Biology subjects

Varshney, R. K.

Publications and source records attributed to Varshney, R. K..

12 recordsLinked to original sources

bioRxiv2026

WheatPanRef: a unified linear pan-reference genome for wheat genomics

Linear reference genomes provide coordinates for read mapping, variant discovery and multi-omics data integration, yet assembly-specific coordinate systems limit data reuse, particularly in the large, repetitive and polyploid wheat genome. Here, we present WheatPanRef, a scalable linear pan-reference and coordinate framework that integrates wheat sequence diversity within a stable coordinate system. We reconciled independent Chinese Spring assemblies by resolving structural and sequences discrepancies to constructed a 14.50-Gb consensus sequences CS-NP. Using CS-NP as backbone, we incorporated 4.37 Gb of non-redundant non-CS sequences from 37 diverse wheat accessions, generating WheatPanRef (18.87 Gb). WheatPanRef improves read-alignment performance and captures putative wild-relative introgressions and sequences absent or unanchored in conventional references. Bidirectional coordinate-translation system enables accurate projection between WheatPanRef and individual assemblies without remapping, facilitating genomic resource integration and reuse. WheatPanRef provides a common sequence and coordinate foundation for population-scale wheat genomics, with potential utility for genomic resource integration in other complex crops.

genomics↗

bioRxiv2026

Next-Generation Soybean Haplotype Map as A Genomic Resource for Enhanced Trait Discovery and Functional Analysis

We present a global soybean haplotype map generated from whole-genome sequencing of 1,278 Glycine max and Glycine soja accessions, comprising 11.37 million SNPs and 2.05 million short insertions and deletions. This map (GmHapMap-II) captures unprecedented worldwide genetic diversity, reflecting the broad extent of the global soybean gene pool. Population structure analyses revealed six geographically distinct subpopulations that affected the linkage and shaped the recombination. The haplotype variation map was used to identify novel genomic regions associated with crude protein content on chromosome 15 that were not detected by a lower SNP density array. LD-based haplotype analysis revealed a superior haplotype for crude protein content. The constructed haplotype map enabled detailed characterization of haplotype diversity and copy number polymorphism at the SCN-associated rhg-1 and Rhg-4 loci, revealing both novel haplotype structures and germplasm lines with elevated CNV relative to previously characterized genotypes. We employed the HapMap matrix for a multi-class variations ML-based genomic prediction approach to predict phenotypes for SCN and catalogued the gene-centric haplotypes in a user-friendly database. The analysis revealed the extent of deleterious alleles present in the soybean germplasm and how breeders have deployed beneficial alleles and purged deleterious ones. The haplotype map will serve as a major genomic resource for trait-based mapping, enhancing efforts in the genomics-enabled development of improved cultivars.

genomics↗

bioRxiv2025

Whole genome sequencing-based multi-locus association mapping for kernel iron, zinc and protein content in groundnut

Malnutrition is a major global challenge, especially in the developing regions, where improving the nutritional content of staple crops is a significant step towards alleviating hidden hunger. Groundnut, a nutrient rich legume contains several mineral nutrients, high protein, essential amino-acids and vitamins that are required for human health. In this study, multi-season phenotyping data for kernel iron (Fe), zinc (Zn) content and protein content (PC) and whole genome re-sequencing (WGRS) data on mini-core collection, were used to perform genome-wide association study (GWAS) analysis. Phenotypic variability analysis revealed a large variation in the Fe (7.6 - 42.8 ppm), Zn (10.9 - 62.4 ppm) and PC (12.7 - 33.6%). GWAS analysis identified a total of 15 marker-trait associations (MTAs) and 28 candidate genes for pooled season data, as well as 44 MTAs and 62 candidate genes for individual seasons. Key candidate genes like MYB transcription factor (Arahy.QI0PHV, Arahy.1I6ZSS), Zn finger MYM type protein, RING finger MYM type protein (Arahy.7P97F6, Arahy.9R964H, Arahy.I3B88T) and NAC domain protein (Arahy.LV3APC), associated with the Fe and Zn homeostasis pathway, genes related to protein homeostasis, such as protein kinase family protein (Arahy.4D7KBI), and E3 ubiquitin-protein ligase (Arahy.PE3CF6), were also identified within significant MTA regions. These findings provide basis for the detection and characterization of the possible candidate genes related to the nutritional quality traits. Single nucleotide polymorphism (SNP)-based KASP (Kompetitive Allele Specific Polymerase Chain Reaction) markers for 9 SNPs were designed and validated. Of these, three markers (snpAH00636, snpAH00641 and snpAH00644) showed polymorphism which could be deployed in the genomics-assisted breeding for the development of nutrient-rich groundnut varieties.

