Jan Dvorak

Jan Dvorak


Research Focus & Metrics

Academic Career Length

31Years (1996-Present)

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

Representative Publications

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29 May 2008 in BMC Bioinformatics
Verified
Journal Article
Open access
PDF file
FYFrank M You
Frank M You
NHNaxin Huo
Naxin Huo
YGYong Qiang Gu
Yong Qiang Gu
MLMing-Cheng Luo
Ming-Cheng Luo
YMYaqin Ma
Yaqin Ma
OAOlin D Anderson
Olin D Anderson
Background: Microsatellite (simple sequence repeat – SSR) and single nucleotide polymorphism (SNP) markers are two types of important genetic markers useful in genetic mapping and genotyping. Often, large-scale genomic research projects require high-throughput computer-assisted primer design. Numerous such web-based or standard-alone programs for PCR primer design are available but vary in quality and functionality. In particular, most programs lack batch primer design capability. Such a high-throughput software tool for designing SSR flanking primers and SNP genotyping primers is increasingly demanded.Results: A new web primer design program, BatchPrimer3, is developed based on Primer3. BatchPrimer3 adopted the Primer3 core program as a major primer design engine to choose the best primer pairs. A new score-based primer picking module is incorporated into BatchPrimer3 and used to pick position-restricted primers. BatchPrimer3 v1.0 implements several types of primer designs including generic primers, SSR primers together with SSR detection, and SNP genotyping primers (including single-base extension primers, allele-specific primers, and tetra-primers for tetra-primer ARMS PCR), as well as DNA sequencing primers. DNA sequences in FASTA format can be batch read into the program. The basic information of input sequences, as a reference of parameter setting of primer design, can be obtained by pre-analysis of sequences. The input sequences can be pre-processed and masked to exclude and/or include specific regions, or set targets for different primer design purposes as in Primer3Web and primer3Plus. A tab-delimited or Excel-formatted primer output also greatly facilitates the subsequent primer-ordering process. Thousands of primers, including wheat conserved intron-flanking primers, wheat genome-specific SNP genotyping primers, andBrachypodiumSSR flanking primers in several genome projects have been designed using the program and validated in several laboratories.Conclusion: BatchPrimer3 is a comprehensive web primer design program to develop different types of primers in a high-throughput manner. Additional methods of primer design can be easily integrated into future versions of BatchPrimer3. The program with source code and thousands of PCR and sequencing primers designed for wheat andBrachypodiumare accessible athttp://wheat.pw.usda.gov/demos/BatchPrimer3/.

24 April 2021 in The Plant Journal
Verified
Journal Article
Open access
PDF file
TZTingting Zhu
Tingting Zhu
LWLe Wang
Le Wang
HRHélène Rimbert
Hélène Rimbert
JRJuan C. Rodriguez
Juan C. Rodriguez
KDKarin R. Deal
Karin R. Deal
MLMing-Cheng Luo
Ming-Cheng Luo
Summary: Until recently, achieving a reference‐quality genome sequence for bread wheat was long thought beyond the limits of genome sequencing and assembly technology, primarily due to the large genome size and > 80% repetitive sequence content. The release of the chromosome scale 14.5‐Gb IWGSC RefSeq v1.0 genome sequence of bread wheat cv. Chinese Spring (CS) was, therefore, a milestone. Here, we used a direct label and stain (DLS) optical map of the CS genome together with a prior nick, label, repair and stain (NLRS) optical map, and sequence contigs assembled with Pacific Biosciences long reads, to refine the v1.0 assembly. Inconsistencies between the sequence and maps were reconciled and gaps were closed. Gap filling and anchoring of 279 unplaced scaffolds increased the total length of pseudomolecules by 168 Mb (excluding Ns). Positions and orientations were corrected for 233 and 354 scaffolds, respectively, representing 10% of the genome sequence. The accuracy of the remaining 90% of the assembly was validated. As a result of the increased contiguity, the numbers of transposable elements (TEs) and intact TEs have increased in IWGSC RefSeq v2.1 compared with v1.0. In total, 98% of the gene models identified in v1.0 were mapped onto this new assembly through development of a dedicated approach implemented in the MAGAAT pipeline. The numbers of high‐confidence genes on pseudomolecules have increased from 105 319 to 105 534. The reconciled assembly enhances the utility of the sequence for genetic mapping, comparative genomics, gene annotation and isolation, and more general studies on the biology of wheat.

