Genome skimming-based STMS marker discovery and its validation in temperate hill bamboo Drepanostachyum falcatum

De novo SSR markers development and genetic diversity assessment in Ailanthus excelsa in India

Ailanthus excelsa is a fast-growing, multipurpose agroforestry tree species of Indian Arid Regions (IAR). It is widely cultivated as tree outside forests (TOFs) on farm lands, roadside, canal banks, etc., where the genetic stocks were randomly planted. To ensure the availability of quality planting materials (QPM) for industrial profitability, the germplasm must undergo a systematic genetic improvement program. Genetic variability in the base population is crucial for effective selection, but the lack of genomic resources and marker impedes this process. This study aimed to generate genome sequence information and de novo development of simple sequence repeats (SSRs) in A. excelsa. About 96 million raw reads were generated using Illumina platform, assembled into ~ 183,000 contigs with 33% GC content and an N50 value of 641 bp. A total of 7,667 microsatellite repeats were identified, with di-nucleotides being the most abundant. AT rich repeats were more prevalent than GC rich motifs. A total of 3,696 primer pairs were designed, and 150 of these were selected for validation. In PCR, 145 SSRs were positively amplified and 15 showed polymorphic banding pattern. These polymorphic SSRs were used to characterize 213 individuals from northern and central India. SSR analysis revealed high gene diversity (He = 0.71; Ar = 9.12) with negligible genetic differentiation in populations. The study presents a comprehensive set of de novo SSR markers and provides baseline knowledge of genetic structure of A. excelsa, essential for conservation and long-term genetic improvement programs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-025-01566-6.

First de novo genome-specific development, characterization and validation of simple sequence repeat (SSR) markers in Bambusa polymorpha, a commercially important bamboo of India

The natural population of Bambusa polymorpha have not been genetically enumerated due to a lack of genome sequence information or robust species-specific molecular marker. The present study was conducted to develop and validate genome-wide de novo simple sequence repeat (SSRs) markers in B. polymorpha through shallow-pass genome sequencing. The genome sequence data of about 13 Gb was generated using Illumina technology, and high-quality sequence reads were de novo assembled into 1,390,995 contigs with GC content 42.34%, contig N 50 value 1047 bp. The Benchmark Universal Single-Copy Ortholog (BUSCO) analysis indicated 75.29% of complete and single-copy genome assembly. By scanning of genome assembly, a total of 73,468 simple sequence repeats (SSRs) were identified, and 44,383 primer pairs were designed. Repeat analysis revealed that the dinucleotide and trinucleotide repeats were most abundantly distributed in the genome with 52.95 and 41.17%, respectively. A subset of 33 SSRs was randomly selected for their PCR amplification and polymorphism in 16 random individuals. Of these, 29 SSRs were successfully amplified with the expected product size and 20 showed polymorphic banding patterns. Polymorphic SSRs were characterized by high expected heterozygosity (H e = 0.72) and polymorphism information content (PIC = 0.68). The clustering pattern obtained using the neighbor joining (NJ) dendrogram revealed the genotypes were clustered in accordance with their geographical locations. The genomic and marker information generated in this study are novel and useful for future studies for genetic improvement and conservation of B. polymorpha.

Exploring Taxonomic and Genetic Relationships in the Pinus mugo Complex Using Genome Skimming Data

Genome skimming is a novel approach that enables obtaining large-scale genomic information based on high-copy DNA fractions from shallow whole-genome sequencing. The simplicity of this method, low analysis costs, and large amounts of generated data have made it widely used in plant research, including species identification, especially in the case of protected or endangered taxa. This task is particularly difficult in the case of closely related taxa. The Pinus mugo complex includes several dozen closely related taxa occurring in the most important mountain ranges in Europe. The taxonomic rank, origin, or distribution of many of these taxa have been debated for years. In this study, we used genome skimming and multilocus DNA barcoding approaches to obtain different sequence data sets and also to determine their genetic diversity and suitability for distinguishing closely related taxa in the Pinus mugo complex. We generated seven different data sets, which were then analyzed using three discrimination methods, i.e., tree based, distance based, and assembling species by automatic partitioning. Genetic diversity among populations and taxa was also investigated using haplotype network analysis and principal coordinate analysis. The proposed data set based on divergence hotspots is even twenty-times more variable than the other analyzed sets and improves the phylogenetic resolution of the Pinus mugo complex. In light of the obtained results, Pinus × rhaetica does not belong to the Pinus mugo complex and should not be identified with either Pinus uliginosa or Pinus rotundata. It seems to represent a fixed hybrid or introgressant between Pinus sylvestris and Pinus mugo. In turn, Pinus mugo and Pinus uncinata apparently played an important role in the origins of Pinus uliginosa and Pinus rotundata.

