1. Earth BioGenome Project (EBP) - A global effort to sequence and annotate roughly 1.5 million known eukaryotic species and create a comprehensive reference library of Earth's biodiversity.
2. Vertebrate Genomes Project (VGP) - Focuses on producing high-quality reference genomes for vertebrate species, providing a major foundation for the wider Tree of Life.
3. Darwin Tree of Life - A UK and Ireland initiative aiming to sequence approximately 70,000 species, creating a detailed genomic map of regional biodiversity.
4. African BioGenome Project (AfricaBP) - A pan-African initiative focused on sequencing Africa's biodiversity while strengthening genomics and bioinformatics capacity across the continent.
5. European Reference Genome Atlas (ERGA) - A European effort to generate high-quality reference genomes for Europe's biodiversity and connect national sequencing efforts.
6. Canada BioGenome Project - Building reference genomes for Canadian biodiversity, supporting conservation, research and the study of ecosystems.
7. California Conservation Genomics Project - Uses genomics to understand and protect California's biodiversity and help inform conservation decisions.
8. Bat1K - An ambitious global effort to sequence the genomes of all known bat species, helping scientists study their evolution, longevity, immunity and unique biology.
9. Bird 10,000 (B10K) - A global project aiming to create genome resources covering the world's bird diversity and reconstruct avian evolutionary history.
10. Global Invertebrate Genomics Alliance (GIGA) - Builds genomic resources for the enormous and genetically diverse world of invertebrates.
11. GenomeIndia - India's national human-genome initiative, designed to capture the country's extraordinary population diversity and create a reference resource for Indian genomics.
12. All of Us Research Program - A US national research program combining genomic information with health and lifestyle data at population scale.
13. 1+ Million Genomes / Genome of Europe - A European effort to enable secure, cross-border use of genomic and health data and develop genome-scale resources involving more than one million people.
14. Korea National Integrated Bio Big Data Project - South Korea's large-scale national effort combining genomic and health information from a very large population cohort.
15. Saudi Genome Program - A national genomics initiative focused on genetic diseases, population genomics and precision medicine in Saudi Arabia.
16. Australian Genomics / Genomics Health Futures Mission - Australia's growing investment in genomic medicine, rare disease research and population-scale health genomics.

1. Merge re-sequenced FastQ files (cat)
2. Read QC (FastQC)
3. Adapter trimming (fastp)
4. Removal of host reads (Kraken 2; optional)
5. Variant calling
   1. Read alignment (Bowtie 2)
   2. Sort and index alignments (SAMtools)
   3. Primer sequence removal (iVar; amplicon data only)
   4. Duplicate read marking (picard; optional)
   5. Alignment-level QC (picard, SAMtools)
   6. Genome-wide and amplicon coverage QC plots (mosdepth)
   7. Choice of multiple variant calling and consensus sequence generation routes (iVar variants and consensus; default for amplicon data || BCFTools, BEDTools; default for metagenomics data)
      • Variant annotation (SnpEff, SnpSift)
      • Consensus assessment report (QUAST)
      • Lineage analysis (Pangolin)
      • Clade assignment, mutation calling and sequence quality checks (Nextclade)
      • Individual variant screenshots with annotation tracks (ASCIIGenome)
   8. Intersect variants across callers (BCFTools)
6. De novo assembly
   1. Primer trimming (Cutadapt; amplicon data only)
   2. Choice of multiple assembly tools (SPAdes || Unicycler || minia)
      • Blast to reference genome (blastn)
      • Contiguate assembly (ABACAS)
      • Assembly report (PlasmidID)
      • Assembly assessment report (QUAST)
7. Present QC and visualisation for raw read, alignment, assembly and variant calling results (MultiQC)

USAGE:

• -query: sequence A in fasta format
• -db: sequence B in fasta format
• -out: output matrix
• -kmer Integer: k>1 (default 32) Use 32 for chromosomes and genomes and 16 for small bacteria
• -diffuse Integer: z>0 (default 4) Use 4 for everything - if using large plant genomes you can try using 1
• -dimension Size of the output matrix and plot. Integer: d>0 (default 1000) Use 1000 for everything that is not full genome size, where 2000 is recommended

Address of the bookmark: https://github.com/estebanpw/chromeister

Contact:
Computer Science Building (Science Park 3)
Altenberger Str. 69, A-4040 Linz, Austria
Tel. +43 732 2468 4520 / Fax +43 732 2468 4539
E-mail secretary@bioinf.jku.at

http://www.bioinf.jku.at/

Install

pip install genomenotebook

How to use

Create a simple genome browser with a search bar. The sequence appears when zooming in.

import genomenotebook as gn

g=gn.GenomeBrowser(genome_path, gff_path, init_pos=10000)
g.show()

Tracks can be added to visualize your favorite genomics data. See Examples for more !!!!

Address of the bookmark: https://dbikard.github.io/genomenotebook/

What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming.

License: GNU General Public License

Citation:

• Cai, Liming, Hongrui Zhang, and Charles C. Davis. 2022. PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome‐skimming data. Applications in Plant Sciences 10(3): 1–9. https://doi.org/10.1002/aps3.11475

Address of the bookmark: https://github.com/lmcai/PhyloHerb/

Key Findings of the Study:

1. Alu Insertion and Tail Loss:
   The researchers discovered an Alu-mediated genetic change in a common ancestor of modern apes and humans. This change disrupted the normal function of a gene involved in tail development, leading to the suppression of tail formation.

2. Gene Disruption Mechanism:
   The Alu insertion was found within a regulatory region of the TBXT gene (also known as T or Brachyury), which is crucial for tail development in vertebrates. This insertion likely altered the gene's expression patterns, leading to tail reduction over evolutionary time.

3. Functional Evidence from Model Organisms:
   To test their hypothesis, the researchers introduced similar genetic modifications in mice. The modified mice exhibited shortened or absent tails, supporting the idea that the identified mutation played a role in tail loss in hominoids.

4. Evolutionary Implications:
   The findings suggest that small, random genomic changes—such as transposable element insertions—can have profound effects on body morphology. This study provides evidence that mobile DNA elements (like Alu) can drive major evolutionary transitions.

5. Relevance to Human Evolution:
   Understanding the genetic basis of tail loss helps in reconstructing the evolutionary history of hominins (the lineage that includes humans and our extinct relatives). It also sheds light on how genetic variations contribute to anatomical diversity among primates.

Significance of the Study:

This research highlights the role of transposable elements in shaping evolutionary traits and provides a concrete genetic explanation for a defining characteristic of humans and great apes. It also demonstrates how mutations in regulatory regions of developmental genes can lead to significant anatomical changes.

Kindly log on to conference website http://rgcb.res.in/IACR2014 for further details and timely updates and registration. We shall truly appreciate if the same be circulated among your friends, scholars and students encouraging them to participate in the meet.

http://210.212.237.38/iacrconference/

Ever since a monk called Mendel started breeding pea plants we've been learning about our genomes. In 1953, Watson, Crick and Franklin described the structure of the molecule that makes up our genomes: the DNA double helix. Then, in 2001, scientists wrote down the entire 3-billion letter code contained in the average human genome. Now they're trying to interpret that code; to work out how it's used to make different types of cells and different people. The ENCODE project, as it's called, is the latest chapter in the story of you. To read the ENCODE research papers and more, visit http://www.nature.com/ENCODE