6 de febrero de 2020

Valida con Travis tu código en un repositorio GitHub

Hola,
tras escuchar un par de charlas en la London Perl Conference 2019 (vídeos aquí) tenía pendiente agregar una validación por integración continua a uno de nuestros repositorios en GitHub. Opté por Travis, aunque otra buena opción si empiezas de cero es https://about.gitlab.com 
https://travis-ci.org



Para qué sirve esto? Pues para no romper nada en bases de código que ya tienen un cierto tamaño cuando haces cambios a lo largo del tiempo. En mi caso, el repositorio https://github.com/eead-csic-compbio/get_homologues tiene más de 20K líneas de código y acumula actualizaciones (commits) desde noviembre de 2016. Al vincular este repositorio a Travis (https://travis-ci.com/eead-csic-compbio/get_homologues) cada vez que hago un nuevo commit/push se lanza una máquina virtual que hace una batería de tests y me informa si va todo bien o si algo se ha roto.

Es sencillo, debes seguir estos pasos:

  1. Vincular tu repositorio GitHub en https://travis-ci.com con el mismo usuario que usas en GitHub.
  2. Agrega al repositorio un fichero .travis.yml con instrucciones para que Travis sepa como instalar correctamente el código del repositorio y sus dependencias. Puedes comprobar mi ejemplo .travis.yml , adecuado para un proyecto en Perl. Verás que las dependencias de Perl están en el fichero cpanfile. Hay documentación para otrs lenguajes, por ejemplo python .
  3. En tu repositorio preparar una batería de tests o pruebas para comprobar que todo funciona cómo esperas. Por defecto Travis hace $ make test, por tanto lo más fácil es crear un fichero Makefile con un objetivo test incluído. Ejemplo: Makefile
  4.  En el fichero markdwon README.md de tu repositorio puedes agregar la siguiente línea, adaptada a tu proyecto, para tener el certificado actualizado de que el repositorio pasa los tests en su estado actual:
    [![Build Status](https://travis-ci.com/eead-csic-compbio/get_homologues.svg?branch=master)](https://travis-ci.com/eead-csic-compbio/get_homologues)
Hasta pronto, Bruno

5 de febrero de 2020

Recursos y presentaciones del NCBI en PAG2020

Hola,
para empezar el año la gente genómica a menudo se cita en una de las conferencias más importantes del año, PAG . Allí se juntan los consorcios que producen los genomas último modelo de animales y plantas, las empresas que fabrican los instrumentos y reactivos, y los grupos que desarrollan los algoritmos y herramientas que lo sostienen todo, como el EBI o el NCBI.

Precisamente de éstos últimos hablo hoy, para compartir con vosotros los recursos y presentaciones que este año hicieron en PAG, entre los que destacaría:
https://github.com/NCBI-Hackathons/TheHumanPangenome

Que aproveche y hasta pronto,
Bruno

8 de enero de 2020

Submit gene with unknown intron to GenBank

Hola de nuevo,
el 31 de diciembre conseguí finalmente enviar a GenBank unas secuencias parciales de genes de cebada utilizadas por mi colega Ana Casas en un estudio. Éste es un paso necesario para publicar en casi cualquier revista seria, pero además es la manera de asegurar que tus secuencias van a ser útiles para otras personas en el futuro.

Antes de que se me olvidé comparto aquí como lo hice, teniendo en cuenta que uno de los genes tiene un intrón de longitud desconocida y se secuenció en dos amplicones que abarcan respectivamete los exones 1-9 y 10-14:
 

