This is the words before all else are thanks given address. I will call in the elements to join us in these very important days. I call upon all of you, the people, to sit with us, to walk with us, to breathe with us as these days are so important. And then I acknowledge our Yukit'n'estan Huja, our Mother Earth, the very element upon which we sustain ourselves and nurture ourselves and see the beauty of all that she has to give and she is our happiness. And then I go to the waters, how fortunate it is to live in a world that still has fresh, clean water to drink and to soothe us. And then I also acknowledge all the fish life within the waters, how lucky we are that they still exist and they're our food and our medicine. I call them all in to be with us.  And then I go to the place of the four legged, the animals, the bug life, how fortunate we are that they still exist.  So I call them all in to join us in this very important day of the year. Then I go to the tree life, to the maple tree, how lucky we are to be in the season of the maple tree. Come join us trees, be with us today. Let's travel these days together and let's call forward the peace. And then I go to the on high, the eagle. As we can see, we have brought our feathers and today is the meeting of the eagle and the condor as we come from many lands that has birds. And we convene here for a great day, two days, and we acknowledge how important it is that they be with us, travel with us. Then I go to the place, and then I go to the place of the grandfather, the winds. They come from the east, they come from the west, they come from the north, and they come from the south. We acknowledge them that they still bring us breath and how powerful they are and how humble we need to be before them. Then I acknowledge our grandfather, the thunders, the thunderbeans. I call them in, be with us today. Let us bring forward the great peace once again as we knew it before.  Be with us. Yeti sa to gua, la diwea las. Togit nitu ha kni guat ni gula. Then I go to that place as the creator had made that there be two orbs in the sky. They just had a family reunion on Monday and how lucky we are to ride the solar maxima and the energy then, the power of that that we bring forward. It is a powerful time. We are living in powerful times. So I acknowledge our brother, the son, Chidawahchia Gyokinika Galakwa and our grandmother, Moon, for all that she gives us and that she lights the night and she pulls forward from the earth all our plant life and she controls the migration of our animals and that she brings forward the babies, our babies, and that the women cycle with her. Togit nitu ha kni guat ni gula. Then I look to the stars, how lucky we are to still see beautiful skies in that they twinkle at night and they're still by which we navigate ourselves so we don't get lost. I call in those stars to be with us so that we can be so powerful as we move forward with the days in that we leave a path of goodness and kindness and love and peace for our children to follow. Let them navigate us to that good thinking. Togit nitu ha kni guat ni gula. Then I go to that place of our four sacred beings who were positioned here on the earth by our crater to watch over us and our children, how lucky we are that they still exist there and look upon us and take pity upon us. Togit nitu ha kni guat ni gula. Then I acknowledge our sacred sky woman, Ujit Jizo, for it is her who fell from the sky world and created the earth and gave birth to a daughter who gave birth to the twin brothers that created all that is here on earth, how lucky we are that we still know her name, we know her story, and she re-enacts and relives herself in the fertility of our young women, how lucky we are that we have that continuity to our first geneticist, our sacred sky woman, Togit nitu ha kni guat ni gula. Then I go to that place, there they call the edge of the sky, Ujit Ujit, yes there her grandson lives and we call him our creator. He is the architect of all that we know that is here on earth and we turn to him with good mind, with powerful thoughts and gratitude and we say nya weha, nya weha for all that you have given us and we acknowledge that you still love your people here and that we acknowledge and so when the sun and moon reunited on Monday, we burned our fires and we sent up one column of smoke and as you entered our territory and we're on the horizon, you knew that we didn't forget who we are and we spoke in our language and we sang our songs and we put up our great feather dance and we acknowledge this huge family reunion and we say to you, our great orbs in the sky and our creator, we're going to do better, we're going to do better. And to acknowledge that and to cap it off, I wrap our minds all together as one, that's Scott Nygulla and I say to you, these are powerful days and we're all born to be in this moment and we're all born with a great purpose, bigger, small, we all have something to contribute. So I acknowledge the company we are in and I take it seriously and from the words of Mama Bear, I've done my best to bring this, words before all else, this acknowledgement, this address of creation and they sit here with us, they sit here with us and they'll walk with us through these days how powerful we are and I acknowledge all of you and I bring our young women and our elders with us to open up this convening of powerful people and of indigenous people and it is that place, it is that place that we must acknowledge and we have to undo the harm that has been done by the big colonial machine and we have to return to that place of originality, of indigeneity, we have to indigeneize our process. It took it in your talk, Nygulla Nygulla. I'm going to share with you a song called Gaeli Niu Nguedige and we acknowledge the four sacred beings from all directions and in this song we're asking that they look over you and their family while you're away from home and while you're on your journey and so I just wanted to, like many others, share some medicine with you today so that we can make better decisions and I just wanted to maybe remind myself and everybody in the room to make sure you represent the love that you come from and that's family and community. That's what I try to represent because I had people that have shown me how to love. We were established by the United States Congress in 1984. The elected representatives of the American people decided it was high time to have a public institution that was solely dedicated to helping prevent and mitigate and resolve violent conflict abroad. We were established by the United States Congress in 1984. The elected representatives of the American people decided it was high time to have a public institution that was solely dedicated to helping prevent and mitigate and resolve violent conflict abroad. Republican funded. We don't take money from the private sector. We don't take it from outside sources. We take it because the American people have an enduring long lasting commitment to peace. Those of us who work at the institute feel deeply the mandate that Congress entrusted to us and all of us who work here every day do our very best to live up to that mandate. It's an honor, really truly a great honor to welcome everyone for the first summit of indigenous peace builders in America's national capital. Leaders from nearly every social, cultural region of the world are with us today from Africa, the Arctic, Asia, Latin America, Eastern Europe, the Russian Federation, Central Asia, Transcaucasia, North America and the Pacific. Please allow us to extend a most special welcome to our friends for whom this is their first visit to the United States. We hope you come back and that you come often. I have the privilege of welcoming to our summit the United States Secretary of the Interior, Madam Deborah Holland. Secretary Holland is an American champion and heroine. The Secretary is an enrolled member of the Pueblo of Laguna in New Mexico where I live. The Secretary made history when she became the first Native American to serve as a Secretary Cabinet in the United States government. She was elected as the first Native American woman to serve in Congress, first Native American woman to lead a state political party in the country. Secretary Holland has broken barriers and opened doors of opportunity for future generations. She is a mentor and an extraordinary leader. We are very pleased also to extend a special welcome to Michael Arona, a special advisor for global strategy and international indigenous issues. Very special welcome to Chief Wilton Littlechild, Vice President of the Indigenous Parliament of the Americas and North American Representative to the UN Permanent Forum on Indigenous Issues. Welcome to USIP. I would like to take a personal moment and acknowledge the leader within the institute who has brought us all together. I first met Bina Negum many years ago in Manipur, her home region in India. I knew then that she was a visionary, committed to peace with every part of her soul and mind. It has been her efforts and her leadership that has made this summit possible. Bina. At USIP we know how hard it is to make peace. We also know that indigenous peace builders are the most determined and some of the most successful in the entire world, drawing on traditions, culture, religious practices to resist violence and to build peace in the face of all odds. We celebrate and re-venerate all of you and welcome the opportunity during the next days to deepen our knowledge of each other, to share our experiences, to develop recommendations to advance the inclusion of indigenous people in peace processes and most of all to work together to build a global network of indigenous peace builders who can coordinate across borders to prevent and mitigate and resolve violent conflict abroad. Madam Secretary. Good morning everyone. So happy to see you all. Thank you for having me. Represent the love that you come from that is profound and incredibly important. If we don't take anything else away from today that statement is one for the ages. Thank you for saying that and I'm happy to be in your presence. My name is Deb Haaland. I'm from the turquoise clan from Laguna Pueblo and