Genomic Distance Research Articles

ParSite is a multicolor DNA labeling system that allows for simultaneous imaging of triple genomic loci in living cells.

The organization of the human genome in space and time is critical for transcriptional regulation and cell fate determination. However, robust methods for tracking genome organization or genomic interactions over time in living cells are lacking. Here, we developed a multicolor DNA labeling system, ParSite, to simultaneously track triple genomic loci in the U2OS cells. The tricolor ParSite system is derived from the T. thermophilus ParB/ParSc (TtParB/ParSc) system by rational design. We mutated the interface between TtParB and ParSc and generated a new pair of TtParBm and ParSm for genomic DNA labeling. The insertions of 16 base-pair palindromic ParSc and ParSm into genomic loci allow dual-color DNA imaging in living cells. A pair of genomic loci labeled by ParSite could be colocalized with p53-binding protein 1 (53BP1) in response to CRISPR/Cas9-mediated double-strand breaks (DSBs). The ParSite permits tracking promoter and terminator dynamics of the APP gene, which spans 290 kilobases in length. Intriguingly, the hybrid ParS (ParSh) of half-ParSc and half-ParSm enables for the visualization of a third locus independent of ParSc or ParSm. We simultaneously labeled 3 loci with a genomic distance of 36, 89, and 352 kilobases downstream the C3 repeat locus, respectively. In sum, the ParSite is a robust DNA labeling system for tracking multiple genomic loci in space and time in living cells.

Bridging the gap: How enhancers cooperate to regulate gene expression over large genomic distances.

By building synthetic regulatory landscapes, Jensen etal.1 and Thomas etal.2 demonstrate in this issue of Molecular Cell that gene expression levels strongly depend on the genomic distance between enhancers and promoters and that enhancer cooperation can compensate for reduced enhancer activity over large genomic distances.

Strain phylogroup and environmental constraints shape Escherichia coli dynamics and diversity over a 20-year human gut time series.

Escherichia coli is an increasingly antibiotic-resistant opportunistic pathogen. Few data are available on its ecological and evolutionary dynamics in its primary commensal niche, the vertebrate gut. Using Illumina and/or Nanopore technologies, we sequenced whole genomes of 210 E. coli isolates from 22 stools sampled during a 20-year period from a healthy man (ED) living in Paris, France. All phylogroups, except C, were represented, with a predominance of B2 (34.3%), followed by A and F (19% each) phylogroups. Thirty-five clones were identified based on their haplogroup and pairwise genomic single nucleotide polymorphism distance and classified in three phenotypes according to their abundance and residence time: 25 sub-dominant/transient (52 isolates), five dominant/transient (48 isolates) and five dominant/resident (110 isolates). Four over five dominant/resident clones belonged to B2 and closely related F phylogroups, whereas sub-dominant/transient clones belonged mainly to B1, A and D phylogroups. The long residence times of B2 clones seemed to be counterbalanced by lower colonization abilities. Clones with larger within-host frequency persisted for longer. By comparing ED strain genomes to a collection of commensal E. coli genomes from 359 French individuals, we identified ED-specific genomic properties including an enrichment in genes involved in a metabolic pathway (mhp cluster) and the presence of a very rare antiviral defense island. The E. coli colonization within the gut microbiota was shaped by both the intrinsic properties of the strain lineages, in particular longer residence of phylogroup B2, and the environmental constraints such as diet or phages.

Dna2bit: high performance genomic distance estimation software for microbial genome analysis

dna2bit is an ultra-fast software specifically engineered for microbial genome analysis, particularly adept at calculating genome distances within metagenome and single amplified genome datasets. Distinguished from existing software such as Mash and Dashing, dna2bit employs feature hashing technique and Hamming distance to achieve enhanced speed and memory utilization, without sacrifice in the accuracy of average nucleotide identity calculations. dna2bit has promising applications in various domains such as average nucleotide identity approximation, metagenomic sequence clustering, and homology querying. dna2bit significantly boosts computational efficiency in handling large datasets including single amplified genomes, thereby facilitating a better understanding of the population heterogeneity and comparative genomics of microorganisms. dna2bit is available at https://github.com/lijuzeng/dna2bit.

