Roshan Kulkarni

Mr. Roshan Kulkarni

Iowa State University

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 June 2019 in BMC Genomics
Verified
Journal Article
Open access
PDF file
POPaul I. Otyama
Paul I. Otyama
AWAndrew Wilkey
Andrew Wilkey
RKRoshan Kulkarni
Roshan Kulkarni
TATeshale Assefa
Teshale Assefa
YCYe Chu
Ye Chu
SCSteven B. Cannon
Steven B. Cannon
Due to the recent domestication of peanut from a single tetraploidization event, relatively little genetic diversity underlies the extensive morphological and agronomic diversity in peanut cultivars today. To broaden the genetic variation in future breeding programs, it is necessary to characterize germplasm accessions for new sources of variation and to leverage the power of genome-wide association studies (GWAS) to discover markers associated with traits of interest. We report an analysis of linkage disequilibrium (LD), population structure, and genetic diversity, and examine the ability of GWA to infer marker-trait associations in the U.S. peanut mini core collection genotyped with a 58 K SNP array. LD persists over long distances in the collection, decaying to r2 = half decay distance at 3.78 Mb. Structure within the collection is best explained when separated into four or five groups (K = 4 and K = 5). At K = 4 and 5, accessions loosely clustered according to market type and subspecies, though with numerous exceptions. Out of 107 accessions, 43 clustered in correspondence to the main market type subgroup whereas 34 did not. The remaining 30 accessions had either missing taxonomic classification or were classified as mixed. Phylogenetic network analysis also clustered accessions into approximately five groups based on their genotypes, with loose correspondence to subspecies and market type. Genome wide association analysis was performed on these lines for 12 seed composition and quality traits. Significant marker associations were identified for arachidic and behenic fatty acid compositions, which despite having low bioavailability in peanut, have been reported to raise cholesterol levels in humans. Other traits such as blanchability showed consistent associations in multiple tests, with plausible candidate genes. Based on GWA, population structure as well as additional simulation results, we find that the primary limitations of this collection for GWAS are a small collection size, significant remaining structure/genetic similarity and long LD blocks that limit the resolution of association mapping. These results can be used to improve GWAS in peanut in future studies – for example, by increasing the size and reducing structure in the collections used for GWAS.

26 June 2019 in BMC Genomics
Verified
Journal Article
Open access
PDF file
TATeshale Assefa
Teshale Assefa
OPOtyama I Paul
Otyama I Paul
ABAnne V Brown
Anne V Brown
SKScott R. Kalberer
Scott R. Kalberer
RKRoshan Kulkarni
Roshan Kulkarni
SCSteven B. Cannon
Steven B. Cannon
Breeding programs benefit from information about marker-trait associations for many traits, whether the goal is to place those traits under active selection or to maintain them through background selection. Association studies are also important for identifying accessions bearing potentially useful alleles by characterizing marker-trait associations and allelic states across germplasm collections. This study reports the results of a genome-wide association study and evaluation of epistatic interactions for four agronomic and seed-related traits in soybean. Using 419 diverse soybean accessions, together with genotyping data from the SoySNP50K Illumina Infinium BeadChip, we identified marker-trait associations for internode number (IN), plant height (PH), seed weight (SW), and seed yield per plant (SYP). We conducted a genome-wide epistatic study (GWES), identifying candidate genes that show evidence of SNP-SNP interactions. Although these candidate genes will require further experimental validation, several appear to be involved in developmental processes related to the respective traits. For IN and PH, these include the Dt1 determinacy locus (a soybean meristematic transcription factor), as well as a pectinesterase gene and a squamosa promoter binding gene that in other plants are involved in cell elongation and the vegetative-to-reproductive transition, respectively. For SW, candidate genes include an ortholog of the AP2 gene, which in other species is involved in maintaining seed size, embryo size, seed weight and seed yield. Another SW candidate gene is a histidine phosphotransfer protein - orthologs of which are involved in cytokinin-mediated seed weight regulating pathways. The SYP association loci overlap with regions reported in previous QTL studies to be involved in seed yield. This study further confirms the utility of GWAS and GWES approaches for identifying marker-trait associations and interactions within a diverse germplasm collection.