I'm honored to serve as the United States Secretary of the Interior. Thank you so much for that very warm welcome and for your dedication to building a more just world for everyone. I'm grateful to join a group like this because it means I'm surrounded by folks who care about the state of our world and the neighbors they share it with just as much as I do. In what is now called the United States, Indian tribes have championed peaceful conflict resolution and democratic governance for thousands of years. I think we can all agree this model is worth replicating. The U.S. government's own constitution is modeled after that of the Haudenosaunee Confederacy who built peaceful decision making and respect for one another into their everyday lives through their own constitution the great law of peace. We know that if we are to build a world that truly serves everyone we must prioritize indigenous peoples and their values into our decision making. This is something the Biden-Harris administration has taken to heart. I'm proud that as we implement President Biden's investing in America agenda the Department of the Interior is ensuring tribes have a direct say in how these resources are spent. This includes the work we have undertaken to rethink what tribal cost stewardship shared decision making over federal lands and waters can truly mean and accomplish and we're putting our words into action. Since the start of our administration we have signed over 200 cost stewardship agreements with tribes to ensure their role in managing their ancestral homelands. Our prioritization of indigenous knowledge and its scientific integrity along cost stewardship also extends to our management of vast landscapes that desperately need our help as extreme drought, wildland fires, and other climate-fueled threats jeopardize entire ways of life. With $2 billion from President Biden's investing in America agenda our department is using a restoration and resilience framework to restore lands and waters that hold precious cultural resources from the powerful bison that support the vital prairie grassland ecosystem to Alaska streams and rivers that are home to the irreplaceable salmon runs. These changes are substantive. They're resilient to whatever the future might hold because they cement the role of tribal influence and how it plays in to how our government operates. Crucial to this legacy is advancing efforts that heal our people from generations of neglect and harm. It's a commitment I made when I first stepped into this role to rebuild what assimilation policies attempted to break. When I announced the federal Indian boarding school initiative I didn't realize that it would become a core legacy issue for our department. Our goal was noble and mighty to unravel the intergenerational trauma that has plagued our communities since the start of this horrific era. An era that saw indigenous children including my grandparents torn from their families and stripped of their languages, their cultures and their ways of life. From my travels to Canada, to Australia, to Paraguay I have heard time and again the recurring challenges that indigenous communities must overcome. From violence against women and girls, to land dispossession, to shared stories of brutal assimilation policies, to even the hard fight for a basic education. These painful stories ring true to me. One simple fact, their struggles are ours. These shared hardships are why we must recognize on a global scale that indigenous peoples deserve to be on their land and that we shouldn't have to fight for our own equality. And they are why governments worldwide must center indigenous principles from peace building to conservation to tackling the climate crisis. If we are to build the world we know is possible. Our work isn't done yet but together we are moving mountains. And it's the partners in this room that are making the change we need to happen on the scale that it demands. Thank you all so much for being here. Thank you for bringing everything that you have to this table. It's incredibly important. Thank you for your heart and your passion. I'm grateful to be your partner on the good work now and tomorrow. Thank you all so much. Thank you. Good morning. Can we have another round of applause for Secretary Haaland please? Good morning everyone. I'm Michael LaRona and I am deeply honored to participate in this historic and timely summit. And I want to thank the U.S. Institute for Peace for bringing us together to discuss this important topic of global indigenous peace building. Let me start by thanking Bear Clan Mother Louise McDonnell-Hearn for the wonderful and beautiful prayer this morning. Thank you. Thank you Maya and Pablo for the wonderful prelude. Thank you both. And I also want to thank U.S. Secretary of Interior Deb Haaland for the groundbreaking work that she continues to do in support of indigenous peoples not only in this country but around the world. Now I work here in Washington DC but I am originally from the Southwestern United States born in Arizona and raised in New Mexico to parents of Apache and Yaqui ancestry. And I'd like to welcome everyone here this morning in my father's language of Apache. Thank you. Now thank you. My global mandate at the U.S. Department of State as senior advisor for international indigenous issues is to partner with government officials and indigenous peoples from around the world to ensure that U.S. foreign policy protects and advances the rights of indigenous peoples. Not let me say this again underscore this not because we have solved these challenges here in the United States but rather because we recognize that these are global challenges that need coordinated and sustained global solutions that require again that require the leadership of indigenous peoples from around the world. Now I believe it is important to underscore that advancing the rights of all people, advancing the rights of indigenous peoples ensures more stable and inclusive societies, more prosperous economies and more peaceful nations because it does. Besides being the morally right thing to do it is in our global security interests to address inequities faced by indigenous peoples. Local and regional conflicts around the world demonstrate how indigenous communities are subject to compounding and disproportionate harm. Societies that successfully address deep rooted disparities tend to be more peaceful, more prosperous and more stable and that is inherently good for all of us as a global community. In my work, my goal is to listen, to listen, to consult, and to collaborate with indigenous peoples. These communities have agency they have always had agency and no better than anyone else the challenges they face and what is needed to overcome them. Historically, as we all know on a global level indigenous peoples for too long have been informed or told rather than leading discussions on decisions that impact them. However, society can no longer categorize indigenous peoples as historical figures whose time has passed but instead now must look to indigenous peoples as a significant element in the construction of a unified world and the establishment of a global civilization. There are over 400 million indigenous peoples across our world. Many are leaders overseeing a wide and diverse range of critical issues, a source of traditional indigenous knowledge and strategies on sustainability. This includes climate change, food security, equitable governance, gender equality, peace building, and so so much more. These are all issues that are important to our very existence as a global society. Indigenous peoples are also uniquely positioned to develop and implement culturally appropriate sustainable solutions and must be at the forefront in the creation of local, regional, national, and global policies and strategies. On the environment, the land inhabited by indigenous peoples constitutes nearly 30% of the global land surface. More reason for indigenous peoples to lead the discussion on global climate change. Collectively, we must help foster a more inclusive society in which indigenous peoples are free to reach our full potential to share indigenous knowledge and unique perspectives and how to confront issues facing our planet. It is this inclusive and consultative approach that will help create a better, safer, and more peaceful world for the benefit of us all. Now, I believe the complete transformation of society necessitates the ability to harness the power of all people. Not allowing or preventing diverse perspectives by diverse participants hinders humanity's ability to achieve our collective destiny. Preventing a segment of humanity. Preventing a segment of humanity. Think about this. Preventing indigenous peoples to express or achieve our full capability is detrimental to the rest of our global community. This complete transformation of society starts with acknowledging our own tragic history. In the United States, this means acknowledging the forced removal of Native peoples from ancestral lands, the legacy of boarding schools, and other tragic policies. And again, I thank Secretary Holland and her staff for the important work they continue to do on these important issues. In conclusion, let me underscore in a world where conflict and justice and social inequality continue to impede the promotion of sustainable development and lasting peace. It is the traditional knowledge systems of indigenous peoples that has never stopped to contribute to peaceful and inclusive societies, which merits greater global attention and support. Indigenous peoples have always had a special role in making our world a more secure and more peaceful place. This is nothing new to us. In support of global food security, we have served as providers of over half of the world's foods, such as corn, potatoes, tomato, squash, beans, and so forth. Now, so shall we provide in this day the spiritual food and guidance to create lasting peace. Native peoples have also provided true healing by giving to the world a pharmacopia of medicine that included quinine, guayacal, petroleum, jelly, arnica, and so many other medicinal cures. And so shall we provide in this day the spiritual healings to heal the