Talk on identification of causal variants given to graduate students at the Universidade Federal de Viçosa in Viçosa, MG, Brasil, on September 9, 2014. It discusses work in my lab to identify causal variants associated with simple and complex modes of inheritance using SNP genotyping and next generation sequencing.
This presentation describes recent changes to the national genetic evaluation system, as well as new research undertaken by AGIL scientists. Topics covered include the 2014 genetic base change, updates to the lifetime net merit selection index, and introduction of the grazing merit index, and the redefinition of daughter pregnancy rate. New research on the use of gene content to predict polled status, and statistical models for accommodating genotype-by-environment interactions also are described.
The national genetic evaluation program
for dairy cattle in the United States is described. Topics include an historical overview of traits and statistical methodology, the structure of the contemporary dairy genetics industry, and the implementation of genomic selection.
If we would see further than others: research & technology today and tomorrowJohn B. Cole, Ph.D.
The dairy industry has historically been an early adopter of technology. Rapid advances in computing and wireless systems have enabled a new era of data-intensive farming. This presentation reviews current and emerging technologies, and places them in context with the modern dairy enterprise. Research opportunities provided by the growth of this new technology are described, and the future of genomics in dairy research is discussed.
Talk on the genetic and genomic evaluation system for US dairy cattle made to scientists at Embrapa Gado de Leite in Juiz de Fora, MG, Brasil, on September 10, 2014.
Using genotypes to construct phenotypes for dairy cattle breeding programs an...John B. Cole, Ph.D.
Modern dairying uses sophisticated data collection systems to maximize farm profitability. This has traditionally included information on cows and their environments, and now commonly includes genotype information from high-density single nucleotide polymorphism (SNP) panels. The US national database alone contains genotypes for 924,543 bulls and cows as of March 23, 2015, and many other countries are also genotyping animals. As the data continue to grow, the prospect of using genotypes to construct phenotypes directly, instead of measuring phenotypes on animals, becomes more attractive. There are many applications for this genomic information other than the prediction of breeding values. A notable recent application is the use of haplotypes in combination with next-generation sequencing data to identify causal variants associated with recessives. The methodology for identifying recessive haplotypes by searching for a deficit of homozygotes was first used in combination with sequence data to identify the causal variant (APAF1) associated with the HH1 haplotype. The US currently tracks 24 recessive haplotypes in four cattle breeds, and thanks to the work of several teams around the world the causal variants for 17 of them are known. The haplotypes include lethal recessive conditions, such as brachyspina, as well as hair coat color and polledness. There is growing interest in the latter to improve animal welfare and increase economic efficiency, but the polled haplotype has a very low frequency (0.41%, 0.93%, and 2.22% in Brown Swiss, Holstein, and Jersey, respectively). Increasing haplotype frequency by index selection requires known status for all animals. Gene content (GC) for non-genotyped animals was computed using records from genotyped relatives. Prediction accuracy was checked by comparing polled status from recessive codes and animal names to GC for 1,615 non-genotyped Jerseys with known status. 97% (n = 675) of horned animals were correctly assigned GC near 0, and 3% (n = 19) were assigned GC near 1. Heterozygous polled animals had GC near 0 (52%, n = 474) and near 1 (47%; n = 433), although 3 animals were assigned a GC near 2. All homozygous polled animals (n = 11) were assigned GC near 2. Genotype information can also be combined with other data, such as milk spectral data, to predict phenotypes for traits that are expensive or difficult to measure directly. These data can be used for precision farm management, including early culling decisions, monitoring of animals at risk for health problems, and identification of efficient and inefficient cows. The most substantial challenge faced by many dairy managers will be the effective use of the new phenotypes that now are available.
This presentation describes recent changes to the national genetic evaluation system, as well as new research undertaken by AGIL scientists. Topics covered include the 2014 genetic base change, updates to the lifetime net merit selection index, and introduction of the grazing merit index, and the redefinition of daughter pregnancy rate. New research on the use of gene content to predict polled status, and statistical models for accommodating genotype-by-environment interactions also are described.
