Sharma’s lab studies the biodiversity of spiders Badger Herald

Sharma’s lab in the University of Wisconsin’s Department of Integrative Biology uses evolutionary biology to discover new species and study the molecular basis of biodiversity. This work allows researchers to identify the exact genes that cause significant physical differences between species.

The lab, led by associate professor in the Department of Integrative Biology and principal investigator Prashant Sharma, aims to further understand the evolutionary relationship between scorpions and spiders and other arachnids, and how this compares to other animal groups.

According to Sharma Lab website, The project analyzes the genomes of the samples and builds a phylogenetic tree – a visual representation of how species are related. This complete lineage of arachnids is an important tool for researchers to understand how mutations occur in new species and to help classify future species.

The findings of this study are relevant to more than just spiders – Sharma said that any small discovery in biodiversity is a victory for the entire field of integrative biology.

“[This lab] It focuses on what biodiversity looks like and how it is maintained at the molecular level — the products of the specific genes that cause these different phenotypes and how they affect our broader understanding, Sharma said. “We don’t really know what species are important to prioritize conservation, and we don’t know what is important to conserve, if we don’t know what is there. That is why this research is important.”

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While evolutionary biology is a broad field, many students have very little experience in the field, as was the case for undergraduates Hugh Steiner, who worked in Sharma’s lab for a year and a half. Steiner said he was inspired to pursue research in the lab after Sharma became a professor, sparking his interest in evolutionary biology and molecular genetics. Steiner said he would like to continue this kind of research in the future, which he had never thought of before meeting Sharma.

Inside Sharma’s lab, Steiner applies molecular evolution techniques to identify and classify new types of blind people cave spiders Taken from 44 cave sites throughout the Levant – a large area in the eastern Mediterranean, including Israel, Palestine, and Syria. Although many of these species are physically indistinguishable with the naked eye, Steiner used molecular data to demonstrate that the species are in fact new and separate.

After his work on the species discovery project, Steiner said he shifted his focus from the computational side more than research to molecular experiments.

“I decided to try my hand at evolutionary research rather than just taxonomy,” Steiner said. “There is a completely different set of research techniques that we use in the lab that I have hardly discovered until now.”

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Evolutionary evolution, another facet of Sharma Laboratories Researchuses genetic data to identify the exact genes that cause differences between species, and work backwards to identify new targets for research, according to Biomed Center. Once the most promising genes are identified, researchers categorize function by removing the gene’s product and observe changes in appearance and behavior. Researchers can simulate evolution by identifying specific genes in spiders that cause clear differences between closely related species.

Sharma’s lab has also started genetic analysis of scorpions using machine learning to predict what kind of scorpion it is The species’ toxins may be medically relevant. Sharma said lab members then analyze these gene products and test toxins for antibacterial or even tumor-reducing properties.

According to Sharma, the new antibiotics that can be discovered using this research are of particular interest because bacteria adapt to frequently used antibiotics, leading to antibacterial resistance. Any new antibiotic discovered will give doctors new tools to fight infection.

“We know that some of these toxins have healing properties, but it’s hard to tell which ones,” Sharma said. “[Artificial intelligence] It allows us to connect [genetic] Sequencing of known toxins with available functional data to predict peptides present in promising arachnid genomes”.

Evolutionary biology involves analyzing huge data sets, with each species’ genome containing billions of base pairs, according to Sharma. Even a small sample size is too large for a human to analyze it manually. Combining current understanding of genetics and molecular physiology with the unparalleled processing power of artificial intelligence has completely changed the field of evolutionary biology.

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Sharma said that machine learning has facilitated much of his recent research. In turn, each biological discovery gives future programs additional data to use, further honing their research techniques.

“We don’t know what’s important if we don’t know what’s out there,” Sharma said. “With these computational tools, we are answering questions that would not even have been asked 20 years ago — we are in the midst of a revolution not only in [biological research] But also in how these questions are asked.”

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