Shadowing Practice: Presentation - Copy Number Variant Interpretation/Dosage Sensitivity Curation (Erica Andersen) - Learn English Speaking with Video
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Hello, my name is Erica Anderson and today I'll be discussing resources used for clinical copy number variant or CNV interpretation.
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I'll review new metrics
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and reporting recommendations developed by our CNV interpretation guidelines committee as
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well as details on how to use our publicly available dosage sensitivity map.
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Resources relating to CNV interpretation are available on the conference website and will be covered in more detail during this workshop.
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I'd like to start by highlighting a couple of challenges to the CNV interpretation process.
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The first being that most CNVs are unique or non -recurrent and thus have variable breakpoints in gene content.
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This figure shows some examples of unique CNVs involving many genes, few genes, and no genes.
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During clinical encounter, evaluating each of these CNVs will involve compiling evidence from different resources,
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then using standardized processes to classify each appropriately, followed by tailoring the clinical report for any CNVs that meet your lab's reporting criteria.
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Recurrent CNVs, which, shown at the bottom, involve the same genomic content,
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collectively account for close to 10 % of CNVs encountered in frontline genomic testing.
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Such CNVs have been shown to associate with variable clinical findings and exhibit reduced penetrance,
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and thus also need to be classified and reported in a standardized way so their significance can be counseled appropriately.
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Another challenge for CNV interpretation is evaluating information relating to genes,
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as those that are disease associated may do so by mechanisms other than deletion or duplication or dosage sensitivity.
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For any particular gene, a variety of variant types may be observed.
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Some variants may be disease -causing and others benign, or some variants may cause different clinical phenotypes depending on the gene.
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This figure illustrates the complexity of the potential mutational spectrum that may be observed for individual genes.
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At the top, a number of disease -associating sequence variants may be reported in the literature,
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only some of which are likely to cause a complete loss of function, similar to a full gene deletion,
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and few, if any, will act similarly to a whole gene duplication.
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Additionally, CNVs both encompassing entire genes, partially overlapping, or occurring within them can have differing effects,
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and so gene level evaluation needs include compiling evidence from different resources,
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including both cytogenomic and molecular resources, understanding of technical limitations and functional effects of variants occurring within genes,
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as well as standardized classification processes.
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In order to improve these processes, a collaborative working group of the American College of Medical Genetics
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and Genomics and ClinGen developed updated technical standards published in late 2019, which I'll be taking you through today.
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For those of you familiar with genomic microarray testing,
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this new set of standards was built using the original 2011 ACMG guideline as a foundation
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and incorporates aspects of new frameworks developed analogously for sequence variant interpretation.
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Ultimately, these new guidelines aim to standardize classification and reporting practices across labs, technologies, and genetic specialties.
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To review these updated CNV technical standards, from the workshop page, click on our working group site,
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click on the technical standards, view citation, then view documents in PubMed Central,
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where you can access the manuscript as a PDF or full text, as well as download all of the supplemental materials.
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These include a very detailed user's guide, as well as example cases and reports.
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So next I'll provide an overview of the new features in these updated guidelines,
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the first of which was to officially adopt the five -tier variant classification system, which had been recommended for sequence variants since 2015.
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It involved separating CNVs classified as likely pathogenic and likely benign out from a primary uncertain category.
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The committee recommends using these standard classification terms for all CNV types in order to avoid confusion for clinicians and families.
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If caveats exist, additional information can be provided in the report text to further explain the result.
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Another major change was the development of a new numerical -based scoring system for CNVs, with separate scoring metrics developed for deletions and duplications.
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Key features of these new metrics include starting each CNV at a baseline of zero corresponding to uncertain or VUS,
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then requiring evidence to both up and downgrade CNV classifications.
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Each piece of evidence is evaluated based on its categorical strength
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and assigned a corresponding point score using categories intended to harmonize with those used for sequence variant interpretation.
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Default values are provided for all evidence types,
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but ranges are included for many categories to provide flexibility based on evidence strength within a category.
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Each CNV metric has the same five key evidence types evaluated, which are separated into different sections and scored independently.
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Section 1 involves assessing genomic content within the deleted
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or duplicated interval to determine if protein coding or other gene regulatory elements are present.
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In Section 2, the user determines whether and to what extent the CNV overlaps any established, dosage -sensitive, or benign genes or regions,
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using resources including the ClinGen dosage sensitivity map which I'll be going over shortly.