The national genetic evaluation program
for dairy cattle in the United States is described. Topics include an historical overview of traits and statistical methodology, the structure of the contemporary dairy genetics industry, and the implementation of genomic selection.
If we would see further than others: research & technology today and tomorrowJohn B. Cole, Ph.D.
The dairy industry has historically been an early adopter of technology. Rapid advances in computing and wireless systems have enabled a new era of data-intensive farming. This presentation reviews current and emerging technologies, and places them in context with the modern dairy enterprise. Research opportunities provided by the growth of this new technology are described, and the future of genomics in dairy research is discussed.
Talk on the genetic and genomic evaluation system for US dairy cattle made to scientists at Embrapa Gado de Leite in Juiz de Fora, MG, Brasil, on September 10, 2014.
Using genotypes to construct phenotypes for dairy cattle breeding programs an...John B. Cole, Ph.D.
Modern dairying uses sophisticated data collection systems to maximize farm profitability. This has traditionally included information on cows and their environments, and now commonly includes genotype information from high-density single nucleotide polymorphism (SNP) panels. The US national database alone contains genotypes for 924,543 bulls and cows as of March 23, 2015, and many other countries are also genotyping animals. As the data continue to grow, the prospect of using genotypes to construct phenotypes directly, instead of measuring phenotypes on animals, becomes more attractive. There are many applications for this genomic information other than the prediction of breeding values. A notable recent application is the use of haplotypes in combination with next-generation sequencing data to identify causal variants associated with recessives. The methodology for identifying recessive haplotypes by searching for a deficit of homozygotes was first used in combination with sequence data to identify the causal variant (APAF1) associated with the HH1 haplotype. The US currently tracks 24 recessive haplotypes in four cattle breeds, and thanks to the work of several teams around the world the causal variants for 17 of them are known. The haplotypes include lethal recessive conditions, such as brachyspina, as well as hair coat color and polledness. There is growing interest in the latter to improve animal welfare and increase economic efficiency, but the polled haplotype has a very low frequency (0.41%, 0.93%, and 2.22% in Brown Swiss, Holstein, and Jersey, respectively). Increasing haplotype frequency by index selection requires known status for all animals. Gene content (GC) for non-genotyped animals was computed using records from genotyped relatives. Prediction accuracy was checked by comparing polled status from recessive codes and animal names to GC for 1,615 non-genotyped Jerseys with known status. 97% (n = 675) of horned animals were correctly assigned GC near 0, and 3% (n = 19) were assigned GC near 1. Heterozygous polled animals had GC near 0 (52%, n = 474) and near 1 (47%; n = 433), although 3 animals were assigned a GC near 2. All homozygous polled animals (n = 11) were assigned GC near 2. Genotype information can also be combined with other data, such as milk spectral data, to predict phenotypes for traits that are expensive or difficult to measure directly. These data can be used for precision farm management, including early culling decisions, monitoring of animals at risk for health problems, and identification of efficient and inefficient cows. The most substantial challenge faced by many dairy managers will be the effective use of the new phenotypes that now are available.
Genomic selection and systems biology – lessons from dairy cattle breedingJohn B. Cole, Ph.D.
Presentation made to the staff of Keygene, NV, in Wageningen, The Netherlands.
(I don't know what the problem is with the template here. It looks fine if you use a dark background.)
