Assessment of Genetic Diversity, Population Structure, and Evolutionary Relationship of Uncharacterized Genes in a Novel Germplasm Collection of Diploid and Allotetraploid Gossypium Accessions Using EST and Genomic SSR Markers

Exploring agro-morphological and fiber traits diversity in cotton (G. barbadense L.)

Cotton (Gossypium barbadense L.) is a leading fiber and oilseed crop globally, but genetic diversity among breeding materials is often limited. This study analyzed genetic variability in 14 cotton genotypes from Egypt and other countries, including both cultivated varieties and wild types, using agro-morphological traits and genomic SSR markers. Field experiments were conducted over two seasons to evaluate 12 key traits related to plant growth, yield components, and fiber quality. Molecular diversity analysis utilized 10 SSR primers to generate DNA profiles. The Molecular diversity analysis utilized 10 SSR primers to generate DNA profiles. Data showed wide variation for the morphological traits, with Egyptian genotypes generally exhibiting higher means for vegetative growth and yield parameters. The top-performing genotypes for yield were Giza 96, Giza 94, and Big Black Boll genotypes, while Giza 96, Giza 92, and Giza 70 ranked highest for fiber length, strength, and fineness. In contrast, molecular profiles were highly polymorphic across all genotypes, including 82.5% polymorphic bands out of 212. Polymorphism information content was high for the SSR markers, ranging from 0.76 to 0.86. Genetic similarity coefficients based on the SSR data varied extensively from 0.58 to 0.91, and cluster analysis separated genotypes into two major groups according to geographical origin. The cotton genotypes displayed high diversity in morphology and genetics, indicating sufficient variability in the germplasm. The combined use of physical traits and molecular markers gave a thorough understanding of the genetic diversity and relationships between Egyptian and global cotton varieties. The SSR markers effectively profiled the genotypes and can help select ideal parents for enhancing cotton through hybridization and marker-assisted breeding.

Uncovering microsatellite markers associated with agronomic traits of South Sudan landrace maize

BACKGROUND

Maize has great importance in South Sudan as the most cultivated cereal after sorghum; however, numerous challenges are encountered in its production. To raise maize production, it is critical to exploit the wealth of its genetic variation for grain yield enhancement.

OBJECTIVE

This study aimed to conduct association analysis to identify specific simple sequence repeat (SSR) markers associated with quantitative agronomic traits.

METHODS

Genetic variation and population structure were investigated among 31 maize accessions by association analysis using 50 SSR markers and seven quantitative agronomic traits.

RESULTS

The genotypes exhibited abundant genetic variation, and 418 alleles were detected with an average of 8.4 alleles per locus. The average genetic diversity, major allele frequency, and polymorphic information content were 0.754, 0.373, and 0.725, respectively. The population structure based on 50 SSR markers divided the maize accessions into two main groups and an admixed group without considering their descent. Association analysis was performed using a general linear model (Q GLM) and a mixed linear model (Q + K MLM). Q GLM detected 44 trait-marker associations involving 23 SSR markers. Q + K MLM detected four marker-trait associations involving three SSR markers (umc2286, umc1303, umc1429) associated with days to tasseling, days to silking, leaf length, and leaf width.

CONCLUSIONS

The detected significant SSR markers related to agronomic traits could be useful for future genetic studies. Additionally, markers affecting several agronomic traits and overlapped SSR markers require further testing on a wide range of genotypes prior to their consideration as candidate markers for marker assisted selection for South Sudan maize improvement.

De novo assembly of Iron-Heart Cunninghamia lanceolata transcriptome and EST-SSR marker development for genetic diversity analysis

Iron-Heart Cunninghamia lanceolata, a wild relative of Chinese fir with valuable genetic and breeding traits, has been limited in genetic studies due to a lack of genomic resources and markers. In this study, we conducted transcriptome sequencing of Iron-Heart C. lanceolata leaves using Illumina NovaSeq 6000 and performed assembly and analysis. We obtained 45,326,576 clean reads and 115,501 unigenes. Comparative analysis in five functional databases resulted in successful annotation of 26,278 unigenes, with 6,693 unigenes annotated in all databases (5.79% of the total). UniProt and Pfam databases provided annotations for 22,673 and 18,315 unigenes, respectively. Gene Ontology analysis categorized 23,962 unigenes into three categories. KEGG database alignment annotated 10,195 unigenes, classifying them into five categories: metabolism, genetic information, biological systems, cellular processes, and environmental information processing. From the unigenes, we identified 5,645 SSRs, with dinucleotides repeats being the most common (41.47%). We observed variations in repeat numbers and base compositions, with the majority of markers ranging from 12 to 29 bp in length. We randomly selected 200 primer pairs and successfully amplified 15 pairs of polymorphic SSR primers, which effectively distinguished Chinese fir plants of different origins. This study provides insights into the genetic characteristics of Iron-Heart C. lanceolata and offers a foundation for future molecular marker development, breeding programs, genetic diversity analysis, and conservation strategies.

Genetic diversity and population structure analyses and genome-wide association studies of photoperiod sensitivity in cotton (Gossypium hirsutum L.)