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A few highlights from this section are rules for intragenic CNV evaluation and HI predictors for deletions.
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section 3 involves a gene count within the cnv interval focusing on the total number of protein coding genes
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and there are rules for regions containing gene families different gene
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count thresholds are also designated for deletions versus duplications section 4
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is the most labor intensive section of the metric as here the user must identify similar cnvs to
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that under investigation and assign points for each reported case based on how specific the associated phenotype is,
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the inheritance pattern, and whether there is overlap with common variation or available case control data to evaluate.
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Finally, in Section 5, the user evaluates the associated phenotype and inheritance pattern for the CNV of the patient being studied.
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To assist users in working through these new metrics, ClinGen has developed a free web -based CNV calculator tool
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that you may access from the ClinGen website and in the materials provided today.
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From the main page, choose the appropriate scoring metric,
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evaluate gene content and whether established dosage -sensitive or benign regions are involved,
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checking to ensure the correct points category applies based on extent of CMV overlap,
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then evaluate protein coding gene count within the interval,
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followed by the detailed evidence evaluation assigning points for each reported proband from the literature using information including phenotype and inheritance patterns.
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In section 5, use the same rules for the patient being studied.
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The calculator will automatically assign a five -tier classification based on the total points scored.
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Scores for each evidence category are summed to a total value and assigned a corresponding classification.
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Pathogenic and benign are reached when beyond the plus or minus 0 .99 threshold.
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Likely pathogenic and likely benign are in a narrower range of plus or minus 0 .9 to 0 .98,
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while the VUS category is the broadest range from negative 0 .89 to 0 .89.
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The total point values were developed to correspond to confidence levels that a particular CNV is disease -causing or benign,
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similar to confidence measures suggested in the 2015 sequence variant interpretation guidelines,
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indicating pathogenic and benign should have a 99 % level of confidence of this classification,
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while likely pathogenic and likely benign should have at least a 90 % level of confidence of this classification.
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So now that you've learned the basics, let's go through an example case.
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Case 1 is a newborn male with poor feeding who is small for his gestational age.
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A genomic microarray was performed and identified an 882 kb deletion within chromosome 20p12 .2.
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Parental testing showed this deletion was de novo.
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Let's Let's take this deletion through the copy number loss metric.
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In the first step of the metric, we examine whether the deletion contains or does not contain protein coding or other functionally important elements.
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You can do this using annotations built into your software or using your favorite genome browser.
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Just remember to double check your input format and match the correct genome build.
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Here, I plug these coordinates into the UCSC genome browser and turn on the NCBI RefSeq genes track,
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which is showing about 9 genes in this region, some of which have multiple transcript isoforms.
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Of these genes, those that are protein coding are indicated with the NM underscore at the beginning of their transcript ID.
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We can see that five of these genes are protein coding,
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so we assign zero points to Section 1A and continue through the metric.
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If conversion of your query sequence to another genome build is needed, you can use tools such as the View
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and Other Genomes tool in UCSC to take coordinates from the current assembly and convert them into another, such as HG38.
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This can be used when sequence builds vary between platforms and resources available to investigate CNVs.
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Here, I converted an HG19 sequence to an HG38 in order to evaluate this CNV in the Decipher database.
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In Decipher, However, users can also find information, such as gene count, and how many genes are protein coding.
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In Section 2 of the CNV Interpretation Metrics,
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we must evaluate whether this multi -gene -encompassing deletion completely overlaps an established dosage -sensitive or benign gene or region,
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which would move scoring for this deletion into a pathogenic or benign category, respectively.
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In order to do this, we're going to first look at the ClinGen dosage sensitivity map, which is stated in the guidelines,
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specifically annotates and scores genes and genomic regions in relationship to dosage sensitivity, and should be used to interrogate most CNVs.
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The dosage map is curated by the ClinGen dosage sensitivity working group.
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In this working group, we aim to address this basic question,
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does loss or gain of a copy of a particular gene or genomic region result in a clinical phenotype?
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Similar to clinical C and B scoring, the ratings assigned for dosage sensitivity correspond to strengths of evidence.
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A 3 -score is the highest level of evidence, corresponding to sufficient evidence for pathogenicity.
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A 2 -score indicates there is some evidence for dosage sensitivity that is emerging.
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1 indicates little evidence and information is limited at this time.
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A 0 -score indicates that either no evidence exists or that evidence available is insufficient.
