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Human genetics and genetic counselling

Genetics / Bioinformatics (B.Sc) · Population and human genetics · free study notes for exams, placements and interviews

In short

Human genetics studies how traits and diseases are transmitted in families and how that knowledge is used in diagnosis, risk prediction and prevention. Genetic counselling is the communication process that helps a family understand a diagnosis, its mode of inheritance, the numerical recurrence risk, the testing and reproductive options, and the support available — delivered non-directively. It matters in India because carrier frequencies for β-thalassaemia (about 3–4% nationally) and sickle cell disease (high in tribal belts) are large, consanguinity is common in parts of the south and in some communities, and congenital anomalies affect roughly 6–7% of newborns. It is examined in B.Sc/M.Sc human genetics papers, CSIR-UGC NET and GATE BT/XL (genetics and biotech sections), DBT-BET and ICMR/JRF screening. It is practised in hospital genetics departments, IVF and prenatal diagnostic labs, NIDAN Kendras under the DBT UMMID initiative, and in clinical-genomics roles at diagnostic companies.

Explained

Pedigree analysis and modes of Mendelian inheritance

Complications of simple Mendelian rules

Chromosomal disorders and cytogenetic nomenclature

Laboratory methods used in counselling

Genetic counselling: definition, process and types

Screening, prenatal diagnosis and newborn screening

Indian law, policy and ethics

Key points

Formulas and examples

Recurrence risk, AR, both parents carriers = 1/4 per pregnancy (independent of previous children)
Carrier probability of a phenotypically normal sib (AR) = 2/3
Carrier frequency from Hardy-Weinberg: q = √(disease incidence); carrier frequency = 2pq, p = 1 − q
Coefficient of relationship r = (1/2)ⁿ summed over all paths, n = number of meioses between the two relatives; inbreeding coefficient of their child F = r/2
Bayes: Posterior = Joint / Σ Joints, where Joint = Prior × Conditional (the conditional is the probability of the observed data under that hypothesis)
Risk with incomplete penetrance = transmission probability × penetrance
Empirical multifactorial sib recurrence ≈ √(population incidence) (Edwards' approximation)
Screening: PPV = TP/(TP + FP); detection rate (sensitivity) = TP/(TP + FN); all probabilities are dimensionless fractions

Example 1 — AR carrier couple, β-thalassaemia. Both parents are HbA2-raised carriers; they have one unaffected daughter and want the risk for the next pregnancy and their daughter's status.

Example 2 — Bayesian carrier risk, Duchenne muscular dystrophy. A woman's mother is a proven *DMD* carrier; the woman herself has two unaffected sons and no genetic test result.

HypothesisPriorConditional (2 normal sons)Joint
Carrier1/2(1/2)² = 1/41/8 = 0.125
Not carrier1/211/2 = 0.500

Example 3 — Consanguinity. A man is a known carrier of an AR disorder and marries his first cousin; no other family history.

Example 4 — Hardy-Weinberg carrier estimate. Sickle cell disease affects 1 in 2,500 newborns in a community.

Example 5 — Why a positive screen is not a diagnosis. NIPT with 99% detection and 99.9% false-positive-free specificity, applied to 100,000 pregnancies where trisomy 21 prevalence is 1 in 500 (200 affected).

TestWhenWhat it detectsNatureMain limitation
Combined first-trimester11–13⁺⁶ wkTrisomy 21/18 riskScreening~85–90% detection, 5% false positive
Quadruple marker15–20 wkTrisomy 21/18, open NTDScreeningLower detection than NIPT
NIPT (cfDNA)≥10 wkTrisomy 21/18/13, SCAScreeningNeeds confirmation; low fetal fraction fails
CVS11–14 wkKaryotype, CMA, DNADiagnostic~0.2% loss; placental mosaicism
Amniocentesis15–18 wkKaryotype, CMA, DNA, AFPDiagnosticLater result; small loss risk
PGT-MPre-implantationKnown familial variantDiagnosticNeeds IVF; no-result/mosaic embryos

Where it is used

Interview questions

Common mistakes

Related topics

Population and quantitative genetics · Molecular genetics and gene expression · Cytogenetics and chromosome banding · Medical biotechnology and gene therapy · Bioinformatics: variant calling and annotation · Biostatistics and epidemiology of screening tests

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