plant biology↗

bioRxiv2025

Genomic analysis uncovers unique haplotype signatures from subspecies and agronomic types associated with blanchability in groundnut

Blanchability, defined as the ease of seed coat removal after roasting, is a vital trait for enhancing processing efficiency and product quality in groundnut (Arachis hypogaea L.). To enable a comprehensive haplotype-level genetic dissection of this trait, SNPs derived from whole-genome resequencing (WGRS) were used to perform genome-wide association study (GWAS) using multi-locus models (BLINK and FarmCPU) on a diverse groundnut mini-core collection phenotyped across two crop seasons. A total of 26 significant SNP-trait associations (STAs) were identified across multiple chromosomes, with major loci on chromosomes Ah05, Ah06, and Ah17, some of which were further validated using KASP (Kompetitive Allele-Specific PCR) markers. Candidate genes, such as those involved in cell wall biosynthesis (e.g., galactoside 2-alpha-L-fucosyltransferase-like protein, protein kinase superfamily members, and glycerophosphoryl diester phosphodiesterase 3), were found to be within linkage disequilibrium (LD) of the identified STAs, suggesting their plausible association with blanchability. Haplo-pheno analyses identified superior high-blanchability haplotypes; Ah05HapBL3, Ah06HapBL5, Ah06HapBL10, and Ah17HapBL6, which were predominantly found in the fastigiata subspecies (including Valencia and Spanish bunch agronomic types) from South Asia and South America, while the low-blanchability haplotypes were from hypogaea subspecies (including Virginia runner and Virginia bunch agronomic types) from Africa. Overall, this study provides valuable insights for customizing blanchability through haplotype-based breeding of processing-grade cultivars thereby improving groundnut value chains to meet diverse industrial demands.

genomics↗

bioRxiv2025

Genomic analysis reveals the interplay between ABA-GA in determining dormancy duration in groundnut

Groundnut is an important leguminous crop however; its productivity and seed quality are frequently reduced due to lack of fresh seed dormancy (FSD). To address this challenge, a mini-core collection of 184 accessions was phenotyped to identify donors in each agronomic type, in addition to analysing data on whole genome re-sequencing and multi-season phenotypic evaluations to identify stable marker-trait associations (MTAs) associated with FSD. Phenotypic analysis revealed substantial variability in dormancy durations, with days to 50% germination (DFG) ranging from 1 to 30 days. Multi-locus genome-wide association studies (ML-GWAS) identified 27 MTAs in individual seasons and 12 MTAs in pooled seasons data, respectively. Key candidate genes identified included Cytochrome P450 superfamily proteins, protein kinase superfamily proteins, and MYB transcription factors involved in the Abscisic acid (ABA) pathway, as well as F-box interaction domain proteins, ATP-binding ABC transporters, associated with the Gibberellic acid (GA) pathway. SNP-based KASP (Kompetitive Allele-Specific Polymerase chain reaction) markers for 12 SNPs were developed and validated, of these 6 markers (snpAH00577, snpAH00580, snpAH00582, snpAH00585, snpAH00586 and snpAH00588) showed polymorphism between dormant and non-dormant lines. Incorporating favourable dormant alleles into breeding strategies could enable the development of high-yielding cultivars with a dormancy period of 2-3 weeks.

genomics↗

bioRxiv2024

Crops under continuous cultivation exhibit less plasticity than those under interrupted cultivation

Evolutionary studies indicate that species in stable environments often evolve with reduced plasticity, whereas those in variable environments tend to maintain higher plasticity to adapt to changing conditions. Our study explores whether this evolutionary principle extends to cultivated crops. In crop science, phenotypic plasticity is generally understood as a short-term response to environmental factors. Yet, the long-term evolutionary changes in both plastic and non-plastic traits under different cultivation regimes remain largely unexamined. Herein, we developed a novel mechanistic crop growth model, collectively termed the Trait-Environment Fitness Interaction (TEFI) Model, to study if and how trait plasticity varies among crops under different cultivation regimes. Our results, based on the TEFI Model, show higher trade-offs between fitness and plasticity. Specifically, we observed the evolution of higher plasticity in crops subjected to intermittent cultivation, which experienced more variable environments. However, this higher plasticity does not compensate for fitness losses due to the high rate of environmental unpredictability. Conversely, species under relatively stable conditions tend to evolve with reduced plasticity. Using real-world crop datasets, we validated the theoretical predictions of the TEFI Model, which suggest that the longer the interruption, the higher the plasticity. Our results highlight the evolutionary impact of cultivation patterns on trait plasticity and its importance in crop fitness. Ultimately, our findings illustrate how evolutionary principles of plasticity, as captured by the TEFI Model, can inform sustainable crop improvement strategies.

