Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Genome Sequences Ka-Lok Ng Asia University History of genome sequencing • 1995, led by Craig Venter’s group, at the Institute of Genomic Research (TIGR) in Maryland • Reported the complete DNA seq. of the bacterium Haemophilus influenzae • The first viral genome seq. (phage phiX174) was produced by Fred Sanger’s group at 1978 • Insulin A, B chains(胰島素) – the first determined amino acid sequence in 1951 by F. Sanger (Cambridge U) • Sanger was awarded two Nobel prizes, the first one in 1958 on the structure of insulin, and the second one in 1980 (both in chemistry) for developing DNA sequencing techniques (with Paul Berg and Walter Gilbert) Genome sequencing up to year 2001 http://www.biochem.arizona.edu/classes/bioc471/pages/Lecture7/Lecture7.html Timeline of genome sequencing http://www.biochem.arizona.edu/classes/bioc471/pages/Lecture7/Lecture7.html First draft of human genome F. Collins and C. Venter Biological sequence space • • • DNA sequence – a seq. of symbols from the alphabet A, T, C, and G – IUPAC notation – R denotes A or G – Y denotes C or T – - denotes Gap RNA sequence – a seq. of symbols from the alphabet A, U, C, and G – IUPAC notation – R denotes A or G – Y denotes C or U – - denotes Gap Protein sequence – a seq. of symbols from 20 alphabets (except U,X, “J,O,B”, Z) RNA secondary structure Biological sequence space • Convenient to model biological seq. as a onedimensional (1D) object • It is also incorrect • It neglects all the information that might be contained in the 3D structure of the molecule • We make this approximation in this course Building blocks of DNA sequences • Backbone • Pyrimidines – single ring –Thymine –Cytosine • Purines – double rings –Adenosine –Guanin Complementary (A,T), (C,G) Building blocks of protein sequences N-terminius, C-terminus (reading protein sequences from N to C) peptide bond O==C –N-H, alpha carbon, the R group Central dogma of molecular biology More with coding DNA DNA is a double strands, there are a total of 6 open reading frame (ORF) Codon translation Alternative splicing Genome sequences • • • • Prokaryotic genomes – Eubacteria and archaes are the two major groups of prokaryotes organisms without nuclei – Generally have a single, circular genome between 0.5 and 1.3 Mbp long – Simple genes and genetic control seqs. Viral genomes – Not free-living organisms – Can be either single or double-stranded, and either DNA or RNA, that is ssDNA, ssRNA, dsDNA ro dsRNA – HIV, SARS Eukaryotic genomes – Ranging in size from 8 Mb for some fungi to 670 Gbp – Human genome is about 3 Gbp long – Baker’s yeast, worm, zebra-fish, fruit-fly, mosquito; mammalian such as human, mouse, and plants such as rice Organellar genomes – Mitochondrion (mtDNA) and chloroplast genome – Only hundreds or tens of thousand of bases long, circular, and contain a few essential genes Working with whole Genomes Below is a circular representation of the E. coli. DNA and Protein Sequences Databases NCBI http://www.ncbi.nlm.nih.gov/ EMBL http://www.ebi.ac.uk/services/ DDBJ http://www.ddbj.nig.ac.jp/ Protein Sequence Databases NCBI Molecular databases http://www.ncbi.nlm.nih.gov/Database/ RefSeq UniProt http://www.pir.uniprot.org/ UniProt = Swiss-Prot + TrEMBL + PIR-PSD UniProt = UniProt Archive (UniParc) + UniProt Knowledgebase (UniProtKB) + UniProt nonredundant reference database (UniRef) ExPasy http://us.expasy.org/ PIR http://www-nbrf.georgetown.edu/ The Entrez system • Redundancy in GenBank • Many different GenBank entries are relevant to a specific gene, esp. for human, E.coli, yeast, fruit fly • 4 entries encompass the same E.coli dUTPase