    Para poder archivar una secuencia así en GenBank utilice tbl2asn en varios pasos:
    1.  Obtención de una plantilla .sbt con https://submit.ncbi.nlm.nih.gov/genbank/template/submission . El fichero resultante especifica los autores y otros metadatos, y lo puedes usar para distintas secuencias. 
    2. Confección de un fichero FASTA con extensión .fsa (unk_intron_gene.fsa) que contenga las secuencias de ambos amplicones separadas por un tramo de 100 Ns. Para facilitar el siguiente paso intrones y exones deben ir en mayúsculas y minúsculas, respectivamente, como en este fragmento que comprende los exones 8, 9 y 10:
      ...TGTCAGatactatgcaattgccacaccaagtgctacacaaagattgctttttggtct
      TGTCAGatactatgcaattgccacaccaagtgctacacaaagattgctttttggtcttct
      tgaagcaccaccatcatgggctccagatgcacttgatgcagcagttcagcttgttgaact
      ccttcgggcagctgaagattatgctactggcatgcggGTATGACATACTGCATGCTGGCT
      GTTGTTTCAGTCCTGTTAGTTGTGATGCCTCACGATACAAAATTTCCATATTCGTATGTT
      TTGGGTGTGCATGTTTATTAATCTTGGTAACTTTAAATTCCTGTTCAGcttccaaaaaat
      tggttgcatcttcatttcttgcgtgcgattggaactgcaatgtctatgagggctggtatt
      gctgccgatacagctgctgcgttgctttttcgcatactatcccaaccaacgttgcttttt
      cctccactaaggcatgctgaaggagttgaagtgcaacatgaaccactgggtggctatgta
      tcatcatacaaaagacagGTATGCAGTAGTTTCTGCATCTAGTTAATTTTTCATTATCTG
      TTCTTCTTTAGTAAAGACTCAANNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
      NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
      NNGGATCCATGTTTTAGTCTTCTTGGTTTTACTGATTGTTGCCTTATGTCTGCATGACTA
      ATTTACCTGCTTGCACTTTGAACTATTCACAGctggaagttcctgcatctgaaaccacaa
      ttgatgccactgcacaaggcattgcttccttgctgtgtgctcatggtcctgatgttgagt
      ggagaatatgtaccatctgggaagctgcctatggtttgttacctctgaattcatcagcag
      ttgatttgcccgaaatcgttgtagctgctccgcttcagccacctactttgtcatggagcc
      tatacttgccactgttgaaagtattcgagtatctacctcgtggaagtccatctgaagcat
      gccttatgagaatatttgtggcaacagttgaagctatactcagaagaactttcccttcgg
      aaacctctgaatcatctaaaagaccaagaagtcaatccaagaaccttgctgttgctgaac
      tccgtacaatgatacattcactctttgttgaatcatgtgcttcaatgaaccttgcttccc
      ggttgttgtttgttgtattaactgtttgcgtcagtcatcaagctttgccagggggcagca
      aaagaccaacgggtagtgaaaaccattcttctgaggaggccactgaggacccaagattaa
      ccaatggaagaaataaggtcaagaagaaacaagggcctgttggtacatttgactcgtatg
      tgctggctgctgtttgtgccttatcttgtgagcttcagctgttccctatcctttgcaaga
      gtgcaacaaactcaaaagtaaaagactctataaagatcctgaagcctggaaaaaacaatg
      ggatcagtaatgagctacagaatagcattagctcagcaattctccatactcgtagaattc
      ttggcatcctggaagctcttttctccttgaagccatcatcagttggtacctcctggaact
      atagttcaaatgagatagttgcagcggctatggttgccgctcatgtttctgagttatttc
      gccggtcgaggccatgcctaaatgcactatcttcactgaagcgatgtaagtgggatgctg
      agatttctaccagggcatcatccctttaccatttgatcgatttgcatggtaaaactgtgt
      cctccatcgtgaacaaagctgagcctctagaagctcacctgacttttacatcagtaaaga
      gagatggtcaacaacacattgaggaaaacagcaccagctcatcgggtaatggcaacttgg
      aaaagaagaatgcttcagcctcacacatgaaaaatggtttttcaagaccactcttgaaat
      gctcagaagaggctaggcgaaatggtaatgttgcaagtacatccgggaaagttcctgcaa
      ctttacaggctgaagcatctgatttggctaacttccttaccatggatagaaatgggggtt
      atcgaggctctcagactctcctaagttctgttatctcagaaaaacaggaattatgcttct
      ctgttgtctcattgctctggcataagcttattgcatctcctgaaacgcagatgtctgcag
      aaagtacatcagctcatcaaggttggagaaagGTA...
       
    3. Obtención de las coordenadas de los exones con ayuda del siguiente script Perl que usa variables especiales de expresiones regulares:
      perl -lne 'if(/^>/){} else{ while(/[a-z]+/g){ printf("%d\t%d\n",$-[0]+1,$+[0])} }' unk_intron_gene.fsa
       
    4. Prepara y completa un fichero .tbl (feature table) por gen. Verás que los campos van separados por tabuladores. Si es un gen parcial deberás indicarlo usando ">" en las coordenadas de inicio y fin, tal como se explica en https://www.ncbi.nlm.nih.gov/Sequin/table.html . Para el gen ejemplo yo obtuve el siguiente .tbl:
      >Feature HvGI Table1
      <1    >7751 gene
          gene HvGI
      1383 1469 mRNA
      1564 1641
      1738 1792
      1881 2023
      2120 2376
      2811 2869
      3079 3319
      3390 3540
      3672 3881
      4821 6320
      6420 6488
      6636 6854
      7014 7106
      7195 7500
      1383 1469 CDS
      1564 1641
      1738 1792
      1881 2023
      2120 2376
      2811 2869
      3079 3319
      3390 3540
      3672 3881
      4821 6320
      6420 6488
      6636 6854
      7014 7106
      7195 7500
          product HvGI
      