plant biology↗

bioRxiv2024

Distinct genetic architecture for trait mean and plasticity in chickpea

Crop plants often face rapid environmental changes, and their ability to adapt to novel conditions depends on whether specific traits can adjust to match these changes. This capacity for adjustment, known as phenotypic plasticity, is frequently regarded as a mere "response" rather than a distinct trait with its own genetic basis, particularly in agricultural science. As a result, plasticity is often oversimplified and viewed as an undesirable phenomenon when the goal is to achieve trait stability. In this study, we present a quantitative metric to measure phenotypic plasticity and provide evidence, through genome-wide association studies (GWAS) in chickpea, that plasticity is indeed a genetically based trait, comparable to any other agronomic trait. This foundational study paves the way for future GWAS efforts to harness phenotypic plasticity, offering new insights for crop improvement strategies.

plant biology↗

bioRxiv2024

Chromosome-level genome assembly of autotetraploid Selenicereus megalanthus and gaining genomic insights into the evolution of trait patterning in diploid and polyploid pitaya species

Yellow pitaya (Selenicereus megalanthus, 2n=4x=44) breeding remains severely hindered due to lacking a reference genome. Here we report yellow pitayas high-quality chromosome-level genome assembly and link the phenotypic trait with genomic data, based on Hi-C, ATAC, and RNA-seq data of specific tissues. We declared yellow pitaya as an autotetraploid with a 7.16 Gb genome size (harboring 27,246 high confidence genes) and majorly evolved from diploid ancestors, which remains unknown. Beyond generating the genome assembly, we explored the 3D chromatin organization which revealed insights into the genome, compartments A (648 and 519), compartments B (728 and 1064), topologically associated domains-TADs (3376 and 2031), and varying numbers of structural variations (SVs) in diploid and polyploid pitaya species, respectively. Overall, TAD boundaries were enriched with the motifs of AP2, WRKY18/60/75, MYB63/116, PHL2, and GATA8 in both pitaya species. By linking the open chromatin genomic structure to function, we identified the major changes in betalains biosynthesis pathway in diploid and polyploid pitaya. Moreover, the higher genetic expression of SmeADH1 [Chr11, Compartment A (135400000 - 135500000), genes inside the TAD region (135480000 - 135520000)], and lower expression of HuDOPA [Chr11, Compartment A (87100000 - 87200000), genes inside the TAD region (87160000-87200000)] acts as a key regulator of yellow and red color on the pericarp of polyploid and diploid pitaya, respectively. In addition, higher expression of HuCYP76AD1 genes in diploid pitaya and lower expression of SmeCYP76AD1 in polyploid pitaya potentially created the difference in the oxidase process that led to the production of betacyanin and betaxanthin, respectively. Furthermore, our results revealed not only the type of motifs that play a potential role in trait patterning but we also further uncovered that motif count in TAD-boundaries may impact the gene expression within the TAD regions of diploid and polyploid pitaya. Our valuable genomic resource and comparison of 3D euchromatin architecture of diploid and polyploid pitaya species will not only aid in the advancement of molecular breeding efforts but also offer insights into the organization of genomes, SVs, compartmentalization (A and B), and TADs, which have the potential to strengthen the idea of TADs-based trait improvement to achieve global food security.

plant biology↗

bioRxiv2023

Pan-genome of pear provides insights into the differentiation of fruit quality traits between Asian and European pears