A constitutive heterochromatic region shapes genome organization and impacts gene expression in Neurospora crassa

BackgroundOrganization of the eukaryotic genome is essential for proper function, including gene expression. In metazoans, chromatin loops and Topologically Associated Domains (TADs) organize genes into transcription factories, while chromosomes occupy nuclear territories in which silent heterochromatin is compartmentalized at the nuclear periphery and active euchromatin localizes to the nucleus center. A similar hierarchical organization occurs in the fungus Neurospora crassa where its seven chromosomes form a Rabl conformation typified by heterochromatic centromeres and telomeres independently clustering at the nuclear membrane, while interspersed heterochromatic loci aggregate across Megabases of linear genomic distance to loop chromatin in TAD-like structures. However, the role of individual heterochromatic loci in normal genome organization and function is unknown.ResultsWe examined the genome organization of a Neurospora strain harboring a ~ 47.4 kilobase deletion within a temporarily silent, facultative heterochromatic region, as well as the genome organization of a strain deleted of a 110.6 kilobase permanently silent constitutive heterochromatic region. While the facultative heterochromatin deletion minimally effects local chromatin structure or telomere clustering, the constitutive heterochromatin deletion alters local chromatin structure, the predicted three-dimensional chromosome conformation, and the expression of some genes, which are qualitatively repositioned into the nucleus center, while increasing Hi-C variability.ConclusionsOur work elucidates how an individual constitutive heterochromatic region impacts genome organization and function. Specifically, one silent region indirectly assists in the hierarchical folding of the entire Neurospora genome by aggregating into the “typical” heterochromatin bundle normally observed in wild type nuclei, which may promote normal gene expression by positioning euchromatin in the nucleus center.

Multiple allelic configurations govern long-range Shh enhancer-promoter communication in the embryonic forebrain.

Developmental gene regulation requires input from enhancers spread over large genomic distances. Our understanding of long-range enhancer-promoter (E-P) communication, characterized as loops, remains incomplete without addressing the role of intervening chromatin. Here, we examine the topology of the entire Sonic hedgehog (Shh) regulatory domain in individual alleles from the mouse embryonic forebrain. Through sequential Oligopaint labeling and super-resolution microscopy, we find that the Shh locus maintains a compact structure that adopts several diverse configurations independent of Shh expression. The most frequent configuration contained distal E-P contacts at the expense of those more proximal to Shh, consistent with an interconnected loop. Genetic perturbations demonstrate that this long-range E-P communication operates by Shh-expression-independent and dependent mechanisms, involving CTCF binding sites and active enhancers, respectively. We propose a model whereby gene regulatory elements secure long-range E-P interactions amid an inherent architectural framework to coordinate spatiotemporal patterns of gene expression.

Predicting gene expression from histone marks using chromatin deep learning models depends on histone mark function, regulatory distance and cellular states.

To understand the complex relationship between histone mark activity and gene expression, recent advances have used in silico predictions based on large-scale machine learning models. However, these approaches have omitted key contributing factors like cell state, histone mark function or distal effects, which impact the relationship, limiting their findings. Moreover, downstream use of these models for new biological insight is lacking. Here, we present the most comprehensive study of this relationship to date - investigating seven histone marks in eleven cell types across a diverse range of cell states. We used convolutional and attention-based models to predict transcription from histone mark activity at promoters and distal regulatory elements. Our work shows that histone mark function, genomic distance and cellular states collectively influence a histone mark's relationship with transcription. We found that no individual histone mark is consistently the strongest predictor of gene expression across all genomic and cellular contexts. This highlights the need to consider all three factors when determining the effect of histone mark activity on transcriptional state. Furthermore, we conducted in silico histone mark perturbation assays, uncovering functional and disease related loci and highlighting frameworks for the use of chromatin deep learning models to uncover new biological insight.

Long-range regulation of transcription scales with genomic distance in a gene-specific manner.

Although critical for tuning the timing and level of transcription, enhancer communication with distal promoters is not well understood. Here, we bypass the need for sequence-specific transcription factors (TFs) and recruit activators directly using a chimeric array of gRNA oligos to target dCas9 fused to the activator VP64-p65-Rta (CARGO-VPR). We show that this approach achieves effective activator recruitment to arbitrary genomic sites, even those inaccessible when targeted with a single guide. We utilize CARGO-VPR across the Prdm8-Fgf5 locus in mouse embryonic stem cells (mESCs), where neither gene is expressed. Although activator recruitment to any tested region results in the transcriptional induction of at least one gene, the expression level strongly depends on the genomic distance between the promoter and activator recruitment site. However, the expression-distance relationship for each gene scales distinctly in a manner not attributable to differences in 3D contact frequency, promoter DNA sequence, or the presence of repressive chromatin marks at the locus.