ESTIMATES OF HERITABILITY AND BREEDING VALUES FOR GROWTH TRAITS IN MADURA CAT...UniversitasGadjahMada
The study is aimed to estimate the heritability for growth traits at weaning and yearling age, and to determine the breeding values for body weight in Madura cattle, reared in Pamekasan Regency. One hundred and four (194) calves were collected for body weight (BW), chest circumference (CC), body length (BL), withers height (WH) at weaning and yearling age. Paternal half-sib correlation method was used for heritability estimates. As a result, the estimates of heritability for growth traits in both weaning and yearling age were categorized in medium to high. The heritability estimates for BW, CC, BL, and WH in weaning age were 0.33±0.30, 0.35±0.31, 0.66±0.37 and 0.53±0.34, respectively. In yearling age, heritability estimates for BW, CC, BL, and WH were obtained to be 0.66±0.43, 0.71±0.67, 0.38±0.58, and 0.36±0.57, respectively. The top 10 sires based on estimated breeding value for body weight were also obtained, with a range value from 80.70 to 88.35 in weaning age, and from 101.86 to 118.55 in yearling age. It was found that the analyzed growth traits may be taken into consideration as selection criteria in Madura cattle.
This is the second presentation from a six part webinar series on the National Sheep Improvement Program (NSIP). The presenter is Dr. Ken Andries from Kentucky State University. The date of the presentation was May 8, 2014.
Dr. Jeff Zimmerman - Things your epidemiologist never told your about surveil...John Blue
Things your epidemiologist never told your about surveillance - Dr. Jeff Zimmerman, Veterinary Diagnostic Laboratory, Iowa State University, from the 2017 North American PRRS/National Swine Improvement Federation Joint Meeting, December 1‐3, 2017, Chicago, Illinois, USA.
More presentations at http://www.swinecast.com/2017-north-american-prrs-nsif-joint-meeting
Estimation of Stillbirth (Co)variance Components and Development of a Calving...John B. Cole, Ph.D.
A national evaluation for stillbirth (SB) for Holstein will be implemented in August 2006. (Co)variance components were required. A calving ability index (CA$) which includes SB and calving ease (CE) was developed.
This is the 5th and final presentation in a 5-part webinar series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
The hunt for a functional mutation affecting conformation and calving traits ...John B. Cole, Ph.D.
Presentation from the 10th WCGALP meeting in Vancouver describing our research to identify the causal variant associated with calving and conformation (body shape and size) traits in Holstein cattle.
This is the 4th webinar in a five part series on Breeding Better Sheep & Goats. This presentation entitled "Performance Evaluation" was given by Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
This was the third presentation in a 6-part webinar series on the National Sheep Improvement Program (NSIP). The presenter was Cody Hiemke, a Shropshire breeder from Wisconsin. The presentation was given on May 15, 2014.
Genomic selection and systems biology – lessons from dairy cattle breedingJohn B. Cole, Ph.D.
Presentation made to the staff of Keygene, NV, in Wageningen, The Netherlands.
(I don't know what the problem is with the template here. It looks fine if you use a dark background.)
ESTIMATES OF HERITABILITY AND BREEDING VALUES FOR GROWTH TRAITS IN MADURA CAT...UniversitasGadjahMada
The study is aimed to estimate the heritability for growth traits at weaning and yearling age, and to determine the breeding values for body weight in Madura cattle, reared in Pamekasan Regency. One hundred and four (194) calves were collected for body weight (BW), chest circumference (CC), body length (BL), withers height (WH) at weaning and yearling age. Paternal half-sib correlation method was used for heritability estimates. As a result, the estimates of heritability for growth traits in both weaning and yearling age were categorized in medium to high. The heritability estimates for BW, CC, BL, and WH in weaning age were 0.33±0.30, 0.35±0.31, 0.66±0.37 and 0.53±0.34, respectively. In yearling age, heritability estimates for BW, CC, BL, and WH were obtained to be 0.66±0.43, 0.71±0.67, 0.38±0.58, and 0.36±0.57, respectively. The top 10 sires based on estimated breeding value for body weight were also obtained, with a range value from 80.70 to 88.35 in weaning age, and from 101.86 to 118.55 in yearling age. It was found that the analyzed growth traits may be taken into consideration as selection criteria in Madura cattle.
This is the second presentation from a six part webinar series on the National Sheep Improvement Program (NSIP). The presenter is Dr. Ken Andries from Kentucky State University. The date of the presentation was May 8, 2014.