ills that have plagued our world for too long. This is our responsibility. This is our destiny. It is our time. We have endured to fulfill it, and so it shall be done. Thank you. Yeah, yeah. Now, if you would please help me welcome Chief Wilton Little Child to the stage. I just bring you greetings in my Cree language to acknowledge all of you present on such an important, important day today and tomorrow. My name is Maikant Mohtio in Cree. I'm also known as Usaugi Heu as a chief. And my residential school name was number 65. My borrowed name is Wee Willie Little Child. So I wanted to mention those by way of honoring the international decade for Indigenous languages. As you know, we lose an Indigenous language every two weeks, similar in the world than Indigenous language dies. So I want to honor that by speaking to you in Cree. Thank you very much to our hosts for, as you heard, through convenience on such an important and timely summit. Timely given the violent conflicts, the wars that are ongoing, we are witnessing it every day, the associated killings. But as we did before, we want to now focus on peace, peace building and Indigenous peace building. You have to forgive me for my hip is not hipping. I broke it recently. So I'm going to be a little shaky here due to a lot of sports injuries. So I'm trying to make peace with my body. I want to also applaud her honor, the Secretary of the Interior, Deborah Hall, and for all the work she continues to do on promoting wellness and healing and peace building. History has recorded other Indigenous peoples' contributions to peace. In 1996, after two meetings in 1993 and 1994, we gathered in Mexico, I believe it was in Chiapas, to form the International Indigenous Initiative for Peace. So this is something that's been going on for a while. Indeed, we declared a decade at that time, which was subsequently made into a United Nations decade for Indigenous peoples. I recall an elder, Chief Dan George's writings in a book, My Heart Sores. I sincerely apologize. I should have got the exact wording when he stated in my paraphrase. As a chief, my power to make war is gone. I can now only fight my peoples' wars with words. And it seems to me that's where we are today. As I reflect back on different and traditional roles of chieftainship, yes, we had war chiefs, we had ceremonial chiefs, we had political chiefs, Sundance chiefs, peace chiefs. So you see, here we are today again to celebrate life, perhaps through an Indigenous lens of justice, healing, reconciliation, and what I've come to call reconciliation. You will hear next day today and tomorrow about traditional systems, practices, laws, natural laws. During the United Nations International Year for Peace, and Elsa will remember this, the states came together and asked themselves a question, should we have a theme for the International Year of Peace? And they said, yes, we should. Perhaps a prayer would be appropriate. And I wanted to thank Mama Bear. I said in my language, I'm from Mesquiteast, the Bear Hills at home, so we're related. But during that discussion, over 380 prayers were sent to the UN to pick one that might be appropriate for International Year of Peace. And you will remember some of you that were there, like Kenneth, I think, was there from the outset in Chiapas. The prayer that was chosen was the International Peace Prayer of St. Francis. And those who practice Catholicism will recall it begins with, Lord, make me an instrument of your peace. Where there's hatred, let me so love. Where there's injury, pardon. Where there's doubt, faith. Where there's darkness, light. Where there's sadness, joy. And where there's despair, hope. And it goes on from there. O great Spirit, let me not so much seek to be consoled as to console. To be loved as to love. To be understood as to understand. And it goes on from there. So that was the prayer that was picked. And we ask ourselves, what does peace look like? Well, you saw it unravel in front of us already this morning with the women from the youth to the spiritual leader to the elder. Show us what peace looks like. We heard it in a song. And a young athlete, I believe is an athlete, basketball player, I think, who came up and said, I'll come back to that.  You might see face in a wrinkled, yet laughing face of a grandma or grandpa. You might see a happy face of parents as they witness their child succeed, perhaps in education, sports or leadership. You see there's a power of sport, and I can't help but reflect on that.  You saw it this morning already. For example, the power of sporting the Olympics, we see every Olympic, there's a truce, a peace truce, where states that are participating in the games put down their arms, weapons of war for the duration of the Olympic truce. But the duration of the games, we need to expand that extended beyond what is normally just a two-week period. It's within us that we can extend that. For example, we saw it this morning in times of ceremony, family union and family reunion. In the world of indigenous games, when we pause and come together at the end of the games, thank you. I should have asked for this before. My dad used to say, will you think you're tough? Wait till those injuries come and pile up on you. So during the world of indigenous games, we pause at the end of the games to have a peace dance, a dance of victory among indigenous people celebrating life. But to go back to indigenous people's peace building, you know that we had treaties among ourselves long before newcomers came to our territories. As you heard, Deb Halland, the Honorable Secretary, say this morning, we have in our Cree language a name of a neighbor town. For example, I sometimes say it's the most mispronounced city in Wataskwan, Canada. It's actually a Cree word, a daily reminder for us about what ought to be our goal. We tusky win in Cree means having good relations. But it hasn't been easy as you heard and as many of you have lived. We have a treaty, for example, of economic alliance with a brother Cree tribe, a treaty with our eastern brothers, the James Bay Cree, to work together in unity. And we saw that play out in the international negotiations on two indigenous declarations, on the rates of indigenous peoples. In 1975, the national chiefs in Canada got together and had a declaration. They made a declaration as chiefs about our right to self-determination. And just before Christmas, we had a chief's assembly in Canada. And I proposed a resolution that there be an immediate ceasefire in the Israeli Gaza conflict. Over 400 chiefs supported at four abstentions, no opposition. So you see our peace building has always been with us. It's a common and lasting activity with each other, peace building. We have those, yes, with our brother nations and those with newcomers. For example, the J Treaty, the migratory birds convention for treaty. Later tomorrow we'll go more into some of the traditional practices reflected in new international laws. We will hear about pre-confederation treaties, the numbered treaties, post-confederation or sometimes called modern treaties. Many of those, if not all, are about peace and justice, peace and healing, peace and reconciliation. So peace building, as you heard her honor, the Secretary of Interior say this morning, has always been in our history. And I dare say, as I think she kind of hinted, we are good at it. We're good at peace building. So our message today, I heard once that a friend of mine said to me, Willie, I've been working on this for 10 years. And I said, way to go, Raymond, way to go. And he said, no, no. Today I finally realized it begins with me. It begins with me. And to that I would add, as we sit here for today and tomorrow, an observation that a Supreme Court of Canada made, and again I paraphrase, we're going to be here for a long time together. So we might as well learn how to get along, to which I would simply add in peaceful coexistence. I will not need the chair. Thank you, Chief Little Child, for your vision, for your courage, and for being with us here today.  And we will carry on the work that you started for a long, long time. Greetings, everyone. Greetings to everyone in my Indigenous language. I pay my obeisance to each and every one of you who are gathered here. On behalf of USIP and our partners, we thank you for all your support, which has made this summit possible today. A big hand for everyone, all who have co-created this event together from day one to each one of you. I pay my respects as we gather here in the ancestral lands of the Nagoj Tank and the Piscatawe people. We pay respects to our elders, past and present, and to our young ones, and those who are waiting to be born. We take a moment to consider how long we have come to be where we are today. We are mindful that we are in the land where the mighty Potomac River flows, and continues to nurture, nourish, and strengthen many who have passed its banks. We have come here today from the many lands where our own mighty river continues to flow. We are here today, many mighty rivers joined together in this particular room. We recognize that in the world of today, we need meaningful peace building that works for everyone. 