gene GenBank entries Sizes X01714 1609 V01578 2568 L10328 136254 AE000441 10562 Entrez Gene • Example: MEN1 AND human[ORGN] • where ORGN = organism Entrez Gene • Read the summary Summary • Official Symbol • Gene type • Gene name • Gene description • RefSeq status • Organism • Lineage • Gene aliases • Summary • Reference • Protein-protein interaction FASTA format Batch Entrez Gene • NCBI site map Batch Entrez Gene • Retrieve multiple sequences information at one time • Uniprot seq. ID, prepare a text file, and upload (use database = protein) Q9XX00 Q8MQ56 Q9XWS4 Q9XU77 Q9XWH5 Q9N2K7 Eukaryotic entry example: AF018430 Use CoreNucleotide to search for the seq. Retrieving GenBank entries without accession number • • Entrez - human[organism] AND dUTPase[protein name] AND must be in capital letters ! Whole Genome DB • NCBI home page Genome Biology Entrez Genome Viral genome DB, Microbial genome ..etc ) Microbial genome – TIGR • http://www.tigr.org/tdb/ • Comprehensive Microbial Resource (CMR) Genome databases • allow you to browse genomes starting from chromosome down to a single gene, an individual exons or a nucleotide. • Ensembl database • http://www.ensembl.org • UCSC database • http://genome.ucsc.edu Microbial Database : GOLD • http://www.genomesonline.org Statistical analysis of biological sequences • Look for sequence structures in biological sequences, either DNA, RNA or protein seqs. • Assuming one starts from 1D structure • Take DNA as an example, one expects the frequency of appearance of nucleotide A, T, C and G are equal random sequence, %A = %T = %C = %G = 25% • In actual DNA seq., this is not true ! Statistical analysis of DNA sequences • • • • Study the base composition GC content Frequent or rare words – words of length k Biological relevance of unusual words (motifs) Counting words in DNA seqs. http://www.genomatix.de/cgi-bin/tools/tools.pl create seq. statistics Counting words in DNA seqs. • NCBI Genome (complete genome sequences) microbial Haemophilus influenzae Rd KW20 , NC_000907.1 (TIGR, dated on 1995) Link: RefSeq FTP or GenBank FTP (L42023.fna) Counting words in Haemophilus influenzae genome Total number of bp GC content agree with NCBI record Counting words in Haemophilus influenzae genome • • • • (%A) strand + = (%T) strand -, (%C) strand + = (%G) strand -, …. Because of the complementary principle, i.e. A-T, and C-G Counting words in Haemophilus influenzae genome Use L-k+1 Percentage of dinucleotide Counting words in Haemophilus influenzae genome • Nucleotide words of length 2 (called dimer) or higher (trimers, k-mers) • Words of length k are called k-grams or k-tuples in computer science, or k-mer in biological science Frequency of 3-mers Finding unusual DNA words • A simple statistical analysis can be used to find under- and overrepresentation of motifs (主題,基本花紋) (i.e. k-mers) • Help us to decide when an observed bias is significant For the case of 2-mers • Compare the observed probability N of the 2-mers with the one expected under a background model, typically a multi-nomial model. The ratio between the two quantities indicates how much a certain word deviates from the background model and is called the odds ratio; rxy N ( xy) N ( x) N ( y ) where N(xy) is the frequency of the dinucleotide xy, N(x) and N(y) denote the frequency of the nucleotide x and y respectively. rxy > 1 or rxy < 1 the xy nucleotide is considered of high or lower relative abundance compared with a random seq. Finding unusual DNA words AA and TA seems to be unusual • • Clearly dimer deviate from value 1 are unusually represented, although the amount of deviation needed to consider this as a significant patterns