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And finally, the dosage sensitivity unlikely category indicates genes and regions for which there is evidence refuting dosage sensitivity.
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We also have a ranking for genes with autosomal recessive inheritance patterns.
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The dosage sensitivity curation process started back in 2011 as an effort of the ISCA, or International Standards for Sciogenomic Arrays Consortium.
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Since then, the group has undergone a number of changes, including to their name.
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Their curation processes have also evolved.
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For the past few years, FOCUS subgroups have been working to curate neurodevelopmental genes,
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recurrent CNVs in other genomic regions, and hereditary cancer genes.
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You can find more information about these subgroups' work on the Dosed Sensitivity Curation Group's website.
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The dosage map is curated by the ClinGen Dosed Sensitivity Working Group.
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You can visit our group page on the ClinGen site to
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learn more about our curation activities as well as to browse currently available curations.
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These curations include over 1400 genes in 72 regions scored for dosage sensitivity.
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You can review information on individual genes as well as genomic regions.
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And you can also input your own genomic coordinates from a CNV under investigation to evaluate our curated genomic content.
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But because this is a very recently updated feature, we're going to evaluate the CNV in case 1 using our legacy dosage map website,
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which now provides a link over to the updated site in ClinGen.
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On the main page, you can input either individual genes or genomic coordinates for CNV regions.
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Here, let's input the genomic coordinates for our deletion, double -checking the correct genome build is used.
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This takes you to a result page with tabs showing genes or regions that overlap our CNV.
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Here, two genes in the deleted region have been curated.
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One has a three score, the other is conferring recessive disease risk.
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On the right, you can click the link starting with ISCA to go to this genes page.
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The gene page includes curation status, date this gene was last evaluated, links out to other gene and disease resources,
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and the curated haploinsufficiency and triplo sensitivity scores with corresponding evidence summarized in the bottom tabs.
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Let's take a closer look at the information available for this gene.
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In the haploinsufficiency tab, you can see evidence relating to deletion and loss of function involving the gene JAG1.
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A three score is the highest level of evidence that deletion of this gene is disease -causing associated with Allergeal Syndrome.
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Historically, three patient reports were considered to provide sufficient evidence for dosage sensitivity,
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and so the current layout allows up to three references with links out to PubMed to be summarized here.
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Though this section is expanding with the updated website.
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At the bottom is a summary comment which typically includes information on the associated phenotype,
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mutational spectrum, genotype -phenotype associations, and inheritance, penetrance, and case control data,
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though not all three scored genes will contain this level of detail, particularly if the gene is already well known.
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This same information can be viewed on the new website in a slightly different format,
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with additional gene level information displayed at the top of the page.
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And so coming back to the classification metric,
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in section 2a we have identified an established haploid -sufficient gene that is fully contained by our patient's deletion.
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Therefore, this deletion will receive the max score of 1 in the metric.
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If you're following along using the calculator, this is what you should see.
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According to the metrics, in general, if a CNV reaches a 1
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or negative 1 score due to complete overlap with an established dosage -sensitive or benign gene or region,
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users of these metrics may not need to proceed further.
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And so with overlap with an established haplois -efficient gene, JAG1, our patient's deletion can be classified as pathogenic.
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However, it is important to point out that although we have a clinical classification, evaluating through the remainder of the metric may still be helpful
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to evaluate the potential phenotypic contribution of additional genes in the interval for genotype -phenotype correlation.
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In this study, the authors showed an association between deletion size and additional phenotypes seen in patients with Allergeal Syndrome,
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where deletions involving sequence outside of the black dotted lines were associated with additional phenotypes.
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Though our patient's deletion for case one, shown in red, is smaller than this interval,
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this type of information can still be useful to evaluate and note in the clinical report.
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So next we're going to return to the CMV Interpretation Guidelines Reporting Recommendations.
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Before we do so, I wanted to point out that on the Dosed Sensitivity Map website,
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we do have a list of useful files that can be downloaded from our FTP site.
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Here you can download several files containing lists of curated genes
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and regions which have been formatted for use in genome browsers as well as visualization software.
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Many of these files are updated daily.
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One track I'd like to highlight is the recurrent CNVs track shown here, displayed in the UCSC genome browser, showing the proximal 22q region.
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This region has a complex genomic architecture with an array of segmental duplications shown with the black bars
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that mediate recurrent deletions and duplications involving the orange regions,
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such as the common DeGeorge syndrome deletion involving the A to D segmental duplication regions.