476 million Indigenous people in over 90 countries and territories live in areas, border zones, which are on the front lines of violent conflict, insurgency, organized crime with devastating humanitarian impact. We remember today all the lives that we have lost, innocent lives in the past years, in the past one year, in our homes where we all come from, including myself. We remember the wisdom which will get us through this all that will pave the way for healing peace people and one planet that we all co-habit together, not wars but let peace be the pathway. We acknowledge that Indigenous people have their own traditions, culture, and religious practices that will help resolve violence and build local peace. While often highly successful Indigenous people's efforts are underappreciated by the peace building community or ignored entirely in formal peace processes. Last year at USIP, here in this very room, we started mapping out some of the root causes of the violent conflicts that are currently happening and we try to analyze what is happening in the world today. And this is what we found. Number one, 80% of the world's conflicts happen in biodiversity areas where Indigenous people live. 80%. Number one, so if you're coming from these zones, no, you're not alone. And together we will find resolve solutions. Second, in order to mitigate violent conflicts, it is imperative that we understand what is happening in these territories, border areas where news don't reach, where our policymakers are hardly present to know what is happening and work with the wisdom of Indigenous people who are living in these territories to be able to resolve and mitigate violent conflicts. Third, that Indigenous people have lived for centuries as many of our esteemed speakers have spoken before. Yet their resilience that they have showed in the face of many of this is noteworthy, extraordinary. And this is the wisdom that will take us through in the hundred years to come from now. Fourth, studies have also found that Indigenous women, Indigenous women here in this room, and those who are listening online, we know that Indigenous women across cultures and nations have evolved extraordinary forms of nonviolent protestant mechanisms that have confronted decades of violence, weaponization and structural wars that have marked their lives for a decade. We must put Indigenous women at the forefront of national, global and multilateral efforts in the field of peace building. Fifth, we realize that to heal people for peace and our planet, we will need to look into traditional mechanisms of conflict resolution and mitigation processes. We just started that in 20 and this is one of the main reasons we are gathered here today. For us at the Institute and our partners in the field, we just therefore came up with this idea of a global summit as I mentioned. We know that Indigenous people have from time immemorial evolved innovative ways of peace building. We heard Secretary Harland speaking about the great law of peace of the Haudenosaunee people and you are here guiding us as we do this work. So thank you Mama Bear and thank you, all of you have come all the way to be here with us. We are truly honored and blessed by your presence. We recognize the extraordinary all roles as we mentioned of Indigenous women are mothers, grandmothers and our ancestors who have forged innovative peace building methods against amidst all odds. As we mentioned that Indigenous people have been trying to engage with the United Nations since the 1970s to resolve, mitigate and prevent violent conflicts. Noting that it was for the first time that special attention was paid to Indigenous people by the peace area of the UN was in connection with the peace process in Guatemala and we have colleagues joining us from Guatemala here with us today and those joining online who have been a part of this. This was here in the year 1995. In UN General Assembly agenda, item number 42A slash 49 slash 882 dated 10th April 1995. Cognizant after this, the Manila Declaration done by Indigenous leaders of the Philippines. In 2000 Indigenous people called for the creation of new systems and institutions of peacemaking that are sourced in Indigenous values and that coexist with existing bodies such as the International Court of Justice and similar regional bodies to ensure the inclusion of independent Indigenous people's tribunals, commissions of inquiry that are recognized as legitimate organs in any poor process of conflict resolution. And then following this in 2007, the UN Declaration on the Rights of Indigenous People and Professor Elsa is here with us today who have been a part of that process that it did contain several articles that are relevant to preventing conflict. 17 years since adoption of undripped conflict in Indigenous lands and territories have not lessened yet it has increased more than ever. We are now in the search to find new solutions and pathways. That is why we are meeting here today and tomorrow. So we are also aware that the Human Rights Council resolution 3325 during the 14th session of 2021, the expert mechanism confirmed its decision to prepare a report on what is happening in the violence in Indigenous lands to address the issue. So we'll be following up very, very acutely on this. To end, what is the way forward? As Michael Orona has mentioned, we're over 476 million Indigenous people living in 90 countries and territories, speaking a majority of more than 7,000 languages representing 5,000 different cultures, faith and way of life. A section of this 470 million are here with us today, each one of you who have taken time travesting countries and oceans to be here with today. You have all come in peace. You have come to us with the wisdom of your people and your ancestors and your young in the hope of a future that our future generations can help in healing people, peace and planet. 107 wars are happening in the world today, displacing 117 million all over the world. Peace-making efforts are negotiated, but Indigenous people are hardly represented. Even in the UN Sustainable Development Goals, it is important that any peace-building methods and conflicts must resolve and include Indigenous people. This is why we are meeting, bringing over 50 extraordinary Indigenous leaders, peace-builders, elders, women and youth from seven social, cultural, Indigenous regions of the world. We welcome each one of you to our summit today. The aim of the summit is to understand what is happening, share Indigenous approaches to peace-building, we will share knowledge, science, research, practices to enable us to work to mitigate violent conflict. So as we mentioned, the aim of the summit are threefold. First, we will be bringing, like all of you are here. Second, we will be, you know, having all your sharing. So in the next two days, please feel free to share the ideas, your thoughts coming from your people and your nations. And then we have, we will be launching a global network of Indigenous peace-builders, negotiators and mediators. The research and the findings will be published so you will ever get the report and what we have done in the next, we'll be doing in the next two days. We will also work to ensure the inclusion of Indigenous peace-building efforts in several peace talks and peace processes. We will engage the UN Permanent Forum and all the multilateral fora on this to quote, from the great law of peace, roots have spread out from the tree of great peace, one to the north, one to the east, one to the south, and one to the west. These are the great white roots and their nature is peace and strength. Thank you. Let the work begin.


okay we should be live testing hello hello hello how are you i can't hear myself yet what's this weird yeah it's like two faces in there kind of thing there is the mesh um yeah the camera is up uh up high camera is in the in the ceiling essentially i don't know why my fingers are jittery like that they're actually not moving at the moment but yeah it's a bit jittery i don't know why if i turn off turn on that light becomes better or not sometimes my head disappears as well and obviously then like essentially two faces there's this face of the back that has this weird foxy eyes mouth and nose kind of thing and then there's this thing overlaid on top it's a bit odd and sometimes yeah the mesh sometimes flickering it's always the separate uh algorithm thing to move the camera a bit but or move myself yeah especially when i'm looking at the other screen the mesh face disappears should somehow integrate the cup unit should be easily detectable as well because it has this nice button on it you can see my mouth can you and to be opening my mouth like this maybe we should change to the other camera last time when i had both of them loaded i had some issues with the microphone it's getting a lot of weird noise coming through through into the mic i'm having issues as a digital twin i would uh let's say a window a video so i still have zero one two three zero and it's using the second camera the one is some sort of virtual camera can a second camera doesn't work give me any proper error or anything it's connected to a separate usb board all right now it's not showing at all have another chip in the shit oh yeah whatever maybe do a 3.5 to restart this camera without physically reconnecting through terminal in ubuntu it's just work no yeah we need to install that two megabytes of stuff wanna reset this camera reset is not available there in the kernel model associated to the camera or model associated to the camera which may have a name like module name okay what does this reload the module okay this should restart the camera no we did not i have two cameras connected the second one is not being recognized here we do have some errors it's actually a lot of errors again all this usb device errors let's suspectify basically unplug i'll start having trouble with the microphone okay now i have second camera connected right okay that works yeah it's just checking that everything is working because actually unplug the usb close this yeah i'm not sure why it's uh not very stable but then okay that's kind of works okay i don't know this is if my cpu is busy with other things and though it's set to performance i'm downloading another data set from vasionet that's probably affecting the avatar performance