    5. Guarda en una carpeta propia los ficheros .fsa y .tbl, un par por gen, por ejemplo genes/
    6. Descarga del binario tbl2asn adecuado para tu sistema operativo desde ftp://ftp.ncbi.nih.gov/toolbox/ncbi_tools/converters/by_program/tbl2asn
    7. Haz el binario ejecutable si fuera necesario 
    8. Haz la conversión, por ejemplo en Linux:
      linux.tbl2asn -t template.sbt -p genes/ -V vb -a r10u
       
    9. Comprueba errores (errorsummary.val) y corrige los respectivos ficheros .tbl y vuelve al paso 8.
    10. Envía los ficheros .sqn resultantes por medio de http://www.ncbi.nlm.nih.gov/LargeDirSubs/dir_submit.cgi
       
    Hasta pronto,
    Bruno



    3 de diciembre de 2019

    Conference: Genetic diversity. The key for improving drought stress tolerance of crops


    Notes taken by Ernesto Igartua on the conference: 
    Genetic diversity. The key for improving drought stress tolerance in crops
    19th - 20th November 2019, Berlin
    Organized by JKI, IPK



    Nov 19th
    Hermann Onko Aeikens. Secretary of State: interesting, launch of new Project (name?), to build wheat ideotypes even for drought. 2M euros.
    Wheat initiative, based at JKI, example of successful networking

    Marie Haga, Crop Diversity Trust
    Food system is in crisis. Controversial assertion. Enough food, too much waste, distribution improvable.
    Calculated: 2% reduction of agricultural yield per degree of temperature increase
    Crop Trust works to ensure conservation and availability of crop diversity worldwide, forever. It is the organism handling the funding that comes from ITPGRFA. No results so far! (last week in Rome). No understanding of the importance of the functioning of the treaty. Could lead to bilateralization (she mentions Nagoya, but positive or negative?), with terrible effects for breeding in the long term.
    Many national genebanks at risk.Seeds4Resilience, 5 genebanks in Africa funded with German money, Ethiopia, Kenya, Zambia, Ghana, Nigeria. 11,5M and 8.5M euros for long and short-term activities.
    Svalbard, backup, completely waterproof now!. 138k accessions shipped back to ICARDA after war. They are starting to return them to the vault. Cost 34M USD, or an endowment fund of 850M USD, to be independent of ups and downs of funding.  IRRI is contributing large sum to hold their 136k accessions.
    Online portal Genesys. There are subsets for drought, to help mine the databases. FIGS developed by ICARDA. Pre-breeding, 100 national and international partners in 43 countries, the “crop wild relative” project. First meeting in Morocco in April 2019. Templeton World Charity Foundation is funding this for grasspea and finger millet. There is one on barley.
    They have 7 fellows working on impact studies about the use of germplasm.
    Material in practice is not accessible (guy from CORDEVA!)
     Very little understanding in general public about the importance of disappearance of PGR.  
    Pandas? Yes; Plants? meh!

    Nils Stein. Genebank genomics
    Genebanks should not be museums. DivSeek-> unlock diversity in germplasm collections. Still alive?  Genebank genomics bridge gap between museum and use for research
    Paper of Voss-Fels in Nature Plants. Effect of breeding, fertilizer, pesticide. Modern varieties do better everywhere!
    GBS of 22k accessions (paper by Milner et al). Comparison with 1K barley core collection (Knupfer and van Hintum). Quite good match, no big gaps. Other collections do not represent barley space that well.
    How do you bring this info to the user? IPK Bridge portal. Searchable database.
    Jochen Reif is doing the same for wheat (9800 so far, goal 28k). G2P-Sol for solanaceae also ongoing, tomato, pepper (IPK), potato, eggplant? Another project for Phaseolus vulgaris (R, Papa coordinates).
    Introduction of concept of pangenome. Barley pangenome is starting, with several core collections of different sizes, to sequence at various resolutions: 20-50-300-1000-22000 from presudolmolecules to GBS, going through Hi-C, and so on. Very advanced project.
    RGTPlanet has a large inversion on 7H, in a recombining region.