Enhancer cooperativity can compensate for loss of activity over large genomic distances.

Enhancers are short DNA sequences that activate their target promoter from a distance; however, increasing the genomic distance between the enhancer and the promoter decreases expression levels. Many genes are controlled by combinations of multiple enhancers, yet the interaction and cooperation of individual enhancer elements are not well understood. Here, we developed a synthetic platform in mouse embryonic stem cells that allows building complex regulatory landscapes from the bottom up. We tested the system by integrating individual enhancers at different distances and confirmed that the strength of an enhancer contributes to how strongly it is affected by increased genomic distance. Furthermore, synergy between two enhancer elements depends on the distance at which the two elements are integrated: introducing a weak enhancer between a strong enhancer and the promoter strongly increases reporter gene expression, allowing enhancers to activate from increased genomic distances.

Identification of cell-type specificity, trans- and cis-acting functions of plant lincRNAs from single-cell transcriptomes.

Long noncoding RNAs, including intergenic lncRNAs (lincRNAs), play a key role in various biological processes throughout the plant life cycle, and the advent of single-cell RNA sequencing (scRNA-seq) technology has opened up a valuable avenue for scrutinizing the intricate roles of lincRNAs in cellular processes. Here, we identified a new batch of lincRNAs using scRNA-seq data from diverse tissues of plants (rice, Arabidopsis, tomato, and maize). Based on well-annotated single-cell transcriptome atlases, plant lincRNAs were found to possess the same level of cell-type specificity as mRNAs and to be involved in the differentiation of certain cell types based on pseudo-time analysis. Many lincRNAs were predicted to play a hub role in the cell-type-specific co-expression networks of lincRNAs and mRNAs, suggesting their trans-acting abilities. Besides, plant lincRNAs were revealed to have potential cis-acting properties based on their genomic distances and expression correlations with the neighboring mRNAs. Furthermore, an online platform, PscLncRNA (http://ibi.zju.edu.cn/psclncrna/), was constructed for searching and visualizing all identified plant lincRNAs with annotated potential functions. Our work provides new insights into plant lincRNAs at single-cell resolution and an important resource for understanding and further investigation of plant lincRNAs.

CTCF-dependent insulation of Hoxb13 and the heterochronic control of tail length

Mammalian tail length is controlled by several genetic determinants, among which are Hox13 genes, whose function is to terminate the body axis. Accordingly, the precise timing in the transcriptional activation of these genes may impact upon body length. Unlike other Hox clusters, HoxB lacks posterior genes between Hoxb9 and Hoxb13, two genes separated by a ca. 70 kb large DNA segment containing a high number of CTCF sites, potentially isolating Hoxb13 from the rest of the cluster and thereby delaying its negative impact on trunk extension. We deleted the spacer DNA to induce a potential heterochronic gain of function of Hoxb13 at physiological concentration and observed a shortening of the tail as well as other abnormal phenotypes. These defects were all rescued by inactivating Hoxb13 in-cis with the deletion. A comparable gain of function was observed in mutant Embryonic Stem (ES) cells grown as pseudoembryos in vitro, which allowed us to examine in detail the importance of both the number and the orientation of CTCF sites in the insulating activity of the DNA spacer. A short cassette containing all the CTCF sites was sufficient to insulate Hoxb13 from the rest of HoxB, and additional modifications of this CTCF cassette showed that two CTCF sites in convergent orientations were already capable of importantly delaying Hoxb13 activation in these conditions. We discuss the relative importance of genomic distance versus number and orientation of CTCF sites in preventing Hoxb13 to be activated too early during trunk extension and hence to modulate tail length.

Sorlinia euscelidii gen. nov., sp. nov., a novel acetic acid bacterium isolated from the leafhopper Euscelidius variegatus (Hemiptera: Cicadellidae).

