BOL: Related items

Must read paper and books in evolution biology !

Abhi — Wed, 05 Oct 2022 18:33:01 -0500

1.       *Nick Barton:*

- The textbook "Evolution" by Nick Barton, with resources for
  exploring the literature: Barton, N. H., Briggs, D. E. G., Eisen, J.
  A., Goldstein, D. B., & Patel, N. H. (2007). Evolution. Cold Spring
  Harbor Laboratory Press.

- Papers from a course named "Classics in Evolutionary Biology":

Evolutionary Synthesis
1. Haldane, J. B. S. 1932. The causes of evolution. Longmans. New York.
   (esp. Ch. IV).
2. Fisher, R. A. 1930. The genetical theory of natural selection. Oxford
   University Press, Oxford. Selected Sections - Fundamental Theorem.

Genetic Variation
1a. Lewontin, R. C., and J. L. Hubby. 1966. A molecular approach to
the study of genic heterozygosity in natural populations. II. Amount
of variation and degree of heterozygosity in natural populations of
Drosophila pseudoobscura. Genetics. 54:595-609.

1b. Sachidandam et al. 2001. A map of human genome sequence variation
containing 1.42 million single nucleotide polymorphisms. 409: 928-33.

2. Wright S., Dobzhansky T., Hovanitz W. 1942 Genetics of natural
populations VII The allelism of lethals in the third chromosome of
Drosophila pseudoobscura. Genetics 27: 363-394.

Recombination and evolution
1. Hill, W. G., and A. Robertson. 1966. The effect of linkage on limits
to artificial selection. Genet. Res. 8:269-294.

2. Maynard Smith and Haigh. 1974. The hitch-hiking effect of a favourable
gene. Genet. Res. 23: 23-35.

Understanding sequence variation
1. Begun D. J., Aquadro C. F., 1992 Levels of naturally occurring DNA
polymorphism correlate with recombination rate in Drosophila melanogaster.
Nature 356: 519-520.

2. Green R. E., Reich D., Pääbo S., 2010 A draft sequence of the
Neandertal genome. Science 328: 710-722.

Quantitative Genetics:  variation in complex traits
1. Galton F., 1877 Typical laws of heredity. Nature 15: 492-495-
512-514- 532-533.

2. Turelli M., 1984 Heritable genetic variation via
mutation-selection balance: Lerch's Zeta meets the abdominal
bristle. Theor. Popul. Biol. 25: 138-193.

Quantitative Genetics:  finding the genes
1. Shrimpton A. E., Robertson A., 1988 The Isolation of polygenic factors
controlling bristle score in Drosophila melanogaster II Distribution of
third chromosome bristle effects within chromosome sections. Genetics
118: 445-459.

2. Boyle E. A., Li Y. I., Pritchard J. K., 2017 An expanded view of
complex traits: from polygenic to omnigenic. Cell 169: 1177-1186.

Neutral Evolution
1. Kimura, M. 1968. Evolutionary rate at the molecular level. Science.
217:624-626.

2a. Kern A. D., Hahn M. W., 2018 The Neutral Theory in Light of Natural
Selection. Molecular Biology and Evolution 110: 21077-6.

2b. Jensen J. D., Payseur B. A., Stephan W., Aquadro C. F., Lynch M.,
Charlesworth D., Charlesworth B., 2018 The importance of the Neutral Theory
in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 112:
2109-4.

2c. Ellegren & Galtier. 2016. Determinants of genetic diversity. Nature
Reviews Genetics.

Mutation and Genetic Variability
1. Luria, S. E., and M. Delbrück. 1943. Mutations of Bacteria from Virus
Sensitivity to Virus Resistance. Genetics. 28(6):491-511.

2. Hill, W G. 1982. "Rates of Change in Quantitative Traits From Fixation
of New Mutations." Proceedings of the National Academy of Sciences (U.S.A.)
79: 142-45.

Testing for selection
1. McDonald & Kreitman. 1991. Adaptive protein evolution at the Adh locus
in Drosophila. Nature.

2. Begun, et al. Mol. Biol. Evol. 16, 1816-1819 (1999).

3. Siddiq et al. 2016. Experimental test and refutation of a classic case
of molecular adaptation in Drosophila melanogaster.  Nature Ecology &
Evolution.

The shifting balance
1. Wright, S. 1932. The roles of mutation, inbreeding, crossbreeding and
selection in evolution. Proceedings of the VI International Congress of
Genetics: 1. pp 356-366.

2. Coyne, J.A., N.H. Barton, and M. Turelli. 1997. A critique of Wright's
shifting balance theory of evolution.  Evolution 51: 643-671.