    Susanne Dreisigacker. Head of molecular breeding program of wheat in CIMMYT
    Use of synthetic hexaploid wheat in breeding in CIMMYT. Triticum dicoccum by aegilops tauschii, then by triticum aestivum (elite). 1524 synthetics developed so far at CIMMYT. To bring new variation into wheat. Good examples of introduction of new disease resistances into wheat. Also good source for improving Zn and Fe content of wheat grain.
    Synthetic derivative lines are shown to improve drought tolerance. Traits: Deep root biomass, larger amounts of small diameter roots in depth, root depth, water extraction, ABA responsiveness, stomatal density and aperture pedigree e, etc.
    Contribution of tauschii genome (D)? Lines derived …17% come from tauschii. D tauschii genome is rapidly reduced in 1-2 generations of crossing. From then on, it is kept more than expected. No region favoured across the genome. About 20% of CIMMYT international trials comes from derivatives of synthetics, with multiple presences in pedigrees.
    85 varieties released with synthetic pedigree (Carmona, first in Spain, and another one in China).
    But no corr between traits in CWR and derived lines! More targeted introgression strategies needed. They did systematic phenotyping of genetic resources and found that. Low predictability in part due to genome alterations (methylations, etc, etc)
    They are now systematic phenotyping at the hexaploid SHW level to identify QTL carriers at hexaploid level, and trace QTL after crossings. For more complex traits, predict SHW x BW crosses.
    Found at least one QTL related to heat and drought tolerance.
    Good prediction ability when predicting wheat hybrids. Basnet et al 2019.
    Routine targeted introgression strategies needed.
    Matthew Reynolds, does not believe much in osmotic adjustment (OA) for breeding. They use thermal imaging and water index (ratio of two freqs with hyperspectral cameras). They have hope on spike photosynthesis, use sort of high throughput system with spike shading (…rest of details described too fast)

    Thomas Altmann. IPK, novel plant phenotyping for drought tolerance
    IPK, about 10 phenotyping platforms. Some with large capacities (>4000 small plants; >1500 large plants).
    Possible to detect QTL phase-specific. Some effects only visible at specific moments! O-localization of multiple omics QTL (transcriptome, metabolome, phenotype, in the same samples) Knoch et al in preparation, QTL for plant height.
    Wheat drought and heat stress experiment, fluorescence imaging
    Dodig et al FIPS 2019, maize, drought and N stress. Time course QTL and correlations.
    Scale of work with Arabidopsis is phenomenal! RNAseq time course analysis during drought and recovery experiments. Found gene networks operating. Erbe, Brautigan, Junker, unpublished. Gene-to-phene network.
    Upgrading platforms for root phenotyping. Pots with one side transparent, transparent only to red light? Root growth undisturbed be light. 400 pots. Shi, Seiler et al 2018 Functional Plant Biology, Shi et al in preparation. Shoot and root imaged at the same time!! B73 drought, lots of root growth in the first cm. Peat based soil, really dark (graveyard soil), to improve contrast in images. See also Narisetti et al Sci. Rep. 2019
    IPK, new Plant Cultivation Hall. Rhizotron, Phenocranes, lots of rhizoboxes for shoot and root phenotyping.
    EMPHASIS ON: Phenotyping in defined/designed and relevant environments
    Excellent systems to test results coming from models!!!

    Menachem Moshelion. HUJI. Risk management strategies and transpiration rates of wild barley in uncertain environments
    Gosa et la 2019, Plant Science, yield-survivability trade-off.
    Defines critic delta as the level of soil water content beyond which water is not accessible for the plant. There is genetic variability for that..
    Plant Ditech lysimeters, soil probes and air probes for each lysimeter, irrigation also controlled individually. Possibility to prepare separated irrigation solutions for each lysimeter.
    Measured: plant biomass gain, transpiration, WUE, stomatal conductance (canopy conductance), root fluxes (how much water is taken from the soil by the plant, identifies critical drought point per plant. The SPAC analysis software online.
    Correlation with yield? Tomato, D. Zamir, field trials and lysimeter experiment. 105 traits between field and greenhouse, stomatal conductance, cumulative transpiration
    Best corrs not from drought period, but from recovery period.
    Galkin et al 2018, Physiol Plant. Fridman’s 1K wild barley. 5 accessions chosen to represent the population. From 5 different ecological niches. Main difference between envs is number of days between 2 rains.
    Relates variance of environments of collection with stability of physiological responses measured at the lysimeter. Two most anysohidric behaviour from North and South, high and low rain, but very stable in terms of time between 2 rains!!!!