Acetic acid bacteria - belonging to the Acetobacteraceae family - are found in the gut of many sugar-feeding insects. In this study, six strains have been isolated from the hemipteran leafhopper Euscelidius variegatus. While they exhibit high 16S rRNA gene sequence similarities to uncultured members of the Acetobacteraceae family, they could not be unequivocally assigned to any particular type species. Considering the clonality of the six isolates, the EV16PT strain was used as a representative of this group of isolates. The genome sequence of EV16PT is composed of a 2.388 Mbp chromosome, with a DNA G+C content of 57 mol%. Phylogenetic analyses based on the 16S rRNA gene sequence and whole-genome multilocus sequence analysis indicate that EV16PT forms a monophyletic clade with the uncultivated endosymbiont of Diaphorina citri, the Candidatus Kirkpatrickella diaphorinae. Such a phylogenetic clade is positioned between those of Asaia-Swaminathania and Kozakia. The genomic distance metrics based on gene and protein sequences support the proposal that EV16PT is a new species belonging to a yet-undescribed genus. It is a rod-shaped Gram-stain-negative bacterium, strictly aerobic, non-motile, non-spore-forming, showing optimal growth without salt (NaCl) at 30 °C and pH of 6-7. The major quinone is Q10, and the dominant cellular fatty acids (>10%) are C18:l ω7c, C19 : 0 cyclo ω6c, C16 : 0 and C19 : 1 2OH. The polar lipid profile comprises diphosphatidylglycerol, phosphatidylethanolamine and phosphatidylcholine, along with unidentified aminophospholipids, glycophospholipids, aminolipids and lipids. Based on a polyphasic approach, including phylogenetic, phylogenomic, genome relatedness, phenotypic and chemotaxonomic characterisations, EV16PT (= KCTC 8296T, = DSM 117028T) is proposed as a representative of a novel species in a novel genus with the proposed name Sorlinia euscelidii gen. nov., sp. nov., in honour of Prof. Claudia Sorlini, an Italian environmental microbiologist at the University of Milan who inspired the research on microbial diversity, including symbiosis in plants and animals.

A Constitutive Heterochromatic Region Shapes Genome Organization and Impacts Gene Expression in Neurospora crassa.

Organization of the eukaryotic genome is essential for proper function, including gene expression. In metazoans, chromatin loops and Topologically Associated Domains (TADs) organize genes into transcription factories, while chromosomes occupy nuclear territories in which silent heterochromatin is compartmentalized at the nuclear periphery and active euchromatin localizes to the nucleus center. A similar hierarchical organization occurs in the fungus Neurospora crassa where its seven chromosomes form a Rabl conformation typified by heterochromatic centromeres and telomeres independently clustering at the nuclear membrane, while interspersed heterochromatic loci aggregate across Megabases of linear genomic distance to loop chromatin in TAD-like structures. However, the role of individual heterochromatic loci in normal genome organization and function is unknown. We examined the genome organization of a Neurospora strain harboring a ~47.4 kilobase deletion within a temporarily silent, facultative heterochromatic region, as well as the genome organization of a strain deleted of a 110.6 kilobase permanently silent constitutive heterochromatic region. While the facultative heterochromatin deletion minimally effects local chromatin structure or telomere clustering, the constitutive heterochromatin deletion alters local chromatin structure, the predicted three-dimensional chromosome conformation, and the expression of some genes, which are qualitatively repositioned into the nucleus center, while increasing Hi-C variability. Our work elucidates how an individual constitutive heterochromatic region impacts genome organization and function. Specifically, one silent region indirectly assists in the hierarchical folding of the entire Neurospora genome by aggregating into the "typical" heterochromatin bundle normally observed in wild type nuclei, which may promote normal gene expression by positioning euchromatin in the nucleus center.

From computational models of the splicing code to regulatory mechanisms and therapeutic implications.

Since the discovery of RNA splicing and its role in gene expression, researchers have sought a set of rules, an algorithm or a computational model that could predict the splice isoforms, and their frequencies, produced from any transcribed gene in a specific cellular context. Over the past 30 years, these models have evolved from simple position weight matrices to deep-learning models capable of integrating sequence data across vast genomic distances. Most recently, new model architectures are moving the field closer to context-specific alternative splicing predictions, and advances in sequencing technologies are expanding the type of data that can be used to inform and interpret such models. Together, these developments are driving improved understanding of splicing regulatory mechanisms and emerging applications of the splicing code to the rational design of RNA- and splicing-based therapeutics.