Dr. Jeff Zimmerman - Things your epidemiologist never told your about surveil...John Blue
Things your epidemiologist never told your about surveillance - Dr. Jeff Zimmerman, Veterinary Diagnostic Laboratory, Iowa State University, from the 2017 North American PRRS/National Swine Improvement Federation Joint Meeting, December 1‐3, 2017, Chicago, Illinois, USA.
More presentations at http://www.swinecast.com/2017-north-american-prrs-nsif-joint-meeting
Estimation of Stillbirth (Co)variance Components and Development of a Calving...John B. Cole, Ph.D.
A national evaluation for stillbirth (SB) for Holstein will be implemented in August 2006. (Co)variance components were required. A calving ability index (CA$) which includes SB and calving ease (CE) was developed.
This is the 5th and final presentation in a 5-part webinar series on Breeding Better Sheep & Goats. The presenter is Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
The hunt for a functional mutation affecting conformation and calving traits ...John B. Cole, Ph.D.
Presentation from the 10th WCGALP meeting in Vancouver describing our research to identify the causal variant associated with calving and conformation (body shape and size) traits in Holstein cattle.
This is the 4th webinar in a five part series on Breeding Better Sheep & Goats. This presentation entitled "Performance Evaluation" was given by Susan Schoenian, University of Maryland Extension Sheep & Goat Specialist.
This was the third presentation in a 6-part webinar series on the National Sheep Improvement Program (NSIP). The presenter was Cody Hiemke, a Shropshire breeder from Wisconsin. The presentation was given on May 15, 2014.
De novo reciprocal translocation t(4;20) (q28;q11) associated in a child with...Apollo Hospitals
The common cause of mental impairment and the wide range of physical abnormalities is balanced chromosome rearrangement. As such, it is difficult to interpret, posing as a diagnostic challenge in human development. We present a unique case report with a denovo autosomal-balanced reciprocal translocation involving chromosomal regions 4q and 20q.The etiology of the translocation, i.e. 46,XX,t (4;20)(q28;q11) was detected by conventional high-resolution Giemsa-Trypsin-Giemsabanding technique. Parents non-consanguineous, with 2 healthy children. To the best of our knowledge this is the first case reported so far with the balanced reciprocal translocation involving 4q and 20q associated with the delayed milestone development.
Genetic Evaluation of Stillbirth in US Holsteins Using a Sire-maternal Grands...John B. Cole, Ph.D.
My talk on the implementation of a national genetic evaluation for stillbirth at the 8th World Congress on Genetics Applied to Livestock Production in Belo Horizonte, Brazil.
20150918 E. Pompilii - Microarray in diagnosi prenatale: la complessità della...Roberto Scarafia
Eva Pompilii, MD
Genetic Counselor , TOMA Advanced Biomedical Assays, S.p.A.,
Gynepro Medical Bologna, Policlinico S.Orsola Malpighi Bologna
• OBJECTIVES:
At present, a precise guideline establishing chromosome microarray analysis (CMA) applications and platforms in the prenatal setting does not exist. The actual controversial
question is whether CMA technologies can or should shortly replace the standard karyotype in prenatal diagnosis practice
• CONCLUSIONS:
Presently CMA analysis can be considered a second-tier diagnostic test to be used after a standard karyotype in selected group of pregnancies, such as those with single
(apparently isolated) or multiple US fetal abnormalities, with de novo chromosomal rearrangements, even if apparently balanced, and those with supernumerary markers chromosomes
An updated version of lifetime net merit incorporating additional fertility t...John B. Cole, Ph.D.
The slides for my upcoming talk on the 2014 revision of the lifetime net merit selection index to be presented at the 2014 ASAS-ADSA-CSAS Joint Annual Meeting in Kansas City, MO.
Genomic evaluation of low-heritability traits: dairy cattle health as a modelJohn B. Cole, Ph.D.
