About

Professor Awais Khan is a faculty member at Cornell University affiliated with the Section of Plant Pathology & Plant-Microbe Biology within the School of Integrative Plant Science. He holds a PhD in Plant Breeding and Genetics/Plant Pathology. His research focuses on disease resistance mechanisms, quantitative genetics, genomics, and bioinformatics, particularly in rosaceous fruits such as apples. Professor Khan's work aims to understand and improve genetic resistance to diseases affecting apples, including fire blight and apple scab, through advanced genetic and molecular approaches. His lab integrates plant breeding, pathology, and genomics to dissect the genetic basis of disease resistance and to develop improved disease-resistant apple varieties. He leads a research group that includes graduate students and postdoctoral researchers working on various aspects of plant disease resistance, pathogen genomics, and functional validation of candidate genes. Professor Khan's expertise and research contribute significantly to the understanding of host-pathogen interactions and the development of sustainable disease management strategies in fruit crops.

Research topics

• Genetics
• Biology
• Computer Science
• Artificial Intelligence
• Botany
• Evolutionary biology

Selected publications

• Energy-Efficient MPC for SiC/GaN-Based Power Electronics in Consumer Device

  2025-01-11 · 1 citations

  article1st authorCorresponding

  This paper presents a novel approach to energy optimization in consumer electronic devices utilizing Silicon Carbide (SiC) and Gallium Nitride (GaN) based power electronics through the application of Model Predictive Control (MPC). As consumer devices increasingly demand higher energy efficiency, the integration of advanced semiconductor technologies such as SiC and GaN offers significant improvements in power conversion efficiency and thermal performance. This research focuses on developing a theoretical framework for MPC, specifically designed for the unique characteristics of these power electronics. The system is modeled mathematically and the MPC algorithm is designed to minimize energy consumption while maintaining device performance. The effectiveness of the proposed control strategy is validated through detailed simulations. The results indicate that the MPC approach significantly improves energy efficiency compared to traditional control methods, demonstrating its potential for widespread application in next-generation consumer electronics.

  PublisherDOI

• Fine-mapping of the Vhc1 QTL for apple scab resistance on linkage group 1 of ‘Honeycrisp’

  Research Square · 2025-06-18

  preprintOpen accessSenior author
  PublisherOA PDFDOI

• A pan-generic marker panel for apples to enable genetic research and breeding across <i>Malus</i> species

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-09

  preprintOpen accessSenior authorCorresponding

  Wild Malus species harbor untapped genetic diversity to advance apple breeding, particularly for disease resistance and stress tolerance. However, existing marker panels, developed mainly using Malus domestica accessions, introduce ascertainment bias and limit detecting rare variants in wild species. We developed and validated a medium-density and cost-effective pan-generic 3K apple DArTag panel optimized to capture genome-wide variation across the Malus genus. The panel was constructed using conserved, syntenic, and collinear genomic blocks identified within the core genome of 13 Malus accessions for cross-species transferability. The panel was validated across three bi-parental mapping populations totaling 593 progeny. Across these populations, 2,461–3,234 SNP markers were polymorphic and 1,482–2,620 were informative. Each population contained over 900 multiallelic micro-haplotype loci, with several hundred loci exhibiting three or four distinct haplotypes. Markers were uniformly distributed across all 17 chromosomes, each containing between 60–230 informative SNPs. The panel was further evaluated on 174 diverse germplasm accessions from 20 Malus species. It exhibited strong cross-species transferability, exceptionally low rates of missing data (&lt;0.5%), and clear genetic differentiation between wild and domesticated accessions. Genome-wide association studies (GWAS) identified a major locus on chromosome 4 significantly linked to fruit length, weight, and width in addition to trait-specific associations on chromosomes 1, 6, 9, and 11. The cost-effectiveness of genotyping per sample (&lt;$15), combined with these results, underscore the panel′s broad utility for quantitative trait locus (QTL) mapping in bi-parental and diverse populations, marker-assisted selection in the breeding programs, and genetic diversity analysis across the Malus genus.