    Kerstin Neumann. IPK. Precision phenotyping, drought QTL barley and wheat collections
    IPK part of DPPN, EPPN, EMPHASIS
    520 pots, 1 plant per pot, to full growth for barley or wheat.
    Dhanagond et al 2019****, barley article(s), 100 2row accessions, 9k chip. 100 entries, 3 reps (in three experiments at three diff dates), very diverse collection in terms of origins.
    Pre-stress, then 27 to 45 days at 10& plant available water, then recovery. GWAS over time. Neumann et al BMC PB 2017 (visto)
    Dependence of wilting time in barley from initial biomass at drought start!!!! The larger, the earlier. In wheat, same, less pronounced.
    Results of project BRIWECS, wheat, interesting, time course GWAS, many traits recorded.135 varieties for GWAS, 15k SNPs. Tested in the field, 5 locations. Published. Correlations greenhouse-field. High corr PH, tiller number, inflection point reasonable corrs. With grain yield. Many corrs with year of rerelease, in similar directions for field and greenhouse. All tillering components increased in modern cultivars.
    They are also studying isolines for drought tol, with a QTL introgressed from emmer (collab with Saranga) QTL from Merchuk-Ovnak 2016
    Conclusion: Landraces might harbour more diversity for drought tolerance!!!

    Hermann Lotze-Campen. Potsdam Institute for Climate Impact Research
    Involved in AGMIP.
    Sustainable development goals.
    Developed model MAgPIE, food, demand, trade, production, crop, land, residues, etc…. including technological change and costs. Dietrich et al 2019. Goals: minimize global production costs. Output: climate-induced agricultural price changes by 2050 (climate extremes not included). 10 to 35% increase in agricultural prices by 2050 in the reference scenario.. Translate ten into cost of food, for 2 scenarios for the World Bank. Biult an agricultural vulnerability indicator, to indicate hotspots in hgh risk of hunger.
    IPCC SRCCL Fig SPM2, find! (climate change increases pressure on land systems)
    What can be done to limit production losses? ->technology, including plant breeding; shift expansion of agricultural land. One conclusion, keeping investment in research absolutely needed.
    Agriculture produces 24% GHG. Reduction must be a part of global mitigation!
    Dramatic land demand for land based reduction…..

    Nov 20th
    Roberto Tuberosa
    Durum wheat.
    Maccaferri et al 2019, durum genome. Pop structure of tetraploid wheats.
    Global durum wheat panel, 1056 accessions. Also tetraploid wheat global collection 1856 accessions. 286 in common.
    Unibo GWAS panel 189 cultivars with only 3-5 days variation in flowering date. Phenotyped in IDuWUE, 14 environments. Maccaferri et al 2011, 14, JXBot. New data coming, for up to 35 envs, from a new project.
    Collection field tested in Lemnatec field analyser in Arizona, Maricopa. (Terra project, Danforth foundation). 2 years severe drought, 1 year mild stress. Traits measured: chlorophyll fluorescence, NDVI, infrared thermography (also with drones and phenomobiles). RWC (rehydration method Babu et al 1988), OA, at day 14 of stress, etc. r=0.78 between active OA and RWC. Several QTL found, some in common OA and RWC, some also for biomass. No yield data due to early harvest, April, to leave room for sorghum crop. Samples collected for RNAseq and metabolites. Big-big data, difficult to manage. Haplotype analysis ongoing
    UAV platforms better quality data than ground. Rehydration method good for high throughput for OA. 6 people sampling, pre-dawn.
    Tribute to A. Blum, PlantStress still managed by Saranga. 
    Roots. Good corr between shovelomics and root angle in seedlings. 2 QTL have effect on yield in a large set of environments!
    Experiment in Julich, they found QTL, how large was the population? Haplotype effect for main QTL studied. CIMMYT materials stop root growth earlier. Another QTL, larger leaf area in CIMMYT materials. He shows haplotype distribution across germplasm groups. Effect of one of the QTL in field results, large GxE interaction related to productivity.
    Work goes ahead in Rooty project, candidate search and QTL backcross to elite materials.

    Shuki Saranga
    Ancestral QTL from wild emmer wheat to enhance drought resistance of modern wheat.
    T turgidum diccocoides, wild wheat (AABB), brittle, hulled. Wild emmer.
    Collection from the wild, from North Israel., 55 x 150 km. But huge environmental variation.
    168 accessions, 2 treatments, rain shelter. 250mm vs 700 mm. Sort of polytunnel, plastic vault, to protect from rain. Peleg et al 2005. Peleg et al 2008, study of 10 individuals per population. Half of the variation was between, half within populations, for spike dry matter, same for genetic diversity SSR. Found six genetic clusters of populations, divided NOT by geographical distance. There were differences for total rainfall. Peleg et al 2008, allelic diversity related to aridity gradient, with largest variation in intermediate aridity. Extremes less diverse. Typical in Ecology, also more richness of species in intermediate environments. Correlates with that Menachem was saying yesterday. Populations from intermediate sites experience more interyear variation in terms of aridity. Pops identified as best drought resistance sources came mostly from intermediate areas. Driven by how you define drought and its boundaries. Populations from arid places are too drought adapted.
    How to harness that for crop improvement. QTL from GWAS? Peleg 2009. Rolling index, carbom discrimination, chlorophyll content, osmotic potential at heading, constitutive and inductive QTL found. 6 regions found interesting for introgression via MAS, tog et NILs.
    Results in Merchuk et al 2016. Several NILs for different QTL. GY enhanced in 3 of them, confirming constitutive or inductive nature, by effect in WW or water limited envs. They found differences in rooting (pictures by students). Now being studied in long plastic sleeves in the greenhouse, 1m depth. More roots in depth under water limitation for the NIL, in DW and length!!! Also agronomic trials, 2014-17. About 10% higher yield by the NIL than original cultivar. Almost significant in a second NIL. Overall, 6,6% advantage. But it is 4.5% under better conditions, 9.8% under lesser productivity.
    Fine mapping of these materials ongoing, 15kchip. Segmental RILs produced. Phenotyping under controlled conditions, not so clear. Ongoing work.       