Genetic selection has been very successful when applied to traits of moderate to high heritability, but progress has been slow for traits with low heritabilities. The problem is further compounded when novel traits are considered because data needed to calculate high-reliability PTA generally are not available. A combination of producer-recorded health event data and SNP genotypes may permit the routine calculation of PTA with reasonable reliabilities for health traits.
Poster presented at the 5th International Symposium on Animal Functional Genetics in Guaruja, Brazil, in 2014.
PyPedal, an open source software package for pedigree analysisJohn B. Cole, Ph.D.
PyPedal is an open source package written in the Python programming language that provides high-level tools for manipulating pedigrees. The goal is to provide expressive tools for exploratory data analysis. This was a poster presented at the 2012 European Association for Animal Production meeting in Bratislava.
Presentation describing how haplotypes can be used to make on-farm management decisions made at the 2012 European Association for Animal Production meeting in Bratislava.
What can we do with dairy cattle genomics other than predict more accurate br...John B. Cole, Ph.D.
Presentation on applications of genomic information in additional to estimation of breeding values made to the Department of Animal Science at North Carolina State University at 2010.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Using genotyping and whole-genome sequencing to identify causal variants associated with complex phenotypes
1. 2014
Using genotyping and whole-genome
causal variants associated with
complex phenotypes
J.B. Cole
sequencing to identify
Animal Genomics and Improvement Laboratory
Agricultural Research Service, USDA
Beltsville, MD
john.cole@ars.usda.gov
2. Overview
l What have we learned about causal
variants?
l What do we know about chromosome 18?
l How can sequencing help us
learn more?
l What did we learn when we
looked at the data?
l How did we approach these
new challenges?
Source: Ianuzzi (Chromosome
Res., 4:448–456)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (2) Cole
3. Genotypes evaluated
400,000
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
Jun
A
O
Jan
Young imputed
Old imputed
Female Young <50K
Male Young <50K
Female Old <50K
Male Old <50K
Female Young >=50K
Male Young >=50K
Female Old >=50K
Male Old >=50K
F
A
M
J
J
A
S
O
N
D
Jan
F
M
A
M
J
J
A
S
O
N
D
Jan
F
M
A
M
J
J
A
S
O
N
D
Jan
F
M
A
M
J
J
A
S
Animals genotyped (no.)
2009 2010 2011 2012 2013
Evaluation date
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (3) Cole
4. Genotypes received since July 2013
Breed Female Male
All
animals
%
female
Ayrshire 1,359 229 1,588 86
Brown Swiss* 892 6,253 7,145 12
Holstein 172,956 31,657 204,613 85
Jersey** 26,434 4,804 31,238 85
All 201,641 42,943 244,584 82
*Includes >5,000 bulls added from Interbull in June 2014
**Includes 1,068 Danish bulls added in November 2013
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (4) Cole
5. Phenotypes may come from genotypes
Name Chrome Location (Mbp) Freq of minor haplotype Gene Name
HH1 5 63.15 1.92 APAF1
HH2 1 94.8 to 96.6 1.66 unknown
HH3 8 95.41 2.95 SMC2
HH4 1 1.27 0.37 GART
HH5 9 92 to 94 2.22 unknown
JH1 15 15.70 12.10 CWC15
BH1 7 42.8 to 47.0 6.67 unknown
BH2 19 10.6 to 11.7 7.78 unknown
AH1 17 65.86 to 66.16 11.80 unknown
For a complete list, see: http://aipl.arsusda.gov/reference/recessive_haplotypes_ARR-G3.html.
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (5) Cole
6. Success – APAF1 (HH1)
l APAF1 - Bos taurus apoptotic peptidase activating factor 1
w ATP binding factor
l Gene expression for APAF1 in murine development begins
between 7 and 9 d in heart, mesenchyme, periderm, and primitive
intestine (Muller et al., 2005)
l Gene knockout of APAF1 in mice leads to embryonic lethality
(Muller et al., 2005)
w Proteins required for this
pathway/cascade are important
for neural tube closure in vivo
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (6) Cole
7. Success – CWC15 (JH1)
Will and Lührmann. 2011.