Hello, my name is Antony Brotodot from Ryan in France. Today, we are going to learn how to annotate a new genome using fan annotate on a Galaxy instance. We're going to use usegalaxy.u, but it should work on another usegalaxy server. And we are going to do this by following the tutorial in the genome annotation section. And we'll use this one, genome annotation, with fan annotate. OK, so why do we need to use this tool? Fan annotate is specifically designed to annotate eukaryotic genomes. At the beginning, it was written to annotate fungal genomes, but now it works on any species. And we need this tool because eukaryotic genes are often quite complicated compared to prokaryotic genes, because you have introns and you have some signals at the sequence level that are not very specific. So like intron, donor, and acceptor sites, for example, there are very short sequence of two letters, which are found in many places that are not every time an intron donor or acceptor site. So fan annotate is a big pipeline that will try to align some evidences against the genome sequence and run some ab initio gene predictors to predict gene structures taking into account all this information. So in our case, we're going to try to annotate mucormucidogeno, which is a fungal species that was assembled following the fly assembly tutorial on GTN too. And we are going to use some RNA-seq data from an RNA-seq experiment that was made available on the public data banks. And we are going to use also some protein sequence alignment from protein of public data banks. We'll solve all this a bit later. After we have run a fan annotate to predict the gene structure, we will try to add some functional annotation to know what is the function of each gene that has been predicted by a fan annotate. So we'll run eggnogmapper and interpolar scan. And after that, we will try to integrate all this information, the structural annotation and the functional annotation, into a single annotation file that can be submitted as is to public data banks like NCBI. And at the end, we'll also visualize our annotation using a genome browser. So it's time to begin the tutorial. So the first step is to get all the data that you will need during this tutorial. So they are all available here. We're going to upload them to your history. So I'm on newsguest.cu. I've created a new story that I will name Fan Annotate, which is not very original. And then I click on Upload Data here, Paste page data. And I paste all the URLs here. Nice dot. OK, so the data sets are now uploaded. So let's have a look at them. The first one here is the genome sequence, as was generated by the fly tool. If you look at the fly assembly tutorial, so it's the mucormucidoo genome, where you only have the sequence. And it has been masked using a repeat massacre with the human data set. If you can see how it was masked following the repeat masking tutorial, which is also available on the GTN. Other data sets include RNA-seq data. So it's paired in data, sequencing data, for an RNA-seq experiment. So it looks like this. And it comes from a public data set from SRA. So you have the R1 reads, the forward reads, and the reverse read here. So this will be used by Phenanotate to see where there is expression along the genome sequence. And Phenanotate will also use this protein sequence file, SwissPod subset. These are sequences from the SwissPod data bank, which is a bank of very good quality protein sequences. It's a subset, which means we have only kept nearly 4,000 sequences from SwissPod. It's a subset because we wanted a smaller data set to make the tutorial a bit shorter, to have some quick processing by Phenanotate. But for real-life data, real-life annotation of a genome, you will use the whole SwissPod data banks. And the two last data sets are alternate annotations. In fact, it's a result of running Phenanotate on the same genome, but with different setting. And we will see at the end of this tutorial how to compare the annotation that you will generate and this one to see which one is the best. I know the two. OK, so now to run Phenanotate, the first step is to prepare the RNA-seq data to align this data along the genome, to produce a BAM file that will be used by Phenanotate then. So to align RNA-seq data, we will use a star, so RNA star here, which is a tool designed specifically to align RNA-seq data along the genome, taking into account intron and exons, as you would expect for this kind of data. So this is paired-end data, and we only have one experiment, so we will use individual data sets. The forward reads is R1, and the reverse one is R2. And we will use a reference genome that is in the history. It's a genome masked, a file you have just uploaded. And we will set this value, the length of the essay, pre-indexing string to 11. Why do we do this? Because 11 is the recommended value for this genome size.  And that's what I did. And I saw that star was saying, hey, you should use 11 for this option. So that's what I did. That's it. We're going to run it this way. And well, if you have multiple RNA-seq data files, you can align them all with RNA star. They will produce each one a specific BAM file as output. And at the end, you can merge them all with a merge SAM files tool here. And there you can select all the BAM files you have generated. When it's finished, you can see that you have the BAM files that you will use for an annotate. It's the half gigabytes of data in binary format that you can't really read like this. This file will not be used. It's the spliced junctions position on the genome. We will not use it. And you have this file, which is a log file of what was aligned by a star. And if you look at the statistics, there is one that is very interesting. It's this percentage, which says that 96% of the reads were uniquely mapped onto the genome in the expected orientation. So that's a very, very good score. And it's normal because, in fact, the RNA-seq data here is not the raw data that was downloaded from SRA. In fact, we've reduced it to a subset of reads that are mapping onto the genome once again to make the fan annotate and RNA star run faster during the tutorial. Anyway, so now we have this map file, and we will use it to run fan annotate. So now we will run the structural annotation prediction using fan annotate predict annotation. So it is this tool here. And we'll see which setting we'll adjust. The first one is which genome we want to annotate. So this one is easy. It's the genome mask sequence, still the same. Then you have this fan annotate database. So in this box, you should select the latest version. So for usegalaxy.eu, it's this one. You can have other version on other usegalaxy servers. And if there is no version, you should contact the usegalaxy administrator to install it from the admin panel. OK, then, perfect. There is this information after that. That fan annotate requires to have some information about the genome we are trying to annotate. So the species is mycore-musedo. The strain name, we don't have an isolate name, but the strain name is macwan. And there is this box where you can select if it's a fungus species or not. Here, we will keep no. You could choose yes, because mycore-musedo is a fungal species. But the thing is, after testing it, you don't get really better results by selecting this option. And you might even get some errors during the process. So in this case, we'll use a no. And in most cases, it's fine to use no. We'll consider that there is only the ploidy of the SMD1. So there are not multiple copies of the same genes because of multiple chromosome copies. The rest will be kept as is. And now, the important part is the evidences here. So this is where you need to select the RNA-seq data you have just mapped in the previous steps. So the fan annotate will use this data to train abinishu predictors, like Augustus and GenMark, to recognize a gene on the specific genome. Then if you have full-length mRNA or EST sequences in fast-stay format that you would like to align against the genome, you can provide it here. But in this tutorial, we don't have these sequences. So we just skip it. Here, you can select protein sequences to align against the genome. In real life, you would use this default option, use uniprot kb-swiss-prott, that is already provided by fan annotate. So it's the full set of swiss-prott proteins to align against the genome. Even if they are proteins from very distant organisms, fan annotate will try to align it. And if it's too distant, in worst case scenarios, this sequence would just not be aligned and it won't pollute the results you will get from fan annotate. In our case, I said at the beginning that we are going to use a subset of swiss-prott to make it faster. So this is this fast affile. We'll leave the defaults here. And then there is these options to tell fan annotate how it should use busco to try to train the models, the ab initial predictors, to recognize gene on this genome. So here, we will select the Daxon, which is closest to our species. And we have some mucorales db, so it's cool, selected. And we will select also an initial Augustus species that is quite close to our organism, which is another fungal species. OK, so then we will not filter the output. We will keep everything, but you can choose to keep on the gene models that have a specific minimum internal length, or maximum internal length, or minimum protein length. That's what you can select here. You can finally tune each sub-command that is run by fan annotate, so Augustus, gene mark, and EVM, for example. We will not do it here. Defaults are fine. And here, we want to keep all the outputs of fan annotate. So we select all like this. OK, so now we are ready to run the tool, and we do it like this. So you get all this data set produced by fan annotate. Let's have a look at each one. The first one is annotation in gene bank format. So it's the list of all the genes that were detected by fan annotate on the genome with their position, and they have an automatic name, which is just fun 1, 2, 3, et cetera, and the protein sequence that was predicted for this gene. And they all have a hypothetical protein name because it's just a structural annotation. There is absolutely no functional annotation at this state. And that's it. Then you have the same information in GFF format here, which is another very standard format like this. So you have the exact same information with the position on scaffold 1 from start to the end. There is a gene with this identifier. And in this gene, there is one mRNA with two exons and two CDS sequences that are part of these exons. And you have this on all the genome. OK, that's cool. You have the NCBI-TBL annotation file, which is quite similar. It's another format describing all the genes that were predicted. And then you have three important files that are the protein sequences. So it's a fast file with a sequence of each gene that was predicted, the protein sequence. The same thing for the mRNA sequence. So the full mRNA, including any UTR, 3 prime or 5 prime. And the CDS