3. Barton. 2016. Sewall Wright on Evolution in Mendelian Populations and
the "Shifting Balance". Genetics.

Evolution of Sex
1.  Muller, H.J. 1964. The relation of recombination to mutational advance.
Mutation Res. 1(1):2-9

2. McDonald et al. 2016. Sex speeds adaptation by altering the dynamics of
molecular evolution. Nature.

Kin Selection, Cooperation, and Conflict
1. Hamilton, W. D. 1964. The genetical evolution of social behaviour I.
Journal of Theoretical Biology. 7:1-52.

2. Trivers, R. L. 1974 Parent-offspring conflict. American Zoologist.
14(1):249-264.

Sexual Selection
1. Zahavi, A. 1975. Mate selection - a selection of a handicap. J. Theor.
Biol. 53:205-214.

2. Kirkpatrick, M., and Ryan, M.J. 1991. The evolution of mating
preferences and the paradox of the lek. Nature. 350:33-38.

Fitness Landscapes
1. Dean, A. 1995. A Molecular Investigation of Genotype by Environment
Interactions. Genetics. 139:19-33.

2. Costanzo et al. 2010. The Genetic Landscape of a Cell. Science.

Speciation
1. Coyne, J. A., and H. A. Orr. 1989. Patterns of speciation in Drosophila.
Evolution. 43:362-381.

2. Corbett-Detig et al. 2013. Genetic incompatibilities are widespread
within species. Nature.

2.       *Marcos Antezana:*

Valen, L. v. 1975. Energy and Evolution. University of Chicago, Department
of Biology.

3.       *Remco Folkertsma:*

1. The work by Hopi Hoekstra on local adaptation and oldfield mice

2. Poelstra, J. W., Vijay, N., Bossu, C. M., Lantz, H., Ryll, B., Müller,
I., ... & Wolf, J. B. (2014). The genomic landscape underlying phenotypic
integrity in the face of gene flow in crows. Science, 344(6190), 1410-1414.

4.       *Joshka Kaufmann and Leslie Turner*

They offer us a link to 'papers every evolutionary biologist should read',
the papers are collected by Leslie Turner.
https://static1.squarespace.com/static/53e8cb7ce4b02c4bc3aeeee4/t/5ab8fcb670a6ad55c67fcdf4/1522072758665/EvoBioClassicsRefList.pdf

5.       *Sarah Stockwell*

Matt Ridley collected classic papers in evolutionary biology and printed
part of these papers in his book Evolution (see Matt Ridley. Evolution
(Univ. of Oxford Press, 2nd edition, 2004))

dcGOR

Martin Jones — Sat, 08 Nov 2014 14:54:28 -0600

An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.

The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:

1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html

2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html

3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html

CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.

Jit — Tue, 26 Apr 2016 11:38:10 -0500

Canu is a fork of the Celera Assembler designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.

Canu is a hierachical assembly pipeline which runs in four steps:

Detect overlaps in high-noise sequences using MHAP
Generate corrected sequence consensus
Trim corrected sequences
Assemble trimmed corrected sequences

Read the documentation

New release https://github.com/marbl/canu/releases

Address of the bookmark: https://github.com/marbl/canu

ORFfinder with smart BLAST

Jit — Tue, 17 May 2016 01:43:15 -0500

ORF Finder

ORFfinder is a graphical analysis tool for finding open reading frames (ORFs). We’ve been working on a few updates, and we’d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.

Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)

Select one or a group of ORFs and BLAST several databases at once, and use the newly developed SmartBLAST to verify protein names. Looking for the traditional results from BLAST? They’re there too.

BBMap/BBTools package: Multipurpose tool designed for converting reads or other nucleotide data between different formats.

Jit — Mon, 13 Jun 2016 05:47:21 -0500

Reformatis a member of the BBMap/BBTools package. It is a multipurpose tool designed for converting reads or other nucleotide data between different formats. It supports, and can inter-convert:

fastq
fasta
fasta+qual
sam
scarf (an old Illumina format)
bam (if samtools is installed)
gzip
zip
ascii-33 (sanger)
ascii-64 (old Illumina)
paired files
interleaved files

It is multithreaded and can process data at over 500 megabytes per second, and can accept streams from standard in and write to standard out, allowing it to be easily dropped into the middle of a pipeline for format conversion. Reformat autodetects formats based on file extensions and content, making it very easy to use; and the autodetection can be overridden, allowing flexibility for people who don't like to follow naming conventions, or out-of-spec fastq files with qualities values like -17 or 120.

The program has been gradually expanded, and can now perform various other functions. None of these will break pairing, if the input is paired.