    Klaus Pillen. Uni Halle
    HEB-25
    Merchuk-Ovnat et al 2018, JXBot.
    HEB-yield study with 48 lines, segregating for Vrn1, Vrn3, denso, Ppd1. Control vs stress trials at each location (N, drought or salt). Correlation between yield and flowering vary according to location and stress or control. Wiegmann et al 2019 Sci Rep.

    Maria von Korff. Uni Dusseldorf. Inflorescence development and floret fertility under drought in barley
    Nice slide comparing Arabidopsis and barley approaches! What is drought stress tolerance?
    Nice conceptual layout.
    She said over dinner that Australian genotypes were very successful in coping with drought!!
    Escape (finish before stress), avoidance (maintain homeostasis), tolerance (minimize damage), hierarchical manner.
    Arta vs Keel (only 2 genotypes, she says she feels embarrassed!). Stress at heading date (drought 50%) and heat stress. RWC, fluorescence, leaf temperature. Treatments, drought, heat and combination. Large diffs in biomass, not in RWC and temperature. Also in phot. Performance, only affected by heat. GY equally reduced by drought and heat. spike number reduced by drought, grain weight more affected by heat. The way yield was reduced was different. Drought avoidance is really strong in barley.
    Mapping pop Arta Keel tested in 13 envs in Syria. Flowering times affect spike and plant architecture. Rollins et al 2013. GY in VrnH2!! Is it because of drought escape, more important than avoidance in the field? AP2, EPS7L included among QTLs, also VRn1, Ppd1, Ft1, etc.
    PPD1 gly->trp change, delayed expression of FT1. PPD1 from wild introgressed in Scarlett, also in Bowman and Golden Promise. 3 very diff backgrounds.
    Drought stress treatment to isolines. Long drought and short drought, until end of cycle. Will show results only from long treatment and Scarlett. Maintenance of RWC in the leaves, over 80, very constant. Drought avoidance at play. Flag leaf cell size and number reduced under stress in both lines, Scarlett and introgressed. PPD1 interacts with drought to control flowering. 10 days delay in Scarlett under drought. No delay in isoline!!! Also seen at time course for Waddington stage. Reproductive development starts from very early, earlier than W2.5, invisible from outside, and it matters. PPD1 interacts with drought to control seed number, huge reduction in Scarlett under drought!!, and seeds per plant. Cross over interaction depending on treatment. Introg. line produces less seeds per plant under control, and more under drought. Qualitative interaction. Striking pictures!!! Seeds not formed or not developed in Scarlett.
    Drought reduces meristem size. PPD1 controls trait canalization?? It controls that traits do not change much under stress, time to flower, seeds per spike. It maintains trait expression across environments, conditions.
    Gene expression. Time course. PPD1 does not change much. FT1 much higher expression in NIL than in Scarlett. BM3, BM8, MADS box genes, also expressed much more in NIL.
    COCL: barley adjusts growth by drought avoidance. Biomass and  developmental stage have major influence on drought effect
    Control RWC rather than field capacity in the soil!!!
    Barley delays reprod development under drought. No or little escape.
    PPD1 interacts with drought to control floral development, spikelet number and seed set-canalization gene.
    PPD1 and drought dependent expression of MADSbox genes correlate with diff response to drought in PPD1 variants.
    Differential investment into vegetative and reproductive drought ????
    Question: PPD1 may affect hormone levels, not just auxin (question by Bartels).
    Question Andreas: PPD1 effect on root? Maria responds, How much root reflects shoot? FT1 has strongest expression in the roots, in parallel with shoots. What is it doing there?