sequence here, which is only the translated sequence of each gene that was predicted. So if there are no UTRs, the sequence in CDS is the same as in mRNA here. And then you have a few output files. So the TBL-2SN error summary here will give you some statistics on potential problems that were found by fan annotates in the genes that were predicted. So it tells you that there is one gene that is probably a partial gene, where a part of it is missing. There are 600 genes that have a very short exon that is maybe problematic or maybe not. It's fan annotate is not sure of that. And there is more than 400 genes that have a very, well, a rare splice consensus done off site, which means it's a typical sequence for done off site of an entrant. OK, the same thing, detailed for each of these hundreds of genes. You have the, every time it tells you that at this position on the genome, the gene that was predicted with this name have a short exon. So you can review this list if you're interested and check what to do with it. And finally, there is a stats file, which is maybe the most important one, that will give you a lot of information on the result that was generated. So first, it gives you information about the fan annotate version, which tool exactly was run by a fan annotate with which data, with exact versions. So as you can notice here, in the video, I selected 2023 version of the fan annotate, but here it's 2022. It's just because I made a trick on the data sets here. So in your history, it should be 2023, all the version that you selected in the form. So you have a few statistics on the assembly that you analyzed. So the number of contigs, the lengths, the N50 and the GC content. So this one should be the same as what is produced in the fly assembly tutorial. And finally, what we were looking for at the beginning, it's the number of genes that were predicted by fan annotate. So here, it produced 14,000 genes and a bit less mRNAs and a few tRNAs. So fan annotate is also able to predict tRNAs. So it means this one, mRNA and tRNA, if you add the two numbers, you get the total number of genes. Other interesting statistics are the average gene length. So it tells you that on average, the 14,000 genes have a length of 1.5 kilobases. And then you have information on the structure of each gene. So the number of genes that have UTR or not, in this case, there is no gene with UTR, which is often the case in this configuration of fan annotate. The number of CDS that have no stop codon or no stop codon, which can happen sometimes if the scaffold is not complete, for example. The total number of exons, how many transcripts have multiple exons? How many have only one exon? What is the exon length on average or the protein length? That's it. So if you look at all these numbers, it gives you a rough idea of how your annotation looks like. If you had 10 times more or less genes, you would be quite surprised. But you know that 14,000 gene for this genome is quite reasonable. It's a clue that gives you a rough idea of the quality of the annotation. But it's not enough. We'll see later how to have better information about that. OK. So now we have an annotation, a structural annotation. And we want to add some functional annotation to it to know which gene was predicted and what is their function. And that's it. So let's have a look at the functional annotation tool. So we will use two main tools to perform functional annotation. The first one is EGNOG Mapper. So EGNOG is a big database of orthology data. So the creators of this database made a lot of orthology analysis to cluster many similar genes that are thought to have the same function in many, many species. These genes are available on a specific EGNOG database. So it's available on this website, like this. So you can see that there are 5,000 organisms that were used. And they produce more than 4 million orthology groups. And with this tool in Galaxy, all the protein sequence that were predicted by Funanotate will be compared to all the ortholog sequences from the EGNOG database. And every time there is a match, the EGNOG Mapper tool will get all the functional annotation that is available in the EGNOG database for the corresponding orthology group and get this information and assign it to the gene that was predicted by Funanotate. This is quite useful. So it's very simple to use. You would just need to select the correct version of EGNOG database. If it's not available, you should contact the use Galaxy administrator to install it. Then you have to select which sequences you want to analyze. So it's just the result of Funanotate, the protein sequences level here. And in the output option, all the options can stay with their default values. But in the output options here, you can unselect this one. Because we want to have some documentation, like some comments in the output files to understand what we are generating.  And while it runs, you can run the other one, which is Interpol Scan here. So this one is a huge script. In fact, Interpol is a big database of protein motifs and patterns that were defined by a lot of people in the world of researchers, specialists of each gene family. And when you use this Interpol Scan tool, it will take each protein sequence predicted by Funanotate and look into it to find any motif that is known into the Interpol database. And when there is a match, you will get the functional annotation that is associated to this motif. And assign it to the protein that is matching. That's it. So here, once again, we select the protein sequence that were predicted. We are analyzing protein sequence here. Here, we need to select the latest Interpol Scan database version. So once again, if it's not available, contact the administrator of the useGalaxy server. And then we have to select which applications we want to run. So this one is a bit tricky.  Here, you have a whole list of different sub-bases of Interpol and specific and corresponding tools. So this one are free to use. So most of the time, you will select them all. If you are in a hurry, you can unselect Panther and PFAM somewhere here. But it's not recommended because these two data banks are, well, they take some time to analyze. That's why you might want to unselect them. But on the other hand, they produce a lot of meaningful and useful results. So most of the time, we keep it and wait patiently to have good results. The other option is this one because there are a few sub-applications of Interpol scan that are not free. They require the acceptance of specific restricted license, which means you use it, but you acknowledge that you will not use it for commercial use, which is hard to define. But you have to think about it for yourself. And there you can select them all or only a few ones. It's up to you. You just need to be aware that these applications are not installed on all use Galaxy servers. So if you are on EU, they should work on .fr2. But on other ones, it's probable that it will not work. Just keep it in mind. That's it. And even if you don't run them, all these ones already give some quite useful results. So don't be afraid to unselect it. OK, the only option we might want to change is this one. By default, you only get a tabular file as output. Here, we want also the XML file. And let's run it and wait for the results. It's finished. Now, let's have a look at the results. Let's begin with EggnogMapper. So you have two results. The first one is seed ortholog files. So yeah, it will display here. What it gives you is the similarity between each protein that is predicted by finite state with a corresponding protein in the Eggnog database that was used by EggnogMapper. So you can see each identifier. And if you use it, you can search it in the Eggnog database to get more information. And you can see how it matched with the value and which part of the protein matched, and so on. So this file might be interesting, but the other one is much more interesting. Usually, it's the annotation file. And here, you see the match between the query, so the protein that was predicted by finite state, and the same protein that is in the Eggnog database with the E-value. So matches with two high E-values were filtered out. And these ones were kept. And the most important part are these columns after that. So Eggnog OGs are a list of an autology group in the Eggnog database that were identified for this specific protein. So every time you get an identifier in various formats, so if you look for it in EggnogMapper here, you can have more information here. We won't go into details, but it's just this identifier. And if you go a bit further to the right, you get a lot of different fields. You get Kogge category, description of this category, and a preferred name, which is a name that was assigned to this protein based on its similarity to an autology group that is known to have this function. So for example, this name, that's it. You have a symbol associated to it, so a gene symbol, which is linked to the description here. And here, you have a list of genontology terms. So if you look on Google for this term, this is, oh, wait. OK, no. This is funny. So genontology term is just a number corresponding to a very standard vocabulary describing a function, for example, or here, a cellular component. So by saying that this predicted gene has the genontology term 1, 2, 3, it says that it's part of the histone-acetyl-transferase complex. So each term like this with a specific number has a specific name and description that has been standardized. And you have a full list like this for each gene based on the ignored database. So it's very long like this. After that, you have information that you can get from the Kogge database. It's a bit the same principle of genontology, but this time it's based on the pathways. So if you looked for this term in a Kogge database, you can find more information. And you have the same thing for another database, which is bright, and CASI, big reaction, PFAM, and so on. So all those columns correspond to specific databases that you might be interested in or not, depending on what you're working on. So all the genes don't have information on all columns, which is absolutely normal. So