The pear (Pyrus spp.) is a remarkable fruit, well known for its diverse flavors, textures, culinary versatility, and global horticultural importance. However, the genetic diversity responsible for its extensive phenotypic variations remains largely unexplored. Here, we de novo assembled and annotated the genomes of the maternal (PsbM) and paternal (PsbF) lines of the hybrid Yuluxiang pear and constructed the first pear pangenome of 1.15Gb by combining these two genomes with five previously published pear genomes. Using the constructed pangenome, we identified 21,224 gene PAVs and 1,158,812 SNPs in the non-reference genome that were absent in the PsbM reference genome. Compared with SNP markers, we found that PAV-based analysis provides additional insights into the pear population structure. In addition, we also revealed that some genes associated with pear fruit quality traits have differential occurrence frequencies and differential gene expression between Asian and European populations. Moreover, our analysis of the pear pangenome revealed a mutated SNP and an insertion in the promoter region of the gene PsbMGH3.1 potentially enhances sepal shedding in Xuehuali which is vital for pear quality. This research helps further capture the genetic diversity of pear populations and provides valuable genomic resources for accelerating pear breeding.

genomics↗

bioRxiv2021

Yield is negatively correlated with nucleotide-binding leucine-rich repeat gene content in soybean

The availability of increasing quantities of crop pangenome data permits the detailed association of gene content with agronomic traits. Here, we investigate disease resistance gene content of diverse soybean cultivars and report a significant negative correlation between the number of NLR resistance (R) genes and yield. We find no association between R-genes with seed weight, oil or protein content, and we find no correlation between yield and the number of RLK, RLP genes, or the total number of genes. These results suggest that recent yield improvement in soybean may be partially associated with the selective loss of NLR genes. Three quarters of soybean NLR genes do not show presence/absence variation, limiting the ability to select for their absence, and so the deletion or disabling of select NLR genes may support future yield improvement.

plant biology↗

bioRxiv2020

A novel high-accuracy genome assembly method utilizing a high-throughput workflow

Across domains of biological research using genome sequence data, high-quality reference genome sequences are essential for characterizing genetic variation and understanding the genetic basis of phenotypes. However, the construction of genome assemblies for various species is often hampered by complexities of genome organization, especially repetitive and complex sequences, leading to mis-assembly and missing regions. Here, we describe a high-throughput gold standard genome assembly workflow using a large-scale bacterial artificial chromosome (BAC) library with a refined two-step pooling strategy and the Lamp assembler algorithm. This strategy minimizes the laborious processes of physical map construction and clone-by-clone sequencing, enabling inexpensive sequencing of several thousand BAC clones. By applying this strategy with a minimum tiling path BAC clone library for the short arm of chromosome 2D (2DS) of bread wheat, 98% of BAC sequences, covering 92.7% of the 2DS chromosome, were assembled correctly for this species with a highly complex and repetitive genome. We also identified 48 large mis-assemblies in the reference wheat genome assembly (IWGSC RefSeq v1.0) and corrected these large mis-assemblies in addition to filling 92.2% of the gaps in RefSeq v1.0. Our 2DS assembly represents a new benchmark for the assembly of complex genomes with both high accuracy and efficiency.

genomics↗

bioRxiv2019

A sorghum Practical Haplotype Graph facilitates genome-wide imputation and cost-effective genomic prediction

Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to increase genetic gain and accelerate cultivar development. To help with data management and storage, we developed a sorghum Practical Haplotype Graph (PHG) pangenome database that stores all identified haplotypes and variant information for a given set of individuals. We developed two PHGs in sorghum, one with 24 individuals and another with 398 individuals, that reflect the diversity across genic regions of the sorghum genome. 24 founders of the Chibas sorghum breeding program were sequenced at low coverage (0.01x) and processed through the PHG to identify genome-wide variants. The PHG called SNPs with only 5.9% error at 0.01x coverage - only 3% lower than its accuracy when calling SNPs from 8x coverage sequence. Additionally, 207 progeny from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes in the progeny were imputed from the parental haplotypes available in the PHG and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from 0.57-0.73 for different traits, and are similar to prediction accuracies obtained with genotyping-by-sequencing (GBS) or markers from sequencing targeted amplicons (rhAmpSeq). This study provides a proof of concept for using a sorghum PHG to call and impute SNPs from low-coverage sequence data and also shows that the PHG can unify genotype calls from different sequencing platforms. By reducing the amount of input sequence needed, the PHG has the potential to decrease the cost of genotyping for genomic selection, making GS more feasible and facilitating larger breeding populations that can capture maximum recombination. Our results demonstrate that the PHG is a useful research and breeding tool that can maintain variant information from a diverse group of taxa, store sequence data in a condensed but readily accessible format, unify genotypes from different genotyping methods, and provide a cost-effective option for genomic selection for any species.

genomics↗