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This track can be useful during genomic analysis to delineate these regions and find the appropriate literature to cite and evaluate,
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especially when dealing with some of the more rare rearrangements involving the central and distal regions.
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We also include links to the evidence curations for these regions on the dosage map site.
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Alongside CNV classification changes, another major change to the updated clinical CNV technical standards was to uncouple variant classification from clinical significance.
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This is because these are two different concepts.
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For CNV classification, we are asking whether there is enough evidence that the CNV under investigation causes disease.
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In determining clinical significance, however, we're asking whether the CNV is responsible for the phenotype of the patient being tested.
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For example, consider how you would classify and interpret the clinical significance for the following scenarios.
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First, a deletion of the recurrent 17p12 region containing the PMTP22 gene,
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which is responsible for a later onset motor and sensory neuropathy, called HMPP, observed in a newborn,
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referred for multiple congenital anomalies or an adult with foot drop.
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Next, consider how you would classify
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and interpret a deletion involving a gene on the X chromosome
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that causes an X -linked recessive cutaneous disorder in males
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that is observed in a 10 -year -old female referred for dysmorphism and severe intellectual disability and developmental delay.
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In both scenarios, the classification of the variant should remain the same.
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The evidence supporting these classifications at the same point in time is the same.
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Therefore, the variant should receive the same classification regardless of the context in which it was observed.
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In each scenario, the clinical significance of the variant could be different.
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In the first scenario, the variant could represent an incidental finding in one patient but explain the indication for testing in another.
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In the second scenario, the variant could be disease causing in a hemizygous male but represent a carrier state in a heterozygous female.
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Clearly labeled sections on a report delineating findings related to the reason for referral,
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findings that may be incidental and findings that may represent carrier status could be utilized to clarify these situations.
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In the supplemental materials provided with updated technical standards,
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we provide several example reports that illustrate how to communicate classification and interpretation for different scenarios.
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This example report describes a pathogenic CNV.
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Here, a deletion associated with progressive hearing loss identified in the workup for a child with developmental delay in autism. In this example,
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the report clearly states at the beginning
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that this test did not identify any variants that can explain the patient's reported clinical features,
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then follows to describe the pathogenic finding and its interpretation with respect to the clinical findings provided.
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Lower in the report are distinct CNV classification
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and relevance category fields to make this information clear to both the patient's family and clinician.
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The new technical standards included updates on the interpretation of secondary and incidental findings.
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During genomic testing, a CNV may be identified that involves a dosage -sensitive gene unrelated to the patient patient's reason for referral.
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Some examples include a large deletion causing syndromic features in a child that also includes a cancer risk gene,
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in this case BRCA1 in 17q,
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and a focal BRCA1 gene deletion identified in a fetal specimen referred for ultrasound anomalies.
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In both cases it would be important to highlight these findings
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as secondary in the patient's report for future medical management and possibly for familial counseling if inherited.
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The committee recommends reporting such CNVs if the mechanism of disease is consistent with haploinsufficiency or triplosensitivity.
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But be sure to consider the mechanism for pathogenicity as not all genes
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that have been annotated as associated with secondary or incidental findings cause disease due to dosage sensitivity.
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The ClinGen dosage sensitivity working group has a curated list of these genes
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that are targeted on the ACMG secondary findings list for sequence variants, which can be accessed from our webpage.
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The last change I'll discuss was also new compared to the 2011 guidance, which focused exclusively on postnatal CNV interpretation.
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In the update, the committee recommended to apply the classification metrics and evaluation process in the same manner for constitutional CNVs, regardless of context.
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Laboratories offering prenatal CNV testing are still allowed to set higher reporting thresholds if warranted, but should clearly state what those are.
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For example, only reporting pathogenic and likely pathic variants or only reporting VUS larger than a specific size threshold.
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So before moving on to our last case I
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wanted to highlight the CNV technical standards web series that's linked up at the top of this slide
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and also present in the materials that were provided to you all today.
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This web series was recorded this time last year actually
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over a nine -week period and covered a lot of the materials
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that I didn't have time to get into detail about today,
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including an overview on the technical standards that was provided by Erin Riggs,
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my colleague who's on the webinar with me today, a webinar devoted to the use of the ClinGen Dosed Sensitivity Map.