Spliceosome structure and
Function. Cold Spring
Harb Perspect Biol.
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (7) Cole
8. There’s still a gap to bridge
l Causal variants for Mendelian recessives
are sometimes easy to identify
l Identification of causal variants for QTL
associated with quantitative traits is
much more complex
w It can be done (e.g., DGAT1)
w Does genomics and next generation
sequencing make that easier?
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (8) Cole
9. A simple strategy doesn’t always work
l Compute SNP effects for trait of interest
l Look for peaks
l Perform bioinformatics on regions under
interesting peaks
w NCBI/Ensembl
w Bovine Gene Atlas
w Bovine QTLdb
l This doesn’t always work…as we’ll see!
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (9) Cole
10. Introduction to chromosome 18
l Several studies (Kuhn et al., 2003; Cole
et al., 2009; Seidenspinner et al., 2009)
have reported QTL on BTA 18 associated
with dystocia
l Bioinformatic analysis using SNP data has
not identified the causal variant
l Next generation sequencing (NGS) has
recently been used to find causal
variants for novel recessive disorders
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (10) Cole
11. Chromosome 18 is different
l Markers on chromosome 18 have large effects
on several traits:
w Dystocia and stillbirth: sire and daughter
calving ease and sire stillbirth
w Conformation: rump width, stature,
strength, and body depth
w Efficiency: longevity and net merit
l Large calves contribute to reduced cow
lifetimes and decreased profitability
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (11) Cole
12. Marker effects for dystocia complex
AR-BFG-`GS-109285
ARS-BFGL-NGS-109285
Cole et al., 2009 (J. Dairy Sci. 92:2931–2946)
Source: https://www.cdcb.us/Report_Data/Marker_Effects/marker_effects.cfm?Breed=HO
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (12) Cole
13. Correlations in dystocia complex
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (13) Cole
14. The QTL also affects gestation length
Maltecca et al., 2011 (Animal Genet. 42:585-591)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (14) Cole
15. The dystocia complex
l The key marker is ARS-BFGL-NGS-109285 at
(rs109478645 ) 57,589,121 Mb on BTA18
l Intronic to Siglec-12 (sialic acid binding Ig-like
lectin 12)
l Recent results indicate effects on gestation
length (Maltecca et al., 2011) and calf birth
weight (Cole et al., 2014), as well as calving
traits (Purfield et al., 2014)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (15) Cole
16. Where did it come from?
Source: http://bit.ly/VsIups
Source: https://www.cdcb.us/CF-queries/Bull_Chromosomal_EBV/bull_chromosomal_ebv.cfm?
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (16) Cole
17. Who popularized it?
57,861 daughters
>2 million granddaus
Source: http://bit.ly/1BkTTsE.
Maternal haplotype from
Ivanhoe
Source: https://www.cdcb.us/CF-queries/Bull_Chromosomal_EBV/bull_chromosomal_ebv.cfm?
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (17) Cole
18. This is a gene-rich region
Discussed on Tuesday
(Abstract 288, Mao).
http://useast.ensembl.org/Bos_taurus/Location/View?r=18%3A57583000-57587000
http://www.ncbi.nlm.nih.gov/gene?cmd=Retrieve&dopt=Graphics&list_uids=618463
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (18) Cole
19. Copy number variants are present
Hou et al. 2011 (BMC Genomics,12:127)
l ARS-BFGL-NGS-109285 is flanked by CNV
w There’s a loss and a gain to the left (8
SNP region)
w There’s a gain to the right (10 SNP
region)