KEY MESSAGE

Genetic diversity and population structure analyses showed progressively narrowed diversity in US Upland cotton compared to land races. GWAS identified genomic regions and candidate genes for photoperiod sensitivity in cotton. Six hundred fifty-seven accessions that included elite cotton germplasm (DIV panel), lines of a public cotton breeding program (FB panel), and tropical landrace accessions (TLA panel) of Gossypium hirsutum L. were genotyped with cottonSNP63K array and phenotyped for photoperiod sensitivity under long day-length conditions. The genetic diversity analysis using 26,952 polymorphic SNPs indicated a progressively narrowed diversity from the landraces (0.230) to the DIV panel accessions (0.195) and FB panel (0.116). Structure analysis in the US germplasm identified seven subpopulations representing all four major regions of the US cotton belt. Three subpopulations were identified within the landrace accessions. The highest fixation index (FST) of 0.65 was found between landrace accessions of Guatemala and the Plains-type cultivars from Southwest cotton region while the lowest FST values were between the germplasms of Mid-South and Southeastern regions. Genome wide association studies (GWAS) of photoperiod response using 600 phenotyped accessions identified 14 marker trait associations spread across eight Upland cotton chromosomes. Six of these marker trait associations, on four chromosomes (A10, D04, D05, and D06), showed significant epistatic interactions. Targeted genomic analysis identified regions with 19 candidate genes including Transcription factor Vascular Plant One-Zinc Finger 1 (VOZ1) and Protein Photoperiod-Independent Early Flowering 1 (PIE1) genes. Genetic diversity and genome wide analyses of photoperiod sensitivity in diverse cotton germplasms will enable the use of genomic tools to systematically utilize the tropical germplasm and its beneficial alleles for broadening the genetic base in Upland cotton.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.)

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Perennial Cotton Ratoon Cultivation: A Sustainable Method for Cotton Production and Breeding

Cotton production is challenged by high costs with multiple management and material inputs including seed, pesticide, and fertilizer application. The production costs can be decreased and profits can be increased by developing efficient crop management strategies, including perennial cotton ratoon cultivation. This review focuses on the role of ratoon cultivation in cotton productivity and breeding. In areas that are frost-free throughout the year, when the soil temperature is suitable for cotton growth in spring, the buds of survived plants begin to sprout, and so their flowering and fruiting periods are approximately 4-6 weeks earlier than those of sown cotton. Due to the absence of frost damage, the ratoon cotton continues to grow, and the renewed plants can offer a higher yield than cotton sown in the following season. Moreover, ratoon cultivation from the last crop without sowing can help conserve seeds, reduce labor inputs, and reduce soil and water loss. In this review, the preservation of perennial cotton germplasm resources, the classification and genome assignment of perennial species in the cotton gene pools, and effective strategies for the collection, preservation, identification, and utilization of perennial cotton germplasms are discussed. Ratoon cultivation is the main driver of cotton production and breeding, especially to maintain male sterility for the utilization and fixation of heterosis. Ratoon cultivation of cotton is worth adopting because it has succeeded in Brazil, China, and India. Therefore, taking advantages of the warm environment to exploit the indeterminant growth habit of perennial cotton for breeding would be an efficiency-increasing, cost-saving, and eco-friendly approach in frost-free regions. In the future, more attention should be given to ratooning perennial cotton for breeding male-sterile lines.

Identification and characterization of genes related to salt stress tolerance within segregation distortion regions of genetic map in F2 population of upland cotton

Segregation distortion (SD) is a genetic mechanism commonly found in segregating or stable populations. The principle behind this puzzles many researchers. The F₂ generation developed from wild Gossypium darwinii and G. hirsutum CCRI12 species was used to investigate the possible transcription factors within the segregation distortion regions (SDRs). The 384 out of 2763 markers were distorted in 29 SDRs on 18 chromosomes. Good collinearity was observed among genetic and physical maps of G. hirsutum and G. barbadense syntenic blocks. Total 568 genes were identified from SDRs of 18 chromosomes. Out of these genes, 128 belonged to three top-ranked salt-tolerant gene families. The DUF597 contained 8 uncharacterized genes linked to Pkinase (PF00069) gene family in the phylogenetic tree, while 15 uncharacterized genes clustered with the zinc finger gene family. Two hundred thirty four miRNAs targeted numerous genes, including ghr-miR156, ghr-miR399 and ghr-miR482, while others targeted top-ranked stress-responsive transcription factors. Moreover, these genes were involved in the regulation of numerous stress-responsive cis-regulatory elements. The RNA sequence data of fifteen upregulated genes were verified through the RT-qPCR. The expression profiles of two highly upregulated genes (Gh_D01G2015 and Gh_A01G1773) in salt-tolerant G. darwinii showed antagonistic expression in G. hirsutum. The results indicated that salt-tolerant genes have been possibly transferred from the wild G. darwinii species. A detailed functional analysis of these genes can be carried out which might be helpful in the future for gene cloning, transformation, gene editing and the development of salt-resistant cotton varieties.