  PublisherOA PDFDOI

• Linkage map construction and QTL mapping for morphological traits in <i>Ipomoea trifida</i> , a diploid sweetpotato relative

  The Plant Genome · 2025-09-01

  articleOpen access

  Ipomoea trifida G. Don (2n = 2x = 30) is considered the closest known diploid relative and a wild ancestor of the autohexaploid sweetpotato, Ipomoea batatas (L.) Lam. (2n = 6x = 90). This study aimed to map quantitative trait loci (QTLs) in a diploid full-sib population (M9 × M19) consisting of 210 progenies based on a high-density genetic linkage map constructed with single-nucleotide polymorphisms (SNPs). In a randomized complete block design with four replications, the phenotypic evaluation of 11 morphological traits was conducted for 188 individuals in 2016 at the International Potato Center under screenhouse conditions in San Ramón, Peru. Heritabilities ranged from 0.30 to 0.80, and genetic correlations varied from -0.22 to 1. An integrated genetic map was constructed with 15 linkage groups and 6410 SNPs spanning 2440.47 cM using the Onemap v.3.0 R package. Major misassemblies were identified and properly fixed on chromosomes 2, 3, and 7. QTL mapping was performed using the composite interval mapping approach for each trait with fullsibQTL v.0.0.901 R package. A total of 37 QTLs were identified, with up to 42.39% of the proportion of phenotypic variance explained by a major QTL on chromosome 3 for a leaf shape-related trait. Reference genome refining and QTL-linked markers contribute to advancing genetic and genomic research on I. trifida and may support sweetpotato breeding programs targeting ornamental traits.

  PublisherDOI

• Investigating the Relationship Between Large Chromosomal Rearrangements and Disease Aggressiveness in North American <scp> <i>Erwinia amylovora</i> </scp> Strains

  Plant Pathology · 2025-03-24

  articleOpen accessSenior authorCorresponding

  ABSTRACT The phytopathogenic bacterium Erwinia amylovora is responsible for causing fire blight, a devastating disease affecting rosaceous plants, including apples and pears. E. amylovora strains exhibit differences in virulence depending on the genetic resistance status of the host and environmental factors. While genetic variations among E. amylovora strains are known to contribute to their genetic diversity, host range and biology, the impact of large chromosomal rearrangements on key bacterial phenotypes like disease aggressiveness is understudied. In order to investigate the relationship between large chromosomal inversions (LCIs) and fire blight aggressiveness of E. amylovora strains, we screened 16 E. amylovora isolates for their fire blight aggressiveness on immature Bartlett pears and continued with de novo genome sequencing of these strains originating from North America to characterise the association of detected LCIs with disease aggressiveness. The immature Bartlett pear assay showed significant differences in fire blight aggressiveness between the strains. Genome sequence comparison showed an average of 68 insertions, 11,166 single‐nucleotide polymorphisms (SNPs), and 10,773 insertions/deletions (indels) across the 16 isolates when compared to the reference strain Ea1189. Additionally, eight distinct LCIs were identified among sequenced isolates. All isolates carried the ubiquitous pEA29 plasmid, whereas EaRJO001 has an additional pEA27 plasmid. Although E. amylovora strains exhibited significant differences in fire blight aggressiveness, their association with LCIs remains unclear.

  PublisherOA PDFDOI

• Development of an open-pollinated genetic mapping framework to facilitate the identification of QTL in apples