Resequencing reveals population structure and genetic diversity in Tibetan sheep

BackgroundThe Tibetan sheep is one of the three major primitive sheep breeds in China, representing a unique and high-quality genetic resource in the Qinghai-Tibet Plateau and neighboring high-altitude regions, exhibiting exceptional adaptability to high-altitude climatic environments. However, research on the genetic relationships among different populations of Tibetan sheep at the whole-genome level remains insufficient. This study aims to explore the population structure and historical dynamics among 11 Tibetan sheep populations, accurately assess the genetic diversity within the populations, and providing a theoretical basis for the development of targeted genetic breeding strategies for Tibetan sheep.ResultsIn this study, a total of 10,884,454 high-quality SNPs were obtained. All Tibetan sheep populations exhibited varying degrees of linkage disequilibrium, with similar decay rates; among them, the WT population showed the fastest decay, while the TS population exhibited the slowest decay rate. Analyses using Tajima’s D and π indicated that the genetic diversity levels of the Tibetan sheep populations are generally low. Fst results revealed that most populations exhibited moderate to low levels of genetic differentiation. The effective population size among Tibetan sheep populations showed an increasing trend over time. The evolutionary relationships among Tibetan sheep populations reflect the correlation between their geographical locations and genomic genetic distances, while also indirectly confirming the impact of historical activities such as early human migration, admixture, fusion, and expansion on the population sizes and distributions of Tibetan sheep.ConclusionsThe results indicate that the genetic diversity levels and genetic differentiation among Tibetan sheep populations are relatively low. In this study, we identified the genetic characteristics of Tibetan sheep populations, which exhibit low levels of diversity, genetic differentiation, and a strong population structure. A deeper genomic exploration of the population structure and diversity status of Tibetan sheep populations will provide theoretical support for subsequent genetic breeding and diversity conservation efforts.

Local adaptation can cause both peaks and troughs in nucleotide diversity within populations.

The amount of standing variation present within populations is a fundamental quantity of interest in population genetics, commonly represented by calculating the average number of differences between pairs of nucleotide sequences (nucleotide diversity, π). It is well understood that both background and positive selection can cause reductions in nucleotide diversity, but less clear how local adaptation affects it. Depending on the assumptions and parameters, some theoretical studies have emphasized how local adaptation can reduce nucleotide diversity, while others have shown that it can increase it. Here, we explore how local adaptation shapes genome-wide patterns in within-population nucleotide diversity, extending previous work to study the effects of polygenic adaptation, genotypic redundancy, and population structure. We show that local adaptation produces two very different patterns depending on the relative strengths of migration and selection, either markedly decreasing or increasing within-population diversity at linked sites at equilibrium. At low migration, regions of depleted diversity can extend large distances from the causal locus, with substantially more diversity eroded than expected with background selection. With higher migration, peaks occur over much smaller genomic distances but with much larger magnitude changes in diversity. Across spatially extended environmental gradients, both patterns can be found within a single species, with increases in diversity at the center of the range and decreases towards the periphery. Our results demonstrate that there is no universal diagnostic signature of local adaptation based on within-population nucleotide diversity, so it will not be broadly useful for explaining increased FST. However, given that neither background nor positive selection inflate diversity, when peaks are found they suggest local adaptation may be acting on a causal allele in the region.

Improved inference of population histories by integrating genomic and epigenomic data.

With the availability of high-quality full genome polymorphism (SNPs) data, it becomes feasible to study the past demographic and selective history of populations in exquisite detail. However, such inferences still suffer from a lack of statistical resolution for recent, for example bottlenecks, events, and/or for populations with small nucleotide diversity. Additional heritable (epi)genetic markers, such as indels, transposable elements, microsatellites, or cytosine methylation, may provide further, yet untapped, information on the recent past population history. We extend the Sequential Markovian Coalescent (SMC) framework to jointly use SNPs and other hyper-mutable markers. We are able to (1) improve the accuracy of demographic inference in recent times, (2) uncover past demographic events hidden to SNP-based inference methods, and (3) infer the hyper-mutable marker mutation rates under a finite site model. As a proof of principle, we focus on demographic inference in Arabidopsis thaliana using DNA methylation diversity data from 10 European natural accessions. We demonstrate that segregating single methylated polymorphisms (SMPs) satisfy the modeling assumptions of the SMC framework, while differentially methylated regions (DMRs) are not suitable as their length exceeds that of the genomic distance between two recombination events. Combining SNPs and SMPs while accounting for site- and region-level epimutation processes, we provide new estimates of the glacial age bottleneck and post-glacial population expansion of the European A. thaliana population. Our SMC framework readily accounts for a wide range of heritable genomic markers, thus paving the way for next-generation inference of evolutionary history by combining information from several genetic and epigenetic markers.

Methods for evaluating unsupervised vector representations of genomic regions.