    Gerd Patrick Bienert. Improving drought tolerance by increasing nutrient efficiency
    “Metalloid transport group”
    B fertilization increases drought tolerance, in diff crops. New Phytol 2019, two contrasting papers with two differing views!!!
    Only known function of B is cell wall, but Bo deficiency reduces shoot and root growth and fertility.
    Water limitation impairs B acquisition and delays flowering.
    Bo deficiency also affects root development, deorganizes vascular system. Good B nutrition ensures vigorous root system and healthy vasculature.
    They found a commercial soil substrate with low B to do experiments. 600 brassica napus cvs screened (winter and spring).. A few B tolerant plants found. Roots also studied, in vertical agar? Large diffs between inefficient and efficient cvs.
    Pop made between contrasting lines, 255 doubled haploid lines. Identification of shoot and root B efficiency traits, with Altmann, pots with one side transparent. 396 rhizopots. Analysis ongoing.
    Work also ongoing in Arabidopsis. 188 genotypes screened, and contrasting genotypes found.
    Ionome traits also determined, at a single point. Cytokinin hypersensitive 1 (CKH1) modulates B efficiency in Arab. Encodes a transcription initiation factor. Gemayel et al 2015 Mol Cell. Variable length of polyglutamine repeats within exons actually affects function of gene.
    N could be the same as B (Tyerman et al 2017, plant aquaporins)

    Dorothea Bartels
    Dessication tolerance in vegetative tissues on angiosperm plants evolved through gene duplications and network rewiring
    Resurrection plants. Oropetium thomaeum (monocot from India) and Craterostigma plantagineum (dicot). They both keep chlorophyll during dessication.
    During dehydration, huge changes in all metabolites. High sucrose, high stress proteins (stress proteins, many LEA).
    Oropetium, smallest genome among grasses (250 Mb), diploid 2n=18, small, 6 cm. Good gene synteny with sorghum, still fair with brachy, bbut almost 10 times more compact in the segment she uses as example. In all, two flod reduction compared to brachy. 28440 genes, 43% repeats, 30% DNA contain evenly spaced unique sequences. Recently duplicated genes are enriched for stress responsive genes. Seed specific pathways expressed in vegetative tissues.
    Also work with L brevidens, dessication tolerant, tetraploid (Craterostigma is octoploid, too complicated to sequence).
    Two examples of abundantly expressed genes in tissues, LEA and ELIP (early light induced proteins, are in thylakoid membranes, possibly protecting chlorophyll by binding to it), described in barley!! ELIP genes overrepresented in dessication tolerant plants!!! Also, in L brevidens, very abundantly expressed.
    Regulatory neofunctionalization of LEA family genes…..
    Present architecture of promoters, selective activity of promoter elements found for LEA genes, diff between dessication tolerant and nontolerant species
    Seed related pathways expressed in vegetative tissues, source of dessication tolerance.

    Matthew Reynolds. Key physiological traits for strategic crossing in breeding wheat for drought adaptation
    Wheat megaenvironments: many different in Spain! Also in Turkey, with some more similar to Russia.
    Physiological pre-breeding pipeline.
    Genetic resources-Phenotyping (HTP, also precision phenotyping)-Genetic analysis (QTL, MAS, genetic complexity)- crossing and selection (introgress them in appropriate background)-evaluation of genetic gains—informatics-crop design
    Which traits? Same conceptual model as Roberto. Spike photosynthesis; remobilisation of CH, photo-protection (wax); canopy T as proxy for rooting depth. BUT, massive GxE, also GxG present, not well understood yet.
    70000 wheat accessions screened for drought in Sonora 2011-13. Several panels derived from there. Synthetic panel (140). Primary synthetics produce a lot of biomass, but they are not as good in partitioning, HI. Also bread wheat panel (344).  
    HTP in not just about tools. You need panels which are fixed for major environmental genes. Breeder friendly tolls needed! Eye-> low resolution stereoscopic spectral radiometer and supercomputer. Canopy temperature is useful. Soil water extraction in depth has increased with breeding in wheat! Lopes et al 2010.-> yield under drought is correlated with root weight at 60-120 cm, but canopy temperature is even more related. It is a proxy for root depth. Small buggies built for several sensors.
    Pinto et al 2010, QTL found for heat and drought adaptation.
    GWS for bread wheat and synthetics, you get different QTLs.
    Spike phot, Molero unpublished. QTLs found, field phenotyping
    Crossing: Basis for source x sink strategy crossing. Interesting scheme in form of a pyramid, which simpler traits affect other traits higher in hierarchy. Strategic crossing combining sevreal of these traits.