l This can result in assembly problems
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (19) Cole
20. What if we look at a different trait?
l Cole et al. (2009) proposed the following
mechanism:
w Siglec-12 may sequester circulating
leptin
w This increases gestation length
w Calf birth weight (BW) is higher
because of increased gestation length
w Higher BW is associated with dystocia
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (20) Cole
21. We don’t have birth weight data
l Birth weights are not routinely recorded
in the US
l Collaborated with Hermann Swalve’s
group to develop a selection index
prediction of BW PTA
l Performed GWAS and gene set
enrichment analysis to search for
interesting associations (Cole et al.,
2014, JDS 97:3156-3172)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (21) Cole
22. GWAS for birth weight PTA
h
Cole et al., 2014 (J. Dairy Sci., 97:3156–3172)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (22) Cole
23. Are we measuring anything new?
l Identified a SNP on BTA16 intronic to
LHX4, which is associated with cow body
weight and length (Ren et al., 2010, Mol.
Bio. Reprod., 37:417-422).
l 4 SNP in the QTL region on BTA 18 had
large effects
l Several other SNP with large effects
intronic or adjacent to genes with
unknown functions
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (23) Cole
24. KEGG pathways for birth weight
What does
regulation of
the actin
cytoskeleton
have to do with
birth weight in
cattle?
That is, do
these results
make sense?
Maybe…these
pathways may
be involved in
establishment
& maintenance
of pregnancy,
as well as
coordination of
growth and
development.
Cole et al. (2014)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (24) Cole
25. Pedigree & haplotype design
Arlinda Chief
AA, SCE: 8
Chief
AA, SCE: 7
MGS
Arlinda Rotate
AA, SCE: 8
δ = 10 Tradition
Melwood
Aa, SCE: 8
CMV Mica
Aa, SCE: 14
Jed
Aa, SCE: 15
Leduc
Aa, SCE: 18
Aa, SCE: 10
MGS
These bulls carry
the haplotype with
the largest, negative
effect on SCE:
Rockman Ivanhoe
Aa, SCE: 6
Delegate
Aa, SCE: 15
Laramie
aa, SCE: 15
Couldn’t obtain DNA:
Combination
??, SCE: 7
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (25) Cole
26. How many scientists does it take…
You just missed his talk
(Abstract 164, Bickhart
et al.)!
You went to her
poster on Tuesday
(Abstract 799,
Cooper et al.), right?
He’s back in
Maryland,
working.
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (26) Cole
27. Sequencing coverage
Bull name SCE1 Genotype2 Total reads Coverage
Pawnee Farm Arlinda Chief 7 AA 333,628,731 12.03
Glendell Arlinda Chief 8 AA 981,726,824 35.41
Sweet Haven Tradition 10 Aa 390,387,538 14.01
Arlinda Rotate 8 AA ~476,000,000 17.00
Arlinda Melwood 8 Aa ~448,000,000 16.00
Juniper Rotate Jed 15 Aa 656,190,604 23.66
CMV Mica 14 Aa 433,353,161 15.63
Lystel Leduc 18 Aa 767,440,677 27.68
Willow-Farm Rockman Ivanhoe 6 Aa 195,769,690 7.06
Cass-River Select Delegate 15 Aa 377,380,110 13.61
Wedgwood Laramie 15 aa 371,477,172 13.39
1Predicted transmitting ability (PTA) for sire calving ease, the percentage of offspring born with difficulty. Small
values are desirable and large values are undesirable.
2The genotype of the tag SNP for the QTL, where “A” and “a” are the major and minor alleles, respectively.
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (27) Cole
28. Results from Illumina sequencing
l Data analyzed using paired-end read
alignments and split-read mapping
l Portions of two exons and a connecting
intron within the Ig-like protein domains
may have been duplicated
l Some heterozygotes with desirable SCE
also have deletions near the N-terminal
end of the protein
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (28) Cole
29. Possible assembly problem on BTA18
This could be a GC-rich region (bias in
Illumina chemistry).
More reads than expected may align
here because repetitive elements were
combined during assembly.