needs to be analyzed with the tools discussed later in this course. The dimer GG looks extremely infrequent in that table but this analysis reveals that this is not likely to be a significant bias because the nucleotide G is low in frequency to begin with. Finding unusual DNA words • the odds ratio can be generalized to a k-mers • For k-mers there are 4 to the k-th power, 4k, possible different patterns rk mers N (k mers) N (1) N (2)....N (k ) Frequent words in H. influenzae, The words AAAGTGCGGT and ACCGCACTTT both appearing more than 500 times. Biological relevance of unusual motifs • Frequent words may be due to repetitive elements • Rare motifs include binding sites for transcription factors • Words such as CTAG that have undesirable structural properties, because they lead to “kinking” of the DNA Virus vs. Bacteria • Words that are not compatible with the internal immune system of a bacterium. Bacterial cells can be infected by viruses, and I response they produce restriction enzymes, proteins that are capable of cutting DNA at specific nucleotide words, known as restriction sites. The nucleotide motifs recognized by restriction enzymes are under-represented in many viral genomes, so as to avoid the bacterial hosts’ restriction enzymes. Analyzing DNA seq. http://bioweb.pasteur.fr/intro-uk.html#dna Analyzing DNA seq. GC composition • • • Calculates the fractional GC content of nucleic acid sequences C+G content, C ≡ G has a triple bond GEECEE http://bioweb.pasteur.fr/seqanal/interfaces/geecee.html Counting long words in DNA seqs. • http://bioweb.pasteur.fr/intro-uk.html • Use AK003076 >gi|12833508|dbj|AK003076.1| Mus musculus adult male spleen cDNA, RIKEN fulllength enriched library, clone:0910001I10 product:DUTPASE homolog [Mus musculus], full insert sequence GGCTTTTTCCACGCCCGCCGCCATGCCCTGCTCGGAAGATGCCGCGGCCGTCT CTGCCTCCAAGAGGGCT CGAGCGGAGGATGGCGCTTCTCTGCGCTTCGTGCGGCTCTCGGAGCACGCCAC GGCGCCCACCCGCGGGT CCGCGCGCGCTGCCGGCTACGACCTATTCAGTGCCTATGATTATACAATATCAC CCATGGAGAAAGCCAT CGTGAAGACAGACATTCAGATAGCTGTCCCTTCTGGGTGCTATGGAAGAGTAGC TCCACGTTCTGGCTTG GCTGTAAAGCACTTCATAGATGTAGGAGCTGGTGTCATAGACGAGGATTACAGA GGAAACGTTGGGGTCG TGCTGTTTAACTTTGGGAAAGAGAAGTTTGAAGTGAAAAAAGGTGATCGGATTGC GCAGCTCATCTGTGA GCGGATTTCTTATCCAGACTTAGAGGAAGTGCAGACCCTGGATGACACCGAGAG AGGCTCAGGAGGCTTC GGCTCCACCGGGAAGAATTAGAACTTTGCTGGAAGTATCTCGCTGTTTCAACACT GGAAACCAGAAGCTC TAACTTCGGAAGCATTTGGTGTTCTAGGATGCAGGAAAGGAGACCTCGATCACAT CACGTTGGAACGATT CTGTTCCCTGGTTGAGGTCGCCTGTAAGTCTGCACTGTGAGCATGGCATTGACA TGCAGACTTGGTAAAA CCCAGGGTACAGTTAGATTTTTTGTTGTTGTTGTATTATTTAAATTATAGCCTTCCA AAAACTGTTTTTG ATCATAATTGCTGTATCATTTGTAATTTTTTTTAATCCAATAAAGTTGCTTTTAGC Analyzing DNA seq. composition Unusual words in different organisms or chromosomes • • • The measure rxy is suitable for a single seq.. In comparing seqs. from different organisms or chromosome account for the complementary anti-parallel structure of DNA modify rxy Reference: Burge, Campbell and Karlin (1992), PNAS, 89, 1358 Double helix Sa = 5’-ATCG....-3’ Sb = 5’-CAGT….-3’ SaI = 3’-TAGC….-5’ SbI = 3’-GTCA….-5’ • Let I = inverted complementary seq., • X = A, T, C, G • a, b = species • faX = freq. of X for species a Observation • Chargaff’s rule double strands total number of A/C = total number of T/G Unusual words in different organisms or chromosomes • • • Question: compare faX and fbX need to consider the union of S and SI why ? Let us consider the case in which one seq. with lots of A, and the other with lots of T in fact it has lots of A in the complementary seq. ! Sa = 5’-AAAACGT....-3’ Sb = 5’-TTTTCGA….-3’ SaI = 3’-TTTTGCA….-5’ SbI = 3’-AAAAGCT….