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We also covered how to score case -level data, considerations for evaluating intragenic CNVs,
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understanding case control data, using resources for population CNVs, both NOMAD
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and the database base of genomic variants more information on how
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to uncouple the variant classification from the clinical significance in the report
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and then we also did a Q &A session finally
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this past November several of us in the United States recorded our own experiences implementing the new guidelines
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which are available at the same web address linked above
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so let's look at another case case 2 is a
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three -year -old male referred for genomic microarray testing for developmental delay a deletion in chromosome 2q was identified
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and the inheritance is unknown
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if you want to follow along you can use the CNV loss metric as this deletion is indicated above.
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Starting again in section 1, a search of the deleted region here shown with the red
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bar shows a number of protein coding genes reside in this region.
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So section 1a would apply.
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Again in section 2 you need to determine whether this deletion
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or any genes within it are known to be dosage sensitive or benign.
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By plugging this region into the ClinGen dosage sensitivity map website, you can see that after sorting by haploinsufficiency score,
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there are no known HI genes in this region.
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We can move down to section 2H as there's no haploinsufficient genes in the region.
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Here, users are prompted to evaluate whether any genes in the region are predicted to be haploinsufficient.
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In order to assign points here,
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at least one gene within the deleted region must have both a high PLI score and a low HI index.
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To evaluate, you can query the region in the Decipher database and sort by these scores.
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Please keep in mind that the PLI scores are calculated in the NOMAD database.
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For this deletion, there are only two genes with a high PLI score, but they do not also have a low HI index,
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and so no points can be assigned in Section 2H.
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In Section 3, users should evaluate the number of protein -coding genes in the region.
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Here, I used the DecipherSearch tool to do this count by limiting my review to only protein -coding genes.
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Of the 23 genes in this deletion, 20 are protein -coding.
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So according to Section 3, the gene count is not high enough to score this deletion towards pathogenicity.
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So zero points is assigned in Section 3.
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Please note that since I made these slides,
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the Decipher database has been updated to exclusively display in HG38.
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So you'll have to follow the tutorial I provided earlier in order to convert your genomic coordinates to use Decipher today.
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Next, in section 4, we will need to do a detailed evaluation of this deletion using published literature,
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databases, and internal data, and looking for information including whether the deletion is de novo or inherited in the literature,
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whether it's segregating with inherited with clinical phenotypes,
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if associated clinical phenotypes are specific or nonspecific,
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and also whether deletions of this region are common in the general population or commonly inherited from relatives who are unaffected.
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But before we move on, let's go back to our dosage map search.
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For this deletion, there's actually a region curation that's been completed.
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So let's take a look at the information by clicking on the ISCA ID on the right.
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From here, you can see that this curation is complete, that it was updated in February of last year, and that the HI score is 1.
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Under the haplow insufficiency tab for this region, you can see the information that has been curated to arrive at a one score for haploid sufficiency.
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This information includes in the evidence section a literature summary which may include up to three references.
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In the comments section an explanation for the dosage score.
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For some entries a description of the genomic region may also be provided.
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An additional relevant literature such as case control data may also be included.
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The description section is used to provide additional information about the CNV.
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Here you can learn that this deletion is caused by recombination involving low copy repeats
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or seg dupes flanking this region in chromosome 2Q11 .2 and
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that genes within this region may be used to distinguish it from others nearby
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but are not necessarily the critical genes within this region.
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Coming back to this region in UCSC,
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we can now load up the recurrent CNVs track and observe where the unique sequence flanked by segmental duplication sequence resides.
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note that the breakpoints called may not perfectly align with the annotated region
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which generally corresponds to the innermost unique coordinates of the LCR
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blocks be sure to inspect the actual data for CNV calling in these regions to ensure
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you are dealing with the typical recurrent CNV.
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So, are we done yet?
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Based on a haploinsufficiency score of 1,
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the potential clinical classification for this deletion per the dosage sensitivity rankings is uncertain.
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However, as noted in the guidelines, for some CNVs, particularly those with incomplete penetrance or variable expressivity,
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additional evaluation may be necessary, and caution is recommended before interpreting a CNV based on this information alone.
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So let's take a look at the literature.
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After confirming no new literature exists,
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we can summarize the two studies that have been reported with the phenotypic association for deletions of this region, which were summarized in the ClinGen review.
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Between these two studies, five unrelated cases were identified identified.