Ecological niche modelling and population genetic analysis of Indian temperate bamboo Drepanostachyum falcatum in the western Himalayas

The present study was conducted to understand the key ecological and biological questions of conservation importance in Drepanostachyum falcatum which aimed to map potential distribution in the western Himalayas and decipher spatial genetic structure. Eco-distribution maps were generated through ecological niche modelling using the Maximum Entropy (MaxEnt) algorithm implemented with 228 geocoordinates of species presence and 12 bioclimatic variables. Concomitantly, 26 natural populations in the western Himalayas were genetically analysed using ten genomic sequence-tagged microsatellite (STMS) markers. Model-derived distribution was adequately supported with appropriate statistical measures, such as area under the 'receiver operating characteristics (ROC)' curve (AUC; 0.917 ± 0.034)", Kappa (K; 0.418), normalized mutual information (NMI; 0.673) and true skill statistic (TSS; 0.715). Further, Jackknife test and response curves showed that the precipitation (pre- and post-monsoon) and temperature (average throughout the year and pre-monsoon) maximize the probabilistic distribution of D. falcatum. We recorded a wide and abundant (4096.86 km²) distribution of D. falcatum in the western Himalayas with maximum occurrence at 1500 to 2500 m asl. Furthermore, marker analysis exemplified high gene diversity with low genetic differentiation in D. falcatum. Relatively, the populations of Uttarakhand are more genetically diverse than Himachal Pradesh, whereas within the Uttarakhand, the Garhwal region captured a higher allelic diversity than Kumaon. Clustering and structure analysis indicated two major gene pools, where genetic admixing appeared to be controlled by long-distance gene flow, horizontal geographical distance, aspect, and precipitation. Both the species distribution map and population genetic structure derived herein may serve as valuable resources for conservation and management of Himalayan hill bamboos.

The relationships between heavy metals and bacterial communities in a coal gangue site

Coal is the main source of energy for China's economic development, but coal gangue dumps are a major source of heavy metal pollution. Bacterial communities have a major effect on the bioremediation of heavy metals in coal gangue dumps. The effects of different concentrations of heavy metals on the composition of bacterial communities in coal gangue sites remain unclear. Soil bacterial communities from four gangue sites that vary in natural heavy metal concentrations were investigated using high-throughput sequencing in this study. Correlations among bacterial communities, heavy metal concentrations, physicochemical properties of the soil, and the composition of dissolved organic matter of soil in coal gangue dumps were also analyzed. Our results indicated that Actinobacteriota, Proteobacteria, Chloroflexi, Acidobacteriota, and Gemmatimonadota were the bacterial taxa most resistant to heavy metal stress at gangue sites. Heavy metal contamination may be the main cause of changes in bacterial communities. Heavy metal pollution can foster mutually beneficial symbioses between microbial species. Microbial-derived organic matter was the main source of soil organic matter in unvegetated mining areas, and this could affect the toxicity and transport of heavy metals in soil. Polar functional groups such as hydroxyl and ester groups (A_226-400) play an important role in the reaction of cadmium (Cd) and lead (Pb), and organic matter with low molecular weight (S_R) tends to bind more to mercury (Hg). In addition to heavy metals, the content of nitrogen (N), phosphorus (P), and total organic carbon (TOC) also affected the composition of the bacterial communities; TOC had the strongest effect, followed by N, SOM, and P. Our findings have implications for the microbial remediation of heavy metal-contaminated soils in coal gangue sites and sustainable development.

Genome survey sequencing-based SSR marker development and their validation in Dendrocalamus longispathus