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-13

  preprintOpen access

  Abstract Genetic mapping of traits in apples ( Malus domestica ), a temperate woody perennial, is challenging due to high heterozygosity, long juvenility, and extensive spatial maintenance requirements for the populations. These factors limit the effective use of traditional quantitative trait locus (QTL) mapping methods in identifying the genetic basis of traits critical for apple production, marketability and sustainability. We explored the use of open-pollinated (OP) genetic mapping as an alternative to conventional bi-parental QTL mapping and genome wide association studies (GWAS). A QTL was simulated and the performance of a mixed linear model (MLM) and a multi-locus mixed model (MLMM) in QTL mapping accuracy was compared using a genotyping-by-sequencing (GBS) dataset of seven interspecific Royal Gala × M. sieversii bi-parental F1 populations. The simulation results show that the MLMM outperformed the MLM by accurately identifying the simulated QTL. Analysis of power indicated that a population size of 137 individuals is required to reach an α = 0.8 for a simulated major effect QTL. Mapping resolution analysis showed that a population size of 470-600 individuals, depending on local recombination rates, is necessary to achieve high resolution within the OP population. Simulations demonstrate the potential of OP-based genetic mapping for identifying QTL in apples, reducing the logistical challenges associated with traditional QTL mapping methods. Our results show that OP-based genetic mapping could be used to speed up the identification of novel alleles directly from diverse germplasm collections in apples. Core Ideas Bi-parental QTL mapping in apples is constrained by limited diversity, high costs, and long-term orchard space. OP-based mapping avoids controlled pollination, clonal propagation, and large-scale F1 orchard requirements. OP-based mapping offers an alternative to bi-parental mapping by leveraging existing germplasm and natural crosses. OP-mapping enables QTL discovery absent full pedigree information to strategically capture broad genetic diversity. OP F1 populations support fast QTL detection, aiding rapid breeding against emerging pathogens.

  PublisherOA PDFDOI

• Advancing Clean Energy: Robust Adaptive Control for SiC/GaN Inverter Systems

  2025-08-23

  article1st authorCorresponding

  The rapid adoption of wide-bandgap (WBG) semiconductors, such as Silicon Carbide (SiC) and Gallium Nitride (GaN), has transformed inverter technology, enabling higher efficiency, faster switching, and superior thermal performance critical for clean and green energy systems. However, traditional control methods like PI and PWM struggle to fully harness these advantages under high-frequency and dynamic conditions prevalent in smart grids, electric vehicles, and renewable energy platforms. This paper proposes a novel adaptive control framework tailored for SiC/GaN-based inverters, addressing challenges in efficiency, thermal management, and dynamic response. By dynamically adjusting control parameters based on real-time current, reference, and measured quantities, the proposed approach optimizes power conversion efficiency, enhances thermal stability, and ensures robust transient performance. Comprehensive simulations demonstrate significant improvements in power density, reduced switching losses, and enhanced fault tolerance compared to conventional methods. With a focus on scalable solutions for next-generation energy systems, this framework supports the integration of WBG inverters in sustainable applications, offering a pathway to compact, high-performance designs for clean energy grids and electrified transportation.

  PublisherDOI

• Assessment of genetic diversity and population structure of Malus sieversii and Malus niedzwetzkyana from Kazakhstan using high-throughput genotyping

  Tree Genetics & Genomes · 2025-07-08

  articleOpen access

  Malus sieversii, the primary progenitor of domesticated apples and a vital genetic resource in Kazakhstan, faces increasing threats from aging, degradation, diseases, and insect infestations despite ongoing conservation efforts and the establishment of genetic reserves. The aim of our work was to examine genetic variability, population structure and characterize the alleles of resistance loci for fire blight, apple scab and powdery mildew from M. sieversii and Malus niedzwetzkyana populations in Kazakhstan. We genotyped 352 accessions of M. sieversii and M. niedzwetzkyana sampled from various regions in Kazakhstan using Axiom JKI50kMd SNP array. Wild apple populations from Zhongar Alatau exhibited reduced genetic diversity, with expected heterozygosity (He) of 0.21, and minimal gene flow. In contrast, populations from Ile Alatau demonstrated higher genetic variability, with expected heterozygosity reaching 0.32, likely influenced by gene flow from cultivated apple varieties. Principal component analysis (PCA), clustering, and phylogenetic tree reconstruction consistently identified distinct population groupings corresponding to their geographic origin. Populations from Zhongar Alatau and Tarbagatai formed a relatively homogeneous group, while populations from Ile Alatau and Ketmen clustered into another group, reflecting a higher degree of genetic mixing and heterogeneity. M. niedzwetzkyana emerged as a separate and genetically divergent cluster and demonstrated a higher frequency of polymorphic disease resistance markers compared to M. sieversii, reinforcing its potential as a valuable genetic resource for breeding disease-resistant apple varieties. These findings provide critical insights for conservation strategies, emphasizing the importance of preserving genetic diversity in wild apple populations to support long-term breeding and disease management efforts.