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The phenotyping common across reported patients included speech delay,
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ADHD, dysmorphic features, and other variable features, which are generally nonspecific.
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And the inheritance patterns across these cases varied when known.
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In most cases, the deletion was inherited.
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Only one de novo case was reported.
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If we were to use this information to score these deletions in Section 4 of the metric,
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only one case would be counted in Section 4C for de novo evidence associated with a nonspecific phenotype,
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which would be given a default score of 0 .1.
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For the inherited cases, parental phenotype information was limited.
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Only the deletion of Subject 1 was noted to have been inherited from a father who had trouble in school.
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In order to score cases with parental inheritance in Sections 4F through H, at least three segregations must be established within a family,
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so we cannot count the deletion of Subject 1 in the metric.
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In the other cases, inheritance was maternal with no phenotypic information for subject 3,
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presumed based on two affected siblings but without further information for subjects 4 and 5,
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or for the case from 2009, the inheritance was unknown.
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According to the metric, only cases associated with the highly specific phenotype can be counted if the inheritance is unknown.
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Therefore, these additional cases would not be scored in section 4e.
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So to summarize, the 2Q11 .2 deletion has been reported in five cases in association with relatively nonspecific and variable clinical phenotypes.
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One case so far has been found to be de novo, giving this evidence 0 .1 points.
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Moving on to section 4L through O,
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let's take a look at the case control and population evidence for this deletion. For recurrent CNVs,
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one of the most comprehensive studies published by Koh et al
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in 2014 compared the frequencies of these cnvs in large clinical
316
and control populations in this study the 2q11 .2 deletion was observed in six cases and zero controls
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which gives a nominally significant p -value but low likelihood ratio that has wide confidence interval bounds.
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In another study of recurrent CNV frequency in a schizophrenia population, this deletion was observed in six cases versus one control,
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which gives both a high p -value and an odds ratio with wide confidence interval bounds.
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According to the CNV interpretation guidelines,
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CNVs counted in this category will be observed at a significantly higher frequency in cases versus controls, with a p -value less than 0 .05,
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and with a strong effect size, an odds ratio or likelihood ratio greater than 5,
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with a relatively narrow associated 95 % confidence interval, whose lower bound must be greater than 1.
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The statistical values for this region do not appear to satisfy these criteria.
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Coming back to the metric, for a deletion with a nonspecific phenotype, a maximum 0 .3 points per study could be assigned.
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But given the nominal significance estimates, we want to utilize the range of scores to downgrade the value of each of these studies.
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Here, I gave each study 0 .1 points for a total of 0 .2.
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Finally, in section 5 of the metric, we could consider the inheritance pattern for the deletion in our case, but here it is unknown,
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so no points could be assigned.
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Here we should note, as is stated in the guidelines, that special considerations may occur, particularly for regions like recurrent C and Vs,
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which may show incomplete penetrance and variable expressivity.
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For example, in some cases, inheritance for a variant that is known to exhibit reduced penetrance may not be appropriate to score in Section 5.
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For this reason, along with other special considerations,
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the use of these metrics for classification of recurrent CNVs should be performed with caution,
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as a standardized classification system for these types of CNVs is still under development.
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However, coming back to the 2Q11 .2 deletion,
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with limited evidence overall, the classification of this variant was calculated as VUS.
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This evidence corresponds to the one score provided in the Region Curation article on the Dosed Sensitivity Map website.
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Our goal in the Recurrent CNV subgroup is to continue to
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update Recurrent CNV curations using a scoring system analogous to the clinical CNV interpretation metric.
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We encourage users of the dosage map to contact us with feedback regarding specific gene
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or region reviews using the report information link on the gene and region page, or submit general questions, suggestions for gene or region reviews,
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and new evidence we should incorporate into our curations.
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I'd like to close by thanking my colleagues in the ACMG ClinGen CMV Interpretation Guidelines Committee,
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as well as the many wonderful members of our dosage sensitivity curation team.
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Please feel free to ask me questions or submit them in the chat.
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Vocabulario y notas de pronunciación para esta lección
Esta lección de conversación se basa en el vídeo “Presentation - Copy Number Variant Interpretation/Dosage Sensitivity Curation”. Las palabras que más se repiten: gene, cnv, deletion, region, section. Este vídeo tiene 346 frases y 5089 palabras para practicar shadowing. La parte hablada dura 42:06. El hablante mantiene un ritmo constante de unas 121 palabras por minuto, cómodo para el shadowing. Solo el 72 % de las palabras está entre las 3.000 más comunes del inglés, por lo que el vocabulario es exigente.