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (29) Cole
30. Genome assembly (simplified)
Reads must be assembled into chromosomes
Assembly is a computational process (Liu et al., 2009; Zimin et al., 2009)
This process is imperfect – repetitive regions are hard to assemble correctly!
Sometimes, this…
should be this.
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (30) Cole
31. Can it be corrected using long reads?
l BTA18 genomic DNA extracted
from CHORI-240 BAC library
(L1 Domino 99375) at AGIL
Source: Pacific Biosystems
l Sequencing libraries constructed at USDA
MARC, pooled, and run on PacBio RS II
BAC ID Insert size (bp) Start End
CH240-389P14 174,682 56,954,654 57,129,335
CH240-234E12 178,618 57,058,248 57,236,865
CH240-280L6 175,831 57,092,237 57,268,067
CH240-34N7 158,841 57,129,383 57,288,223
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (31) Cole
32. Processing of PacBio reads
l BAC DNA was pooled at MARC to have
enough material to construct a
sequencing library
l Reads were assembled into contigs using
HGAP in SMRTanalysis v2.2.0
l 44 contigs with an N50 of 31 kb were
constructed
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (32) Cole
33. Analysis of alignments
l PacBio contigs aligned against UMD3.1
contigs using MUMmer 3.0
l Short (Illumina) reads aligned against
PacBio contigs using BWA 0.7.5a-r405
l Paired-end discordancy interrogated
using custom scripts (Bickhart,
unpublished data)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (33) Cole
34. Alignment of BAC contigs with UMD3.1
A line with a slope of 1 indicates that a segment
is conserved between the two sequences – this
contig is almost identical between our PacBio
assembly and the UMD3.1 reference assembly.
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (34) Cole
35. Discordancy analysis
l Illumina reads aligned w/PacBio contigs
l Reads with lengths ±4σ were counted
l Discordancies may indicate
w Problems in the PacBio assembly
w The presence of repetitive elements
w Structural differences between the
Holstein and Hereford (unlikely)
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (35) Cole
36. DNA in PacBio and not in UMD3.1
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
Reads map to PacBio and UMD3.1 contigs.
~10 kbp of DNA in PacBio contig that doesn’t map to
UMD3.1!
Reads map to PacBio and UMD3.1—
ARS-BFGL-NGS-109285 is placed here.
0 50000 100000 150000 200000 250000 300000
scf7180000000136|quiver
REF
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (36) Cole
37. There are clearly assembly problems
25000
20000
15000
PacBio sequence duplicated
10000
5000
0
PacBio sequence duplicated
on UMD3.1 contig
on UMD3.1 contig
0 20000 40000 60000 80000 100000 120000
scf7180000000103|quiver
REF
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (37) Cole
38. What have we learned?
l This is more complex than SNP
genotyping, and unsuccessful
experiments are expected
l You needs lots of high-quality DNA for
constructing PacBio libraries
l Overlapping BACs should not be pooled
(some people already know this)
l Data editing and error-correction are
critical
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (38) Cole
39. Next steps
l Re-assemble raw reads following more
stringent edits and data cleaning
l Re-sequence single BACs or pooled, non-overlapping
BACs
l Sequence the RPCI-42 Holstein BACs
(Monsanto calf)
w Are structural differences between
Holstein and Angus in this region
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (39) Cole
40. Conclusions
l Structural variants in and around the
Siglec-12 gene are associated with
differences in SCE
l SNP are misplaced on the UMD3.1
assembly
l A region ~8 kb downstream of ARS-BFGL-NGS-
109285 appears to be misassembled
l The causal variant on BTA18 has not yet
been conclusively identified
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (40) Cole
41. Acknowledgments
l USDA-ARS appropriated project 1245-31000-
101-00
l CNPq “Ciência sem Fronteiras” program
l Cooperative Dairy DNA Repository and Council
on Dairy Cattle Breeding
Universidade Federal de Viçosa, MG, Brasil 9 September 2014 (41) Cole