  PublisherOA PDFDOI

• Fine-mapping, candidate gene identification, and marker development for the apple scab resistance gene <i>Rvi2</i>

  Journal of Experimental Botany · 2025-11-13

  articleOpen access

  Breeding elite apple cultivars with scab resistance is a key global goal, as reliance on fungicides is unsustainable. The causal fungus, Venturia inaequalis, evolves rapidly, threatening cultivars with single-gene resistance. Since the 1980s, breeding programmes have introduced novel resistance sources via backcrossing. Here, we generated a haplotype-phased genome assembly of Russian apple R12740-7A and an Oxford Nanopore assembly of the Rvi2-resistance accession TSR34T15, enabling detailed dissection of the Rvi2 resistance locus. Fine-mapping using a 'Royal Gala' × TSR34T15 segregating family delimited Rvi2 to a narrow genomic interval, within which we identified a 10 041 bp long terminal repeat retrotransposon (LTR-RT) insertion-an insert-based structural variant (SV) strongly linked with Rvi2. Notably, this LTR-RT harbours an FPPS gene, a member of the farnesyl pyrophosphate/geranylgeranyl pyrophosphate (FPP/GGPP) synthase family, located 2 kb from a key candidate defence gene. Although the FPPS gene exhibits stable expression, its integration within the retrotransposon suggests a cis-regulatory role, potentially priming adjacent defence genes for robust up-regulation upon pathogen attack. We validated the marker derived from this SV in diverse germplasms and successfully implemented it in marker-assisted selection across extensive seedling cohorts. This marker will streamline the development of scab-resistant apple varieties.

  PublisherDOI

• Population-level gene copy number variations reveal distinct genetic properties of different Malus species

  BMC Genomics · 2025-07-23 · 2 citations

  articleOpen accessSenior author

  Copy number variations (CNVs) are crucial in plant evolution, adaptation, and domestication. In this study, we explored how CNVs contribute to genetic diversity, evolution, and adaptation during apple domestication. We examined the genome-wide CNV profiles and segmental duplications (SDs) in 116 Malus accessions, including domesticated apple (Malus domestica) and its primary progenitor species (M. sieversii and M. sylvestris). On average, two accessions of the same species showed differences in at least 7,000 genes with varying copy number (CN) profiles. In contrast, accessions from different species had at least 20,000 genes with differing CN profiles. Notably, 700 genes exhibited distinct CN profiles between M. domestica and M. sieversii, with an enrichment in defense response genes. Genes related to fruit ripening, flavor, and anthocyanin biosynthesis had higher copy numbers in M. domestica. Additionally, 360 genes showed differential CN profiles between M. domestica and M. sylvestris, with enrichment in polygalacturonase activity, which may influence differences in fruit flavor. The study also identified 3,000 genes with significant CN differentiation (VST > 0.28) between M. domestica rootstock and scion cultivars enriched in lignin metabolic pathways, underscoring their role in stress resistance and mechanical support. Segmental duplications were particularly enriched in genes related to sorbitol metabolism, fruit development, and fruit quality traits, highlighting their evolutionary importance in defining apple morphology and physiology. These findings offer valuable insights into the evolutionary mechanisms driving apple domestication and adaptation and provide a comprehensive resource for future research and apple breeding.

  PublisherOA PDFDOI

Frequent coauthors

• Jugpreet Singh

  ResearchWorks (United States)

  77 shared

• Zhangjun Fei

  Cornell University

  44 shared

• Richard Tegtmeier

  Plant (United States)

  30 shared

• Dorcus C. Gemenet

  Centro Internacional de Mejoramiento de Maíz Y Trigo

  29 shared

• Mingyue Zhang

  Inner Mongolia University

  22 shared

• Mengfan Qin

  22 shared

• Mercy Kitavi

  21 shared

• Anže Švara

  Cornell University

  20 shared

Labs

• Khan Lab: Mechanisms of Fruit Diseases and ResistancePI

Education

• Ph.D., fire blight of apples

  Swiss Federal Institute of Technology (ETH)

• M.S.

  Georg-August University