My name is Avinash Karn, I go by Avi, I am a plant molecular breeder and computational biologist; and an amateur astronomer, painter, online blogger, photographer and vivid cook. :)
I obtained my secondary and higher secondary education in my hometown Birgunj, Nepal. Next, I came to the United States to earn my Bachelor of Science degree in Agricultural Sciences, specializing in plant genetics at Truman State University, and finally, earned my PhD at the University of Missouri Columbia specializing in plant breeding, genetics and genomics.
I specialize in plant breeding, statistical genetics and computational biology. Currently, I am a post-doctoral computational biologist at Cornell University in Geneva, New York. I intend to use my education and training in pursuing a career in a research organization that is involved to improve human nutrition, health and environment for both developed and developing communities.
I was first introduced in the field of plant breeding and genetics in my freshmen year in college, and was involved in plowing field with a tractor, planting seeds with hand, pollinating and collecting agronomic data from field trials, harvesting and statistically analyzing data. While still pursuing my undergraduate career, I worked with diverse panel of maize germplasms, and developed gene specific markers to aid in the development of high amylose maize lines. Carrying my passion in plant genetics and big data analysis to my graduate school, I was involved in the development of two novel populations: near isogenic (NIL) and synthetic lines derived from domesticated corn and its wild relative, teosinte to elucidate the teosinte genetic diversity for agronomic and domestication traits in maize. While still in graduate school, I developed statistical models to non-destructively estimate seed composition traits (total starch, protein, oil and individual fatty acids) traits in intact maize kernels and soybean seeds using near infrared reflectance spectroscopy (NIRS) and nuclear magnetic resonance (NMR) instruments. The key findings from my PhD dissertation research were that the teosinte bears novel alleles for various plant and kernel architecture traits, which can be utilized for the improvement modern maize germplasm, and in addition can provide unique source of variations to breeders and geneticist in further QTL and molecular studies, which will accelerate in the development of future elite maize germplasm. Currently, as a computation biologist in VitisGen2 project at Cornell, I am involved in the analyzing large-scale genotyping data from various platforms such as Simple Sequence Repeats (SSR), Genotyping-by-Sequencing (GBS), Amplicon Sequencing (AmpSeq), Whole genome sequencing (WGS) for variant and haplotype calling, genome alignment, assembly and genomic selection and prediction. I have also co-lead in the development of a rhAmpSeq (RNase H2 enzyme-dependent amplicon sequencing) haplotype strategy targeting the collinear core genome to improve marker transferability across a diverse genus. Similarly, I work with nation-wide grape breeders to apply AmpSeq/rhAmpSeq marker data for accelerated marker-assisted breeding. In addition, I build genetic maps (in Lep-Map3) of inter- and intraspecific Vitis populations; performed quality control (QC) analysis, interval mapping (in R/QTL) and genome-wide association (GLM, MLM, FarmCPU); and big data visualization in R software using packages such as ggPlot and CIRCOS (written in PERL). In addition, I have been also involved in managing grapevine breeding database www.VitisBase.org in collaboration with Boyce Thompson Institute and Breeding Insight project (USDA); as well as led setting up trials and high-throughput phenotype data collection on Field Book® android application. So far I have supervised three undergraduate research summer scholars from different parts of the country as well as assisted graduate students (both national and international) in genetic and statistical analyses. In my spare time, I do write tutorials on my blog https://AviKarn.com
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