it's nice. Now our genes have names and functions, and that's pretty cool based on ignored database. And now the same kind of result has been generated by Interpluscan using another method, which is very important because at the end you will want to aggregate all the information that you get from Egnog and Interpluscan. We'll see that a bit later. So the output of Interpluscan says that, yeah, let's look at this one, no, this one. For a specific protein predicted, this column is just an identifier, a unique identifier based on the protein sequence. You're not very much interested in it. What you're interested in is this one, pro side profiles. It's, well, for each protein, you will have a line, and each line corresponds, you can have multiple lines, and each line corresponds to a match to a specific motif with an identifier here from a specific sub-database of Interpluscan, of Interpluscan. So it means this protein has a match with the motif PS50110 from the pro side profiles database. So if you look for, ah, sorry. If you look for it in Interpluscan, Interplus, sorry, I always confuse that. If you look for it, you should have a match here, and you can click on it and get a lot of information. So it's a pro side profile with a full description of what this domain that was found in a protein to what it corresponds. So this one means that the protein that contains this domain is probably involved in the response to, it's probably a response regulatory domain. Yeah, sorry. OK, so then you have some score information and some full text description here, here too. And IPR number is another identifier that is available in the Interpluscan. In fact, each individual motif like this from specific database is integrated into Interplus into a general IPR ID here. And this one is a more general description of the motif, and it can contain a different motif that corresponds to the same function. This one. OK, and then you have all the good terms that are assigned by Interpluscan based on the profile matches, and a lot of external identifiers like metacic database identifiers or hecto and so on. OK, that's great. So we have stricter annotation, functional one. And as I said, we'd like to integrate all this data into a single final annotation that could be ready for submission to NCBI. So let's try to do it. So if you want to submit your annotation to NCBI, there are a number of things that you need to consider. So let's have a look at the submission to NCBI section of the tutorial. First, you don't want to perform a real one with the data from this tutorial because you don't want to pollute the NCBI database. So please just generate the files but don't submit them really to NCBI. And then when you need to submit an annotation, you have to prior to that to prepare all your raw data and a few other things. First, you need to create a bio project and a biosample on the NCBI portal. So this will describe which genome you're trying to sequence, assemble, and then annotate, and then submit to NCBI. So which species, which environment it was taken from before sequencing, et cetera. You have the biosample, which describes very precisely which biological sample was used for sequencing and for an assembly of the sequencing data annotation. You should already have submitted your raw reads to, well, DNA-seq and RNA-seq data. This data should be submitted to SRA first and have identifiers associated to them. And they should be linked to the bio project and biosample. And also, you should consider first submitting the assembly to NCBI before submitting the annotation because there is a good chance that NCBI will look into your assembly data, your genome sequence, and ask you to modify it if they found some problems in the sequence. So you should do it first before really trying to annotate the genome. The other thing that you need to have before submitting an annotation is a locustag. So this is the prefix that is used in the predicted gene names identifier, at least. For now, we are using FUN0001. That is the default prefix. But you should have a specific one, which is assigned by NCBI when you want to create your annotation submission to the portal. When you have done all this, you have to prepare a specific template file, which is just a text. We'll see structure a bit later that you can generate by using this form. So let's do it. So let's say we are John Doe. We have a wonderful email address, which is johndoe.exe.org. We work for Foo in the bar department, which is located in Foo Bar Street in Paris in France. The first author is John Doe. So this field has changed since last time. So here you can write the name of a potential paper you would write on this, which is unpublished. And here you would write, if you have it, the bioproject and biosymbol identifier that you can get from the NCBI portal. So once you have filled all these fields, you can create the template file and download it. It looks like this. So it's not very pretty for the human eye. But yes, we will upload it to our Galaxy History now. Drag it from here. Oh, yeah, you haven't seen the structure. I will show you it. So the template SBT file looks like this. It's not very pretty for the human eye, as I said earlier. So now we have this template file. We have the result of Intaproscane and Ecnogmapper and the first predicted annotation by FunAnnotate. So we want to integrate all this into the final annotation ready for submission. So to do this, we have a specific FunAnnotate tool here, which is FunAnnotate Functional Annotation here. And here we have to select first the FunAnnotate predict output. So it's a gene bank format. It's the one that was predicted a bit earlier here. Here, again, we have to select a specific FunAnnotate database. So choose the latest one and the same one that you used earlier in the predicted state. Then you have to select the template from the NCBI submission for Porta here. You have to select the Ecnog output, so the annotations output here. So we don't have anti-smash, which is more of a prokaryotic stuff. So we don't have one for this genome. We have InterProscane output in XML format here. And once again, we have to select which busco model we want to use. So the one closest to our genome is McCorales. That's it. We have to use the same strain name as earlier, Mc1. And here, you have to specify the Locustag that most of the time will be provided by the NCBI. In our case, it's mmusedo underscore. And we select which output we want, so we select all. And that's it. You run the tool. And we wait a little. So let's have a look at the different files. There are many ones. The most important are gene bank outputs here. So it's, once again, all the genes that were predicted by an annotate. But this time, you see that the prefix is different. Here, it's mmusedo, as we asked. You have the protein sequence. And for specific genes, you have all the functional annotation from Ecnog and InterProscane that is associated to the gene in the gene bank format. So you have Ecnog data here with different identifiers and InterProscane data here. And yeah, you might even have some gene names that were changed for specific genes. This one is named Taf5.1, because Ecnog say that it was this name for this gene. That's great. You have this file, which is the same kind of information, but in another format, which is just a tabular format. This one's a split AGP, TBFR, second genomes, and scaffold sequences. All these are files that will be asked when you submit your genome to NCBI. So you have it. They contain the same kind of information in different formats. So it's not very interesting to look at them one after the other. You also get the protein sequences here and the mRNA and CDS sequences, just as the beginning. But just notice that the identifiers have been changed to mmusedo. And the GFF format, which is here once again, the gene names have changed, and you have some functional annotation integrated. You have a lot of reports describing here. You have a few more checks that are done on the annotation with specific warnings telling you to have a look at specific genes that might have a problem, even if it's not sure. So this is the general report, but you have other things like product massfix. So here you don't have. Need correction, no. New name pass. Here you have a few new names that are not done by fanatite yet. It's not very important at this time. But you have here statistics. It's just as the fanatite predicts step, but here you have these lines that are different. And here you see how many Go terms were assigned to genes, how many Interpol scan matches were integrated, how many Hagnog matches to, and how many PFAM links to and the different databases. So that's quite interesting to look at these numbers to guess if your annotation looks good and if it was probably functionally annotated. That's it. So we have now a good annotation ready for submission, but we want to evaluate it a bit better and to visualize it. So there is one cool tool to evaluate an annotation, which is BUSCO, which is also used for assembly evaluation. So you will have more information about it in assembly. But the main principle of BUSCO is to look at your annotation and see if it can find a set of genes that are expected to be present in any species of a specific taxon. So for example, if you take a micro-LS, you know that all the species of this group are expected to have a set of genes in one single copy in the genomes. And it's probable that these genes are essential for the life of these organisms. So we use it, I mean, the BUSCO tool use it to guess if your annotation contains all the genes that it is supposed to be present or not. So it's a good way to have a feeling about your annotation to check if it looks good or not. So how does it work? You select the protein sequences, the last one that were predicted, and then you say that you want to run in protein mode here. And you select a specific line edge, which is micro-LS once again. Here you have, by default, when you run BUSCO, it will download everything it needs to run, and you don't have to worry.  