-5’ • Need to symmetrize 對稱化 the nucleotide frequencies, take into account of complementary seq. • • I = inverted complement of X Define S* = S + SI fX* = (fX + fI(X))/2 * means the union, that is count the freq. of X in both strand and take the average f A* f A f I ( A) 2 f T f I (T ) f A fT f fA T 2 2 Work with single DNA only, no need to find out the complementary seq. fT* 2 f fT* f I*( A) * A similarly f C* f G* Compare the double strand quantity f*, that is compare f*aX and f*bX Unusual words in different organisms or chromosomes How about counting frequency of 2-mers ? * f GT f GT f I (GT ) 2 f AC f I ( AC ) 2 f GT f AC f AC f GT 2 2 * f AC * * f GT f AC in _ general f * XY f * I ( XY ) f XY f I ( XY ) 2 I = inverted complement of XY Unusual words in different organisms or chromosomes How about the odd ratio for 2-mers ? * GT r * f GT 2( f GT f AC ) * * f G fT ( f G f C )( fT f A ) similar _ for _ other _ 2 mers * * you _ can _ proof , rGT rAC in _ general , * rXY rI*( XY ) A conservative estimation of low and high odd ratios are less than 0.78 and higher than 1.22 respectively. Unusual words in different organisms or chromosomes How about the odd ratio for 3-mers ? * XYZ r * f XYZ f X* fY* f Z* * * * f XY fYZ f XNZ where, N _ is _ any _ nucleotide, and f * XYZ ( f XYZ f I ( XYZ ) ) 2 Compare statistical properties (1-mer and 2-mers) of human and chimp complete mitochondrial DNA NC_001807 and NC_001643 Human f A* f C* Human Chimp A (%) 30.86% 31.13% C (%) 31.33% 30.80% G (%) 13.16% 12.89% T (%) 24.66% 25.18% Chimp f A f I ( A) 30.86 24.66 2 31.33 13.16 2 2 22.245% 27.76% f A f I ( A) 31.13 25.18 28.155% 2 2 30.80 12.89 f C* 21.845% 2 f A* Both species have similar fX Compare statistical properties (1-mer and 2-mers) of human and chimp complete mitochondrial DNA second nucleotide second nucleotide A C G T A C G T first A 0.0962 0.0902 0.0483 0.0738 first A 1.0042 0.8812 1.1750 1.0293 nucl. C 0.0927 0.1074 0.0265 0.0868 nucl. C 0.9664 1.1537 0.5742 1.0861 G 0.0371 0.0432 0.0258 0.0254 G 0.9819 1.0328 1.5773 0.7321 T 0.0826 0.0725 0.0309 0.0606 T 1.0352 0.9857 0.9296 1.0019 * rXY rI*( XY ) Human Chimp 4x4 = 16, symmetric only need to compute 8 numbers not 16 ! second nucleotide symmetric A C G T first A 1 2 3 4 nucl. C 5 6 7 3 G 8 7 6 2 T 4 8 5 1 Compare statistical properties (1-mer and 2-mers) of human and chimp complete mitochondrial DNA * rXY * 2( f XY f I ( XY ) ) f XY * * f X fY ( f X f I ( X ) )( fY f I (Y ) ) 2( f XY f I ( XY ) ) / N 2 [( f X f I ( X ) )( fY f I (Y ) )] / N 2 2 N ( p XY pI ( XY ) ) ( p X pI ( X ) )( pY pI (Y ) ) where _ p _ denotes _ percentage _ of _ the _ word See my human and chimp k-mers Excel file Linguistic study of DNA sequences • Does genomic sequences have any resemblance to a natural language ? open question ! – Coding regions • Bacteria: no introns • Archaea: some introns, TATA boxes • Eukarya: many introns and exons, TATA boxes – Noncoding regions • Pseudogenes • Repetitive sequences – Mini-satellites – Micro-satellites – Alphabets, words, sentences – Coding regions words – Non-coding regions ? How to obtain inverted complementary seq. ? • • Prepare a FASTA format file Biological software web site http://bioweb.pasteur.fr/intro-uk.html#dna seq. tools EMBOSS program name: revseq Advanced revseq form output file : outseq.out GC content Factors contributing to the variation of GC content 1. Environmental temperature 2. Levels of methylation 3. Recent transposon activity (DNA jumps around) • Over stretches of hundreds of kb, GC content should vary by <1% as a result of random sampling • But most genomes show a bias ranging over as much as 30% ! GC content Figure. Distribution of GC content along human chromosome 1. GC content