1 November 2017 in Nature
Verified
Journal Article
Open access
PDF file
MLMing-Cheng Luo
Ming-Cheng Luo
YGYong Q. Gu
Yong Q. Gu
DPDaniela Puiu
Daniela Puiu
HWHao Wang
Hao Wang
STSven O. Twardziok
Sven O. Twardziok
JDJan Dvorak
Jan Dvorak
A combination of advanced sequencing and mapping techniques is used to produce a reference genome of Aegilops tauschii, progenitor of the wheat D genome, providing a valuable resource for comparative genetic studies. Sequencing the genomes of crops plants provides useful resources for crop improvement and breeding. Jan Dvořák, Katrien Devos, Steven Salzberg and colleagues report a reference genome for Aegilops tauschii, the diploid progenitor of the D genome of hexaploid wheat. They use a combination of ordered-clone genome sequencing, whole-genome shotgun sequencing and BioNano optical genome mapping to assemble this large and highly repetitive genome. This provides a useful resource for comparative genomics studies of wheat. Aegilops tauschii is the diploid progenitor of the D genome of hexaploid wheat1 (Triticum aestivum, genomes AABBDD) and an important genetic resource for wheat2,3,4. The large size and highly repetitive nature of the Ae. tauschii genome has until now precluded the development of a reference-quality genome sequence5. Here we use an array of advanced technologies, including ordered-clone genome sequencing, whole-genome shotgun sequencing, and BioNano optical genome mapping, to generate a reference-quality genome sequence for Ae. tauschii ssp. strangulata accession AL8/78, which is closely related to the wheat D genome. We show that compared to other sequenced plant genomes, including a much larger conifer genome, the Ae. tauschii genome contains unprecedented amounts of very similar repeated sequences. Our genome comparisons reveal that the Ae. tauschii genome has a greater number of dispersed duplicated genes than other sequenced genomes and its chromosomes have been structurally evolving an order of magnitude faster than those of other grass genomes. The decay of colinearity with other grass genomes correlates with recombination rates along chromosomes. We propose that the vast amounts of very similar repeated sequences cause frequent errors in recombination and lead to gene duplications and structural chromosome changes that drive fast genome evolution.

1 September 1998 in Theoretical and Applied Genetics
Verified
Journal Article
Closed access
PDF file
JDJan Dvorak
Jan Dvorak
MLMing-Cheng Luo
Ming-Cheng Luo
ZYZ.-L. Yang
Z.-L. Yang
HZH.-B. Zhang
H.-B. Zhang

4 February 2013 in New Phytologist
Verified
Journal Article
Open access
PDF file
JWJirui Wang
Jirui Wang
MLMing-Cheng Luo
Ming-Cheng Luo
ZCZhongxu Chen
Zhongxu Chen
FYFrank M. You
Frank M. You
YWYuming Wei
Yuming Wei
JDJan Dvorak
Jan Dvorak
Summary: Hexaploid wheat (Triticum aestivum, genomes AABBDD) originated by hybridization of tetraploid Triticum turgidum (genomes AABB) with Aegilops tauschii (genomes DD). Genetic relationships between A. tauschii and the wheat D genome are of central importance for the understanding of wheat origin and subsequent evolution. Genetic relationships among 477 A. tauschii and wheat accessions were studied with the A. tauschii 10K Infinium single nucleotide polymorphism (SNP) array. Aegilops tauschii consists of two lineages (designated 1 and 2) having little genetic contact. Each lineage consists of two closely related sublineages. A population within lineage 2 in the southwestern and southern Caspian appears to be the main source of the wheat D genome. Lineage 1 contributed as little as 0.8% of the wheat D genome. Triticum aestivum is subdivided into the western and Far Eastern populations. The Far Eastern population conserved the genetic make‐up of the nascent T. aestivum more than the western population. In wheat, diversity is high in chromosomes 1D and 2D and it correlates in all wheat D‐genome and A. tauschii chromosomes with recombination rates. Gene flow from A. tauschii was an important source of wheat genetic diversity and shaped its distribution along the D‐genome chromosomes.

14 April 2003 in Genome Research
Verified
Journal Article
Open access
PDF file
EAEduard D. Akhunov
Eduard D. Akhunov
AGAndrew W. Goodyear
Andrew W. Goodyear
SGShu Geng
Shu Geng
LQLi-Li Qi
Li-Li Qi
BEBenjamin Echalier
Benjamin Echalier
JDJan Dvorak
Jan Dvorak
Genes detected by wheat expressed sequence tags (ESTs) were mapped into chromosome bins delineated by breakpoints of 159 overlapping deletions. These data were used to assess the organizational and evolutionary aspects of wheat genomes. Relative gene density and recombination rate increased with the relative distance of a bin from the centromere. Single-gene loci present once in the wheat genomes were found predominantly in the proximal, low-recombination regions, while multigene loci tended to be more frequent in distal, high-recombination regions. One-quarter of all gene motifs within wheat genomes were represented by two or more duplicated loci (paralogous sets). For 40 such sets, ancestral loci and loci derived from them by duplication were identified. Loci derived by duplication were most frequently located in distal, high-recombination chromosome regions whereas ancestral loci were most frequently located proximal to them. It is suggested that recombination has played a central role in the evolution of wheat genome structure and that gradients of recombination rates along chromosome arms promote more rapid rates of genome evolution in distal, high-recombination regions than in proximal, low-recombination regions.