Representation learning models have become a mainstay of modern genomics. These models are trained to yield vector representations, or embeddings, of various biological entities, such as cells, genes, individuals, or genomic regions. Recent applications of unsupervised embedding approaches have been shown to learn relationships among genomic regions that define functional elements in a genome. Unsupervised representation learning of genomic regions is free of the supervision from curated metadata and can condense rich biological knowledge from publicly available data to region embeddings. However, there exists no method for evaluating the quality of these embeddings in the absence of metadata, making it difficult to assess the reliability of analyses based on the embeddings, and to tune model training to yield optimal results. To bridge this gap, we propose four evaluation metrics: the cluster tendency score (CTS), the reconstruction score (RCS), the genome distance scaling score (GDSS), and the neighborhood preserving score (NPS). The CTS and RCS statistically quantify how well region embeddings can be clustered and how well the embeddings preserve information in training data. The GDSS and NPS exploit the biological tendency of regions close in genomic space to have similar biological functions; they measure how much such information is captured by individual region embeddings in a set. We demonstrate the utility of these statistical and biological scores for evaluating unsupervised genomic region embeddings and provide guidelines for learning reliable embeddings.

Multi-omics profiling of longitudinal samples reveals early genomic changes in follicular lymphoma

Follicular lymphoma (FL) is the most common indolent type of B-cell non-Hodgkin lymphoma. Advances in treatment have improved overall survival, but early relapse or transformation to aggressive disease is associated with inferior outcome. To identify early genetic events and track tumor clonal evolution, we performed multi-omics analysis of 94 longitudinal biopsies from 44 FL patients; 22 with transformation (tFL) and 22 with relapse without transformation (nFL). Deep whole-exome sequencing confirmed recurrent mutations in genes encoding epigenetic regulators (CREBBP, KMT2D, EZH2, EP300), with similar mutational landscape in nFL and tFL patients. Calculation of genomic distances between longitudinal samples revealed complex evolutionary patterns in both subgroups. CREBBP and KMT2D mutations were identified as genetic events that occur early in the disease course, and cases with CREBBP KAT domain mutations had low risk of transformation. Gains in chromosomes 12 and 18 (TCF4), and loss in 6q were identified as early and stable copy number alterations. Identification of such early and stable genetic events may provide opportunities for early disease detection and disease monitoring. Integrative analysis revealed that tumors with EZH2 mutations exhibited reduced gene expression of numerous histone genes, including histone linker genes. This might contribute to the epigenetic dysregulation in FL.

Unveiling the genetic landscape: Exploring the SSR-based genetic architecture and amino acid dissection of Gossypium barbadense and G. darwinii genomes

Genetic maps highlight the genome organization and structure but also provide the chance of tagging superior traits for crop improvement through marker-assisted selection. Amino acids are building blocks of proteins and perform crucial function in regulating the signaling of molecules involved in the development and growth of plants. Plant architecture also have an impact on crop productivity. In order to select elite cultivars for breeding and identification of favorable alleles and their functional properties, a deep understanding of genetic architecture and development of genetic map is essential. In present investigation, an interspecific cross of Gossypium barbadense XH-18 × G. darwinii 5-7 was made to develop a genetic map utilizing single sequence repeat markers for the dissection of amino acids involved in genetic architecture of G. barbadense and G. darwinii. We measured chromosomal distribution of 20 amino acids across the whole genome of both species. The map consists of 613 markers spread across all 26 chromosomes, covering 2371.4 cM of cotton genome with an average inter-marker distance of 9.35 cM. The marker number anchored on the chromosomes varied from 5 to 76 with an average of 23.57 on each chromosome. The Dt sub-genome had more markers (83.03%) than the At sub-genome (15.66%). Moreover, the longest chromosome was 143.387 cM, the shortest was 58.430 cM, and the average length was 91.207 cM. The Dt subgenome spans a greater genomic distance than the At subgenome. A sum of 21,035 genes were discovered, covering the complete genome of G. barbadense; G. darwinii and have been found to be involved in tRNA 3'-trailer cleavage, macromolecule modification, peptide deformylase activity, response to biotic stimulus and defense response. The minimum Glutamic acid (Glu), Histidine (His), and Lysine (Lys) were found on Chr.13 (0.00-17.74), Chr.02 (0.00-8.01), and Chr.06 (0.00-17.97), respectively found through chromosomal amino acid dissection. The genome-wide SSR interspecific genetic map of G. barbadense and G. darwinii is first of its kind, and studying chromosomal distribution of amino acids will set a landmark step to dissect the genome structure of G. darwinii.