varies between 20% and 65% at several different levels of resolution, including for the entire 220Mb of chromosome 1 average over 1-Mb windows (top) and within just 1 Mb for 200-bp windows (bottoms). A gap in the IHFSE seq. can be seen at the 400-kb mark on the 1-Mb scale. GC content • • • • Karyotypic bands revealed by nuclear dyes such as Giemsa tend to correlate with GC content (dark bands being more AT-rich), possibly reflecting their propensity to coil into superstructure, but clearly other features of the DNA contribute to chromatin assembly. Chromosome is 2 ~ 3 cm long The 46 chromosomes (over 1m long) are packed inside the nucleus with a size of 0.001 cm ! Amazing !! CpG dinucleotides are underrepresented in mammalian genomes overall, but cluster as CpG islands between 0.5 and 2 kb in length that are significantly enriched just upstream of genes. hsa-mir-639 UCSC database http://genome.ucsc.edu Finding internal repeats in DNA seqs. • tandem repeats, inverted repeat • repeats often involved in genome rearrangements or regulatory mechanisms of gene expression • tools result depend on scoring system and ranking • Dot-plot approach http://arbl.cvmbs.colostate.edu/molkit/ Finding internal repeats in DNA seqs. TF sequence Transcription factor, TFIIIA for X.laevis, K02938 >gi|214818|gb|K02938.1|XELTFIIIA X.laevis 5S RNA gene transcription factor (TFIIIA) mRNA, complete cdsGAATTCCGGAAGCCGAGGGCTGTTCAGTTGCTGAAGGAGAGATGGGAGAGAAGGCGCTGCCGGTGGTGTATAAGCGGTACATCTGCTCTT TCGCCGACTGCGGCGCTGCTTATAACAAGAACTGGAAACTGCAGGCGCATCTGTGCAAACACACAGGAGAGAAACCATTTCCATGTAAGGAAG AAGGATGTGAGAAAGGCTTTACCTCGCTTCATCACTTAACCCGCCACTCACTCACTCATACTGGCGAGAAAAACTTCACATGTGACTCGGATGG ATGTGACTTGAGATTTACTACAAAGGCAAACATGAAGAAGCACTTTAACAGATTCCATAACATCAAGATCTGCGTCTATGTGTGCCATTTTGAGA ACTGTGGCAAAGCATTCAAGAAACACAATCAATTAAAGGTTCATCAGTTCAGTCACACACAGCAGCTGCCATACGAATGTCCTCATGAAGGCTG TGACAAGCGGTTTTCTTTGCCTTCCCGTTTAAAACGTCATGAAAAAGTCCATGCAGGCTATCCCTGCAAAAAGGATGATTCTTGCTCATTTGTGG GAAAGACTTGGACATTATACTTGAAACACGTGGCAGAATGCCATCAGGACCTAGCAGTATGTGATGTGTGTAATCGAAAATTCAGGCACAAAGA TTACTTGAGGGATCATCAGAAAACTCACGAAAAAGAGCGAACTGTGTATCTCTGCCCTCGAGATGGCTGTGACCGCTCCTATACCACTGCATTC AATCTTAGAAGCCATATACAATCATTTCATGAGGAACAGAGACCTTTTGTTTGTGAGCATGCTGGCTGCGGGAAATGCTTTGCAATGAAAAAAAG CCTAGAAAGACATTCAGTTGTACATGATCCAGAGAAGAGGAAGCTGAAGGAGAAATGCCCTCGCCCAAAGAGAAGCCTGGCCTCTCGCCTCAC TGGATACATACCCCCCAAGAGCAAAGAAAAAAATGCATCCGTTTCGGGAACAGAAAAGACTGATTCACTTGTGAAAAATAAGCCCTCTGGCACT GAAACAAATGGCTCATTGGTTCTAGATAAATTAACTATACAATAATATAAGAAAACATTTAAATTTATTTTTTTATTTGTTAAAATTGCCCTCAGGAT GGTTAACCCATATTTAGTGTGGGTTTTTTCTTTTTTTACAGCTTTAATTCATTTTTTTTCGGCTATAACAAAAGGAATCTGTTCTAGACGCATGATT TGTTTTATGAACTGCAGTATTGGCCATGCCTACAGGTAAAGGCACAGTGTTAATGGCTACATACCTCTTCTACCCCATGTTTGCTATTAAAAGTG AGGTGCAGCAGCCACTGGTCTGTTTATTTACAATACATTCATTTAGTAAGACTCTGTATTCATTTTCAAAAGAATCACTAAGGGAATGTGCAAAAT TGTTATCACTCTACTGTAAACACAAATGTACTGCTTGCACCCTGTTGGTGGGGCTTTTTTTGGGGAGGTTGACTGACCCTGTTTTTTTTTTAACG GAATTC Rosalind Franklin The Dark Lady of DNA (1920~1958) By Brenda Maddox • Maddox tells her readers, in their Nobel acceptance speeches in 1962 Watson and Crick made no mention of Rosalind Franklin at all. It was only Wilkins who “uttered” Franklin’s name, mentioning her as one of two people (the other being Alex Stokes), who “made very valuable contributions to the X-ray analysis.” • Watson, Francis Crick, and Maurice Wilkins. The latter three received a Nobel Prize for their discovery in 1962. Franklin was ignored. • For more about the story read http://www.humanistperspectives.org/issue151/books.html Sodium deoxyribose nucleate from calf thymus, Structure B, Photo 51, taken by Rosalind Franklin and R G Gosling, 2 May 1952, with Linus