In this case, you can use cached line edge data and select the latest one here. If the use Galaxy administrator have installed it. In this case, BUSCO will not try to download, and it will run just a little bit faster and avoid potential download problems. Anyway, whether you select this option or this one, you will get the same results. I know that on EU it works with this one, so I select it. And finally, here I want the short summary text and the summary image. And I can run it. When it's finished, you can look at a beautiful image here, which is a bit too big, like this. So this is a summary of the results. So on a total number of 2,281 genes that are specific to Mucorales species, BUSCO tried to find them all on the annotation that we have generated. And it found 2,250 genes in single copy, and they only found three. Oh, wait. No, the total number that was searched is this one. 2,449. And yes, 2,281 were found to be complete in the genome, in the annotation we provided. And this number were in single copy, as expected, and 31 were in duplicated genome, which is not supposed to happen, except if there's really a duplication in the genome in the species, or if maybe there is an assembly problem with the path of a genome that was what is present in two copies in the assembly instead of one. It can happen, too. Then you have the fragmented ones. So there are a few genes that were found but incomplete in the genome, or in multiple chunks in multiple scaffolds. So this, again, can come from an assembly problem. And a few ones, too, 140 were not found in the annotation, which means either they are not present in the assembly, or they were not detected by fun annotates. And probably it's a mix of the two. So you have the same numbers in text format, which is maybe more readable if you want to have a look at it. And that's it. So is it good or not here? You can see that the vast majority was found in the annotation in single copy and complete, which is a good evidence that your annotation is in good shape. So on its own, it's interesting. But if you have multiple annotations, you can always run BUSCO on each one and see which one is the best. And what is important, too, is to compare these numbers to the result of running BUSCO on the row assembly output. So just giving it the sequence of the genome and letting it find the genes in the sequence prior to annotated genome. So it's good to have the numbers before and after annotation and to compare it. So I know it's quite similar, which means the annotation is in good shape in this example. For now, we only have seen a text output of annotation. We might want to visualize it. So we have a cool genome browser available in Galaxy, which is Jbrows. So it's just a way to visualize the annotation and the assembly. So we will give it genome. So the first data set we uploaded, genome masked. And then we have to select a few data sets that we want to display on this genome. So we will display it in two groups. We add two groups. The first one will be annotation. And the other one will be RNA-seq. In annotation, we add one specific track in GFF format, which is the GFF output of the last finalized functional run. And that's it. We leave all the other options, like as is. And in RNA-seq, we select the output of RNA-style. The first two, we run into this tutorial. And no, it's not this data set. This option is BAMP by labs here. And we select this to display a specific visualization. OK, let's run it. So how does it look? So you can open it here. What I prefer to do with J-brows is open it in another tab, like this, to get the full J-brows. Wait, it's not doing what I expected. OK, never mind. It's OK like this. So here, you have a genome brother with a list of scaffolds you can see. So I just realized that it's not displaying the correct one. OK, never mind. I tried to be too smart, so I chose a wrong J-brows history. I have uploaded a new one here. And that should display properly. On your history, you display just fine the first time. It's my fault. OK, so this is a standard J-brows application where you can navigate on the genome. Here, you have a specific scaffold, which is displayed. And here, you can see the whole scaffold coordinates from 0 to 1 million bases. And you have this region in red that is displayed, that is zoomed in in this section. And here, you have a list of tracks that you can display. So we can first have a look at the genes that were predicted by phenolotates. So you can see them like this. They have a hypothetical protein name for the one that don't have functional annotation, or if they can have good names like this. So the big blocks are x-zones. And the little, the thin ones are introns. And if you look at them, here you can get all the functional annotation associated to it with the identifiers that you can use in search on the Interpro or Go or Eggnog databases. Fine. And you can display also RNA-seq data like this. It can take a little while to load. But when it displays, you can see a coverage plot showing you how many reads were aligned to the genomes at specific position. The light gray means it's reads that were aligned at this position. And the dark gray means you have reads that were split between two x-zones. And these regions are the gaps between these x-zones. So you can see the specific reads one by one using this option. So you can see that phenolotate was able to use these evidences, this RNA-seq data aligned to the genomes to predict x-zones of specific genes. And you can go and look at other regions on a region. There is a specific J-Brass tutorial if you want to look more into details how it works. Fine. OK, so now the last things you might want to do with an annotation is compare it to another one. And remember, you have in your history here an alternate annotation that was performed by myself using phenolotate but with different settings and bad settings, in fact. We'll see how it looks. So the first tool you might want to run is HGN Parseval. So here you have to select a reference GFF-free file. It will be the one you have generated. And the prediction GFF file, which is the one that the alternate one that you uploaded at the beginning. And the output type you want is HTML. So you just run this. And the other tool that you want to use is phenolotate compare, where you will select genome annotation in gene bank format. So the one you have generated and the one, the alternate one. And here you select once again the latest phenolotate database like this. And that's it. You run it too. And you wait a little. Phenolotate compare can take quite some time and Parseval too, I guess. So be patient or be patient. Once it's finished, you can have a look at it. So HGN will give you an HTML file showing you various details on the tool annotation. Here you have a list of scaffolds where you can have more details on each gene. And you have some specific numbers after that. So if you go to the scaffold 11, this one, as is explained in the tutorial, you click on the first look here to get more information. And here you will see a specific region of the scaffold 11 and a comparison of the genes that were predicted by phenolotate in the two annotation. So this one is the one that was predicted by yourself in that tutorial. And this one is from the alternates annotation. So you can see that based on this, phenolotate with all the correct settings we used was able to predict four different genes in different orientations. And if you look at the alternates annotation, phenolotate only predicted once big genes with exons in the same directions and with a huge entrance. That's it. What it reflects is that this annotation is probably better. And in fact, it's exactly the real situation because the alternates annotation was done using phenolotate without giving any RNasec data and choosing a wrong line age for Bisco, which was insecta. So it had a lot of trouble predicting genes and predicted like aberrant stuff like this. So yeah, this agent stuff can help you decide which annotation looks better. And the other tool is phenolotate compare. Let's have a look at the reports. So here you have a lot of information. First, the stats. You can see how many genes were predicted in each annotation. The one you have generated as, yeah, this number is wrong here. But it should be 14,000. And the other one as 9,000. It's wrong because once again, I try to be too smart. But in your case, it should be the correct number. If you look at the orthologs, you can see a list of orthologs between genes in your annotation that you predicted and other genes that look similar in the alternates annotation. So you have a full list of orthology groups like this. And you can get more details like this. If you look at Interpro, for example, you can see how many genes from the first or the second annotation have specific Interpro numbers associated to them. So what you can mainly see is that the one, the annotation that you generated, have more genes with the corresponding Interpro terms than the alternate one, which is once again a good clue telling you that your annotation is better. It's the same for PFAM and other stuff like Merobs and so on. If you look at Go here, you can see some specific Go terms that are under or other represented in each annotation. So in this case, it's not very representative. But in other cases, it can be useful. OK, so we now have finished this tutorial. As you can see, it's a complex subject, annotation of genomes. If you want to give us some feedback on this tutorial, you can always, and it's very much appreciated, use this feedback form here or contact us on the Slack channel if you are running it during Smogersport, other training session. And finally, you might be interested in another tutorial concerning annotation, which is the Apollo tutorial here, refining genome annotation. This one will show you how you can use the Apollo application, which looks like this, to manually curate an annotation. So if you have a look at your annotation, and for example in Gebros, and you realize that finality predicted a quite good annotation, but there are some genes that are wrong and you want to correct it manually, this Apollo application allows you to do it easily. So it might be interesting in the following the tutorial. OK, that's it. Thanks for listening.