Vocabulario clave de este vídeo
15 palabras del vídeo que vale la pena aprender, con su pronunciación y significado:
| Palabra | Pronunciación | Significado |
|---|---|---|
| gene sustantivo | /d͡ʒiːn/ | gen, gene |
| dosage sustantivo | /ˈdəʊsɪd͡ʒ/ | posología |
| classification sustantivo | /ˌklæsɪfɪˈkeɪʃən/ | clasificación |
| metric adjetivo | /ˈmɛt.ɹɪk/ | métrico |
| sensitivity sustantivo | /ˌsɛn.səˈtɪv.ə.ti/ | sensibilidad |
| variant sustantivo | /ˈvæɹi.ənt/ | variante |
| evaluate verbo | /ɪˈvaljʊeɪt/ | evaluar |
| interpretation sustantivo | /ɪnˌtɜːpɹəˈteɪʃən/ | interpretación |
| involve verbo | /ɪnˈvɑlv/ | involucrar |
| inheritance sustantivo | /ɪnˈhɛɹɪtəns/ | herencia, heredad |
| benign adjetivo | /bɪˈnaɪn/ | benigno |
| sequence sustantivo | /ˈsiː.kwəns/ | secuencia |
| assign verbo | /əˈsaɪn/ | asignar |
| correspond verbo | /ˌkoɹəˈspɑnd/ | corresponder, equivaler |
| observe verbo | /əbˈzɜːv/ | servar, observar |
Phrasal verbs que vas a escuchar
| Palabra | Significado |
|---|---|
| point out verbo | señalar, apuntar |
| go through verbo | atravesar |
Gramática en este vídeo
Las estructuras que más usa el hablante, con las palabras exactas del vídeo:
| Estructura | En el vídeo |
|---|---|
| Present perfect have/has + participio pasado — una acción pasada que sigue importando ahora | have been shown · has developed · you've learned |
| Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace | will be covered · have been shown · be classified |
| Oraciones de relativo who / which + oración — información extra sobre una persona o cosa | evaluated, which are · map, which is · regions which have |
Pronunciación a tener en cuenta
El hablante usa 17 contracciones y formas reducidas, como I'll, we're, I'd. Dilas en su forma corta, tal como las oyes.
- Los sonidos de “th”: threshold /ˈθɹɛʃ(h)oʊld/, pathogenic /pæθəˈd͡ʒɛnɪk/, pathogenicity /ˌpæθəd͡ʒəˈnɪsɪti/
- Los sonidos de “sh” y “zh”: classification /ˌklæsɪfɪˈkeɪʃən/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, evaluation /ɪˌvæljuˈeɪʃn̩/, ratio /ˈɹeɪ.ʃoʊ/, threshold /ˈθɹɛʃ(h)oʊld/
- Palabras largas — cuida el acento: classification /ˌklæsɪfɪˈkeɪʃən/, sensitivity /ˌsɛn.səˈtɪv.ə.ti/, interpretation /ɪnˌtɜːpɹəˈteɪʃən/, inheritance /ɪnˈhɛɹɪtəns/, significance /sɪɡˈnɪfɪkəns/
Sonidos difíciles para hispanohablantes:
- s + consonante al inicio — sin añadir una “e” delante: spectrum /ˈspɛktɹəm/, slide /ˈslaɪ̯d/
- /v/ — no es /b/: los dientes tocan el labio inferior: sensitivity /ˌsɛn.səˈtɪv.ə.ti/, variant /ˈvæɹi.ənt/, evaluate /ɪˈvaljʊeɪt/, involve /ɪnˈvɑlv/, observe /əbˈzɜːv/
- /z/ — sonora, no /s/: observe /əbˈzɜːv/, browser /ˈbɹaʊ.zəɹ/, mechanism /ˈmɛk.ə.nɪ.zəm/, exhibit /ɪɡˈzɪbɪt/, summarize /ˈsʌməˌɹaɪz/
Cómo practicar con este vídeo
- Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
- Haz shadowing frase por frase a velocidad normal, repitiendo cada una hasta que tu ritmo coincida con el del hablante.
- Grábate y compara con el original, prestando atención a palabras como gene, dosage, classification.
¿Qué es la Técnica de Shadowing?
Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.