Pauling’s holographic annotations to the right of the photo. This photo shows the double helices structure of DNA with a separation of 20A. Discovery of the double helix structure of DNA The discovery is based on three pieces of works 1. Chargaff’s rule (discovered in 1949) • Chargaff – an Austrian-American biochemist • total number of A/C = total number of T/G 2. Linus Pauling - discover the alpha-helix structure of protein 3. X-ray diffraction pattern of crystal – Did by Rosalind Franklin – Crystal X-ray diffraction – by William Bragg and his son William Junior Bragg http://www.virtualsciencefair.org/2004/mcgo4s0/p ublic_html/t2/dna.html http://post.queensu.ca/~forsdyke/bioinfo1.htm Erwin Chargaff (1905 -2002) Discovery of the double helix structure of DNA Linus Pauling • Nobel Prize in Chemistry in 1954 • Nobel Peace Prize in 1963 • who championed the use of Vitamin C, • live to be 93 (he died in 1994) • nature was a marvelous 令人驚異的 contrivance 發明,想出的辦法 composed of molecules assembled by the Great Mechanic • http://www.utoronto.ca/jpolanyi/public_affairs/pu blic_affairs4i.html • Watson and Crick conjectured that DNA is made up of two, three or four helices, but their model did not fit the X-ray data. • They stop their work for almost one year • Crick continued his Ph.D thesis, Crick worked on his tobacco virus research • So as Pauling, he proposed the three helices model of DNA. • They were wrong, because they did not know the complimentary principle yet. Discovery of the double helix structure of DNA • Watson and Crick also proposed DNA is made up of two exactly same helix with the same nucleotide on the opposite helix wrong • Jerry Donohue, a visiting chemist at Cambridge from Cal-Tech, asserted that the shape of those DNA bases ought to be the keto form and not the enol form, as the textbooks of the day asserted. • Armed now with the memory of Franklin’s clear photograph 51, this next to-last-step in the emergence of the final model was absolutely crucial. Donohue (1920 – 1985) Discovery of the double helix structure of DNA • “‘The point was important,’ [Crick] said, ‘because if the unit cell is strictly C2, one must have the DNA chains in pairs, running in opposite directions.’” • This scientific point was crucial for Watson and Crick. In separate papers published that same year, Franklin had said that “C2 is the only space group possible.” Why, Maddox wonders, had Watson or Crick failed to mention the importance of this in either of their Nature papers of 1953? • A physicist, he worked with John Randall in the late 1930s on the development of radar, moving to the USA during World War II to work on the Manhattan project. After the War he joined Randall at King's College London and with Rosalind Franklin began an investigation into the structure of DNA. Watson (1928-) and Crick (1916-2004) Maurice Wilkins (1916-2004) Diffraction of X ray by crystal • Max von Laue who was awarded the Nobel prize for physics in 1914 "for his discovery of the diffraction of Xrays by crystals". His collaborators Walter Friedrich and Paul Knipping took the picture on the right in 1912. • http://cxpi.spme.monash.edu.au /xray_history.htm Max von Laue (1897-1960) A beam of X-rays is scattered into a characteristic pattern by a crystal. In this case it is copper sulphate. Diffraction of X ray by crystal • Sir William Lawrence Bragg, Australian born British physicist, won the Nobel prize (1915) with his father William Henry Bragg "for their services in the analysis of crystal structure by means of Xrays“, when he was only 25 years old. William Henry Bragg William Lawrence Bragg (1862-1942) (1890-1971) Bragg’s law of diffraction