96 hybrid F1 individuals with a total of more than 20 Tb were collected for mutation site identification. Based on these variations information, we constructed the first tea tree variation web service database TeaPVs ( http://47.106.184.91:8025/ and http://liushang.top:8025/ ). It supports users to search all SNP, Indel, SV mutations and SSR/Polymorphic SSR sequences by location or gene ID. Furthermore, the website also provides the functions of gene expression search of different transcriptome, sequence blast, sequence extraction of CDS and mutation loci, etc.The features of the TeaPVs database make it a comprehensive tea plant genetic variation bioinformatics platform for researchers, and will also be helpful for revealing new functional mutations in the tea plant genome and molecular marker-assisted breeding.

CottonMD: a multi-omics database for cotton biological study

Cotton is an important economic crop, and many loci for important traits have been identified, but it remains challenging and time-consuming to identify candidate or causal genes/variants and clarify their roles in phenotype formation and regulation. Here, we first collected and integrated the multi-omics datasets including 25 genomes, transcriptomes in 76 tissue samples, epigenome data of five species and metabolome data of 768 metabolites from four tissues, and genetic variation, trait and transcriptome datasets from 4180 cotton accessions. Then, a cotton multi-omics database (CottonMD, http://yanglab.hzau.edu.cn/CottonMD/) was constructed. In CottonMD, multiple statistical methods were applied to identify the associations between variations and phenotypes, and many easy-to-use analysis tools were provided to help researchers quickly acquire the related omics information and perform multi-omics data analysis. Two case studies demonstrated the power of CottonMD for identifying and analyzing the candidate genes, as well as the great potential of integrating multi-omics data for cotton genetic breeding and functional genomics research.

Retrieving a disrupted gene encoding phospholipase A for fibre enhancement in allotetraploid cultivated cotton

After polyploidization originated from one interspecific hybridization event in Gossypium, Gossypium barbadense evolved to produce extra-long staple fibres than Gossypium hirsutum (Upland cotton), which produces a higher fibre yield. The genomic diversity between G. barbadense and G. hirsutum thus provides a genetic basis for fibre trait variation. Recently, rapid accumulation of gene disruption or deleterious mutation was reported in allotetraploid cotton genomes, with unknown impacts on fibre traits. Here, we identified gene disruptions in allotetraploid G. hirsutum (18.14%) and G. barbadense (17.38%) through comparison with their presumed diploid progenitors. Relative to conserved genes, these disrupted genes exhibited faster evolution rate, lower expression level and altered gene co-expression networks. Within a module regulating fibre elongation, a hub gene experienced gene disruption in G. hirsutum after polyploidization, with a 2-bp deletion in the coding region of GhNPLA1D introducing early termination of translation. This deletion was observed in all of the 34 G. hirsutum landraces and 36 G. hirsutum cultivars, but not in 96% of 57 G. barbadense accessions. Retrieving the disrupted gene GhNPLA1D using its homoeolog GhNPLA1A achieved longer fibre length in G. hirsutum. Further enzyme activity and lipids analysis confirmed that GhNPLA1A encodes a typical phospholipase A and promotes cotton fibre elongation via elevating intracellular levels of linolenic acid and 34:3 phosphatidylinositol. Our work opens a strategy for identifying disrupted genes and retrieving their functions in ways that can provide valuable resources for accelerating fibre trait enhancement in cotton breeding.

Integrating Genome-wide association and whole transcriptome analysis to reveal genetic control of leaf traits in Gossypium arboreum L

Leaves are important organs for crop photosynthesis and transpiration, and their morphological characteristics can directly reflect the growth state of plants. Accurate measurement of leaf traits and mining molecular markers are of great significance to the study of cotton growth. Here, we performed a Genome-wide association study on 7 leaf traits in 213 Asian cotton accessions. 32 significant SNPs and 44 genes were identified. A field experiment showed significant difference in leaf hair and leaf area between DPL971 and its natural mutant DPL972. We also compared the leaf transcriptome difference between DPL971 and DPL972, and found a batch of differentially expressed genes and non-coding RNAs (including lncRNAs, microRNAs, and circRNAs). After integrating the GWAS and transcriptome results, we finally selected two coding genes (Ga03G2383 and Ga05G3412) and two microRNAs (hbr-miR156, unconservative_Chr03_contig343_2364) as the candidate for leaf traits. Those findings will provide important genomic resources for cotton leaf improvement breeding.

GRAND: An Integrated Genome, Transcriptome Resources, and Gene Network Database for Gossypium

With the increasing amount of cotton omics data, breeding scientists are confronted with the question of how to use massive cotton data to mine effective breeding information. Here, we construct a Gossypium Resource And Network Database (GRAND), which integrates 18 cotton genome sequences, genome annotations, two cotton genome variations information, and also four transcriptomes for Gossypium species. GRAND allows to explore and mine this data with the help of a toolbox that comprises a flexible search system, BLAST and BLAT suite, orthologous gene ID, networks of co-expressed genes, primer design, Gbrowse and Jbrowse, and drawing instruments. GRAND provides important information regarding Gossypium resources and hopefully can accelerate the progress of cultivating cotton varieties.