    Peter Langridge
    Long history of breeding for wheat and barley. Lots of diversity incorportated. We must understand what is already achieved, maybe some traits are already almost fixed, and should be less prioritized, like flowering and plant height. They have been taken care already.
    Drought is a very complex feature. Australia, 1 t/ha needed to break even. Frost, wind, heat, frost, UV, drought, pests, diseases, nutrient deficiencies and toxicities, salinity, sodicity, alkalinity, all limiting factors-
    Now, with commercial breeding, trget environments are larger than they used to be. Also, more concern about performance under abnormal conditions.
    Targeting specific components of the stress environment. Example of B tolerance. Genes found in wheat and barley. In barley, tolerant varieties combine two mechanisms, Sutton et al TIPS 2011. Both mechanisms are optimized in tolerants. Nice story about origin of Bo tolerance genes in Pallotta et al 2014 Nature. ….
    Trade-offs. Negative relation yield and protein. National data. ENvs divided into Chenu classification. GY-GPC …. Unpublished. Also Ranimi-Eiche et al Afronomy 2019. Breeders have traded yield for protetin. Can the negative relation GY-GPC be broken? Maybe, if breeders select under strees and low N. ***
    Limitations in using variation. Uses of unadapted germplasm. Beyond serendipity and opportunism, Screen for simple traits, clear phenotype, FIGS. Identify variation for complex traits is difficult. Linkage drag, 60-80% of each chromosome rarely recombines (if ever).
    Reference germplasm collection in bread wheat, survey of potential users…..
    Australia: CRISPr, simple knockouts will not be regulated!!!!
    Braun: happy to do editing if we knew what to edit (not knock out, real editing)

    Heike Lehnert
    Genetic diversity in wheat regarding mycorrhization of roots.
    Menciona dos artículos
    20% carbohidrates fixed by plant go to fungi and other microorganisms in the rhizosphere!!

    Hans-Joachim Braun
    Wheat most important source of protein in most countries in the world. Wheat only major crop with good frost tolerance, difficult to substitute.
    Good communication in wheat between private and public sectors.
    Investment in wheat works because of royalties.
    Gives examples of returns of investment on wheat research.
    Data published by Wheat Initiative
    Gray et al 2019 1stIWC Saskatoon. Comments on royalties. Search!
    Australia best example. They pay after harvest, based on harvest. Canada, farmers happy to pay more royalties if money goes to public centers!!!
    CENEB, CIMMYT, principal breeding site for yield, heat and drought. Centro Experimental Norman E Borlaug. .
    Global Precision Phenotyping Network, platforms hosted at NARs where environments are optimal for trait phenotyping.
    Kenia, 600000 accessions tested for UG99, wheat, rye, barley
    Wheat blast appeared in Bangladesh in 2015, before only in Latin America. Fungicide resistant race. Pre-emptive screen done in Bolivia in 2010. Allowed rapid response.
    Long history of research collaboration, must be maintained. Royalties are fine, but do not go beyond that.
    Agriculture, problem or opportunity. 24% GHG emissions, but 50% employment, 5% global GDP, 30% if whole food system is considered, but only 5% of global RD investment. Agriculture is big business!!
    Informationisbeautifulnet graph, search, cannabis, wheat… invest in poppy!
    Food processing companies do not invest in RD agriculture. They want to stay away from “biotechnology”. Also, value chain for millers start at receiving the grain, not at sowing!! We are not in the picture!!!

    Stephen Visscher. Global Institute for Food Security, Saskatoon, Canada
    Biology does not have all the answers. It is quite new organization. Harness crop genetic diversity, mechanisms and example. DivSeek.
    Established in 2012, funded largely by private companies. Focus not only on discovery, but also on delivery.
    Research p pillars: seed and developmental biology, root-soil microbial interaction, phenotyping and genomics
    International collaboration: grand challenges need different approach….Complexity need coordination and program management….
    IWYP, new model for funding and conducting coordinated international research program. Public and private partners, Wheat initiative included. Research focus on several issues. Buscar esquema por si sirve de inspiración para España. Projects funded all over the world. All results had to be routed through the hub at CIMMYT, to compare and combine synergies. Allows release to worldwide breeding programs. Enables IWYP to drive discoveries towards market.
    DivSeek (Susan McCouch). White paper in 2014 by Marie Haga. Aim at facilitating networking of like-minded mind…..Spain still not there, creo
    Digital AG: tools to enhance plant breeding. Recruiting….
    Earth Biogenome Project. A Grand Challenge, a moonshot for Biology.
    Darwin Tree Life, Welcome Trust now sequencing of all UK species!!!
    DivSeek Canadian not for profit organization, DivSeek International Network Inc, 68 organization, 28 countries. Showcase best practices for generation, curation, ….integration of data about PGR.Encourage linking of digital info. Support human resource development. Contribute scientific perspective on PGR….