若手研究者インターナショナル・トレーニング・プログラム(ITP)
バイオインフォマティクスとシステムズバイオロジーの国際連携教育研究プログラム 報告書

Name：Zhao JinTitle ： Using simulating data to evaluate the annotation of short metagenomics sequences
fragments
Institute: Bioinformatics Center, Institute for Chemical Research, Kyoto University
Partner institute: Bioinformatics Program, Boston University
Duration: January 16, 2012 ~ April 8, 2012
Report:1. General Report:
With the support of ITP program, I received a chance to visit Boston University as an exchange
student, studying in Dr. Daniel Segre’s lab for about 3 months.
Segre lab belongs to the Bioinformatics Program,which locates in the 9th floor of Life Science andEngineering Building of BU. Led by Associate
Professor Daniel Segre, there’re two postdoctoral
fellows and over 10 PhD students working in thelab, some of whom are double advised with otherprofessors. Therefore, besides the basic weekly
group meeting on every Friday, we can also enjoy
the lively discussions in those joint meetings withdifferent labs. I was really surprised by the active
communications and open-minded ideas of all theparticipants every time. They would not only focus
on the researches, but also other related studies,interesting references, even something that seems
to have nothing to do with the current topics. It
confused me at first when they were having aheated discussion on something that totally
unconcerned which may last for an hour or more. However, as time went by, I discovered that it’s
just the discussion that provide great opportunities to encourage everyone to express opinions nomatter right or wrong, which make the lab always have enough communications and stay in arelaxed mood. This experience gave me an impressive lesson that science should be strict but also
could be flexible and enjoyable.
Besides Boston University, there’re many other top universities in Boston, such as Harvard
University and Massachusetts Institute of Technology (MIT). These universities communicate
with each other frequently, so it’s very convenient for the college students to visit different campus
in order to attend open seminars or listen to speeches given by famous scholars. For example,

若手研究者インターナショナル・トレーニング・プログラム(ITP)
バイオインフォマティクスとシステムズバイオロジーの国際連携教育研究プログラム 報告書

there’s an informal scientific seminar called Bauer Forum talks held in Harvard University every
Wednesday, which was designed to foster communication and collaboration among people with anactive interest in genomics and systems biology. In a word, various speeches on advanced
researches in such open seminars expanded my horizon greatly, which was also precious
experience I gained during ITP program.
2. Research Project:
There are multiple research interests in Segre lab which mainly focus on the dynamics andevolution of metabolism in individual microbes and in microbial ecosystems. At first, I wassuggested to work on the functional comparisons between metagenomes across bacteria, using 16SrRNA from the metagenomic datasets. However, we discovered that this project would take several
months to process due to the large size of data and complicated methods, so I have to change myproject after 2 weeks’ study.
The second project was still concerned with metagenomics whose annotation became a very
important part in current research. BLAST finds regions of local similarity between sequences andit can be used to infer functional and evolutionary relationships between sequences as well as help
identify members of gene families. However, BLAST is basically designed for long sequencescomparing, how well it works on short metagenomic sequences is still not clear. In this study, wetried to use simulating data to verify the effect of BLAST on short fragments.
We collected total 728,225 protein sequences belong to 7,784 clusters in the PRK category ofCLUSTERS from NCBI FTP as our original database. Next, 61 sequences from different clustersof various sizes were chosen as samples. Every sequence was cut into fragments of 7 kinds oflengths, which were 20mer, 30mer, 40mer, 50mer, 60mer, 70mer, 80mer. We did all the cutting on
every sequence from beginning to the end, in order to ensure that all the possible fragments withcertain length on this sequence would be collected in the study. Therefore, there’re a great many
fragments for each sequences of each length.
Secondly, we blasted all the fragments against our database, basically using default e-value 10.
Then several methods were developed to filter the blast results.
1) The blast hits with "Identities" > 90% were picked out as group1 data.
2) The blast hits with e-value < 10-5 were picked out as group2 data.
3) The blast hits with alignment_length > 0.8 were picked out as group3 data.
alignment_length = abs(query.end -query.start) / length_of_query_sequence.
Thirdly, the three groups data were used for further analysis called “Hit-back-value” which was
to find out how many blast hits belong to the original cluster, the calculation should be:
Hit-back-value = (Number of blast hits belong to original cluster) / (Total blast hits number)
For example, we have 100 blast hits, and 50 of them could be found in the original cluster, thenthe "Hit-back" percent should be 50/100=50%.
For every sample sequence, it had lots of fragments in different lengths with different results;
we calculated the average percentage for every certain length of sample and put the results on若手研究者インターナショナル・トレーニング・プログラム(ITP)
バイオインフォマティクスとシステムズバイオロジーの国際連携教育研究プログラム 報告書

plots, then every single line on the chart stands for one
sequence.
As the results plots showed(Figure 1), we could see,for both group1 and group3 data, the "Hit-back" plots
are quite similar, which suggested that fragments
longer than 50mer would give a perfect result inBLAST search, but the perfect percentage would onlyappear when fragments were longer than 80mer ingroup2.
During normal BLAST search, we usually filter theresults by reducing e-values; however, our study
indicated that the same method may not work wellwhen the data are fragments that are shorter than80mer. In this case, it’s better to develop othermethods to extract blast hits such as identities oralignment_length used above.
Because of the time limit, we didn’t finish testing all
the clusters, and only chose one sample sequence tostand for one cluster, which were quite unilateral. We
are going to test more sequences and clusters in thefuture in order to complete the results. What’s more,
the plots shown left gave the average values for whole
sequences, however, fragments picked from different location would show quite different results inBLAST, it’s also necessary and interesting to study typical fragments.
The result has been submitted to ISME14 as co-authorship.
Acknowledgement:
I would like to thank Professor Minoru Kanehisa, Professor Hiroshi Mamitsuka, and AssociateProfessor Susumu Goto for providing me such a valuable study opportunity. I would also like toexpress my gratitude to Dr. Daniel Segre, administrator Caroline Lyman, and all the Segre lab
members for their kindness and supports during my stay in BU.

若手研究者インターナショナル・トレーニング・プログラム(ITP)
バイオインフォマティクスとシステムズバイオロジーの国際連携教育研究プログラム 報告書

Left photo: Dr. Daniel Segre(left), Zhao Jin.
Right photo: left side of the table from front, Dr. Daniel Segre, Christopher Jacobs, Zhao Jin,
Dr. Zhuoyun Zhuang, Rama Krishna Simhadri, Dr.Varun Mazumdar;
Right side of the table from front, Amrita Kar, Brian Granger, Sara Baldwin, Lina
Faller, Arion Stettner.

Left photo: Statue of the Three Lies in Harvard University.
Right photo: MIT Building 10 and the Great Dome.