High temperature induced changes in quality and yield parameters of tomato (Solanum lycopersicum L.) and similarity coefficients among genotypes using SSR markers

High temperature induced by climatic fluctuations are an important threat for plant growth, development and quality of agricultural produces. Adaptableness to environmental changes generally derives from a large set of genetic traits affecting physio-morphological, biochemical and agronomic parameters. Therefore, the identification of genotypes with higher yield and good quality parameters at high temperatures is becoming increasingly necessary for future breeding programs. Here, we analyzed the performance of different tomato genotypes grown under elevated temperatures in terms of yield and nutritional quality of the fruit. High temperature stress was induced from flower initiation to maturity stage by keeping the pots in a temperature controlled green house facility for 45 days. The quality and yield parameters were taken at the harvesting stage. Starch and soluble sugar concentration in the leaves of tomato genotypes showed significant reduction in its amount under heat stress. Titrable acidity (TA), total soluble solids (TSS) and ascorbic acid content of tomato fruits were highest under high temperature conditions compared to ambient condition but lycopene content decreased with rise in temperature. The yield attributes viz., number of fruits/plant, fruit set %, average fruit weight (g), yield per plant (g/plant) were significantly lower for Arka Saurabh, Arka Rakshak and Pusa Rohini when compared to other genotypes under study. Molecular characterization of selected 22 tomato genotypes were assessed using 25 simple sequence repeat (SSR) markers. Phylogenetic tree was constructed by the unweighted neighbour-joining method (UPGMA) using NTSYSpc cluster analysis software. The Jaccard's similarity matrix was constructed using the SIMQUAL method using UPGMA algorithm in NTSYSpc. Jaccard's similarity matrix among these tomato genotypes ranged from a minimum of 0.22 to a maximum of 1 with an average genetic similarity of 0.67. Hence this study has importance in identifying genotypes that could maintain good quality and higher yield under high temperature condition.

Sequencing Multiple Cotton Genomes Reveals Complex Structures and Lays Foundation for Breeding

Cotton is a major fiber plant, which provides raw materials for clothing, protecting humans from the harsh environment of cold or hot weathers, enriching the culture and custom of human societies. Due to its importance, the diploid and tetraploid genomes of different cotton plants have been repeatedly sequenced to obtain their complete and fine genome sequences. These valuable genome data sets revealed the evolutionary past of the cotton plants, which were recursively affected by polyploidization, with a decaploidization contributing to the formation of the genus Gossypium, and a neo-tetraploidization contributing to the formation of nowadays widely cultivated cotton plants. Post-polyploidization genome instability resulted in numerous structural changes of the genomes, such as gene loss, DNA inversion and translocation, illegitimate recombination, and accumulation of repetitive sequences, and functional innovation accompanied by elevated evolutionary rates of genes. Many these changes have been asymmetric between subgnomes of the tetraploid cottons, rendering their divergent profiles of biological regulation and function. The availability of whole-genome sequences has now paved the way to identify and clone functional genes, e.g., those relating to fiber development, and to enhance breeding efforts to cultivate cottons to produce high-yield and high-quality fibers, and to resist environmental and biological stress.

Genetic Diversity and Population Structure Analysis of Dalbergia Odorifera Germplasm and Development of a Core Collection Using Microsatellite Markers

Dalbergia odorifera T. Chen (Fabaceae) is a woody tree species indigenous to Hainan Island in China. Due to its high medicinal and commercial value, this tree species has been planted over 3500 ha² in southern China. There is an urgent need for improvement of the D. odorifera germplasm, however, limited information on germplasm collection, conservation, and assessment of genetic resources is available. Therefore, we have built a database of 251 individuals collected across the whole of southern China, which included 42 wild trees and 210 cultivated trees, with the following objectives. (1) Evaluate genetic diversity and population structure of the database using 19 microsatellite markers and (2) develop a core collection for improvement and breeding programs. Totally, the 19 microsatellite markers harbored 77 alleles across the database with the polymorphic information content (PIC) ranging from 0.03 to 0.66. Medium genetic diversity level was inferred by Nei’s gene diversity (0.38), Shannon’s information index (0.65), and observed (0.33) and expected heterozygosity (0.38). Structure analysis showed that four was the optimum cluster size using the model-based Bayesian procedure, and the 251 D. odorifera individuals were grouped into five populations including four pure ones (RP1-4) and one mixed one (MIX) based on their maximum membership coefficients. Among these populations, the expected heterozygosity varied from 0.30 (RP3) to 0.38 (RP4). Analysis of molecular variance (AMOVA) showed 11% genetic variation existed among populations, and moderate population differentiation was inferred by the matrix of pairwise Fst (genetic differentiation among populations), which was in the range of 0.031 to 0.095. Moreover, a core collection of 31 D. odorifera individuals including six wild and 25 cultivated trees was developed, which was only 12.4% of the database but conserved the whole genetic diversity. The results of this study provided additional insight into the genetic structure of the large D. odorifera germplasm, and the core collection will be useful for the efficient and sustainable utilization of genetic resources, as well as efficient improvement in breeding programs.