Josh Paul Clevenger

A chromosome-level genome assembly of Thecaphora frezzii, cause of peanut smut, reveals the largest genome among the true smut fungi

The paper presents a chromosome-level genome assembly of Thecaphora frezzii, the largest genome among true smut fungi, and compares it with 49 other smut fungi genomes to explore genomic traits and evolutionary adaptations.

KhufuEnv, an auxiliary toolkit for building computational pipelines for plant and animal breeding

KhufuEnv is an open-source toolkit for building genomic analysis pipelines, demonstrating rapid QTL identification and ROH calculation on published datasets.

An X-linked sex determination mechanism in cannabis and hop

The paper identifies an X-linked sex determination mechanism in cannabis and hop, showing that an X-linked gene involved in ethylene biosynthesis controls female inflorescence development, while the Y chromosome lacks clear sex-determining genes.

Long-Read Low-Pass Sequencing for High-Resolution Trait Mapping

This study develops and applies long-read low-pass sequencing for high-resolution trait mapping in peanut, showing improved variant detection and cost-effectiveness compared to short-read methods.

A haplotype-resolved chromosome-level assembly and annotation of European hazelnut (C. avellana cv. Jefferson) provides insight into mechanisms of eastern filbert blight resistance

The paper presents a haplotype-resolved chromosome-level genome assembly of European hazelnut, identifying gene candidates linked to EFB resistance.

Accurate analysis of short read sequencing in complex genomes: A case study using QTL-seq to target blanchability in peanut (Arachis hypogaea)

The paper introduces Khufu, a pipeline that improves QTL-seq accuracy in complex genomes by filtering loci based on optimal short read alignment, validated using peanut and other species datasets.

AhNGE : A Database for Arachis hypogaea Nodule Developmental Gene Expression

AhNGE provides RNAseq data and ortholog analysis for peanut nodule development, enabling comparative genomics with other legumes and non-legumes.

Machine learning as an effective method for identifying true SNPs in polyploid plants

This paper develops machine learning models to identify true SNPs in polyploid plants, achieving high accuracy using real and simulated data.