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<p class="MsoNormal"><span style="font-size:11.0pt">Dear all,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt">Please join us in Marley 230 on Tuesday, Oct. 1 at 4:00 PM for a seminar presented by Dr. Bonnie Hurwitz from the Department of Biosystem Engineering, University of Arizona. with Dr. Alonso Favela as the host.
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<p class="MsoNormal"><span style="font-size:11.0pt"><a href="https://arizona.zoom.us/j/83044711714?pwd=IQ994mWIPwbsRKMnfF9sERx5sNtv4m.1">Zoom link</a>: https://arizona.zoom.us/j/83044711714 (password: SPLS24).<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt">Refreshments will be provided in the Marley Lobby at 3:30 PM.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:11.0pt">Title: Finding novel viruses in lichen metagenomes
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<p class="MsoNormal"><b><span style="font-size:11.0pt">Abstract</span></b><span style="font-size:11.0pt">: Viruses infect all domains of life and are highly adapted to their host and their environmental niches. Despite the growing body of research on the role
and impact of bacteriophage populations across various ecosystems, identifying viral sequences within large metagenomic datasets remains a significant challenge. The absence of a universal gene marker for viruses means that bioinformatics methods often depend
on sequence homology searches against reference genome databases. Recent advances in bioinformatics have introduced machine learning-based tools designed to identify features indicative of phage origin, aiming to uncover previously unknown viral sequences.
Here, we evaluate different machine-learning methods to investigate novel viral communities associated with lichens. Lichens form a highly diverse group, with more than 20,000 different known species and are able to colonize a vast range of habitats. These
complex composite organisms arise from the mutualistic relationship of an algae or cyanobacteria living among filaments of multiple fungi. In this context, the potential role of viruses is currently unknown and largely unexplored. We apply cutting edge bioinformatic
tools to detect viruses in a collection of lichen metagenomes, to investigate the diversity of the viral population associated with lichens and their role in the complex mutualistic association forming lichens.<o:p></o:p></span></p>
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<p class="MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:10.0pt;font-family:"Courier New";mso-ligatures:none">===============================================================<br>
</span><b><span style="font-size:20.0pt;font-family:"Vladimir Script";mso-ligatures:none">Zhongguo Xiong</span></b><span style="font-size:10.0pt;font-family:"Courier New";mso-ligatures:none"> <br>
School of Plant Sciences BIO5 Institute<br>
BIO5 Email: <span style="color:blue"><a href="mailto:zxiong@arizona.edu"><span style="color:blue">zxiong@arizona.edu</span></a></span>
<br>
Phone: (520)-621-9869<br>
Forbes 303, P.O. box 210036 Fax: (520)-621-7186<br>
University of Arizona <br>
Tucson, AZ 85721-0036 <span style="color:blue"><a href="http://ag.arizona.edu/~zxiong"><span style="color:blue">http://ag.arizona.edu/~zxiong</span></a></span><br>
===============================================================</span><span style="font-size:11.0pt;mso-ligatures:none"><o:p></o:p></span></p>
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