Bamboo is an important genetic resource in India, supporting rural livelihood and industries. Unfortunately, most Indian bamboo taxa are devoid of basic genomic or marker information required to comprehend the genetic processes for further conservation and management. In this study, we perform genome survey sequencing for development of de novo genomic SSRs in Dendrocalamus longispathus, a socioeconomically important bamboo species of northeast India. Using Illumina platform, 69.49 million raw reads were generated and assembled into 1,145,321 contig with GC content 43% and N50 1228 bp. In total, 46,984 microsatellite repeats were mined-out wherein di-nucleotide repeats were most abundant (54.71%) followed by mono- (31.91%) and tri-repeats (9.85%). Overall, AT-rich repeats were predominant in the genome, but GC-rich motifs were more frequent in tri-repeats. Afterwards, 21,596 SSR loci were successfully tagged with the primer pairs, and a subset of 50 were validated through polymerase chain reaction amplification. Of these, 36 SSR loci were successfully amplified, and 16 demonstrated polymorphism. Using 13 polymorphic SSRs, a moderate level of gene diversity (He = 0.480; Ar = 3.52) was recorded in the analysed populations of D. longispathus. Despite the high gene flow (Nm = 4.928) and low genetic differentiation (F_ST = 0.119), severe inbreeding (F_IS = 0.407) was detected. Further, genetic clustering and STRUCTURE analysis revealed that the entire genetic variability is captured under two major gene pools. Conclusively, we present a comprehensive set of novel SSR markers in D. longispathus as well as other taxa of tropical woody bamboos.

Genome-wide characterization leading to simple sequence repeat (SSR) markers development in Shorea robusta

Tropical rainforests in Southeast Asia are enriched by multifarious biota dominated by Dipterocarpaceae. In this family, Shorea robusta is an ecologically sensitive and economically important timber species whose genomic diversity and phylogeny remain understudied due to lack of datasets on genetic resources. Smattering availability of molecular markers impedes population genetic studies indicating a necessity to develop genomic databases and species-specific markers in S. robusta. Accordingly, the present study focused on fostering de novo low-depth genome sequencing, identification of reliable microsatellites markers, and their validation in various populations of S. robusta in Uttarakhand Himalayas. With 69.88 million raw reads assembled into 1,97,489 contigs (read mapped to 93.2%) and a genome size of 357.11 Mb (29 × coverage), Illumina paired-end sequencing technology arranged a library of sequence data of ~ 10 gigabases (Gb). From 57,702 microsatellite repeats, a total of 35,049 simple sequence repeat (SSR) primer pairs were developed. Afterward, among randomly selected 60 primer pairs, 50 showed successful amplification and 24 were found as polymorphic. Out of which, nine polymorphic loci were further used for genetic analysis in 16 genotypes each from three different geographical locations of Uttarakhand (India). Prominently, the average number of alleles per locus (Na), observed heterozygosity (Ho), expected heterozygosity (He), and the polymorphism information content (PIC) were recorded as 2.44, 0.324, 0.277 and 0.252, respectively. The accessibility of sequence information and novel SSR markers potentially enriches the current knowledge of the genomic background for S. robusta and to be utilized in various genetic studies in species under tribe Shoreae.

Genome skimming-based simple sequence repeat (SSR) marker discovery and characterization in Grevillea robusta

Proteaceae, a largely southern hemisphere family consisting of 80 genera distributed in Australia and southern Africa as its centres of greatest diversity, also extends well in northern and southern America. Under this family, Grevillea robusta is a fast-growing species got popularity in farm and avenue plantations. Despite the ecological and economic importance, the species has not yet been investigated for its genetic improvement and genome-based studies. Only a few molecular markers are available for the species or its close relatives, which hinders  genomic and population genetics studies. Genetic markers have been intensively applied for the main strategies in breeding programs, especially for the economically important traits. Hence, it is of utmost priority to develop genomic database resources and species-specific markers for studying quantitative genetics in G. robusta. Given this, the present study aimed to develop de novo genome sequencing, robust microsatellites markers, sequence annotation and their validation in different stands of G. robusta in northern India. Library preparation and sequencing were carried out using Illumina paired-end sequencing technology. Approximately, ten gigabases (Gb) sequence data with 70.87 million raw reads assembled into 425,923 contigs (read mapped to 76.48%) comprising 455 Mb genome size (23 × coverage) generated through genome skimming approach. In total, 9421 simple sequence repeat (SSR) primer pairs were successfully designed from 13,335 microsatellite repeats. Afterward, a subset of 161 primer pairs was randomly selected, synthesized and validated. All the tested primers showed successful amplification but only 13 showed polymorphisms. The polymorphic SSRs were further used to estimate the measures of genetic diversity in 12 genotypes each from the states of Punjab, Haryana, Himachal Pradesh and Uttarakhand. Importantly, the average number of alleles (Na), observed heterozygosity (Ho), expected heterozygosity (He), and the polymorphism information content (PIC) were recorded as 2.69, 0.356, 0.557 and 0.388, respectively. The availability of sequence information and newly developed SSR markers could potentially be used in various genetic analyses and improvements through molecular breeding strategies for G. robusta.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01035-w.