Quality trimming (either or both ends)
Quality filtering
Fixed-length trimming
Generation of histograms (base composition, quality, etc)
Subsampling (to a fraction of input reads, or an exact number of reads or bases)
Changing fasta line-wrapping length
Reverse-complementing (all reads or only read 2)
Adding /1 and /2 suffix to read names
GC-content filtering
Length-filtering
Testing for corrupted interleaved files

Reformat is compatible with any platform that supports Java 1.7 or higher. It also has a bash shellscript for simpler invocation. Typical usage examples:

Reformat fastq into fasta:
reformat.sh in=x.fq out=y.fa

Interleave paired reads:
reformat.sh in1=x1.fq in2=x2.fq out=y.fq

Note - you can actually use a shortcut if paired read files have the same name with a 1 and a 2. This is equivalent to the above command:
reformat.sh in=x#.fq out=y.fq

De-interleave reads:
reformat.sh in=x.fq out1=y1.fq out2=y2.fq

Verify that interleaving appears correct, assuming Illumina namimg conventions:
reformat.sh in=x.fq vint

Convert ASCII-33 to ASCII-64:
reformat.sh in=x.fq out=y.fq qin=33 qout=64

Quality-trim paired reads to Q10 on the left and right ends and discard reads shorter than 50bp after trimming:
reformat.sh in1=x1.fq in2=x2.fq out1=y1.fq out2=y2.fq outsingle=singletons.fq qtrim=rl trimq=10 minlength=50

Subsample 10% of the first 20000 pairs in an interleaved file:
reformat.sh in=x.fq out=y.fq reads=20000 samplerate=0.1 int=t
(in this case "int=t" overrides interleaving autodetection, to ensure reads are treated as pairs)

Pipe in a gzipped sam file and pipe out fasta:
reformat.sh in=stdin.sam.gz out=stdout.fa

Reverse-complement reads:
reformat.sh in=x.fq out=y.fq rcomp

For reformatting a file with very long sequences, Reformat will need more memory; just add the additional flag "-Xmx2g". For example, to change the line-wrapping length on the human genome (which has individual sequences over 200Mbp long) to 70 characters:
reformat.sh -Xmx2g in=HG19.fa.gz out=HG19_wrapped.fa.gz fastawrap=70

For additional functions, please run the shellscript with no arguments, or just read it with a text editor. If you have any questions, please post them in this thread.

For people using a non-bash terminal, you may need to type "bash reformat.sh" instead of just "reformat.sh".
For users of Windows or other platforms that do not support bash shellscripts, replace "reformat.sh" with "java -ea -Xmx200m /path/to/bbmap/current/ jgi.ReformatReads"
for example,
java -ea -Xmx200m C:\bbmap\current\ jgi.ReformatReads in=x.fq out=y.fa

Reformat can be downloaded with BBTools here:
https://sourceforge.net/projects/bbmap/

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm)

Abhimanyu Singh — Thu, 29 Dec 2016 03:26:45 -0600

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program developed at Oak Ridge National Laboratory and the University of Tennessee. Key features of Prodigal include:

Speed: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.
Accuracy: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).
Specificity: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.
GC-Content Indifferent: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the Pseudomonas aeruginosa curated annotations.
Metagenomic Version: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.
Ease of Use: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.
Open Source: Prodigal source code is freely available under the General Public License.

Download the latest version of Prodigal at the Prodigal github page.
or
Browse the wiki documenation.

Address of the bookmark: http://prodigal.ornl.gov/

maf2synteny

Abhimanyu Singh — Thu, 18 May 2017 05:31:30 -0500

A tool for converting for recovering synteny blocks from multiple alignment (in MAF fromat)

This tool is a standalone version of Ragout module [http://fenderglass.github./Ragout]

Address of the bookmark: https://github.com/fenderglass/maf2synteny

PhyloGrapher - Graph Visualization Tool

Jit — Wed, 07 Mar 2018 18:11:25 -0600

PhyloGrapher is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements). PhyloGrapher is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use PhyloGrapher to visualize any type of relations between elements.

https://www.youtube.com/watch?v=WgufqYMHCvM

Address of the bookmark: http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html

SynVisio: An Interactive Multiscale Synteny Visualization Tool for McScanX.

Jit — Sun, 31 May 2020 02:01:14 -0500

SynVisio lets you explore the results of McScanX a popular synteny and collinearity detection toolkit and generate publication ready images.

SynVisio requires two files to run:

The simplified gff file that was used as an input for a McScanX query.
The collinearity file generated as an output by McScanX for the same input query.
Optional track file in bedgraph format to annotate the generated charts.

SynVisio offers different types of visualizations such as Linear Parallel plots, Hive plots, Stacked Parallel Plots and Dot plots. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.

Address of the bookmark: https://synvisio.github.io/#/

Panacus : A Counting Tool for Pangenome Graphs

Neel — Fri, 14 Jun 2024 14:42:28 -0500

panacus is a tool for calculating statistics for GFA files. It supports GFA files with P and W lines, but requires that the graph is blunt, i.e., nodes do not overlap and consequently, each link (L) points from the end of one segment (S) to the start of another.

panacus supports the following calculations:

coverage histogram
pangenome growth statistics
path-/group-resolved coverage table

Address of the bookmark: https://github.com/marschall-lab/panacus