18 October 2020 in Genes
Verified
Journal Article
Open access
PDF file
RKRoshan Kulkarni
Roshan Kulkarni
RCRATAN CHOPRA
RATAN CHOPRA
JCJennifer Chagoya
Jennifer Chagoya
CSCharles E. Simpson
Charles E. Simpson
MBMichael R. Baring
Michael R. Baring
MBMark Burow
Mark Burow
The use of molecular markers in plant breeding has become a routine practice, but the cost per accession can be a hindrance to the routine use of Quantitative Trait Loci (QTL) identification in breeding programs. In this study, we demonstrate the use of targeted re-sequencing as a proof of concept of a cost-effective approach to retrieve highly informative allele information, as well as develop a bioinformatics strategy to capture the genome-specific information of a polyploid species. SNPs were identified from alignment of raw transcriptome reads (2 × 50 bp) to a synthetic tetraploid genome using BWA followed by a GATK pipeline. Regions containing high polymorphic SNPs in both A genome and B genomes were selected as targets for the resequencing study. Targets were amplified using multiplex PCR followed by sequencing on an Illumina HiSeq. Eighty-one percent of the SNP calls in diploids and 68% of the SNP calls in tetraploids were confirmed. These results were also confirmed by KASP validation. Based on this study, we find that targeted resequencing technologies have potential for obtaining maximum allele information in allopolyploids at reduced cost.

24 October 2024 in Genes
Verified
Journal Article
Open access
PDF file
CSCheng-Jung Sung
Cheng-Jung Sung
RKRoshan Kulkarni
Roshan Kulkarni
AHAndrew Hillhouse
Andrew Hillhouse
CSCharles E. Simpson
Charles E. Simpson
JCJohn Cason
John Cason
MBMark Burow
Mark Burow
The identification of informative molecular markers is useful for linkage mapping and can benefit genome-wide association studies by providing fine-scale information about sequence variations. However, high-throughput genotyping approaches are not cost-effective for labs that require frequent use, such as breeding programs that need to perform genotyping on large populations with hundreds of individuals. The number of single nucleotide polymorphism markers generated by those approaches can be far more than needed for most breeding programs; instead, breeders focus on the use of at most hundreds of polymorphic molecular markers for analysis. To help make use of molecular markers a routine tool for breeding programs, we aim to develop a cost-effective genotyping system by using the Tecan Allegro Targeted Resequencing V2 kit. This provides a customized probe design, which indicates that all the DNA fragments synthesized are known targets. SNPs obtained from previous peanut next-generation sequencing data were pre-filtered and selected as targets. These SNP targets were polymorphic among different tetraploid accessions and were selected to be distinguishable from paralogs. A total of 5154 probes were designed to detect 2770 SNP targets and were tested on 48 accessions, which include some closely related sister lines from a breeding population. The results indicated that genotyping by a targeted resequencing approach reduced the cost from around USD 28 (SNP chip and GBS) to USD 18 per sample, while providing polymorphic markers with accurate SNP calls. With this cost-effective genotyping platform, pre-selected SNP markers can be used effectively and routinely for more breeding programs.

18 April 2020 in bioRxiv
Verified
Preprint
Open access
PDF file
OPOtyama I Paul
Otyama I Paul
RKRoshan Kulkarni
Roshan Kulkarni
KCKelly Dawn Chamberlin
Kelly Dawn Chamberlin
POPeggy Ozias-Akins
Peggy Ozias-Akins
YCYe Chu
Ye Chu
JCJuliet Chu
Juliet Chu
Cultivated peanut ( Arachis hypogaea ) is an important oil, food, and feed crop worldwide. The USDA peanut germplasm collection currently contains 8,982 accessions. In the 1990s, 812 accessions were selected as a core collection on the basis of phenotype and country of origin. The present study reports genotyping results for the entire available core collection. Each accession was genotyped with the Arachis_Axiom2 SNP array, yielding 14,430 high-quality, informative SNPs across the collection. Additionally, a subset of 253 accessions was replicated, using between two and five seeds per accession, to assess heterogeneity within these accessions. the genotypic diversity of the core is mostly captured in five genotypic clusters, which have some correspondence with botanical variety and market type. There is little genetic clustering by country of origin, reflecting peanut’s rapid global dispersion in the 18th and 19th centuries. A genetic cluster associated with the hypogaea/aequatoriana/peruviana varieties, with accessions coming primarily from Bolivia, Peru, and Ecuador, is consistent with these having been the earliest landraces. The genetics, phenotypic characteristics, and biogeography are all consistent with previous reports of tetraploid peanut originating in Southeast Bolivia. Analysis of the genotype data indicates an early genetic radiation, followed by regional distribution of major genetic classes through South America, and then a global dissemination that retains much of the early genetic diversity in peanut. Comparison of the genotypic data relative to alleles from the diploid progenitors also indicates that subgenome exchanges, both large and small, have been major contributors to the genetic diversity in peanut. All data is available at the National Ag Library: https://doi.org/10.15482/USDA.ADC/1518508 and at PeanutBase: https://peanutbase.org/data/public/Arachis_hypogaea/mixed.esm.KNWV